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PMC10003233

Jaeyoung Moon,Ichiwa Kitty,Kusuma Renata,Sisi Qin,Fei Zhao,Wootae Kim

DNA Damage and Its Role in Cancer Therapeutics

01-03-2023

DNA damage,cancer therapeutics,mutations

DNA damage is a double-edged sword in cancer cells. On the one hand, DNA damage exacerbates gene mutation frequency and cancer risk. Mutations in key DNA repair genes, such as breast cancer 1 (BRCA1) and/or breast cancer 2 (BRCA2), induce genomic instability and promote tumorigenesis. On the other hand, the induction of DNA damage using chemical reagents or radiation kills cancer cells effectively. Cancer-burdening mutations in key DNA repair-related genes imply relatively high sensitivity to chemotherapy or radiotherapy because of reduced DNA repair efficiency. Therefore, designing specific inhibitors targeting key enzymes in the DNA repair pathway is an effective way to induce synthetic lethality with chemotherapy or radiotherapy in cancer therapeutics. This study reviews the general pathways involved in DNA repair in cancer cells and the potential proteins that could be targeted for cancer therapeutics.

DNA Damage and Its Role in Cancer Therapeutics DNA damage is a double-edged sword in cancer cells. On the one hand, DNA damage exacerbates gene mutation frequency and cancer risk. Mutations in key DNA repair genes, such as breast cancer 1 (BRCA1) and/or breast cancer 2 (BRCA2), induce genomic instability and promote tumorigenesis. On the other hand, the induction of DNA damage using chemical reagents or radiation kills cancer cells effectively. Cancer-burdening mutations in key DNA repair-related genes imply relatively high sensitivity to chemotherapy or radiotherapy because of reduced DNA repair efficiency. Therefore, designing specific inhibitors targeting key enzymes in the DNA repair pathway is an effective way to induce synthetic lethality with chemotherapy or radiotherapy in cancer therapeutics. This study reviews the general pathways involved in DNA repair in cancer cells and the potential proteins that could be targeted for cancer therapeutics. DNA, as genetic material, plays a major role in living organisms and needs to be maintained to transmit hereditary information. However, DNA is prone to damage that occurs either endogenously or exogenously. There are several types of DNA damage, including single-strand DNA breaks (SSBs), double-strand DNA breaks (DSBs), DNA-protein crosslink (DPC), bulky adducts, and base mismatch [1,2]. DNA damage changes the sequence of DNA, leading to the disruption of proteins and their functions [3]. Accumulation of DNA damage can have several harmful effects on human health, resulting in senescence, aging, apoptosis, and genomic instability [4,5]. The accumulation of this phenomenon leads to severe cancer progression in normal cells [6]. However, the DNA damage that occurs in cancer cells has remarkable connections with cancer patients. If the cancer cell cannot restore and activate the DNA damage response (DDR), the affected cancer cell dies [7,8]. The activation of DDR promotes cell repair, by which numerous proteins that play a role in this pathway assemble in the same region where damage occurs. These proteins perform a repair mechanism based on the type of damage (Figure 1) [2,9]. SSBs can be directly or indirectly repaired by base excision repair (BER) [9,10]. DSBs can be repaired using two types of mechanisms: error-prone or non-homologous end-joining (NHEJ), and less error-prone or homologous recombination (HR) [9]. Other damage types, such as DNA adducts, crosslinks, and oxidized bases, can be repaired using nucleotide excision repair (NER). When a DNA mutation such as an insertion, deletion, or base mismatch occurs, mismatch repair (MMR) is activated [2,9]. These mechanisms can be used by cancer cells to repair the damage caused by drugs or other therapies [2]. Cancer is a severe illness with high rates of incidence and mortality, thus necessitating research on the development of cancer treatments. This has led to the development of four main cancer treatments: surgery, chemotherapy, radiotherapy, and immunotherapy. Since their discovery in the 19th and 20th centuries, surgery and radiotherapy have been used to treat cancer, but their success rates are low. Since the discovery of chemotherapy, an increase in the number of cancer survivors has been recorded [11,12]. However, this form of treatment may have numerous negative effects on patients. In addition to damaging cancer cells, it can harm other cells, thereby causing toxicity and loss of function in healthy cells and tissues. Therefore, more research on precise and targeted cancer therapies that are safe for normal cells and have minimal side effects is required [11,12]. These targeted cancer therapies need to have higher efficacy rates than previous treatments by targeting the tumorigenic pathway to inhibit cancer growth and eliminate the cancer [13]. Certain tumorigenic pathways can be targeted for this precision therapy, including the DNA damage pathway. Understanding the mechanism of the cancer damage pathway can aid in the development of treatments specific to cancer cells [14]. HR is a mechanism for recovering DNA double helices without the loss of genetic information. The HR is recovered using the genetic information of the cloned DNA or homologous chromosomes, and occurs during DNA replication. Therefore, it occurs mostly in the S and G2 phases of the cell cycle [15]. Owing to challenges associated with precise chromosome segregation during cell division, DSBs are the most genotoxic type of DNA lesion. Although this is a relatively accurate and effective repair process, sister chromatid DNA must be present for HR repair to take place [16]. If DSBs occur, 53BP1 is activated, and the 53BP1-RIF1-shieldin-CST/ASTE1 complex stabilizes chromatin at the DSB site [17,18,19]. The MRE11-RAD50-NBN (MRN) complex detects DSBs first, recruiting the BLM helicase and EXO1 onto the breaks to initiate 5′–3′ double-stranded DNA resection. The overhang of 3′ single-stranded DNA (ssDNA) was covered by RPA, thereby preventing additional resection. Through the RPA-ATRIP interaction, ATR localizes to RPA in damage sites and activates the ATR-Chk1 DNA damage checkpoint. This causes cell cycle arrest and preserves the cell strand [20]. RAD51 recruitment is mediated by BRCA1, BRCA2, BARD1, PALB2, and RAD51, and override RPA from the 3′ overhangs to form presynaptic filaments. Subsequently, strand invasion occurs and causes the development of a D-loop between the homologous chromosome and the invading 3′ overhang strand [21]. Then, DNA synthesis and ligation occur on each of the resected ends using the template. The BTRR dissolvasome disintegrates the Holliday junctions connecting sister chromatids and completes HR repair [20]. HR deficiencies are more susceptible to destruction by DNA-damaging agents or by substances that block other repair pathways or checkpoint systems [22,23]. HR needs several mediator proteins, such as BRCA1 and BRCA2. Multiple cancers, including breast, ovarian, and pancreatic cancer, involve altered HR genes [24]. Therefore, HR proteins are prospective targets for cancer therapeutics due to their roles in tumorigenesis and their involvement in therapeutic resistance [25]. DSBs can be restored through a mechanism called NHEJ. NHEJ pathways in the DDR pathway are less accurate, but still effective, and can introduce DNA rearrangements. In addition, they did not require duplicated DNA [26]. To maintain genomic stability, DSBs must be repaired quickly; therefore, cells use the NHEJ pathway to repair DSBs. However, NHEJ contains errors, because several bases can be inserted or deleted. A homologous template is not required because the break ends are directly ligated. Although NHEJ is involved in the cell cycle, the G1 phase is more significant. The first step of NHEJ is the recognition of DSB by Ku, a heterodimer comprising Ku70 and Ku80 proteins. Ku interacts with the DNA ligase IV complex and XRCC4-like factor (XLF) and may serve as a docking site for another NHEJ protein. XLF is involved in NHEJ ligation steps, interacting with DNA ligase IV and XRCC [27]. When Ku is recruited to a DSB, DNA-PKcs are attached to create the DNA-PK complex, which undergoes autophosphorylation, and phosphorylates NHEJ factors to draw them to the DSB for repair. In the NHEJ environment, XRCC4’s functions also make it easier to recruit components for the DSB. When LIG4 and XRCC4 are bound together, LIG4 ligase activity increases, sealing the blunt or homologous overhang ends of the DSB. XRCC4-LIG4 interacts with XLF and PAXX [28]. The Artemis DNA PKcs complex, which has various endonucleolytic properties, functions as a nuclease [29]. The polymerization that takes place throughout NHEJ is accomplished by the Pol X family of polymerases, and Pol l is preferred because it can function in a template-independent manner. The DNA ligase IV-XRCC4-XLF complex is responsible for the final closure of the DNA break [30]. NHEJ stabilizes the genome in normal cells, but promotes genomic instability and carcinogenesis in cancer cells. Elevated Ku expression increases tumor proliferation and metastasis and results in shorter survival duration [31]. For instance, in non-melanoma skin cancer, up-regulation of Ku70 and Ku80 protein levels is correlated with the tumor proliferation rate. Meanwhile, mutations in genes that participate in NHEJ lead to hereditary breast and ovarian cancers. Cancer progression and low survival rates have been linked to increased expression of DNA-PKcs. DNA-PKcs expression at the mRNA level is much higher in NSCLC tumor tissues than in the surrounding normal tissues, and the increased expression is linked to a higher mortality risk [32]. Therapies aimed at the NHEJ pathway may be used to target tumor cells that depend on this pathway [33]. MMEJ is an alternative non-homologous end joining (Alt-NHEJ) mechanism that is used to repair DSBs. When the broken ends are aligned before joining MMEJ, microhomologous sequences are used, resulting in deletions on either side of the initial break. Chromosome anomalies such as translocations, deletions, inversions, and other intricate rearrangements are typically linked to MMEJ. The utilization of 5–25 base pair (bp) microhomologous sequences during the alignment of broken ends before joining, resulting in deletions flanking the initial break, is the primary characteristic that sets MMEJ apart. Chromosome abnormalities such as deletions, translocations, inversions, and other intricate rearrangements are frequently linked to MMEJ [34,35,36,37,38,39]. In MMEJ, end resection by the MRE nuclease, which leaves single-stranded overhangs, initiates the repair of the DSB [40]. Microhomologies, which are brief areas of complementarity (often 5–25 base pairs) between the two strands, are where these single-stranded overhangs anneal. Polymerase theta-mediated end-joining (TMEJ), a type of MMEJ, can repair breaks [41,42]. The DNA polymerase theta helicase domain has single-strand annealing activity that is ATP-dependent and may encourage the annealing of microhomologies [43]. Overhanging bases are eliminated by nucleases such as Fen1 after annealing, and gaps are filled by DNA polymerase theta [44]. Polymerase theta’s capacity to fill gaps contributes to the stabilization of the annealing of ends with little complementarity. In addition to microhomology footprints, the mutational signature of polymerase theta includes templated inserts, which are believed to be the result of a template-dependent extension that failed and was then re-annealed at secondary homologous sequences [42]. MMEJ is an inherently mutagenic mechanism for DSB repair. In primary human cancer cells, oncogenic chromosomal translocation breakpoints carry microhomology signatures, suggesting that MMEJ may be the mechanism causing this translocation [45,46]. DNA polymerase θ (Polθ) is a protein that promotes MMEJ. Polθ overexpression in breast, lung, bladder, colorectal, gastric, glioma, pancreatic, prostate, melanoma, and uterine malignancies is associated with poor prognosis. As NHEJ-deficient cells also rely on MMEJ, the application of a Polθ inhibitor is possible for the treatment of cancer. Collectively, these findings offer a compelling reason to focus on MMEJ for malignancy therapy, especially for tumors resistant to PARP inhibitors [22,47]. BER is the most adaptable excision repair mechanism and oversees the fixation of most endogenous lesions, including oxidized bases, AP sites, and DNA SSBs. The fundamental BER mechanism in E. coli was discovered for the first time [48]. The BER pathway is responsible for repairing DNA SSBs, which are most frequently caused by modified bases, abasic sites, and their processing of more than 20,000 events per cell per day [49,50]. BER is a type of repair that simply removes the base, and is distinguished into two techniques: short and lengthy patch repair. Long patch repair fixes 2–10 nucleotides, whereas short patch repair fixes only one. The primary path is typically a brief patch fix, and simply performs the following actions: excision, incision, end processing, repair synthesis, and base lesion. DNA glycosylase, AP endonuclease, DNA polymerase, and DNA ligase are key enzymes. First, aberrant bases, such as uracil bases, are identified and cleaved by DNA glycosylation enzymes [51]; an apyrimidine (AP) is present. Cleavage of the damaged N-glycosidic bond of the base results in the creation of an AP site. AP spots can be recognized by AP endonucleases such as APE1 [52]. Therefore, the phosphodiester bond was broken. APE cleaves to the AP site to generate 3′-OH and 5′-deoxyribose phosphate (dRP) termini. The intrinsic dRP lyase activity of DNA polymerase β (Pol β) cleaves the dRP residue to produce 5′-phosphates. DNA ligase I is more crucial than DNA ligase III for BER [53,54]. Therefore, the 5′ to 3′ exonuclease activity of DNA synthase I can repair damaged bases and restore them to normal bases. DNA ligase ligates the nick; however, this repair may result in structural distortions or ground-level issues. The BER pathway repairs residues damaged by ROS, IR, and alkylating agents. ROS-induced DNA damage is thought to play a role in the development of cancer, aging, and neurodegeneration. DNA oxidative stress can result in mutations that turn tumor suppressor genes on or off [55]. The likelihood of genetic changes resulting in neoplastic events is influenced by numerous DNA repair mechanisms as well as other cellular stress response pathways, including cell cycle arrest and apoptosis. Numerous types of DNA damage have been firmly linked to tumor development. Therefore, BER could be of critical importance for cancer prevention [56]. Typically, the intermediates of the BER pathway are more hazardous than the original base lesion. As a result, altering the amounts of BER proteins may be a viable gene therapy strategy for eliminating cancer cells. Other potential pharmacological targets for cancer therapy are Pol β, APE1, and DNA ligases [57,58,59]. Analysis of BER gene mutations in cancers might be useful to comprehend the genesis of malignancies in a specific organ and, more importantly, the potential function of BER in metastasis. Additionally, BER enzymes are crucial targets for cancer drugs, as they prevent cell sensitivity to several chemical substances and ionizing radiation (IR). The NER pathway, which predominantly addresses UV-induced damage, also plays a significant role in addressing DNA damage caused by platinum salts, and deals with mutated nucleotides that alter the structural integrity of the double helix [60]. UV causes DNA damage. This effect leads to the formation of thymine dimers. Thymine dimers cause severe distortion of the DNA strand. NER is a mechanism for removing this type of damage. UvrAB moves along the DNA and identifies distortions. When a damaged area is encountered, UvrA is released, and UvrC is combined to form UvrBC. UvrBC breaks the positions of 4′–5′ nucleotides to 3′ and 8′ nucleotides to 5′ at the thymine dimer site to create a gap. Helicase activity in UvrD eliminates damage and releases UvrB and UvrC. DNA polymerase I binds to repair the gap, and DNA ligase connects the nick. The thymine dimer is then repaired. NER may remove a variety of helix-distorting DNA lesions that are mostly caused by environmental mutagens such as ultraviolet light (UV) irradiation and large chemical compounds [61]. If UV irradiation is not controlled, in addition to causing regular cell death, it can disrupt DNA integrity and cell and tissue homeostasis, resulting in oncogene and tumor-suppressor gene mutations. If left unchecked, these mutations can result in aberrant cell proliferation and increase the probability of cancer development [62,63]. According to extensive tumor mutation research, NER may underlie a variety of mutational signatures [64,65]. Genetic variation or mutations in nucleotide excision repair genes can influence cancer risk. Therefore, cancer susceptibility may result from hereditary polymorphism changes in NER genes [66]. A technique called MMR is used to identify and correct base errors that may occur during the replication and recombination of DNA, as well as various types of DNA damage [67,68]. The MMR pathway addresses replication mistakes, such as nucleotide insertions and deletions, as well as mismatched base pairing [69]. First, MutS determines the base pair error. The MutS/MutL complex binds to MutH, which is already bound to a semi-methylated sequence. MutH is then activated to cleave the unmethylated strands. The exonuclease removes the nascent strand from the cut point to the error base-pair portion, and DNA polymerase III fills the resulting gap. The DNA ligase then connects the nick, and the error base pair is repaired normally. The fact that reduction in the MMR protein expression causes a predisposition to colorectal, gastric, endometrial, and ovarian malignancies emphasizes the crucial function of MMR in carcinogenesis. Furthermore, 15% of all primary tumors contain MMR deficiencies [70]. Base substitution and frameshift mutations are greatly elevated in the mutator phenotype, which is caused by microsatellite instability (MSI) and mismatch repair deficiency. Microsatellites, which are found throughout the genome, are brief tandem repeating DNA sequences of 1–4 base nucleotides. These repetitions have a high error rate during replication, and if tumor suppressor genes contain them, a poor repair could have negative consequences [71]. DPCs are formed when proteins covalently bond to DNA strands. Crosslinks are particularly dangerous because they can successfully stop DNA replication and gene transcription. IR, UV rays, and other transition metal ions, such as chromium and nickel, can generate DPCs [72]. Furthermore, DPCs are frequently created by interactions with aldehydes and binding of different enzymatic intermediates to DNA, and can cause severe mutations and cell death if not repaired promptly [73]. DPC repair involves HR and nucleotide excision. Ruijs-Aalfs syndrome and Fanconi anemia are related to deficiencies in DPCs repair pathways. The amines of DNA bases can react with acetaldehyde, an important metabolite of ethanol and an intermediate in glucose metabolism, to produce DPCs [74,75,76]. The repair or avoidance of DNA adducts created by acetaldehyde has been found to depend on the NER, HR, and Fanconi anemia (FA) pathways [74]. Multiple chromosomal instability disorders, an increase in bone marrow loss, and a propensity for malignancy are the hallmarks of FA [77,78,79]. Several genotoxic effects, including chromatid breaks and chromosomal abnormalities and mutations, result from DPCs that are not repaired [80]. DPCs need various FA proteins to complete the repair [81]. DNA lesions occur in several forms, including insertion or deletion mismatches, SSBs, and DSBs [82]. DNA lesions that cannot immediately be repaired could generate miscellaneous mutations. These mutations can cause genomic instability, which is the primary driver of cancer development and progression [83]. Considering that every cell is easily exposed to various carcinogens, both endogenously and exogenously, cells have developed numerous DNA repair pathways, referred to as DDR, that allow for their survival [84,85]. Contingent upon persistent DNA damage, normal cells undergo either apoptosis or senescence as an outcome of DDR (Figure 2). The lack of proper DDR after exposure to stressors may result in elevated occurrence of genomic instability and mutations, further injury to the DNA repair ability, and escalation of cancer development [86]. Mutated DNA repair genes are frequently detected in human cancers (Table 1), indicating that the dysregulation of DNA repair factors promotes cancer progression [87]. Even though mutations in the DNA repair system could lead to the development of certain cancers, these mutations could be a weakness for cancer cells as well. Multiple cancer cells with DDR alterations have been shown to be more sensitive to genotoxic stress generated from immunotherapy, radiotherapy, and/or chemotherapy [88]. For instance, mutations in BRCA1 and/or BRCA2 increase the risk of breast and other cancers, such as ovarian and prostate cancer [89,90]. Patients with cancer that have alterations in the BRCA1 and/or BRCA2 genes are highly sensitive to platinum chemotherapy and PARP inhibitors [91,92]. BRCA2’s mutation partner and localizer (PALB2) is associated with pancreatic and breast cancer malignancies. Cancer patients with mutations in these genes tend to receive more benefits from chemotherapeutic approaches, including platinum-based chemotherapy (NCT 03140670), mitomycin C, and cisplatin [93,94]. Cancer cells with the BRCAness phenotype do not have BRCA germline mutations, but share a similar phenotype with BRCA germline mutations and, as a consequence, this type of cancer exhibits defective HR [95]. For example, cancers with ATM, ATR, and TP53 mutation; METTL16 overexpression; PTEN deletion; and RAD51C hypermethylation could lead to the forfeit of the HR repairing system [96,97]. Moreover, tumors with the BRCAness phenotype are sensitive to DNA-damaging agents such as cisplatin, mitomycin C, and PARP inhibitors [98]. KU70 and KU80 mutations are associated with higher genomic instability and eventually facilitate the development of cancer. KU70 and KU80 polymorphisms are found in several types of cancer, such as breast, prostate, oral, bladder, colon, and lung cancers [99,100,101]. Cancer cells with mutations in either KU70 or KU80 are found to be more sensitive to IR [102]. Mutations on the tumor suppressor gene ATM are associated with a broad range of human cancers, such as lung, colorectal, hematopoietic, and breast cancers. Patients with an ATM loss of function are hypersensitive to IR [103]. ATR mutations have been detected in endometrial cancer, and cancer cells with defective ATR are vulnerable to several DNA-damaging chemotherapy agents and IR [103,104]. Meanwhile, DNA mismatch repair deficiency (MMRd) is also associated with several types of cancer, such as hereditary nonpolyposis colorectal cancer (HNPCC) and colorectal cancer (CRC) [105]. Any mutation on MLH1, MSH2, MSH6, or PMS2 that could generate an MMRd tumor is sensitive to immunotherapy with checkpoint inhibitors [106]. Furthermore, DNA polymerase epsilon (Pol ε) and MutY DNA glycosylase (MUTYH) are involved in a BER repair system [107,108]. The mutated POLE gene, which encodes Pol ε, is known to initiate a hypermutator phenotype in cancers such as endometrial cancer [109,110]. Mutations in this gene are sensitive to immune checkpoint inhibitors (ICIs) [111]. Meanwhile, mutations in MUTYH could damage its glycosylase activity and diminish its capacity to eradicate mispaired bases, which increases the risk of cancers such as pancreatic ductal adenocarcinoma (PDAC) and CRC [108,112,113]. Tumors with MUTYH mutations may efficiently respond to ICI treatment [114]. Furthermore, the ERCC2 mutation could lead to the loss of cellular NER capacity and bladder cancer development [115]. Patients with bladder cancer who have somatic ERCC2 mutations have a higher sensitivity to cisplatin-based neoadjuvant chemotherapy [116]. For several years, radiotherapy and chemotherapy have been used to eliminate or at least reduce the number of cancer cells; however, these methods have several drawbacks. Many tumor types remain insensitive to both methods, which causes the success rate to differ depending on tumor type and grade [120]. Naturally, cells have several DDR pathways that can moderately compensate for each other [121]. Hypothetically, cancer cells already exhibit DDR, which contributes to genomic instability. The deficiencies of a single DDR could be resolved by the compensatory pathway, making cancer cells overdependent on that pathway [122]. The concept of synthetic lethality refers to a situation where two or more genes are mutated, and cell death occurs only when both genes are mutated simultaneously. For example, there are two crucial DNA repair pathways to repair DSB HR and NHEJ. DSBs can be lethal for the cell when both DNA repair systems are inhibited and cell death is then triggered [123]. Thus, synthetic lethality induction could be exploited as an alternative to overcome the limitations of chemo- or radiotherapy by targeting the compensatory pathways, which would prevent cells from repairing and elevate cancer cell vulnerability to radio- and/or chemotherapy, leading to the apoptosis of the cancer cells [23,124,125]. Cancer cells have several strategies that allow them to develop some ability to withstand cancer treatment. As previously mentioned, the induction of synthetic lethality in cancer cells could improve the effectiveness of cancer treatments. In line with the synthetic lethality concept, DDR inhibitors have been developed to target specific genes through specific mechanisms that block compensatory DNA repair pathways and subsequently induce the death of cancerous cells (Table 2) [124]. DNA-PKcs is a nuclear serine/threonine kinase and a critical protein that facilitates NHEJ [126]. Autophosphorylation of DNA-PKcs, which appears to be significant in NHEJ, causes a conformational shift that allows for end-processing enzymes to reach the ends of the DSBs [127]. DNA-PKcs work in conjunction with ATR and ATM to activate the phosphorylation of proteins involved in DNA damage checkpoints. Small compounds that target the AP-binding site of the kinase domain are the most effective methods of inhibiting DNA-PK to date [128]. The inhibition of DNA-PKcs would impede the kinase ability of DNA-PKcs and reduce the phosphorylation of cGAS. In addition, the use of DNA-PKcs inhibitors can sensitize cells to damaging agents [9,129]. Wortmannin has been used to inhibit DNA-PKcs. The clinical use of this substance is restricted by its lack of specificity, low solubility in aqueous solutions, and in vivo toxicity [130]. The plant flavonoid quercetin has a morpholine derivative, LY294002, which is also a widely used non-specific DNA-PK inhibitor. SCR7 is a small molecule that inhibits NHEJ [131]. NHEJ is eliminated because Ligase IV’s DNA-binding domain (DBD) is selectively bound by SCR7, preventing Ligase IV from attaching to the damaged chromatin. NHEJ is frequently overexpressed in various malignancies, which aids in resistance to several chemotherapeutic and radiation treatment methods. The other DNA-PK inhibitor, M3814, can be used to treat some types of cancer, alone or combined with other therapies, such as radiotherapy. For instance, M3814 can reduce tumor growth in combination with radiotherapy and the drug avelumab [129]. A class of proteins called poly ADP-ribose polymerase (PARP) is involved in several biological processes such as DNA repair, genomic stability, and cell death [132]. Furthermore, BER pathways and SSB repair depend on PARP [133]. So far, many PARP families have been identified, and PARP-1 and PARP-2 proteins are essential for cell survival. PARP-1 and PARP-2 use NAD+ as a substrate to perform PARylation and release nicotinamide. These modifications regulate the conformation, stability, and activity of target proteins. Normal cells are repaired when damaged through HR, but cancer is fatal when PARP-1 is suppressed because the important proteins for HR, BRCA1 and BRCA2, are broken. PARP inhibitors engage in DNA repair and inhibit the ribosomes needed when cancer cells proliferate. DDX21 is required to produce ribosomes, while PARP-1 is necessary for DDX21 function. Therefore, PARP inhibitors can suppress cancer progression. Therefore, numerous treatments for breast, ovarian, prostate, and colon cancer are either undergoing clinical studies or are already being utilized in certain cases. Olaparib, lucaparib, niraparib, talazoparib, and celiparib are currently being used for cancer treatment [22]. The PARP inhibitor, in combination with immunotherapy, can be used to target the immune system to treat some types of cancer, such as ovarian, lung, gastrointestinal, and prostate cancers. For example, in ovarian cancer, the use of the PARP inhibitor can decrease the overall response rate (ORR) in patients (ORR range: 45–63%; range of the disease control rate (DCR) from the control sample: 73–81%) [129]. ATM plays a critical role in the HR repair system of DSB. ATM also controls cell cycle progression, transcriptional regulation, chromatin remodeling, and apoptosis. Various cofactors of ATM have been identified, including the MRN complex, TIP60, ING3, ATMIN, and WIP1. Inhibiting ATM factors sensitizes cells to IR and induces DSB. Numerous ATM inhibitors are currently being researched for cancer treatment. KU-55933 (2-morphin-4-yl-6-thianthren-1 yl-pyran-4-one) is an ATM inhibitor. Cancer cells exposed to KU-55933 were sensitized to the cytotoxic effects of IR and chemotherapeutic agents that induced DNA DSB, such as camptothecin, doxorubicin, and etoposide. Therefore, inhibition of ATM proteins is an alternative approach to suppressing tumor growth; in addition, compared to other DDR-targeted agents such as PARP inhibitors, the study of ATM inhibitors is still in the early stages [124]. Therefore, inhibition of ATM proteins is an alternative approach to suppressing tumor growth [124,134]. KU-59403, an upgraded version of KU-55933, can also be used for cancer treatment. This inhibitor has higher potential, solubility, and bioavailability than KU-55933. Though KU-59403 alone has no effect on tumor growth, it increases the anti-tumor effects of other inhibitors, such as topoisomerase inhibitors, when combined with them [103]. ATR can sense stalled replication forks and induce various responses to DNA replication stress, which is important for maintaining the genomic integrity of cells. ATR also plays a role in the HR repair system in the presence of DSB along with interstand and cross-link repair systems. ATR is important for cell survival, particularly in the context of ATM mutations, making ATR a prospective target for cancer treatment [124,135,136]. Inhibiting ATR activity elevates the sensitivity of cancer cells to genotoxic agents and/or induces apoptosis. In addition, partial inhibition of ATR, resulting in cell stress, can cause aging in mice models [103]. NU6027, an ATR inhibitor, can increase the sensitivity of certain types of cancer, such as breast cancer, to irradiation and other cancer therapies [103]. However, the development of cancer therapy targeting the ATR signaling cascade was initially focused on CHK1 inhibitors rather than the ATR kinase itself. This may be due to the difficulty of obtaining the pure active form of the kinase protein BAY 1895344, which is a highly compelling and selective oral ATR inhibitor [135,136]. CHK1 plays an important role in DNA damage response and DNA damage repair. The phosphorylation of CHK1 by ATR mediates the repair process, and CHK1 delays the process of cell cycle progression, allowing cells to be repaired. Therefore, CHK1 acts as a cell-cycle checkpoint which can improve the survival rates of cells and increase the resistance of cancer cells to therapy [124,137]. Therefore, the regulation of CHK1 is used as an anticancer target in cancer therapy. Inhibition of CHK1 can result in cancer cell death by preventing the restart of stalled replication forks. Previous studies have identified numerous CHK1 inhibitors. The inhibition of CHK1 could increase the susceptibility of cancer cells to drugs, thus inducing replication stress in cancer cells. Some clinical studies have shown that CHK1 inhibitors can act as single agents to inhibit cancer cells and can work with other drugs or therapies to inhibit tumor growth [124,137,138,139,140]. There are two generations of CHK1 inhibitors. When combined with a cytotoxic agent, cancer cells showed sensitivity to the first generation of CHK1 inhibitors, but studies on this kind of inhibitor were limited due to its high toxicity. Second-generation CHK1 inhibitors have shown improvement compared to the first generation. LY2880070 and SRA737 are some of the CHK1 inhibitors that are currently under study. These drugs are being used in combination with other damaging agents, therapies, and antimetabolites [9]. Targeting the DNA repair pathway is an efficient method for cancer therapy. However, all DDR-related inhibitors under pre-clinical or clinical trials target enzymes, such as kinases (ATM, ATR, and DNA-PK) or PARP. Most regulators involved in the DDR pathway are scaffold proteins that are important for signal transduction, but without any enzyme activity, which complicates the design of small-molecule inhibitors for targeting these proteins. Therefore, the development of alternative strategies to target these untargetable scaffold proteins will broaden our options for cancer therapy. PROteolysis-TArgeting Chimeras (PROTACs) are a powerful class of compounds that selectively degrade proteins of interest through the cellular ubiquitination system. Recently, PROTACS targeting C-MYC, BET, androgen receptors, and BRD7 have effectively killed cancer cells [141,142]. Therefore, targeting scaffold proteins in the DDR pathway with PROTACs may also be a feasible method for cancer therapy. In addition to PROTACs, CRISPR/CAS9-mediated gene editing has been tested for cancer therapy in preclinical and clinical trials [143]. Inactivation of key scaffold proteins in the DDR pathway with CRISPR/CAS9 may enhance the efficiency of cancer chemotherapy or radiotherapy. Generally, these new technologies will afford us additional cancer therapy options, but further evaluation is required before their clinical application.

PMC10003234

Marta Witkowska,Ewelina Golusińska-Kardach,Wojciech Golusiński,Ewa Florek

Polydopamine-Based Material and Their Potential in Head and Neck Cancer Therapy—Current State of Knowledge

03-03-2023

polydopamine,biomaterials,head and neck,cancer therapy

Head and neck cancers (HNC) are among the most common cancers in the world. In terms of frequency of occurrence in the world, HNC ranks sixth. However, the problem of modern oncology is the low specificity of the therapies used, which is why most of the currently used chemotherapeutic agents have a systemic effect. The use of nanomaterials could overcome the limitations of traditional therapies. Researchers are increasingly using polydopamine (PDA) in nanotherapeutic systems for HNC due to its unique properties. PDA has found applications in chemotherapy, photothermal therapy, targeted therapy, and combination therapies that facilitate better carrier control for the effective reduction of cancer cells than individual therapies. The purpose of this review was to present the current knowledge on the potential use of polydopamine in head and neck cancer research.

Polydopamine-Based Material and Their Potential in Head and Neck Cancer Therapy—Current State of Knowledge Head and neck cancers (HNC) are among the most common cancers in the world. In terms of frequency of occurrence in the world, HNC ranks sixth. However, the problem of modern oncology is the low specificity of the therapies used, which is why most of the currently used chemotherapeutic agents have a systemic effect. The use of nanomaterials could overcome the limitations of traditional therapies. Researchers are increasingly using polydopamine (PDA) in nanotherapeutic systems for HNC due to its unique properties. PDA has found applications in chemotherapy, photothermal therapy, targeted therapy, and combination therapies that facilitate better carrier control for the effective reduction of cancer cells than individual therapies. The purpose of this review was to present the current knowledge on the potential use of polydopamine in head and neck cancer research. Head and neck cancers (HNC) are very common on a global scale. In 2018, they were in sixth place in terms of the most common cancers in the world [1]. According to The Surveillance, Epidemiology, and End Results (SEER) program HNC in 2022 it is estimated that there will be 54,000 new cases of the oral cavity and pharynx cancer and an estimated 11,230 people will die of this disease. Oral cancer is more common in men than women, among those with a history of tobacco or alcohol use, and people infected with human papillomavirus (HPV) [2] (Figure 1). Smoking can cause head and neck cancer and is correlated with the frequency and intensity of smoking [3]. Another factor is the consumption of alcohol, which acts as a solvent, increasing the exposure of the mucous membranes to carcinogens [4]. The risk is significantly increased when smoking and drinking alcohol at the same time. However, individual variability in genetic susceptibility plays an important role because not all smokers and drinkers develop HNC [5]. Head and neck tumors constitute a large group of neoplasms and include organs such as lips, oral cavity, pharynx, paranasal sinuses, larynx, and ear [6]. One of the most common is squamous cell tumors, which are moderately sensitive to radiation and chemotherapy. In approximately 30–40% of patients, HNC is present in the early stages of the disease and has a 5-year survival of 70–90% with treatment [7]. Most cases of HNC are diagnosed in the advanced stages when medical treatment is less effective and surgical treatment cripples organs necessary for speech and swallowing [7]. HNC is a complex and difficult disease. In the early stages, the primary treatments include surgery, radiation therapy, chemotherapy, immunotherapy, gene therapy, photothermal therapy (PTT), and photodynamic therapy (PDT) [1]. Surgery is the primary treatment of oral cancer, while radiotherapy is the primary treatment for nasopharyngeal cancer. Due to the anatomical sensitivity of these tumors and surrounding tissues, current treatments may result in adverse effects such as mucositis, neurotoxicity, tissue or bone necrosis, fibrosis, and even infection [2]. The Food and Drug Administration (FDA) has approved various chemotherapeutic agents such as cisplatin, carboplatin, 5-fluorouracil, docetaxel, methotrexate and bleomycin, and three monoclonal antibodies for the treatment of HNC. The current standard of treatment for recurrent head and neck cancers focuses on chemotherapy based on cetuximab and platinum with cisplatin or carboplatin as well as methotrexate and 5-fluorouracil, and doctors additionally introduce surgery and radiotherapy [3]. Chemotherapy diffuses its distribution, which reduces the effectiveness of the treatment and leads to severe side effects. Radiotherapy, in turn, often promotes the development of tumor resistance, leading to a negative prognosis [4]. It is important to use multidisciplinary treatment in the therapeutic process, as well as to adjust the treatment plan continuously according to changes in the patient’s body [5]. Patients with relapsed HNC and disseminated metastases do not respond to treatments, such as surgical ablation in combination with radiotherapy and chemotherapy. Resistance to cancer metastasis is largely due to the different and heterogeneous subpopulations of metastatic cells, in which they modify gene expression, growth rate, properties, and cell surface functions compared to primary cancer cells, which may be the cause of resistance to commonly used drugs and a problem with drugs reaching metastatic sites, contributes to poor therapy outcomes [6]. The arising applications of nanotechnologies in biomedicine provide new opportunities for dealing with the problems of therapies in cancer treatments. Nanomaterials are particles at the nanometric scale that have great potential in the medical field due to their specific material properties [7]. Nanomedicine may have a tremendous impact on head and neck cancer therapies through its targeted approach and potential reduction of side effects. The controlled delivery of drugs is very important to the pharmaceutical industry because such therapy allows for the delivery of a higher concentration of the drug to the tumor cells while giving patients a lower dose. In the case of HNC treatment, it is very important due to the lack of specificity of conventional cytotoxicity agents [8]. Nanocarriers smaller than 100 nm may be a vehicle for systemic administration due to their prolonged blood circulation [9]. The induction of cytotoxicity in neoplastic cells depends on the size of polydopamine nanomaterials (PDA). Due to their small size, nanoparticles can be captured by cancer cells through the effect of increased permeability and retention (EPR), causing local accumulation and cytotoxic effects on these cells [10]. Polydopamine can be easily synthesized by simple dopamine oxidative self-polymerization and due to its excellent biocompatibility, degradability, low toxicity, and good photothermal conversion efficiency, it can serve as an ideal nanocarrier or photothermal agent for cancer treatment. Importantly, due to its excellent photothermal effects and strong adhesive capacity, PDA can be easily functionalized with numerous nanomaterials for synergistic anti-cancer therapy [11]. Herein, we describe the current status of various polydopamine-based nanostructures administered to support the treatment of HNC and describe the potential future use of polydopamine. Curiosity to discover how mussels adhere to various wet surfaces with a force that can withstand ocean currents led to the discovery of adhesive proteins secreted by mussels, which inspired the creation of the compound PDA, which turned out to be crucial for mollusks adhesion [12]. Polydopamine is a brown-black, insoluble biopolymer [13]. It is formed in the process of dopamine oxidation in alkaline conditions [14]. PDA is composed of indole units with varying degrees of hydrogenation, probably linked by carbon-carbon (C-C) bonds between the benzene rings. The polymer has the ability to tautomerize quinoid and catechol units, which results from the presence of two oxygen atoms in the structure bound to the benzene ring. Polydopamine is also made of dopamine units that are not cyclic, i.e., they contain aminoethyl side chains [15]. An undoubted advantage of PDA is also the ease of its preparation—dopamine undergoes self-polymerization in mild conditions [16]. PDA synthesis is described as fast and simple, and the required reagents as inexpensive [17]. The monomer of polydopamine is dopamine. There are several ways to obtain polydopamine: by oxidation in an aqueous solution, by electropolymerization and by enzymatic oxidation [18]. The first method consists in dissolving dopamine hydrochloride in an alkaline solution. In the presence of oxygen, spontaneous auto polymerization of dopamine to polydopamine occurs. Liu et al. observed a color change of the solution from colorless through pale yellow to dark brown during the reaction [19]. For example, Sahiner et al.’s team synthesized PDA in Tris buffer at pH 8.5 at room temperature with 300 rpm agitation. After 24 h, precipitated PDA particles were observed [20]. The advantage of this method is its simplicity, no need to use environmentally harmful reagents, complicated equipment or to ensure extreme reaction conditions [19]. The thickness of the film can be adjusted by changing the concentration of dopamine and appropriately extending or shortening the polymerization time. The disadvantage of the above method is the difficulty in obtaining a film layer of uniform thickness. The electropolymerization method produces a film of greater and more uniform thickness and the obtained polydopamine can be deposited directly on electrodes. The reaction takes place in the absence of oxygen, however he limitation of the method is the fact that the PDA film can only be created on electrically conductive materials. The third method of obtaining polydopamine is enzymatic oxidation, in which the enzyme tyrosinase catalyzed the dopamine oxidation reaction [18]. Scientists paid attention to the excellent adhesive properties of polydopamine, which enables it to be deposited on the surface of all types of organic and inorganic substrates, even highly hydrophobic ones, creating a stable coating [19,20]. Polydopamine is a hydrophilic compound. This provides the desired properties of the surface to be coated with the compound without the need for other modifications. As a result, polydopamine can be used as a substance that improves hydrophilicity [21]. Their polar groups are responsible for the high surface energy and hydrophilicity of the polydopamine molecule [22]. As the main pigment of naturally occurring melanin, PDA has excellent optical properties and good biocompatibility [20]. Other advantages of polydopamine, deciding its wide application, including in medicine, there is sensitivity to changes in pH and biodegradability [23]. Polydopamine also can absorb near-infrared radiation and convert it into heat with high photothermal conversion, which makes it possible to use this nanomaterial in photodynamic therapy [24]. Eumelanin and polydopamine have close absorption spectra in the UV-VIS wavelength range in the electromagnetic spectrum. Their quantum fluorescence efficiency is low. Both of these compounds have the ability and can transform most of the absorbed light into heat [25]. Liu et al. showed that irradiation with a near-infrared laser of 2 W/cm2 near-infrareds, a suspension of polydopamine nanoparticles, can increase the temperature by about 33.6 °C, compared to a water sample where the temperature increased by 3.2 °C. The scientists found that neoplastic tissues, after injection of polydopamine and irradiation with a laser, can be heated to a temperature of 50 °C, which would result in the death of the cancer cells after 5 min. The high thermal conversion efficiency of polydopamine allows it to be used as a photothermal material [26]. They can use the polymer in photothermal therapy for cancer treatment, which is characterized by high selectivity and low invasiveness, and near-infrared laser for a specific tumor site. Therefore, polydopamine is a promising candidate for anti-cancer therapy [25]. PDA molecules are rich in reducing functional groups—as a result, polydopamine shows a wonderful ability to scavenge free radicals and, reactive oxygen species (ROS), and thus reduce inflammation caused by ROS [27]. Due to its chemical structure, polydopamine can be easily modified by a reaction between amino or thiol groups and quinone groups present in the structure of polydopamine [28]. Another property of polydopamine resulting from its specific structure is its high ability to bind and transport drugs (e.g., doxorubicin)—through π-π bonds or hydrogen bonds. At the same time, a constant pH-dependent release of the transported particles was observed [28]. Cui and colleagues conducted a study that confirmed the pH-dependent release of doxorubicin from the PDA nanocarrier. Drug release was analyzed in buffer at a pH ranging from 5.0 to 7.4. It was observed that doxorubicin was released slowly at pH 7.4, while at pH 6.0 this rate increased, and at pH 5.0 almost 85% of the drug was released within 12 h [29]. Because the tumor microenvironment is acidic [30], this mechanism may be of particular importance in the design of the controlled release of drugs based on nanomaterials. Polydopamine can chelate metals with oxygen or nitrogen atoms of the molecule, which is dependent on pH, which makes it possible to complex polyvalent metal ions, e.g., iron (III), copper (II), and zinc (II) ions. This enables binding with radioisotopes and transition metals, which makes it possible to use polydopamine in radioisotope therapy for cancer or to purify water from heavy metals [31,32]. Reactions of polydopamine with coated surfaces allow for many modifications of these surfaces, which enable obtaining the desired properties. Zmerli et al. synthesized polyethylene glycol (PEG) modified polydopamine nanoparticles to combine photothermic therapy and photodynamic therapy, thereby increasing the effectiveness of anti-cancer therapy [33]. Targeted therapy is a type of precise treatment, with targets proteins that control cancer cells’ growth and spreading throughout the body. Neoplastic tissue accumulates nanoparticles faster than other tissues. This is the so-called enhanced permeability and retention effect, which is responsible for passive targeting (Figure 2). Active targeting can be achieved through molecular recognition, which enables the homogeneous distribution of nanoparticles in the tumor tissue and thus delivery of the drug to a specific site [34]. Appropriate modification of the surface of nanoparticles can extend their circulation time in the blood and also reduce the uptake of macrophages by the phagocytic system. Thus, nanoparticles can increase the selectivity and effectiveness of methods of provoking the death of cancer cells with minimal toxicity to non-malignant cells [35]. An important reason for nanoparticle modification is the control of nanoparticle interactions with cells, enabling the targeting of peptides, ligands, or small particles [36]. One example is the epidermal growth factor receptor (EGFR), which overexpression is common with head and neck squamous cell carcinoma (HNSCC). Its high level is associated with poor prognosis in various neoplasms, which indicates the usefulness of receptor-targeted therapies. Another one is folic acid (FA) receptors, which are attached to the surface of cells with a high affinity for folic acid and are overexpressed in many malignancies such as breast, ovarian, lung, kidney, head and neck cancer, etc. [37]. Folic acid is a water-soluble B vitamin that is essential for DNA synthesis. Folic acid retains the ability to bind to folate receptors after being coupled to other structures and often improves endocytosis [11]. Properties of polydopamine enable them to penetrate through the cell membrane, including the blood-brain barrier, increase the half-life of active substances, or delay their metabolism. Biomaterials for more effective drug delivery at HNC are strongly associated with unique features of the tumor microenvironment, such as low pH, high ROS levels, enzyme overexpression, and hypoxia [38]. Targeted drug delivery nanomaterials respond to these changes in the microenvironment, leading to more accurate drug delivery, better tumor penetration, and sustained drug release, while reducing the dose of chemotherapeutic agents delivered, resulting in fewer side effects [39]. Polydopamine-based nanomaterials can be used to target therapy due to their pH dependence. Drug release may be based on the effect that the pH around the tumor is slightly acidic compared to healthy tissues [40]. Studies by Cheng et al. showed that polydopamine-modified mesoporous silica nanoparticles loaded with doxorubicin released smaller amounts of a chemotherapeutic agent than other nanoparticles at pH = 7.4. The release of the drug polydopamine was significantly higher at lower pH values, especially at pH = 5.0. Polydopamine had a positive effect on the release of doxorubicin at the tumor site, where there is an acidic environment [41]. Most tumor cells, even under normal oxygen conditions, obtain energy mostly through glycolysis. The ongoing process of glycolysis and the resulting product—lactic acid, lowers the pH to about 6.0, which differs from the pH of healthy tissues, which is around 7.2–7.4. Acidification of the environment significantly accelerates the delivery of the drug to the cancer cells [42]. Other aspects in the tumor microenvironment which may lead to the targeted release of the drug are high-level or reactive oxygen species and occurring glutathione. On the surface of PDA, there are reactive phenolic or hydroxyl groups that are oxidized by hydrogen peroxide. As a result, the hydrogen bonds between the drug and polydopamine are weakened. Glutathione can apply the same effect by disrupting the π-electron bonds [42]. A high concentration of glutathione makes it possible to apply therapy based on targeted drug delivery and release, depending on the level of glutathione (GSH) [27]. The connections of disulfide bond break and release the drug when exposed to an environment with a lot of GSH [43]. Drug delivery systems are modified to achieve the highest selectivity. It is possible through biological pathways and targeting of polydopamine, for example, individual receptors, peptides, and even genes [44]. One of the methods of selective therapy is to take advantage of the fact that tumors overexpress folic or hyaluronic acid receptors. Coating the polydopamine surface with analogous ligands improves the targeting of the therapy and ensures its effectiveness. Modifying with peptides allows binding and, as a result, contributes to increasing the impact of polydopamine on cells [40]. In vivo application of interfering strategy via siRNA or shRNA uprise many challenges, like transfection and tissue targeting. Due to the excessive hydrophilic properties of these molecules, and poor in vivo stability, there is a need to use the vectors [45]. Modified mesoporous polydopamine (MPDA) nanoparticles proved useful for delivering siRNA in thyroid cancer cells. In their research Martimprey et al. and Niemela et al., 2020 showed, that nanoparticles were able to accurately and effectively deliver siRNA or drugs into thyroid cancer cells [45,46]. Asghar et al. 2021 prepared mesoporous polydopamine particles with surface modification by N,N-dimethylethylenediamine (DMEA) and loaded them with siRNA. The cells efficiently took up these nanoparticles and released the siRNA after 96 h. They were also investigating the effect of empty or STIM1-siRNA loaded nanoparticles on cell invasion and proliferation, however, they found no effect of empty nanoparticles, and both the invasion and proliferation were significantly downregulated by STIM1-siRNA loaded nanoparticles [47]. Since the use of pharmacological blockers or siRNA in the inhibition of e.g., STIM1 is problematic, Asghar et al., showed that siRNA-loaded nanoparticles could be used to successfully knock down STIM1, and thereby reduced both proliferation and invasion of the ML-1 cells. A combination of siRNA-loaded nanoparticles and lower doses of cytostatic could be an alternative approach to critical thyroid cancer progression, causing less adverse effects of the chemotherapy [47]. Chemotherapy is the most widely used cancer therapy. Doctors recommend combined comprehensive multimodal treatment for patients with terminal-stage of head and neck cancer [21]. We can divide the use of chemotherapy into induction chemotherapy, synchronous chemotherapy, and adjuvant chemotherapy [22]. Induction chemotherapy is used before surgery to reduce the volume of tumors, synchronous chemotherapy is used to increase the effectiveness of radiotherapy while reducing the risk of lymph node metastases. The goal of adjuvant chemotherapy, on the other hand, is to kill small lesions that cannot be surgically removed or to reduce relapses and improve survival. In chemotherapy over HNC treatment, drugs such as fluorouracil (5-FU), methotrexate (MTX), bleomycin, mitomycin C, hydroxyurea, cisplatin, and carboplatin are used [4]. Chemotherapy is very effective in fighting against both primary tumors and metastases, however, it has its drawbacks. One of them is low selectivity—chemotherapeutic agents do not limit their cytotoxic activity only to neoplastic cells, but they also destroy healthy cells and tissues [23]. Another issue is the growth of resistance to these drugs. In patients with advanced neoplastic disease, cytostatic resistance is one of the most serious therapeutic challenges [24]. Controlled drug delivery systems are one way to increase the effectiveness of chemotherapy and decrease the risk of side effects. Nanocarriers can easily deliver drugs directly to the tumor, taking advantage of the phenomenon of increased blood vessel permeability at its site. As a result, bioavailability increases, while the toxic effect of drugs on healthy cells and the risk of resistance occurrence are reduced. The consequence is also a decrease in the costs of therapy [23]. Cheng et al. designed a folding nanocarrier system of d-a-tocopheryl polyethylene glycol 1000 succinate (TPGS)-functionalized polydopamine-coated mesoporous silica nanoparticles for the delivery of cytostatics—doxorubicin (DOX). The effect of the obtained nanocomposite (MSNs-DOX@PDA-TPGS) on drug-resistant lung cancer cells was investigated in vitro and in vivo. MSNs-DOX@PDA-TPGS showed greater toxicity to multi-drug resistant cancer cells than free DOX. It was also observed that MSNs-DOX@PDA-TPGS can increase the concentration and extend the residence time of DOX at the tumor site. The increased release of DOX in the tumor’s acid microcirculation, and thus the lower toxicity of the drug in healthy cells, was due to the sensitivity of PDA to changes in pH [25]. Polydopamine systems with doxorubicin are often used [11]. In the studies of Wang et al., the combination of doxorubicin and gossypol gives beneficial effects resulting from synergistic action. However, the π-π bonds between them are not stable enough. This may be due to the different hydrophilic nature of the two substances. The use of polydopamine, which also contains π electrons in its structure, increases the stability of the system used. This results in an extension of the biological half-life, and this translates into the effectiveness of the therapy [23]. Radiotherapy is a widely used treatment that adopts high-energy rays to inhibit the proliferation of cancer cells. However, the high-energy rays inevitably induce damage to the normal tissues, exerting hazardous effects related to radiotherapy [26]. One of the methods to improve is radiosensitization, introducing agents, that would make the tumor more sensitive to ionizing radiation [27]. Nanocarriers such as polydopamine can transport not only drugs but also radioisotopes and thus increase the selectivity and effectiveness of radiation therapy, which was the subject of a study by Zhong et al. [28]. The polydopamine synthesized by them has been functionalized with polyethylene glycol to increase its stability. Then, the technetium 99mTc radioisotope was introduced into some of the particles, and the 131I radioisotope and doxorubicin were introduced into some of the particles, resulting in the 131I-PDA-PEG/DOX nanocomposite. The effectiveness of the resulting complex in chemotherapy combined with radiotherapy has been studied both in vitro and in vivo. In vitro, it was observed that the cytotoxicity of 131I-PDA-PEG was higher than the cytotoxicity of 131I alone—the use of a carrier significantly increased the uptake of radioactive iodine by tumor cells. In contrast, the toxicity of free doxorubicin and PDA-PEG/DOX was comparable. In an in vivo study, mice that received combination therapy with 131I-PDA-PEG/DOX showed the highest level of tumor cell destruction. Importantly, no significant long-term toxicity was observed [28]. Photodynamic therapy involves the non-invasive introduction of a drug into the tumor cell to destroy it [29]. Clinical studies have shown that during PDT, the oral cavity of oral squamous cell carcinoma (OSCC) patients retains its structure, function, and appearance as well as minimizes side effects without permanent or systemic toxicity [30]. It is a method that can be a good alternative treatment for patients who are difficult to treat with surgery [31]. Due to its favorable properties, polydopamine can be used as a carrier. Targeted delivery to the tumor can be ensured, which reduces and spares the accumulation of the active ingredient in healthy cells. Most conventional photosensitizers (PS) are stimulated by visible light (VIS), which cannot reach deeply located tumor tissues. Therefore, near-infrared (NIR) light has begun to be used in PDT, as it can penetrate deep into tissues. Studies have shown that nanoparticles can convert NIR light into VIS, which can then be absorbed by PS [32]. PDT uses photosensitizers which, under the influence of irradiation, pass from the ground state to the excited state, i.e., the triplet one [33]. In its active state, the substance molecule transfers energy to oxygen and stimulates the production of singlet oxygen. The resulting product may further generate free radicals. A significant increase in their level causes the death of the cancer cell. Most of the substances used are hydrophobic, so the advantage of polydopamine, which is increasing the hydrophilicity of the system, is used, which translates into more efficient delivery to the target [34]. Photosensitizers can be bound by PDA through chemical interactions. The attachment of substances takes place due to the presence of amine or thiol groups. Also, the presence of carboxyl groups allows the carbodiimide reaction to take place and the bond to be formed. In addition to chemical bonds, physical processes can also take place. Compounds containing aromatic groups react through π electrons [33]. The photosensitizers used include, among others porphyrins, or macrocyclic aromatic systems. They are characterized by strong fluorescence and the ability to generate free radicals. PDA increases the hydrophilicity of these systems for effective delivery and therapy. Apart from porphyrins, various metal complexes are also used, e.g., ruthenium, iridium, and gold [35]. In the study by Yan et al., A PDA carrier modified with the presence of folic acid (FA) was created (folate receptors (FR) are present in the neoplastic tissue in much greater amounts than in the healthy tissue—this feature can be used as a therapeutic and diagnostic target). After loading the cationic phthalocyanine (Pc) photosensitizer, the PDA-FA-Pc nananolide was obtained, the effect of which was tested in vitro and in vivo (mouse model). The photosensitizer was gradually released in the acidic environment of the tumor. Much higher PDA-FA-Pc uptake by cancer cells than by healthy cells was observed. Finally, the investigated PDA-FA-Pc nanocomposite caused a significant inhibition of tumor growth [36]. The purpose of photothermal therapy is to increase the temperature in tumor tissues while preventing damage to surrounding healthy tissues [37]. Local hyperthermia can have direct cell-killing effects. Nanoparticle-mediated photothermic therapy uses photosensitive light-to-heat conversion to effectively remove neoplastic tissue, and due to the limited depth of light penetration, it is more suitable for the treatment of superficial tumors such as skin cancer and HNSCC [38]. In the case of single cancer cells, the heating process may change the permeability of the cell membrane and receptors, change the enzymatic activity and cell structure, inducing apoptosis of single cancer cells. At the same time, exposure of cells to heating causes rapid translocation of nucleolin from the nucleolus into the nucleoplasm, which inhibits DNA replication and synthesis. The main factors in the tumor microenvironment that have a strong influence on the tumor response to hyperthermia are perfusion, permeability, pO2, pH, and pressure [8] (Figure 3). There is a need for photothermal converting agents (PTAs) with high tumor accumulation and photothermal conversion performance [39]. Due to the slow or non-degradable photo thermal converting agents based on metals such as gold nanopeel, gold nanocoating, gold nanocage, and CuSx nanocrystal, they are retained in many organs after the mission is completed. It was found that in the case of hollow gold nanospheres, about 70 and 95% of them can be retained in the liver and spleen, respectively [40]. A special property of polydopamine is its photothermal conversion ability [23]. Under the influence of light with a wavelength of λ = 808 nm, the emission of heat by polydopamine is most effective. Also, other ranges may cause this phenomenon, e.g., below 1064 nm, which results from differences in the thickness of the PDA layer [41]. Polydopamine can occur in various shapes or in the packing densities of oligomers, which means that it can have different photothermal properties, depending on its properties. For example, nanoparticles that are less than 200 nm are more commonly used in in vivo research because of their pharmacokinetic properties. Temperature changes in photothermal therapy show a dependence on the concentration of nanoparticles, but in the case of high PDA concentrations, they have a greater light attenuation factor, and thus a smaller penetration depth [42]. In this therapy, photosensitizers are used, most often chlorin e6, which absorbs photons from the active radiation. This allows oxygen to move from a singlet, ground to an excited state. The produced products react with other particles, transferring energy to them, and also contributing to the generation of further free radicals [34]. Upon radiation exposure, conversion takes place and heat is released. This has the effect of hyperthermia and this contributes to the induction of apoptosis. The mechanism causing cancer cell death is related to the induction of oxidative stress in mitochondria under the influence of temperature [43]. The pathways associated with the pro-apoptotic protein Bid, cytochrome c, and caspase 3 are activated [44]. The mechanisms related to the generation of ROS occur at the temperature of 41–45 °C. The uptake of drugs delivered in the polydopamine system by cancer cells also increases to this extent. On the other hand, increasing the temperature to 46 °C causes necrotic death [44]. In photothermal therapy and photodynamic therapy, the ability of polydopamine to affect reduced glutathione is used. PDA reacts with GSH and reduces its level in the cancer cell environment [45]. This contributes to the weakening of the antioxidant effect of the tripeptide. As a result, the level of free radicals generated when using PTT or PDA is higher, and the applied therapy is more effective [46]. However, the limited area of action of PPT carries the risk of recurrence of the disease, as hidden neoplastic cells may remain around the tumor beyond the radiation range. Hence, combining PTT with other types of cancer therapy seems beneficial. The team of Chen et al. developed a combination of photothermal therapy with immunotherapy and chemotherapy. As a carrier for doxorubicin and imiquimod, nanoparticles of polydopamine inoculated with folic acid, a ligand with a high affinity for folic receptors abundant in neoplastic tissue were used. The obtained particles had several unique advantages, including ease of manufacture, full biocompatibility, and high drug delivery efficiency to the tumor. The combination of the above forms of therapy gave a synergistic effect in the fight against cancer—PTT and chemotherapy led to the almost destruction of the tumor, and immunotherapy saved the mice participating in the experiment from tumor recurrence [47]. Photothermal therapy is one of the non-invasive cancer treatments. It is based on the conversion of photon energy into heat energy, which is cytotoxic to cancer cells. PTT is a local therapy with relatively few side effects [48]. However, the limited area of action of PPT carries the risk of recurrence of the disease, as hidden neoplastic cells may remain around the tumor beyond the radiation range. Hence, combining PTT with other types of cancer therapy seems beneficial. The team of Chen et al. developed a combination of photothermal therapy with immunotherapy and chemotherapy. As a carrier for doxorubicin and imiquimod, nanoparticles of polydopamine inoculated with folic acid, which is a ligand with a high affinity for folic receptors abundant in neoplastic tissue, were used. The obtained particles had several unique advantages, including ease of manufacture, full biocompatibility, and high drug delivery efficiency to the tumor. The combination of the above forms of therapy gave a synergistic effect in the fight against cancer—PTT and chemotherapy led to the almost destruction of the tumor, and immunotherapy saved the mice participating in the experiment from tumor recurrence [47]. Polydopamine is also used in gene therapy [49]. Its purpose is different from the case of chemotherapy or radiotherapy. The supply of nucleic acids does not act on the symptoms but on the source of the disease, which are various mutations that promote tumorigenesis. However, DNA is sensitive to degradation by lysosomes. Due to its properties, polydopamine can be used as a carrier. In this case, PDA with a modified polyethyleneimine [50] was used. The ability to photochemically convert under the influence of radiation is also advantageous. The generated heat and free radicals contribute to the disruption of endosome membranes, which translates into reduced nucleic acid uptake. By passing the fundamental barrier that interferes with drug delivery, it is possible to increase the effectiveness of the therapy [11,51]. In a study by Zhang et al., polydopamine was grafted with folic acid, creating a nanocarrier for siRNA—a short interfering RNA that can silence the expression of sequences homologous genes—in this case, the ROC1 oncogene [Zhang et al., 2021]. Gene silencing by RNA interference appears to be a promising therapeutic strategy. To improve the safety, biodistribution, pharmacokinetics, selectivity, and efficacy of siRNA therapy, it is necessary to use appropriate nanocarriers [52]. The nanovector designed by Zhang and colleagues was characterized by good biocompatibility and, thanks to the presence of FA, selectively delivered the transported siRNA directly to liver cancer cells through receptor-associated endocytosis. Then, siRNA was released from the nanocomposite into the tumor microenvironment—this process was conditioned by the change in pH. As a result, not only was the proliferation of neoplastic cells inhibited but also their apoptosis was stimulated. The combination of the above gene therapy with photothermal therapy has shown an excellent inhibitory effect on the growth of liver cancer, in vitro and in vivo [53]. Nanomedicine is a rapidly developing field. Due to the small size of nanocarriers, smaller than 100 nm, they can be used as a vehicle for systemic administration, thanks to their prolonged blood circulation [54]. Their small size also enables the uptake of polydopamine by cancer cells [55]. Due to its excellent biocompatibility, pH sensitivity, and good adhesion, polydopamine is a suitable material for use in the treatment of cancer. To this day, several materials with polydopamine have been used in head and neck cancers, taking advantage of its many properties (Table 1). Most oral cancers are derived from epithelial and mucosal mutations found in the exposed parts of the mouth, which enables the use of photothermal therapy [56]. Li et al. developed a pH-responsive charge reversal nanomedicine system for oral cancer. They synthesized polydopamine-modified black phosphorus nanosheets (BP NSs) as basal material, then used polyacrylamide hydrochloride-dimethylmaleic acid (PAH-DMMA) charge reversal system for further surface modification, which can be negatively charged at blood circulation, and become a positive surface charge in the tumor site weakly acidic conditions due to the breaking of dimethylmaleic amide [57]. Polydopamine coating not only enhanced the photothermal properties of this material but also greatly improved its stability [11]. BP@PDA-PAH-DMMA constructed by Li et al. was suitable for intravenous delivery, the ability to promote tumor cell uptake, as well as excellent photothermal properties in vivo and in vitro due to the use of polydopamine, and the killing effect of oral cancer cells, providing a new idea for the treatment of oral cancer [57]. The epidermal growth factor receptor (EGFR) is overexpressed in many neoplastic cells, including head and neck cancer. Cetuximab, a chimeric anti-EGFR monoclonal antibody, has been approved by the FDA as an EGFR inhibitor for the treatment of colorectal cancer and head and neck cancer [58]. He et al. developed a photothermal converting nanomaterial based on the core/shell structure of biodegradable poly(lactide-co-glycolide) (PLGA) and polydopamine and to enhance effectiveness they encapsulated doxorubicin (DOX) into the cetuximab functionalized nanoparticle [59]. With the help of an anti-EGFR antibody, the nanoparticle could efficiently penetrate head and neck cancer cells and convert near-infrared light into heat to trigger drug release from the PLGA core. Scientists used polydopamine because polydopamine nanoparticles can generate heat after NIR irradiation [60]. In the experiment by He et al., it was shown that the PLGAa nanoparticle itself did not generate heat after irradiation, and PLGA/PD showed a concentration-dependent photothermal effect. Due to the unique concentration of PLGA/PD, overheating or burnout situations could be easily prevented. Since the nanoparticle was retained in the tumor tissue and then released, the cardiotoxicity associated with the use of doxorubicin was minimal. The authors stated that thanks to the biodegradability of DOX@PLGA/PD-C, the nanoparticle may be a promising tool in the treatment of head and neck cancer [59]. Maor et al. investigated if NIR laser-induced photothermal response could expedite the release of theranostic agents like copper oxide nanoparticles (CuO-NPs) from PLGA nanospheres, coated with the efficient light-absorbing PDA. Maor et al. demonstrated the significant effect of the PDA shell in heat induction when they irradiated the target with the NIR-laser beam after using polydopamine to enable simultaneous complementary photothermal therapy. Heating efficiency was higher than 85%, compared to uncoated copper oxide nanoparticles loaded with PLGA or water, as a control group [61]. The excellent adhesive properties of polydopamine make it possible to use it to cover the surfaces of polymeric nanocarriers and inorganic NPs. Due to the surface modification, it was possible to obtain a stealth effect using PEG to reduce interaction with the immune system. PEGylation is also commonly used to extend the circulating half-life by functionalizing a hydrophilic polymer such as PEG at the surface of a nanoparticle. In the case of polydopamine, the -SH or -NH2 terminated polyethylene glycol can be modified on the PDA surface, which can further reduce the recognition and destruction of nanoparticles by the reticuloendothelial system (RES), thereby extending the circulation time [23]. Maor et al. expressed that controlled release connected with high heating efficiency allows the designing of a thermal therapy approach, capable of killing tumor cells with lower laser power and shorter time than in conventional therapies. The results also showed the effect of the PDA coating on heat induction and showed that it mainly influences temperature. They attributed the light-induced response to the polydopamine coating as a light-sensitive polymer. Its wide absorption spectrum, especially in the first biological optical window (650–950 nm), allows for an increase in temperature at a level useful in the treatment of hyperthermia [61]. Jin et al. in their studies designed a nanocomplex PDA–SNO–GA–HA–DOX (PSGHD) to enable effective and accurate tumor therapy. PSGHD nanocomplex was tested in vitro with tongue squamous cell carcinoma (HN6 cells) and in vivo of WSU–HN6 tumor-bearing nude mice. Their multi-mode therapy was based on four different functions, whilst polydopamine was used for its photothermal conversion. The coactive effect of photothermal conversion by polydopamine and enzyme-triggered gambogic acid released from a gambogic acid-derivatized hyaluronic acid (HA–GA) resulted in tumor microenvironment-dependent gentle photothermal therapy [62]. New therapeutic strategies for papillary thyroid cancer based on organelle-targeted nanomaterials are very welcome to avoid excessive treatment with conventional surgery. Wang et al. demonstrated a strategy to inhibit mitochondria-targeted strategy and exocytosis inhibition of PDA-coated inorganic nanoparticles to enhance therapy for papillary thyroid cancer. Polydopamine has been used as a universal, multi-functional surfactant for coating inorganic NPs because of its abundant catechols that react with thiols and amines via Michael addition or Schiff base reactions. Taking advantage of its strong photothermal action, PDA-coated nanomaterials exhibit enhanced photothermal performance and act as promising photothermal agents in cancer treatment. They combined the mitochondria-targeted approach with photothermal therapy to achieve a non-invasive and improved thermal ablation of TPC-1 cells. These findings indicated that it has been shown that PDA-coated inorganic NPs can be used to develop a mitochondria-targeted anti-cancer therapy strategy that can selectively release drugs into the mitochondria and support cancer treatment by inhibiting exocytosis [63]. Esophageal cancer is a difficult disease to treat and has a high mortality rate. Doctors used stent implantation as the primary treatment method. However, neoplastic and inflammatory cells severely interfere with the clinical use of the stent and limit its long-term performance. One solution is to provide the stent with a continuous anti-cancer function. For this purpose, Zhang et al. synthesized a functional layer consisting of polydopamine and polyethyleneimine (PEI). As polydopamine has strong binding properties, which makes it possible to conjugate molecules [64]. In this study, polydopamine is used in the PDA/PEI layer to bind polyethyleneimine. It is possible due to the great amount of imino group in PEI, which can be attached via Michael addition and Schiff base reaction. Polyethylenimine was used, due to its good mechanical property and stability, and has also been proven to kill cancer cells [65]. In this work, esophageal cancer cells were cultured on each surface to evaluate the PDA/PEI layers’ anti-cancer function. The results demonstrated the PDA/PEI layers possessed excellent and continuous anti-cancer function, suggesting the promising potential of the layers for the application on surface modification of the esophageal stent materials [66]. Similar use of polydopamine was found in Zhang et al. later research, where they studied the PDA/PEI/5-Fu coatings, which inhibited the esophageal tumor cells (Eca109), epithelial cells (Het-1A), fibroblast (L929) and macrophages adhesion to the surface [67]. Polydopamine, as stated before, has a high photothermal performance, however, it can also be used for bonding PS to obtain photodynamic activity. In previous research, PDA with photosensitizers showed their anticancer effects in vitro and in vivo, however, using them may lead to PS release into blood circulation. To prevent the release of photosensitizers in the blood, it is attached to polydopamine nanoparticles by covalent bonds. However, the cleansing properties of ROS pose problems. Controlled release of PS at the tumor site is possible by combining the photosensitizers with sensitive materials that are cleavable by the relevant tumor microenvironment, such as acidic pH, oxidative stress, or an enzymatic reaction, and also through external energy sources such as light. To prevent this from happening, Zmerli et al. proposed affixing a TS linker to the PS, which would enable PS release in the selected tissue [42]. Zmerli et al. synthesized and characterized a new PEGylated PDA-based nanoplatform with bifunctional PTT and PDT properties, allowing bimodal cancer therapy with the possibility of releasing the photosensitizer on demand by bonding PS to polydopamine by covalent bonds. PEGylation of nanoparticles is a frequently used approach to increase their circulation time in the bloodstream or improve drug delivery efficiencies to target cells and tissues [68]. Created nanoplatforms showed low cytotoxicity in vitro, with high photothermal conversion efficiency and higher photodynamic effects on esophageal cancer cells [42]. At this stage of the polydopamine research, we can say that there are several unresolved problems. Scientists consider polydopamine a biocompatible compound. There are results confirming its biocompatibility with head and neck cancer cells. In the He et al. study, they conducted a live and dead assay study for polydopamine with PLGA on head and neck cancer cells. For cells co-incubated with the PLGA/PD nanoparticle, almost all cells were green, suggesting that the PLGA/PD nanoparticle itself is non-toxic [59]. Studies also show the biocompatibility of polydopamine in vivo [69]. However, with preclinical studies, there are only short-term research and at the moment there are no studies of chronic toxicity. Especially, one based on an animals model which would enable obtaining the results needed for further work on the use of nanostructures based on polydopamine. There are also no studies on the possible accumulation of polydopamine or its biodistribution, and biodistribution is a key issue in future clinical applications of PDA. The nanoparticles have the potential to interact with the mononuclear phagocyte system (MPS), which is made up of lymph nodes, spleen and liver and consists of immune cells responsible for identifying and removing foreign bodies from the blood. In addition, their surface coating may also affect the fate of therapeutic systems [70]. Another important challenge of using PDA is its fate in the body. Antibodies, peptides, and other bio-recognition molecules can often be used to target nanoparticles in nanotherapy systems precisely using PDA in theory, but in practice, nanoparticles undergo non-specific binding and endocytosis in vitro [71] and uptake by RES in vivo [71], which may be a case also with polydopamine. One more important limitation of the use of polydopamine in clinical trials is the difficulty of its structural identification. PDA analysis is further complicated by its insolubility in water as well as in organic solvents. As a result, the PDA study using typical analytical tools, such as e.g., solution copy NMR spectrum, solution UV-vis spectroscopy, gel permeation chromatography and many mass spectroscopy techniques are not possible [72]. All of this makes the understanding of polydopamine in the body incomplete and inhibit the further development of PDA-based nanostructures in forthcoming clinical trials. Future research that would focus on solving these problems would help with the potential future clinical application of these PDA-based nanostructures. Head and neck cancers represent a wide range of cancers. The prognosis depends on the age, sex, and location of the tumor. In the last few years, interest in the use of polydopamine in head and neck cancers has increased. In this review, we demonstrated the potential of polydopamine in smart drug delivery systems, and polydopamine-based nanomaterials in particular. A characteristic feature that distinguishes polydopamine is its high adhesion capacity. This enables the use of polydopamine as a surface layer on other nanoparticles, which can modify or improve their activities, and attach various compounds to use the therapeutic effect of the current method of treatment, including chemotherapy and radiotherapy. Most research focusing on head and neck cancer therapy uses polydopamine in photothermal therapy due to its excellent light absorption characteristics to selectively over-heat cancer cells. Another important aspect of polydopamine used in HNC was its chemical reactivity. The many functional groups were found in PDA, which were able to react with a broad spectrum of molecules so that the materials achieved desired properties. Polydopamine-based nanomaterials used in head and neck cancer are just becoming popular, so additional research is still very much needed due to the variety of materials used, as well as their applications in cancer therapy. There is also one more important aspect of this variety of materials used in cancer, and that is toxicity, which is often overlooked. Polydopamine is considered being a biocompatible material, however, as of today there is no long-term toxicity research. This review describes nanotherapeutics systems, which are made of many compounds, and these compounds affect their physicochemical properties and the toxicity of these materials that have not been tested.

PMC10003235

Ryszard Sitarz,Dariusz Juchnowicz,Kaja Karakuła,Alicja Forma,Jacek Baj,Joanna Rog,Robert Karpiński,Anna Machrowska,Hanna Karakuła-Juchnowicz

Niacin Skin Flush Backs—From the Roots of the Test to Nowadays Hope

27-02-2023

niacin skin flush test,niacin sensitivity,PUFA,psychosis,first episode psychosis,ultra-high risk,UHR,schizophrenia,omega-3,omega-6

The niacin skin flush test (NSFT) is a simple method used to assess the content of fatty acids in cell membranes and is a possible indicator of factors hidden behind various outcomes in patients. The purpose of this paper is to determine the potential usefulness of NSFT in mental disorder diagnostics along with the determination of factors that may affect its results. The authors reviewed articles from 1977 onwards, focusing on the history, variety of methodologies, influencing factors, and proposed mechanisms underlying its performance. Research indicated that NSFT could be applicable in early intervention, staging in psychiatry, and the search for new therapeutic methods and drugs based on the mechanisms of NSFT action. The NSFT can contribute to defining an individualized diet for patients and prevent the development of damaging disease effects at an early stage. There is promising evidence for supplementation with polyunsaturated fatty acids, which have a beneficial influence on the metabolic profile and are effective even in the subclinical phase of the disease. NSFT can contribute to the new classification of diseases and a better understanding of certain mental disorders’ pathophysiology. However, there is a need to establish a validated method for assessing the NSFT results.

Niacin Skin Flush Backs—From the Roots of the Test to Nowadays Hope The niacin skin flush test (NSFT) is a simple method used to assess the content of fatty acids in cell membranes and is a possible indicator of factors hidden behind various outcomes in patients. The purpose of this paper is to determine the potential usefulness of NSFT in mental disorder diagnostics along with the determination of factors that may affect its results. The authors reviewed articles from 1977 onwards, focusing on the history, variety of methodologies, influencing factors, and proposed mechanisms underlying its performance. Research indicated that NSFT could be applicable in early intervention, staging in psychiatry, and the search for new therapeutic methods and drugs based on the mechanisms of NSFT action. The NSFT can contribute to defining an individualized diet for patients and prevent the development of damaging disease effects at an early stage. There is promising evidence for supplementation with polyunsaturated fatty acids, which have a beneficial influence on the metabolic profile and are effective even in the subclinical phase of the disease. NSFT can contribute to the new classification of diseases and a better understanding of certain mental disorders’ pathophysiology. However, there is a need to establish a validated method for assessing the NSFT results. Focusing on the arguments of David Horrobin postulating for the evolution of human nutrition as the basis of psychotic disorders, it is necessary to realize that with a sedentary lifestyle and the Industrial Revolution, we have lost the supply of essential fatty acids in optimal amounts for the proper functioning of the nervous system [1]. According to Horrobin, a diet overloaded with saturated fats and a shortage of those essential ones in company with possibly some unfavorable genetic endowment could led to the release of psychosis from the framework of diet, strictly defined by nature for thousands of years, undeniably contributing to the development of all mankind and shaping humanity [2]. To the group of psychotic disorders belong not only schizophrenia (SCH) but also schizoaffective disorders (SCHAD) and bipolar disorder (BD), pointing to the need to recognize its physiological heterogeneity by identifying subgroups of patients sharing a common biological signature and thus enabling to conduct further research on risk, course, and treatment efficacy [3,4,5]. SCH was described by Kraepelin as “dementia praecox” in the late 19th century and renamed by Bleuler’s term “the group of schizophrenias” in the early 20th century, argued in favor of the diversified development and course of psychosis [6,7,8,9]. A growing body of scientific evidence suggests that psychosis may have a common biological basis [10,11]. Following the example of other medical fields based on etiopathophysiological premises, modern expectations focus on a personalized approach in terms of genetic, neuroscience, and behavioral sciences to better understand and reveal the contemporary taxonomy of mental illness [12]. The Bipolar–Schizophrenia Network for Intermediate Phenotypes (B-SNIP) used a biological approach to identify distinct psychosis subtypes and after examining more than 70 variables, none allowed for the classification of patients according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) categories. Analyzes of external validators showed the advantage of a biotypic approach to identify biologically homogeneous subgroups of psychosis [13]. The literature provides genetic and biological evidence for the underlying causes of SCH and BD, including shared risk genes and overlapping family lines with psychosis diagnoses [14,15,16]. It also appears that SCHAD is used in clinical practice as an intermediate condition, with clinical manifestations of both psychosis and mood instability. This diagnosis is somewhat solid evidence of the blurring of the current classification of psychiatric disorders in the context of a diverse and arbitrary division of the image of psychosis [17]. The purpose of this paper is to update the usefulness of the NSFT with the presentation of the SKINREMS method as a simple, non-invasive, and inexpensive test for patients with symptoms of psychosis understood as SCH, BD, and SCHAD, as well as individuals at increased risk. Literature from PubMed, Google Scholar, and Web of Science databases was extracted. It included original articles, review articles, systematic reviews, and meta-analyses published during 1977–2022. No limits were set for the publication year. The inclusion criterion was the English language. Only human studies were included in the final analysis. The literature was analyzed in terms of history, variety of methodologies, influencing factors, and proposed mechanisms of NSFT action. All SCH spectrum disorders and other psychotic disorders were chosen. The search strategy included the following keywords: (niacin skin flush test OR niacin sensitivity OR niacin) AND (psychiatry OR psychosis OR psychotic OR schizophrenia OR unipolar OR bipolar OR schizoaffective OR affective OR depression OR manic OR hypomanic OR mania OR hypomania OR Horrobin OR prostaglandin OR phospholipid OR polyunsaturated fatty acids OR PUFA OR first episode psychosis OR ultra-high risk OR UHR OR phospholipase A2 OR arachidonic acid OR linoleic acid OR alpha-linolenic acid OR omega-3 OR omega-6 OR nutrition OR diet). In addition to the literature search on databases, references included in the analyzed papers were also taken into account. Ultimately, 86 articles were estimated as relevant to the theme and included in the review. For clarity, this section has been divided into the following subsections: The NSFT is a non-invasive and repeatable test method. It involves the application of an aqueous solution of methyl nicotinate on the skin, which causes its redness. Weak response to the niacin skin flush test (NSFT) related to SCH is widely known and observed in repeated studies, differing in methodology [18,19,20,21]. These include those where niacin was taken orally and the temperature changes were measured in the core body or on the earlobe [22,23]. Consistent with the current state of knowledge that SCH is a heterogeneous mental disease in terms of pathophysiology, the reaction to the NSFT turns out to be etiologically diverse [3,24]. Moreover, it seems that attenuated or delayed skin flushing does not always occur in patients with SCH, because even strong reactions to niacin have been reported [25]. This inconsistency in observations may be explained by the surprising results of a study by Berger et. al, which proved a significantly increased reaction in ultra-high risk (UHR) patients. Such sensitivity was inversely correlated with omega-3 and -6 fatty acids levels, but positively with phospholipase A2 (PLA2). It was concluded that the emergence of psychosis could be reflected in a “pro-inflammatory state” [26]. Tavares et al. showed in their study a significantly higher PLA2 activity among individuals with SCH [27]. Thus, the cascade of prostaglandin-forming reactions seems to be the key to the test. Furthermore, such excessive activation leads to the intensified synthesis of cyclooxygenases causing inflammatory reactions [28]. If the disturbances are similarly present in the brain area, they can significantly affect its functions influencing regional cerebral blood flow along with the neuronal activity [29]. Adding these observations to the hypothesis of neurodevelopment disturbance affecting both autonomic and higher cortical functions, Nilsson et al. showed poor test results of niacin non-responders in the cognitive aspect. In a study, as might be expected, non-responders showed not only lower IQ scores but also impaired psychomotor functions [30]. The process is significantly influenced by the hydroxycarboxylic acid receptor 2, which is coupled with the G protein and is expressed on the immune cells of the epidermis and keratinocytes. Interaction between niacin and niacin G protein-coupled receptor HM74A on epidermal cells increases the concentration of cytosolic calcium which triggers phospholipase A2 activity [31]. Thus, the hydrolysis of membrane phospholipids occurs as well as the release of AA, which is converted to prostaglandin D2 (PGD2) and prostaglandin E2 (PGE2) via cyclooxygenase-2 (COX-2). This reaction leads to the relaxation of the smooth muscle, causing the dilation of blood vessels [32,33]. Therefore, it has been postulated that the decreased skin reaction in patients with SCH may be caused by AA deficiency in the cell membrane [34,35,36]. The mechanism of the niacin action on the cell membrane is presented in Figure 1. Studies using NSFT differ in terms of methodology. So far, the methods used could be divided into those based on (1) thermal, (2) optical, and (3) blood flow and optical spectroscopy change measurements. In 1980, David Horrobin maintained that patients suffering from schizophrenia need more than 250 mg of niacin, taken orally, than normal individuals to flush [37]. In the 1990s, Rybakowski et al. conducted a study by administering 200 mg of oral niacin followed by thermometric recordings. Flushing was observed at the face, neck, and chest levels. Using an electronic thermometer, the temperature of the left earlobe was measured [23]. In addition, the body temperature measurement method was used by Glen et al. where, after oral intake of 200 mg of nicotinic acid, body temperature was measured using an oral thermometer and skin temperature by electrodes placed on both earlobes. Niacin response was defined as an increase in skin temperature of 2 degrees Celsius or more [34]. A very common method of conducting NSFT research is the optical one. It assumes observing the skin reaction at various time intervals and then documenting local redness, most often in the area of the forearm. Predominantly three or four concentrations of aqueous methyl nicotinate (i.e., 0.1 M, 0.01 M, 0.001 M, and 0.0001 M) are used. By tissue papers of the same size, methyl nicotinate is applied to the skin for a certain time. In this methodology, a topical skin reaction is assessed subjectively by flush status, often based on measurement scales created especially for these purposes, i.e., 0 = no reaction, 1 = minimal redness, 2 = moderate redness, and 3 = maximal redness. In addition, edema associated with local redness is sometimes described [18,27,38,39]. Since significant cutaneous vasodilation can occur in the absence of visually detectable edema, some studies measure skin changes using Doppler flowmetry [20,40,41]. The use of specialized equipment is also associated with the measurement of skin color changes using optical reflection spectroscopy [42]. The authors would like to present an alternative measurement method—SKINREMS as an innovative device for NSFT assessment [33]. The NSFT method assumes the application of methyl nicotinate solutions (Sigma Chemical, St. Louis, MO, USA) in three concentrations (0.1 M, 0.01 M, and 0.001 M) sprinkled on 2 × 2-cm tissue paper to the forearm skin for 90 s. The subsequent examination period lasts 15 min when the patient holds their forearm in the designed measuring device. A multidisciplinary team of researchers from the chair of the Department of Psychiatry, Psychotherapy and Early Intervention, Medical University of Lublin, designed and developed a novel measurement system for NSFT assessment. The initial design of the device is presented in Figure 2, which is distinguished by the simplicity of construction and low economic outlay. Thanks to the ergonomic design, patient examination is possible in all conditions. The measuring device consists of a tightly closed tube, which is evenly illuminated inside and has an entrance for a camera lens, which during the examination registers skin changes based on a fifteen-minute time-lapse movie, in which the photo is captured every 30 s, and thus the examination undergo dynamic changes. A total of 90 images are obtained per patient for all three concentrations of methyl nicotinate. The observed formation, disappearance, and intensity of the reaction differ over time. In Figure 3 we present an example of a trial conducted on a patient suffering from SCH and a person from the control group. We believe that the new method of NSFT assessment may be a simple tool to enable accurate differentiation of patients with SCH and BD and the identification of the patients group with observed disorders of membrane lipid metabolism, who should be expected to have a favorable therapeutic response to the implementation of unsaturated fatty acid supplementation and limit the amount of saturated and trans-unsaturated fatty acids in the diet. In our previous studies, without the use of the designed measuring system, the sensitivity and specificity of the performed NSFT were 71% and 66%, respectively, for the compared SCH patients and the control group; 55% and 54%, respectively, for the compared BD and the control group; and 91% and 72%, respectively, for the compared SCH and the BD patients [33]. It is expected that the usage of a newly designed measuring device will increase both test parameters. NSFT has been performed over the years involving patients suffering from schizophrenia and affective disorders. Table 1 is based and modified on Sun et al. and presents the diagnostic accuracy of NSFT, arranged from the highest sensitivity method used [43]. Clinically defined help-seeking UHR individuals seem to require intensive monitoring. Noting the fact that psychotic outbreaks often occur in the most productive age of early adulthood, it is crucial to ensure early intervention [48]. Diverse clinical approaches attempt to prevent full-blown psychotic disorders based on available criteria and concepts of prodromal symptoms [49,50]. As the use of antipsychotic drugs in the prevention of psychosis is controversial, there are studies showing the validity of PUFA supplementation [51]. The role of emerging studies that present different dynamics of NSFT reactions depending on the progression of the disease should be emphasized [52,53]. Langbein et al. showed various reactions to niacin solution across different UHR groups (UHR-B—BLIPS group, UHR-A—attenuated symptoms group, and UHR-G—genetic risk group) based on PACE criteria [54]. Moreover, Smesny et al. maintain that PUFA supplementation leads to the normalization of PLA2 activity, implying protective properties against the onset of a psychotic episode [55]. The studies of Nilsson et al. showed lower electrodermal activity after auditory stimulation in patients with SCH after orally taking niacin. However, neither ectodermal activity nor niacin sensitivity correlated with their age [21]. Taking into consideration the double hit hypothesis, other reports by Nilsson et al. support the assumption of neurodevelopmental disturbance affecting higher cortical and autonomic function, which reflected the niacin test results. Still, in this case, niacin non-responders did not differ in age from responders [30]. Yao et al., examining the skin reaction with a laser doppler flowmeter in individuals diagnosed with SCH and BD, also proved that niacin response abnormality was not influenced by the age or race of the patients [41]. Despite studies that do not confirm age as a confounder, some findings challenge this position [18,23,56]. Smesny et al. showed the influence of age and the differences in the response of men and women on the NSFT results [57]. Generally, women showed a stronger skin reaction to the NSFT, but the reaction became weaker with the increasing age of the women. Not only the widely discussed protective effect of estrogens on the onset of SCH, but also the menstrual cycle, could be important in deliberating skin re-actions in the NSFT [58,59,60]. In another study, Wang et al. showed significant effects in the case of gender, alcohol drinking, and education, but only at specific niacin concentrations [45]. On the other hand, Nilsson et al. did not show a difference in education years between non-responders and responders [30]. Based on clinical and theoretical considerations by David Horrobin, that prostaglandin deficiency is associated with patients diagnosed with SCH as well as those abusing alcohol, it is worth noting that the results of the Fiedler et al. study showed impaired skin reaction in NSFT in individuals addicted to alcohol [35,61,62]. Taking substance use into consideration, there are reports confirming that smoking cigarettes do not affect the NSFT results [41,46]. Likewise, Smesny et al. presented the results of the study that showed no observable effect on skin redness during the NSFT in cannabis users [42]. In another publication by Smesny et al., cannabis smoking also did not influence niacin flushing. Nevertheless, observations showed that cannabis use was much more common in first-episode compared to multi-episode patients [63]. However, there are also research results that show the influence of smoking cannabis on healthy individuals’ skin reactions. In such subjects, the redness of the skin during NSFT was less intense [64]. Additionally, the study of Chang et al. showed that the consumption of coffee did not affect the NSFT results. Although, some studies showed that only the age difference between relative and proband and the coffee drinking status affect the flush response [39]. The history of allergy in the family was also irrelevant [65]. As for the duration and medication of the illness, in a study by Nilsson et al., these factors do not correlate with niacin sensitivity and have no significant effect on the NSFT results [21,30]. In a study conducted by Liu et al., no niacin concentration showed significance on skin flushing regarding a medication with neuroleptics or mood stabilizers [46]. Similarly, in a study by Bosveld-van Haandel et al., antipsychotics did not appear as confounders [25]. There are studies claiming that the number of hospital admissions did not matter in response to niacin flushing [64]. Based on a study by Rybakowski et al., even a family history of SCH has no bearing on the test result [23]. Both the studies by Nilsson et al. and Liu et al. showed that the Positive and Negative Syndrome Scale (PANSS) had a nonsignificant effect on the NSFT results [21,30,46]. Taking into account Global Assessment Functioning (GAF), in the study by Yao et al., no significant correlations were found between the scores of the scale and NSFT outcomes [41]. In contrast, 1990 Revised Symptom Check List (SCL 90-R) showed an association between reduced skin flushing and high SCL 90-R ratings [63]. In a study by Glen et al., it turned out that on the Montgomery Asberg Depression Rating Scale (MADRS) and the Nurses’ Observation Scale for Inpatient Evaluation (NOSIE), flushers scored significantly higher than subjects whose reaction to niacin was disturbed [34]. Interestingly, by using the Brief Psychiatric Rating Scale (BPRS), Scale of Assessment of Positive Symptoms (SAPS), and Scale of Assessment of Negative Symptoms (SANS), Smesny et al. obtained results indicating no significant difference between first-episode and multi-episode patients. Moreover, neither total scores nor individual subscales correlated significantly with response to the NSFT [63]. Concerning pathogenesis at the molecular level, no association has yet been found between phospholipid abnormalities and an impaired response to the NSFT. There were attempts to assess mRNA levels of genes of the PLA2/COX cascade, which have shown some regularities. Yang et al. showed that five single nucleotide polymorphisms in PTGS2 and one PLA2G4A were significantly associated with the degree of response to NSFT, thus causing the disturbance in the free AA catabolism and inducing overexpression of IL-6. In the study, the level of CREB1, COX-2, and the PGE2 receptor EP4 were downregulated, which may be a significant trace to a poor reaction in the niacin test [66]. Covault et al. showed that C to T single nucleotide polymorphism in the first intron of the FACL4 gene for long-chain fatty acid-CoA ligase type 4 involved in AA, EPA, and DHA metabolism is associated with a stronger skin reaction in the niacin test in SCH patients and in the control group. In addition, a significant excess of the T allele was observed in individuals suffering from major depression compared with controls (49% vs. 38%; p = 0.003) and a non-significant excess of the T allele was observed in SCH patients (44%; p = 0.29). Moreover, male SCH patients with the T0 genotype showed similar erythema to males from the control group with C0 genotype but reduced when compared with the control group with T0 genotype [67]. A study by Chang et al. that compared the skin reaction to the niacin flush test in families with only one person diagnosed with schizophrenia and those with a pair of affected siblings showed more impaired niacin flushing in SCH patients and relatives from families with higher genetic loading [65]. A study by Nadalin et al. focused on the etiology of poor response to the NSFT in patients with SCH based on the two functional A/G polymorphisms of the PLA2G4A and PTGS2 genes and the content of fatty acids in red blood cells. Both polymorphisms had a statistically significant impact on the NSFT results showing G alleles responsible for more intense niacin reactions. Additionally, PUFA values were significantly reduced in patients. However, their association with niacin sensitivity was not detected by the test methodology used by the researchers [68]. Furthermore, Nadalin et al. tested polymorphic variants for the PLA2G6 and PLA2G4C genes, which encode calcium-independent phospholipase A2 beta (iPLA2β) and cytosolic phospholipase A2 gamma (cPLA2γ) enzymes that mediate phospholipid remodeling and replenish the AA reservoir for prostaglandin synthesis. Nevertheless, this study did not demonstrate an influence of genetic polymorphisms on the NSFT results [69]. Studied factors that could potentially affect the results of the NSFT are presented in Figure 4. Adaptation of staging in psychiatry raises hopes for the treatment of the disease’s initial phase, which implies greater efficiency, safety, and precision and entails lower economic, social, and emotional burdens for the patient [70]. As the first episode of SCH appears most frequently in late adolescence or early adulthood, and prodromal symptoms occur from 3 to 5 years before the full outbreak of the disease, precise staging seems to be the key to the prevention and early intervention of vulnerable individuals [71]. Over the years, concepts for the course of SCH have been put forward, beginning with Fava and Kellner in 1993, then the Mark Agius model, which then led to an even more extensive concept by McFarlane et al. [72,73,74]. So far, the most comprehensive clinical staging model framework for psychotic and severe mood disorders was developed by McGorry et al. The model specifies the characteristics of the disorder clinical picture, a proposal for an appropriate intervention at a given stage, and distinguishes specific biological markers. Interestingly, in the early stages, it proposes a simple, non-invasive NSFT as a potential test to estimate the risk of psychosis [75]. At this point, returning to the assumptions of David Horrobin, who called SCH a prostaglandin deficiency disease, one should focus on the significance of AA, which forms the basis of the skin reaction in the NSFT [35]. Since Horrobin suggested the NSFT as a screening for SCH, there have been attempts to adapt the test to artificial intelligence technology that could be widely available. Such activities create the concept of individualized medicine and allow for a holistic approach to the patient’s difficulties, giving hope for simple solutions such as modification of the diet and lifestyle [76]. It has long been known that dietary interventions have the potential to improve both the physical and mental health of an individual. Unfortunately, prioritizing such recommendations in daily practice is extremely rare, and nutritional psychiatry is just beginning to show how food choices can affect SCH spectrum disorders [77]. Even if there are currently limited nutritional guidelines for mental health issues, the World Federation of Societies of Biological Psychiatry (WFSBP) and the Canadian Network for Mood and Anxiety Disorders (CANMAT) contributed to the creation of clinician guidelines for the treatment of psychiatric disorders with nutraceuticals and phytoceuticals. They emphasize the preventive role of omega-3 fatty acids in the transition to psychosis in high-risk youth with pre-existing fatty acid deficiency [78]. As polyunsaturated fatty acids (PUFAs) are the major constituents of neuronal membranes, their meaning in mental disorders is crucial [79]. Almost 100 years ago, Burr and Burr discovered the importance of linoleic (LA) and alpha-linolenic acid (ALA) and created the term “essential fatty acids”, since they must be supplied to the organism along with the diet [80]. A substantial point of PUFA metabolism is that n-3 and n-6 PUFAs compete for the same delta-6-desaturase enzyme. Hence, the basis of their optimal transformation is the proportion in which they are delivered [81]. Industrialization resulting in dynamic changes in diet is undoubtedly a new phenomenon in the history of mankind. It has led, among other things, to an increase in the consumption of saturated fat, omega-6 fatty acids, and trans-fatty acids, decreasing omega-3 fatty acids intake. Additionally, trans-fatty acids interferes with the desaturation and elongation of omega-6 and omega-3 acids, which leads to a reduction in the availability of AA in human metabolism [82,83]. The ratio of omega-6 and omega-3 fatty acids in a Western diet, poor in omega-3, fluctuates within 15–20: 1 instead of 1:1 to 4:1 [84,85]. It has been proven that a significantly increased omega-6 to omega-3 ratio is associated with the occurrence of various chronic diseases including inflammatory bowel disease, cardiovascular disease, rheumatoid arthritis, and mental disorders [86]. Additionally, in the aspect of eating habits, there are systematic review reports on the dietary patterns of individuals suffering from psychotic disorders that are worth paying attention to [87]. Based on discussed articles some eating habits of patients are presented in Figure 5. There is much promising evidence for the pivotal meaning of PUFA in terms of dietary research on mental disorders. Robinson et al. report that omega-3 supplementation has the potential to relieve depression and anxiety symptoms in subjects who have recently experienced psychosis [88]. Jones et al. also reported protective effects of long-chain omega-3 and omega-6 fatty acids in SCH. It has been suggested, however, that individuals suffering from SCH may have a disturbed mechanism for converting short-chain to long-chain PUFAs [89]. Moreover, some speculate that PUFA biomarkers may be useful in identifying individuals with deteriorating neurocognitive functioning, which entails a worse prognosis. The basis for this statement is the results of the study conducted by McLaverty et al., who emphasize the importance of PUFAs, especially in terms of verbal fluency in the UHR population [90]. Interesting results regarding PUFA supplementation are presented by Hsu et al. who claim that supplementation with omega-3 acids reduces the conversion rate to psychosis and has a positive effect on both positive and negative symptoms as well as global functioning in the case of UHR adolescents [91]. Moreover, it appears that omega-3 fatty acids have a biological effect similar to antipsychotic drugs, with the advantage that they have no side effects and favorably affect the metabolic state of a patient. Otherwise, they prove to be effective even before the first symptoms of SCH appear, where antipsychotics are not applicable. Notwithstanding the low cost of supplementation has its strengths, but it is possible that in terms of personalized medicine, only selected subjects will be able to benefit from it [92]. Some authors report that omega-3 supplementation is most effective in patients in the prodromal phase or early onset stages, which, concerning niacin screening trials, gives hope for faster treatment [93]. There is also evidence that the prompt identification of patients with omega-3 fatty acid shortage is essential to obtain the maximum benefit from such an intervention [94]. Nevertheless, in opposition to these observations, some studies report that decreased levels of essential fatty acids among patients with schizophrenia may be related not to the disease itself but to other independent factors, such as cigarette smoking status [95]. There is an urgent need to improve NSFT as a simple, non-invasive, reproducible, cheap method that can be of potential importance in the following areas: Creating a new classification and diagnosis of mental disorders, especially psychosis, based on pathophysiological premises. Searching for new therapeutic options and drugs based on the mechanisms of NSFT action. Early intervention and staging in psychiatry. Defining an individualized diet for patients, which may be a factor in alleviating symptoms and perhaps even leading to remission and its maintenance. Considering the above, there is an opportunity to improve diagnostics, which can contribute to reducing the individual, social, and economic burden of a debilitating disease, and starting treatment on time would prevent its unnoticed, insidious, and destructive course. More scholars should consider studies investigating the niacin skin flush test outcomes connected with physiological indicators such as EEG and near-infrared techniques as well as various biological markers. The specificity of NSFT should be explored from multiple dimensions to provide more conclusive evidence of its clinical application.

PMC10003236

Kimyeong Kim,Haejin Yoon

Gamma-Aminobutyric Acid Signaling in Damage Response, Metabolism, and Disease

26-02-2023

gamma-aminobutyric acid,metabolite,neurotransmitter,liver disease,cancer

Gamma-aminobutyric acid (GABA) plays a crucial role in signal transduction and can function as a neurotransmitter. Although many studies have been conducted on GABA in brain biology, the cellular function and physiological relevance of GABA in other metabolic organs remain unclear. Here, we will discuss recent advances in understanding GABA metabolism with a focus on its biosynthesis and cellular functions in other organs. The mechanisms of GABA in liver biology and disease have revealed new ways to link the biosynthesis of GABA to its cellular function. By reviewing what is known about the distinct effects of GABA and GABA-mediated metabolites in physiological pathways, we provide a framework for understanding newly identified targets regulating the damage response, with implications for ameliorating metabolic diseases. With this review, we suggest that further research is necessary to develop GABA’s beneficial and toxic effects on metabolic disease progression.

Gamma-Aminobutyric Acid Signaling in Damage Response, Metabolism, and Disease Gamma-aminobutyric acid (GABA) plays a crucial role in signal transduction and can function as a neurotransmitter. Although many studies have been conducted on GABA in brain biology, the cellular function and physiological relevance of GABA in other metabolic organs remain unclear. Here, we will discuss recent advances in understanding GABA metabolism with a focus on its biosynthesis and cellular functions in other organs. The mechanisms of GABA in liver biology and disease have revealed new ways to link the biosynthesis of GABA to its cellular function. By reviewing what is known about the distinct effects of GABA and GABA-mediated metabolites in physiological pathways, we provide a framework for understanding newly identified targets regulating the damage response, with implications for ameliorating metabolic diseases. With this review, we suggest that further research is necessary to develop GABA’s beneficial and toxic effects on metabolic disease progression. Metabolites are mainly used as energy sources and cellular building blocks. Sometimes, they are directly involved in signaling pathways. Gamma-aminobutyric acid (GABA) is a key signaling molecule and neurotransmitter in the brain system [1]. Since GABA affects neuronal activity, GABA-transaminase (GABA-T) inhibitors and GABA agonists have been used to treat brain diseases. GABA levels have been linked to metabolic organs and the progression of metabolic diseases. GABA plays important roles not only in the brain but also in different metabolic organs. We will focus on its roles in metabolic organs to understand the mechanisms associated with GABA signaling and dysfunction in metabolic diseases caused by excessive lipid accumulation. The harmful effects of lipid overload can lead to replication stress, consequently causing DNA damage in the liver [2], which is directly regulated by GABA metabolism. Cellular levels of GABA regulate ion-dependent transporters in the liver [3]. GABA receptors (GABARs) co-ordinate hepatocyte depolarization and hyperpolarization with lipid accumulation in metabolic disorders, including hyperinsulinemia and insulin resistance. The toxic effect of hepatic GABA can improve insulin resistance by inhibiting skeletal muscle glucose clearance. GABA released from island β cells can act on α cells and β cells through the paracrine and autocrine pathways. GABA stimulation can affect β-cell membrane depolarization and activate the PI3K/Akt signaling pathways [4], thus playing an important role in cellular growth and differentiation. It is important to understand the hepatic GABA function and the action of GABARs in various disease conditions. GABA is generated from glutamate through glutamate decarboxylase (GAD) enzymes, which are expressed differently in various organs, leading to the following new questions: (1) How does GABA have beneficial or toxic effects in different metabolic organs? (2) What is the upstream regulator that modulates GABA function? and (3) How do intracellular GABA intermediates directly contribute to cellular dysfunction? In this review, we will highlight the emerging role of GABA in various metabolic organs and its beneficial and toxic effects on disease progression. Among metabolites, GABA is known as a signaling molecule. GABA is an inhibitory neurotransmitter by regulating ionic channel inflow and outflow. Both glutamate and GABA are key neurotransmitters in the brain, including the overall level of excitement in the brain. The levels of these metabolites are important for maintaining physiological homeostasis. Since long-term imbalances in these metabolites can lead to brain diseases [5], an understanding of the regulation of GABA uptake is necessary. The GABA-A receptor is a quintessential ligand-gated ion channel that mediates synaptic inhibition throughout the central nervous system [6]. After GABA performs its action as a neurotransmitter, it is reabsorbed into the presynaptic neurons and neural bridges [7]. Since a GABA-T inhibitor causes GABA accumulation in the brain by increasing extracellular GABA concentrations and inhibiting neuronal activity [8], many research studies have been conducted to investigate the control of GABA and glutamate in neurons. GABAergic, a neuron which produces GABA, and glutamate neurons play an important role in the activity of gonadotropin-releasing hormone (GnRH) neurons by maintaining stable rates of glutamate receptor synaptic transfer to ionic GABA and GnRH neurons in various estrogen feedback situations [9]. Glutamate and GABA were shown to depolarize cells in the ventricular region of the mouse embryo neocortex in the early stages of cortical neurogenesis. Glutamate can selectively interact with α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) and kainate-type glutamate receptors (AMPARs and KARs) and bind to GABA-B receptors. GABA and glutamate can increase the concentration of Ca2+ in ventricular zone cells but decrease DNA synthesis by activating voltage-gated Ca2+ channels. GABA and glutamate can boost DNA synthesis during treatment with GABA-A and AMPA/Kainate receptor antagonists [10] (Figure 1). Therefore, it is important to understand how GABA regulates the levels of ions with receptors and the mechanism of signal transmission. Three types of GABARs have been identified: A, B, and C. Types A and C are ligand Cl− inflow channels. Type B activates potassium outflow channels through G-protein signaling to induce hyperpolarization. Tension inhibition mediated by the GABA-A receptor can decisively regulate neuronal excitability and brain function [11]. GABA-A is required to trigger the Ca2+ response. For example, GABA was shown to activate ionic GABARs to stimulate cerebrovascular angiogenesis and promote neurovascular binding in cerebrovascular endothelial cells [12]. The mechanism of GABA is that the GABARs-dependent Ca2+ response leads to promoting cerebrovascular angiogenesis and inducing neurovascular binding for activating brain function. Signaling cascades consisting of GABA-B receptor G protein and G-protein-gated K+ channel (GIRK), which induce hyperpolarization by increasing potassium outflow, can inhibit the nervous system in the brain and the expression of GABA-B receptor can accelerate GIRK activation. GABA-B receptors also affect the fundamental activity of K channels [13]. Moreover, GABA-B receptor signaling is involved in the regulation of binge eating [14]. The activity of the GABA-B receptor mitigates binge eating by inducing hyperpolarization with K+ outflow. The GABA-B receptor, which can be proposed as a potential treatment target for Alzheimer’s disease (AD), inhibited oxidative stress damage in the neurons of AD model rats by activating the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway [15] (Figure 1). BHF177, a positive allosteric modulator of the GABA-B receptor, can activate GABA-B receptors to induce the expression of insulin receptor substrate 1 (IRS-1), PI3K, and anti-apoptotic factors (including Bcl-2 and mTOR); inhibit apoptotic factors, including BCL2 Associated X (Bax), which is known as an apoptosis regulator by releasing cytochrom C in the inner membrane of mitochondria, in hippocampal tissues; and protect against refractory epilepsy (RE) via IRS-1/PI3K [16]. Studying diverse mechanisms involving GABA, especially in the context of neurotransmitters, offers an entry point for understanding the metabolite-mediated signaling cascade in the brain. GABA exerts different cellular effects and plays an important role in many cells in many organ systems. Impairments in GABA signaling have significant consequences in a range of human physiological processes and diseases. This includes acting as a signaling molecule in the liver. The activation of GABA signaling can protect the liver from D-galactosamine damage by reducing toxic damage in hepatocytes and reducing the proliferation of bile duct cells [17]. GABA not only decreased liver damage caused by a toxic reagent but also reduced liver ischemia and reperfusion injury by modulating the hepatic insulin signaling and gluconeogenesis pathways [18] (Figure 2). GABA improved insulin resistance through glucose transporter 4 (GLUT4) and reduced the glucagon receptor gene expression to inhibit gluconeogenesis [19]. Moreover, pre-emptive treatment with GABA was shown to protect against severe acute liver damage in mice through anti-apoptosis co-ordinating with the STAT3 pathway [20]. GABA supplementation increased the mRNA expression levels of peroxisome proliferator-activated receptor γ (PPARγ) and GABARs and reduced the expression of toll-like receptor 4 (TLR4)/nuclear factor-κB (NF-B) signaling [21], thus protecting the liver from damage. Among the metabolic pathways, the GABA transporter is associated with lipid metabolism. An intracellular accumulation of DAG due to excessive fatty acid inflow into the liver can result in the activation of protein kinase C (PKC). PKC increases insulin resistance by inhibiting the phosphorylation of IRS-1. An excess of FFA through the activation of inflammatory TLRs can inhibit the phosphorylation of Akt, leading to ceramide synthesis and ceramide accumulation [22]. The accumulation of specific lipids, including DAG and ceramides, impairs hepatic insulin signaling, leading to a pathological increase in hepatic glucose production. The hepatocyte membrane potential regulates serum insulin and insulin sensitivity. Given the role of the membrane potential in regulating media GABA concentrations, GABA import and export are mediated by ion-dependent transporters in the liver. For example, hepatic vagal nerve activity is inhibited by GABA-A receptor stimulation. Hepatocyte depolarization causes hyperinsulinemia and insulin resistance by reducing hepatic vagal afferent nerve (HVAN) activity and increasing GABA outflow from the liver. Interestingly, the GABA release concentration in obese mice is about 180 μmol/mg, while the GABA release concentration in lean mice is about 100 μmol/mg. The different GABA concentration is due to hepatic depolarization in obese mice. The betaine/GABA transporter (BGT-1/GAT2) primarily acts as a GABA reuptake transporter by inducing hepatic hyperpolarization, which limits GABA signaling to the HVAN and promotes metabolic dysfunction. Studies on GABA transporters could provide additional insight into the mechanisms responsible for preserving metabolic health in people with type 2 diabetes [23] (Figure 2). The GABA shunt classically refers to a tricarboxylic acid (TCA) cycle detour that converts α-ketoglutarate (α-KG) to succinate and concomitantly breaks down a molecule of GABA through GABA-T (Figure 3). However, in the liver, GABA-T mediates GABA synthesis. Hepatic lipids can activate reversed GABA shunt activity in hepatocytes. Increased GABA-T activity, together with the production of GABA, produces α-KG, leading to gluconeogenesis. GABA-T knockdown in obese mice had no effect on body weight. However, it led to decreases in basal serum insulin and glucose concentrations. The inhibition of hepatic GABA production improves insulin sensitivity primarily by increasing the skeletal muscle glucose clearance, which directly affects blood flow. Thus, GABA-T represents a promising target for decreasing hyperinsulinemia and insulin resistance by limiting hepatic GABA production [24], highlighting the importance of understanding hepatic GABA function and the action of GABARs in various disease conditions. We will discuss how GABA metabolism is involved in liver diseases. Non-alcoholic fatty liver disease (NAFLD) is currently the most common liver disease worldwide. It can advance to hepatic steatosis, a consequence of lipid acquisition exceeding lipid disposal [25]. Increased glucose can further induce the development of NAFLD by activating transcription factors, including ChREBP and PPAR gamma coactivator 1-b (PPARGC1B), to activate fat production by the liver. The symptoms of NAFLD include deficiencies in lipolysis in the liver (decreased ATGL/CGL-58 activity), deficiencies in triglyceride (TG) export, and an increase in de novo lipogenesis [26]. In simple steatosis, the storage of lipid-droplet-binding TGs is physiologically inactive. However, these lipid complexes are related to hepatocellular damage and apoptosis in non-alcoholic steatohepatitis (NASH). Interestingly, a Western diet challenge was shown to increase triacylglycerol concentrations and induce the mRNA expression levels of macrophage-1 antigen, a cluster of differentiation (CD) 45, CD68, and NF-κB in the liver, promoting the development of hepatic inflammation [27]. Iron overload in the liver is also known to be involved in the pathogenesis of NASH through oxidative stress. High-fat diets (HFDs) were reported to increase iron concentrations in the livers of experimental animals with steatohepatitis [28] (Figure 3). We will focus on the symptoms of NAFLD and how GABA signaling affects NAFLD progression. Dysfunction in lipid metabolism can lead to NAFLD. An increase in fatty acid oxidation (FAO) has been suggested as a treatment for NAFLD. FAO is controlled by PPARα and occurs mainly in the mitochondria, providing a source of energy to generate ATP in low glucose conditions. In mammalian cells, the mitochondria, peroxisomes, and cytochromes mediate FAO. The entry of fatty acids into the mitochondria relies on carnitine palmitoyltransferase 1 (CPT1) situated in the outer mitochondrial membrane. However, since mitochondria lack the ability to oxidize very long-chain fatty acids (VLCFAs), these are preferably metabolized through peroxisomal β-oxidation [25]. Increased growth/differentiation factor-15 (GDF-15) in the liver decreased lipid accumulation and NALFD development in obese mice by increasing FAO in the liver [29]. Moreover, for lipid metabolism, many transcription factors and metabolic signaling are involved in liver diseases. Fibroblast growth factor-21 (FGF21) is a circulating hepatokine that beneficially affects carbohydrate and lipid metabolism and is an autocrine factor induced in adipose tissues. It functions in feed-forward loops to regulate the activity of PPAR, a key transcription regulator of fat production [30]. Moreover, the energy sensor AMP-activated protein kinase (AMPK) plays an essential role in the homeostatic regulation of liver lipids. Activated AMPK signaling pathways were shown to increase FAO and reduce lipid synthesis hepatocytes, thereby ameliorating liver steatosis [31] (Figure 3). Lipid metabolism is linked to oxidative stress. Oxidative stress is defined as an imbalance between oxidants and antioxidants in favor of the former, resulting in an overall increase in the cellular levels of reactive oxygen species (ROS) [32]. Nuclear factor-erythroid-2-related factor 2 (Nrf2), a transcription factor that activates antioxidant response elements (AREs), plays a central role in stimulating the expression of various antioxidant-associated genes in cellular defenses against oxidative stress [33]. This oxidative stress is a key mechanism of hepatocyte injury and disease progression in patients with NASH. Transcription factor Nrf2 plays a central role in stimulating the expression of various antioxidant-related genes in cellular defenses against oxidative stress (Keap1), which directly activates Nrf2 [34]. Inhibiting mitochondrial oxidative damage was shown to prevent metabolic stress-induced NAFLD in mice [35]. Interestingly, GABA inhibits H2O2 and ROS formation through p65 signaling and regulates Keap1-Nrf2 signaling to repress oxidative stress. Moreover, GABA protected human umbilical vein endothelial cell (HUVEC) injury from H2O2-driven oxidative damage by inhibiting caspase 3-dependent apoptosis [36]. In addition, GABA has another mechanism to maintain the cellular redox status by modulating glycogen synthase kinase (GSK)-3β and the antioxidant-related Nrf2 nuclear mass ratio. Therefore, GABA may have potential as a pharmacological formulation in the prevention or treatment of cardiovascular diseases associated with oxidative damage [37]. The expansion of peripheral adipose deposits provides buffering capacity, which protects the liver from excessive FFA flux that can promote hepatic lipid accumulation. Within hepatocytes, long-chain fatty acids (LCFAs) are esterified with glycerol-3-phosphate (derived from glycolysis) to form mono-acylglycerols, diacylglycerols (DAG), and TG [38]. The production of DAG has been implicated as a cause of hepatic insulin resistance. The conversion of TG to DAG is mediated by adipose triglyceride lipase (ATGL) [39]. Non-esterified hepatic lipids can induce endoplasmic reticulum (ER) stress, leading to the activation of c-Jun N-terminal kinases and NF-κB, two major regulators of inflammatory pathways aggravating hepatic insulin resistance and increasing intrahepatic cytokine production [40]. Deregulated NF-κB activation had a notable effect on the development of hepatic steatosis, insulin resistance, inflammation, fibrosis, and cancer [2]. HFD increased NF-kB activation in mice, which is directly related to chronic inflammation in the liver and fat, hepatic steatosis, and whole-body insulin resistance [41]. Interestingly, GABA regulates inflammation by macrophage cell fate. GABA inhibits interleukin (IL)-1β production by inflammatory macrophages during macrophage maturation. This is due to GABA-dependent mitochondrial protein succinylation, suggesting GABA treatment as a new therapeutic strategy for macrophage-related inflammatory diseases [42]. GABA protected lipopolysaccharide (LPS)-induced inflammation in bovine mammary epithelial cells (MAC-T cell line), by reducing TLR4, NF-κB p65, and MyD88 mRNA expression [43]. However, the physiological significance of the effect of GABA on inflammation remains an open question and the subject of active investigations. The ER is a major site of lipid synthesis in hepatocytes, and ER homeostasis in the liver is important for maintaining membrane lipid composition and controlling both intrahepatic and plasma lipid homeostasis. Since the accumulation of ectopic TG in hepatocytes leads to steatosis, it is important to understand ER-dependent lipid homeostasis in the liver in the first stage of NAFLD. Chronic ER stress, which is another important ER function regulating protein homeostasis, directly affects liver lipid metabolism by inducing de novo lipogenesis, and ER stress is indirectly involved in very-low-density lipoprotein (VLDL) secretion, insulin signaling, and autophagy. Conversely, increasing the hepatocellular lipid content causes chronic ER stress [44]. One of the representative symptoms of ER stress is insulin resistance. An imbalance in lipid contents, such as the activation of TG-levels-induced ER stress, influences insulin resistance [45]. Moreover, ER stress can cause hepatic insulin resistance by increasing de novo lipogenesis and directly interfering with insulin signaling by activating the c-Jun N-terminal kinase (JNK) and IκB kinase (IKK) pathways [46]. ER stress is also regulated by the metabolic signaling pathways. AMPK was shown to enhance insulin sensitivity either by directly regulating PI3K or by suppressing the negative feedback loop of IRS1 regulation by inhibiting mTOR/S6K [47]. AMPK enhances glucose transporter GLUT4 regulation, which is a key regulator of insulin resistance [48], since tumor necrosis factor-α (TNF-α) plays a critical role in the development of NAFLD and progression to NASH by upregulating key molecules associated with lipid metabolism, inflammatory cytokines, and fibrosis in the liver [49]. This TNF-α induction leads to the PP2C-mediated inactivation of AMPK, which increases the fatty acid levels and, potentially, insulin resistance [50]. AMPK also regulates fatty acid synthesis and plays a potential role in hepatic steatosis [51]. Therefore, AMPK may serve as a promising therapeutic target by reducing ER stress [52]. Ferroptosis is a novel form of programmed cell death caused by iron-dependent lipid peroxidation. Iron overload caused by metabolic dysfunction can aggravate liver damage in NASH patients [53]. Abnormal iron metabolism, lipid peroxidation, and the accumulation of polyunsaturated fatty acid phospholipids trigger ferroptosis, suggesting ferroptosis as a new strategy for the treatment of liver disease. Emerging evidence indicates that ferroptosis plays a critical role in the pathological progression of NAFLD. Hepatocyte ferroptosis precedes cell apoptosis, which, in turn, leads to liver damage, immune-cell infiltration, and inflammation [54]. Ferroptosis is also associated with ER stress, a cellular state accompanied by the accumulation of unfolded or misfolded proteins [55]. The unfolded protein response is also involved in the regulation of DNA-damage-induced ferroptosis. The loss of E3 ubiquitin-protein ligase ring finger protein 113A (RNF113A) was shown to trigger DNA-damage-related ferroptosis [56]. Glutathione peroxidase 4 (GPX4) is known as an inhibitor of ferroptosis, and GPX4 is highly expressed in the liver. GPX4 protects the liver from lipid peroxidation, performing an essential role in liver function and liver cell survival [57]. Recent studies showed that ferroptosis genes are involved in GABA. We previously mentioned that GABA regulates the Keap1-Nrf2 and Notch signaling pathways [36]. Nrf2-related anti-oxidative stress is strongly associated with ferroptosis suppression. Nrf2 silencing dramatically reduced cystine/glutamate transporter (SLC7A11) levels [58]. The SLC7A11/GPX4 pathway functions as a canonical defense against ferroptosis by assisting intracellular glutathione (GSH) synthesis and alleviating lipid peroxidation [59]. Moreover, the GABA-B receptor agonist Taurine reduced ferroptosis and alleviated oxidative stress by regulating the GABA-B/AKT/GSK3/β-catenin signaling pathway. Therefore, clinical studies aimed at activating GABA function may offer new opportunities for treating ferroptosis-mediated liver disease. Hepatocytes in NAFLD display the hallmarks of replication stress, including a slow replication fork progression and the activation of an S-phase checkpoint (ATR signaling). Replication-associated DNA lesions accumulate in NAFLD hepatocytes. Patients with NASH reportedly have higher levels of oxidative DNA damage in the liver than patients with other liver diseases [60]. The nucleotide pool imbalance occurring during NAFLD is a key driver of replication stress. Proliferating mouse NAFLD hepatocytes exhibited replication stress with alterations in the replication fork speed and activation of the ATR pathway, which is sufficient for DNA breaks [61]. Lipid overload in proliferating human hepatocytes can lead to replication stress, consequently causing DNA damage. Hepatocyte DNA damage through lipid oxidative stress activates cGAS-STING signaling and leads to the development of sterile inflammation, which drives the pathological process of NAFLD. Injury-induced hepatocyte necrosis or apoptosis can result in the release of nuclear DNA or mtDNA, which can behave as damage-associated molecular proteins (DAMPs) to trigger innate immune responses, giving rise to a sterile inflammation in the liver [62]. Therefore, GABA represents a promising target for decreasing oxidative stress and DNA damage. ROS-driven DNA damage is a by-product of metabolism in hepatocytes, and DNA damage was increased in NAFLD as a consequence of elevated mitochondrial FAO and inadequate mitochondrial respiratory chain activity [63]. Impairment of mitochondria oxidation leads to active fatty acid metabolism [64]. These studies suggest that the regulation of both GABA and fat metabolism is important in liver disease (Figure 3). Future clinical studies aimed at activating GABA function might reveal an attractive therapeutic strategy for DNA-damage-driven NAFLD. Patients with NAFLD are exposed to the risk of HCC. The prevalence of NAFLD-related HCC is rising worldwide [65]. NASH patients have much higher risks of HCC compared to patients with simple hepatic steatosis. HCC is associated not only with NAFLD but also with NAFLD-related metabolic diseases, including obesity and diabetes [66]. For example, PI3K signaling, which regulates metabolism, cell growth, and cell survival, is activated by insulin [67]. PI3K transgenic mice developed steatosis, steatohepatitis, and liver cancer [68]. AKT is downstream of the PI3Ks and is, thus, a major effector of insulin signaling. AKT activation promotes hepatic lipogenesis and modifies the activity of a multitude of downstream targets through phosphorylation. AKT activation led to fatty liver disease and hypertriglyceridemia, whereas AKT inhibition protected against hepatic steatosis [69]. AKT signaling is controlled by phosphatase and tensin homolog (PTEN). PTEN dephosphorylates the lipid second messenger, phosphatidylinositol 3,4,5-trisphosphate (PIP3), a direct product of PI3K. Thus, PTEN is an important negative modulator of the insulin-signaling pathway by antagonizing PI3K–AKT signaling [70]. PTEN loss-of-function mutations, PTEN deletion, or low PTEN expression enhanced insulin sensitivity and promoted hepatic steatosis, steatohepatitis, fibrosis, and liver cancer [71,72,73]. Notably, the combination of oxidative damage and the proliferative response seems to promote carcinogenesis. During early liver cancer development in mouse NAFLD models, oncogene activation led to DNA damage and chromosomal instability [74]. DNA damage due to oxidative stress leads NASH into hepatocellular carcinoma. GABA may perform ROS scavenging and induce Nrf2 activity in liver cancer to reduce oxidative stress. Interestingly, GABA is known to activate PI3K/AKT signaling in the liver. Whereas GABA has beneficial effects on liver biology, GABA-dependent AKT signaling leads to liver cancer. Questions remain regarding the extent to which modulating GABA in the liver can confer a therapeutic benefit. We can suggest that symptoms should be alleviated from NASH to NAFLD through the activity of GABA and FAO before hepatocellular carcinoma deterioration in NASH (Figure 3). GABA is a non-proteinogenic amino acid and neurotransmitter that is produced in the islets at levels as high as in the brain. GABA is synthesized by glutamic acid decarboxylase (GAD) [75]. GABA is a product of glutamate. Its metabolism involves the TCA cycle in the pancreatic islets and depends mainly on three enzymes: the synthetic enzyme GAD, the catabolic enzyme GABA transaminase (GABA-T), and succinic semialdehyde dehydrogenase (SSADH). Glucose and glutamine are the most important sources providing glutamate, the substrate for GAD. Subsequently, GAD decomposes glutamic acid to form GABA. GABA is degraded to succinate by GABA-T and SSADH in two steps. The first catabolic step involves the transfer of GABA to α-KG by transamination, which results in the formation of succinic semialdehyde and glutamate. In the second step, succinic semialdehyde is oxidized to succinate with the reduction of nicotinamide adenine dinucleotide (NAD) to NADH. β cells release GABA through a synaptic-like microvesicle (SLMV)-mediated mechanism, which is Ca2+-dependent exocytosis, during membrane depolarization [76]. In human β cells, GABA was shown to exert stimulatory effects on proliferation with anti-apoptotic effects [77]. GABA released from islet β cells can act on α and β cells through the paracrine and autocrine pathways. β-cell membrane depolarization through GABA stimulation and VDCC-induced Ca2+ influx activated the PI3K/Akt signaling pathway [76]. PI3K/Akt acts as a downstream mediator of the insulin receptor-2 signaling cascade and plays a vital role in protecting β cells from apoptosis while inducing their growth and differentiation [78] (Figure 2). Adipose tissues play a key role in the modulation of systemic energy homeostasis in response to physiological stimuli. In obese visceral adipose tissues, increases in the proinflammatory response are positively associated with insulin resistance (Figure 2). Adipose tissue inflammation is a key mediator linking obesity to metabolic complications. GABA was reported to reduce obesity-induced adipose tissue macrophage (ATM) infiltration in subcutaneous inguinal adipose tissue (IAT). GABA also ameliorated systemic insulin resistance in HFD-fed mice and concurrently enhanced the insulin-dependent glucose uptake in IAT [79]. Skeletal muscle is the main metabolic organ consuming ingested glucose in lean individuals with a normal glucose tolerance. Damage to skeletal muscle endothelium following intracellular cascade defects in obese patients led to insulin resistance in this tissue [80]. GABA-A receptor activation modulated skeletal muscle function through muscle sympathetic nerve activity [81] (Figure 2). Further studies on GABA in peripheral tissues may provide an important target for therapeutic intervention for tissue damage. The various functions of GABA may illuminate new targets for the treatment of metabolic diseases. Since it is important to regulate the action of GABA and GABARs in brain biology, some drugs can inhibit GABA as well as modulate GABARs. With the GABA mechanism, clinical trials are commonly used in brain disease. GABA receptor agonist drugs have been used for anesthesia, anxiety, and insomnia. Abecarnil is a partial agonist, acting selectively at the benzodiazepine site of the GABA-A receptor [82]. Barbiturates are a class of depressant drugs chemically derived from barbituric acid [83]. Muscimol binds to the same site on the GABA-A complex as GABA itself, unlike other GABAergic drugs, such as barbiturates and benzodiazepines, which bind to separate regulatory sites [84]. Propofol is the drug used almost exclusively to induce general anesthesia, and has largely replaced sodium thiopental [85]. Moreover, zolpidem regulates GABA-A, suggesting zolpidem treatment may be a new strategy to control motor symptoms in Parkinson’s disease [86]. GABA receptor antagonists produce stimulant and convulsant effects and are mainly used for counteracting the overdoses of sedative drugs. Clozapine is a tricyclic dibenzodiazepine, classified as an atypical antipsychotic agent [87]. Bicuculline is a phthalide-isoquinoline compound and a light-sensitive competitive antagonist of GABA-A receptors [88]. These clinical shreds of evidence suggest that GABA-A receptor agonists and antagonists may be used in different metabolic disorders including liver disease. As with GABA-A receptors, there are drugs that identify a GABA-B receptor agonist. Lesogaberan (AZD3355) was developed for the treatment of gastroesophageal reflux disease (GERD) [89]. Recently, AZD3355 has been used for the treatment of NASH as a GABA-B agonist [90]. A compelling future direction for the field of GABA biology and metabolism will be the repositioning of GABA target drugs for metabolic disorders. While these clinical trials were developed by the mechanism of GABA in physiology, studies to validate the clinical trial drugs for their repositioning in different cell systems and in vitro for another mechanism would be important for understanding the GABA function. This challenge suggests we should bridge the gaps between the in vitro, animal, and clinical studies of GABA. GABA biosynthesis is tightly linked to nitrogen metabolism (Figure 4). Glutaminase can catalyze the hydrolysis of the amide group of glutamine to form glutamate and ammonia [91]. Glutamine synthase (GS) catalyzes the reverse reaction, an ATP-dependent reaction responsible for the formation of glutamine from glutamic acid and ammonia. GS is a key enzyme in the glutamic acid–glutamine cycle. It plays a major role in the brain homeostasis of glutamic acid, glutamine, and ammonia. GABA is synthesized by the decarboxylation of glutamic acid by GAD [92]. Glutamate required for GABA synthesis is synthesized from two pathways: glutamine and TCA cycle-derived α-KG. Glutamate dehydrogenase (GDH) catalyzes the reaction between glutamate, α-KG, and ammonia using NAD+ or NADP+ as coenzymes [93]. GDH is important in glutamic acid and GABA neurotransmission because it directly regulates glutamic acid concentrations and indirectly regulates GABA levels by changing the availability of precursors. GDH is potentially inhibited by GTP and activated by ADP [94]. GABA decomposition requires the conversion of GABA-T to GABA to succinate semialdehyde (SSA) through an amino group transition with glutamic acid and α-KG, both of which are auxiliary substrates. The glutamine–glutamate/GABA circuit transfers glutamine from astrocytes to neurons and transfers neurotransmitter glutamic acid or GABA from neurons to astrocytes. Much more glutamine is transferred from astrocytes to glutamate than from GABAergic neurons [95]. Glutamate is a metabolic precursor of glyceraldehyde 3-phosphate through glyceraldehyde 3-phosphate circuits. GABA synthesis is unique among neurotransmitters. Homocarnosine and pyrrolidinone are two distinct isoenzymes of GAD with major effects on GABA metabolism in the human brain [5]. Therefore, the modulation of the GABA biosynthetic and metabolic pathways may offer new opportunities for GABA-linked metabolic disease therapy. In this review, we summarized the diverse roles of GABA in several organs, and its original role as a neurotransmitter. Increasing evidence suggests that GABA has a marked effect on metabolism at the cellular level of several organs, including the pancreas, muscle, fat, and liver, in addition to its role as an inhibitory neurotransmitter, with a major role in regulating various alert states. Current studies showed that GABA works through intercellular actions, such as autocrine and paracrine functions, in peripheral organs. However, the extent of modulating the absolute levels of GABA in the blood and each metabolic organ needed to confer a therapeutic benefit in metabolic disorders remains unclear. The cellular function would be different in many different organs and physiological conditions as well as in vitro systems; therefore, further studies are necessary to define the different GABA effects in in vitro and in vivo systems to understand the limitations of GABA research. Many studies have shown that the biosynthesis of GABA is relevant to important metabolites, including α-KG and glutamate. GABA-T enzymes are generally known to convert α-KG to glutamate and decompose GABA to succinic semialdehyde. However, GABA-T can synthesize GABA in the liver. Lipid accumulation in the liver can induce insulin resistance by activating GABA-T to activate gluconeogenesis through the accumulation of α-KG. The modulation of these key TCA metabolites is important not only for energy metabolism but also for obesity-related diseases. Therefore, whether clinical interventions with GABA transporters and GABA-T might mitigate disease progression, including obesity and insulin resistance, remain to be investigated. Currently, the cellular effects of glutamate and glutamine are well-known. However, the role of intracellular GABA has not been elucidated. Further studies on the intracellular effects of GABA in the liver and other metabolic diseases, as well as the cellular compartmentalization of GABA and other related nitrogen metabolites in liver diseases, are necessary. This approach may provide an opportunity to move beyond the role of GABA as a neurotransmitter.

PMC10003237

Martina Gatti,Katarina Stoklund Dittlau,Francesca Beretti,Laura Yedigaryan,Manuela Zavatti,Pietro Cortelli,Carla Palumbo,Emma Bertucci,Ludo Van Den Bosch,Maurilio Sampaolesi,Tullia Maraldi

Human Neuromuscular Junction on a Chip: Impact of Amniotic Fluid Stem Cell Extracellular Vesicles on Muscle Atrophy and NMJ Integrity

03-03-2023

neuromuscular junction,amniotic fluid stem cells,extracellular vesicles,muscle atrophy,oxidative stress

Neuromuscular junctions (NMJs) are specialized synapses, crucial for the communication between spinal motor neurons (MNs) and skeletal muscle. NMJs become vulnerable in degenerative diseases, such as muscle atrophy, where the crosstalk between the different cell populations fails, and the regenerative ability of the entire tissue is hampered. How skeletal muscle sends retrograde signals to MNs through NMJs represents an intriguing field of research, and the role of oxidative stress and its sources remain poorly understood. Recent works demonstrate the myofiber regeneration potential of stem cells, including amniotic fluid stem cells (AFSC), and secreted extracellular vesicles (EVs) as cell-free therapy. To study NMJ perturbations during muscle atrophy, we generated an MN/myotube co-culture system through XonaTM microfluidic devices, and muscle atrophy was induced in vitro by Dexamethasone (Dexa). After atrophy induction, we treated muscle and MN compartments with AFSC-derived EVs (AFSC-EVs) to investigate their regenerative and anti-oxidative potential in counteracting NMJ alterations. We found that the presence of EVs reduced morphological and functional in vitro defects induced by Dexa. Interestingly, oxidative stress, occurring in atrophic myotubes and thus involving neurites as well, was prevented by EV treatment. Here, we provided and validated a fluidically isolated system represented by microfluidic devices for studying human MN and myotube interactions in healthy and Dexa-induced atrophic conditions—allowing the isolation of subcellular compartments for region-specific analyses—and demonstrated the efficacy of AFSC-EVs in counteracting NMJ perturbations.

Human Neuromuscular Junction on a Chip: Impact of Amniotic Fluid Stem Cell Extracellular Vesicles on Muscle Atrophy and NMJ Integrity Neuromuscular junctions (NMJs) are specialized synapses, crucial for the communication between spinal motor neurons (MNs) and skeletal muscle. NMJs become vulnerable in degenerative diseases, such as muscle atrophy, where the crosstalk between the different cell populations fails, and the regenerative ability of the entire tissue is hampered. How skeletal muscle sends retrograde signals to MNs through NMJs represents an intriguing field of research, and the role of oxidative stress and its sources remain poorly understood. Recent works demonstrate the myofiber regeneration potential of stem cells, including amniotic fluid stem cells (AFSC), and secreted extracellular vesicles (EVs) as cell-free therapy. To study NMJ perturbations during muscle atrophy, we generated an MN/myotube co-culture system through XonaTM microfluidic devices, and muscle atrophy was induced in vitro by Dexamethasone (Dexa). After atrophy induction, we treated muscle and MN compartments with AFSC-derived EVs (AFSC-EVs) to investigate their regenerative and anti-oxidative potential in counteracting NMJ alterations. We found that the presence of EVs reduced morphological and functional in vitro defects induced by Dexa. Interestingly, oxidative stress, occurring in atrophic myotubes and thus involving neurites as well, was prevented by EV treatment. Here, we provided and validated a fluidically isolated system represented by microfluidic devices for studying human MN and myotube interactions in healthy and Dexa-induced atrophic conditions—allowing the isolation of subcellular compartments for region-specific analyses—and demonstrated the efficacy of AFSC-EVs in counteracting NMJ perturbations. Skeletal muscle is a very plastic tissue, but its regenerative potential is hampered during aging [1]. The loss of muscle mass and function associated with muscle-wasting conditions greatly affects the quality of life in elderly populations [2]. Muscle atrophy is characterized by an activation of proteolytic systems that leads to the elimination of contractile proteins and organelles, with loss of skeletal muscle mass, quality, and strength [1,3]. In addition to this, the loss of alpha motor neurons (MNs) and negative alterations of neuromuscular junctions (NMJs) play a key role in musculoskeletal impairment that occurs with aging [4,5]. NMJs are specialized regions where muscle and nerve can communicate—a fundamental connection to govern vital processes, such as breathing and voluntary movements [6]. In physiological conditions, after neuronal loss, denervated orphan muscle fibers, together with some other types of cells, such as terminal Schwann cells, produce chemotactic signals that stimulate the growth of new neurites and, consequently, their re-innervation. These compensatory strategies start failing with aging and the fibers that have not re-innervated become apoptotic, leading to a decline in muscle capabilities [7,8,9]. Moreover, the depletion of adult satellite cells (SCs), the characteristic muscle stem cell compartment, aggravates this dramatic context [10]. This loss in muscle integrity leads to alterations in NMJ morphology that becomes fragmented, and to functional changes in neuromuscular transmission [11]. This initial NMJ change is accompanied by an increase in inflammatory cytokine production and loss of trophic support with consequent neurodegeneration [12]. Furthermore, the age-associated increase in oxidative stress and mitochondrial dysfunction plays a crucial role in NMJ degeneration and muscle atrophy. This oxygen metabolism defect, associated with the reduction in mitochondrial energy production and increase in intracellular calcium, intensifies the pre-synaptic decline and reduces the release of synaptic vesicles. The increase in reactive oxygen species (ROS)—due to mitochondrial dysfunction—in both muscle and neural tissues leads to an accumulation of damaged cell components with alteration in their communication [6,13]. Nevertheless, in this fundamental crosstalk, it has not yet been clarified whether NMJ alteration precedes or follows muscle decline, nor what role oxidative stress components play under such circumstances. Based on these considerations, combining neuro-muscular protection, anti-inflammatory, and antioxidant capabilities may be a promising way to counteract NMJ degeneration. In recent years, mesenchymal stem cells (MSCs), including amniotic fluid stem cells (AFSCs), have been proposed as a potential therapy for human tissue repair and regeneration, given the encouraging evidence in different experimental neuromuscular disease models [14,15]. Moreover, recent studies demonstrated the potential of MSCs, isolated from different tissues (adipose, umbilical cord, and bone marrow), to induce muscle regeneration [16,17,18]. Human amniotic fluid stem cells (hAFSCs) have different advantages, such as their minimal ethical concerns and being easy to obtain from leftover discarded samples of routine prenatal screening amniocentesis (II trimester of gestation). Among the scientific community, it has become increasingly accepted that the therapeutic potential of these cells can be at least in part attributable to bioactive molecules secreted into extracellular vesicles (EVs). Furthermore, EVs have the advantage of being a cell-free therapy candidate, reducing the risks associated with live cell transplantation. In a recent work, Villa et al. demonstrated the human AFSC pro-survival effect on damaged cardiomyocytes, counteracting apoptosis and mitochondrial impairment [19]. Additionally, the neurogenic potential of these cells has been demonstrated by the presence—although in low amounts—of the neural growth factor BDNF in their EVs cargo, suggesting a neurotrophic activity promoting neuronal survival and neurodevelopmental processes [20]. The beneficial potential of MSC transplantation in amyotrophic lateral sclerosis (ALS) mice has been demonstrated by several studies that have shown a reduction in disease phenotype and progression, but above all else, a partial recovery of motor functions [21,22,23]. It is well known that NMJs become vulnerable in degenerative diseases [24], however evidence on the efficacy of MSC-EVs on NMJ complexes is still lacking. Based on that, the present study aims to explore the paracrine antioxidant and neuroprotective effects of human AFSC-EVs against NMJ perturbations in age-related muscle degeneration. The use of innovative commercially available microfluidic devices allowed us to set up an in vitro model of muscle atrophy induced by glucocorticoid supplementation. Muscle atrophy was induced in vitro by myotube exposure to 20µM Dexamethasone for 24 h. Preliminary studies have identified this non-cytotoxic concentration (Supplementary Figure S1A,B) as the one able to induce an atrophic phenotype (Supplementary Figure S1C) in hMAB-myotubes. The analysis of immunofluorescence (IF) images of myotubes—stained with myosin heavy chain (MyHC), a typical marker for mature muscle differentiation—showed a reduction in number of nuclei per myotube, and above all, myotube thickness—the main sign of muscle atrophy—after Dexa treatments, while all these typical differentiation indexes were restored by AFSC-EV treatment, although the fusion index was not fully restored (Figure 1A). Moreover, we did not observe significant alterations in the total nuclei number among the different conditions. In addition, an increased number of MyHC-negative cell nuclei compared to the control one in AFSC-EV-treated samples suggests possible improved preservation of stemness. Increasing evidence links oxidative stress and reactive oxygen species (ROS) to muscle atrophy [25,26]. Therefore, we decided to investigate the ROS content alteration during the early phase of atrophy induction in hMABs (Figure 1B) by DCFH-DA probe. This analysis showed a significant increase in oxidative stress level, prevented by AFSC-EV exposure. Moreover, gene expression analysis confirmed the ability of AFSC-EV treatment in restoring the morphological impairment in our in vitro atrophy model (Figure 1C). Indeed, several muscle-specific genes, such as MyHC1, MyHC3, Pax3, and desmin, redox-sensitive signal pathway genes including the forkhead box class O 3 (FOXO3), main regulator of oxidative stress defenses [27], and autophagy-related genes (LC3β and beclin-1) were dysregulated with Dexa treatment. Notably, EV exposure restored the levels of those genes and the increased expression of both FOXO3 and SIRT1 was accompanied by an upregulation of SOD1, GPX, PDRX3, and TrxR3 antioxidant genes. To generate in vitro functional and morphological mature motor neurons (MNs), we used human-iPSCs differentiated via the 28-day differentiation protocol already published by Guo et al. [28]. The differentiation success was confirmed by gene expression analyses that showed, at day 28, the upregulation of typical pan-neuronal (MAP2 and β-tubulinIII) but also of specific motor neuron (HB9 and Islet-1) markers, and the downregulation of pluripotency markers (NANOG, SOX2), compared to day 10 of differentiation (Supplementary Figure S2A). Additionally, IF images confirmed the positivity of differentiated MNs for synaptophysin (SYPH) and Islet-1 (Isl-1) (Supplementary Figure S2B). Moreover, to be sure that the effect on MNs in co-culture was mediated only by myotubes, we demonstrated that the 20 µM Dexa treatment (24 h) has no effect on motor neuron morphology and differentiation potential (Supplementary Figure S3A), nor does it have a significant impact on the expression of differentiation, redox, and apoptosis marker genes (Supplementary Figure S3B), as demonstrated by immunofluorescence and RT-qPCR analyses. To understand the consequences of muscle atrophy on NMJ integrity, we set up an in vitro model of a motor neuron-myotube co-culture using microfluidic devices (Figure 2). Then, to study the potential of AFSC-EVs in counteracting muscle atrophy injuries, we only treated the muscle compartment with Dexamethasone and examined the modification in myotube and neurite distribution. Dexa treatment reduced the number of MyHC-positive myotubes, while the exposure to EVs recovered the myotube presence (Figure 3A). In parallel, the analysis of neurite density into the muscle compartment was carried out. Interestingly, AFSC-EV exposure was able to restore the neurite density affected during muscle atrophy induction (Figure 3B). These results led us to study the possible consequences of these impairments on NMJ formation. NMJs were identified as co-localizations between αBtx-positive AChRs and NEFH/SYPH-positive neurites on myotubes (Figure 4A). While the percentage of innervated myotubes was not significantly reduced upon Dexa treatment (Figure 4B), a reduction in NMJ numbers per myotube was observed (Figure 4C) and human AFSC-EVs were effective in counteracting this affection. In addition, NMJs could be distinguished for their morphology as single-contact-point NMJs—less mature—when a neurite touches a AChR cluster one time, or multiple-contact-point NMJs—characteristic of a more mature development state of co-culture—when neurites will fan out and engage with the AChR cluster over a larger surface [29]. Based on this, we observed a reduction in both of these types of interaction in the Dexa-induced atrophy model, while it was prevented by EV pre-exposure (Figure 4D). In order to investigate the functional consequences of morphological alteration in this muscle atrophy model and the therapeutic potential of AFSC-EVs, live-cell calcium imaging was performed (Figure 5A,B). As shown in Figure 5C, Dexa treatments significantly reduced the percentage of motor neuron-stimulated active myotubes, compared to untreated ones, while EV exposure prevented the Dexa-mediated impairment compared to the control. This result brought us to investigate the intracellular calcium transient waves. While significant modifications of the cellular calcium intensity peak were not observed (Figure 5D), this analysis showed a delay of Ca2+ peak onset after Dexa treatment, indicating an alteration in myotube functionality. On the other hand, AFSC-EVs were able to reduce this delay in myotube functionality (Figure 5E). Among many factors, oxidative stress and mitochondrial dysfunction may perform key roles in NMJ decline, muscle strength, and integrity loss [4]. To investigate the oxidative stress alteration in our system, we performed live-imaging assays using fluorescent probes for intracellular ROS and mitochondrial O2•− detection. A schematic overview of experiments is shown in Figure 6A. First, we measured the ROS level variations in neurites after up to 28 min of treatment with Dexa. Dexa exposure increased the ROS content in the neurites that have crossed the microgrooves to contact the myotubes. Notably, EVs protected MN elongations from oxidative stress induced by atrophic muscle cells, in all time points of analysis (Figure 6B). To investigate the implication of mitochondrial superoxide (O2•−) in this oxidative context, MitoSoxTM live-cell imaging analysis of neurites was performed (Figure 6C). EV pre-treatment was able to reduce mitochondrial O2•− levels, increased by Dexa exposure, for every investigated time point (Figure 6D). In recent years, human AFSCs have been proposed as potential therapeutic approaches for human tissue repair and regeneration, thanks to the encouraging results obtained from different experimental disease models [14,15]. Many of the observed effects can be, at least in part, attributed to the presence of bioactive molecules secreted into extracellular vesicles (EVs), such as antioxidant and anti-inflammatory compounds. Despite the complexity, the pathogenesis of age-related muscle wasting conditions, such as muscle atrophy, could be linked to a reduction in protein synthesis and/or an enhanced proteolysis, associated with an increase in oxidative stress [30]. In the present study, we aimed to deepen the understanding of the therapeutic potential of EVs, obtained from AFSCs, in rescuing the pathological atrophic phenotypes and detrimental consequences on NMJ integrity induced by Dexa. Dexa is a synthetic glucocorticoid widely used as a treatment to control different pathological alterations linked to inflammation [31]. Despite its beneficial effects, its abuse can lead to skeletal muscle atrophy, mainly via two pathways: the glucocorticoid receptor (GR)-mediated catabolic processes and the oxidative stress-related pathway [32,33,34]. Given the similar mechanism of muscle damage to age-related atrophy, glucocorticoids are largely used in research for this purpose. FOXO3 plays a crucial role in these catabolic events, regulating both metabolism and oxidative stress defenses. FOXO3 controls the two principal systems of muscle proteolysis: ubiquitin-proteasomal and autophagic/lysosomal pathways. In our in vitro atrophy model, we observed gene expression increase in FOXO3, associated with an overexpression of autophagy-related markers Beclin-1 and LC3β [35]. Moreover, the myotube morphology appeared affected, as shown by the fusion index, nuclei per myotube, and myotube thickness reduction, accompanied by a downregulation of late muscle differentiation markers (myosin heavy chain 1 and 3). Contrarily, the expression of structural muscle protein Desmin appeared increased. Desmin is an intermediate filament fundamental for the maintenance of muscle structure, cellular integrity and size, mitochondrial homeostasis, and proteostasis [36]. Recent studies demonstrated that Desmin gene expression levels increase in different models of heart failure, as a compensatory mechanism for its augmented misfolding and degradation [37,38,39]. Therefore, we assume that a similar self-rescuing response occurred in our atrophy model. Notably, AFSC-EV treatment restored not only the myotube morphology affected by Dexa but also gene expression of all the altered muscle activation/differentiation markers. Considering the central role of oxidative stress in muscle atrophy progression, and the potential of extracellular vesicles in redox modulation, we investigated it in our Dexa-induced atrophy model. Interestingly, in the presence of EVs, we observed a significant reduction in ROS levels increased by Dexa, accompanied by an upregulation of Sirtuin 3 (Sirt3), FOXO3, and antioxidant genes superoxide dismutase 1 (SOD1), glutathione peroxidase (GPx), peroxiredoxin 3 (PDRX3), and thioredoxin reductase 3 (TrxR3). Sirt3 is a mitochondrial NAD-dependent histone deacetylase (HDAC) principally implicated in stress-adaptive responses by inhibiting mitochondrial oxidative stress. Moreover, the main targets of Sirt3 are FOXO family transcription factors, which once deacetylated increase their transcriptional activity and reduce their degradation via phosphorylation and/or ubiquitination [40]. The FOXO3-activated pathway by Sirtuins upregulates a set of FOXO3a-dependent mitochondrial antioxidant enzymes including superoxide dismutase, thioredoxin, and peroxiredoxin [41]. Additionally, we recently demonstrated that AFSC-EV exposure counteracts oxidative stress in an in vitro model of Alzheimer’s disease and osteoporosis, at least in part by reinforcing the Sirtuin/FOXO antioxidant defenses pathway [42,43]. The results obtained in this work led us to hypothesize a similar mechanism, although it has not been further investigated since our main focus was on NMJ alterations. Considering the bi-directional communication between nerve and muscle, recent findings have highlighted that skeletal muscle can be a fundamental source of signals for neuron survival, axonal growth, and maintenance of synaptic connection [6]. Based on this, we investigated the muscle impairment consequences on distal axon and the protective potential of vesicles from AFSCs. In order to study the atrophy consequences in a more complex system focusing on NMJs, we used microfluidic devices to set up an in vitro co-culture of human iPSC-derived motor neurons and myotubes with an atrophic phenotype induced by Dexa. The fluidically isolated compartments, where only neurites can growth through microgrooves, not only allows the maintenance of a cell-type-specific microenvironment, but also allows the isolation of subcellular compartments, as distal and proximal parts of the axon, to carry out region-specific analyses [44,45]. Interestingly, the muscle wasting environment induced by Dexa affected the neurite presence in the muscle side and the NMJ maintenance. Furthermore, both types of NMJs—mature multiple contact point and newly formed compensatory single contact point—were impaired due to Dexa treatment. Moreover, AFSC-EVs presence prevented all these neural alterations, probably protecting motor neurons from the detrimental environment created into the synaptic space during atrophy-related muscle wasting. Upon exploring the functional consequences, we noticed a reduction in the number of active myotubes after MN stimulation, compared to the total active myotubes, in the Dexa-atrophy model. Even though we did not observe significant alterations in the calcium influx intensity peak between different conditions during stimulation, the myotube response reactivity to MN stimulation over time was delayed in atrophic conditions. This effect could be reversed by AFSC-EV pre-treatment. Notably, several studies on amyotrophic lateral sclerosis (ALS) models demonstrated that increased oxidative stress and compromised mitochondria, in both muscle and nerve, are among the major contributory factors in affecting presynaptic heath [46,47,48]. In particular, NMJ in vitro exposure to exogenous H2O2 induces a strong inhibition of spontaneous neurotransmitter release in frog sartorius muscle [49]. In light of this, we propose that the observed alterations in the timing of myotube contraction could be explained as an impairment in the synaptic vesicles’ release by presynaptic terminals affected by an atrophy-related redox imbalance. Nevertheless, we cannot exclude that this may also be due to an impairment in myotube contractile machinery. Furthermore, experiments on mutant SOD1 mouse models demonstrated that oxidative stress originates from distal muscles before the onset of ALS pathology. This suggests that oxidative damage starts at the postsynaptic side of the muscle and propagates to motor neurons’ presynapse and further up to the axon in a retrograde manner towards the neuronal soma, ultimately leading to apoptosis of the entire cell [50,51,52]. To evaluate this hypothesis in our model, the oxidative stress and the mitigating effect of EVs in atrophy-related NMJ alterations were investigated. To this purpose, we followed the redox modification of neurites reaching the myotube area, the ones likely creating NMJs. We observed that the treatment with AFSC-EVs reduced not only the increased ROS levels but also the mitochondrial superoxide (O2•−) overproduction in neurites, associated with muscle atrophy induction. Antioxidant proteins carried by AFSC-EVs, including SOD1, could have a direct effect on ROS scavenging, re-equilibrating the redox balance affected in NMJs. Importantly, increased local activities of ROS are linked to a reduction in motor neuron and NMJ integrity and efficiency in muscle contraction, and the permanence of this oxidative stimuli leads to a permanent disruption in their structure and functionality [53,54]. The analysis of our data demonstrated that the re-equilibration of redox balance by AFSC-EVs, together with their immunomodulatory and neurogenic activity, have a protective effect on NMJ and motor neuron damage associated with muscle atrophy. The human amniotic fluid stem cells (hAFSCs) were obtained from amniotic fluids collected from 3 healthy pregnant women at the 16th week of gestation who underwent amniocentesis per maternal request (not foetal anomalies) at the Unit of Obstetrics and Gynecology, Policlinico Hospital of Modena (Modena, Italy). The amniocentesis was performed under continuous ultrasound guidance, in a sterile field, with a 23-Gauge needle. The risk related to the procedure and the purpose of the study were explained to all patients before the invasive procedure, and the ob-gyn specialist collected a signed consent form before starting the exam (protocol 360/2017, dated 15 December 2017 and approved by Area Vasta Emilia Nord). For this study, unused (supernumerary) flasks of AF cells cultured in the Laboratory of Genetics of the TEST Lab (Modena, Italy) for 2 weeks were used. hAFSCs were isolated as previously described [55]. Briefly, human amniocentesis cultures were harvested by trypsinization and subjected to c-kit immunoselection by MACS technology (Miltenyi Biotech, Germany). hAFSCs were subcultured routinely at 1:3 dilution and not allowed to grow beyond 70% confluency. hAFSCs were grown in αMEM culture medium (Corning, Manassas, VA, USA) supplemented with 20% fetal bovine serum (FBS) (Gibco, Waltham, MA, USA), 2 mM L-glutamine, 100 U/mL penicillin, and 100 µg/mL streptomycin (all reagents from EuroClone Spa, Milano, Italy). hAFSCs were grown in 75cm2 flasks until sub-confluence (around 106 cells). Then, cells were maintained in FBS-free culture medium (10 mL) for 4 days, to avoid contamination by EVs from the FBS solution. The collected conditioned medium (CM) was centrifuged at 300× g for 10 min at 4 °C to eliminate cellular debris, and then concentrated up to 2 mL by using centrifugal filter units with a 3K cut-off (Merk Millipore, Burlington, MA, USA) [54]. The concentrated CM was again centrifuged at 10,000× g for 30 min at 4 °C and then, the supernatant was ultracentrifuged in polypropylene ultracentrifuge tubes (13.5 mL, Beckman Coulter) at 100,000× g for 90 min at 4 °C in a Beckman Coulter Optima L-90 K centrifuge (SW-41 rotor); the supernatants were discarded and the pellets were resuspended in 13 mL DPBS (Corning, Manassas, VA, USA) and ultracentrifuged again (100,000× g, 90 min at 4 °C) [56]. The pellet was resuspended in 100 µL of DPBS for subsequent analyses and treatments. Size distribution and concentration of EVs were analyzed, after a 1:100 dilution, by a NanoSight particle tracker from NanoSight Ltd. (Malvern Panalytical, Worcestershire, UK). Human Mesoangioblasts (hMABs) were isolated as previously described [57,58]. hMABs were cultured on collagen from calf skin-coated flasks in IMDM growth medium (Sigma, Milan, Italy) supplemented with 1% sodium pyruvate, 1% non-essential amino acids, 1% L-glutamine, 1% insulin transferrin selenium (all reagents from EuroClone Spa, Milano, Italy), 5 ng/mL recombinant human basic fibroblast growth factor (bFGF) (PeproTech, Rocky Hill, NJ, USA). Medium was changed every 3 days. Since physical contact between hMABs initiates fusion and reduces the myogenic potential, cells were trypsinized before 70% confluency [59]. To induce myotube differentiation, confluent hMABs were exposed for 1 week to a differentiation medium composed of 1:1 DMEM/F12 (Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 2% horse serum (Thermo Fisher Scientific, Waltham, MA, USA) and 1% sodium pyruvate (EuroClone Spa, Milano, Italy) on collagen from calf skin-coated supports. In order to induce muscle atrophy, after 7 days myotubes, were treated with 20 µM Dexamethasone (Dexa) (Sigma Aldrich, St Louis, MO, USA) in differentiation medium for 20 min (for ROS analysis) or 24 h (for all other experiments). AFSC-EVs t (1.3 × 108 particles/cm2) were added 24 h before Dexa treatment and maintained for the glucocorticoid treatment time. To obtain mature motor neurons (MNs) from iPSCs (GibcoTM Episomal hiPSC Line) (Gibco, Thermo Fisher Scientific, Waltham, MA, USA), the protocol by Dittlau et al. was applied [28,29]. Briefly, iPSCs were harvested using Collagenase type IV (Gibco, Waltham, MA, USA), transferred into Ultra-low attachment multi6-well plates (Corning Manassas, VA, USA) to promote cluster formation and maintained in Neuronal medium (50% DMEM/F12 and 50% Neurobasal Medium (both from Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) with 2 mM L-glutamine, 100 U/mL penicillin, and 100 µg/mL streptomycin (all reagents from EuroClone Spa, Milano, Italy), 1% N2 supplement, 2% B-27TM without vitamin A, 0.1% β-mercaptoethanol (all reagents from Thermo Fisher Scientific, Waltham, MA, USA), 0.5 µM ascorbic acid (Sigma-Aldrich, Milan, Italy)) supplemented with 5 µM Y-27632 (Merck Millipore, Burlington, MA, USA), 0.2 µM LDN-193189 (Stemgent, Beltsville, MA, USA), 40 µM SB431542, and 3 µM CHIR99021 (both from Tocris Bioscience, Bristol, UK) for 2 days, changing the medium every day. From day 2, Neuronal medium was supplemented with 0.1 µM retinoic acid (Sigma-Aldrich, Milan, Italy), 500 nM smoothened agonist (SAG) (Merck Millipore, Burlington, MA, USA), and from day 7, brain-derived neurotrophic factor (BDNF) and glial cell-derived neurotrophic factor (GDNF) (both from PeproTech, Rocky Hill, NJ, USA) were added. On day 9, 20 µM DAPT (Tocris Bioscience, Bristol, UK) was added. On day 10, single cells were obtained from floating clusters by 0.05% trypsin (Gibco, Waltham, MA, USA) treatment, and seeded onto poly-L-ornithine- (PLO) and laminin- (both from Sigma, St Louis, MO, USA) coated plates. Single cell neural progenitor cells (NPCs) were maintained in culture until experiments in Neuronal medium supplemented with BDNF, GDNF, and CNTF (ciliary neurotrophic factor) were conducted, and the medium was refreshed every 2 days. To test the effect of Dexa on mature motor neurons, at day 27 of differentiation, Dexa treatment was applied at a concentration of 20 µM for 24 h. Microfluidic devices (XonaTM Microfluidics, Temecula, CA, USA; Cat N° XC150) were sterilized in 90% ethanol and left to air-dry in a sterile laminar flow hood. Devices were placed individually in 10 cm petri dishes for easy handling. Before cell seeding, devices were coated using 100 µg/mL poly-L-ornithine (PLO) in DPBS for 3 h and then 20 µg/mL laminin (both from Sigma, St Louis, MO, USA) in Neurobasal medium (Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) overnight. All coated materials were incubated at 37 °C, 5% CO2, and a volume difference of 100 µL between two sides was applied to allow the coating to pass through the microgrooves (maximum capacity for each device well: 200 µL). The day after, devices were carefully washed once with DPBS before neural cell plating. Myotubes and MNs were co-cultured into XonaTM microfluidic devices according to a previously described protocol [59]. Briefly, day 10 MN-precursor cells were seeded into one side of devices at a seeding density of 1.25 × 105 cells/well (total 2.5 × 105 cells/side) and maintained in day-specific differentiation medium according to the differentiation protocol. After 1 week (day 17), hMABs were seeded into the opposite compartment (105 cells/well, total 2 × 105 cells/side), and the day after (day 18), myotube differentiation was started (differentiation medium described in section “Derivation, Maintenance, Differentiation, and Treatment of Human Mesoangioblasts”). On day 21, a chemotactic and volumetric gradient was established: neuronal compartments received 100 µL/well of neuronal medium without neurotrophic factors, while myotube compartments received 200 µL/well neuronal medium supplemented with 30 ng/mL BDNF, GDNF, CTNF (all reagents from PeproTech, Rocky Hill, NJ, USA), 20 µg/mL laminin (Sigma, St Louis, MO, USA), and 0.01 µg/mL recombinant human agrin protein (R&D Systems, Minneapolis, USA). The gradient and laminin/agrin treatment were maintained until the end of the co-culture period. At day 26, AFSC-EVs were added to both compartments in day 21 medium (4.16 × 107 particles/well), and after 24 h, only the myotube compartment was also treated with 20 µM Dexa for 20 min for oxidative stress analysis or 24 h for all other analyses. For the quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) assay, the Purelink® RNA mini kit (Thermo Fisher Scientific, Waltham, MA, USA) was used to isolate total RNA, and RNA samples were purified by a TurboTM DNA-free kit (Thermo Fisher Scientific, Waltham, MA, USA) following manufacturers’ instructions. First, 1 µg of RNA was reverse-transcribed using the Superscript III Reverse Transcriptase First-Strand Synthesis SuperMix (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturers’ protocol. Then, Platinum SYBR Green QPCR SuperMix-UDG (Thermo Fisher Scientific, Waltham, MA, USA) was used to dilute cDNA (1:5). The RT-qPCR was performed by a Viia7 384-plate reader (Thermo Fisher Scientific, Waltham, MA, USA) [60]. Oligonucleotide primer forward/reverse sequences are listed in Table 1. For immunofluorescence analysis, cells—seeded on coverslips or into microfluidic devices—were processed and confocal imaging was performed using a Nikon A1 confocal laser scanning microscope, as previously described [43,59]. Primary antibodies to detect neurofilament heavy chain (NEFH) (Abcam, Cambridge, UK), synaptophysin (SYPH) (Cell Signaling Technology, Lieden, Netherlands), Islet-1 (Isl-1) (Millipore, Burlington, MA, USA), β-tubulinIII (βtubIII) (Cell Signaling Technology, Lieden, Netherlands), and myosin heavy chain (MyHC) (In-house, SCIL, dil. 1:20) were used following the datasheet-recommended dilutions. α-Bungarotoxin-tetramethylrhodamine (Sigma-Aldrich, MO, USA) was incubated with secondary antibodies according to the manufacturers’ protocol. Alexa secondary antibodies (Thermo Fisher Scientific, Waltham, MA, USA) were used at a 1:200 dilution. To obtain three-dimensional projections, the confocal serial sections were processed with ImageJ software [61], while image rendering was performed with Adobe Photoshop software [62]. For myotube fusion index, nuclei per myotube, myotube thickness analyses, and NMJ quantifications, MyHC-positive cells containing multiple nuclei were selected as myotubes. Fusion index percentage was calculated as a ratio percentage between the number of nuclei inside myotubes and total nuclei. Myotube thickness was measured using ImageJ software. For NMJ quantification into microfluidic devices, 40× magnification images of MyHC-positive myotubes were collected using an inverted confocal microscope. The number of co-localizations between NEFH/SYPH and α-bungarotoxin (αBtx) (Sigma, St Louis, MO, USA), for Acetylcholine Receptor (AChR) identification, was counted manually through each z-stack, and the number of co-localizations was normalized to the number of myotubes present in the z-stack. NMJ morphology, single or multiple contact point, was analyzed looking at neurite interactions with AChR clusters, as previously described by Dittlau et al., 2021 [29]. Briefly, NMJs were identified as a single contact point when a neurite touched a AChR cluster once, while a multiple contact point was defined as a neurite fanning out and engaging with the AChR cluster over a larger surface. Neurite density-outgrowth quantification was performed as previously described by Dittlau et al. 2021 [29]. Briefly, tile scan images of NEFH fluorescence were taken using an inverted Leica SP8 DM18 confocal microscope and neurites were isolated using Ilastik 1.3.3post1 Pixel Classification software. A custom ImageJ 1.52p software linear School analysis script was used to quantify the total number of pixels that intersect an intersection line (distance between lines: 50 µm). The measuring was started at a 100 µm distance from the microgrooves due to the high neurite density at the exit of microgrooves. After AFSC-EV and/or Dexamethasone treatments, the myotube compartment was incubated with 5 µM Fluo-4 AM (Thermo Fisher Scientific, Waltham, MA, USA) for 25 min in the dark (5% CO2, 37 °C). MNs were stimulated with 50 mM KCl and Fluo-4 fluorescence was recorded in the myotube compartment (1 picture/second for a total of 60 s, 10× magnification). Calcium transients were recorded after KCl stimulations in two different fields for each replicate. The fluidic isolation of the compartments in the microfluidic devices ensured no direct contact between the high KCl solution and the myotubes. To verify the myotube functionality, a positive test was performed by direct stimulation of myotubes with 50 mM KCl in the myotube compartment. The percentage of MN-stimulated active myotubes was calculated as a ratio between MN-stimulated active myotubes and total active myotubes. Recordings were acquired and analyzed using a Nikon A1R confocal microscope and NIS-Elements AR 4.30.02 software. Calcium waves were calculated as a ratio between the myotube fluorescence at each analyzed point and the fluorescence mean during the first 5 s of recording. Time intensity peak was calculated considering the time of peak starting onset. hMABs were seeded and differentiated into 96-well plates (5 × 105 cell/well) with 5 replicates for each condition. After 7 days, myotubes were treated with 1, 10, 20, or 40 µM Dexamethasone (Dexa) (Sigma Aldrich, St Louis, MO, USA) in differentiation medium for 24 h. At the end of the treatments, 0.5 mg/mL MTT was added and incubated for 3 h at 37 °C. After incubation, the medium was removed, and acidified isopropanol was added to solubilize the formazan salts. The adsorbance was measured at 570 nm using a microplate spectrophotometer (Appliskan, Thermo-Fisher Scientific, Vantaa, Finland). To evaluate the intracellular ROS levels, a dichlorodihydrofluorescein diacetate (DCFH-DA) assay was performed as previously described [63]. For myotube oxidative stress investigation, hMABs were seeded and differentiated into 96-well plates (5 × 105 cell/well) with 5 replicates for each condition, while for co-culture oxidative stress analysis, myotubes and MNs were cultured in microfluidic devices as described above. Culture medium was removed from each well and 5 µM DCFH-DA was incubated in PBS with 1 gr/L of glucose for 20 min at 37 °C and 5% CO2. Dexa 20 µM treatment was only added to myotubes with the probe in the meantime and maintained for 20 min. In the 96-well plates, the probe solution was replaced with PBS/glucose and the fluorescence was read at 485 nm (excitation) and 535 nm (emission) using the multiwell reader Appliskan (Thermo Fisher Scientific, Waltham, MA, USA). Cellular autofluorescence was subtracted as a background using the values of the wells not incubated with the probe. For devices, after 20 min of Dexa treatment, the probe solution was replaced with PBS/glucose buffer and the neurite fluorescence was recorded for 8 min into the muscle compartment with a Nikon A1 confocal laser scanning microscope equipped with a live-cell imaging system. Live images were taken between microgroove exits and myotubes in order to select the neurites most likely to have contacted myotubes and to avoid myotube fluorescence noise. Confocal images were obtained using a Nikon A1 confocal laser scanning microscope equipped with a live-cell imaging system. During live imaging, cells were maintained in a PBS-glucose (1g/L) buffer at 37 °C, 5% CO2. All acquisition settings, including detector sensitivity and camera exposure time, were maintained constant during recording. To avoid photobleaching and to reduce cell stress, laser power was set to minimum. To identify mitochondria, at day 27—after 24 h of AFSC-EVs exposure—both microfluidic device compartments were washed once with PBS/glucose buffer and then incubated with 100 nm MitoTrackerTM Green FM probe (Invitrogen, Waltham, MA, USA) in PBS/glucose buffer, and, in only the myotube compartment, with 20 µM Dexa for 20 min at 37 °C, 5% CO2. After the first 10 min, 5 µM MitoSoxTM Red was added to both compartments to identify mitochondrial superoxide production. After the incubation time, microfluidic devices were gently washed 3 times and maintained in PBS/glucose during live imaging analysis. MitoSoxTM and MitoTrackerTM fluorescence was recorded in myotube compartments next to the microgrooves exit (20× magnification, with 10 s interval for a duration of 8 min). MitoSoxTM signal was normalized on MitoTrackerTM for each time point. All the experiments were performed with 3 biological replicates. For quantitative comparisons, the values were reported as the mean ± SD based on a triplicate analysis for each sample. One-way ANOVA with a Bonferroni post hoc test or a Student’s t-test were applied to test the significance of the observed differences amongst the study groups. Statistical significance was considered as a p-value < 0.05. Statistical analysis and plot layout were obtained by using GraphPad Prism® release 8.0 software. In this study, we investigated the protective effect of AFSC-EV treatment upon Dexa-induced muscle atrophy and its consequences on the presynaptic part of NMJs. We took advantage of the microfluidic human MAB/iPSC-MN co-culture system to study muscle-nerve cross-communication during muscle atrophy. Glucocorticoids exposure confirmed the neurodegeneration induced by muscle atrophy; however, the AFSC-EV administration ameliorated the disease progression, thanks also to their ROS regulation capability. While this study is descriptive in nature, it is providing evidence for beneficial effects of AFSC-EVs on NMJs alterations transmitted by muscle atrophy, and this microfluidic NMJ system can be further explored for small molecule screening and mechanistic follow-up studies.

PMC10003240

Gang Wang,Juncheng Wang,Lirong Yao,Baochun Li,Xiaole Ma,Erjing Si,Ke Yang,Chengdao Li,Xunwu Shang,Yaxiong Meng,Huajun Wang

Transcriptome and Metabolome Reveal the Molecular Mechanism of Barley Genotypes Underlying the Response to Low Nitrogen and Resupply

28-02-2023

barley,genotypes,nitrogen,transcriptome,metabolome

Nitrogen is one of the most important mineral elements for plant growth and development. Excessive nitrogen application not only pollutes the environment, but also reduces the quality of crops. However, are few studies on the mechanism of barley tolerance to low nitrogen at both the transcriptome and metabolomics levels. In this study, the nitrogen-efficient genotype (W26) and the nitrogen-sensitive genotype (W20) of barley were treated with low nitrogen (LN) for 3 days and 18 days, then treated with resupplied nitrogen (RN) from 18 to 21 days. Later, the biomass and the nitrogen content were measured, and RNA-seq and metabolites were analyzed. The nitrogen use efficiency (NUE) of W26 and W20 treated with LN for 21 days was estimated by nitrogen content and dry weight, and the values were 87.54% and 61.74%, respectively. It turned out to have a significant difference in the two genotypes under the LN condition. According to the transcriptome analysis, 7926 differentially expressed genes (DEGs) and 7537 DEGs were identified in the leaves of W26 and W20, respectively, and 6579 DEGs and 7128 DEGs were found in the roots of W26 and W20, respectively. After analysis of the metabolites, 458 differentially expressed metabolites (DAMs) and 425 DAMs were found in the leaves of W26 and W20, respectively, and 486 DAMs and 368 DAMs were found in the roots of W26 and W20, respectively. According to the KEGG joint analysis of DEGs and DAMs, it was discovered that glutathione (GSH) metabolism was the pathway of significant enrichment in the leaves of both W26 and W20. In this study, the metabolic pathways of nitrogen metabolism and GSH metabolism of barley under nitrogen were constructed based on the related DAMs and DEGs. In leaves, GSH, amino acids, and amides were the main identified DAMs, while in roots, GSH, amino acids, and phenylpropanes were mainly found DAMs. Finally, some nitrogen-efficient candidate genes and metabolites were selected based on the results of this study. The responses of W26 and W20 to low nitrogen stress were significantly different at the transcriptional and metabolic levels. The candidate genes that have been screened will be verified in future. These data not only provide new insights into how barley responds to LN, but also provide new directions for studying the molecular mechanisms of barley under abiotic stress.

Transcriptome and Metabolome Reveal the Molecular Mechanism of Barley Genotypes Underlying the Response to Low Nitrogen and Resupply Nitrogen is one of the most important mineral elements for plant growth and development. Excessive nitrogen application not only pollutes the environment, but also reduces the quality of crops. However, are few studies on the mechanism of barley tolerance to low nitrogen at both the transcriptome and metabolomics levels. In this study, the nitrogen-efficient genotype (W26) and the nitrogen-sensitive genotype (W20) of barley were treated with low nitrogen (LN) for 3 days and 18 days, then treated with resupplied nitrogen (RN) from 18 to 21 days. Later, the biomass and the nitrogen content were measured, and RNA-seq and metabolites were analyzed. The nitrogen use efficiency (NUE) of W26 and W20 treated with LN for 21 days was estimated by nitrogen content and dry weight, and the values were 87.54% and 61.74%, respectively. It turned out to have a significant difference in the two genotypes under the LN condition. According to the transcriptome analysis, 7926 differentially expressed genes (DEGs) and 7537 DEGs were identified in the leaves of W26 and W20, respectively, and 6579 DEGs and 7128 DEGs were found in the roots of W26 and W20, respectively. After analysis of the metabolites, 458 differentially expressed metabolites (DAMs) and 425 DAMs were found in the leaves of W26 and W20, respectively, and 486 DAMs and 368 DAMs were found in the roots of W26 and W20, respectively. According to the KEGG joint analysis of DEGs and DAMs, it was discovered that glutathione (GSH) metabolism was the pathway of significant enrichment in the leaves of both W26 and W20. In this study, the metabolic pathways of nitrogen metabolism and GSH metabolism of barley under nitrogen were constructed based on the related DAMs and DEGs. In leaves, GSH, amino acids, and amides were the main identified DAMs, while in roots, GSH, amino acids, and phenylpropanes were mainly found DAMs. Finally, some nitrogen-efficient candidate genes and metabolites were selected based on the results of this study. The responses of W26 and W20 to low nitrogen stress were significantly different at the transcriptional and metabolic levels. The candidate genes that have been screened will be verified in future. These data not only provide new insights into how barley responds to LN, but also provide new directions for studying the molecular mechanisms of barley under abiotic stress. Nitrogen is the most important mineral element in plants, the essential nucleotide and protein for life, and the main component of plant hormones [1,2]. To increase crop yields, more than 100 million tons of nitrogen fertilizer is used annually worldwide, but excessive nitrogen application may cause air and water pollution [3]. In some parts of the world, excessive nitrogen also has a negative impact on biodiversity, human health, and climate [4,5]. Simultaneously, excessive nitrogen application also promotes the ratio of environmental nitrogen to phosphorus, thus affecting ecological structure and function [6]. Moreover, plants growing under excessive nitrogen application are more likely to lodge due to overgrowth and tenderness of branches, diseases, and insect pests, thereby reducing crop quality [7]. Generally, the ratio of yield to total nitrogen supply is called nitrogen use efficiency (NUE) [8]. On average, the absorption of nitrogen fertilizer is less than half of the amount of nitrogen fertilizer applied, so it is meaningful to improve the NUE of crops [9]. Nitrate and ammonium are the two main forms of inorganic nitrogen in soil. Among them, nitrate is the main form of nitrogen available for most higher plants in the aerobic environment, and ammonium is usually the main form of plants in waterlogged or acidic soil [10,11]. The process of nitrogen utilization can be divided into absorption, transport, and assimilation, so the transporters and assimilation enzymes of nitrate or ammonium are the most important components that determine the NUE [12]. For most plants, the nitrate absorbed by the root is assimilated into the root, while the majority is transported to the ground. In general, nitrate is first reduced to nitrite by nitrate reductase (NR) in the cytoplasm of leaves, and then further reduced to ammonium by nitrite reductase (NIR) in chloroplasts and glutamine synthetase (GS) in the cytoplasm [13,14]. Ammonium, coming from nitrate or directly absorbed by the ammonium transporter, is assimilated to amino acids by glutamate synthase (GOGAT), while α-ketoglutarate acid is the product of tricarboxylic acid cycle (TCA), with a C5 carbon skeleton. α-Ketoglutaric acid and ammonia can be converted into glutamic acid under GS and GOGAT [15]. α-Ketoglutaric acid can also be converted into glutamic acid under glutamate dehydrogenase (GDH), which is the key enzyme connecting biological carbon and nitrogen metabolism [16]. Glutamate synthase includes ferredoxin-dependent glutamate synthase (FD-GOGAT) and NADH-dependent glutamate synthase (NADH-GOGAT); the former mainly exists in the chloroplast, and the latter in the cytoplasm [17]. Both the yield of barley and the planting area of cereal crops rank fourth in the world [18]. By the end of the 21st century, the annual output of barley is expected to reach 140 million tons in the world, covering an area of over 55 million hectares [19]. Barley is mainly used as animal feed and grain, as well as for malt. Currently, people are becoming more and more aware of the high nutritional value of barley, so barley is deeply loved by the public for its high content of β-glucan and low gluten [20,21]. As a highly adaptable crop, most of the barley in the world is produced in areas with poor grain growth (such as corn and rice), and barley is distributed near the arctic and subtropics. Therefore, it is of great importance to increase the yield of barley in harsh environments for the future [22]. Moreover, the great genetic diversity and resilience of barley in harsh environments, and the unique adaptation mechanism to abiotic stress, are of great value for the agroecological transformation and the reduction of nitrogen fertilizer input [23,24,25]. However, at present, there are insufficient studies on the molecular mechanism of barley tolerance to low nitrogen stress [24,26,27]. Transcriptome refers to the sum of all RNAs transcribed by a particular tissue or cell at a certain time or in a certain state. Transcriptome has been used in many plants to investigate the complex regulatory mechanisms of roots and leaves under nitrogen stress. In the transcriptome analysis of potatoes under low nitrogen stress, the co-expressed genes and potential pathways related to nitrogen transport and absorption in roots, stems, and leaves were confirmed [28]. The transcriptome of Elymus breviaristatus treated with different concentrations of ammonium showed that ribosomal proteins were regulated in roots and might affect the regulation of sieve tube transport or stress resistance [29]. In addition, studies have also explored the physiological and comparative transcriptome mechanism of high NUE acquisition by using a low nitrogen-tolerant genotype and a low nitrogen-sensitive genotype. For example, through transcriptome analysis of two Tibetan wild barley genotypes with different NUEs under low nitrogen, it was found that the high expression of the nitrate transporter and the response for auxin (IAA) and ethylene (ETH) to low nitrogen stress may also be related to genotypes [24]. The transcriptome of pepper genotypes with different NUEs under low nitrogen was found to be different DEGs that do not directly participate in nitrogen metabolism [30]. Metabolomics is applied to crop abiotic stress, aiming at investigating the changes of its metabolites or the changes with time after abiotic stress, thereby screening the differential metabolites (DAMs) between the experimental group and the control group, exploring the DAMs and metabolic pathways of crops after abiotic stress, and revealing the mechanism of metabolism involved in crop stress resistance. At present, multi-group analysis is widely used to study the response of plants to abiotic stress [31,32,33]. Schlüter used a combination of transcriptomes in studying the changes in carbon, nitrogen, and phosphorus metabolism in maize under low temperature and low nitrogen [34]. There are also some studies on the response of Arabidopsis roots to nitrogen and hormones, by combining transcriptome and phenotypic analyses [35,36]. Some studies also evaluate how parsley integrates nutrition and hormone signaling pathways, thereby controlling root growth and development [37]. In addition, the mechanism of the low nitrogen tolerance of wild soybean seedlings has been revealed by the analysis of soybean transcriptome and metabolome in some studies [38]. W26 and W20 are two genotypes with significant differences in NUE after low nitrogen stress, and they were screened in the field previously. After the two genotypes were treated with low stress (LN) and resupply nitrogen (RN), the dry weight and nitrogen content were measured, and then the NUEs after 21 days of plant growing for the two genotypes were estimated after LN, and it was proved that there was indeed a large difference in NUE between the two genotypes after LN. After the transcriptome and metabolomic analysis of leaves and roots, the differentially expressed genes (DEGs) and differentially expressed metabolites (DAMs) could be identified. Based on the enrichment analysis of DEGs and DAMs, the difference in metabolic pathways between the two genotypes after LN and RN was also identified. In addition, this study also focused on the differential expression of key enzyme genes and nitrogen transporter genes in the nitrogen metabolism pathway to better understand the situation of the nitrogen metabolism pathway in barley after LN stress. At present, single-omics studies on barley after low nitrogen stress are usually conducted [39,40], but there are few reports on the differences in NUEs in different parts of genotypes. This study not only provides unique access to the nitrogen reprogramming of barley under deficiency/resupply, but also demonstrates the close cooperation between nitrogen-efficient genes and metabolic functions. From the appearance of the two genotypes, it can be seen that there are great differences in the morphology of W26 and W20 under different treatments (Figure 1), but only the results of shoot dry weight and root dry weight can quantify this difference. After 3 days of LN, there was a significant difference in shoot CK and LN between W26 and W20 (Figure 2a). The roots of W26 increased by 17.27% compared with the CK after LN in roots, but there was no significant difference between the CK and the LN of W20 (Figure 2b). As for biomass (the sum of shoot dry weight and root dry weight), there was no significant difference between the CK and the LN of W26 (Figure 2c), while the LN of W20 decreased by 7.52% compared with the CK. After 18 days of LN, there was still a great difference in the shoot dry weight of the two genotypes between the CK and the LN, and there was also no significant difference in root dry weight between the two genotypes after LN. W26 and W20 increased by 13.52% and 10.83%, respectively, compared with the CK. Simultaneously, there was no significant difference in biomass between the CK and the LN in W26, while W26 decreased by 17.77% compared with the CK after LN. After 21 days, there was a significant difference in the dry weight of shoots of W26 between the CK and the LN, as well as the CK and the RN. Meanwhile, there was no significant difference between the LN and the RN, but great differences among CK, LN, and RN as for W20. For root dry weight, there was no significant difference between W26 LN and RN, and the root dry weight of W20 increased by 17.62% and 15.37%, respectively compared with the CK, while the LN and RN of W20 increased by 13.07% and 9.72%, respectively. There was no significant difference in the biomass of W26 among the CK, LN, and RN, but W20 showed a significant difference among the three different treatments. After 3 days of nitrogen stress, there was no significant difference in shoot nitrogen content between the CK and the LN of W26, but the shoot nitrogen content of W20 significantly decreased, from 39.04 mg·plant−1·g−1 to 35.95 mg·plant−1·g−1 (Figure 3a). At this time, there was no significant difference in root CK and LN between the two genotypes (Figure 3b). After 18 days of low nitrogen stress, the nitrogen content in shoots of W26 and W20 decreased by 3.69 mg·plant−1·g−1 and 6.66 mg·plant−1·g−1, respectively, and there were significant differences between CK and LN, and the nitrogen content in the roots of W26 decreased from 30.77 mg·plant−1·g−1 to 28.30 mg·plant−1·g−1, while that of W20 decreased from 30.47 mg·plant−1·g−1 to 21.07 mg·plant−1·g−1. After 21 days, there was a significant difference in nitrogen content between CK and LN of W26 shoots, but there was no significant difference between LN and RN, and there were significant differences among three different treatments of W20. The nitrogen content was 41.73 mg·plant−1·g−1, 37.83 mg·plant−1·g−1 and 37.50 mg·plant−1·g−1, respectively. Simultaneously, there was a significant difference between the CK and the LN, and it was also found between the CK and RN in the root nitrogen content of W26, but there was no significant difference between the LN and the RN. There were significant differences among the three different treatments of W20, the values were 33.97 mg·plant−1·g−1, 26.07 mg·plant−1·g−1, and 32.99 mg·plant−1·g−1. The measured dry weight and nitrogen content in the leaf and root genotypes of barley in 21 days under CK and LN were estimated. The definition of NUE itself is also very complex, and there is no fixed calculation method. N uptake efficiency (NUpE = Output nitrogen/Input nitrogen × 100%) is one of the methods to estimate NUE [17]. The NUpE can be estimated according to the nitrogen content, dry weight, and seeding growth conditions (nutrient solution concentration, planting density, nutrient solution replacement times). After 21 days of treatment, the NUE of the two genotypes increased significantly under the LN condition (Table 1). The NUE of W26 in the LN condition is 87.52%, which was significantly higher than 61.74% of W26. The transcriptome data of the 72 samples described in this study have been stored in the National Biotechnology Information Center (NCBI) database, with the biological project entry number PRJNA896249. The total number of bases of 497.49 Gb raw data was obtained by sequencing, with a total of 3,316,251,936 read numbers. After filtering, the Q20 values of GC were all greater than 96.26%, and those of Q30 were all greater than 90.52%. The percentages of G and C in the four bases after filtering were 47.3% and 58.76%, respectively. The summary of the data with an overall sequencing error rate of less than 0.03% is listed in Table S1, which met the sequencing quality control requirements. The Pearson correlation coefficient among the three biological repeats was higher (Figure S1), which can be analyzed and sequenced later. The minimum number of clean reads in all samples was 40,028,848, with the maximum 52,892,072. The number and percentage of reads aligned to the genome were 72.26–92.78%. Among these genes that can match the genome, the probability of specific pairing was 71.12–89.5% (Table S2). In the leaves, the numbers of up-regulated and down-regulated genes in W26 were all less than those in W20 on the 3rd days and 21st days (Figure 4a–d). On the 18th day, the numbers of up-regulated and down-regulated genes in W26 (1782 and 1624, respectively) were much greater than those in W20 (374 and 1071, respectively), which may be related to the time of LN stress. However, once the normal nitrogen was restored, the number of DEGs in both genotypes rapidly declined, but it was more rapidly declined in W26. The number of W26 DEGs decreased from 3406 (1782 up-regulated and 1624 down-regulated) on the 18th day to 46 (26 up-regulated and 20 down-regulated) on the 21st day, and the number of W20 DEGs decreased from 1445 (374 up-regulated and 1071 down-regulated) on the 18th day to 301 (118 up-regulated and 183 down-regulated) on the 21st day. The reason for the above situation may be that the number of DEGs for W26 treated with LN was higher than that of the resupplied nitrogen, the low nitrogen stress effect disappears, and the number of DEGs decreases rapidly. According to the identification of DEGs in roots, the numbers of up-regulated and down-regulated genes in W26 were greater than those in W20 on the 3rd and 21st days (Figure 4f–h). On the 18th day, the numbers of up-regulated and down-regulated differential genes in W26 were less than those in W20. The roots were the main organ for higher plants to absorb nitrogen, and were more sensitive to the change in nitrogen concentration. Moreover, nitrogen absorbed by barley roots must be transported to the shoots through the xylem and phloem. Moreover, the plant itself was much smaller in the early stage of stress, with a relatively small demand for nitrogen. It can be observed from the above analysis that there was no significant difference in the number of DEGs in the shoots and roots of the nitrogen-efficient genotype and the nitrogen-sensitive genotype. To understand the function of differential genes, GO enrichment analysis was performed for the leaves and roots of W20 and W26. The numbers of DEGs in the leaves of W26 and W20 under different treatments were 3630 and 4358, respectively, and those in the roots were 4728 and 4518, respectively. These DEGs could be divided into three categories by GO enrichment analysis, namely, biological process, molecular function, and cell component (cellular components). The first 50 terms, significantly enriched according to the results of padj ≤ 0.05 GO enrichment analysis, were analyzed with column charts drawn. According to the GO enrichment analysis of leaves and the classification of the “biological process”, the six most common functional groups (Figures S2 and S3) enriched by W26 and W20 were “cellular homeostasis”, “cell redox homeostasis”, “nucleoside metabolic process”, “glycosyl compound metabolic process”, “metal ion transport”, and “alpha-amino acid metabolic process”. The specific functional groups of W26 were “cellular amino acid metabolic process”, “ncRNA metabolic process”, “tRNA metabolic process”, “response to biotic stimulus”, and “protein folding”. The specific functional groups of W20 were the 11 functional groups, e.g., “multi-organism process”, “defense response”, “cell recognition”, “pollination”, and “pollen-pistil interaction”. As for the “cell components”, the functional groups enriched by the two varieties were the same, namely, “photosystem II”, “photosystem II oxygen evolving complex”, and “oxidoreductase complex”. There were 20 common functional groups in the classification of “molecular function”, such as “calcium ion binding”, “gated channel activity”, “ion gated channel activity”, “carbohydrate binding”, “pattern binding”, and “polysaccharide binding”. The specific functional groups of W26 included the 10 functional groups, such as “ligase activity”, “catalytic activity, acting on a tRNA”, “nucleoside binding”, “purine nucleoside binding”, “GTP binding”, and “ribonucleoside binding”. There specific functional groups of W20 included the eight functional groups, such as “substrate-specific channel activity”, “transferase activity, transferring hexosyl groups”, “sequence-specific DNA binding”, “oxidoreductase activity, acting on single donors with incorporation of molecular oxygen”, “ADP binding”, and “signaling receptor activity”. According to the GO enrichment analysis of roots DEGs, W26 and W20 had seven common functional groups (Figures S4 and S5) in the classification of “biological processes”, namely, “response to oxidative stress”, “response to biotic stimulus”, “amine biosynthetic process”, “cellular biogenic amine biosynthetic process”, “multi-organism process”, “cellular biogenic amine metabolic process”, and “cellular amine metabolic process”. W26 had eight specific functional groups, e.g., “tricarboxylic acid metabolic process”, “nicotianamine metabolic process”, “nicotianamine biosynthetic process”, “tricarboxylic acid biosynthetic process”, “oxoacid metabolic process”, and “organic acid metabolic process”. W20 had the specific functional groups, e.g., “cell recognition”, “pollination”, “pollen-pistil interaction”, “recognition of pollen”, and “reproduction”. As for the “cell components”, the functional groups enriched by the two varieties were the same, namely, “extracellular region”, “cell wall”, “external encapsulating structure”, “apoplast”, and “cell periphery”. In the “molecular function” category, the two varieties shared the main functional groups of “peroxidase activity” and “oxidoreductase activity”, including 15 functional groups, such as “oxidoreductase activity, acting on peroxide as acceptor”, “antioxidant activity”, “ADP binding”, “transferase activity, transferring hexosyl groups”, and “hydrolase activity, hydrolyzing O-glycosyl compounds”. The specific functional groups of W26 were “nicotianamine synthase activity”, “sulfotransferase activity”, “transferase activity, transferring sulfur-containing groups”, “oxidoreductase activity, acting on single donors with incorporation of molecular oxygen, incorporation of two atoms of oxygen”, “ligand-gated ion channel activity”, and “ligand-gated channel activity”. The specific functional groups of W20 were the six functional groups, namely, “carbohydrate binding”, “transferase activity, transferring acyl groups”, “coenzyme binding”, “glucosyltransferase activity”, “transferase activity, transferring acyl groups other than amino-acyl groups”, and “vitamin binding”. According to the GO enrichment analysis, W26 and W20 had both common and specific functional groups in the classification of biological processes and molecular functions. However, in the classification of cell components, the greatly enriched functional groups of the roots of the two genotypes were completely the same. The Kyoto Encyclopedia of Genes and Genomes (KEGG) is a comprehensive database that integrates genomic, chemical, and system function information. In the study, KEGG analyzed the pathway enrichment in the roots and leaves of the two genotypes with different NUEs, with padj as the threshold of significant enrichment. According to the analysis of leaves, both W26 and W20 have 114 pathways involved. According to the KEGG analysis of roots, 111 and 112 pathways were identified in W26 and W20, respectively. Among the pathways of significant enrichment in leaves, there were 10 and 14 pathways in W26 and W20, and 5 and 8 in roots (padj ≤ 0.05). All significant enrichment pathways are related to carbon metabolism, nitrogen metabolism, fatty acid synthesis, and flavonoid biosynthesis. According to the results of KEGG significant enrichment in leaves, there were 10 pathways (Figure 5a,b) shared by the two genotypes, namely, “Ribosome”, “Photosynthesis-antenna proteins”, “Glyoxylate and dicarboxylate metabolism”, “Photosynthesis”, “Porphyrin and chlorophyll metabolism”, “Carbon metabolism”, “Biosynthesis of cofactors”, “Carbon fixation in photosynthetic organisms”, “Aminoacyl-tRNA biosynthesis”, “Glycine, Serine, and threonine metabolism”. The specific enrichment pathways of W20 were “Glutathione (GSH) metabolism”, “amino acid biosynthesis”, “Pentose phosphate pathway”, and “Carotenoid biosynthesis”. As for the common pathways of roots KEGG enrichment (padj ≤ 0.05) were four pathways shared by the two genotypes (Figure 5c,d), namely, “Photosynthesis-antenna proteins”, “Phenylpropanoid biosynthesis”, “Nitrogen metabolism”, and “Photosynthesis”. The specific enrichment result of W26 was “Plant-pathogen interaction”, and the specific enrichment results of W20 were “Flavonoid biosynthesis”, “Glyoxylate and dicarboxylate metabolism”, “Cysteine and methionine metabolism”, and “Carbon metabolism”. To verify the results of RNA-seq, qRT-PCR was used to analyze the expression of five genes in the leaves and roots of the two genotypes, respectively. The qRT-PCR analysis results were basically consistent with the RNA-seq data (Figures S6–S9). These results confirm the reliability of the RNA-seq results and reflect the actual transcriptome changes in this study. After 3 days of low nitrogen, a total of 421 DAMs were identified in W26 leaves (including 172 up-regulated DAMs and 249 down-regulated DAMs), and 463 were identified in W20 leaves (including 287 up-regulated and 176 down-regulated) (Figure 6a–d). On the 18th day, 367 DAMs were identified in W26 (including 202 up-regulated and 165 down-regulated), while 240 DAMs were identified in W20 (including 85 up-regulated and 155 down-regulated). On the 21st day, 185 DAMs were identified in W26 (including 61 up-regulated and 124 down-regulated), while 83 DAMs were identified in W20 (including 20 up-regulated and 63 down-regulated). As for the DAMs in the roots of the two genotypes, a total of 355 DAMs were identified in W26 after 3 days (including 176 up-regulated and 179 down-regulated), while 243 DAMs were identified in W20 (including 76 up-regulated and 167 down-regulated) (Figure 6e–h). After 18 days, there were 436 DAMs identified in W26, (including 310 up-regulated and 126 down-regulated), and 387 DAMs in W20 (including 202 up-regulated and 185 down-regulated). On the 21st day, 298 DAMs were identified in W26 (including 79 up-regulated and 219 down-regulated), while 227 DAMs were identified in W20 (including 85 up-regulated and 142 down-regulated). As for the 3 days, with exception of the 3rd day when the DAMs in leaves W26 were less than those of W20, the total numbers of DAMs in W26 were much higher than those in W20 at the other time points, as well as the DAMs in the roots of W26 on the 3rd day. This indicated that the nitrogen-efficient material W26 had a much stronger response to low nitrogen stress. There were also 23 co-expressed DAMs identified in the experiment, including 14 in leaves and 9 in roots. In addition, in the identification of differential metabolites, one plant hormone was identified as 3-indole butyric acid (IBA) in leaves, and two hormones were identified as 3-indolepropionic acid and brassinolide (BR) in roots. Two candidate hormones with low stress tolerance were selected from the roots (Figure 7). By mapping the DEGs and DAMs to the KEGG pathway database, their common pathway information was obtained, and the main biochemical pathways and signal transduction pathways involved in DAMs and DEGs were determined [41]. There were 26 KEGG co-enrichment pathways in W26 (Figure 8a), and GSH metabolism was a pathway that was significantly enriched between DAMs and DEGs. Thirty co-enrichment pathways were identified in W20 by KEGG joint analysis (Figure 8b), and GSH metabolism was also significantly enriched. Through analysis of the metabolic pathway, major metabolites were also found. DAMs, GSH, amino acids, and amides were the main identified DAMs in leaves. According to the KEGG joint analysis of roots between DEGs and DAMs, 30 co-enrichment pathways were identified in W26 (Figure 8c), among which phenylpropane biosynthesis was the significantly different metabolic pathway between DAMs and DEGs. Twenty-eight co-enrichment pathways were identified in W20 (Figure 8d), and GSH metabolism was also significantly enriched between DAM and DEGs. It indicated that GSH metabolism was most closely related to low nitrogen in barley. In addition, the enrichment results showed that GSH, amino acid, and phenylpropane were the main DAMs found in roots. Under low nitrogen stress, barley absorbed nitrate and ammonium, and completed the basic metabolic of nitrogen by virtue of a series of transporters and related enzymes. Tables S3 and S4 exhibit a list of related differential genes in nitrogen metabolism identified in this study. Figure 9 presents the nitrogen metabolism pathway and the associated differential gene heat chart, in which those marked with yellow dots are the similar upward and downward trends of W26 and W20 at the three different time points. In leaves, the gene HORVU.MOREX.r3.6HG0541410 controlled the nitrate reductase. In roots, nitrate transporter genes were HORVU.MOREX.r3.6HG0543390 and HORVU.MOREX.r3.6HG0543380, ammonium transporter was HORVU.MOREX.r3.5HG0530810, nitrate reductase gene was HORVU.MOREX.r3.6HG0541410, and glutamine synthetase gene was HORVU.MOREX.r3.6HG0613270. The aforementioned genes with similar expression trends in the two genotypes can be considered the core genes in the nitrogen metabolism pathway in this study, having no concern with the genotypes. On the way, the other DEGs were the genes with different expression trends in the two genotypes. As shown in Figure 9, glutathione metabolism and nitrogen metabolism can be connected. For GSH metabolism of leaves, HORVU.MOREX.r3.7HG0713570, HORVU.MOREX.r3.1HG0051860, and HORVU.MOREX.r3.7HG0666960 genes were down-regulated and up-regulated in two genotypes, respectively, and they all belonged to GSH S-transferase. A gene with the same expression trend was identified in roots. HORVU.MOREX.r3.2HG0188850 belonged to GSH peroxidase. Simultaneously, five different metabolites were identified, oxidized GSH (GSSG), cysteinylglycine (Cys-Gly), L-γ-glutamyl-L-amino acid (L-γ-glutamyl-L-aminoacid), and 5-oxypropane (5-oxoproline). The upward and downward trends of 5-oxypropane (5-oxoproline) and (5-murine L-glutamyl)-L-amino acids in leaves and L-γ-L-glutamyl-L-amino acids (Glutamyl-L-aminoacid) in roots were the same. Nitrogen is an essential nutrient element that plays an important role in plant growth and development. In this study, the biomass and nitrogen content of the two materials decreased after low nitrogen. According to previous studies, low nitrogen stress can inhibit plant growth and reduce shoot dry weight and total biomass [42,43]. Biomass or dry weight can usually be used as an index of plant tolerance under nutritional stress [44,45]. When applying low nitrogen stress, plants may also absorb more nitrogen by increasing the root–shoot ratio, so as to cope with the low nitrogen stress [43]. As for the barley genotypes with a high NUE, the total biomass and nitrogen accumulation decreased after low nitrogen stress, but the NUE increased [46]. In this study, by measuring the dry weight and nitrogen content of the genotype, it was proved that W26 was more tolerant to low nitrogen and had a higher NUE than W20. The related genes of the plant nitrogen metabolism pathway have a close relationship with plant NUE. Nitrate is the main form of nitrogen absorbed by plant roots, and the nitrate transporter (NRT) is mainly responsible for nitrate transport. For example, NRT1.1 in Arabidopsis thaliana is a parental nitrate transporter that can absorb nitrate over a wide range of concentrations [47]. Moreover, the NRT1/PTR of proton-coupled transporters is responsible for nitrogen assimilation in eukaryotes and bacteria, and members of this family have evolved to transport nitrates and other secondary salts in most plant species [48]. In Arabidopsis thaliana AtNRT1.1 knockout mutants with high nitrogen levels, the expression levels of high-affinity nitrogen transporter genes, such as AtNRT2.1, AtNRT2.4, and AtAMT1, showed a decrease [49,50]. The ammonium transporter (AMT) represents the main entry pathway of NH4+ absorbed by roots. As excessive ammonium absorbed by plants may lead to poisoning, ammonium absorbed by the root plasma membrane must be strictly regulated [51]. In addition to nitrate transport proteins and ammonium transport proteins, relevant enzymes also play an important role in plant nitrogen metabolism pathways. For example, nitrate reductase (NR) activity can affect plant NUE. Scholars have found that mutated indica rice and japonica rice have different nitrogen use efficiencies, and this is due to the different nitrate reductase activities. The variation of OsNR2 alleles encoding nitrate reductase results in OsNR2 proteins with different alleles encoding structures of mutated indica rice and japonica rice, while indica rice OsRN2 shows higher NR activity [52]. Low nitrogen stress can cause a great decrease in the transcription levels and activities of NR, NIR, GS, and GOGAT. For example, after applying low nitrogen stress, and treating wheat with potassium nitrate and ammonium nitrate, the expression and activity of NR, NIR, GS, and GOGAT are restored [53]. According to studies, glutamine synthetase 2 (GS2) and FD-GOGAT are two key enzymes involved in the GS/GOGAT cycle, which are necessary for plant nitrogen assimilation [53]. The GS-GOGAT pathway is the key metabolic pathway of glutamate and glutamine. By optimizing this pathway, the metabolic flux of glutamine can be caused, thereby increasing the production of glutamine and reducing the production of by-product glutamate [54]. Glutamine and glutamate are metabolized to aspartate and asparagine by aspartate aminotransferase and asparagine synthetase, respectively [55]. As the signaling molecules of low nitrogen stress, plant hormones have a complex regulatory network under low nitrogen stress. IBA plays a strong role in all aspects of root development, including the regulation of root tip meristem size, root hair elongation, lateral root development, and adventitious root formation [56]. Studies on maize indicate that BR treatment can increase the biomass and nitrogen yield index [57]. The application of BR can greatly increase the chlorophyll content, photosynthetic rate, and light energy use efficiency of seedlings, and promote the activities of key enzymes in nitrogen metabolism [58]. In this study, GSH metabolism was the pathway of significant enrichment of the two genotypes in the KEGG joint analysis. In a Saccharomyces cerevisiae study, the content of GSH (GSH) increased from 7 to 17 nmol (mg dry weight)−1 during the first 2 h [59]. The total nitrogen content of soybean treated with Ag-NP (which can inhibit the formation of nodules) and GSH was more than 5 times higher than that of soybean treated with Ag-NP alone [60]. The above studies show that low nitrogen stress can induce an increase in GSH content, and GSH also increases the accumulation of nitrogen. GSH was the most important antioxidant that regulated plant abiotic stress response [61,62]. It could also stabilize the intracellular redox dynamic balance, stimulate stress-related signals, detoxify foreign substances, and promote stress survival [63]. Under the low nitrogen treatment of Labisia pumila Blume, it was found that the antioxidant activities (DPPH and FRAP) were significantly positively correlated with total flavonoids, GSH, GSSG, anthocyanins, and ascorbic acid, indicating that the higher content of these compounds under low nitrogen conditions might be one of the reasons for the enhanced antioxidant activity [64]. GSH was oxidized to GSH-disulfide in plant cells, and performed normal physiological functions under stress. GSH was also a reservoir of reduced sulfur, and played a vital role in nucleic acid and protein synthesis that regulated enzyme activity [64]. GSH repairs -SH groups through a GSH-disulfide exchange reaction to protect the -SH groups of some enzymes and structural proteins from oxidation [65]. Previous studies have shown that some APX, GPX, and GST genes are induced under oxidative stress [66]. In eukaryotic cells and almost all Gram-negative bacteria, GSH synthase (GSH2) and γ-glutamylcysteine synthase (GSH1) catalyze GSH synthesis, and GSH1 is inhibited by GSH feedback [67]. It was found in maize that GGT activity and protein were unevenly distributed in tissues, and were more distributed in the epidermis and stomata, parenchyma of conducting elements, and root meristem [68]. The above studies show that GSH can indeed play a role in the response of plants to low nitrogen stress, and this role may be related to GSH’s antioxidant protection of nucleic acid and protein activities. The full seeds of barley varieties W26 and W20 were soaked in 5% sodium hypochlorite solution for 10 min, rinsed three times, and germinated in a germination box with three layers of filter paper, ensuring an appropriate amount of sterilized water was sprayed every day. Seven days later, seedlings with the same growth were selected and transferred to hydroponic boxes. The hydroponic box has a volume of 10 L and was used with Hoagland’s nutrient solution. Normal concentration was set to 2 mM [24] (Table 2; Nitrogen concentration of CK and RN), and the low nitrogen concentration was set to 0.4 mM (LN). Since the seedlings were transplanted to the hydroponic box with normal nitrogen treatment and low nitrogen treatment, the nutrient solution needed to be renewed every 6 days. When the seedlings grew to the 18th day, half of the seedlings treated with low nitrogen began to be treated with normal nitrogen (RN) (Figure 1a), and the other half was subjected to continuous low nitrogen, with the other managements the same. During the growth of seedlings, the number of plants in each hydroponic box is 12. Seedlings were sampled on the 3rd, 18th, and 21st days. Then, the samples were rapidly frozen in liquid nitrogen and stored at −80 °C for later RNA-seq and metabolite analysis. Moreover, some seedings were separated into the shoots and the roots, which were then placed at 105 °C for 40 min and dried at 70 °C to obtain a stable weight for dry weight determination, and 3 biological repeats were necessary. Nitrogen content was determined with BUCHIKjelMasterK-375. All samples (in total, 72, 2 genotypes (W26 and W20) × 2 parts (leaves and roots) × 2 treatments (LN and CK/RN) × 3 time points (3rd day, 18th day, and 21st day) × 3 biological replications) were prepared for further RNA-seq analysis. After the total RNA was extracted with the Radix Scutellariae polysaccharide polyphenol kit DP441, the concentration, purity, and integrity of RNA were determined by adopting the Nano Photometer® spectrophotometer, the Qubit® 2.0 fluorometer, and Agilent 5400, respectively. Finally, the RNA samples, whose RIN values were greater than 7, were selected to build a database for sequencing. The mRNA with a poly-A tail was enriched by total RNA with Oligo (dT) magnetic beads, and then the mRNA was randomly interrupted by divalent cations in fragmentation buffer and used as a template. Random oligonucleotides were used as primers to synthesize the first chain of cDNA in the M-MuLV reverse transcriptase system, and then RNaseH was used to degrade the RNA chain. The second chain of cDNA was synthesized with dNTPs in the DNA polymerase I system. After giving terminal repair, A tail addition, and sequencing junction connection to the purified double-stranded cDNAs, the cDNAs of about 370–420 bp were selected with AMPure XP beads, the PCR amplification was performed, and the PCR product was purified with AMPure XP beads. Finally, the library was obtained. After completing the construction of the library, the Qubit 2.0 fluorometer was used to quantify the library initially, and then the library was diluted to 1.5 ng/uL. Next, the insert size of the library was detected by using the Agilent 2100 bioanalyzer. After the insert size met the expectations, the effective concentration of the library needed to be measured accurately (the effective concentration of the library was higher than 2 nM) with qRT-PCR to ensure the quality of the library. After passing the library inspection, different libraries were sequenced by using Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA) after pooling, according to the effective concentration and the target amount of off-machine data, with 150 bp paired-end reads produced. The basic principle of sequencing was sequencing while synthesizing (sequencing by synthesis). Four kinds of fluorescently labeled dNTP, DNA, polymerase, and splice primers were added to the sequenced flow cell for amplification. When extending each sequenced cluster with the complementary chain, each fluorescently labeled dNTP can release the corresponding fluorescence. The sequencer could capture the fluorescence signal, and the optical signal could be converted into the sequencing peak by computer software, thus obtaining the sequence information of the fragment to be tested. The image data measured by the high-throughput sequencer were transformed into sequence data (reads) by CASAVA base recognition. The file was in fastq format, and it mainly contained the sequence information of sequencing fragments and the corresponding sequencing quality information. The original data obtained by sequencing included a small amount of reads with sequencing connectors or low sequencing quality. To ensure the quality and reliability of data analysis, it was necessary to filter the original data, mainly including the removal of reads with connectors (adapter), the removal of reads containing N (N means that the base information cannot be determined), and the removal of low quality reads (reads whose base number of Qphred ≤ 20 accounted for more than 50% of the total read length). Simultaneously, the contents of Q20, Q30, and GC in clean data were calculated, and all subsequent analyses were based on the high-quality clean data analysis. The reference genome (Hordeum_vulgare_MorexV3) and gene model annotation files can be downloaded directly from the website “https://ftp.ensemblgenomes.ebi.ac.uk/pub/plants/release-54/fasta/hordeum_vulgare/dna/ (accessed on 19 August 2022)”. HISAT2v2.0.5 was used to build an index of the reference genome, and HISAT2v2.0.5 was adopted to compare the paired terminal clean reads with the reference genome. HISAT2 was selected as the alignment tool, because HISAT2 could generate spliced databases based on the gene model annotation files, and it had better alignment results than other non-splicing comparison tools. Six biological repeats are required in the identification of metabolites, so a total of 144 samples are used for analyses. The Vanquish UHPLC liquid chromatograph and the QExactive liquid HF-X liquid phase mass spectrometer were used in scanning the prepared metabolite extracts and QC samples (QC samples were equal volume mixed samples of the experimental samples, used to balance the GC-MS system and monitor the status of the instrument, and to evaluate the stability of the system during the whole experiment). The data measured with the liquid phase mass spectrometer were preprocessed by CD3.1 data processing software, to make the identification more accurate. Then, the peak was extracted according to the ppm, signal–noise ratio, and adduct ion set, as well as other information, and the peak area was quantified simultaneously. Next, the metabolites were identified by comparing the high-resolution secondary spectrogram databases mzCloud and mzVault and the first-level database of MassList (searching the database), with the specific principles as follows. The molecular weight of the metabolite was determined according to the mass–charge ratio of the parent ion in the first-order mass spectrometry, the molecular formula was predicted with information such as mass number deviation (ppm) and adduct ions, and then the database was matched. Moreover, the database with the secondary spectrum matched the information of fragment ion and collision energy of each metabolite in the database, according to the actual secondary spectrum, thereby realizing the secondary identification of metabolites. The metabolites, with a coefficient of variation less than 30% in QC samples [69], were retained as the final identification results for subsequent analysis. In the analysis of leaves and roots, LN/CK was taken as the comparison pair of the 3rd and 18th days, and LN/RN was taken as the comparison pair of the 21st day. DESeq2 software was used in standardizing the original read count and detecting the differentially expressed genes, and then |lg(FoldChange)| ≥ 1 & padj ≤ 0.05 was adopted as the standard for selecting DEGs. The screening of DAMs mainly referenced the three parameters, namely, VIP, FC, and p value. VIP refers to the variable importance in the projection of the first principal component of the PLS-DA model [70], with the value indicating the contribution of the metabolite to the grouping. Fold change refers to the multiple of differences, which was the ratio of the mean value of the repeated quantitative values of all organisms in the comparison group. p value was calculated by T-test [71], indicating the significant level of difference. The threshold was set as VIP ≥ 1.0, lg(FoldChange)| ≥ 1 & p value ≤ 0.05 [70,72,73]. To verify the reliability of the results of leaves and roots transcriptome sequencing, qRT-PCR was carried out on 5 genes related to low nitrogen in roots and leaves, respectively. The first strand of cDNA was synthesized by the Goldenstar RT6 cDNA Synthesis Mix (Tsingke, Wuhan, China) kit, and qRT-PCR was carried out by using instrument QuantStudioTM 1 Plus (ABI, Carlsbad, CA, USA) and 2 × T5 Fast qPCR Mix (SYBR Green I) (Tsingke, Wuhan, China) kits. The relative expression of each gene was calculated by the 2–ΔΔC method [74], and the internal reference was HvActin (NCBI key number: AY145451) [75]. As indicated by the analyses of RNA-seq and metabolites of W26 and W20 under low nitrogen, there were great differences in LN and RN among barley genotypes with different NUEs. Under low nitrogen, the differential genes and DAMs of the two genotypes were obviously enriched in GSH metabolism, which could be related to the regulation of GSH. The transporters of the NRT and AMT genes; the NR, NIR, GS, and GDH genes; and the GOGAT genes were also selected in the main pathways of nitrogen metabolism, including the genes of tolerance to low nitrogen stress. Among them, some of the genes had no concern with varieties, showed the same upward and downward trends in the two genotypes, and could also be called core genes of tolerance to low nitrogen. This study provides a theoretical basis for further understanding the complex metabolic process of barley under low nitrogen stress. The functional verification of candidate genes for nitrogen-efficient utilization will continue to be carried out in the future, which will improve NUE in crops.

PMC10003241

Oxana Lungu,Denise Toscani,Jessica Burroughs-Garcia,Nicola Giuliani

The Metabolic Features of Osteoblasts: Implications for Multiple Myeloma (MM) Bone Disease

03-03-2023

osteoblasts,metabolism,glutamine,multiple myeloma,bone disease

The study of osteoblast (OB) metabolism has recently received increased attention due to the considerable amount of energy used during the bone remodeling process. In addition to glucose, the main nutrient for the osteoblast lineages, recent data highlight the importance of amino acid and fatty acid metabolism in providing the fuel necessary for the proper functioning of OBs. Among the amino acids, it has been reported that OBs are largely dependent on glutamine (Gln) for their differentiation and activity. In this review, we describe the main metabolic pathways governing OBs’ fate and functions, both in physiological and pathological malignant conditions. In particular, we focus on multiple myeloma (MM) bone disease, which is characterized by a severe imbalance in OB differentiation due to the presence of malignant plasma cells into the bone microenvironment. Here, we describe the most important metabolic alterations involved in the inhibition of OB formation and activity in MM patients.

The Metabolic Features of Osteoblasts: Implications for Multiple Myeloma (MM) Bone Disease The study of osteoblast (OB) metabolism has recently received increased attention due to the considerable amount of energy used during the bone remodeling process. In addition to glucose, the main nutrient for the osteoblast lineages, recent data highlight the importance of amino acid and fatty acid metabolism in providing the fuel necessary for the proper functioning of OBs. Among the amino acids, it has been reported that OBs are largely dependent on glutamine (Gln) for their differentiation and activity. In this review, we describe the main metabolic pathways governing OBs’ fate and functions, both in physiological and pathological malignant conditions. In particular, we focus on multiple myeloma (MM) bone disease, which is characterized by a severe imbalance in OB differentiation due to the presence of malignant plasma cells into the bone microenvironment. Here, we describe the most important metabolic alterations involved in the inhibition of OB formation and activity in MM patients. Osteoblasts (OBs) are bone-forming cells that originate from multipotent mesenchymal stem cells (MSCs) located in the bone marrow (BM). OBs are essential for skeletal development and fracture repair as they are the only cells able to form new bone in vertebrates [1]. Their differentiation from MSCs is triggered by the expression of specific genes, which are subsequentially regulated by pro-osteogenic pathways, including the wingless/int1 (WNT)/β-catenin signaling pathway and runt-related transcription factor 2 (RUNX2) [2]. Once differentiated, mature OBs can become osteocytes, which are incorporated into the bone matrix [3]. During bone remodeling, OBs cooperate with osteoclasts (OCs) to ensure that bone formation is coupled with bone resorption [4]. Given their primary role in maintaining bone integrity and health, OBs need a substantial amount of energy. Glucose represents one of the main fuels that sustain energy production, mainly through glycolysis, although metabolic plasticity features characterize OB differentiation [5]. In addition to glucose, fatty acids and amino acids are additional sources to sustain energy metabolism in OBs. Studies into amino acid metabolism have received high attention, in particular those regarding glutamine (Gln). This non-essential amino acid represents one of the main fuels for OBs since its uptake and metabolism increase during OB differentiation [1,6,7]. Several Gln transporters and enzymes have been implicated in the regulation of bone formation, opening a new potential therapeutic scenario for malignant bone-related diseases. Among these, multiple myeloma (MM) represents the main hematological malignancy condition characterized by severe uncoupled and unbalanced bone remodeling [8]. In this context, malignant plasma cells (PCs) accumulate and proliferate in the bone marrow, disrupting the physiological bone remodeling process, leading to impaired OB differentiation and osteolytic lesions. Recent studies highlight the importance of the alterations of MM metabolism in controlling OB functions within the microenvironment. In particular, the Gln-deprived microenvironment characteristic of MM inhibits the OB differentiation of MSC by altering the expression of OB markers, pointing to a clear involvement of amino acid metabolism in MM bone disease [7]. Here, we discuss the main pathways involved in OB differentiation in physiological conditions and the involvement of glucose, fatty acids, and amino acids in sustaining their bioenergetic demand and differentiation. Additionally, we focus on the involvement of OBs in bone disease, with a special emphasis on MM, and the main metabolic alterations responsible for their dysregulation in MM bone disease. The BM niche is a synergetic network of several cellular populations that supports the hematopoietic stem cells (HSCs). In 1968, Friedenstein et al. demonstrated that not only HSCs but also MSCs reside in the BM [9]. MSCs are multipotent cells characterized by the ability to give rise to OBs, adipocytes, or chondrocytes [10]. The OBs play a crucial role in the formation and preservation of the bone architecture; these cells are responsible for the deposition of bone matrix and the regulation of OCs. During the course of development, OBs can have three possible fates: they can become a bone-lining cell or an osteocyte, or undergo apoptosis [3]. The osteoblastic differentiation process is deeply controlled by numerous molecular factors present in the BM microenvironment, and it occurs in a specific chronological sequence. The pathways and factors principally involved in osteoblastic differentiation will be outlined below. RUNX2 is the main transcription factor crucial for OB differentiation. It belongs to the RUNX family, which consists of RUNX1, RUNX2, and RUNX3 [11]. In OB precursors, RUNX2 interacts with CBFβ, a co-transcription factor, and regulates the expression of osterix (OSX), as well as that of bone matrix genes including type I collagen (COL1A1), COL1A2, osteopontin (OPN), bone sialoprotein (BSP), and osteocalcin (BGLAP2), inducing OB maturation [12]. Furthermore, RUNX2 enhances osteoblastogenesis by modulating the expression of the hedgehog (HH) signaling pathway, fibroblast growth factor (FGF), WNT pathway, parathyroid hormone (PTH), and distal-less homeobox 5 (DLX5) genes [13]. Therefore, RUNX2 is a key cross-functional transcription factor, and CBFβ regulates bone structure by modulating the stability and activity of RUNX family proteins. It has also been reported that the interaction of RUNX2 and transforming growth factor-beta (TGF-β)/bone morphogenic protein (BMP) signaling induces the expression of OB-specific genes [14]. Signal transduction by TGF-β/BMPs occurs through canonical SMAD-dependent pathways (TGF-β/BMP ligands, receptors, and SMAD) and non-canonical SMAD-independent signaling pathways (the p38 mitogen-activated protein kinase, MAPK pathway) [15]. The binding of BMPs to their receptors determines the phosphorylation of SMAD1, SMAD5, or SMAD8, which, forming a complex with SMAD4, enter the nucleus and regulate gene expression, improving the function of mature OBs. BMP-2 significantly increases osteocalcin levels, while BMP-7 induces the expression of osteoblastic markers, such as alkaline phosphatase (ALP) activity, and increases calcium mineralization [16]. WNT-family proteins secreted by cells can induce cellular mechanisms through the activation of a trans-membrane complex composed of FZD (frizzled) receptors and LRP5/6 co-receptors. Once the pathway is activated, intracellular proteins and transcription factors regulate proliferation, migration, and gene expression [17]. WNTs stimulate at least three distinct signaling cascades: the canonical WNT/β-catenin pathway and two β-catenin independent non-canonical pathways (WNT/Ca2+ and WNT/planar polarization) [18]. Among these, the canonical pathway is of high relevance in osteoblastic differentiation. β-Catenin inactivation results from ubiquitination and proteosomal degradation due to a lack of binding between WNT proteins and the FZD receptor. The activation of the pathway, on the other hand, promotes β-catenin accumulation in the cytoplasm by inhibiting the formation of the degradation complex. β-catenin next translocates into the nucleus where it regulates and induces the expression of several genes involved in OB differentiation [19]. Furthermore, WNT/β-catenin signaling promotes the expression of osteoprotegerin (OPG) in mature OBs, which in turn suppresses osteoclastogenesis [20]. Sclerostin, encoded by the SOST gene, inhibits canonical WNT signaling by binding to LRP5/6 and preventing it from binding to the FZD receptor [21]. It is widely expressed by osteocytes and negatively regulates the differentiation and function of OBs. Indeed, mutations in the SOST gene generate sclerosing bone disorders such as sclerosteosis and Van Buchem disease [22]. Dickkopf-1 (DKK-1) is another WNT signaling antagonist that is highly expressed in bone tissue and, by binding to the LRP5/6 receptor, leads to the internalization of the complex and inhibition of cell signaling [23]. The intricate interaction between these components leads to the regulation of RUNX2 and OSX expression while inhibiting the expression of adipogenic transcription factors and blocking preadipocyte differentiation [24]. In addition to the other factors described above, PTH, produced by parathyroid gland cells, also influences OB differentiation through the stimulation of proteins involved in bone formation, such as insulin-like growth factor (IGF-1), FGF-2, and WNT/β-catenin. Besides increasing the number of OBs, PTH also promotes higher matrix deposition and suppresses apoptosis. The main PTH-stimulated physiological pathway involves the activation of the PTH1 receptor (PTH1R) and further stimulation of cAMP, which brings about the phosphorylation and activation of protein kinase A (PKA) [25]. NOTCH activation in the early stages of OB differentiation reduces the maturation of cells able to synthesize a mineralized matrix, while its induction in mature cells prevents further differentiation and results in an accumulation of abnormal OBs [26]. These effects are most likely mediated by the downregulation of RUNX2 transcription and decreased WNT signaling. Indeed, it has been shown that in cells overexpressing NOTCH, cytosolic β-catenin levels and the stimulation of ALP activity by WNT3 are suppressed by NOTCH [27]. While some studies report that NOTCH signaling inhibits OB formation [27,28], others suggest opposite phenotype [29]. FGF signaling has different roles in OB lineage cells. FGFs have both autocrine and paracrine functions on tumor and stromal cells, and by binding tyrosine kinase receptors (FGFRs), they activate multiple signaling pathways, including RAS-MAPK, PI3K-AKT, and canonical WNT signaling [30]. These pathways regulate pre-osteoblastic proliferation and osteoblastic differentiation, including the function of mature OBs [31]. An overview of the main signaling pathway involved in OB differentiation is reported in Figure 1. Bone is a metabolically active connective tissue presenting four types of cells: OBs (cells that form new bone), bone-lining cells that cover the surface of bone, osteocytes, and OCs (cells that destroy bone). Its function is to ensure the shape, protection, and sustenance of body structures and to facilitate locomotion [4]. Bone is mostly composed of hydroxyapatite crystals and several types of extracellular matrix proteins, including COL1A1, osteocalcin, osteonectin, secreted phosphoprotein 1 (SPP1), Integrin-Binding Sialoprotein (IBSP) and proteoglycans. Most of these bone matrix proteins are secreted and deposited by polarized mature OBs [32]. The combined activity of the cells listed above forms the temporary anatomical structure called the Basic Multicellular Unit (BMU). Within the BMU, cellular activity is coupled, which means that the amount of bone destroyed by OCs is equal to the amount of bone formed by OBs. Osteocytes, which are former OBs distributed throughout the mineralized bone matrix, perceive and react to mechanical and hormonal stimuli and coordinate the function of OBs and OCs [33]. Bone remodeling is a continuous cycle that occurs at targeted sites in the skeleton due to mechanical and metabolic influences. The cycle begins with the formation and activation of OCs that mediate bone resorption; this process is followed by a long period of OB-mediated bone matrix formation, culminating in matrix mineralization [34] (Figure 2). The process starts with the recruitment of hemopoietic myelomonocytic precursors by chemotactic cytokines released from nearby cells. Monocyte chemoattractant protein-1 (MCP-1, also known as CCL2) is secreted by OBs and is one of the most important cytokines in the recruitment of OC precursors [35]. Another chemokine produced by bone vascular endothelial cells and BM stromal cells, stromal cell-derived factor 1 (SDF-1), binds to OC precursors expressing the chemokine receptor CXCR4 and induces the expression of matrix metallopeptidase 9 (MMP-9) since the collagen-rich bone matrix is degraded by proteases such as cathepsin K and matrix metalloproteinases [36]. The osteoclastogenic factors expressed by OB lineage cells include receptor activator of nuclear factor-B ligand (RANKL) and macrophage colony-stimulating factor (M-CSF). RANKL interacts with its monocyte-expressed RANK receptor, inducing the activation of tumor necrosis factor (TNF) receptor-associated factor 6 (TRAF6). In turn, TRAF6 stimulates NF-ĸB and MAPKs, such as p38, which are responsible for the activation of transcription factors such as AP-1 (c-Fos) and NFATc1 [37]. Furthermore, OBs are involved in the regulation of osteoclastogenesis through modulation of the RANKL/OPG ratio. Indeed, OBs synthesize OPG, a soluble decoy receptor for RANKL, which is involved in the competitive inhibition of RANK/RANKL signaling, thereby preventing RANK and OC activation in several bone remodeling diseases [38]. Osteocytes are the cells that probably determine which bone surface will be resorbed by OCs. They are interconnected in the bone matrix through a network of osteocyte canaliculi-containing osteocyte dendritic processes [39]. It has been proposed that microfractures and loss of mechanical loading in bone are first detected by osteocytes, which then trigger OC differentiation [40]. During the transition phase, also known as the reversal phase, bone resorption is coupled with bone formation. OCs stimulate the differentiation of OBs, thus enabling bone growth in the gaps of bone resorption. While bone formation is activated, the high amount of extracellular calcium released during resorption induces the apoptosis of OCs via Bim/caspase-3 or through the Fas/Fas ligand pathway [41]. In addition, connexin-mediated communication between OBs stimulates the differentiation and activation of OBs themselves. The presence of connexin was also observed in OCs. These data suggest that due to the presence of gap junctions between OCs and OBs, intercellular communication can happen while the cells are next to each other [42]. OC–OB communication can also occur without cell–to-cell contact. Indeed, following resorption, growth factors such as TGF-β, BMPs and IGF-II are released from the bone matrix, activating osteoblastic bone formation [43]. New bone formation can be described in two stages: first, OBs form and secrete an osteoid matrix rich in COL1; second, OBs regulate osteoid mineralization [44]. During the mineralization, hydroxyapatite crystals are settled between collagen fibrils. This process is complicated, and how it is controlled is not completely comprehended [44]. New bone formation is regulated by the local and systemic phosphate/calcium levels and by inhibitors of mineralization, including pyrophosphate and non-collagenous proteins such as SPP1 [45]. Tissue non-specific ALP and ectonucleotide pyrophosphatase activities are the main factors that determine the inorganic pyrophosphate to phosphate ratio, which represents a key regulator of mineralization [45]. Once mineralization is over, OBs undergo apoptosis, become bone-lining cells, or remain trapped in the bone matrix and terminally differentiate into osteocytes. Osteocytes play a key role in signaling the end of remodeling through the secretion of osteogenesis antagonists, particularly WNT signaling pathway antagonists, such as sclerostin [46]. The most important pathways that determine the balance between resorption and bone formation are RANKL/RANK/OPG [47] and WNT signaling [48]. An altered expression of RANKL and OPG is a driving mechanism behind bone metastasis [49], cancer treatment-induced bone loss, and osteolysis in patients with MM [50]. At this terminal stage, OC differentiation is suppressed, probably through OPG produced by OBs. OC–OB interaction may induce NOTCH signaling in OBs, resulting in increased OPG production that inhibits RANK signaling and, thus, osteoclastogenesis [51]. In conclusion, communication between OBs and OCs at various stages of their differentiation is crucial for bone remodeling cycles. The beginning of fusion, attachment, activity, and apoptosis in OCs is controlled by cells of the OB lineage, including lining cells, pre-OB, and osteocytes. On the other hand, OCs control the level of OB activity through the release of factors within the matrix. Thus, it is through these complex intercellular communication pathways that bone can respond effectively to hormonal, mechanical, and inflammatory stimuli, providing a strong and versatile structure for the human body. The efficient functioning of OBs needs considerable energy production, particularly during stages of new bone formation and remodeling. In humans, the remodeling process requires about 120 days, and the bones of the skeleton are completely remodeled every 10 years [52]. Bone mass preservation during the remodeling process is crucial for skeletal strength and calcium homeostasis. Since both modeling and remodeling processes necessitate the synthesis of collagen and various matrix proteins by OBs, they use a considerable amount of energy in the form of adenosine triphosphate (ATP) [52]. Very early studies showed that an increased number of mitochondria characterized mature OBs [53,54]. Later, several papers demonstrated OBs’ metabolic plasticity with increased ATP production during differentiation [5]. Recent studies have revealed that the WNT pathway directly reprograms cellular metabolism by stimulating aerobic glycolysis, fatty acid oxidation, and Gln catabolism in OB lineage cells [55]. WNT-mammalian target of rapamycin complex-1 (mTOR) signaling increases protein levels of key enzymes implicated in glucose and Gln metabolism [55]. Furthermore, mRNA levels for genes implicated in fatty acid oxidation increased in response to β-catenin activation [52]. In the next paragraphs, we will provide an overview of the main metabolic pathways regulating OB functions (Figure 3). One of the most significant fuel substrates for OBs is glucose. It is carried into cells via glucose transporters (GLUTs) in a process known as facilitated diffusion that does not consume energy. [56]. In OBs, glucose transporter 1 (GLUT1), encoded by SLC2A1, appears to be the major glucose transporter, although GLUT3 and GLUT4 are also expressed [57]. Glucose transport through GLUT1 has been seen to stimulate the differentiation of OBs and, consequently, bone formation by blocking the proteasomal degradation of RUNX2 [58] and by stimulating mTORC1-mediated protein synthesis to enhance collagen matrix production [59]. In fact, a GLUT1-deficient mouse model in osteolineage cells showed altered OB differentiation and formation compared to wild-type animals [58]. Once internalized by the cell, the enzyme hexokinase (HK) phosphorylates glucose to form glucose-6-phosphate (G6P). Next, G6P can be catabolized through multiple pathways, such as glycolysis, the hexosamine biosynthetic pathway (HBP), and the pentose phosphate pathway (PPP) [60]. Via glycolysis, one molecule of glucose is converted into two molecules of pyruvate and two of adenosine triphosphate (ATP). Pyruvate is transported to the mitochondrion, where it is decarboxylated and oxidized to acetyl-CoA. Acetyl-CoA subsequently enters the tricarboxylic acid cycle (TCA) for mitochondrial respiration. Throughout this multistep process, three moles of NADH and one mole of FADH2 are generated. Such molecules are required to supplement oxidative phosphorylation (OXPHOS) and guide the electron transport chain, leading to ATP formation [61]. As stated before, during differentiation, OBs and their progenitors undergo profound energetic reprogramming. Guntur et al. showed that mouse OB progenitors mainly rely on glycolysis to generate ATP, while oxidative phosphorylation is preferred after the onset of differentiation and matrix production. After mineralization, mature OBs prefer glycolysis [5]. Supporting these observations, metabolic tracing studies revealed that in mature OBs, most of the glucose is converted to lactate and ATP is generated mostly via glycolysis [62,63]. The reason why OBs choose aerobic glycolysis is currently not fully comprehended. From a bioenergetic point of view, aerobic glycolysis has a lower efficiency in terms of ATP production than metabolism via TCA and OXPHOS [64]. Tumor cells show related metabolic reprogramming, known as the Warburg Effect, which is supposed to provide amino acids, nucleotides, and lipids necessary to sustain cell division. Furthermore, enhanced aerobic glycolysis could help reduce reactive oxygen species and also contribute to the generation of more amino acids to support protein synthesis in OBs [65]. WNT3A/LRP5 signaling contributes to the regulation of OB metabolism by stimulating aerobic glycolysis, a mechanism mediated by mTORC2-AKT signaling but independent from β-catenin [62]. Moreover, the metabolic rewiring seems necessary for OB differentiation since glucose shortage impairs differentiation in response to WNT3A [62]. PTH/PTHR1 signaling promotes bone anabolism by stimulating the expression of glycolytic enzymes and aerobic glycolysis. This mechanism is mediated by the IGF/mTOR pathway, which plays an essential role in bone metabolism [66]. Interestingly, the inhibition of glycolysis reduces the anabolic effect of PTH in mice [66], providing a possible link between bone metabolism and the anabolic effect of PTH. Conversely, the NOTCH pathway restricts OB differentiation by inhibiting the expression of enzymes involved in the glycolysis pathway and mitochondrial respiration in primary mesenchymal progenitors, resulting in decreased mitochondrial respiration and AMPK activity [67]. Until now, only a few signaling pathways have been proposed to regulate the energy metabolism of OBs such as HH, IGF1, and BMP. In particular, HH, by inducing IGFs, stimulates OB differentiation and mTORC/AKT signaling, thus providing a possible link between OB differentiation and energy metabolism [68]. Many BMP molecules have been implicated in the regulation of glucose metabolism by increasing glucose uptake and utilization. More importantly, BMPs indirectly control glucose metabolism by regulating the WNT, PTH, and mTOR pathways [69]. BM fat can occupy about 70% of the available bone volume in healthy adults. This suggests that fatty acids released from triglycerides stored in the marrow may be an important source of energy to meet the energetic demands of bone formation [70]. Lipids can be acquired as free fatty acids taken up by cell surface transporters or as lipoprotein particles bound by members of the LDL receptor family. Once inside the cell, the fatty acids are transported to the mitochondria via a shuttle formed by carnitine palmitoyltransferase 1 (CPT1) situated on the outer mitochondrial membrane and CPT2 placed on the inner membrane [71]. Fatty acids are metabolized in the mitochondrial matrix via β-oxidation, which sequentially cleaves two carbons as acetyl-CoA, which then enters the TCA cycle [72]. Fatty acid oxidation provides more energy than that produced by glucose or amino acid metabolism. Compared to glycose, few studies have investigated the role of fatty acid metabolism in OBs. Several groups demonstrated that β-oxidation contributes to ATP production in bone tissue [73,74] and that the expression of CPT1 increases during OB differentiation [75]. Indeed, the inhibition of CPT1 reduces OB differentiation in vitro and bone healing in vivo. Recently, van Gastel et al. [76] showed that the scarcity of fatty acids stimulates chondrocyte differentiation rather than OB differentiation. On the contrary, when fatty acids are present, skeletal progenitors are stimulated to undergo OB differentiation, reflecting the different metabolic state of OBs compared to chondrocytes [76]. It has also been demonstrated that fatty acid utilization by OBs is under the control of WNT-LRP5 signaling. Mutant mice with LRP5 deletion have been shown to have reduced bone mass and increased fat mass and triglyceride levels, suggesting deficient fatty acid catabolism. In fact, the expression of various enzymes of β-oxidation was reduced in primary OBs in LRP5-deficient mice but increased in primary OBs expressing a variant of LRP5 (LRP5G171V) associated with increased bone mass [77]. Further studies in OB-specific β-catenin-deficient mice suggested that WNT signaling controls fatty acid catabolism through the canonical WNT-β-catenin pathway [78]. Amino acids can be used by OBs for protein synthesis, or they can be metabolized to generate energy in the form of ATP. According to their catabolic pathway, ketogenic amino acids are degraded into acetyl-CoA or acetoacetate, while glucogenic amino acids are decomposed into pyruvate or various TCA intermediates [79]. Consequently, amino acids can directly support ATP production through the TCA cycle and OXPHOS. Gln, which is a nonessential amino acid (NEAA) mostly synthesized by the enzyme Gln synthetase (GS) utilizing glutamate (Glu) and ammonia (NH3) as sources, has emerged as an important regulator of OBs as the enhanced matrix synthesis associated with bone formation raises the requirement for amino acids [80]. Gln has multiple functions in cellular metabolism, from participation in the TCA cycle to the biosynthesis of nucleotides, glutathione (GSH), and NEAA [80]. It is carried into the cells via plasma-membrane Gln transporters, including SLC1A5 (ASCT2), SLC7A7, and SLC38A2 (SNAT2) [6,7]. Under normal conditions, OBs take up Gln mainly through SLC1A5, a Na+-dependent transporter that can also carry asparagine, serine, threonine, and alanine [81]. Throughout the proliferation phase, OBs’ Gln uptake is controlled by the general control non-depressible 2 (GCN2) mechanism. Under conditions of high-protein synthesis such as OB proliferation and matrix production, the alpha subunit of eukaryotic translation initiation factor 2 (eIF2α) is phosphorylated by GCN2. As a result, this causes an enhanced translation of the transcription factor ATF4, which promotes the expression of amino acid transporters, including SLC1A5 [82]. Once in the cell, the enzyme glutaminase 1 (GLS1) converts Gln to Glu, releasing ammonium ions. Glu can then be used for GSH biosynthesis, an antioxidant that protects cells from oxidative damage, or can be metabolized to alpha-ketoglutarate (α-KG) by Glu dehydrogenase 1 (GLUD1 or GDH1) [83]. α-KG then enters the TCA cycle and supports the OXPHOS pathway or the reductive carboxylation pathway [84]. In addition, Glu can be recruited from the extracellular compartment through the SLC1A3 transporter [85]. Besides the SLC1A3 transporter, OBs express N-methyl-D-aspartate Glu receptor (NMDAR). In vitro studies have shown that Glu can stimulate OB differentiation via NMDA or α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors [86]. GLS inhibition using the Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide (BPTES) significantly reduced intracellular Glu and αKG, but had no impact on other products of Gln metabolism, suggesting that Gln carbon is mainly used to provide αKG, which is involved in amino acid biosynthesis in skeletal stem cells (SSCs) [1]. BM stromal cells (BMSCs) consume a large quantity of Gln when they differentiate into OBs, but not into adipocytes. It has been reported that Gln increases the activity of GLS and GDH via the mTOR/S6 and MAPK signaling pathways, thereby promoting cell proliferation [87]. Furthermore, the WNT/mTORC1 pathway promotes the expression of genes involved in protein anabolism. The mTORC1-mediated increase in protein synthesis leads to higher uptake of Gln to generate more energy through the TCA cycle in order to overcome the energy deficit that occurs during OB differentiation [88]. The activation of β-catenin by WNT stimulates Gln transport via SLC7A7, while mTORC1 controls basal Gln uptake by SLC1A5 [6]. Since the OB progenitors proliferate rapidly into mature OBs able to synthesize bone matrix, the differentiation process is characterized by the increased consumption of Gln. Indeed, it has been seen that when OBs are stimulated to mineralize, glucose is not sufficient to meet their energy requirements. Only when cells are supplemented with glucose and Gln does the degree of mineralization increase [89]. Additionally, the genetic inhibition of Gln metabolism in SSCs has been shown to lead to a reduction in bone mass due to a decrease in OBs, and GLS-deficient OBs exhibit reduced bone formation [1]. Interestingly, the administration of PTH stimulates Gln uptake by inducing SLC1A5 and GLS1-dependent Gln catabolism in mice. The genetic deletion of GLS1 in mice inhibits the bone anabolic effect of PTH. Beyond Gln, some other amino acids are implicated in supporting the elevated anabolic demands of OBs. A recent study reported an important role for the NEAA proline (Pro). Most of the Pro is taken up via SLC38A2 and incorporated directly into OB-associated proteins, such as RUNX2, OSX, and COL1Al [90]. Its consumption has been demonstrated to increase during osteogenic differentiation, while the deletion of SLC38A2 in OSX-expressing cells has a negative impact on OB differentiation and bone development [90]. Another amino acid implicated in protein synthesis and the regulation of gene expression is methionine. The dietary restriction of this essential amino acid (EAA) has been seen to negatively impact bone properties, particularly OB differentiation [91]. However, the mechanism of these metabolic abnormalities has yet to be elucidated. Arginine (Arg) is a conditional EAA that can be taken up mainly through the SLC7 transporters. Arg is implicated in the synthesis of nitric oxide (NO), which consequently increases glycolysis and OB differentiation. In addition, the loss of arginosuccinate lyase (ASL) in OBs, an enzyme that generates Arg and fumarate, causes a reduction in bone mass [92]. The tryptophan degradation pathway produces kynurenine metabolites that are related to bone mass loss in patients with osteoporosis. Indeed, kynurenine administration in adult mice has been seen to reduce bone mass [93,94]. All these studies indicate that OBs and progenitors use different amino acids in their metabolism to support anabolic functions during bone formation and mineralization. To ensure that there is no alteration in bone mass or quality after each remodeling cycle, healthy bone remodeling needs close coupling between resorption and bone formation. Still, this essential physiological process can be hindered by multiple events, such as hormonal fluctuations associated with menopause, alterations in physical activity, drugs, age-related factors, and secondary diseases [95]. Osteoporosis is by far the most widespread disorder of bone remodeling. The pathogenesis of osteoporosis in women involves increased bone resorption resulting from changes in estrogen and FSH levels at menopause and decreased bone formation caused by a variety of factors associated with the aging process [96]. In addition to secondary forms of osteoporosis, hematologic malignancy as MM plays a very significant part. The effects of hematologic diseases on bone are not only due to the physical relationship between BM cells and bone, but also to a wide range of circulating factors that can affect bone turnover, increasing the activity of OCs and reducing OBs activity [8]. MM represents the most important pathological condition that exhibit a negative impact on bone remodeling process [8]. Osteolytic bone disease is a main feature of MM leading to bone pain, skeletal-related events and, subsequently, decreased quality of life. The proliferation of malignant PCs into the BM alters the bone remodeling process, leading to uncoupled and unbalanced bone formation and resorption [97]. Both soluble factors and physical interactions are responsible for the altered bone remodeling in MM. Cell-to-cell contact between MM and BM microenvironment cells leads to enhanced production by BMSC of the osteoclastogenic factor RANKL and decreased releases of its decoy receptor OPG. As a result, the BM of MM patients is characterized by an increased RANKL/OPG ratio and enhanced OC activation. Other factors favoring osteoclastogenesis are increased into the BM by MM cells, such as chemokine (C-C motif) ligand (CCL)-3, interleukin (IL)-1, IL-3, IL-6, activin A, and TNFα [98]. Simultaneously, the alterations of bone resorption promote the growth of malignant PCs, supporting the vicious cycle within bone niche. MM–stromal cell interactions also impair OB formation by reducing the activity of RUNX2 in human OB progenitors [99]. Other molecules, such as IL-7 and hepatocyte growth factor (HGF), reduce RUNX2 activity contributing to OB impairment [100,101]. In the next paragraph, we will describe the main mechanisms responsible for OB suppression in MM and the metabolic implications for bone disease. The impaired osteoblastic function in MM derives mainly from the inhibition of osteogenic differentiation of mesenchymal progenitors into mature OBs. Several studies have reported that bone remodeling in MM is uncoupled and unbalanced, with an increase in OC activation and, consequently, enhanced bone resorption and a decrease in bone formation caused by a reduction in the number and activity of OBs [102]. In addition, patients with MM have low levels of bone formation markers such as ALP and osteocalcin, while MM patients without bone disease exhibit balanced bone remodeling with normal OC differentiation and bone formation [98]. The main mechanism behind the OB suppression by myeloma cells is the inhibition of RUNX2 activity and expression. RUNX2 regulates the expression of various factors produced by OBs at different steps of maturation, including DKK1, WNT10, OPN, TGF-β1, BMP-4, RANKL, and OPG [103]. RUNX2 inhibition is mediated in part by cell-to-cell contact between MM cells and OB progenitors and in part by soluble molecules produced by MM cells [104]. Adhesive interactions between malignant PCs and BMSCs are mediated by VLA-4 (α4β1 integrin) on MM cells and VCAM-1 present on BMSCs [105], while soluble factors include soluble crest-related protein (sFRP), DKK1, CCL-3, IL-7, activin A, and TNF-α. It has been demonstrated that OB-RUNX2 deficiency induced by soluble factors released by MM cells can fuel the dissemination and progression of MM cells. Mechanistic studies have shown that OB-RUNX2 deficiency generates a highly chemoattractive and immunosuppressive BM microenvironment, which is responsible for the recruitment and progression of MM cells to new bone sites [106]. Moreover, malignant PCs secrete WNT inhibitors that are involved in the development of osteolytic lesions by affecting OB differentiation [107,108]. Besides sclerostin and DKK1, other suppressors of the WNT signaling are secreted by MM cells. These include sFRP-2/3, which are produced by both MM cell lines, and most primary MM cells [109]. Sclerostin, by binding to the extracellular domain of LRP5/6 receptors, inhibits the canonical WNT pathway. As a result, β-catenin phosphorylated by a multiprotein destruction complex, in particular by GSK-3β, is degraded by proteasomal ubiquitination. Furthermore, it increases apoptosis in mature OBs by triggering the caspase pathway, resulting in the inhibition of bone formation and mineralization [110,111]. It was also demonstrated that the complete deletion of the SOST gene in immunocompromised SCID mice suppressed the evolution of MM-induced osteolytic lesions [112]. DKK1 is a protein belonging to the DKK family that plays a key modulatory role in bone disease in MM [113]. It is an antagonist of the WNT pathway and has a significant role in osteoblastogenesis and bone formation. DKK1 binds to LRP5/6 and the transmembrane protein Kremen1/2 to form a complex that results in LRP internalization, inhibiting the activation of the canonical WNT/β-catenin pathway [114]. It also impairs BMSCs’ differentiation into mature OBs by suppressing WNT autocrine signaling, which is required for BMP-2-mediated OB differentiation [115]. In turn, undifferentiated BMSCs release interleukin-6 (IL-6), which promotes PC growth in MM [116]. DKK1 operates synergistically with sclerostin; it deregulates the WNT pathway-mediated production of RANKL and OPG, leading to an increase in the RANKL/OPG ratio; consequently, osteoclastogenesis is indirectly enhanced [117]. Activin A, a protein belonging to the TGF-β family, recognizes the transmembrane receptor type II serine/threonine kinase (ActRIIA/B) and induces the activation of the SMAD signaling cascade, leading to the translocation of the SMAD2/3/4 complex into the nucleus. Activin A is a transcriptional factor that regulates cell proliferation, differentiation, apoptosis, and metabolism [118]. High-circulating levels of activin A have been linked to MM progression and a poor prognosis [119]. It has been observed that the communication between BMSCs and MM cells is responsible for the secretion of activin A, which exerts its inhibitory effects on OBs via the downregulation of the transcription factor DLX5 in OB precursor cells [120]. Among the soluble factors, IL-7 and CCL-3 derived from MM cells are responsible for the inhibition of OB formation through the downregulation of RUNX2 and OSX, respectively. Moreover, CCL-3 supports the survival and the homing process of MM cells into the BM niche [100,121]. Beyond the pathways involved in the osteoblastic inhibition described above, metabolic alterations in the BM microenvironment also play a crucial role in OB activity in MM patients [122]. Glucose and Gln are known to be the two main nutrients used by cancer cells to meet their energy needs [123]. Recent data indicate that malignant PCs are Gln-addicted since the cells exhibit high levels of GLS and a lack of GS expression, a feature that makes the cells particularly dependent on extracellular Gln. This characteristic modifies the physiological levels of Gln in the microenvironment with a significant impact on bone remodeling, especially on OB differentiation [124]. Our group found that Gln depletion imposed by MM cells in patients’ BM compromises OB differentiation [7] (Figure 4). Analyzing the transport of Gln in MM cells and stromal cells, we saw that MM cells internalize a greater amount of Gln than stromal cells, resulting in a decrease in amino acids in the culture medium. Moreover, the differentiation potential of stromal cells decreases when they are cultured in a medium conditioned by MM and is restored by the addition of Gln. These observations suggest that MM cells generate a microenvironment characterized by low Gln levels that can affect the differentiation and activity of OBs. In fact, differentiated MSCs in the presence of a concentration of Gln mimicking the medullary plasma of patients with MM show a significant decrease in osteoblastic markers [7]. The molecular mechanism responsible for Gln’s effects is correlated with the induction of SNAT2 and GLS1 in MSCs, which are blunted by amino acid deprivation. In fact, the inhibition of GLS by CB-839 and SNAT2 using MeAIB impaired the expression of OB markers, suggesting the relevance of GLS and SLC38A2 transporter activity during osteoblastogenesis [7]. Additionally, in vitro characterization of the intracellular content of amino acids in differentiated MSC showed higher levels of the amino acid asparagine (Asn) than undifferentiated cells. Interestingly, the differentiation of OBs compromised by Gln deprivation has been reestablished by Asn integration. Analysis of the expression of asparagine synthase (ASNS), the enzyme responsible for the synthesis of Asn from Gln and aspartate (Asp), revealed an increase during differentiation, while its knockout induced a decrease in osteoblastic markers in the stromal cell line [7]. Mechanistically, Asn may be necessary to synthetize OB-specific proteins in Gln-depleted conditions. Moreover, it has been demonstrated that Asn favors the uptake of arginine and serine, thus inducing mTORC [125], which is known to stimulate OB differentiation. These data demonstrate that MM cells may hinder osteoblastogenesis by blocking mesenchymal Asn synthesis via Gln depletion, providing a possible metabolic mechanism behind OB inhibition in MM. Further studies are needed to elucidate the role of other amino acids in the MM bone microenvironment. Besides MM, the involvement of amino acid metabolism in bone homeostasis has been hypothesized in other models of bone disease. In particular, in osteoarthritis (OA), it has been demonstrated that Gln exerts positive effects on the recovery of fractured bones in standardized albino rats by achieving a positive nitrogen balance [126]. In addition, a combination of heat treatment and Gln administration has been shown to suppress OA progression in a rat model of OA [127]. Other than Gln, data indicate that L-tryptophan stimulates the proliferation of BMSCs by increasing the expression of osteocalcin and ALP. Previous studies on female rats have shown that tryptophan levels and tryptophan 2,3-dioxygenase (TDO) activity decrease in all tissues with age, correlating it with the reduction in bone mass associated with aging [128,129]. Other studies are needed to confirm the contribution of amino acid metabolism in the pathogenesis of bone-related diseases. In the last years, different studies have investigated the role of energetic metabolism in OBs in physiological and pathological conditions. The metabolic plasticity of OBs is essential for their normal functions during bone remodeling. To date, the best-characterized source of energy for OBs is the glucose used by the cells to fulfill their high energetic demand during differentiation. Less is known about how OBs utilize fatty acids and amino acids during bone formation. Gln represents the main modulator of OB functions by acting at different steps of differentiation. In turn, several osteogenic molecules, such as WNT and RUNX2, regulate both glucose and Gln metabolism by increasing their uptake and catabolism. Studies also provide interesting data on the involvement of other amino acids, such as proline, arginine, and glutamate, in bone formation, although the specific mechanism remains to be investigated. Interestingly, bone-related diseases provide important evidence for the role of amino acids in regulating OB differentiation. In particular, the metabolic alterations of Gln in the MM bone niche restrict OB differentiation and function by reducing the expression of Gln transporters and enzymes, as well as the synthesis of Gln-related amino acid ASN. Lastly, from a translational perspective, targeting amino acid metabolism could represent a potential strategy to prevent bone disease. Numerous attempts have been made to target GLS and ASCT2 in MM to reduce tumor burden [130,131]. However, the results need to be finalized in vivo, and the possible effect on bone cells remains to be determined. Indeed, the supplementation of specific amino acids has been shown to improve bone health in patients with bone loss disorders [132,133]. More translational research is needed to understand the mechanism of OB metabolism regulation and, more importantly, the effectiveness of metabolic-based therapy to stimulate bone formation in MM patients.

PMC10003244

Matanel Tfilin,Nikolai Gobshtis,David Fozailoff,Vadim E. Fraifeld,Gadi Turgeman

Polarized Anti-Inflammatory Mesenchymal Stem Cells Increase Hippocampal Neurogenesis and Improve Cognitive Function in Aged Mice

24-02-2023

mesenchymal stem cells (MSC),pituitary adenylate cyclase-activating peptide (PACAP),MSC2,systemic inflammation,aging,cognitive decline,hippocampal neurogenesis

Age-related decline in cognitive functions is associated with reduced hippocampal neurogenesis caused by changes in the systemic inflammatory milieu. Mesenchymal stem cells (MSC) are known for their immunomodulatory properties. Accordingly, MSC are a leading candidate for cell therapy and can be applied to alleviate inflammatory diseases as well as aging frailty via systemic delivery. Akin to immune cells, MSC can also polarize into pro-inflammatory MSC (MSC1) and anti-inflammatory MSC (MSC2) following activation of Toll-like receptor 4 (TLR4) and TLR3, respectively. In the present study, we apply pituitary adenylate cyclase-activating peptide (PACAP) to polarize bone-marrow-derived MSC towards an MSC2 phenotype. Indeed, we found that polarized anti-inflammatory MSC were able to reduce the plasma levels of aging related chemokines in aged mice (18-months old) and increased hippocampal neurogenesis following systemic administration. Similarly, aged mice treated with polarized MSC displayed improved cognitive function in the Morris water maze and Y-maze assays compared with vehicle- and naïve-MSC-treated mice. Changes in neurogenesis and Y-maze performance were negatively and significantly correlated with sICAM, CCL2 and CCL12 serum levels. We conclude that polarized PACAP-treated MSC present anti-inflammatory properties that can mitigate age-related changes in the systemic inflammatory milieu and, as a result, ameliorate age related cognitive decline.

Polarized Anti-Inflammatory Mesenchymal Stem Cells Increase Hippocampal Neurogenesis and Improve Cognitive Function in Aged Mice Age-related decline in cognitive functions is associated with reduced hippocampal neurogenesis caused by changes in the systemic inflammatory milieu. Mesenchymal stem cells (MSC) are known for their immunomodulatory properties. Accordingly, MSC are a leading candidate for cell therapy and can be applied to alleviate inflammatory diseases as well as aging frailty via systemic delivery. Akin to immune cells, MSC can also polarize into pro-inflammatory MSC (MSC1) and anti-inflammatory MSC (MSC2) following activation of Toll-like receptor 4 (TLR4) and TLR3, respectively. In the present study, we apply pituitary adenylate cyclase-activating peptide (PACAP) to polarize bone-marrow-derived MSC towards an MSC2 phenotype. Indeed, we found that polarized anti-inflammatory MSC were able to reduce the plasma levels of aging related chemokines in aged mice (18-months old) and increased hippocampal neurogenesis following systemic administration. Similarly, aged mice treated with polarized MSC displayed improved cognitive function in the Morris water maze and Y-maze assays compared with vehicle- and naïve-MSC-treated mice. Changes in neurogenesis and Y-maze performance were negatively and significantly correlated with sICAM, CCL2 and CCL12 serum levels. We conclude that polarized PACAP-treated MSC present anti-inflammatory properties that can mitigate age-related changes in the systemic inflammatory milieu and, as a result, ameliorate age related cognitive decline. Neurogenesis continues throughout life in the dentate gyrus of the hippocampus in many mammals examined thus far and, arguably, also in humans [1,2]. Neurogenesis is associated with spatial learning and memory, as well as other cognitive functions [2]. Consequently, age-related decline in cognitive functions is linked to reduced hippocampal neurogenesis, which, to a great extent, is caused by changes in the systemic inflammatory milieu [3]. Indeed, brain aging is associated with increased systemic levels of anti-neurogenic pro-inflammatory chemokines and cytokines such as CCL11, CCL12, CCL2, CCL19, b2-microglobulin, hepatoglobin and a decreased expression of pro-neurogenic factors such as GDF11 [4]. Thus, ameliorating these pro-inflammatory changes can potentially treat brain aging and related cognitive impairments [5]. Mesenchymal stem cells (MSC) are stromal cells found in a wide range of adult tissues and can be easily isolated and expanded from bone marrow and adipose tissue [6]. MSC are characterized by their ability to differentiate into various mesodermal cell lineages including bone, cartilage and adipose cells [7]. However, much of their therapeutic properties result from their secretome [8]. MSC are known modulators of the immune system and immune responses. MSC were shown to have direct immunosuppressive properties by inhibiting the activation and proliferation of effector T cells (Th1 and Th17) while increasing proliferation of regulatory T (Treg) cells via cell-to-cell contact and the secretion of various soluble factors [9,10]. The abundance of MSC mediators and proposed mechanisms suggests a reciprocal relationship in which MSC may be either immunosuppressors or immune activators [11,12,13]. Akin to immune cells, MSC can also polarize into pro-inflammatory MSC (MSC1) and anti-inflammatory MSC (MSC2) following activation of Toll-like receptor 4 (TLR4) or TLR3, respectively [14,15]. In the present study, we have found that treating MSC with the neuropeptide pituitary adenylate cyclase-activating peptide (PACAP) can polarize MSC towards MSC2-like phenotype. We hypothesized that administration of polarized MSC (pMSC) to aged mice could increase hippocampal neurogenesis and improve cognitive functions. Indeed, we have found that systemic administration of pMSC reduced serum levels of pro-ageing chemokines accompanied by beneficial effects on hippocampal neurogenesis and behavior. Expanded bone-marrow-derived MSC were cultured in vitro for 7 days in serum free medium supplemented with or without 20 nM PACAP (1–27). A one-week incubation of MSC with PACAP did not change the expression of cell surface MSC markers: PACAP-treated MSC expressed typical markers as we previously reported for naïve MSC [16]. In flow cytometry analysis murine MSC were found to be negative for CD45 (<8%) and CD11b (<5%) and positive for CD106 (>50%), CD29 (>80%), CD44 (>70%), CD73 (>60%) and sca-1 (>40%) (Figure 1A). Both naïve and PACAP-treated MSC expressed mRNA for vasoactive intestinal peptide -2 (VPAC2) but not for VPAC1 and PACAP receptor type-I (PAC1), the currently known receptors for PACAP (Figure 1B). Since polarization of MSC to MSC1 and MSC2 is achieved through TLR4 or TLR3 activation, respectively, we tested their relative gene expression in PACAP-treated MSC. PACAP treatment increased the gene expression ratio of TLR3 versus TLR4 compared to naïve non-treated MSC (Figure 1E). Conditioned medium harvested from the last 24 h of culture was assayed for cytokine secretion using the Proteome Profiler Mouse Cytokine Array Kit (R&D). As seen in Figure 2, the cytokine secretion profile differs between naïve and PACAP-treated MSC. In the PACAP-treated cells, the anti-inflammatory chemokines and cytokines IL-2, IL-3, IL-4, IL-27, IP10, IL-1ra, RANTES, SDF-1, CCL2(JE), CCL-1 (i-309), G-CSF and BLC were over-expressed, while the pro-inflammatory cytokines IL-17, IL-1a, IFN-ɣ and soluble ICAM-1 were downregulated (Figure 2). Among these cytokines, the increased expression of IP10 (CXCL10), RANTES, IL-1ra and IL-4 was previously demonstrated for MSC2 with an immunosuppressive phenotype [15]. Thus, PACAP-treated MSC display clear MSC2-like features. To assess whether polarized MSC indeed affect the systemic immunological environment associated with brain aging, polarized (PACAP-treated) MSC were injected (2 × 105 cells) into the tail vein of aged (18-months old) ICR mice. Three weeks later, serum cytokine levels were examined using the Proteome Profiler Mouse Cytokine Array kit. We noticed that polarized MSCs reduced the serum levels of the following chemokines: sICAM-1, CXCL12(SDF-1), CXCL1(KC), CCL2(MCP-1) all are known to be upregulated during aging. This reduction normalized plasma levels to that of normal young (3 months old) animals (Figure 3). Moreover, CCL12(MCP-5), a pro-aging chemokine [4], though not being increased in 18-month-old mice, was nevertheless reduced by the polarized MSC treatment (Figure 3). Similarly, CCL11(Eotaxin), another known pro-aging chemokine (Smith LK et al., 2017), showed a trend towards reduced levels following polarized MSC treatment (Figure 3). We further assessed whether polarized MSC influence the reduced hippocampal neurogenesis, one of the characteristics of brain aging. Three weeks following the administration of polarized MSC, but not of naïve MSC (2 × 105 cells i.v.), increased hippocampal neurogenesis was evident, as reflected by an increase in the number of DCX+ newly formed neurons in the granular cell layer of the dentate gyrus (Figure 4A). Additional staining for proliferating Ki67+ progenitors in the subgranular zone showed an increase in proliferating cells in aged male mice treated with both polarized MSC and naïve MSC (Figure 4B). Interestingly, inverse correlation was observed between sICAM-1 serum levels and the number of DCX+ cells (Pearson r = −0.8, p < 0.05, n = 7) and Ki67+ cells (Pearson r = −0.87, p < 0.05, n = 7) in the dentate gyrus of aged animals (Figure 4C,D). Finally, we tested the effect of polarized MSC systemic administration on behavior. Three days following the injection, mice were exposed to a series of behavioral assays. General locomotion activity assessed by the total distance traveled by the mice in the open field test was not found to differ between the different treatment groups (Figure 5A). Control non-treated aged mice displayed impaired spatial learning in the Morris water maze assay (Figure 5B). Over the 5-day assay, no statistically significant differences were detected in the latency durations obtained on days 2–5 compared with day 1 (repeated measures two-way ANOVA with Tukey’s multiple comparison test). However, in aged mice administered with polarized MSC, significant improvement was observed at days 4 and 5 of the assay (p < 0.05). A milder effect was noted in aged animals injected with naïve MSC, and while their improvement on day 5 was not significant compared with day 1, their scores on day 5 did not differ from the scores obtained by polarized MSC-treated animals. However, in the probe trial, MSC-treated animals displayed a significantly lower platform quadrant duration than animals treated with polarized MSC (Figure 5C). In the Y-maze paradigm, aged mice administered with polarized MSC demonstrated significantly better results, with an increased percentage of arm alterations, than did control aged or naïve-MSC-treated mice (Figure 5D). Notably, an inverse correlation was observed between aged mice performance in the Y-maze paradigm and plasma levels of the ‘pro-aging’ chemokines CCL2/MCP-1 (Pearson r = −0.806, p < 0.03, n = 7) and CCL12/MCP-5 (Pearson r = −0.804 p < 0.03, n = 7), corresponding with the putative influence of these plasma cytokines on hippocampal neurogenesis and cognitive functions (Figure 6). To determine the survival and distribution of naïve and polarized MSC following systemic administration, we injected 2 × 105 DiR labeled naïve and polarized MSC into the tail vein of 3-month-old ICR mice. Labeled cells were tracked in various organs following dissection using the Maestro imaging system at days 0, 1, 4, 7 and 14 after injection. Labeled cells were tracked in the lungs 2 h following injection (day 0) and maintained through day 7 (Figure 7A). From day 1 through 14, cells were also traced in the liver and brain (Figure 7B,C). Overall engraftment to the lungs was more prominent in pMSC than naïve MSC, peaking at day 7, while engraftment to the liver was more prominent in naïve MSC than pMSC, peaking at day 14. Engraftment to the brain was prominent in both naïve and polarized MSC only by day 14 (Figure 7C). MSCs are well known for their immunomodulatory properties as they can induce both immune suppression and immune activation [11,13]. It was proposed that MSCs can be polarized to MSC1 (immune activation) and MSC2 (immune suppression) by activation of TLR4 and TLR3, respectively [14,15]. Pituitary adenylate cyclase-activating polypeptide (PACAP) is a neuropeptide with well-known anti-inflammatory properties [17]. Indeed, PACAP may also play a key role in the anti-inflammatory response induced by MSC [18]. It was further demonstrated in vitro that PACAP treatment can increase TLR3 gene expression in monocytes [19]. Similarly, we have found that short-term treatment of MSC with PACAP in vitro increased the TLR3/TLR4 gene expression ratio and polarized MSC towards a phenotype resembling MSC2, as indicated by the expression of anti-inflammatory cytokines (Figure 1 and Figure 2). PACAP-treated MSC retained their mesenchymal features, as observed in the similar marker expression in naïve MSC (Figure 1A). Interestingly, both naïve and polarized MSC expressed VPAC2 receptor for PACAP, suggesting its role in mediating the anti-inflammatory phenotype by PACAP. Indeed, it was previously shown that overexpression of VPAC2 in T cells promotes their polarization to Th2 with anti-inflammatory cytokine expression [20]. Previous reports have only found PAC1 to be expressed in human MSC following treatment with the pro-inflammatory cytokine INF-γ [18]. Age-related decline in cognitive function is associated with reduced hippocampal neurogenesis caused by changes in the systemic immune milieu [4,21]. These changes involve a decrease in plasma level of ‘pro-youth’ factors such as GDF-11 and an increase in ‘pro-aging’ factors, mainly inflammatory chemokines such as CCL11, CCL12, CCL19, CCL2, β2-microglobulin and haptoglobin. Other pro-inflammatory changes during aging also contribute to the effect of aging on the central nervous system and on hippocampal neurogenesis [3,22,23]. It is, therefore, reasonable to assume that anti-inflammatory strategies would be beneficial in promoting neurogenesis in aged animals. However, conventional treatment with anti-inflammatory drugs failed to elicit neurogenesis in a previous study [24]. On the other hand, targeting hippocampal neurogenesis using stem cells can be a promising approach. Indeed, we have previously shown in murine models of neurodevelopmental impairment that resemble premature aging with impaired neurogenesis that MSC administration to the CNS can restore neurogenesis [16,25]. Furthermore, local intracerebroventricular transplantation of MSC increased hippocampal neurogenesis and improved spatial learning in aging rats [26]. Park et al. (2013) demonstrated improved cognitive functions in aged mice intravenously administered with adipose-tissue-derived MSC, however, engraftment rates to the hippocampus were lower than intracerebroventricular administration and depended on multiple administrations [27]. The concerns were also raised regarding the effectiveness of intravenous administration and the engraftment of MSC in aged animals following stroke [28]. We, thus, tested the systemic administration of our polarized MSCs in aged mice and, indeed, found that polarized MSC treatment reduced the serum levels of three ‘pro-aging’ chemokines (CCL11, CCL12 and CCL2, Figure 3). In parallel, polarized MSC administration resulted in the elevation of hippocampal neurogenesis and improvement in cognitive functions (Figure 4 and Figure 5). In contrast, naïve MSC administration had a milder effect on neurogenesis and, similarly, had a milder effect on cognitive function as assessed by the behavioral assays. Although we did not analyze chemokine levels following naïve MSC administration and, therefore, cannot exclude their effect on systemic chemokine expression, the overall results imply that polarized MSC are more suitable than naïve MSC for treating brain aging. Previously, similar results were obtained with umbilical cord blood MSC that were shown to increase neurogenesis and cognitive function following serial intraperitoneal injections in a rat model of aging [29]. The authors of this study attributed the effect to secreted factors, typical for ‘young’ MSC, as no long-term engraftment of the cells in body organs was observed. Indeed, systemic delivery of MSC results mainly in engraftment to the lungs and spleen with the therapeutic effect attributed mainly to their secretome [8,30]. As opposed to that, two studies performed on aged mice and D-galactose-induced brain aging in rats demonstrated engraftment and neural differentiation of intravenously administered MSC following multiple injections [27,31]. Fabian et al. (2017) demonstrated long-term engraftment of MSC to the cortex but not to the hippocampus of aged mice following a single intravenous injection, as detected by genomic PCR 28 days post injection. Furthermore, engraftment of aged MSC to the spleen and blood was also evident in aged mice [32]. In comparison to their observations, our study, conducted shortly following the injection, found significant engraftment of MSC to the CNS only by day 14 in 3-month-old mice. Engraftment to extra CNS organs, notably, the lungs and liver, was evident along the first two weeks following injection (Figure 7). It is, therefore, reasonable to assume that the changes in neurogenesis observed in our study arise from their influence on extra-hippocampal tissues, including blood, rather than on direct engraftment to the hippocampus. In the present study, we suggest that, regardless of brain engraftment, polarized MSC can affect the systemic inflammatory milieu, which in turn, affect hippocampal neurogenesis and cognitive functions. The negative correlation found in the present study between sICAM-1, CCL2, CCL12 and newly formed DCX+ neurons, Ki67+ and Y-maze results (Figure 4 and Figure 6) suggest a mechanistic relation between plasma chemokines, hippocampal neurogenesis, and its related cognitive functions. We propose that by normalizing the levels of ‘pro-aging’ chemokines, polarized MSC can alleviate impaired neurogenesis and cognitive deficits in aged mice. Indeed, few studies demonstrated that blocking the expression of ‘pro-aging’ factors such as, β2-microglobulin and CCL2 in knockout mice resulted in increased neurogenesis [33,34]. Nevertheless, we do not exclude the possible effect of polarized MSC on neurogenesis and behavior by direct engraftment of the cells to the CNS. We conclude that polarized anti-inflammatory MSC are better candidates for treating brain aging, via systemic administration, than naïve bone-marrow-derived MSC. Further studies should explore their therapeutic potential in other neurodegenerative and neuropsychiatric disorders associated with inflammation-related pathology. All experimental procedures were performed in accordance with National Institutes of Health guidelines. MSC were isolated from 8 weeks old ICR mice. Behavioral and molecular experiments were conducted in 18-month-old male ICR mice. ICR mice were purchased from Harlan laboratories (Jerusalem, Israel). Food and water were provided ad libitum. Mesenchymal stem cells (MSCs) were isolated from the bone marrow of 8-weeks old ICR mice. Briefly, tibias and femurs were removed and cleaned from connective tissue following animal euthanasia. Marrow was flushed out from epiphysis cut bones and disintegrated to cell suspension by passage through a series of needles (19 G, 21 G, 23 G and 25 G). Cells were then suspended in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 20% fetal bovine serum, 100 units/mL penicillin, 100 µg/mL streptomycin and 2 mM L-glutamine. Suspended marrow cells were plated in a 100-mm dish and cultured at 37 °C in 90% air + 10% CO2 atmosphere, with non-adherent cells removed 24 and 48 h following plating. For culture expansion, the same composition of medium was applied but with 10% FBS. Medium was changed twice weekly, cultures were subcultivated upon reaching confluence. MSCs were expanded in culture for up to 20 passages. Pituitary adenylate cyclase-activating peptide (PACAP) amino acids 1–27 was purchased from Bachem AG (Switzerland) cat. No. 127317-03-7. Polarization of MSC was achieved by treating MSC cultures with expansion medium supplemented with 20 nM of the neuropeptide PACAP (1–27) for 4 days. Cell culture reagents were purchased from Biological industries (Beit Haemek, Israel). To characterize the mesenchymal phenotype of polarized MSC, PACAP-treated MSC were immunophenotyped by FACS analysis (FACSCalibur with CellQuest software, Becton Dickinson, Franklin lakes, NJ, USA) using the mouse multipotent mesenchymal stromal cell marker antibody panel (cat No. SC018; R&D systems, Minneapolis, MN, USA), as we previously described [16]. Cultures were tested for the positive expression of the stromal markers CD29, CD44, CD73, CD106, SCA-1 and negative expression for the hematopoietic markers CD45 and CD11b. A cytokine array detection assay was performed on cultured cell conditioned media or animal serum samples. Following 4 days of treatment with PACAP, cells were suspended in 5 mL serum-free DMEM and seeded into new 100 mm plates for an additional 24 h. The conditioned medium was collected, filtered through a 0.45 µm membrane and used for the analysis. Serum samples were prepared from blood samples collected directly from the heart following deep anesthesia of the animals induced by a mixture of ketamine (150 mg/kg) and xylazine (10 mg/kg). Serum was separated by centrifugation at 1000 RPM for 10 min. Serum samples were stored for long term at −20 °C. Cytokine expression was detected in 100 μL of serum or pooled conditioned media using the Proteome Profiler Mouse Cytokine Array Kit (R&D Systems, Cat no. SC018), according to the manufacturer’s protocol. Kit membranes were developed and imaged using the ImageQuant instrument. Images were analyzed using ImageJ software (Version 1.52a). For systemic administration of MSC, naïve and PACAP-treated MSC cultures were trypsinized and suspended in 0.9% saline. Then, 2 × 105 cells were injected into the tail vein of aged (18-months old) male mice. Three days following the injection, the mice were exposed to a series of behavioral assays to assess their behavior. Control animals were injected with vehicle only. The general locomotor activity of the mice was evaluated using the open field paradigm. The open field arena consists of a 40 × 40 × 40 cm plastic box. Mice were placed at the center of the arena and were allowed to travel freely for a period of 6 min. Mice movements (total distance walked, time spent in different arena parts) were detected, recorded and analyzed using EthoVision Version 16 (Noldus; Wageningen, Netherlands), computerized video tracking system. Between each test, the arena was cleaned with 70% ethanol. The Morris water maze (MWM) test was used to assess spatial learning and memory. The MWM arena consisted of a 100 cm diameter, 40 cm height black plastic pool filled with water at 23 ± 2 °C to a height of 25 cm, with a hidden platform near the edge. The arena was marked with equal distance geometrical marks. The test was conducted over 5 consecutive days, with each mouse being placed at 3 different points for 1 min with a 60-min interval between trials. If the mouse reached the platform before 1 min, the time was recorded, and the mouse was allowed to stay on the platform for an additional 20 s. If the mouse failed to escape, it was manually placed on the platform for 20 s. The escape latency time was recorded using the EthoVision XT Version 16 tracking system software. On the fifth day, after the third trial (trial 15), a probe trial was performed with the platform removed, and the mice were allowed to swim for 60 s. The total duration spent in the platform zone was measured and learning curves showing the decrease in latency as the days progressed were compared between groups. In the Y-maze test, the mouse was placed in the middle of the maze at the three-arm junction and left for 5 min. All his entrances to any arm were detected using EthoVision XT tracking system software. The spontaneous alteration behavior index was calculated and defined as the number of variable entries of the animal divided into the number of potential variable entrances. Immunohistochemistry was performed to assess the effect of MSC administration on hippocampal neurogenesis. After the completion of behavioral assays, 2 weeks post MSC injection, mice were sacrificed through intracardial perfusion with PBS, followed by 4% paraformaldehyde (PFA). The brains were then removed, fixed overnight and equilibrated in 30% sucrose phosphate buffer. Brain tissue sections (20 μm) were cut using a MEV Slee Semi-Automatic Cryostat (SLEE medical GmbH, Nieder-Olm, Germany). Frontal sections of the hippocampus were stained for doublecortin (DCX), a neuronal differentiation marker, and Ki-67, a proliferation marker, using an immunohistochemistry kit (Cat. No. ab2253; Millipore, Burlington, Ma, USA) according to the manufacturer’s protocol. The sections were refixed with 4% PFA for 10 min and treated with 3% H2O2 for 10 min to block endogenous peroxidase. They were then permeabilized with 0.01% Triton X-100 for 5 min, followed by a 45-min incubation with blocking solution (provided by the kit). The sections were then incubated overnight with primary rabbit polyclonal anti-DCX (Abcam, UK. Cat No. ab18723) diluted 1:1000 in 0.5% bovine serum albumin or primary rabbit polyclonal anti-Ki-67 (Abcam, UK. Cat No. ab15580) diluted 1:1000 in 0.5% bovine serum albumin at 4 °C. Subsequently, the sections were treated with a horseradish peroxidase (HRP) one-step polymer conjugated secondary antibody for 30 min at room temperature. Visualization was achieved through a 10-min incubation with 3,3′ Diamino-benzidine tetrahydrochloride (DAB) buffer and DAB chromogen. The sections were washed with PBS 3 times for 5 min between each step. Doublecortin positive cells in the granular cell layer of the dentate gyrus in the hippocampus were counted in six representative sections, and the average number of positive cells per dentate gyrus per section was calculated for each mouse. Ki67-positive cells in the subgranular zone of the dentate gyrus were counted in a similar manner. Micrographs were acquired using an OLYMPUS BX53 microscope (Tokyo, Japan) equipped with OLYMPUS camera U-TV0.5XC-3 with OLYMPUS CellSens imaging software (Version 1.18). Total RNA was extracted from MSC culture using an RNeasy Purification mini kit (QIAGEN, cat no. 74104) according to the manufacturer’s protocol. RNA was quantified according to absorbance at 260 nm, measured using the NanoDrop 2000. Then, 1 µg of total RNA was reverse transcribed using GoScript™ Reverse Transcription System (Promega, cat No. A5003). After reverse transcription, real-time PCR analysis by real-time PCR QuantStudioTM machine was conducted for the expression of TLR3 and TLR4 using LightCycler SYBR Green I Master (Roche, cat No. 04887352001) according to the manufacturer’s instruction with 300 nM primers concentration. GAPDH gene was used for sample normalization. Amplification was performed under the following conditions: 5 s denaturation at 95 °C, followed by 30 s annealing at 59 °C and then followed by 30 s extension at 72 °C for a total of 40 cycles. Primer pairs used were TLR3 forward 5′-TTGTCTTCTGCACGAACCTG-3′ and TLR3 reverse 5′-CGCAACGCAAGGATTTTATT-3′; TLR4 forward 5′-ACCTGGCTGGTTTACACGTC-3′ and TLR4 reverse 5′-CTGCCAGAGACATTGCAGAA-3′; GAPDH forward 5′-GGGGCTCTCTGCTCCTCCCTGT-3′ and GAPDH reverse 5′-TGACCCTTTTGGCCCCACCCT-3′; VPAC1 forward 5′-CAAGGATATGGCCCTCTTCA–3′ and VPAC1 reverse 5′- TGATGAACACACTGGGCACT-3′; VPAC2 forward 5′-CAGATGTTGGTGGCAATGAC-3′ and VPAC2 reverse 5′-CCTGGAAGGAACCAACACAT-3′; PAC1 forward 5′-GACCTGATGGGCCTAAATGA -3′ and PAC1 reverse 5′-GCCAGAATCCCCTATGGTTT–3′. primers were synthesized commercially (Sigma-Aldrich). PCR product specificity was confirmed using melting curve analysis and relative gene expression was calculated as 2(−ΔΔCT). Naïve and polarized (PACAP-treated MSC) were suspended and incubated with 1 mM DiR fluorescent dye (Applied Biosystems. Cat No. GC-C019) dissolved in PBS for 15 min at 37 °C followed by 5 min at 4 °C). Labeled cells were washed twice with PBS and resuspended in saline. Approximately 200,000 DiR labeled MSC were intravenously injected to the tail vein of 3-months-old ICR mice. Control animals were injected with vehicle only. At days 0 (2 h), 1, 4, 7 and 14 following injections, mice were sacrificed, dissected, and immediately imaged using the Maestro In Vivo Imaging System (CRi Maestro ll), DiR signal was visualized using 780 nm/810 nm ex/em filter. All data in graphs are presented as mean with bars representing standard error. Statistical significance between two groups was assessed using Student’s t-test. For multiple group analyses, one-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test was performed. For Morris water maze tests, repeated measures one-way ANOVA was performed. Correlations were calculated using the Pearson correlation test. All statistical analysis were performed using Prism GraphPad software (Version 9.5.1).

PMC10003248

Qi Long,Bingjie Lv,Shijiu Jiang,Jibin Lin

The Landscape of Circular RNAs in Cardiovascular Diseases

26-02-2023

circRNA,cardiovascular disease,biomarker

Cardiovascular disease (CVD) remains the leading cause of mortality globally. Circular RNAs (circRNAs) have attracted extensive attention for their roles in the physiological and pathological processes of various cardiovascular diseases (CVDs). In this review, we briefly describe the current understanding of circRNA biogenesis and functions and summarize recent significant findings regarding the roles of circRNAs in CVDs. These results provide a new theoretical basis for diagnosing and treating CVDs.

The Landscape of Circular RNAs in Cardiovascular Diseases Cardiovascular disease (CVD) remains the leading cause of mortality globally. Circular RNAs (circRNAs) have attracted extensive attention for their roles in the physiological and pathological processes of various cardiovascular diseases (CVDs). In this review, we briefly describe the current understanding of circRNA biogenesis and functions and summarize recent significant findings regarding the roles of circRNAs in CVDs. These results provide a new theoretical basis for diagnosing and treating CVDs. The incidence of cardiovascular disease (CVD) has been increasing rapidly in recent years, which is the leading cause of death worldwide [1,2]. CVDs are characterized by high morbidity, high disability rate, and high mortality, as well as various complications. As such, there is an urgent need to identify new potential biomarkers and therapeutic targets for the prevention and treatment of CVDs. The accumulating evidence has indicated that only a small percentage of the human genome encoded proteins and the rest were non-coding RNAs (ncRNAs) [3]. Recent studies have shown the roles ncRNAs played in cellular homeostasis and disease pathophysiology. Based on their size, ncRNAs could be divided into two groups: small ncRNAs and long ncRNAs. Circular RNA(CircRNA), a particular type of long ncRNA, forms a closed-loop framework by covalently constituting single-stranded RNAs without the usual terminal structures such as the 5′cap or polyadenylated tail. CircRNAs are also characterized by their high abundance and sometimes could even exceed 10 times that of linear transcripts [4]. In the past decade, great attention has been paid to the biogenesis and function of circRNAs in different diseases, including in CVDs. In addition, the potential clinical applications, such as diagnostic and prognostic biomarkers, as well as therapeutic targets in heart disease, are new emerging domains [5,6,7,8]. In the present review, the literature on circRNAs and CVDs published in the English language in PubMed data, from January 2013 to January 2023, was searched with keywords including “RNA, Circular” and “Cardiovascular Diseases”. We summarized the existing knowledge of circRNAs in CVDs, from cardiovascular-related cells to different diseases, and pointed out directions of potential future researches. CircRNAs are closed circular biomolecules, which distinguish them from other linear RNA biomolecules. They are circularized by joining the 3′ and 5′ ends together via exon circularization or intron circularization [9]. At present, three major mechanisms have been reported for the generation of circRNAs: “lariat-driven circularization”, “intron-pairing-driven circularization” and “RBP-driven circularization” [10] (Figure 1. Lariat-driven circularization is associated with exon skipping, in which one or more transcript exons are skipped, and then the remaining lariat itself is joined by a spliceosome and becomes an exon circle. Intron-pairing-driven circularization, on the other hand, is mostly related to complementary motifs present in the intronic regions. In this model, direct RNA base pairing with reverse complementary sequences, such as Alu repeats in the human genome across introns flanking exons, is brought into proximity to promote circularization [11,12]. CircRNAs can also be cyclized by RNA-binding protein (RBP). In RBP-driven circularization, trans-acting factors recognize and dock on specific motifs located in the introns flanking the circularized exons. The splice sites are brought into close proximity through these protein–protein interactions or dimerization, and after that the spliceosome could engage in a back-splicing reaction [13]. It is worth noting that circular intronic circRNAs (ciRNAs) have a special lariat circularization method in which only introns remain. CircRNAs can be classified into at least three categories: EcircRNAs (exonic circRNAs), EIcircRNAs (exonic-intronic circRNAs) and ciRNAs (circular intronic circRNAs), according to their synthesis mechanism and constituent components (Table 1) [14,15,16,17,18,19]. EcircRNAs now make up a notable proportion of the known circRNAs. Despite the rapid research progress in the field, the biological functions of circRNAs in eukaryotic cells have not been fully understood. To date, several potential functions of circRNAs have been revealed: (1) acting as miRNA sponges; (2) interacting with RNA-binding proteins (RBP); (3) acting as dynamic scaffolding molecules that modulate protein–protein interactions; (4) acting as transcription or translation regulators; (5) participating in the translation of proteins [13,20,21,22] (Figure 1). The function CircRNAs as miRNA sponge has been a focus of recent research. CircRNAs can competitively bind to miRNAs and lead to the reduction of miRNAs. Then, the reduced miRNAs have reduced inhibitory effects on target genes, resulting in the upregulation of these genes. For example, circRNA_000203 can regulate the occurrence of cardiac hypertrophy by directly sponging miR-26b-5p and miR-140-3p [23]. Apart from miRNA sponges, circRNAs can also function as protein sponges, such as RBP sponges. The binding of RBPs with circRNAs would lead to the function inhibition of RBPs, especially those participating in the transcription and translation of genes. For instance, circANRIL competitively recruited PES1 (pescadillo homolog 1, an essential 60S-preribosomal assembly factor), leading to the inhibition of ribosome biogenesis in vascular smooth muscle cells and macrophages [24]. CircANRIL induced nucleolar stress and p53 activation, which was followed by the induction of apoptosis and inhibition of proliferation in atherosclerosis. Moreover, in the presence of internal ribosomal enter sites and a corresponding open reading frame, circRNAs can affect protein translation and act as a scaffold for enzymes, guiding them to indicate location. CircFOXO3 binds to CDK2 and p21, contributing to the formation of the circFOXO3-p21–CDK2 ternary complex and then serving as a scaffold, affecting cancer cell-cycle progression [25]. In addition, circRNAs mediated the regulation of the transcription of parental genes. For example, Ci-ankrd52 can bind to the transcription sites and enhance host-gene transcriptional progress by acting as a positive regulator of Pol II transcription [26]. Although circRNAs were initially recognized as non-coding RNAs, studies conducted in recent years have demonstrated that circRNAs can serve as templates for protein translation via some modification [27]. CircZNF609 has an IRES element and can be translated into a protein that functions in myoblast proliferation [28]. CircRNAs were first discovered in the early 1970s, however, due to limited available technology, they have been poorly studied in the past [29,30]. With the development of high-throughput sequencing (HTs) and bioinformatic tools, scientists have found that circRNAs are general features of the human transcriptome, and their biological functions have been intensively investigated. To date, there are more than 200,000 different circRNAs present in the union of all noncurated databases, to the best of our knowledge [31,32]. The current methods used to detect and quantify circRNAs include high-throughput sequencing (HTs), microarray and conventional RT-PCR/qPCR, and northern blot [33]. Most recently, Li et al. developed a rapid and useful screening tool for functional circular RNAs based on the CRISPR-Cas13d system [34]. This technology may provide a new tool for circRNA research. Cellular levels of circRNAs are known to be low in proliferating and neoplastic human cells. Recent studies performed on the human heart have shown that it expressed about 7000 to 16,000 different circRNAs [35]. In the cardiovascular system, circRNAs appear to be robustly expressed and show differential regulation in different related cells and cardiac diseases. Currently, there are several different datasets about circRNAs using microarray or HTs technology that focus on cardiovascular diseases such as atherosclerosis and acute myocardial infarction (MI). We summarized these gene expression omnibus (GEO) datasets in Table 2. This is a treasure to be discovered. Due to the space limitation, we would only focus on some cardiovascular-related cells and diseases. Data mining in the future may reveal more important circRNAs and their roles in CVDs. There are many cells related to cardiovascular diseases. In this review, we focus on endothelial cells, smooth muscle cells, cardiomyocytes and cardiac fibroblast (Figure 2). Some other cells such as immune cells are not our primary focus here, but a special summary is also needed for these other cells in the future. Endothelial cells (ECs) are the foundation of the vascular system and EC injury occurs in the early stage of atherosclerosis. Several factors contribute to EC injury and dysfunction, such as oxidized low-density lipoprotein (ox-LDL), oxidative stress and hypoxia [70,71]. Ox-LDL is a common stimulating factor of atherosclerosis in vitro. Hsa_circ_0003575 was significantly upregulated in ox-LDL-stimulated human umbilical vein endothelial cells (HUVECs) in vitro. Functional tests indicated that silencing hsa_circ_0003575 could lead to the promotion of HUVEC proliferation and angiogenesis ability [72]. These results indicated that hsa_circ_0003575 may promote atherosclerosis by inducing cell apoptosis. In another study, circ_0003645 had been identified to promote the development of ox-LDL-induced HUVEC injuries. In that study, propofol protected against the viability inhibition and apoptosis promotion of HUVECs by decreasing the circ_0003645 level. Mechanically, circ_0003645 could induce TRAF7 upregulation following propofol treatment through sponging miR-149-3p [73]. The redox imbalance of the ECs plays a causative role in a variety of cardiovascular diseases. CircANKRD12, derived from the junction of exon 2 and exon 8 of the ANKRD12 gene, was significantly upregulated in H2O2-treated ECs. In a network analysis performed for the identified circANKRD12, the p53 and Foxo pathways were proven to play a fundamental role in the oxidative stress response in many different systems. Further, the downregulation of circANKRD12 affected the redox imbalance response, suggesting the potential role of circANKRD12 in the protection of ECs against oxidative stress [74]. In an EC and hypoxia study, cZNF292 was found to be expressed in the ECs and induced by hypoxia. Moreover, the silencing of cZNF292 reduced the tube formation and spheroid sprouting of ECs in vitro. The circRNA cZNF292 exhibits proangiogenic activities in vitro, and this circRNA was involved in the regulation of EC function. No validated microRNA-binding sites for cZNF292 were detected, indicating that cZNF292 may not act as a microRNA sponge [75]. Furthermore, Chen et al. demonstrated that CircDLGAP4 was significantly decreased in HUVECs suffering ischemia/reperfusion (I/R) injury [76]. CircDLGAP4, which acts as an miR-143 sponge, promoted HECT domain E3 ubiquitin protein ligase 1 (HECTD1) expression. HECTD1 could inhibit the apoptosis and migration in ECs associated with endoplasmic reticulum (ER) stress. The study suggested an important role for circDLGAP4 and HECTD1 in ER dysfunction induced by I/R. In addition, the circRNA-0024103/miR-363/MMP-10 axis was reported to regulate endothelial cells behaviors such as proliferation, apoptosis, migration and invasion [77]. Vascular smooth muscle cell (SMC) is the major component of the medial layer and could maintain intravascular pressure and blood perfusion through coordinating vascular relaxation and contraction. Zeng et al. demonstrated that overexpression of circMAP3K5 inhibited the proliferation of human coronary artery SMCs [78]. Loss of TET2 was found to downregulate the circMAP3K5-mediated antiproliferative effect on vascular SMCs in SMC-specific TET2 knockout mice. CircMAP3K5/miR-22-3p/TET2 was found to be the mechanism axis. In addition, circ-SATB2 was reported to regulate the differentiation, proliferation, apoptosis, and migration of VSMCs through enhancing STIM1 expression [79]. The knockdown of circSOD2 was found to inhibit PDGF-BB-induced SMC proliferation. On the contrary, circSOD2 ectopic expression promoted SMC proliferation. CircSOD2 acted as a sponge for miR-206, leading to the upregulation of notch receptor 3(NORCH3) and NOTCH3 signaling [80]. CircSOD2 is thus regarded as a novel regulator that mediates SMC proliferation and neointima formation following vascular injury. What is more, Sun et al. reported that circ_RUSC2/miR-661/spleen-associated tyrosine kinase (SYK) could contribute to VSMC proliferation, phenotypic modulation and migration [81]. Furthermore, hsa_circ_0001445has been suggested as an indicator of stable coronary artery disease (CAD). This circRNA is produced from the SWI/SNF-related matrix-associated actin-dependent regulator of the chromatin subfamily A member 5 (SMARCA5) locus, and its levels in the plasma may be a predictor of coronary artery atherosclerosis in suspected patients. Interestingly, the decreased secretion of hsa_circ_0001445 could be observed when the human coronary SMCs were exposed to atherogenic conditions in vitro [82]. CircRNAs are mentioned as powerful cardiac development regulators affecting cardiac regeneration. CircNfix was overexpressed in adult hearts in humans, rats, and mice compared to infants. Experiments in vitro and in vivo indicated that cardiomyocyte proliferation was promoted when circNfix was downregulated. Huang et al. demonstrated that super-enhancer-regulated circNfix could suppress Ybx1 ubiquitin-dependent degradation and increase miR-214 activity to inhibit cardiac regenerative repair and functional recovery after myocardial infarction (MI) [83]. In addition, the upregulation of circSNRK could also contribute to the reduction of apoptosis and cardiomyocytes proliferation. In the post-infarction area after acute myocardial infarction (AMI), circSNRK promoted cardiomyocytes regeneration by acting as a sponge for miR-103-3p and upregulating the expression of SNRK [84]. What is more, Zhou et al. reported that circRNA-68566 could participate in myocardial I/R injury by regulating the miR-6322/PARP2 signaling pathway [85]. MiR-6322 was proven to be a direct target of circRNA-68566. CircRNA-0068566 inhibited I/R injury through reducing oxidative stress and apoptosis via miR-6322. A study conducted by Zong et al. indicated that overexpressed circANXA2 could inhibit hypoxia/reoxygenation (H/R)-treated H9C2 cell proliferation. Moreover, further study demonstrated that circANXA2 could reverse the inhibition of myocardial proliferation and increasing cardiomyocyte apoptosis by acting as a sponge for miR-133 [86]. Luo et al. demonstrated that suppressing circPVT1 expression could prevent heart I/R injury in rats and improve cardiomyocyte viability by regulating the circPVT1/miR-125b/miR-200a axis [87]. It has been reported that the absence of circ-CBFB could offer cardiac protection against H/R-triggered cardiomyocyte injury through the miR-495-3p/VDAC1 axis, suggesting its potential role for acute myocardial infarction treatment [88]. Additionally, hypoxia treatment upregulated the expression of circHSPG2 in AC-16 cells (human cardiomyocyte). In this study, exposing AC-16 cells to hypoxia resulted in a reduction in cell viability and proliferation as well as the promotion of apoptosis. The progressions were diminished by the silence of circHSPG2 [89]. Furthermore, hsa_circ_0000848 was notably downregulated in hypoxia-induced cardiomyocytes [90]. The silence of hsa_circ_0000848 inhibited the proliferation while accelerating the apoptosis. This circRNA interacted with the ELAV-like RNA-binding protein 1 protein to stabilize SMAD family member 7 mRNA and affected the development of cardiomyocyte cells cultured under hypoxia. The activation and phenotypical transition of cardiac fibroblasts (CFs) could contribute to cardiac fibrosis. It was proven that circBMP2K enhanced the regulatory effects of miR-455-3p on its downstream target gene, SUMO1, which led to the inhibition of TGF-β1 or Ang II and resulted in the activation and proliferation of CFs [91]. In addition, circPAN3 knockdown was reported to attenuate autophagy-mediated cardiac fibrosis after myocardial infarction via the miR-221/FoxO3/ATG7 axis [92]. In another study, circRNA_010567 was proven to be markedly upregulated in CFstreated with Ang II. CircRNA_010567 silencing could upregulate miR-141 and downregulate TGF-β1 expression, and it suppressed fibrosis-associated protein resection in CFs, including Col I, Col III and α-SMA, which suggested that circRNA_010567 played an regulatory role in CFs [93]. Moreover, circNFIB, which was identified as a miR-433 sponge, was downregulated in adult CFs after treated with TGF-β [94]. The overexpression of circNFIB could attenuate the pro-proliferative effects induced by the miR-433 mimic, while the inhibition of circNFIB exhibited opposite results. CircNFIB is thus regarded as critical for protection against cardiac fibrosis. Recent research has demonstrated that the profile expression of circRNAs is associated with different types of cardiovascular diseases, such as coronary artery disease, cardiomyopathies, chronic heart failure, hypertension, atrial fibrillation, and so on [95,96,97]. CircRNAs played an important role in atherosclerosis and coronary artery diseases [26]. The SNPs on chromosome 9p21.3 were revealed to be correlated with the severity of atherosclerosis by a genome-wide association study (GWAS) [98]. The antisense non-coding RNA at the INK4 locus (ANRIL) and the related circular ANRIL (circANRIL) are transcribed on chromosome 9p21. It was reported that circANRIL upregulation could inhibit the development of vascular disorders, especially coronary artery diseases [99]. As mentioned above, circANRIL bound to PES1, impairing exonuclease-mediated pre-rRNA processing and ribosome biogenesis and leading to p53 activation [36,100]. This, in turn, led to a subsequent apoptosis increase, proliferation decrease, and the migration of VSMCs and macrophages. In addition, circANRIL overexpression could promote EC apoptosis and exacerbate EC inflammation. Therefore, circANRIL may play a role in atherosclerosis and CAD development by inducing the apoptosis and inflammation of these atherosclerotic-associated cells. In addition, cardiomyocyte apoptosis and necrosis were important features in AMI. The CircRNA CDR1AS was found in abundance in the hearts of mice [101]. CDR1AS was a sponge for miR-7. CDR1AS was shown to be pro-apoptotic in vitro, consistent with the anti-apoptotic role of miR-7. More importantly, the overexpression of CDR1AS in mouse hearts resulted in larger infarct sizes after AMI, which could be prevented by the overexpression of miR-7. Recently, Wang et al. revealed that novel circRNA, mitochondrial fission and apoptosis-related circRNA (MFACR) could regulate mitochondrial dynamics and apoptosis in the heart by targeting the miR-652-3p-MTP18 signaling axis [102]. Recently, the experiments conducted by Si et al. illustrated the important role of circHipk3 in the regeneration of the heart after AMI. The expression of circHipk3 has also been found to be increased in fetal and neonatal mice hearts. An important observation is that the inhibition of circHipk3 expression also leads to the inhibition of the proliferation of cardiomyocytes [103]. In addition, circHIPK3 acted as a sponge for miR-133a to promote connective tissue growth factor (CTGF) expression, activating endothelial cells and improving cellular function. The overexpression of circHipk3 is associated with a decrease in cardiac dysfunction, which translates into a reduction in the area of fibrosis after AMI. CiRS-7 was reported as a classic miRNA sponge. It has been confirmed that ciRS-7 has over 70 miR-7 binding sites [17,20]. Geng et al. reported increased ciRS-7 expression after MI in the cardiac tissue. In addition, when the ciRS-7 level was increased by a lentiviral-based overexpression in a rodent MI model, an increase in the extent of the MI area was also observed. The authors have also stated that ciRS-7 affected the axis of PARP/SP1 by sponging miR-7, and it thus regulated the apoptotic pathway. Moreover, it is well known that plaque instability is very important in the pathogenetic mechanism of CAD. CircRNAs play a vital role in sustaining atherosclerotic plaque stability [104]. The results of the research obtained by Bazan et al. show the upregulation of circRNA-16 accompanying the downregulation of miR-221 in acutely ruptured carotid plaques. E26 transformation-specific-1 (ETS1), a key transcription factor of endothelial inflammation and tube formation, is the target of miR-221 [105]. MiR-221 bound to ETS1 and downregulated several EC inflammatory molecules and decreased the adherence of Jurkat T cells to activated HUVECs. In another study, miR-221-3p could promote pulmonary arterial SMC proliferation by targeting axis inhibition protein 2 (AXIN2) [106]. Therefore, circRNA-16 may play an important regulatory role in the stability of atherosclerotic plaques through acting as a sponge for miR-221. In myocardial ischemia-reperfusion injury (MIRI) and the hypoxia/reoxygenation treatment models, the expressions of circ-GTF2I were significantly upregulated in vivo and in vitro when compared with that in the sham group. The knockdown of circ-GTF2I relieved neonatal rat cardiomyocyte damage and MI severity. Further study verified that circ-GTF2I induced the abnormal expressions of IL-6, TNF-α, LDH, Bax, Bcl-2, and Cyt-c in MIRI and the hypoxia/reoxygenation treatment models by regulating miR-590-5p and the heart development transcription factor KBTBD7. Circ-GTF2I promoted MIRI deterioration and induced the neonatal rat cardiomyocyte damage by targeting miR-590-5p and KBTBD7. Transient receptor potential melastatin-3 (TRPM3, a calcium-permeable ion channel) is detected in VSMCs and is functionally related to contractility and the secretion of inflammatory factors such as IL-6 [107]. Nine kinds of circRNAs, including hsa_circ_0089378, could promote the expression of TRPM3 via interacting with hsa-miR-130a-3p in CAD patients [108]. This suggested that the progression of CAD may be regulated through the circRNA-miR-130a-3p/TRPM3 axis [109]. As stated above, different types of circRNAs have also been found to affect the function of atherosclerotic cells and plaque stability and participate in the development of CAD. Cardiomyopathies were recognized as a heterogeneous group of disorders of the myocardium that can change cardiac function (mechanical and/or electrical dysfunction) and structure and lead to heart failure. Heart failure (HF) represents one of the major challenges facing healthcare systems in industrialized societies, and an increasing burden in developing countries. The circRNA exhibiting the highest level in the human heart is encoded by the SLC8A1 (solute carrier family 8 member A1) gene. Upregulated circSLC8A1 sequestered miR-133a to increase the expression of multiple miR-133a target genes, which indicated that the circSLC8A1/miR-133a-mRNAs axis may serve as a pivotal mechanism in cardiac hypertrophy pathogenesis [110]. In line with these observations, when compared with the control group, circSLC8A1 expression was elevated in the autopsy heart samples from sudden-cardiac-death patients with acute ischemic heart disease [111]. CircFndc3b is another significantly downregulated circRNA in the cardiac tissues of ischemic cardiomyopathy patients [47]. It interacts with the FUS RNA binding protein and increases vascular endothelial growth factor (VEGF)-A expression. This regulation enhances angiogenic activity and reduces cardiac endothelial cell apoptosis. In the hypoxic myocardium, the presence of circFndc3b in cardiac endothelial cells enhanced the function of the endothelial cells and protected cardiomyocytes against death. cTTN1 is an abundant circRNA in the human heart and is downregulated in DCM [112]. RBM20 (RNA-binding motif protein 20) plays a critical role in the splicing of many cardiac genes, whose mutation will cause aggressive DCM [113,114]. RBM20 is dependent on cTTN and targets multiple key cardiac genes, such as calcium/calmodulin-dependent kinase II (CAMK2D) [115]. Another circRNA that regulates cardiac function is circ-Foxo3, which is usually increased in aged hearts [116]. In vitro, the ectopic expression of circ-Foxo3 induced senescence in fibroblasts; on the other hand, in vivo, the silencing of circ-Foxo3 reduced doxorubicin-induced cardiomyopathy in mice. Functionally, circ-Foxo3 could bind to several proteins that were involved in cellular stress response, including E2F transcription factor 1, inhibitor of DNA binding 1, focal adhesion kinase, and hypoxia-inducible factor 1α, resulting in the cytoplasmic sequestration of these proteins. Whether circ-Foxo3 contributes to cardiac ageing remains to be further investigated. Moreover, the circRNA described to be functional in the heart was termed heart-related circRNA (HRCR) [117]. Wang et al. conducted a study in mice. In this study, Wang et al. demonstrated that HRCR was normally expressed in mouse hearts and was repressed in hypertrophic and failing hearts. Biologically, HRCR seemed to function as an miRNA sponge, binding and thereby sequestering miR-223, an miRNA that caused cardiac hypertrophy via the inhibition of the protein ARC (apoptosis inhibitor with CARD domain). The overexpression of HRCR in an isoproterenol-induced hypertrophy mouse model inhibited hypertrophy, which the authors attributed to the inhibition of miR-223. In HF tissues and H9C2 cells treated with oxygen–glucose deprivation (OGD), circSnap47 was upregulated when compared to the control group [118]. Wang et al. revealed that circSnap47 could relieve OGD-induced H9C2 cell damage and affect the progression of HF by inactivating the miR-223-3p/MAPK axis. Essential hypertension is a multifactorial disease with high morbidity. A recent study found that, when compared to the healthy group, hsa-circ-0037909 was significantly upregulated in essential hypertension patients. This circRNA contributed to the pathogenesis of hypertension by acting as a sponge to inhibit miR-637 activity [119]. Hsa-circ-0005870 exhibited significant downregulation in patients with high blood pressure. Then, a network of hsa-circ-0005870-targeted miRNAs, including hsa-miR-5095, hsa-miR-1273g-3p, hsa-miR-6807-3p, hsa-miR-619-5p, and hsa-miR-5096, and their corresponding mRNAs was observed [55]. Hsa-circ-0005870 may represent a novel biomarker and the hsa-circ-0005870-miRNA-mRNA network may provide a potential mechanism for hypertension. Atrial fibrillation (AF) is an abnormal heart rhythm characterized by the rapid and irregular beating of the atria. Zhang et al. [119] performed an association analysis of the AF-related circRNAs and their parental genes and revealed that hsa_circ_0000075 and hsa_circ_0082096 participated in the AF pathogenesis via the TGF-beta signaling pathway. In addition, circRNA calmodulin binding transcription activator 1 (circCAMTA1) was reported to be related to AF development [120]. CircCAMTA1 knockdown alleviated atrial fibrosis through downregulating TGFBR1 expression intermediated by miR-214-3p in AF. Aortic dissection is an emergency and serious aneurysm disease in the cardiovascular system. Zheng et al. found an obviously upregulated circRNA in aortic tissues, hsa_circ_000595, from patients with aortic dissection aneurysms [121]. Hsa_circ_000595 was reported to promote the apoptosis of vascular smooth muscle cells (VSMCs) through upregulating miR-19a expression. Vascular calcification (VC) is characterized by calcium phosphate crystals accumulating in the vessel wall. It is critical to reveal the novel mechanisms involved in VC as the pathogenesis is diverse and so many factors and mechanisms are involved. It was reported that circSamd4a had an anti-calcification property via the sponging of miR-125a-3p and miR-483-5p [122]. Nowadays, a variety of circulating molecules, such as troponins, creatine kinase-MB and N-terminal pro brain natriuretic peptide (NT-proBNP), have been widely used in clinical laboratory tests. However, these molecules are easily influenced by factors such as age, medications and heart-associated diseases [123,124,125]. Circular RNAs have great biomarker potential for the following reasons: (1) they are extraordinarily stable due to the lack of exposed terminal ends [126]; (2) they have a large amount of cell-specific circRNA [127]; and (3) they are abundant in whole blood, plasma and extracellular vesicles [128]. Many studies have demonstrated the potential of circulating circRNAs as promising predictors and biomarkers. MICRA (myocardial infarction-related circular RNA) improves risk classification after MI [129]. Vausort et al. demonstrated reduced MICRA expression in MI patients and found that a lower MICRA level was related to a higher left ventricular dysfunction risk [130]. Further study found a close link between hsa-circRNA11783-2 and CAD in CAD patients’ peripheral blood by microarray. What is more, hsa_circ_0000284, hsa_circ_0001946, and hsa_circ_0008507 were found to be independent risk factors for CAD [131]. A recent study determined that hsa_circ_0124644 was closely associated with CAD, which could be used as a potential diagnostic biomarker for CAD, with a specificity of 0.626 and sensitivity of 0.861 [43]. Moreover, Wang et al. found that hsa_circ_0001879 and hsa_circ_0004104 were significantly upregulated in CAD patients compared with controls in another study [41]. As these circRNAs have been shown to have high sensitivity and specificity to CAD, they may be potential biomarkers of CAD. AF is a common complication in patients who have undergone coronary artery bypass grafting (CABG). In the plasma of patients with new-onset AF after isolated off-pump CABG, hsa_circ_025016 was found to be upregulated [132]. ROC analysis revealed a high diagnostic value, and it was confirmed by a large validation cohort. Another study has shown that, when compared with healthy controls, the expression of hsa_circ_0037911 in essential hypertension patients was upregulated. Hsa_circ_0037911 was proposed as a key circRNA for essential hypertension development, by affecting serum creatinine concentration, and a marker for the early detection of essential hypertension [133]. CVDs are the leading cause of death worldwide. In this review, we summarized the circRNAs involved in cardiovascular-related cells and diseases. Presently, the differential expression of circRNA in cardiovascular diseases has been observed, indicating that circRNAs might participate in the pathophysiological processes of diseases and could be used as biomarkers and therapeutic targets for disease. However, circRNA research in CVDs is still in its infancy and there is still a long way to go. Firstly, the lack of a uniform and standard naming system and detection method for circRNAs may confuse the researchers and be a hindrance for communications among different laboratories. Secondly, though there has been technical progress in the past decade for circRNAs, it is still difficult to verify the roles of circRNAs in vivo by overexpression or downregulation, and most functional studies have focused on the sponge as it is relatively easy to be validated. More researches are needed in the future to reveal the functions of circRNAs. Moreover, the mechanisms for circRNAs in different diseases, especially CVDs, need to be further clarified. Thirdly, circRNAs are more stable than linear RNAs and are detectable in body fluids such as peripheral blood through exosome secreting, making them potential biomarkers for cardiovascular diseases. However, these biomarkers need to be further verified by more different laboratories, and several conditions, such as sensitivity, specificity, feasibility, reliability, and repeatability, need to be optimized to meet the clinical test criteria. Finally, progress in the circRNA field might also expand their therapeutic potential. The high stability of circRNAs makes them potential long-lasting regulators of specific cellular functions. In a recent study, the overexpression of an artificial circRNA could inhibit HCV viral protein production through sponging the liver-specific miRNA-122, which is required for the life cycle of the hepatitis C virus (HCV) [134]. As a rising research star, circRNAs have potential in therapies such as circRNAs vaccines and genetically edited treatments. In brief, we have illustrated the landscape of circRNAs in cardiovascular diseases and shed light on the importance and potential effectiveness of circRNAs in the diagnosis and therapy of CVDs.

PMC10003249

Maria Carmen Andreo-López,Victoria Contreras-Bolívar,Manuel Muñoz-Torres,Beatriz García-Fontana,Cristina García-Fontana

Influence of the Mediterranean Diet on Healthy Aging

24-02-2023

aging,Mediterranean diet,molecular pathways,microbiome

The life expectancy of the global population has increased. Aging is a natural physiological process that poses major challenges in an increasingly long-lived and frail population. Several molecular mechanisms are involved in aging. Likewise, the gut microbiota, which is influenced by environmental factors such as diet, plays a crucial role in the modulation of these mechanisms. The Mediterranean diet, as well as the components present in it, offer some proof of this. Achieving healthy aging should be focused on the promotion of healthy lifestyle habits that reduce the development of pathologies that are associated with aging, in order to increase the quality of life of the aging population. In this review we analyze the influence of the Mediterranean diet on the molecular pathways and the microbiota associated with more favorable aging patterns, as well as its possible role as an anti-aging treatment.

Influence of the Mediterranean Diet on Healthy Aging The life expectancy of the global population has increased. Aging is a natural physiological process that poses major challenges in an increasingly long-lived and frail population. Several molecular mechanisms are involved in aging. Likewise, the gut microbiota, which is influenced by environmental factors such as diet, plays a crucial role in the modulation of these mechanisms. The Mediterranean diet, as well as the components present in it, offer some proof of this. Achieving healthy aging should be focused on the promotion of healthy lifestyle habits that reduce the development of pathologies that are associated with aging, in order to increase the quality of life of the aging population. In this review we analyze the influence of the Mediterranean diet on the molecular pathways and the microbiota associated with more favorable aging patterns, as well as its possible role as an anti-aging treatment. Currently, the global population has a notably increased life expectancy compared to decades ago, exceeding 60 years of age in most cases. According to the World Health Organization (WHO), the percentage of people over 60 years of age will double globally by 2050 [1]. However, a longer life expectancy leads us to reconsider not only the health of older people but also what kind of implications aging has [2]. Aging is a natural physiological process that leads to a progressive loss of cellular functionality, with consequences that predispose people to an increased risk of frailty, morbidity, and mortality [3]. The role of lifestyle and diet can promote “healthy aging”, in which quality of life takes precedence. According to the WHO, this concept refers to the process of developing and maintaining a functional capacity that enables well-being in old age [1,4]. Several cellular and molecular hallmarks are involved in the aging process. In particular, there are nine hallmarks that are decisive in the aging process: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, the dysregulation of nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell depletion, and altered intercellular communication [5]. These molecular mechanisms are involved in the development of age-related diseases such as cancer, obesity, diabetes, cardiovascular disease (CVD), and neurodegenerative diseases [3]. These age-related diseases have been associated with risk factors that can be modified mainly through nutrition, which constitutes one of the pillars of health [6]. In addition, the microbiota, which is modified by diet, has also been involved in aging [6]. It has been suggested that the age-related decline in immune system function (immunosenescence) and chronic low-grade inflammation could lead to microbiota disturbances that are associated with several age-related pathologies. Thus, it has been argued that a balanced diet can modulate the proliferation of specific bacteria within the gut microbiota. This has been associated with improved health status in older people [7]. In light of the above, the aim of our review was to analyze the available data regarding the potential effects of the Mediterranean diet (MedDiet) as a whole, or of individual elements of it, on the nine hallmarks of aging, to provide further evidence of its health benefits. Moreover, we have also reviewed the effect of MedDiet on the microbiota and its relationship to aging. From a biological point of view, aging can be defined as the physiological and progressive accumulation of senescent cells in organs and tissues, which occurs during the lifetime of an individual and leads to progressive functional slowing or the total loss of function [8,9,10]. Pleiotropic antagonist genes comprise a set of genes that regulate cellular senescence, performing an important role in preventing the degeneration of malignant cells in the cell cycle [11,12]. These genes are also involved in protective mechanisms in physiological cellular senescence processes and in age-related diseases. However, aging cells produce proinflammatory and lytic extracellular matrix molecules in a process known as the senescence-associated complex secretory phenotype (SASP), resulting in degeneration and pathological senescence. Moreover, the aging process involves the immune system; in particular, the cell-mediated defense mechanism is slowed down. Senescent cells do not produce sufficient signals to activate immune cells. Likewise, senescence is induced by the accumulation of various factors at the cellular level that is responsible for macromolecular damage, such as secondary DNA alterations due to oxidative damage, telomere shortening, and endoplasmic reticulum (ER) degeneration [13]. Thus, aging is the result of multifactorial interactions between local and systemic environmental factors and involutional factors due to cellular senescence. Therefore, the number of senescent cells in a person’s body increases with age as the aging immune system becomes less efficient and senescent cells accumulate. This makes individuals more vulnerable to further deterioration after exposure to environmental stressors [13]. The disease occurs when environmental stressors attack tissues that are already in the presence of senescent cells with very low resilience [14,15]. Frailty develops due to an increasing decline usually linked to age, severe deterioration, and the onset of pathological states. This leads to a condition of increased vulnerability and reduced adaptive capacity, and ultimately, negative health changes are triggered by even mild stressors. It is considered more appropriate to speak of “frailty syndrome”: a chronic pathological condition resulting from the interaction between several factors, including aging-related physiological alterations, pluripathology, nutritional deficiencies up to severe malnutrition, and the negative impact of socio-environmental factors [16]. In fact, a high proportion of undernourished people are frail, and undernutrition leads to weight loss, which can contribute to frailty syndrome [17]. At the other extreme, obesity increases the risk of frailty [18]. In terms of body composition, frailty has been associated with a higher body fat mass and fat percentage and with a low muscle mass and is often without association with the body mass index [19,20,21]. All of this can lead to the frail elderly losing all self-sufficiency, increasing the risk of falls, and can result in a state of confusion with severe impairment of cognitive functions that ultimately increases the risk of the development of diseases [22]. The term MedDiet was first coined by Ancel Keys in the 1960s [23]. The MedDiet reflects the dietary patterns typical of civilizations based around the Mediterranean Sea, especially Greece, the island of Crete, and southern Italy in the early 1960s [24]. In fact, the MedDiet is closely linked to traditional olive growing areas in the Mediterranean region and has been associated with low rates of chronic diseases (lower risk of CVD and metabolic diseases associated with excess weight) and, consequently, high life expectancy [24,25]. The MedDiet is characterized by a high consumption of olive oil (OO) as the main source of fat—especially virgin (VOO) and extra virgin (EVOO)—and the high consumption of plant foods (vegetables, fruits, legumes, potatoes, bread, and other cereals (minimally refined), nuts and seeds), as well as fresh seasonal, locally grown, and minimally processed foods. Dairy intake is moderate (mainly cheeses and yogurts), and fish (an excellent source of long-chain poly-unsaturated fatty acids (PUFAs), particularly omega-3) and poultry are consumed in low or moderate amounts. The MetDiet includes the low consumption of red meat and sweets and moderate consumption of wine at meals. No more than four eggs are consumed per week. In general terms, caloric intake in the form of fat does not exceed 30% of the intake, with less than 8–10% contributed by saturated fats. Some bioactive compounds in the MedDiet include vitamins, minerals, polyphenols, fiber, nitrates, PUFAs, and mono-unsaturated fatty acids (MUFAs) that, in combination or separately, are beneficial to health [26,27,28]. Among the PUFAs, the essential omega-6 fatty acid is linoleic acid (LA). In addition, longer omega-3 PUFAs, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are derivatives of alpha-linoleic acid. These are mainly present in fish oils [29]. For these reasons, MedDiet is unique and different from other healthy dietary patterns [29]. The aging process has been linked to nine distinctive cellular and molecular features [5] (Figure 1). Each of these plays its role in the trajectory of natural aging; their experimental exacerbation accelerates the process, and their optimization slows it down, thus increasing lifespan [30]. External lifestyle factors such as diet can modulate the aging process [31,32]. Aging increases susceptibility to DNA alterations resulting from a combination of oxidative stress, epigenetic alterations, damaged DNA, and telomere attrition [33]. Unrepaired DNA could increase the risk of mutations and favor the beginning or development of age-related diseases [34,35]. The MedDiet could play a protective role against genomic alterations. Indeed, bioactive compounds that are contained in the MedDiet, such as melatonin, phytosterols, carotenoids, polyphenols (such as resveratrol and hydroxytyrosol (HT)), vitamins, and glucosinolates (in cruciferous vegetables), can promote DNA repair and attenuate telomere shortening [36,37]. These positive effects have been explained by the anti-inflammatory effects of the MedDiet and the direct and indirect (epigenetic) modifications induced by the MedDiet on gene expression [38,39,40,41]. DNA damage due to oxidative stress is a result of the failure of oxidative damage-repair mechanisms as a result of excess reactive oxygen species (ROS) [42]. Guanine is an important target for DNA oxidation, generating oxidized metabolites. Among them, 8-oxo-2′-deoxyguanosine (8-OHdG) is considered a marker of oxidative stress with mutagenic potential [43,44,45]. Urquiaga et al. related the MedDiet, including a moderate intake of red wine, with a reduction in 8-OHdG levels in the peripheral blood leukocyte DNA, which impacts positively on the control of oxidative stress [46]. Similarly, lower levels of another marker of oxidative stress, the deoxyguanosine adduct, were associated with greater adherence to the MedDiet in the Italian cohort of the EPIC (European Investigation into Cancer and Nutrition) study [47]. Nuts and cooked tomato sauce using OO highlight the protective role against oxidative DNA damage [48,49,50]. This defense phenomenon was found in intervention studies in the human population after the consumption of tomato [51,52], broccoli [53,54], spinach [55,56], and blueberries [57,58]. In addition, a study in rats fed with a diet enriched with VOO found an association with less damage in the genetic material in peripheral blood cells vs. rats fed with sunflower oil [59]. In this context, MUFAs and PUFAs have been demonstrated to play a protective role against oxidative stress and DNA damage [60,61,62]. In a sub-analysis of the PREDIMED study, the intervention group with the MedDiet with MUFA (EVOO) or PUFA (walnuts) compared to the control (low-fat diet) showed a significant improvement in cardiovascular outcomes and a lower proportion of oxidative markers in urine [63]. Likewise, another clinical trial demonstrated better control of atherosclerosis markers in individuals on the MedDiet consuming OO; however, only the group whose main fat source was VOO decreased urinary 8-OHdG levels [64]. In general, the MedDiet and OO intervention groups showed positive results in the regulation of DNA repair genes. In fact, a low expression of the polymerase k gene, which encodes a protein that is responsible for replicating damaged DNA, was identified in the MedDiet and OO intervention groups [64]. Thus, this dietary pattern showed a favorable effect on blood pressure, insulin sensitivity, and lipid levels exerted in people with a high cardiovascular risk [65,66,67,68,69]. Modifications in dietary habits towards the Mediterranean pattern have been proposed as positive in the reduction in oxidative DNA damage in cancer patients [70]. In addition, several studies indicate an inverse association between adherence to the MedDiet and very prevalent neoplasms such as breast cancer, colorectal cancer (CRC), bladder cancer, or prostate cancer [71,72,73]. Specifically, individuals with CRC and high adherence to the MedDiet presented a lower histological grade and a lower frequency of synchronous adenomas compared to oncologic patients with low adherence to the MedDiet. In fact, elevated values of glutathione peroxidase (with antioxidant properties) and decreased 8-OHdG values were detected in patients with higher adherence to the MedDiet [74]. Regarding neurodegenerative diseases, a decreased risk of Alzheimer’s disease (AD) was associated with the direct effect of MedDiet components on the pathogenesis of AD [75,76]. The beneficial effects of this neurodegenerative disorder were primarily due to EVOO consumption. Oleuropein (one of the main phenolic components of green olive pulp) reduced Poly ADP-ribose polymerase (PARP)-1 activation, protecting neuronal cells from oxidative damage. Furthermore, Zhang et al. observed an age-dependent increase in 8-OHdG in human brain tissues, particularly in those belonging to people with AD [77]. In people with mild cognitive impairment, an increase in 8-OHdG was detected in certain brain areas, and this could be interpreted as a biomarker predictive of AD pathogenesis [78]. Thus, when evaluating oxidative DNA damage according to 8-OHdG values in patients with mild cognitive impairment who consumed EVOO for one year, 8-OHdG levels were reduced [79]. Overall, it seems that the Mediterranean pattern has potentially positive effects on genomic instability. Telomeres are nucleotide sequences at the ends of chromosomes, which progressively shorten with age. They are known as biomarkers of aging. Chronic oxidative stress is associated with telomere attrition [80]. In addition, inflammation stimulates telomere shortening by increasing the rate of hematopoietic stem cell replication to supply the leukocyte demand generated in the inflammatory process [81]. Although telomere length is inherited, it is influenced by external factors such as smoking, obesity, and a sedentary lifestyle. In turn, telomere shortening increases the risk of CVD, cancer, and mortality, especially at early ages [82,83]. Greater adherence to the MedDiet was associated with longer telomeres and greater telomerase activity [84,85], which could relate to lower levels of inflammation and oxidative stress [84,86]. In their meta-analysis, Canudas et al. established a positive association between MedDiet adherence and telomere length in the blood cells except for samples taken from men [87]. However, it should be noted that the included studies were cross-sectional and, therefore, did not establish causality. Nevertheless, this result can be contrasted with the two prospective studies conducted to date [88,89]. The work of Meinilä et al. prospectively studied 1046 Dutch subjects with a mean age of 61 years over a period of 10 years and did not establish an association between the male sex and adherence to the MedDiet. In the same study, women had faster telomere shortening [89]. On this subject, the only clinical trial found to date was by García-Calzón et al.; this was a sub-analysis of the PREDIMED-Navarra study, which evaluated 520 individuals, comprising 55% women aged 55–80 years. Three intervention groups were randomly assigned to a control or low-fat diet and there were two MedDiet groups, one supplemented with EVOO and the other with mixed nuts. In the cross-sectional analysis at the baseline, better adherence to the MedDiet was associated with longer telomeres only in women. However, assignment to the MedDiet-nuts group was associated with a higher risk of telomere shortening 5 years after the intervention, with no differences for the group supplemented with EVOO [88]. There was no consistent explanation for these findings, although cohort variables such as ethnicity, genetics, or sex could be related. In the work of Gu et al., a positive association was found between MedDiet adherence and telomere length in non-Hispanic white people [90]. This association was not found in African Americans or Hispanics [90]. However, in another sub-analysis of the PREDIMED-Navarra study, it was shown that the Pro12Ala polymorphism in the peroxisome proliferator-activated receptor γ2 (PPARγ2) gene interacted with MedDiet to prevent telomere shortening [91]. Regarding PUFAs, omega-3 was better than omega-6 since attenuated telomere shortening was shown in a cohort of people over 65 years of age with mild cognitive impairment supplemented with this kind of fatty acid [92]. Similarly, the Breitas–Simoes clinical trial demonstrated attenuation in telomere attrition in cognitively unimpaired elderly people who supplemented their usual diet with walnuts (a source of omega-3 PUFAs) for 2 years [36]. However, LA supplementation in a population of 299 elderly people with recent myocardial infarction was associated with increased leukocyte telomere length, and no relationship was established with other PUFAs [93]. In general, it can be concluded that it is beneficial to follow a healthy diet in which PUFAs are present. Telomere length has been linked to several types of cancer. The finding of short telomeres in CRC suggests that telomere shortening contributes to tumorigenesis and the genetic instability of premalignant cells. In fact, severely short telomeres have been shown to cause senescence in healthy cells or genomic instability in premalignant cells [83,94,95]. Indeed, altered telomere length homeostasis and unrepaired DNA damage were considered key in the onset, progression, and prognosis of CRC [95]. In this regard, the MedDiet could be useful primarily as a preventive therapy since several studies show the association between good adherence to the MedDiet and telomere preservation [84,91]. In addition, telomere shortening has been related to neurodegenerative diseases [96,97]. In fact, Guo et al. suggested that telomere length has a causal effect on the risk of AD due to oxidative stress and inflammation [97]. Furthermore, telomere shortening has been associated with cognitive impairment, amyloid pathology, and tau protein hyperphosphorylation in AD [96]. In this regard, the oleuropein aglicone from OO inhibits protein aggregation in AD [98]. Further, the Mediterranean diet could prevent telomere shortening after oxidative damage thanks to antioxidant-rich vegetables such as nuts and seeds [99]. Resveratrol (an antioxidant present in grapes) generated neuroprotective effects in a study on a mouse model of AD [100]. In summary, increased adherence to the MedDiet could attenuate telomere attrition. However, these beneficial effects could be limited to specific subgroups of the population. Further studies are needed to resolve the controversies raised. Epigenetics encompass inherited genomic changes that occur in the absence of direct DNA damage. Young, healthy individuals maintain compact chromatin and the optimal epigenetic regulation of biological processes. However, aging favors the accumulation of chromatin damage, which compromises genome integrity and alters cellular function [101]. DNA methylation (mDNA) is considered one of the best-known epigenetic markers. mDNA is used as a clock for the calculation of biological age [102]. The long interspersed nuclear element (LINE-1) was used as a marker of global mDNA because it is the most common repetitive sequence in the human genome, and 1/3 of mDNA occurs in LINE-1 [103,104]. Specifically, the hypomethylation of LINE-1 occurs during aging and is associated with multiple cancers and CVD [105]. In addition, oxidative stress plays a role in mDNA via the carbon cycle [42], so the more ROS there is, the greater the DNA damage; finally, DNA undergoes hypomethylation to defend itself [106]. In this context, a diet rich in antioxidants, such as the Mediterranean diet, is proposed as an epigenetic diet. To date, several studies have linked MedDiet adherence to LINE-1 hypomethylation. Specifically, there are two clinical trials that establish an inverse relationship between these two factors [107,108]. In the work of Agodi et al., women of childbearing age with low adherence to the MedDiet, particularly those with lower fruit intake, were at higher risk of LINE-1 hypomethylation [109]. This finding may be related to the fact that fruit is a folate-rich food, and folate is an important donor of methyl groups. Other more specific components of the MedDiet, such as nuts and EVOO, are able to induce methylation changes in several peripheral white blood cell genes related to diabetes, inflammation, and signal transduction, which may have potential health benefits [110]. Similarly, the MedDiet could contribute to delaying the process of carcinogenesis that is related to DNA methylation processes since several studies have shown lower LINE-1 methylation levels in different types of tumors, such as CRC or breast cancer [111,112]. Regarding CVD, the review published by Muka et al. supported the suggestion that global mDNA, according to repeated LINE-1 hypomethylation, is inversely associated with CVD risk independently of established cardiovascular risk factors [105]. In general terms, LINE-1 hypomethylation is linked to an unfavorable cardiovascular risk profile due to its association with diabetes, obesity, lower HDL-cholesterol levels, elevated total cholesterol levels, and inflammation [113,114]. However, the expression of RNA (ribonucleic acid) contributes to the epigenetic modulation of gene expression that alters cellular functionality. In this context, the overexpression of miR-155-3p has been linked to carcinogenesis [115]. In fact, Ping Li et al. detected an increased expression of miR-155-3p in relation to CRC tumor growth [116]. In addition, Let-7b, a regulator of histone H2B ubiquitination, showed a probable antitumor effect [117]. In respect of this line, Li et al. showed that let-7b-3p inhibited tumor growth and metastasis in lung cancer, correlating with the low expression of this molecule with poor prognosis in lung adenocarcinoma patients [118]. As a preventive therapeutic strategy, good adherence to the MedDiet could decrease the expression of miR-155-3p and increase the expression of let-7b-3p, improving the risk and evolution of cancer [119]. In relation to neurodegenerative diseases associated with aging, epigenetic modifications play important roles in AD [120]. Specifically, mDNA is a highly controlled mechanism involving nicotinamide adenine dinucleotide (NAD)-dependent deacetylase Sirtuin 1 (SIRT1) that prevents altered methylation [121]. In this regard, Luccarini et al. demonstrated that quercetin and other EVOO polyphenols activate the SIRT1 pathway with suggestive therapeutic and preventive benefits [122,123]. Therefore, it is likely that there is an age-related disease—epigenetic interaction that may benefit from a healthy Mediterranean pattern diet. Proteostasis, or protein homeostasis, refers to the work of a complex network of pathways that are essential for cell function and viability, ensuring the appropriate concentration, folding, and interactions of proteins from synthesis to degradation [5]. Specifically, chaperones and two proteolytic systems (the ubiquitin-proteasome and the lysosome-autophagy system) are responsible for the maintenance of proteostasis [124]. The progressive loss of cellular protein homeotasis is detected during aging, and proteomes that are more stable or more resistant to alterations are found in the longest-lived species [125]. The age-related deterioration of proteostasis affects chaperone functionality due to the cellular energy deficit that is inherent to senescence [126]. In addition, autophagy and the proteasome are altered with age, influencing proteotasis [127,128]. In this regard, experimental interventions that enhanced autophagy-activating properties were associated with healthier aging [129]. Dietary habits could be beneficial for the optimization of proteostasis. Indeed, MedDiet polyphenols such as resveratrol can directly activate autophagy [129]. Likewise, oleuropein has been highlighted as an autophagy enhancer through a protein mammalian target of rapamycin (mTOR) and the adenosine monophosphate-activated protein kinase (AMPK)-dependent mechanism [130]. Furthermore, the antioxidant properties of these MedDiet components could attenuate the excess of oxidized proteins associated with senescence and age-related diseases [131]. Age-related diseases such as neurodegenerative diseases (in particular, AD and Parkinson´s disease, PD) have been related to the deterioration of proteostasis [132]. In AD, hyperphosphorylated tau protein was aggregated abnormally and created insoluble neurofibrillary tangles, which were involved in neurodegeneration [133,134]. In addition, amyloid-beta (Aβ) peptide accumulated and formed plaques that damaged neuronal cells [135]. In relation to PD, aggregates of insoluble α-synuclein protein fibrils were present in the neurons of people with PD and were neurotoxic [136]. Overall, this loss of proteostasis in neurodegenerative diseases is closely linked to inflammation and cellular senescence [13,137]. Shannon et al. proposed the MedDiet as a mechanism by which to prevent neurodegeneration due to its modulating effect on protein homeostasis [30]. By enhancing autophagy, OO could mitigate the effects of toxic vascular agents, favoring the prevention of late-onset AD [29]. Specifically, oleocanthal could reduce tau protein polymerization [138]. The interaction between oleocanthal and tau proteins induces a tau rearrangement that may explain the antifibrillogenic effect of oleocanthal [139]. Thus, oleocanthal intervention in mice has been shown to increase the yield in the activity of blood–brain barrier transporter proteins that remove Aβ peptides (P-glycoprotein and low-density lipoprotein receptor-related protein 1). Thus, the percentage of degraded Aβ peptides was higher in the treated group [140]. The beneficial effect of oleocanthal in mice was extensible to human cell lines since an improvement in Aβ transport by Aβ-secreting cells was observed after administering oleocanthal for 72 h [141]. Further, resveratrol reduced β-secretase activity and Aβ-peptide aggregation in AD murine models and acted as a neuroprotectant in AD and PD [142]. In relation to CVD, alterations in protein homeostasis and stability in the proteome can influence healthy cardiac aging [143]. The increased accumulation of misfolded protein aggregates was detected in CVD by the downregulation of the HSP70 chaperone in vascular tissue during aging [144,145]. In general terms, decreased proteasome activity was detected in the atherogenic plaques of aged rats and elderly patients [124,146]. In this context, oleuropein raised the rates of proteosome-mediated degradation in human fibroblast cultures, their lifespan was increased, and senescence was delayed by 15% [147]. A diet rich in EVOO also increased messenger RNA levels of the autophagy marker LC3 in older rats compared to rats that were fed using other sources of dietary fat [148]. Urra et al. identified altered proteostasis as a hallmark of cancer. The hypermetabolism of cancer cells and the overexpression of oncogenes were related to ER stress. In response to this stress, the unfolded protein response (UPR) was generated [149]. Therefore, the UPR functioned as an adaptive mechanism during cancer progression [149]. Nevertheless, the activation of UPR at different stages of cancer evolution experienced a complex progression [149]. The role of the UPR during the early phase of cancer development prevented oncogene-induced malignant progression [150]. Cells surviving oncogene-induced apoptosis elevated UPR activation levels. Thus, in later stages of cancer progression, the UPR modified part of its function and contributed to tumor growth, aggressiveness, microenvironment adaptation, and resistance to treatment [149]. In fact, in human biopsies of breast cancer, lymphoma, or multiple myeloma, x-box-binding protein-1 (XBP-1), a protein that signals the activation of the UPR complex, was highly expressed and correlated with poor prognosis [151,152,153,154]. In addition, the IRE1α-XBP1 UPR signaling pathway was linked to the promotion of triple human breast [155], prostate [156], and hepatocellular cancers [157]. In this sense, MedDiet could prevent the perpetuation of this process. The work of Yubero-Serrano et al. observed that the MedDiet decreased the expression of genes relating to endoplasmic erythrocyte stress, such as XBP1 [158]. In addition, OO MUFAs “colonized” cell lipid membranes, which was associated with reduced susceptibility to ER stress and apoptosis [159]. In addition, secoiridoids such as oleuropein from EVOO favored the turnover of misfolded proteins in the cell by promoting compensatory UPR activity. Nevertheless, these bioactive compounds were able to inhibit the growth of highly aggressive mammary malignant cells [160,161]. Overall, the prevention of neurodegenerative, CVD, and oncological diseases may be of great interest given the proteostasis-activating role played by some components of the MedDiet. Nevertheless, further studies are needed to clarify the role of specific MedDiet nutrients in the prevention of these pathologies. These pathways are signaling systems responsible for detecting the availability of cellular resources that are essential for maintaining functionality, growth, and reproduction and thus participate in the aging process [162]. In fact, it is hypothesized that the proper regulation of these signaling pathways may extend lifespan and decrease the risk of age-related diseases [5]. In particular, the dysregulation of some nutrient-sensing pathways such as insulin/insulin-like growth factor-1 (IIS), mTOR, AMPK, and sirtuins was linked to an increased risk of non-inheritable diseases associated with age [5,163]. The IIS pathway is the most conserved aging control pathway in evolution, and it regulates glucose metabolism [5]. Multiple genetic polymorphisms or mutations that reduce the intensity of signaling in the IIS pathway were associated with an increased lifespan in mice [164]. Paradoxically, however, in physiological or pathological aging, growth hormone (GH) and insulin-like growth factor-1 (IGF-1) levels decrease [165]. This phenomenon is explained as a defensive response of the organism to minimize cell growth and metabolic response in a scenario of systemic damage [166]. Nevertheless, low concentrations of IGF-1 at the peripheral level are associated with an increased risk of type 2 diabetes mellitus, CVD, sarcopenia, osteoporosis, and frailty in elderly humans [167,168]. This has been explained by the decrease in insulin sensitivity that appears with age [168]. However, reduced IIS pathway signaling stimulates longevity-related Forkhead Box O (FOXO) proteins, which improve mitochondrial function and promote glucose metabolism through lipid oxidation [169]. In this regard, Calnan et al. proposed to control FOXO activity by up-regulating the expression of genes involved in resistance to metabolic stress and apoptosis to promote healthy aging [170]. Together with the IIS pathway, mTOR is the main accelerator of aging [5]. The mTOR pathway identifies high concentrations of amino acids, and its regulation has been associated with healthy aging. Specifically, mTOR is a kinase that is formed by two protein complexes: mTORC1 and mTORC2 [171]. In mice with low levels of mTORC1 or S6K1 (the ribosomal S6 protein kinase 1) activity (main substrate of mTORC1) and normal levels of mTORC2, increased life expectancy was detected [172,173]. The hyperstimulation of this pathway was frequently observed in diseases associated with aging, such as cancer [174,175], AD [176], and diabetes [177]. However, the inhibition of mTOR activity also showed undesirable effects, including wound healing problems, insulin resistance, and testicular degeneration in mice [178]. In contrast to the IIS and mTOR pathways that sense nutrient abundance and favor anabolism, AMPKs, and sirtuins sense nutrient scarcity and promote energy catabolism. In fact, the activation of AMPK promoted longevity by the inhibition of one mTOR complex, mTORC1 [179], and one of the sirtuins, SIRT1, could have triggered peroxisome proliferator-activated receptor gamma 1-alpha (PGC-1α) coactivator upon deacetylation [180,181]. This coactivator is involved in the transcription of antioxidant genes and is a key regulator of mitochondrial biogenesis [182] (Figure 2). In animal models, a dietary restriction has been shown to promote healthy aging mediated by nutrient-sensing pathways [183]. However, in humans, less stringent and more realistic interventions are being proposed [163]. In this regard, MedDiet, characterized by low-moderate protein intake, low glycaemic index, and polyphenol-rich foods, may be an alternative [184]. Polyphenol-rich foods activate the AMPK and sirtuin pathways, while mTOR is inhibited and autophagy is stimulated [185,186]. Interestingly, oleocanthal exhibited potent neuroprotective and antitumoral properties by inhibiting mTOR activity [187]. Antiproliferative effects were observed in certain breast cancer cell lines, although this effect was not fully clear in other neoplasms, such as CRC and cervical cancer, probably due to the lower expression of the mTOR pathway in these two malignant processes [141]. Moreover, oleuropein and HT showed an antidiabetic effect in addition to attenuating oxidative stress in rats with diabetes mellitus [188,189]. Further, adherence to the MedDiet may be of interest to patients with AD. In these cases, neurons presented a reduced activity of glucotransporters, GLUT1 and GLUT3, leading to altered insulin signaling [190], altering fasting blood glucose along with lipid metabolism dysfunction [191]. In addition, low IGF-1 values were detected with a low-glycemic-index diet compared with a high-glycemic-index diet [192], which could attenuate the signaling intensity of the IIS pathway favoring longevity. However, in the study of Levine et al., people aged from 50 to 65 years who ingested more protein (above 20% of the daily caloric intake) presented higher mortality, and 25% of deaths were associated with cancer [193]. Those individuals with moderate intake recorded a lower IGF-1 concentration by down-modulating the activity of the IIS and mTOR pathways [192,194]. In addition, high protein intake was linked to an increased risk of type 2 diabetes, obesity, and CVD [195]. Nevertheless, the protein quality is important. In this context, in murine models, methionine restriction showed a prolonged life expectancy and protection against multiple chronic diseases, particularly cancer [196]. Other essential branched-chain amino acids (in poultry, dairy, and eggs) such as leucine, isoleucine, and valine were identified as key in the regulation of insulin sensitivity via mTOR [197]. In fact, Fontana et al. reported that selective reduction in the dietary intake of branched-chain amino acids improved glucose tolerance, β-cell metabolic stress, and body composition [198]. Accordingly, there is robust evidence that some components of the MedDiet have properties that favor healthy aging, especially EVOO, so it would be interesting to further explore this through its action on nutrient signaling pathways. Mitochondria are cellular organelles that are responsible for producing much of the adenosine triphosphate (ATP) necessary for cell survival and modulating signaling toward apoptosis. Much of the total oxygen taken up by cells is metabolized in the electron transport chain located in the inner membrane of the mitochondria. The formation of ROS at this level represents potential intracellular damage to the organelle. In general, mitochondria are altered by oxidative damage with aging, and their deterioration is a consequence of the tissue’s inability to repair or eradicate the damage [199]. In the elderly, an excess of dysfunctional mitochondria can result in less energy in the form of ATP and more ROS than in the younger populations [5]. Indeed, this mitochondrial imbalance has been associated with age-related neurological diseases such as PD and AD [200,201], cancer [202], and metabolic syndrome [203]. Mitochondrial dysfunction is also implicated in the pathophysiology of type 2 diabetes mellitus, obesity, dyslipidemia, and CVD [203]. These pathologies are usually described as metabolic syndrome. Impaired mitochondrial energy metabolism is considered the main cause of metabolic syndrome [203]. Specifically, in type 2 diabetes mellitus, high glucose levels increase ROS production with consequent damage to the mitochondria [204] and inhibition of the IIF pathway, which favors lipid accumulation leading to metabolic disorders [205,206,207,208,209,210]. Aging, the alteration of mitochondrial antioxidant effects, and genetic factors promoting insulin resistance are the main causes of many metabolic diseases [203]. In this sense, the MedDiet with MUFAs and antioxidants may have a beneficial effect. In fact, different experimental models have demonstrated that components of MedDiet, such as polyphenols, plant-derived compounds, and PUFAs, could correct mitochondrial dysfunction and improve mitochondrial metabolism [211]. Indeed, the PREDIMED study demonstrated the cardiometabolic benefits [212]. Varela-López et al. demonstrated that OO has a favorable effect on the mitochondrial structure and function of aged rats [213]. Along the same lines, MUFA-rich OO played a key role in adapting the lipid profile of mitochondrial membranes to provide resistance against oxidative damage and dysfunction associated with aging [141]. In fact, the predominant dietary fat source impacted mitochondrial membrane biochemistry by modifying the fatty acid composition profile and electron transport systems [214]. In addition, PUFA sources favored the oxidation of mitochondrial membranes compared to saturated or MUFA sources [215]. In this sense, Ochoa et al. measured the mitochondrial fatty acid profile, catalase activity, and hydroperoxide levels in the liver, heart, and skeletal muscle of Wistar rats when supplemented with different fat sources (sunflower oil versus OO) [216]. Those with higher OO intake had more MUFAs in their mitochondrial membranes, and those fed mainly with sunflower oil had more omega-6 PUFAs. These variations were consistent with the levels of oxidative damage, i.e., those fed OO had fewer hydroperoxides in their body tissues compared to those who were fed sunflower oil. Therefore, a diet rich in OO generated membranes with fewer PUFAs, which attenuated an increase in age-related lipid peroxidation in post-mitotic tissues such as the heart and skeletal muscle [217]. Furthermore, in the liver (the prototype of regenerative tissue) and heart, a greater increase in catalase activity—essential for antioxidant defense in relation to life expectancy—was observed in rats who were fed a diet rich in OO [218,219]. However, HT and oleuropein reduce oxidative stress and optimize mitochondrial function [220,221]. HT improves neuronal inflammation and may delay the development of AD [222]. In fact, mitochondrial dysfunction is critical in the early stages of AD and PD, and the antioxidant power of wine polyphenols can protect organelles [200,223,224]. Quercetin and procyanidins (the main polyphenols in wine) can decrease ROS and improve the cell viability of neuronal and astrocytic cell lines [225,226]. Specifically, quercetin decreases ROS production through the overexpression of the AMPK/SIRT1 signaling pathway [227]. Resveratrol improved the antioxidant status in PD rats and reduced dopamine loss [228]. However, the mechanism by which resveratrol protects mitochondrial function and homeostasis is not fully understood but has been investigated for its potential applications in the treatment of age-related diseases [229]. Overall, several polyphenols are present in wine and individually carry out promising mitochondrial protection. However, Kurin et al. demonstrated greater antioxidant potency when combining several polyphenols with respect to their individual activity [230]. Thus, light to moderate wine intake in humans can favor the expression of antioxidant enzymes in the blood [231]. Although most of the studies evaluating the impact of MedDiet components on mitochondrial dysfunction were conducted in animals, they are also consistent with those conducted in humans. Fish oil, a high-omega-3 PUFA source, has a protective effect on age-related mitochondrial dysfunctions similar to that observed for OO. Afshordel et al. demonstrated that fish oil supplementation for 21 days restored the concentration of omega-3 PUFA derivatives, improving mitochondrial function and consequent ATP synthesis in the brains of older mice [232]. The benefits of omega-3 PUFAs in neurodegenerative diseases have been observed in preclinical studies, while most of the controlled clinical trials have not met expectations. In this regard, initiating clinical work prematurely in the course of the disease and increasing the durability of the study may be helpful in obtaining the expected outcomes [233]. In addition, in cerebral ischemia, DHA showed beneficial results, and the reduction in stroke events was related to less disruption of the blood–brain barrier, less brain edema, and less inflammatory cell swelling [234]. Cell membranes with high concentrations of peroxidized PUFAs, which are typical of aging, led to apoptosis and growth inhibition [202]. In fact, the main products of lipid peroxidation are toxic and mutagenic aldehydes such as malondialdehyde (MDA) and 4-hydroxynonenal/4-hydroxy-2-nonenal (HNE). In addition, elevated MDA values were recorded in the plasma and blood of patients with breast, lung, and ovarian cancer [235,236,237,238,239]. In the work of Li YP et al., HNE promoted breast cancer cell growth and angiogenesis [240]. In this sense, the antioxidant capacity of OO could attenuate peroxidation, preventing or defending against the activation of carcinogenesis [217]. In fact, EVOO could have a beneficial effect on breast cancer risk [241]. In conclusion, mitochondrial dysfunction and oxidative damage play a crucial role in the pathogenesis of aging and longevity-related diseases. Together, different components of the MedDiet, such as OO, PUFA, and red wine, contribute to the maintenance of mitochondrial function. However, more studies are needed to evaluate the synergistic effect of MedDiet components on this hallmark. Senescent cells often exhibit irreversible DNA damage, leading to cell cycle arrest. In addition, these cells produce a proinflammatory secretome or SASP that contributes to aging [242,243]. Cellular senescence is associated with other features of aging, including mitochondrial dysfunction, autophagy disorders, altered nutrient signaling, and epigenetic effects [5,244]. Overall, age increases the number of senescent cells, which increases the likelihood of age-related diseases [245]. This hallmark defends tissues from damaged and potentially oncogenic cells [5]. However, it requires progenitor cells with a regenerative capacity to compensate for the cellular deficit associated with aging [5]. Similar to DNA damage, exaggerated mitogenic (senescence-inducing) signaling is the other stress that is strongly associated with senescence. There are important cellular mechanisms that defend an organism against oncogenic or mitogenic alterations, such as the p16 INK4a/Rb and p19 ARF/p53 pathways [246]. Indeed, p16 INK4a (and, to a lesser extent, p19 ARF) levels correlate with age in most of the tissues analyzed [247,248]. In a meta-analysis performed by Jeck et al., the INK4a/ARF genomic locus was found to be the locus most closely linked to age-associated pathologies, including several types of CVD, diabetes, glaucoma, and AD [249]. Senolytic therapies, including dietary intervention, may delay or prevent cellular aging [250,251]. In fact, the MedDiet has demonstrated senolytic properties thanks to various food components. For example, nuts and certain vegetables seem to prevent the accumulation of senescent cells [53,55,252]. Further, the phenolic components of EVOO (oleocanthal or oleuropein), with antioxidant and anti-inflammatory effects, could play a relevant role in neurodegenerative diseases such as AD [253,254,255]. Specifically, tauopathy was associated with astrocyte or microglia senescence [256,257] and oleocanthal-reduced tau protein polymerization [138]. In addition, the Aβ peptide was identified as a potent inducer of cellular senescence [258,259,260,261,262]. The intervention with oleocanthal in mice showed increased performance in the activity of blood–brain barrier transporter proteins in charge of eliminating Aβ peptides (P-glycoprotein and low-density lipoprotein receptor-related protein 1), with the percentage of degraded Aβ peptides being higher in the treated group. The beneficial effect of olocanthal in mice may be extensible to human cell lines [141]. Resveratrol can delay or prevent senescence, as proven in human cell models (mesenchymal stem cells) [263,264]. Further, quercetin, when associated with Dasatinib (BCL family apoptotic inhibitors) in people with diabetic nephropathy, reduced the number of senescent cells in human adipose tissue [265]. However, there is clinical evidence of an association between age-related cardiac pathologies and the release of SASP components by senescent cells. The heart diseases that have been studied are heart failure, ischemia and myocardial infarction, and cardiotoxicity secondary to cancer chemotherapy [266]. However, the specific role of senescent cells in these conditions is unclear, and existing information is contradictory [266]. Presumably, the presence of maintained (and not transient) cellular senescence promotes deleterious effects in cardiac disease, such as the functional impairment of cardiac progenitor cells [267]. In addition, this hallmark can impair adult cardiomyocyte proliferation [267]. In this case, the MedDiet could reduce the production of proinflammatory substances since resveratrol inhibits the nuclear transcription of factor κB (NF-κB), which is essential for the genesis of SASP [268,269]. In addition, quercetin (associated with dasatinib) can facilitate programmed senescent cell death by inhibiting the PI3K-AKT pathway [251]. Furthermore, the antioxidant properties of the MedDiet can act on ROS by attenuating DNA damage and decreasing the excess number of senescent cells [42,68]. Regarding cancer, cellular senescence can protect tissues against tumorigenesis [270]. Indeed, anti-cancer therapies (chemotherapy or radiotherapy) induce senescence in cancer cells [271]. However, the persistence of therapy-induced senescent cells can be detrimental. Overall, a strategy that eliminates these persistent cells in the long term to minimize tumor progression and avoid adverse effects is of interest. Specifically, quercetin, in combination with dasatinib in aged mice, eliminated senescent cells and optimized cardiovascular function and survival [269,272]. However, in the elderly, senescent cells represent a high percentage of the cellular reserve, and this could jeopardize tissue structural integrity or affect vascular endothelial cells, leading to liver damage and the fibrosis of perivascular tissue with important repercussions on health [273,274]. In summary, the MedDiet may be useful as a senolytic tool, although more molecular studies are needed to clarify the synergistic action of the various anti-aging foods on tissue senescent cells. Stem cells in humans have the capacity for self-renewal and differentiation in various tissues [275]. A decrease in the regenerative capacity of tissues is characteristic of aging [5]. This is a consequence of intrinsic and extrinsic causes that generate a vulnerable scenario for stem cell preservation in all human tissues [276]. This scenario includes reduced cell-cycle activity in longer-lived stem cells [277], accumulated DNA damage [277], the overexpression of p16 INK4a (cell cycle inhibitory) proteins [278], and telomere shortening [279,280]. In addition, an optimal balance between the activation of cell regeneration and the inactivation of the cellular process is essential for proper cell function. Therefore, circuits that safeguard progeroid stem cells’ quiescence, such as INK4 induction and IGF-1 depletion, are essential [5]. Overall, the deterioration in stem cell regenerative capacity and its lack of control contribute to aging and increase the risk of age-related diseases. In the case of hematopoietic tissue, the regenerative potential diminishes with age, and immunosenescence occurs. This phenomenon can often favor subclinical inflammation, which contributes to the development of age-related diseases [281]. Some components of the MedDiet, in combination or separately, have shown benefits in attenuating stem cell depletion. In the work of Cesari et al., adherence to the MedDiet in very old people was associated with increased numbers of endothelial progenitor cells [282]. Endothelial stem cells are essential for maintaining vascular homeostasis and renewing injured vascular cells [283,284]. Thus, the MedDiet intervenes in the early stages of the atherosclerotic process, which could have important implications for the early prevention of CVD [30]. Particularly, oleuropein and oleacein play a protective role in the senescence of endothelial progenitor cells induced by angiotensin II (a key pathological factor in hypertension) [285]. In addition, oleopurein stimulates osteoblastogenesis and the mineralization of the cellular matrix and inhibits bone resorption. An increase in serum osteocalcin levels was detected in elderly patients on the MedDiet enriched with VOO [286,287]. Overall, the risk of osteoporosis was reduced, including a bone protective effect in a two-year intervention study derived from PREDIMED [286]. In relation to carcinogenesis, an increased incidence of hematological malignancies has been associated with immunosenescence [288]. In this sense, multiple polyphenols in OO preserve hematopoietic stem cells and their differentiation [141,289]. Further, there is an increased risk of aggressive and invasive skin cancers (melanoma and basal cell carcinoma) associated with aging and exposure to ultraviolet radiation [290,291]. Both circumstances induce the premature senescence of fibroblasts and the activation of fibroblast-to-myofibroblast transitions [290,292]. These findings could favor fibrosis along with the loss of skin elasticity and an increased risk of oncogenesis. As an anti-aging and preventive therapy against hyperplasia and skin cancers, resveratrol can induce anti-inflammatory and antioxidant changes [293]. However, further studies are needed to conclude with certainty the benefits of resveratrol. AD is included in the group of SASP or pathologies secondary to an altered secretome (growth factors, ROS, cytokines, and metalloproteinases). In fact, late astrocytes generate increased secretion of SASP factors that deregulate physiological functions. Dysfunctional astrocytes produce a chronic inflammatory response and pathologies of the central nervous system. In this context, altered synaptic plasticity, blood–brain barrier impairment, and glutamate excitoxicity with decreased neural stem cell proliferation have been observed [257,294]. As a preventive option to avoid this pathological condition, studies with DHA plus EPA supplementation have shown beneficial effects in patients with mild AD [295,296]. Therefore, MedDiet may be useful, as omega-3 PUFA-rich components are frequently ingested. Similarly, this consumption has shown a protective effect against the incidence of AD [296]. Flavonoids from cereals, vegetables, fruits, and OO had potentially beneficial effects, including free-radical scavenging, anti-inflammatory effects, and protection against Aβ neurotoxicity [297,298,299]. Further, the positive influence of polyphenols on cerebrovascular health is considered relevant, including lipoprotein oxidation, platelet aggregation, and endothelial cell reactivity [300]. In conclusion, MedDiet can be useful in the prevention of prevalent age-related diseases thanks to foods such as OO, which can palliate or slow down the deterioration of stem cells. However, more studies are needed to contrast this approach, as there are controversies on some points. Cellular coordination is essential for proper functionality. Different soluble molecules allow intercellular communication: cytokines, chemokines, growth factors, and neurotransmitters [301]. Multiple intercellular, endocrine, and neuronal pathways undergo alterations in the aging process. Specifically, neurohormonal signaling is altered in aging as inflammatory reactions increase and immune system reactivity to pathogens and precancerous cells decreases [5]. Aging is related to inflammation, one of the most relevant intercellular communication processes, and this association is multicausal. Among the causes are the accumulation of proinflammatory tissue damage by the increased secretion of cytokines and adipokines, excess ROS, immunosenescence, increased activation of the NK-κB pathway, changes in the gut microbiome and intestinal permeability, and altered autophagy response [302,303,304,305,306]. Thus, the elderly presents a low-grade systemic inflammatory phenomenon that favors age-associated chronic diseases and increases the risk of mortality [307]. The MedDiet demonstrated anti-inflammatory effects in relation to different markers, such as interleukin 6 (IL-6) or tumor necrosis factor-alpha (TNFα) [38,308,309]. In this context, multiple in vitro studies have positioned OO polyphenols as sources of health-promoting properties [141]. Zhang et al. highlighted the anti-inflammatory properties of HT mediated by the suppression of cyclooxygenase-2 (COX-2) and the expression of inducible nitric oxide synthase [310]. HT also reduces superoxide ions and inhibits the excess of important inflammatory mediators in humans, prostaglandin E2, probably due to the reduced expression of COX-2 [311]. Thus, it is intuited that the ability of polyphenols to regulate the production of proinflammatory molecules may have a salutary impact on older people. In addition to HT, other polyphenols such as oleocanthal and oleouropein inhibit TNFα-induced matrix metalloproteinase 9 through the anti-inflammatory pathway shared with ibuprofen (a non-steroidal anti-inflammatory drug that inhibits COX-2) [253,312]. Further, the flavonoid apigenin can act as an immunomodulator and principal regulator of TNFα in lipopolysaccharide-induced inflammation [313]. Atherosclerosis is an inflammatory disease and is closely linked to endothelial dysfunction. Dell’Agli et al. showed that OO polyphenols slow down the expression of proatherogenic molecules through the inactivation of NF-kB in endothelial cells [314]. These polyphenols were also potent against ROS, prevented the oxidative damage of genetic materials, and enhanced the antioxidant power of endothelial cells [315]. In this sense, the study of Meza-Miranda et al. determined that a breakfast based on VOO favorably regulated the pathophysiological mechanisms of premature atherosclerosis in endothelial cells [316]. Camargo et al. demonstrated that a breakfast rich in OO could curb the expression of proinflammatory genes and favor a less harmful inflammatory profile [317]. In addition, EVOO enhances the anti-inflammatory effect of high-density lipoprotein cholesterol and increases age-related antiatherogenic activity [318]. Moreover, the inflammation of neuronal cells is a fundamental mechanism in neurodegeneration. Proinflammatory immune-mediated mechanisms are essential in the pathogenesis and progression of AD and PD [319]. MedDiet has been associated with a lower risk of developing AD and PD [320]. In addition, the positive effects of omega-3 PUFAs on AD are due to their antioxidant and anti-inflammatory power. However, these PUFAs tend to oxidize. Therefore, the antioxidant capacity of polyphenols may be of interest as adjuvants [29]. This is more supportive of adherence to the Mediterranean diet than the individual intake of a certain food that is commonly present in the MedDiet. Further, fruits and vegetables (including in the MedDiet), with great antioxidant and anti-inflammatory properties, reduce the risk of PD [321,322]. Regarding carcinogenesis, senescent tumor cells produce SAPS that control the senescence of neighboring cells [323]. Initially, secretome factors could prevent tumor progression or eradicate malignant cells except in situations where there is acute aggression to SASP [323]. At this point, some polyphenols, such as quercetin and phytosine, exhibit senolytic properties through the inhibition of the PI3K-AKT pathway [324,325]. Regarding the most prevalent cancers today, MedDiet, when applied to CRC, has shown a protective effect thanks to different compounds [326]. Among them, oleuropein is promising as a protective agent against colitis-associated CRC, and in mice with induced CRC and inflammatory cytokines such as TNF-α, IL-6, and COX-2 decreased [327,328]. Further, oleocanthal could reduce the risk of inflammatory bowel diseases and CRC [329,330]. Therefore, the inflammatory response is regulated by OO polyphenols as they inhibit NF-κB, and this implies the lower expression of different interleukins and COX-2. This microenvironment hinders tumor proliferation [331,332]. Therefore, the evidence supports the suggestion that the MedDiet has anti-inflammatory properties and, consequently, may positively influence the aging phenotype. The gastrointestinal tract is colonized by an array of microorganisms, including bacteria, viruses, fungi, and protozoa. These coexist symbiotically with enterocytes without being identified by the immune system as pathogens [333]. These microorganisms make up the microbiota, which consists of a total of 52 different phyla and up to 35,000 species of bacteria, mainly Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria [334]. The intestinal microbiota has its origin in the placenta, with low levels of non-pathogenic bacteria, mostly Bacteroidetes, and Firmicutes. After birth, the intestine of the newborn and infant is rapidly colonized. Factors such as the type of delivery (vaginal or caesarean) or the type of feeding (breastfeeding or formula feeding) are determinants of the microbiota [333]. During the first three years of life, the microbiota has low diversity. After the third year, the microbiota is similar to that of the adult stage. With aging, changes occur in the morphology and function of the microbiota. Thus, after 65 years of age, the microbiota experiences a decrease in Firmicutes and Bifidobacterium, with an increase in diversity for Clostridium [28]. The changes produced throughout life could alter the diversity of the microbiota, giving rise to metabolic and inflammatory alterations and causing the appearance of conditions such as inflammatory bowel disease or irritable bowel syndrome, among others [335]. Moreover, the microbiota has not only been linked to diseases of the gastrointestinal tract but also to other diseases such as obesity, diabetes, CVD, or cancer [336]. In fact, since the concept of the “gut–brain axis” was created, gut microbiota has also been linked to neurodegenerative diseases [337]. The mechanisms by which the microbiota change with age are not fully understood. It is known that, in aging, physiological changes occur, such as alterations in dentition or decreased digestion and absorption, and modifications of lifestyle conditions, such as hospitalization or nursing homes. These modifications could be responsible, in part, for changes in diet and thus for the nutritional status of the elderly [338]. Moreover, in aging, especially in respect of frailty, there is usually a reduction in the amount and variety of food, which leads to the appearance of malnutrition [339]. Diet seems to be one of the pillars of changes in the microbiota. The microbiota may modulate changes in aging-related to innate immunity, cognitive function, and sarcopenia, which are components of frailty syndrome [340]. In fact, recent studies have suggested that loss of the gut microbiota is more related to age-associated frailty than to chronological age [341]. During the transition from adult to elderly, the main changes in the intestinal microbiota occur. Microbial diversity decreases compared to young adults [342]. In elderly centenarians, the microbiota consists mostly of Bacteroidetes and Firmicutes. However, in comparison with young adults, there are changes in subgroups such as Firmicutes, with an increase in Bacilli and a decrease in Clostridium. In addition, there is also an increase in Protebacteria [343]. Intestinal dysbiosis mainly involves changes in the abundance of commensal bacteria, also including some that function as opportunistic pathogens. The importance of the dysbiosis phenomenon is that it stimulates the excretion of endotoxins, i.e., amyloid and microbial lipopolysaccharides, to promote intestinal wall permeability and increase the peripheral circulation of proinflammatory cytokines [344]. In the ELDERMET study, the microbiota was studied in elderly people living in a community or living in long-stay homes in Ireland [338]. In the first group, microbiota configurations were more affected by antibiotic use than the microbiota of individuals in long-stay residences. However, this first group presented greater recovery after antibiotic use. The second group showed a loss of microbial components associated with ill health and a gain in altered microbiota associated with aging [338]. These findings on the relationship between microbiota, diet, and health status are supported by Claesson et al. [342]. They demonstrated, through an analysis of the composition of the fecal microbiota separated in 178 elderly subjects, that a change in diet associated with a transfer to a nursing home caused a change in the composition of intestinal bacteria, which correlated with nutritional status, inflammatory markers, comorbidity, and frailty [342]. Thus, the aging process and other environmental factors may alter the composition of the microbiota and contribute to the development of chronic low-grade inflammation [7]. Therefore, maintaining diversity in the microbiota appears key to maintaining health status and preventing frailty. Diet has a major impact on the biology of the gut microbiota [345]. Some nutrients have effects on the structure, function, and secretion of metabolites of the gut microbiota that can modulate immune functions and multiple metabolic and inflammatory pathways [346,347]. Emerging evidence is showing that adherence to the MedDiet promotes beneficial effects on the microbiota, favoring microbial diversity mainly in the colon, and it is associated with a reduction in Clostridium and an increase in Bacteroidetes and Firmicutes [28] (Figure 3). Variations in the microbiota have been linked to the development of diseases. The microbiota can be modified through diet. In fact, polyphenols from the MedDiet play a key role in the microbiota. These compounds can reach the gut microbiota and modify the bacterial population and its metabolism. In this respect, it has been reported that the administration of polyphenols in rats, specifically resveratrol and curcumin, was associated with alterations in the Bacteroidetes and Clostridium groups of bacteria, thus providing metabolic benefits in glycemic control [348]. Additionally, the high content and bioavailability of fiber in the MedDiet (two times higher than in a Western diet) have beneficial effects on the cardiovascular system of older adults. These benefits could be due, in part, to changes in the microbiota. Fiber appears to have a positive impact on the composition of the gut microbiota, increasing the number of beneficial bacteria, inhibiting the growth of pathogens, and reducing atherogenic serum cholesterol in the microbiome. It also prevents glucose intolerance by reducing postprandial hyperglycemia through the formation of a viscous layer around the small intestine, which slows down the chyme transition [7]. This, in turn, increases the thickness of the aqueous layer through which solutes must pass to reach the enterocyte membrane, leading to a decrease in glucose in the enterocyte blood and resulting in a decreased absorption of glucose, lipids, and amino acids [7]. High fiber intake has been found to promote modifications of the gut microbiota with an increase in Bacteroidetes (in particular, Bacteroides acidifaciens), which produce high levels of short-chain fatty acids, including acetate, butyrate, and propionate [349]. Some of the beneficial effects of these metabolites are thought to be mediated by binding to specific G-protein-coupled receptors expressed on enteroendocrine and immune cells [349]. Conversely, poor adherence to the MedDiet was associated with an increase in l-Ruminococcus and Streptococcus bacteria and an increased concentration of trimethylamine N-oxide (TMAO) in urine. Compared to the Western diet, the MedDiet has significantly lower contents of choline and L-carnitine (present in egg, cheese, and red meat), and the production of TMAO by the microbiota has been shown to be lower [350]. This could reduce the risk of CVD, independent of the presence of cardiovascular factors. Zhu et al. concluded that an elevated level of TMAO could also be involved in the pathogenesis of obesity and type 2 diabetes mellitus, as it induces vascular inflammation and a prothrombotic effect by increasing platelet hypersensitivity to multiple agonists [351]. Indeed, the review by Cornejo-Pareja et al. concludes that the increase in fat mass in obese patients is not only due to more efficient energy uptake but that the microbiota is involved in changes in endotoxemia, intestinal permeability, insulin resistance, the hormonal environment, the expression of lipogenesis regulatory genes, interaction with bile acids and changes in the proportion of brown adipose tissue [352]. Numerous epidemiological studies have supported the importance of lifestyle factors and exposure to known or suspected carcinogens in the development of cancer. In fact, it is estimated that 30–35% of cancer risk factors are associated with diet, physical activity, and/or energy imbalance [353], and 15–20% of cancers are caused by infectious agents [354]. The microbiota that inhabits our body can be considered an environmental factor to which we are continuously exposed throughout life. However, the underlying mechanisms by which the MedDiet decreases the risk of cancer are not entirely clear [355]. In the diet–microbiota interaction, it has been observed that many dietary and digestive components are metabolized by bacteria in the gastrointestinal tract, leading to tumor suppressor metabolites and putative oncometabolites [356,357]. As an example, the excessive consumption of red meat, present in the Western diet, is a risk factor for CRC and other cancers by several mechanisms, including some that are dependent on intestinal bacteria. Elevated levels of protein intake can lead to an increase in certain types of bacteria, including Bacteroides and Firmicutes. These ferment amino acids into N-nitroso compounds, which induce DNA alkylation and mutations in the host [357]. Proteobacterias that encode nitroreductases and nitrate reductases are also related to this process, which is strongly associated with inflammation [358]. In addition, in the process of the digestion of saturated fat associated with red meat consumption, approximately 5% of the primary bile acids escape from the enterohepatic circulation and reach the colon, where they are converted by bacteria into secondary bile acids. Primary cholic acid is converted to secondary deoxycholic acid by certain bacteria, including Clostridium scindens. Secondary deoxycholic acid functions as a tumor promoter by disrupting cell membranes to release arachidonic acid, which is converted by cyclooxygenase-2 and lipooxygenase into prostaglandins and ROS that trigger inflammation and DNA damage [359]. By contrast, the dietary fiber present in the MedDiet is fermented by certain types of colonic bacteria, such as Clostridium groups IV and XIVa, into short-chain fatty acids. Butyrate, which is one of the most abundant short-chain fatty acids, is the main source of energy for colonocytes and is involved in the prevention of CRC. It has been observed that butyrate probably exerts its tumor-suppressive properties through multiple mechanisms. Butyrate epigenetically regulates the expression of genes that are involved in apoptosis and cell proliferation apoptosis [116]. It also acts as a ligand for certain G-protein-coupled receptors due to its involvement in tumor suppression [360]. Both mechanisms are believed to be important for butyrate’s ability to induce regulatory T cells. In addition, butyrate helps maintain the epithelial barrier function, which is important for preventing inflammation. Other components of the MedDiet that are related to cancer prevention are polyphenols. Ellagitannins are polyphenols found in nuts and berries. When they reach the intestine, they are modified by the microbiota and transformed into different compounds. Urolithin is one of the most studied products, and it has been shown that it can be absorbed by the enterohepatic circulation and transported by the blood and thus distributed to different tissues. It has anticarcinogenic effects through the inhibition of the Wnt signaling pathway, which could have a protective effect against CRC [361]. Thus, our diet dictates whether the microbiota produces metabolites that exacerbate or enhance tumor progression [362]. Regarding neurodegenerative diseases, better cognitive functions and a lower risk of dementia have been associated with higher adherence to the MedDiet. The PREDIMED study demonstrated a modest beneficial effect of adherence to the MedDiet for 4–6 years on cognitive functions in cognitively healthy adults at high risk of CVD, especially in the domains of global cognition, memory, and executive function [363,364]. By contrast, no benefit on cognitive function was reported after 1 year of the MedDiet in older adults in the NU-AGE trial. However, participants with higher adherence to the MedDiet demonstrated better global cognition and episodic memory compared with those that have low adherence [365]. These benefits appear to be related to certain components of MedDiet (omega-3 fatty acids, antioxidants, and polyphenols) as they may inhibit neuroinflammation associated with AD and other degenerative diseases [366]. Changes in the microbiota could also be involved in the pathogenesis of these diseases by initiating and perpetuating neuroinflammatory processes. In this respect, a study demonstrated the existence of the brain microbiota in cerebral blood vessels through micrographs of the human brain [367]. These bacteria and gut-derived toxins appear to compromise the integrity of the blood–brain barrier and could contribute to early neuroinflammatory changes by stimulating microglia and hindering amyloid clearance [368,369]. In addition, microbial amyloid and circulating liposaccharides activate innate resistance receptors, such as the Toll-like receptor and the receptor for advanced glycation end products, to increase proinflammatory signaling and to promote chronic neuroinflammation and progressive neurodegeneration, especially in sensitive brain regions such as the hippocampus [368,370]. Moreover, the microbiota has also been linked to other disorders, such as epilepsy. In fact, one study in epileptic patients found that antibiotic treatment reduced seizure frequency by 10% [371]. Nearly 60% of the variation in gut microbiota is attributable to diet [372]; therefore, modulation of the gut microbiota through diet could be an effective approach for reducing the inflammation associated with neurological diseases. Preliminary data have shown positive associations between the MedDiet and increased numbers of beneficial species of the microbiota, e.g., Bacteroidetes, and their short-chain fatty acid metabolites, which have anti-inflammatory effects [373,374]. However, only a few studies have evaluated dietary patterns and gut microbiota, most of them being observational, which prevents establishing causality [375,376]. Further research is therefore needed to understand the complex relationships between the gut microbiota and cognitive health and whether diet-induced effects are mediated by alterations in gut microbiota. All of this is important because increasing evidence suggests that the reprogramming of gut microbial functions through long-term adherence to healthier diets can influence physiological responses to nutrients and other features of host biology that are critical to promoting health and longevity [377]. Thus, the modification of the microbiota through MedDiet could benefit the evolution and prognosis of these diseases. Interventional studies involving animals or humans, and other studies that require ethical approval, must list the authority that provided approval and the corresponding ethical approval code. A comprehensive search of the literature published in PubMed from November 2022 was conducted to identify articles relating to MedDiet, microbiota, aging, and frailty. Search strategies were based on the following search terms: MedDiet, polyphenols, omega-3 PUFAs, healthy aging, hallmarks of aging, telomere length, microbiota, oxidative stress, mitochondrial function, inflammation, cellular senescence, anti-senescence compounds, frailty, and sarcopenia. A selection of articles published in English providing original human research, observational prospective and retrospective studies, randomized controlled trials, reviews, and meta-analyses were included. In addition, we considered case series, single-case reports, editorials, research or original articles, letters to the editor, comments (on an article or from the editor), responses (to a comment, letter, or article), corrections, short reports, short communications, perspectives, opinions, and discussions. Priority was given to the largest studies and to the strongest available evidence and most recent studies. There is an increasingly aging global population. However, the way to achieve healthy aging has not yet been fully elucidated. The loss of function and frailty syndrome associated with aging increases the vulnerability of the elderly and their propensity to disease. There are different molecular pathways or hallmarks involved in aging that bring us closer to understanding the deterioration associated with the senescence process, such as genomic instability, telomere attrition, epigenetic effects, proteostasis, nutrient-sensing pathways, mitochondrial dysfunction, cellular senescence, stem cell depletion, and altered intercellular communication. Likewise, microbiota disturbances seem to play a relevant role in frailty in the elderly. It has been shown that MedDiet promotes healthy aging, increasing the life expectancy of the population. This review has shown that MedDiet positively influences the molecular pathways that determine age. Consequently, MedDiet has been associated with a lower risk of age-related diseases, mainly CVD, neurodegenerative, and oncological diseases. Therefore, further evidence of the beneficial effects of this dietary pattern on human health and longevity has been provided. However, most studies do not evaluate the impact of the Mediterranean diet pattern as a whole on the hallmarks of aging but rather its individual components, especially certain bioactive components. Certainly, there are some clinical trials exploring the role of the Mediterranean diet (mostly PREDIMED substudies), but they focus on specific dietary supplementation with nuts or EVOO. Therefore, it would be useful to evaluate the pattern as a whole without special emphasis on these more studied components. In addition, more quality studies on the MedDiet and the prevention of frailty and disease in aging are needed, as many studies are observational, and causality cannot be determined. Overall, more research is needed to provide a better understanding of the mechanism of action of MedDiet on aging. However, at present, MedDiet could be recommended as a baseline anti-aging therapy to prevent frailty and maintain functionality until the later stages of life, as the benefits of MedDiet on human health present robust evidence.

PMC10003252

Adrianna Szczakowska,Agata Gabryelska,Oliwia Gawlik-Kotelnicka,Dominik Strzelecki

Deep Brain Stimulation in the Treatment of Tardive Dyskinesia

27-02-2023

tardive dyskinesia,schizophrenia,antipsychotics,deep brain stimulation

Tardive dyskinesia (TD) is a phenomenon observed following the predominantly long-term use of dopamine receptor blockers (antipsychotics) widely used in psychiatry. TD is a group of involuntary, irregular hyperkinetic movements, mainly in the muscles of the face, eyelid, lips, tongue, and cheeks, and less frequently in the limbs, neck, pelvis, and trunk. In some patients, TD takes on an extremely severe form, massively disrupting functioning and, moreover, causing stigmatization and suffering. Deep brain stimulation (DBS), a method used, among others, in Parkinson’s disease, is also an effective treatment for TD and often becomes a method of last resort, especially in severe, drug-resistant forms. The group of TD patients who have undergone DBS is still very limited. The procedure is relatively new in TD, so the available reliable clinical studies are few and consist mainly of case reports. Unilateral and bilateral stimulation of two sites has proven efficacy in TD treatment. Most authors describe stimulation of the globus pallidus internus (GPi); less frequent descriptions involve the subthalamic nucleus (STN). In the present paper, we provide up-to-date information on the stimulation of both mentioned brain areas. We also compare the efficacy of the two methods by comparing the two available studies that included the largest groups of patients. Although GPi stimulation is more frequently described in literature, our analysis indicates comparable results (reduction of involuntary movements) with STN DBS.

Deep Brain Stimulation in the Treatment of Tardive Dyskinesia Tardive dyskinesia (TD) is a phenomenon observed following the predominantly long-term use of dopamine receptor blockers (antipsychotics) widely used in psychiatry. TD is a group of involuntary, irregular hyperkinetic movements, mainly in the muscles of the face, eyelid, lips, tongue, and cheeks, and less frequently in the limbs, neck, pelvis, and trunk. In some patients, TD takes on an extremely severe form, massively disrupting functioning and, moreover, causing stigmatization and suffering. Deep brain stimulation (DBS), a method used, among others, in Parkinson’s disease, is also an effective treatment for TD and often becomes a method of last resort, especially in severe, drug-resistant forms. The group of TD patients who have undergone DBS is still very limited. The procedure is relatively new in TD, so the available reliable clinical studies are few and consist mainly of case reports. Unilateral and bilateral stimulation of two sites has proven efficacy in TD treatment. Most authors describe stimulation of the globus pallidus internus (GPi); less frequent descriptions involve the subthalamic nucleus (STN). In the present paper, we provide up-to-date information on the stimulation of both mentioned brain areas. We also compare the efficacy of the two methods by comparing the two available studies that included the largest groups of patients. Although GPi stimulation is more frequently described in literature, our analysis indicates comparable results (reduction of involuntary movements) with STN DBS. Tardive dyskinesia (TD) is a group of symptoms characterized by irregular and involuntary movements that most commonly affect the tongue, lips, jaw, face, and sometimes the peri-orbital areas. In some cases, patients also have irregular movement of the trunk and limbs [1,2]. Tardive dyskinesia (TD) might be also present as tremor, akathisia, dystonia, chorea, tics, or as a combination of different types of abnormal movements. In addition to movement disorders (including involuntary vocalizations), TD patients may have various sensory symptoms, such as the urge to move (as in akathisia), pain, and paresthesia [3]. TD is a specific type of secondary dystonia, mainly caused by the chronic use of dopamine receptor antagonists. The onset of TD usually occurs after years of taking neuroleptics but may also appear earlier, even after several months. The risk is related, among others, to the strength of the drug binding to the dopaminergic D2 receptor. In the elderly, symptoms may become apparent after a shorter period of use of the drug, the early onset of these symptoms and their intensity may indicate features of organic brain damage [4]. Due to the need for long-term treatment, neuroleptics are the main reason for TD’s appearance in clinical practice. Nevertheless, when using other antidopaminergic drugs such as antiemetics (domperidone, bromopride, and metoclopramide); antidepressants such as trazodone, amitriptyline, clomipramine, fluoxetine; and sertraline or calcium channel blockers, the risk of TD appearance, while significantly lower, should be highlighted [5]. Interestingly, tardive dyskinesia can appear both during the use and after the discontinuation of neuroleptics. The prevalence of tardive dyskinesia is estimated at 0.4–9% in patients receiving antipsychotics, while some studies indicate a more frequent occurrence of TD (20–50%) [6,7]. According to the DSM-5, TD can be diagnosed when antipsychotic-induced tardive dyskinesia follows exposure to neuroleptics for at least three months (one month in individuals aged ≥60 years) and persists for at least one month after the last dose of the drug [8]. This iatrogenic complication may persist long after drug discontinuation and might become permanent [1,6]. TD often results in disability, with mild to severe functional impairment (significantly impaired gait, speech, and swallowing) in about 10% of cases, causing a heavy burden on both patients and their caregivers [6]. In addition to physical burden and pain, tardive dyskinesia leads to social exclusion and ostracism in patients with these symptoms. The involuntary movements typical of TD are a significant burden for patients in a social context, representing one of the archetypal images of mental illness and a reason for stigmatization. Aside from pharmacological interventions (changing the dose or the drug) or implementing TD-targeted treatment, there is a promising method that may offer new opportunities for this group of patients—deep brain stimulation (DBS). DBS is a clinical procedure in which a precisely controlled electric current is passed through electrodes surgically implanted in the brain. This method enables rapid and, more importantly, long-term improvement in motor function and quality of life (QoL) in patients with TD [1,5]. It is of key importance that TD has a genetic predisposition, which mediates the risk for TD development [5,9]. Nevertheless, the usage of dopamine receptor antagonists is responsible for the exposure of this predisposition [10,11]. Table 1 shows the factors associated with an increased risk of TD [12,13,14,15,16,17,18,19]. Table 2 summarizes the genetic factors that modulate the risk of TD [20,21,22,23]. The main pathogenetic mechanisms associated with the development of TD are the hypersensitivity of postsynaptic D2 receptors and their upregulation associated with their long-term blockade. This leads to changes in cortico-striatal transmission and motor symptoms [24]. The abnormalities also concern the increase in blood flow in the prefrontal cortex, the anterior cingulate gyrus, and the cerebellum, which accompany the increase in the activity of the prefrontal and premotor cortex during the appearance of involuntary movements, which may indicate a decrease in impulse selection and lead to the appearance of involuntary movements [25]. The constant blocking of D2 receptors along with D1 activation may also be important to explain the appearance of symptoms over a longer period of time and their irreversibility [26]. However, it seems that not only disorders of dopaminergic transmission are involved in the development of TD, but changes in serotonergic, glutamatergic, cholinergic, and opioid transmission may play a supportive role [27,28]. The involvement of the serotonin system in TD is indicated by studies on animal models. It was found that inhibition of serotonergic neurons with 8-OH-DPAT (8-hydroxy-2-(dipropylamino)tetralin significantly reduces TD severity. 8-OH-DPAT is one of the first discovered agonists of the serotonergic 5-HT1A receptors. It mediates hyperpolarization and reduction of the firing rate of the postsynaptic neuron. Conversely, administration of fenfluramine or fluoxetine (both increasing the level of serotonin) suppressed the previously obtained improvement. Preclinical studies indicate that deep brain stimulation of the subthalamic nucleus (STN DBS), a technique described latter in this article, reduced the release of 5-HT in the hippocampus and prefrontal cortex, while deep brain stimulation of the EPN (entopeduncular nucleus, internal globus pallidus (GPi) equivalent in rodents) did not affect 5-HT release. Nevertheless, both STN and EPN DBS attenuate TD with equal effectiveness, despite their different effects on the 5-HT system, leading to the conclusion that the mechanism of 5-HT reduction does not determine the effectiveness of DBS in rats. Oxidative stress and related neuronal damage both might also participate in the etiology of TD. Antipsychotics, especially classic drugs, may be toxic by directly inhibiting complex I of the mitochondrial electron transport chain. Toxicity may also result from the increased production of free radicals and hydrogen peroxide, which are a consequence of the blockade of the D2 receptor and an increase in dopamine turnover [20,29,30]. The weakening of the antioxidant mechanisms may explain the progressive nature of the changes and their irreversibility [31,32,33]. In neuroimaging studies, a decrease in the caudate nucleus volume was observed in the group of patients diagnosed with schizophrenia with TD compared to those with this psychosis without dyskinesia [10,34,35]. The most widely used instrument to assess TD is the Abnormal Involuntary Movement Scale (AIMS). The patient performs several tasks described in the instructions. On that basis, the severity of facial and oral movements, extremity movements, trunk movements, and global judgments is scored on a 0–4 scale (up to 40 points in total) [36]. A separate evaluation concerns dental status (with an annotation yes/no). Another scale is The Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS), which consists of movement and disability subscales. This tool measures dystonia in nine body regions (incl. the eyes, mouth/speech and swallowing, neck, trunk, arms, and legs; each extremity is assessed individually) with scores ranging from 0 (lack of symptoms) to 120 [37]. TD treatment is difficult and often leads to disappointing results, so the best method is to prevent its onset [38]. Atypical antipsychotics have a lower potential to cause TD. The drugs should be used in the lowest effective doses, particularly if TD appeared earlier or the current treatment induced its onset. When TD appears, initially, it is necessary to reduce the drug dose or, if this does not eliminate TD, switch to a drug with a lower potential for inducing TD, such as clozapine or quetiapine. The pharmacological treatment of TD is challenging; conventionally administered pharmacotherapies are only beneficial at the initial stage, and the available data point to a lack of satisfactory outcomes in long-term use [6]. VMAT2 (vesicular monoamine transporter 2) inhibitors: tetrabenazine, valbenazine, and deutetrabenazine are the first drug group recommended for TD treatment [2]. In randomized controlled trials, valbenazine and deutetrabenazine demonstrated efficacy in ameliorating TD symptoms with a favorable benefit–risk ratio. For this reason, valbenazine and deutetrabenazine should be considered a first-line treatments for TD. While the currently available evidence suggests that tetrabenazine is another good option for TD, it is not considered a first-line drug due to greater side effects than other VMAT2 inhibitors and very few studies. Amantadine (300 mg per day) may be used when these treatments are ineffective or contraindicated. However, evidence to support the use of amantadine for TD is scarce and limited to short observations [2]. Another discussed treatment option is the short-term administration of clonazepam, but the effectiveness of this method is also limited. Furthermore, considering the acute and long-term consequences (sedation, cognitive decline, tolerance, addiction, and risk of falls, especially in the elderly), routine use of benzodiazepines is not recommended [2,6]. The use of Vitamin E does not improve TD symptoms but may prevent their worsening. When other options fail, some authors recommend pyridoxine (vitamin B6) use, but the optimal dose and treatment duration has not been established yet [2]. In focal dystonia, such as cervical dystonia, botulinum toxin injection may be applied. It is a highly effective approach, but the level of satisfaction with this treatment is low in some of the patients, and they fail to follow up for repeated injections. Therefore, the pharmacotherapeutic method should be regarded as adjuvant therapy instead of a priority choice (the dose reduction of the TD-inducing drug or change to another drug if possible) as the symptoms progress to the advanced stage [6]. The level B recommendations of the American Academy of Neurology for TD treatment indicate clonazepam, Gingko biloba extract (EGb-761), and diltiazem, while amantadine, tetrabenazine, galantamine, and eicosapentaenoic acid are level C. Other test substances, including reserpine, bromocriptine, biperiden, selegiline, vitamin E, vitamin B6, baclofen, and levetiracetam, have not received a recommendation from the academy at this stage [39]. Newer recommendations position new-generation VMAT2 inhibitors (deutetrabenazine and valbenazine) at level A of recommendation, clonazepam and Ginkgo biloba at level B, while amantadine, tetrabenazine, and GPi DBS (globus pallidus internus deep brain stimulation) are at level C [40]. The American Psychiatric Association (APA) indicates a reversible inhibitor of the VMAT2 (deutetrabenazine and valbenazine as more studied than tetrabenazine) as the first-line treatment for TD [41]. In recent decades, DBS has been successfully used to treat several movement disorders, including Parkinson’s disease and dystonia. More recently, DBS has also been used to treat patients with tardive dyskinesia and OCD, especially in drug-resistant forms [6,7]. Monopolar (unilateral) stimulation modes are the most commonly used, although we also have descriptions of bipolar mode [42,43,44,45,46]. In addition to the potential for rapid and long-term improvement, the advantages of DBS include its relatively nondestructive nature, adjustability, reversibility, and the ability to perform DBS bilaterally in a single surgical session [6,47]. According to the available studies, this method is safe and minimally invasive, with no severe complications during the follow-up periods [6]. The disadvantages of the DBS technique are the requirement for continuous follow-up visits with repeated optimization of pacing parameters (it can also offer potential parameter adjustments) and the risk of hardware complications (incl. electrode displacement, battery depletion, inflammation around parts of the device) [47]. When the effectiveness of pharmacotherapeutic methods is unsatisfactory and symptoms are chronic and very severe, DBS becomes the treatment of last resort [48]. The primary criterion for inclusion in DBS is a high severity of symptoms that significantly impede function and have lasted for more than a year, with no satisfactory response to pharmacological treatment with clozapine or tetrabenazine for at least four weeks at the highest doses tolerated by the patient. Exclusion criteria are similar to those for patients with other dystonias—significant cognitive impairment, unstable mental status, severe depressive symptoms, and comorbid medical problems that may increase surgical risk; an initial brain scan before the decision on DBS applicability is recommended [45]. In addition to correct patient selection and electrode placement (more effective by image guidance or microelectrode recording implemented in leading centers), proper and time-coordinated programming of the equipment is crucial. This is important because we already have multisegment electrodes (from Abbott/St. Jude, Boston Scientific, and Medtronic), and each segment’s current characteristics can be programmed separately. It complicates programming (current of different amplitude, frequency, amperage, and pulse width can be used) but certainly expands the possibilities for stimulation. Once the electrode has been placed, the adjustment of the electrical field optimizes the clinical outcome. It allows continuous monitoring of the effectiveness of the stimulation and provides an opportunity to implement modifications, but it becomes vital when the initially planned electrode placement has failed (in about 40%). The typical inaccuracy of surgical robots or stereotaxic methods is 1–2 mm. In addition, during surgery, the brain can change position by 2–4 mm, which can be minimized by a staged operation [49,50,51,52,53,54,55,56,57,58]. A similar problem arises when the electrode is displaced. Reprogramming often avoids reoperation and allows optimization of parameters if the dislocation is not critical [59,60]. It is worth adding that no clear guidelines have been developed so far, although there are recommendations regarding the programming of stimulators [61,62,63]. In programming, it is important to be aware of the temporal sequence of observed changes—not all symptoms respond to stimulation simultaneously. For example, during stimulation of the subthalamic nucleus in Parkinson’s disease, first (in seconds) the tremor subsides, followed by rigidity (seconds–minutes), bradykinesia (minutes–hours), and axial symptoms (hours–days). These symptoms appear after the stimulation is turned off in the same order [64,65]. Previous research in TD patients has focused on the stimulation of two areas in the brain: the inner globus pallidus (GPi) and the subthalamic nucleus (STN) belonging to the basal ganglia. These nuclei belong to motor circuits, including cortico-thalamic-basal ganglia junctions, which are believed to be the morphological substrate of TD. Most projects focused on the stimulation of the GPi, the preferred target, while less is known about STN stimulation [4,6]. Nevertheless, both STN and GPi stimulation were shown to be beneficial in reducing TD [38]. The primary target of GPi DBS is the posteroventrolateral part [46,47,66,67,68,69]. Several descriptions concern the stimulation of the posteroventromedial area [70,71]. Ventral parts of the posterior globus pallidus have a somatotopic organization associated with the motor cortex, which determines the goals of stimulation; the median part is related to the limbic cortex, while the dorsal area is associated with the prefrontal cortex [72]. Stereotactic techniques based on MRI (magnetic resonance imaging) or CT-MRI (a combination of CT and MRI techniques) help correct electrode placement [73]. The optimal electrode placement is typically within 19–22 mm lateral to the line between the anterior and posterior commissure, 4–6 mm inferior to that line, and 2–4 mm anterior to the mid-commissural point [45,46,67,71,74,75,76,77,78,79]. In one description, the electrode position corresponded to the somatotopic face area [80]. The most common practice uses microelectrode recordings (MERs) to detect discharges of neurons in the GPi and to order “noisy signals” with DBS. The most common stimulation parameters used were the voltage (amplitude) of the current (1.0–7.0 V) [43,67], frequency (60–185 Hz) [42,69,78,81], and pulse width (60–450 µs) [42,45,78,81,82,83]. A detailed list of electrodes used, voltages, location, and effectiveness of the treatments can be found in the study by Morigaki et al. [84]. With several exceptions of bipolar modes [42,43,44,45,46], other reports concern monopolar stimulations. Much of the literature was single-patient reports [43,47,68,70,73,74,75,77,78,80,82,85,86,87,88,89], small groups of 2–4 people [46,48,67,69,71,79,90,91], or slightly larger groups [42,45,76,81,83,92,93,94,95], and 19 patients comprised the largest cohort [38] (Table 3). The reported efficacy (reduction in dystonia scores) ranges from 28% to 100%, with most reports showing ≧60% improvement, with a follow-up period of up to 11 years [38]. Improvement is described as stable even after 4-year follow up. In addition to improvement in symptoms, most investigators consistently report a significantly favorable change in the quality of life and daily functioning. Nevertheless, there are also descriptions of no overall change in this area [45,96]. Clinical responses appear either during the surgical procedure and the first activation of stimulation or in the first days after turning on the equipment [45,46,67,68,70,76,86,91]. If clinical responses are observed shortly after switching on the device, we can precisely program the equipment at the outset; in other cases, patient adjustments are carried out at follow-up visits or via the Internet, more recently [97]. The manufacturer recommends the lowest sufficient stimulator settings, combining optimal performance with less load and then longer battery life or less frequent recharging. Changes in the treatment of choreiform dyskinesia are noted earlier, tonic postural dystonia responds later, symptoms improve gradually, and changes are observed after weeks or even months of stimulation [44,46,75,86,91,92,93]. In fixed dystonias, the efficacy of GPi DBS is lower [42,45,67,81]. Despite its invasiveness, DBS is characterized by a low number of complications and is considered a safe, effective, and well-tolerated method [4]. The frequency of all side effects reaches 9%. Observations of nonmotor effects are very rare. DBS may induce transient affective states (mild to moderate depressive syndrome in most cases); the authors also emphasized some increase in suicidal risk [73,98]. However, at longer follow up, there was an improvement in mood, which could also be explained by relief from the burden of motor symptoms, disability, or social impact [38,45,76,80,99]. In one study, six months after treatment, one patient had a brief psychotic episode, and another patient had symptomatic improvement allowing the discontinuation of antipsychotic drugs [76]. Contrary to the first reports, the negative influence of continuous pallidal (GPi) DBS on cognitive functions has not been confirmed [38,45,71], while one study notes improvement [99]. The procedure of implanting the electrode (in both locations, GPi and STN) is associated with the possibility of incorrect placement or electrode displacement, infections, pain associated with the connection cable, intracranial hemorrhage, and seizure. Gait and balance disturbances contributing to falls have also been observed. These disturbances were transient and resolved after the optimization of DBS parameters [38]. The GPi is involved in speech fluency; thus, slowing, halting, and imprecise oral articulation and reduced voicing control are common symptoms during DBS in this area. Bilateral DBS induces more speech difficulties [100]. Dysarthria occurs in almost 30% of patients; severe cases may require speech therapy [38]. Despite the complications being infrequent, the risk–benefit ratio always needs to be weighed. DBS becomes the last resort in patients with severe TD when symptoms are severe, functioning is significantly impaired, and other treatment options are insufficient. Table 4 shows the most common side effects, along with the structures whose stimulation is responsible for their appearance. The subthalamic nucleus (STN), belonging to the basal ganglia, was the first neurosurgical target in the treatment of dystonia (thalamotomy), but data about STN DBS in treating TD are still scarce. Less frequent use is, among others, related to psychiatric complications (depression, suicidality, mania, and impulse-control problems) observed during DBS of this brain structure in patients with Parkinson’s disease. The best control of motor symptoms is provided by stimulation of the sensorimotor (dorsolateral) area of the STN [101]. So far, only a limited number of cases of STN DBS for TD have been reported. In addition to the Deng study, which we will discuss later [6], Zhang et al. published a description of a series of nine patients treated with STN DBS for secondary dystonia (two with tardive dystonia) [102]. In one case, the dystonia following neuroleptic treatment improved by 92% in the BFMDRS 3 months after stimulator implementation. Long-term observation of one of those patients with severe TD dystonic symptoms initially is described by Meng et al.; the patient had no neurological symptoms after 144 months (6 and 12 years after the operation BFMDRS total score was 0) [4]. Another study (12 patients with primary dystonia and 2 with TD) using STN DBS showed improvement ranging from 76 to 100% in the BFMDRS [103]. One patient underwent DBS electrode placement in the left and right STN with a near-complete resolution of tremors [104] (data summarized in Table 5). The anatomical location of the STN is very close to several functionally significant areas. Therefore, the induced side effects are also associated with stimulating adjacent nuclei and nerve tracts. Table 6 presents the most common side effects with the postulated structures responsible for their appearance. Due to the lack of detailed descriptions regarding TD, the table lists observations during STN DBS in Parkinson’s disease. Authors suggest better results for STN DBS using lower stimulation parameters than in GPi DBS, but no studies compared the effects of DBS in the two areas. In the following section, we will compare the results of two studies of the GPi and STN involving the largest groups of TD patients. The largest study evaluating the efficacy of GPi DBS is by Pouclet-Courtemanche et al. It originally included 19 patients, while 18 reached a 6-month follow up, 14 participants were assessed at long-term follow up (6–11 years) [38]. Meanwhile, Deng et al. analyzed STN DBS results in a group of 10 patients, with all included evaluations at 6 months and long-term follow up (12–105 months) [6]. The aforementioned time points were common for both studies among other follow-up lengths. Furthermore, the mutual form of assessment of motor symptoms was only the AIMS. We compared the effectiveness of DBS at the different sites using a two-sample z-test for proportions. In the case of the study by Pouclet-Courtemanche et al., no median/mean data for the AIMS score were available at all time points. Regardless, the calculation of proportions was possible based on the graph analysis presenting a change in the AIMS score at the different follow ups. For the 6-month follow-up time point, the proposition was 0.49 (n = 18) and 0.15 (n = 10) for the GPi DBS and the STN DBS, respectively. In the comparison, the difference did not reach statistical significance with p = 0.079, mostly due to the small sample sizes in both studies, as the trend is visible (Figure 1). We did perform a statistical analysis of a long-term follow up due to a disparity in the observation period, which could affect the result. Deep brain stimulation (DBS) is an established treatment for patients with tardive dyskinesia when pharmacological therapy alone does not provide sufficient relief or is associated with disabling side effects. With this method, patients achieve satisfactory results in both the short and long term, with a relatively small number of complications. As we previously mentioned, the main sites with proven efficacy of stimulation are the subthalamic nucleus (STN) and internal globus pallidus (GPi). Although the GPi remains the standard stimulation target, our comparison in small groups shows at least comparable efficacy of STN and GPi DBS, including 6-month follow up. Similar conclusions come from comparisons of the two methods in PD [105]. However, further research is needed to confirm this conclusion, also because the trend may indicate an advantage for STN DBS. DBS studies in PD allow some conclusions that may also apply to the treatment of TD with this method. The advantage of GPi stimulation lies in the possibility of effective use of the electrode unilaterally and somewhat easier optimization of current parameter programming. On the other hand, some researchers report that STN DBS may be less likely to cause adverse symptoms in mood, cognitive function, gait, and speech [106]. The GPi is occasionally indicated as the preferred target in treating oral TD and dystonia, while STN DBS could be considered an effective and safe procedure in patients with predominant tardive Parkinsonism and/or tardive tremor [104]. In contrast, studies by Sun et al. indicate some advantages of STN DBS stimulation in dystonias, including TD. According to these authors, symptomatic improvement begins immediately after stimulation, which allows for a quick selection of the best stimulation parameters. The stimulation parameters used for the GPi are higher than those used during STN DBS, resulting in longer battery life for STN DBS (longer intervals between charges). According to the authors, STN DBS results in better symptomatic control than GPi DBS in dystonia patients (compared to data obtained by other teams) [103]. To broaden knowledge and outline plans for necessary research, it is worth looking at solutions employed in DBS procedures in patients with other health problems. DBS is a method that has been implemented for years in various conditions such as dystonia, Parkinson’s disease, and obsessive–compulsive disorder. This method is also recommended for patients with severe and treatment-resistant forms of the disease. It is noteworthy that the STN is the standard site of stimulation in PD [107]. According to the symptomatic profile of PD, preferences include alternative targets, e.g., the thalamic ventral intermediate nucleus (VIM) or the GPi. Recent research in this area has focused on the search for other sites of stimulation such as the posterior subthalamic area (PSA) or the caudal zona incerta (cZi). The PSA is located ventrally to the VIM, between the red nucleus and the STN. PSA DBS is not significantly different from VIM DBS in suppressing tremor, but clinical benefit from PSA DBS is attained at lower stimulation amplitudes [108]. Furthermore, several open-label studies have shown a good effect in the reduction of PD symptoms with DBS in the caudal zona incerta (cZi) [109]. While both TD and PD treatment have the same standard stimulation sites, it is worth investigating other experimental stimulation sites in TD treatment, such as the PSA or the cZi, or finding new targets. Treatment of refractory TD with DBS is not a low-cost method, requiring an experienced neurosurgical team and precise instrumentation. It is also not a life-saving method, but, if we want to have a full range of possible medical procedures that may expand our understanding of the brain (we consider it crucial), this research must be continued and intensified. The latest technical achievements in the field of construction of stimulators and electrodes, e.g., modeling the shape of the impact field, as well as the results of new studies focused on the paths connecting the gray matter of various brain regions allow us to expect discoveries in research using DBS, hopefully also in TD.

PMC10003253

Khadiga M. Sadek,Sara El Moshy,Israa Ahmed Radwan,Dina Rady,Marwa M. S. Abbass,Aiah A. El-Rashidy,Christof E. Dörfer,Karim M. Fawzy El-Sayed

Molecular Basis beyond Interrelated Bone Resorption/Regeneration in Periodontal Diseases: A Concise Review

27-02-2023

inflammation,osteocytes,mesenchymal stem cell,bone regeneration,bone resorption

Periodontitis is the sixth most common chronic inflammatory disease, destroying the tissues supporting the teeth. There are three distinct stages in periodontitis: infection, inflammation, and tissue destruction, where each stage has its own characteristics and hence its line of treatment. Illuminating the underlying mechanisms of alveolar bone loss is vital in the treatment of periodontitis to allow for subsequent reconstruction of the periodontium. Bone cells, including osteoclasts, osteoblasts, and bone marrow stromal cells, classically were thought to control bone destruction in periodontitis. Lately, osteocytes were found to assist in inflammation-related bone remodeling besides being able to initiate physiological bone remodeling. Furthermore, mesenchymal stem cells (MSCs) either transplanted or homed exhibit highly immunosuppressive properties, such as preventing monocytes/hematopoietic precursor differentiation and downregulating excessive release of inflammatory cytokines. In the early stages of bone regeneration, an acute inflammatory response is critical for the recruitment of MSCs, controlling their migration, and their differentiation. Later during bone remodeling, the interaction and balance between proinflammatory and anti-inflammatory cytokines could regulate MSC properties, resulting in either bone formation or bone resorption. This narrative review elaborates on the important interactions between inflammatory stimuli during periodontal diseases, bone cells, MSCs, and subsequent bone regeneration or bone resorption. Understanding these concepts will open up new possibilities for promoting bone regeneration and hindering bone loss caused by periodontal diseases.

Molecular Basis beyond Interrelated Bone Resorption/Regeneration in Periodontal Diseases: A Concise Review Periodontitis is the sixth most common chronic inflammatory disease, destroying the tissues supporting the teeth. There are three distinct stages in periodontitis: infection, inflammation, and tissue destruction, where each stage has its own characteristics and hence its line of treatment. Illuminating the underlying mechanisms of alveolar bone loss is vital in the treatment of periodontitis to allow for subsequent reconstruction of the periodontium. Bone cells, including osteoclasts, osteoblasts, and bone marrow stromal cells, classically were thought to control bone destruction in periodontitis. Lately, osteocytes were found to assist in inflammation-related bone remodeling besides being able to initiate physiological bone remodeling. Furthermore, mesenchymal stem cells (MSCs) either transplanted or homed exhibit highly immunosuppressive properties, such as preventing monocytes/hematopoietic precursor differentiation and downregulating excessive release of inflammatory cytokines. In the early stages of bone regeneration, an acute inflammatory response is critical for the recruitment of MSCs, controlling their migration, and their differentiation. Later during bone remodeling, the interaction and balance between proinflammatory and anti-inflammatory cytokines could regulate MSC properties, resulting in either bone formation or bone resorption. This narrative review elaborates on the important interactions between inflammatory stimuli during periodontal diseases, bone cells, MSCs, and subsequent bone regeneration or bone resorption. Understanding these concepts will open up new possibilities for promoting bone regeneration and hindering bone loss caused by periodontal diseases. Periodontium is considered the mirror that reflects many of the human body’s internal status and secrets [1]. Periodontal diseases are chronic infectious conditions causing irreversible damage to the periodontium and its surrounding bone. Worldwide, severe periodontitis is considered among the most prevalent chronic inflammatory conditions affecting the periodontal apparatus [2]. Many factors are involved in the pathogenesis of periodontal diseases where the primary etiological factor is the microbial biofilm. Other etiological factors include some environmental factors, such as smoking and certain systemic diseases such as diabetes mellitus in addition to genetic risk factors affecting the inflammatory and immunologic response of the host [3]. The relationship or balance between the local microbiota and the host’s immune reaction plays a major role in the development and progression of periodontitis [4]. Periodontitis is principally initiated and sustained via dental plaque and the oral microbial biofilm in addition to dysbiosis occurring in the periodontium, causing an extensive release of cytokines, chemokines, and some matrix-degrading enzymes originating from the gingival tissues, the infiltrating immune cells, and the fibroblasts. The net effects of such destructive mediators lead to tissue breakdown, loss of periodontal attachment, and subsequently complete tooth loss [5]. The acute innate immune response during periodontal inflammation depends on a variety of immune cells, such as natural killer cells, neutrophils, and macrophages, besides other variable cytokines. Neutrophils represent the first wave of immune cells within 24 h after the microbial attack. Monocyte–macrophages lineage cells represent the second wave of inflammatory cells peaking at 48–96 h [6]. In an attempt to damage the proteins present in the membranes of some bacteria, neutrophils release elastase; however, this results in the breakdown of type I–IV collagen and the elastin of the periodontal ligaments. Elastase is also able to degrade the extracellular matrix (ECM) by accelerating matrix metalloproteinases (MMPs) cascades, all of which result in attachment loss and pocket formation [7]. The breakdown of the tissues is further exacerbated by neutrophils through the release of MMPs and reactive oxygen species (ROS) [8]. In addition, activated neutrophils increase the expression of receptor activator of nuclear factor kappa-B ligand (RANKL), resulting in a stimulation of osteoclastogenesis and subsequently bone resorption [8,9]. Activated neutrophils release chemokines mediating chemotactic recruitment of T helper (TH)-1 and TH17 cells. TH17 augments the recruitment, the activation, and hence the survival of neutrophils through the release of cell-derived cytokines, for instance, interleukin (IL)-17, interferon-γ (IFNγ), CXC-chemokine ligand 8 (CXCL8; also known as IL-8), granulocyte–macrophage colony-stimulating factor (GM-CSF), and tumor necrosis factor (TNF). Activated neutrophils also secret cytokines capable of mediating the survival, differentiation, and maturation of B cells [8]. Activated B and T cells are also a source of RANKL, resulting in the resorption of bone present in the area of diseased gingival tissues. Additionally, when B cells are activated, this results in the proliferation, differentiation, and maturation of plasma cells. Plasma cells can produce some cytokines such as TNF-α, transforming growth factor-β (TGF-β), IL-6, and IL-10. TNF-α induces the expression of MMPs, thus promoting MMPs-mediated periodontal tissue destruction [10]. Once, the monocyte–macrophage system is activated by the periodontal bacteria and their products, production of huge proinflammatory cytokines occurs [11]. Two distinct phenotypes of macrophages exist: the proinflammatory (M1) macrophages and the anti-inflammatory (M2), arising from the polarization [6]. The M1 and M2 transition is a significant mechanism for the transition between the active periodontitis and the inactive type. Macrophage polarization into M1 is triggered by various stimuli, including microbial stimuli such as IFN-γ and lipopolysaccharide (LPS). M1 produces various proinflammatory factors and represents the primary sources of IL-6, IL-1β, TNF-α, prostaglandin E2 (PGE2), MMP-1, and MMP-2, resulting in the degradation and destruction of the periodontal connective tissues followed by bone resorption [11]. Figure 1 summarizes the role of inflammatory cells in periodontal tissue destruction. Thus, the relationship between immune surveillance, which is the processes permitting the cells of the immune system to look for and to identify foreign pathogens, and the oral microbe-induced host immune response dictates the progress of the periodontal disease. If a mild host immune response and a local stimulation are balanced, there will be immunological surveillance with a proper immune response. Though, if the pathogenicity of the local microbiota increases due to the colonization of keystone pathogens that overactivate the host immune response, the initiation of tissue destruction arises. Yet, the detailed pathogenesis and immune response to periodontitis remain uncertain and still have many controversies [12]. Bone tissue depends on the activity of three main types of cells: osteoblasts, osteocytes, and osteoclasts. Osteocytes make up about 95% of the total cell population [13]. The osteoblast is considered the anabolic part of the previously mentioned cell triad. Osteoblasts deposit osteoid tissue, which is a newly synthesized ECM, consisting of collagen type 1, water, and proteoglycans. This osteoid is then mineralized with hydroxyapatite crystals to obtain the normally required stability [14]. Osteoblasts are derived from skeletal stem cells (SSC), which is a subpopulation of mesenchymal stem cells (MSCs), found in the bone marrow. SSCs can give rise to different cell types, namely, chondrocytes, adipocytes, and osteoblasts [15]. Osteoclasts are large (50–100 nm) multinucleated cells originating from hematopoietic stem cells rather than MSCs [16]. They are resorptive cells, having a ruffled border on the bone matrix-facing side to increase the surface area. This ruffled membrane contains a high number of H+-ATPases in order to lower the localized pH to 4.5, which is needed to dissolve the chemical bonds of calcium in the bone matrix. Osteoclasts attach to the osseous tissue by integrins to ensure a tight seal around the area of low pH. To break down proteins, mainly collagen type I, osteoclasts primarily secrete Cathepsin K and MMPs. This is followed by endocytosis of organic and inorganic fragments [17,18]. Osteocytes are the mature phenotype of osteoblasts. Osteocytes get trapped in the synthesized matrix, locating themselves in the lacuno-canalicular system which is filled with bone fluids. Osteocytes possess 50–60 cellular processes radiating from the cell body and extending through canaliculi, all buried in the mineralized bone matrix [19]. Although osteocytes do not undergo mitotic division, have a slow metabolism, and are anchored to their surroundings, they have a great impact on bone metabolism. They form contact points with each other, osteoblasts, and osteoclasts, spanning a network over the entire bone. This way osteocytes are able to conduct bone turnover [16] (Table 1). Due to their specific properties, including stemness, proliferation, migration, multilineage differentiation, and immunomodulation, stem cells have been considered a viable strategy to treat tissue damage caused by inflammation [20,21,22,23,24]. In periodontitis, stem cells can be transplanted or recruited to the infection site, acting as key regulators for the inflammatory and immune responses, accelerating the regeneration process [25,26]. Infected tissue-derived stem cells have normal stem cell properties, including reduced immunogenicity and immunosuppression [21]. Dental mesenchymal stem cells (DMSCs), nondental stem cells, and induced pluripotent stem cells are all possible stem cell candidates for periodontal regeneration. In this review, we will focus on DMSCs, specifically those associated with the periodontal tissues, periodontal ligament stem cells (PDLSCs), gingival mesenchymal stem cells (GMSCs), stem cells from the apical papilla (SCAP), and dental pulp stem cells (DPSCs) [25]. The interaction of stem cells and immune cells in the inflammatory milieu may be radically different from that in a healthy state. Maintenance of stemness, colony formation, greater proliferation rate, multilineage differentiation capacity, decreased immunogenicity, and immunosuppression are all features of inflamed stem cells [20]. PDLSCs harvested from inflamed periodontal ligaments (iPDLSCs) constitute a convenient source for stem cells for periodontal regeneration. iPDLSCs are characterized by their enhanced proliferation and migration potential; however, they showed reduced osteogenic potential [27,28] and reduced immunosuppressive properties [29]. They were shown to express high levels of IFN-γ, TNF-α, IL-2, and indoleamine 2,3-dioxygenase (IDO) and low expression of IL-10 [30]. iPDLSCs implanted on collagen sponges successfully formed periodontal-like tissues upon implantation in rats, demonstrating their potential in periodontal regeneration [31]. Similarly, stem cells isolated from inflamed dental pulp (iDPSCs) showed a regenerative potential for periodontal tissues. Additionally, the iDPSCs retained surface marker expression, proliferation, and multilineage differentiation potential as compared to those isolated from healthy pulp [32,33]. iDPSCs impregnated on β-tricalcium phosphate stimulated the formation of alveolar bone in root furcation defects [34]. Periodontal-affected DPSCs and GMSCs showed a high proliferation rate, higher osteogenic potential, and higher calcification deposits than the healthy group. Additionally, proinflammatory cytokines caused cytoskeleton remodeling, which is thought to drive enhanced acquisition in the inflammatory environment, proving their potential in periodontal regeneration [35]. The effect of TNF-α on the osteogenic potential of inflamed SCAPs was assessed in mice’s athymic nude [36]. TNF-α demonstrated a potent inhibitory effect of the bone morphogenic protein (BMP)-9-mediated osteogenic potential of inflammable SCAPs, as well as suppressing ALP, OPN, and OC activities. These inhibitory effects were partially counteracted by high levels of BMP-9, highlighting the potential therapeutic effect of BMP-9 in bone regeneration resulting from chronic inflammation conditions [36]. TNF-α, IL-1, IL-6, and IFN-γ, the most efficient proinflammatory cytokines during periodontitis, were reported to exert critical effects on the immunomodulatory abilities of stem cells and their subsequent role in bone remodeling [37,38,39]. IL-1 has a contradictory effect on osteogenesis and bone formation. MSC development into osteoblasts and subsequent mineralization has been reported to be aided by IL-1, primarily through the noncanonical Wnt-5a/Ror2 pathway [40]. At doses ranging from physiologically healthy to those found in chronic periodontitis, IL-1β plays a dual role in the osteogenesis of PDLSCs. Low doses of IL-1β enhance osteogenesis of PDLSCs by activating the BMP/Smad signaling pathway; however, higher doses of IL-1β decrease osteogenesis by activating the NF-κB and mitogen-activated protein kinases (MAPK) signaling pathways, meanwhile, suppressing BMP/signaling. PDLSCs with poor osteogenesis release more inflammatory cytokines and chemokines, driving macrophage chemotaxis and highlighting the function of PDLSCs in the etiology of periodontitis [41]. By upregulating the Wnt signaling pathway antagonists DKK1 and sclerostin, IL-1 can effectively suppress osteoblastogenesis [42]. In a highly inflammatory environment, IL-1 levels have also been linked to osteoclastic bone loss [43]. To imitate in vivo periodontitis-inflammatory milieu, GMSCs isolated from free gingival tissues of Sprague–Dawley rats were treated with Porphyromonas gingivalis lipopolysaccharides (P. gingivalis-LPS) (10 μg/mL). To counteract the deleterious effects of LPS, different doses of IL-1 receptor antagonist (IL-1ra) (0.01–1 μg/mL) were utilized. Cell counts, clone formation rate, cell migration rate, proinflammatory cytokine production, osteogenic differentiation-associated protein/mRNA expressions, and mineralized nodules were found to be inhibited in a time-dependent manner in response to P. gingivalis-LPS therapy, a condition that was significantly reversed by dose and time-dependent IL-1ra treatment. TLR4 and IkBα (cellular protein that inhibits the NF-κB) mRNA expressions were also significantly reduced when IL-1ra was added to the LPS-induced media. TLR4/NF-κB activation was similarly reversed by IL-1ra, as evidenced by western blot [44]. IL-6 plays a role in the modulation of osteoblastogenesis. DPSCs isolated from healthy pulp and further treated with IL-6 showed significantly increased osteogenic differentiation and increased expression of osteoblasts markers OC and runt-related transcription factor 2 (RUNX2) [45]. IL-6 and its soluble receptor (sIL-6R) potentiated ascorbic acid-mediated osteoblastic differentiation of periodontal ligament cells with upregulation of RUNX2 and ALP activity through insulin-like growth factor production in periodontal ligament cells [46]. IL-6 and sIL-6R also significantly increased osteogenic differentiation and ALP activity of MSCs [47]. Levels of IL-6 and IL-6R significantly increased during bone marrow MSC osteogenic differentiation with a positive correlation to osteogenic differentiation of stem cells. IL-6/IL-6R interaction can induce osteoblastic differentiation of bone marrow MSCs via activation of the signal transducer and activator of the transcription (STAT3) pathway [48]. Conditioned medium of osteocytes treated with IL-6 stimulated upregulation of osteoblastic late marker OC in osteoblasts cell culture [49]. Other reports demonstrated a negative effect of IL-6 on osteoblasts differentiation. IL-6 was associated with downregulation in osteoblasts-related genes, including RUNX2, osterix (OSX), and OC in vitro through activation of Src homology 2 (SHP2)/MAPK kinase/extracellular signal-regulated kinase (ERK), Janus kinase (JAK)/STAT3, and SHP2/phosphoinositide 3-kinase (PI3K)/Akt2 signaling pathways [50]. IL-6 also inhibited osteoblast-calcified nodule formation and ALP activity [51]. Overexpression of IL-6 in mice significantly reduced osteoblastogenesis and increased osteoclastogenesis [52]. Evidence suggests that IL-6 might have a dual role in osteoblasts modulation. Infection-stimulated bone resorption can be suppressed in vivo by IL-10. IL-10-deficient mice exhibited osteopenia, reduced bone formation, and mechanical fragility of the long bones [53,54]. In addition, IL-10 has been shown to enhance bone formation and speed up the healing of bone fractures. IL-10 (10 or 20 nM) increased the metabolic switch from glycolysis to oxidative phosphorylation in DPSCs, whereas IL-10 (5 and 50 nM) had no effect on osteogenic differentiation. The oxidative phosphorylation inhibitor impeded the IL-10-induced enhancement of osteogenic differentiation. These findings reveal that IL-10 can boost DPSC osteogenesis by activating oxidative phosphorylation [55]. IL-17 also has a dual role in osteoblasts regulation. While some evidence suggests that IL-17 upregulates osteoblastogenesis and can protect the alveolar bone against periodontitis-mediated bone resorption, others suggest that IL-17 is associated with the downregulation of osteoblastogenesis and may therefore contribute to periodontitis-associated alveolar bone resorption. Interaction of IL-17 with its receptor upregulated osteogenic differentiation of MSCs. Coculturing with osteocytes demonstrated a synergistic effect [56]. It also upregulated expression of ALP, OC, RUNX2, and RANKL expression, meanwhile, reducing mineralization in vitro, indicating that it can exert its influence during the early stages of osteoblastofiggenesis [57]. Other reports demonstrated a positive effect of IL-17 on both early and late osteoblastic differentiation [58,59]. IL-17 was also associated with increased osteoblasts differentiation, mineralization, and proliferation in addition to osteoblast-mediated osteoclastogenesis in vitro and lamellar bone formation in rats with clavarial defects [60]. On the other hand, IL-17 inhibited BMP-2-induced osteoblastogenesis and was associated with reduced expression of ALP, OC, RUNX2, and OSX expression in vitro [61,62]. Treatment of PDLSCs with IL-17 significantly downregulated their osteogenic potential through activation of ERK1,2 and c-Jun N-terminal kinase (JNK) MAPK, implying their role in periodontal-associated bone destruction [63] and inhibited bone formation in rats [62]. However, TNF-α is well-known to inhibit bone formation; its dual function has been proven. TNF-α can either suppress or promote osteogenesis depending on its dose, cell type, and exposure time [6]. TNF-α can favor osteogenic differentiation via NF-κB through increasing expression of BMP-2, OSX, RUNX2, OC, and Wnt signaling pathways [64]. It has been authorized that (10 ng/mL) TNF-α treatment for 0, 3, 5, 15, 30, 60, and 120 min activated the NF-kB pathway during the osteogenic differentiation of DPSCs. Furthermore, TNF-α increased mineralization and expression of BMP-2, ALP, RUNX2, and COL I. It was reported that Pyrrolidine dithiocarbamate, an NF-kB inhibitor, blocked the osteogenic differentiation induced by TNF-α [65]. In the early stages of bone repair, a TNF-α-mediated inflammatory stimulus is mandatory for recruiting osteoblast progenitor cells. This has been confirmed in TNF receptor-deficient mice where only granulation tissue appeared in the marrow cavity on day three after model establishment, while in wild-type mice, young osteoblasts appeared in the marrow space in the same time interval. Moreover, downregulation of type I collagen and osteoclast mRNA expressions has been reported in TNF receptor-deficient mice to 50% as compared to wild-type mice. Endochondral bone formation was downregulated in TNF receptor-deficient mice; however, osteogenesis was not inhibited. On the contrary, intramembranous bone formation was completely absent [66]. TNF-α and its receptors are expressed in a biphasic fashion during bone repair. In mouse models, TNF-α concentration peaks 24 h after bone fracture and returns to baseline within 72 h. TNF-α is mostly expressed by macrophages and other inflammatory cells at this time [67,68]. This short TNF-α signaling is thought to trigger the release of secondary signaling molecules and has a chemotactic impact, attracting bone-regeneration cells. Approximately 2 weeks later, during endochondral bone formation, TNF-α levels rise again. TNF-α is produced by osteoblasts and other mesenchymal cells during this time, including hypertrophic chondrocytes undergoing endochondral bone formation [67,69,70]. TNF-α enhanced osteogenic differentiation and matrix mineralization in MSCs in vitro in a dose-dependent manner [66,71]. Additionally, RUNX2 and OSX levels were downregulated in cell cultures treated with TNF-α at high dosages [72]. It has been reported that the proliferation of human PDLSCs was significantly upregulated following treatment with 10 ng/mL TNF-α; however, ALP enzyme activity and alizarin red mineralization nodule size were significantly reduced following TNF-α treatment for 7 or 21 days. Moreover, the gene and protein expression levels of osteogenic differentiation markers, including RUNX2, OC, and COL-1, were significantly downregulated [73]. These results are contrary to Feng et al. who reported no effect of TNF-α treatment up to 2 h on the proliferation of DPSCs or the cell cycle [65]. Long-term treatment with TNF-α induced inhibitory effects on the in vitro mineral nodule formation of MSCs [72]. TNF-α also stimulates MSC proliferation and immunosuppression via the NF-κB pathway [74], while its inhibitory effect on osteoblast development is mediated by increased production of DKK-1 and Wnt signaling pathway antagonists [75]. Additionally, the infected microenvironment has been reported to affect DMSCs. P. gingivalis-LPS, for example, greatly increased the cellular proliferation of DMSCs [76]. Furthermore, coculturing PDLSCs with IL-1β/TNF-α may boost their proliferation rate [77]. On the contrary, P. gingivalis-LPS and Escherichia coli-LPS, in particular, impede PDLSC osteoblastic differentiation [76,78]. In the absence of BMP-2, an osteogenic supplement, TNF-α and LPS had no effect on the expression of osteogenic markers by human bone marrow MSCs. TNF-α and LPS, on the other hand, increased ALP activity and subsequent matrix mineralization in osteogenic differentiation media or in combination with BMP-2. Both mediators greatly boosted matrix mineralization in preosteoblasts regardless of culture conditions. As a result, it was concluded that both inflammatory factors significantly boost MSCs’ osteogenic potential as well as MSCs that have committed to the osteogenic lineage [79]. Furthermore, preconditioning murine MSCs for 3 days with TNF-α and LPS and then coculturing with macrophages increased anti-inflammatory M2 macrophage marker expression (Arginase 1 and CD206) while decreasing inflammatory M1 macrophage marker expression (TNF-/IL-1ra). MSC immunomodulation of macrophages was dramatically boosted when compared to single treatment controls or a combination of IFN and TNF-α. The only MSCs that displayed enhanced osteogenic differentiation, including ALP activity and matrix mineralization, were those that were preconditioned with LPS and TNF [80]. No change in the surface markers has been reported for the PDLSCs and GMSCs within the IL-1β and TNF-α-inflamed microenvironment; however, when the IL-1β and TNF-α stimulation exceeds a specific level, their favorable effect on cell proliferation and recruitment may be weakened or possibly lead to stem cell death [25,81]. Despite this, transient and low levels of proinflammatory cytokines and microbial pathogens may be involved in the differentiation potential of DMSCs [81]. In the local periodontal environment, IL-1β and TNF-α are responsible for suppressing PDLSC osteogenesis by boosting the canonical Wnt/-catenin pathway and blocking the noncanonical Wnt/Ca2+ pathway [28]. MSCs’ proliferation and immunomodulatory functions have been found to be stimulated by IFN-γ [82]. Low doses of IFN-γ enhance stem cells’ antigen-presenting activities, minimizing their lysis. High doses, reciprocally, would have the opposite impact [83,84]. For bone marrow MSCs to exert their immunosuppressive effect on T lymphocyte proliferation, IFN-γ has been authorized to be implicated. In addition, both LPS and IFN-γ may cause bone marrow MSCs to secrete functional indoleamine 2,3-dioxygenase and IL-10 [85]. Furthermore, IFN-γ is required for MSC commitment to the osteoblastic lineage, which potentiates bone regeneration both in vitro and in vivo [40,86]. Mice with a knockout IFN-γ receptor exhibited a reduction in bone volume with a low-bone-turnover pattern, a decrease in bone formation, a significant reduction in osteoblast and osteoclast numbers, and a reduction in circulating levels of bone formation and bone resorption markers. These data support an important physiologic role for IFN-γ signaling as a potential therapeutic target for bone loss [87]. Other literature has reported that IFN-γ suppresses allogeneic MSC-induced osteogenesis [88]. Through T cell activation, IFN-γ also has a stimulatory effect on osteoclastogenesis and bone loss [89]. TGF-β is a well-known anti-inflammatory cytokine that can help MSCs proliferate and differentiate [69]. Signaling between TGF-β and BMP is involved in the vast majority of cellular functions and is crucial throughout life. TGF-β/BMP signaling is mediated by both canonical Smad-dependent and noncanonical Smad-independent pathways (e.g., p38 and MAPK). Both the Smad and p38 MAPK pathways converge on the RUNX2 gene following TGF-β/BMP activation to govern mesenchymal precursor cell development [90]. TGF-β activated receptors form a complex with Smad4, which translocates from the membrane into the nucleus to interact with RUNX2, resulting in numerous osteogenic genes being activated [91]. High dosages of TGF-β1, on the other hand, hindered bone marrow MSC osteogenesis and slowed bone healing in vivo. The effects of different TGF-β1 levels on osteogenic differentiation and bone repair were inversely proportional. Low TGF-β1 dosages activated Smad3, increased their binding to the promoter of BMP-2, and enhanced BMP-2 production in bone marrow MSCs. At high TGF-β1 levels, BMP-2 production was suppressed by modifying Smad3 binding sites on its promoter. Furthermore, high TGF-β1 doses elevated tomoregulin-1 levels in mice, causing BMP-2 suppression as well as hindering bone formation [92]. The latter study clarifies the conflicting results of the negative relationship between TGF and osteoblastogenesis [58]. Other cytokines might have an effect on MSCs during in vitro and in vivo bone regeneration and remodeling. IL-22, for example, stimulates MSCs’ osteogenic activity [93]. By stimulating the canonical Wnt-catenin pathway, IL-23 has been shown to induce osteogenic differentiation of MSCs [94]. Furthermore, new evidence suggests that the anti-inflammatory cytokine IL-27 can enhance bone production by inhibiting osteoblast death and suppressing osteoclastogenesis [95]. Osteoclasts are hematopoietic in origin; they arise through the fusion of multiple monocytes [96,97]. The process of osteoclastogenesis begins with common myeloid progenitor cells, which arise from hematopoietic stem cells within the bone marrow under the influence of factors, including stem cell factors, IL-3, and IL-6. Common myeloid progenitors are stimulated to give rise to granulocyte/macrophage progenitors under the influence of GM-CSF. Granulocyte/macrophage progenitors further differentiate into the monocyte–macrophage lineage, the precursor of osteoclasts, following stimulation by macrophage-CSF (M-CSF) [98,99]. M-CSF is essential for osteoclasts proliferation and survival [100]. The binding of M-CSF to its receptor CSF-1 receptor (c-Fms) activates intracellular PI3K and growth factor receptor bound protein 2 (Grb 2), which in turn activates Akt and ERK signaling in osteoclasts precursor [101]. Within the bone environment, M-CSF arises primarily from osteoblast cells in addition to bone marrow stromal cells [102]. Further differentiation of osteoclasts precursor is mediated by osteoblasts and bone marrow stromal cells through RANK and its ligand (RANKL) through OPG, RANKL, and RANK axis. OPG, RANKL, and RANK are both TNF/receptor superfamily members [103]. RANKL exerts its function through binding to RANK on osteoclast progenitors’ surfaces, resulting in a signaling cascade that eventually promotes differentiation and fusion of osteoclast precursors. It can also promote mature osteoclasts’ survival and activity [100,103]. RANKL is a key player in periodontitis-associated bone resorption. It is expressed by osteoblasts and bone marrow stromal cells [100]; it is also expressed by gingival epithelial cells and fibroblasts [104,105] and periodontal ligament cells [106]. Activated T and B cells can express RANKL in periodontal-diseased gingival tissue which potentiates bone resorption [107,108]. Additionally, cementoblasts have also been shown to express RANKL and can enhance osteoclastogenesis in vitro [109,110]. Upon binding of RANKL to RANK, TNF receptor-associated factors become activated, which results in a cascade of intracellular signaling, eventually activating cascades of adaptors/kinases such as NF-κB and MAPKs, including p38, JNK, and ERK. Eventually, this results in several transcription factors’ activation, including NF-κB, activator protein-1, cyclic adenosine monophosphate response element-binding protein, and nuclear factor of activated T cells 1 (NFATc1), which in turn results in the induction of the expression of osteoclastogenic markers, including tartrate-resistant acid phosphatase (TRAP), a dendritic cell-specific transmembrane protein, osteoclasts-associated receptor (OSCAR), β3 integrin, osteopetrosis-associated transmembrane protein-1, B-lymphocyte induced maturation protein 1, and cathepsin K [101]. The process of osteoclastogenesis is regulated by OPG, which is a decoy ligand to the RANKL receptor. The binding of OPG to RANK can downregulate osteoclast differentiation [103,111,112]. Periodontal ligament cells can regulate osteoclastogenesis through the expression of OPG [106]. Osteoclast differentiation in periodontal diseases is illustrated in Figure 2. Several cytokines can modulate the process of osteoclastogenesis during periodontal disease with subsequent modulation of the process of alveolar bone resorption. IL-1 super family (IL-1ɑ, IL-1β, IL-33, IL, IL-36), IL-6, IL-8, IL-11, IL-17, IL-22, IL-34, and TNF are proinflammatory cytokines that can upregulate osteoclast differentiation [113,114,115,116,117,118]. Periodontitis-associated bone destruction can be attributed to the upregulation of proinflammatory cytokines that favors bone resorption. IL-1 was associated with increased osteoclastogenesis in periodontitis. Osteoclast formation and the progression of inflammatory cells toward alveolar bone were significantly reduced upon blocking of IL-1 and TNF in nonhuman primates [119]. Furthermore, periodontal ligament fibroblasts precultured with IL-1 β significantly upregulated osteoclastogenesis in peripheral blood mononuclear cells culture [120]. IL-1 receptor antagonist significantly reduced the number of osteoclasts in an experimental tooth movement rat model [121]. IL-1 can potentiate RANKL-induced osteoclastogenesis [122,123]. Additionally, IL-1 can upregulate RANKL expression by stromal cells to induce osteoclastogenesis through p38 MAPK [115]. IL-1β can potentiate cementoblasts-induced osteoclastogenesis via upregulation of cementoblast RANKL expression [110]; IL-1ɑ was associated with upregulation of RANKL and downregulation of OPG mRNA expression in periodontal ligament cells via the ERK pathway [124]. IL-1 can also induce osteoclastogenesis via an intracellular pathway independent of RANKL/RANK interaction [123]. Binding between IL-1 and its dimeric receptors IL-1R1 on the surface of osteoclast progenitors triggers intracellular signaling cascade and upregulating transcriptional factors, including JNK, P38, and ERK. IL-1 can also upregulate microphthalmia transcription factor, which induces osteoclast-specific genes such as OSCAR and TRAP [123]. However, IL-1 can only upregulate differentiation of osteoclasts precursor in presence of RANKL or TNF-α, which can upregulate IL-1 secretion by stromal cells and can upregulate IL-1RI expression via c-Fos and NFATc1 [115,123]. RANKL is responsible for priming bone marrow macrophage osteoclast genes, including the gene coding for NFATc1, to be responsive to IL-1-mediated osteoclastogenesis [125]. IL-33 is also involved in upregulating osteoclastogenesis. IL-33 can potentiate RANKL-induced osteoclastogenesis [126]; it was involved in the upregulation of RANKL expression by osteoblasts via ERK and p38 MAPK [127] and by periodontal ligament cells in vitro [128]. Further, expression of IL-33 was upregulated in gingival samples from patients with chronic periodontitis and in rats with induced periodontitis and was accompanied by increased RANKL expression in gingival epithelial cells [129]. IL-33 can also upregulate osteoclastogenesis through a pathway independent of RANKL/RANK interaction. IL-33 interacts with its receptor to activate signaling molecules required for osteoclastogenesis, including a spleen-associated tyrosine kinase, phospholipase Cc2, Grb2-associated-binding protein 2, MAPK, TAK-1, NF-kB, IL-33, TNF-α receptor-associated factor 6 (TRAF6), nuclear factor of activated T cells cytoplasmic 1, c-Fos, c-Src, cathepsin K, and calcitonin receptor [126]. On the contrary, other reports demonstrated that IL-33 was associated with a significant reduction in the number of osteoclasts in vivo [130] and can downregulate the process of osteoclastogenesis through impeding osteoclast differentiation factors such as NFATc1 [131], meanwhile, upregulating osteoclasts apoptosis via upregulation of pro-apoptotic molecules, such as BAX, Fas, and FasL [132]. Additionally, IL-33 is highly expressed in chronic apical periodontitis lesions with a negative correlation with RANKL and a positive correlation with OPG expression, suggesting a protective role of IL-33 against bone loss in periodontitis [133]. The conflicting results regarding IL-33’s effect on osteoclastogenesis can be attributed to its local concentration. A high concentration of IL-33 was associated with increased RANKL expression in periodontal ligament cell culture, while lower levels of IL-33 were associated with increased OPG expression, suppressing the process of osteoclastogenesis [128]. IL-36 γ was also suggested to be involved in periodontitis-associated osteoclastogenesis. IL-36 γ expression in the gingiva was upregulated and positively correlated with a RANKL-to-OPG ratio, indicating its role in RANKL-mediated osteoclastogenesis [134]. IL-6 interacts with its receptor IL-6R to upregulate the process of osteoclastogenesis [52,135] through upregulating RANKL expression on osteoblasts [113]. Soluble IL-6R in the presence of IL-6 can upregulate osteoclastogenesis in bone marrow cells cocultured with osteoblasts [136]. IL-6R inhibition can block osteoclastogenesis in vivo and in vitro [137] and can significantly reduce alveolar bone resorption in the periodontitis model in rats [138]. IL-6 can also upregulate osteocyte RANKL expression to upregulate osteoclastogenesis [139]. IL-6 can also upregulate osteoclastogenesis via a pathway independent of RANK/RANKL interaction [114]. Both IL-6R and IL-11R are expressed on osteoclasts and can transduce signals via the GP130 signaling pathway [114,140]. IL-6 and IL-11 were both able to induce osteoclastogenesis in CD14+ monocytes in the absence of RANKL-expressing cells. Further, osteoclastogenesis was not inhibited by OPG or RANK-Fc (a recombinant RANKL antagonist) but was inhibited by glycoprotein 130 antibodies, denoting that IL-6 can upregulate osteoclastogenesis independent of RANKL [114]. However, the osteoclastogenic effect of IL-6 is dependent on the presence of RANKL in the environment [141]. On the contrary, IL-6 was demonstrated to be nonessential for physiologic bone resorption in vivo but can stimulate osteoblastic bone formation [140]. Moreover, IL-6 was associated with reduced osteoclastogenesis via suppression of NF-κB pathways [142]. A dual role of IL-6 in osteoclastogenesis was revealed. IL-6 and sIL-6R, in the presence of a high level of RANKL, upregulated osteoclast differentiation through the upregulation of NF-κB, ERK, and JNK phosphorylation. While in the presence of low levels of RANKL, IL-6 and sIL-6R downregulated osteoclast differentiation [141], indicating that the level of RANKL is essential for directing the cellular response to IL-6. In the periodontitis rat model, IL-17A was linked to increased alveolar bone loss and a rise in osteoclasts [143,144]. Blocking of IL-17A in rats with induced periodontitis significantly reduced the alveolar bone loss osteoclast number [145]. IL-17A can also upregulate osteoclastogenesis via RANKL upregulation. IL-17A upregulated RANKL expression in osteoblasts [143] and periodontal ligament cells [128] and stimulated osteoclastogenesis via upregulation of the expression of autophagy-related genes and proteins in vitro [143,144]. Periodontitis-associated upregulation of IL-17A and RANKL is mediated through eliciting receptors expressed on myeloid cells-1 (TREM-1). TREM-1 blockage downregulated IL-17A and RANKL expression while OPG expression was upregulated [146]. Another IL involved in periodontitis-associated bone catabolism is IL-22. Levels of IL-22 were significantly higher in the gingiva of patients with periodontitis as compared to healthy individuals and were positively correlated with pocket depth [147]. Patients with periodontitis’ tissue homogenates actively promoted osteoclast activity. When IL-22 was neutralized, this effect vanished, showing how it affects osteoclast activity [147]. IL-22 mediates osteoclastogenesis through the upregulation of RANKL expression. Increased levels of Il-22 and RANKL was correlated with increased alveolar bone resorption in experimental periodontal lesions in rats [148]. Additionally, IL-22 upregulated RANKL expression in vitro in human periodontal ligament fibroblasts via the MAPK signaling pathway, indicating their role in osteoclastogenesis [149]. IL-8, produced mainly by dendritic cells during periodontal inflammation, was implicated in the upregulation of osteoclastogenesis through stimulating inflammatory cells to secrete IFN-γ, IL-17, TNF-α, IL-1β, and RANKL [150]. IL-11 could upregulate RANKL expression by osteoblasts in vitro, thus supporting osteoclastogenesis [151], and could upregulate osteoclastogenesis independent of RANK/RANKL interaction [114]. IL-34 was also linked to increased bone resorption in periodontitis. IL-34 expression in gingival fibroblasts is upregulated upon TNF-α and IL-1β treatment in vitro. IL-34 significantly upregulated osteoclastogenesis in vitro the in presence of RANKL in bone marrow macrophages [152]. TNF acts on osteoblasts [151], stromal cells [153,154], gingival epithelial cells via TNFR1 and protein kinase A signaling [104], and osteocytes [155] to increase RANKL expression. TNF-α can upregulate RANK expression on osteoclasts precursor and sensitize precursor cells to RANKL [154]. IL-1, IL-6, and TNF show a synergistic effect on stimulating osteoclastogenesis [156]. TNF can also downregulate OC, ALP, and RUNX2 expression, impeding osteoblast differentiation [157]. It can also inhibit the WNT signaling pathway to downregulate osteoblast function [158] and increase osteoblast apoptosis [159], resulting in suppression of osteoblast action, which aggravates bone loss in periodontitis. TNF alone cannot initiate osteoclastogenesis; the presence of RANKL is essential for TNF-mediated osteoclastogenesis [115,153,160,161,162] as RANKL prime macrophages undergo osteoclast differentiation in response to TNF [153]. Even though some studies demonstrated that TNF could stimulate osteoclastogenesis independent of the RANK/RANKL pathway [163,164], TNF-α failed to stimulate osteoclastogenesis in RANK-deficient mice [165]. TNF-α and RANKL have a synergistic effect on the process of osteoclastogenesis via the activation of NF-kB and SAPK/JNK [153]. Micro RNA (miRNA) also plays a role in the regulation of osteoclastogenesis in periodontitis. Several miRNAs, including miRNA-124 [166] and miR-218, can reduce periodontitis-associated bone resorption through the downregulation of MMP 9 [167]. While miRNA-31 was upregulated during the process of osteoclastogenesis under RANKL stimulation, miRNA-31 inhibition suppressed RANKL-induced osteoclastogenesis and was associated with impaired actin ring formation via upregulation of RhoA expression [168]. Treatment of cells with a combination of TNF-α and RANKL effectively altered the expression of 44 microRNAs. miR-378 was upregulated and miR-223 was downregulated, while miR-21, miR-29b, miR-146a, miR-155, and miR-210 were upregulated during osteoclastogenesis upon administration of a combination of TNF-α and RANKL [169]. Cytokines and pathways involved in osteoblastogenesis and osteoclastogenesis in periodontitis are summarized in Table 2. The complex bacterial species responsible for periodontal disease include P. gingivalis, Tannerella forsythensis, Treponema denticola, Prevotella intermedia, and Aggregatibacter actinomycetemcomitans [170]. Precisely, P. gingivalis, Tannerella forsythensis, and Treponema denticola are identified as the red complexes that have obtained the attention of researchers [171]. The oral administration of P. gingivalis [172] and Aggregatibacter actinomycetemcomitans [173] resulted in increased alveolar bone resorption which was accompanied by an increase in osteoclasts numbers with a decrease in osteoblasts numbers [174,175]. These results could be explained by the upregulation of RANKL expression in osteoblasts and the downregulation of OPG in vitro induced by P. gingivalis [176,177]. Several studies reported that alveolar bone resorption is commonly associated with multiple bacterial infections rather than a single bacterial infection [178,179,180]. Microbe-associated molecular patterns are unique structural components, including LPS and peptidoglycan (PGN), that can elicit an immune response [181]. The recognition of microbe-associated molecular patterns by the host cell occurs through TLR and nucleotide-binding oligomerization domain (NOD)-like receptors [182,183]. LPS is a bacterial endotoxin capable of provoking a local immune response [76]. LPS is a major component of gram-negative bacteria’s outer membrane that consists of three parts. The outermost domain is formed of polysaccharide chains (O-antigen), while the innermost domain consists of hydrophobic fatty acid chains (lipid A). The O-antigen is attached to lipid A through the oligosaccharide core [184]. The virulence of LPS is attributed to the release of lipid A, which activates the immune response [185]. Bacterial LPS interacts with TLR-4 expressed on innate immune cells, such as macrophages and dendritic cells [186,187]. Consequently, this interaction promotes the production of different cytokines, such as TNF-α, IL-1, and PGE2 [153,188,189]. These cytokines have an important role in osteoclast progenitor cells maturation and bone resorption as they can stimulate RANKL expression in osteoblasts [151,190]. Moreover, LPS is involved in osteoclast formation. The addition of Escherichia coli-derived LPS to murine RAW 264.7 macrophage cells (osteoclast progenitor cell line) induces the formation of osteoclasts with bone-resorbing activity [191]. It was reported that LPS can directly interact with TLR-4 on osteoblast-enhancing RANKL expression [192]. The RANKL/RANK interaction led to the differentiation and activation of osteoclasts. This was confirmed by the inhibition of TLR-4 and TLR-2 expression in mouse-derived osteoblasts, which led to a reduction in RANKL expression upon exposure to LPS [193]. Additionally, LPS is capable of inhibiting RANKL-induced osteoclastogenesis during the early stages of osteoclastic differentiation [194]. LPS-mediated RANKL expression signaling pathways are dependent on the type of bacteria from which LPS originate and their binding with TLR. It was reported that LPS derived from P. gingivalis upregulate RANKL expression by activating the JNK pathway and activator protein-1 transcription factor in osteoblasts [177]. In the same way, Porphyromonas endodontalis upregulate RNAKL expression through the JNK pathway [193]. On the other hand, Escherichia coli-derived LPS upregulate RNAKL expression by activating PI3K signaling molecules or extracellular signal-regulated kinase [193]. Although studies are reporting that LPS alone inhibit osteoclast formation from osteoclast precursors and only promote osteoclastogenesis in RANKL-pre-treated cells [194,195], others reported that LPS induced bone resorption in vitro and in vivo [196,197,198,199]. Therefore, future research addressing the role of LPS in osteoclastogenesis using RANK knockout culture systems and animal models is recommended. PGN is a polymer composed of sugars in addition to peptides present in gram-negative and gram-positive bacteria. It was demonstrated that the systemic administration of Staphylococcus aureus PGN-induced systemic arthritis, evident by bone resorption in vivo [200]. Furthermore, PGN promotes the fusion of osteoclasts during osteoclastogenesis of macrophage-like Raw264.7 cells [201]. Comparable to LPS, PGN also can inhibit osteoclastogenesis in a dose-dependent manner, which indicates that the timing of RANKL stimulation is a critical factor for osteoclastogenesis [194,202,203]. Despite the local administration of Staphylococcus aureus, PGN in mice induced alveolar bone resorption while Escherichia coli PGN failed to induce bone resorption [204]. PGN induces bone resorption through stimulation of TLR-2 [205]. In addition, PGN fragments stimulate inflammatory responses via NOD1 and NOD2, which are cytoplasmic proteins that sense bacterial byproducts. It was reported that PGN-derived, gram-positive bacteria stimulate NOD2 [206,207,208], while gram-negative PGN is a potent stimulator of NOD1 and a weak stimulator of NOD2 [206,207,209]. Although NOD1 is expressed in most tissues, NOD2 is especially expressed in immune cells, such as macrophages [210,211]. This could explain the increased bone resorption activity associated with gram-positive PGN. Furthermore, the role of PGN during bone resorption in periodontitis was emphasized in P. gingivalis-induced periodontitis in NOD2 knockout mice, which resulted in suppression of RANKL expression and impaired alveolar bone resorption [212]. Even though several studies addressed the role of LPS and PGN in osteoclastogenesis in vitro and in vivo, further studies focusing on the exact mechanisms responsible for their effect and how they could be counteracted are needed. The crosstalk among osteocytes, osteoclasts, and osteoblasts is essential for physiological bone turnover and homeostasis maintenance. RANKL is primarily obtained from osteocytes, which acts upon RANK, regulating osteoclast differentiation. Osteocytes express RANKL ten times higher than osteoblasts [213,214]. Moreover, osteocytes are able to control osteoclast formation and bone resorption by upregulating RANKL and downregulating OPG or, in reverse, stimulating the opposite conditions to decrease bone resorption [215]. Osteocytes can exert a stimulatory and inhibitory effect on osteoblasts. Among the most potent signals originating from osteocytes, Sclerostin and DKK1 are strong antagonists of Wnt/β-catenin signaling, which play an important role in promoting osteoblastogenesis and matrix formation [216,217]. Periodontitis tissue contains many pathological factors, including biologically active substances in bacterial plaques and inflammatory mediators produced by immune cells as discussed earlier. These factors are able to increase RANKL expression in osteocytes. LPS from gram-negative bacteria are recognized by TLR2 on the osteocyte surface, which irritates the downstream MAPK/ERK 1/2 signaling pathway and transcription factors, resulting in upregulation of IL-6 expression [218]. IL-6 causes glycoprotein 130-mediated JAK activation, which then phosphorylates STAT [219], that translocates into the nucleus and eventually increases RANKL expression in osteocytes [219,220]. TNF-α binds to the TNF receptor on the osteocyte surface, TNF-α activates the ERK1/2, P38, and JNK/MAPK signaling pathways and/or the NF-κB, which boosts RANKL expression in osteocytes and subsequently promotes alveolar bone resorption [155,221]. Strikingly, RANKL content is significantly increased, accompanied by downregulated OPG levels in periodontitis [222]. As the RANKL/OPG ratio increases, the bone resorption area enlarges by the increased osteoclasts cells number [223]. oRANKL subcellular trafficking regulation in osteocytes were investigated; osteocytes provide RANKL as a membrane-bound form to osteoclast precursors through direct cell-to-cell interaction at the extremities of dendritic processes. OPG acts as a RANKL trafficking regulator by transporting the newly synthesized RANKL to the cell surface when it is stimulated with RANK to regulate osteoclastogenesis [224]. Sclerostin, a secreted glycoprotein generated by osteocytes and encoded by the SOST gene, was found to be highly expressed inGCF ofC\chronic periodontitis patients compared to healthy patients [225]. TNF- α enhance Sclerostin expression in osteocytes via an NF-κB-dependent mechanism, where NF-κB binds to the SOST promoter region and induces an increase in sclerostin expression [221,226]. Moreover, DKK1, which is an endogenous secretory protein mainly produced by osteocytes, can enhance the TNF-α-induced sclerostin in osteocytes to inhibit osteoblast activity [227]. Sclerostin can be considered an effective therapeutic target for periodontal disease treatment, as alveolar bone volume improvement was noticed using DKK1- and Sclerostin-specific antibodies [228,229]. Both Sclerostin and DKK1can interrupt Wnt/β-catenin signaling and compete with WNT proteins for binding to the extracellular regions of low-density lipoprotein receptor-related protein-5/6 on osteoblasts, thus hindering osteoblastogenesis [230,231]. Moreover, DKK1 can inhibit the Wnt/β-catenin signaling pathway, thereby decreasing OPG expression, which in turn leads to an increase in the local ratio of RANKL/OPG in osteocytes, which increases osteoclastogenesis and promotes bone absorption [232,233]. Aging and osteoporosis are common causes of osteocyte senescence [234]. However, in young individuals, early senescence can occur as a stress reaction to inflammation or extracellular matrix remodeling through the secretion of senescence-associated secretory phenotype proteins, which leads to a state of irreversible growth stagnation [235,236]. It was demonstrated that the advanced senescence of osteocytes is related to periodontal pathogens and their products being in close contact with the alveolar bone for a long period. LPS exposure can cause DNA damage in osteocytes to exacerbate the adaptive immune response and periodontal inflammation [237]. This process is called inflamm-aging and may risk bone remodeling and bone homeostasis [238]. In periodontitis, for inflammatory cells and periodontium cells, including osteocytes, apoptosis is amplified. The apoptosis of these cells exerts a significant effect on the progression of chronic inflammation and tissue damage [239,240]. Although it is still debatable, there is an intrinsic and complex cross-talk mechanism between apoptotic osteocytes and osteoclastogenesis. Apoptotic osteocytes produce apoptotic bodies that promote osteoclast progenitor cells to differentiate into osteoclasts. Apoptotic osteocytes can secrete RANKL and directly modulate osteoclast formation and bone remodeling [241,242]. However, this process is not entirely dependent on RANKL, as osteoclastogenesis is not decreased in the presence of OPG concentrations ranging from 50 ng/mL to higher levels (>400 ng/mL). necrosis occurs when apoptotic osteocytes are not removed which aggravates the secretion of multiple cytokines and immune cells aggregation, which potentiates the generation of pro-inflammatory molecules and stimulates the secretion of RANKL in neighboring cells [243]. Mononuclear osteoclast precursor cells produce TNF-α that recognizes apoptotic osteocytes surface markers, leading to enhanced osteoclast formation [244]. Apoptosis of osteocytes may also be aided by bacterial stimulus and inflammatory substances, according to literature [245]. Clarifying the role of osteocyte death in periodontitis will help to improve future clinical prevention, diagnosis, and treatment of periodontitis. Some biomarkers could be used as diagnostic tools for the course of many diseases in the human body, including periodontal diseases [246]. Many studies were performed to correlate the presence of one or a group of cytokines in the saliva or the GCF and the periodontal condition of the patient [139,244,247,248,249]. Focusing on the biomarkers present in the GCF, it was proved that IL-1 with both its types, IL-1α and IL-1β, possess great potential in distinguishing periodontitis from periodontal healthy cases [247]. Such biomarkers could reveal improved diagnostic ability when combined with anti-inflammatory cytokine, IFN-γ, and IL-10 [247]. Another group of biomarkers that could be used in the diagnosis of periodontal diseases is IL-1β, IL-8, MMP-13, osteoprotein, and osteoactivin [139]. In addition, the level of IL-17, IL-18, and IL-21 in the GCF could be correlated with the severity of the periodontal disease; their high level in the GCF reflects an extent of destruction in periodontal tissues, though IL-21 has a particular significance, as it could be used to differentiate between periodontitis and gingivitis [250]. Additionally, TNF-α present in the GCF could be used for the diagnosis of periodontal diseases/inflammation, as its increased concentration in GCF was remarked in patients suffering from periodontal diseases at different stages [251]. According to a recent systematic review and meta-analysis, it was concluded that the salivary biomarkers that have a potential for the diagnosis of periodontal diseases are TNF-α, TNF-β, IL-1α, IL-1β, IL-4, IL-6, IL-8, IL-10, IL-17, IL-32, PGE2, MMP-8, MMP-9, MIP-1α, and TIMP-2. In addition, the IL-1β, TNF-α, MMP-8, and MMP-9 biomarkers could be used to monitor the prognosis of the periodontal condition after the scaling and the root planning [252]. Such findings reveal the potentiality of using the patient’s saliva for the diagnosis/prognosis of periodontal diseases relying on salivary/GFC biomarkers. This requires the assistance of digital microfluidics for the clinical translation of such promising biomarkers, allowing some chair-side Lab-on-a-chip technology available for easy and rapid clinical use [248,253,254]. Periodontitis has multiple etiological factors acting at multiple aspects, primarily the presence of dysbiotic microbial communities and the environmental and systemic health status that direct the host response to such a challenge. Periodontitis is widely accepted now to be a dysbiotic inflammatory disease; thus, the main factor affecting the extent of the destruction is now believed to be the host immuno-inflammatory status, whether hypo- or hyperresponsive to the existing dysbiotic microbiota [255]. Treatment methods employed currently fail to address the uncontrolled host immune response; hence, considerable attention is now directed toward the potential role of modulating the innate immune response to periodontal pathogens to control the inflammatory response, control osteoclastogenesis, and restore physiological bone turnover and homeostasis [256]. Immunotherapies aim to target the key players in periodontitis, particularly neutrophils, monocytes, macrophages, T lymphocytes, and inflammatory cytokines. Several strategies are now widely investigated, including the use of antioxidants to reduce oxidative stress and prevent periodontitis. Resveratrol, an antioxidant supplement, was shown to reduce the production of ROS by human gingival fibroblasts and improved the cellular response in vitro [257]. Other strategies include drugs targeting key immune cells and cytokines in periodontitis, antibacterial therapies through vaccinations, employing stem cell therapy and cell-free therapies using secretome and exosomes, gene therapies, and others (reviewed in [256]), or the use of biomaterials functionalized/loaded with immunomodulating agents (reviewed in [258]). However, the translation of these approaches clinically is rather still limited, and more research is needed to fully assess the efficacy, safety, and employment of different immunotherapies. Periodontitis is an inflammatory disease that is initiated by dysbiotic oral microbiota which is believed to protect their existence through dysregulation of the host immune response. When the immune cells become unable to control the dysbiotic microbial attack, the extensive release of cytokines, matrix-degrading enzymes, and chemokines occur. Subsequently, this leads to increased periodontal tissue breakdown. Several proinflammatory cytokines released during the process of periodontitis could have a great toll on the alveolar bone. Selective inhibition of these cytokines or their cellular receptors can be beneficial to reduce periodontitis-associated bone resorption. Microbe-associated molecular patterns have a great role in initiating host immune response and bone resorption; therefore, addressing the exact mechanisms of their effect and how to counteract them is mandatory. Consequently, tissue-specific host immunity should be the future of research for the pathogenesis of periodontitis to unveil such a complicated process and hence to reach tissue-specific diagnostic/therapeutic solutions for patients with periodontal diseases worldwide.

PMC10003255

Silvia D’Ambrosi,Stavros Giannoukakos,Mafalda Antunes-Ferreira,Carlos Pedraz-Valdunciel,Jillian W. P. Bracht,Nicolas Potie,Ana Gimenez-Capitan,Michael Hackenberg,Alberto Fernandez Hilario,Miguel A. Molina-Vila,Rafael Rosell,Thomas Würdinger,Danijela Koppers-Lalic

Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection

02-03-2023

liquid biopsy,biomarkers,circular RNA,messenger RNA,platelets,lung cancer,cancer diagnosis

Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection.

Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection. With 1.8 million deaths per year, lung cancer remains the leading cause of cancer mortality worldwide [1]. This high mortality can be attributed to two main reasons: late diagnosis and the inefficiency of the treatments available. Most of the patients present an advanced stage of the disease at the time of diagnosis, leading to an expected survival at 5 years below 10% [2,3,4,5]. Novel reliable, sensitive, and accurate diagnostic tests are required since early-stage identification is associated with longer life expectancy. In recent years, liquid biopsy (LB) has been proposed as a highly promising diagnostic approach for the detection and management of cancer patients. An analysis of tumor-derived biomarkers present in human body fluids offers a minimally invasive, safe, and sensitive alternative or complementary approach to tissue biopsies. Besides the commonly used blood-based biosources and biomolecules, such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), and extracellular vesicles (EVs), blood platelets have recently emerged as promising novel carriers of cancer biomarkers [6,7,8]. Platelets dynamically interact with tumor cells, which can lead to a direct and an indirect alteration of their transcriptome [9]. Changes in the RNA profile of these tumor-educated platelets (TEPs) can be used as a surrogate signature for the detection, localization, and molecular profiling of different types of cancer [10,11,12,13,14]. Furthermore, it has been established that a considerable fraction of platelets are also generated within the lung, which may position them as a more advantageous indicator of lung cancer due to the possible impact of the disease on platelet formation [15,16,17,18]. Platelet RNA repertoire includes several types of RNA families which can be potentially used as biomarkers. A first insight of the diagnostic potential of the TEPs transcriptome was described during the profiling of the platelet mRNA repertoire of metastatic lung patients and asymptomatic individuals. This study discovered that the presence of cancer results in altered spliced mRNA profiles [19]. Afterwards, the use of platelet spliced mRNA as a biomarker for the detection and classification of various tumor types has been investigated in numerous studies [10,11,20,21,22]. More recently, the expression of other types of RNAs has been found dysregulated in platelets [14,23]. In particular, human platelets are highly enriched in circular RNA (circRNA) [24]. This type of RNA is characterized by a covalent loop structure generated by a noncanonical alternative splicing process named back-splicing. Due to their high stability, abundance, and spatiotemporal specific expression, circRNA have received increasing attention for their potential role as cancer biomarkers [25]. Recently, we have provided evidence that platelet-derived circRNA profile changes in the presence of NSCLC, indicating that circRNA may hold the potential as a biomarker for liquid biopsy tests [14]. Previous studies on platelet transcriptome were based on the use of RNA-seq technology. Although RNA-seq is currently the most used methodology for genomic-based biomarker discovery, its implementation in the clinic has several limitations due to its time-consuming and elaborate library preparation protocol, the lack of standardized methods, the high cost, and complex data analysis [26]. NanoString nCounter, a platform for the high-throughput analysis of gene expression, has grown in popularity both in clinical settings and in translational research due to its fast, simple, and reliable protocol. By directly hybridizing and counting the individual targets, nCounter technology enables the multiplex analysis of signatures up to 800 genes with high reliability and reproducibility. In contrast to RNA-seq methods, nCounter RNA analysis does not require reverse transcription, amplification, nor cDNA library construction. Altogether, all these features make this system less prone to bias, leading to a more accurate quantification of the targets. Clinical tests have been developed employing nCounter technology, including the FDA-approved nCounter Prosigna test, which stratifies breast cancer subtypes and predicts recurrence risk in post-menopausal women [27,28], and the tumor inflammation signature (TIS) assay, which forecasts PD-1 checkpoint blockade and clinical response across several tumor types [29]. This platform has also been employed for the discovery of potential biomarker signatures in various types of LB biosources, including cfDNA, cell-free RNA (cfRNA), EVs (including DNA, micro RNA (miRNA) and mRNA), as well as CTCs [30,31,32,33,34,35,36]. However, the platelet transcriptome has not been explored yet through this technology for LB purposes. Here, we present the development of a protocol for the interrogation of platelet mRNA and circRNA repertoire using NanoString nCounter technology and machine learning (ML) approaches. We applied this methodology to the platelet transcriptome obtained from lung cancer and non-cancer individuals in order to identify and evaluate the diagnostic value of each of the individual mRNA and circRNA signatures. Since a single type of biomarker may lack sensitivity and specificity for the enrichment of reliable clinical diagnostics information, we also explore a multi-analyte-based approach, using a combinatorial analysis of platelets-derived mRNA and circRNA to improve the detection of lung cancer. We investigated if a direct platelet RNA analysis might provide adequate gene expression information without performing any pre-amplification step. Due to the limited amount of total RNA present in platelets, we tested different concentrations to determine the minimum amount of RNA input necessary to preserve critical gene expression information. Six different RNA concentrations (1 ng, 3 ng, 6 ng, 12 ng, 24 ng, and 48 ng) obtained from platelets of a lung cancer patient and a non-cancer individual (indicated as control) were analyzed by using the human immunology v2 panel (Supplementary Figure S1A) [37]. As expected, the highest total number of counts (after negative background removal) was observed using 48 ng of total RNA (Figure 1a,b, Supplementary Table S1A,B). The number of counts decreases along with the concentration, following a linear regression model (R2 = 0.99, p-value < 0.0001, both for cancer and control samples, Figure 1a,b), suggesting that hybridization efficiency between probes and RNA remains consistent also at the lowest concentrations. Similar results were obtained when considering the average counts per transcript (R2 = 0.98, p-value < 0.0001, for control and R2 = 0.97, p-value < 0.0002 for cancer, Supplementary Figure S1B) confirming the previous observations. However, we found a significant drop in the number of transcripts detected when 1 ng and 3 ng of total RNA were used compared with higher concentrations (Supplementary Table S1A,B). Using PCA analysis, we observed that samples generated with total RNA inputs of 1 ng and 3 ng deviated from the main cluster that encompassed the other concentrations examined. This implies that the RNA profiles of samples generated with 3 ng or less of RNA input are not consistent with those acquired with higher RNA input, which could hamper subsequent gene expression analyses (Figure 1c,d). Therefore, we conclude that a minimum concentration of 6 ng of platelet RNA without pre-amplification process is recommended for sufficient and robust transcripts expression profiles for platelet-RNA analysis with nCounter. Following the protocol described in Figure 2, we investigated the potential use of platelet mRNA (using human immunology v2 panel [37]) and circRNA (with the 78-circRNA custom panel [38]) as diagnostic biomarkers. We selected a cohort of 60 platelet samples isolated from lung cancer patients (n = 30) and non-cancer controls (n = 30) equally distributed per age and gender (Table 1). Since early-stage detection is crucial for lung cancer diagnosis, we selected samples from patients with mainly early-stage (from stage IA to stage IIIA) lung cancer (n = 20) while the remaining samples were from patients diagnosed with metastatic tumor stage (n = 10). We include both asymptomatic individuals (n = 27) and samples from patients with confirmed benign lung nodules (n = 3) in the control group. Total RNA extracted from platelets was stored in RNAlater (as explained in Section 4 Materials and Methods) and checked for quality before further processing (Supplementary Figure S2A–F). After subtracting the background (negative control) signal, we observed that 159 out of the 594 genes in the human immunology v2 panel were not present in any of the processed samples. A total of 402 platelets-derived mRNA were detected in both the control and cancer groups, whereas 18 transcripts were exclusively found in the control group and 15 in the lung cancer group (Figure 3a). All the 78 circRNAs present in the custom-made panel were detected in at least one of the samples. Only three circRNAs (circNOL6, circPTPRM, circGAyS8) were exclusively detected in the lung cancer group (Figure 3b). All these three circRNAs have been previously found to be dysregulated in lung cancer [39,40,41,42]. The analysis of the average number of transcripts detected per group using the human immunology v2 panel revealed 185 ± 97 mRNAs in the control group and 218 ± 85 mRNAs in the cancer group (Figure 3c). Although the average number of transcripts is slightly higher in the cancer group than in the control, the difference is not statistically significant (ns) (Mann–Whitney’s U p-value > 0.05) (Figure 3c). Out of the 78 circRNA present in the custom-made panel, an average of 54 ± 8 circRNA were detected in the cancer group and 53 ± 9 for the control group (Figure 3d). Moreover, in this case, no statistical difference between the two groups was observed (Mann–Whitney’s U p-value > 0.05) (Figure 3d). mRNA raw count data (Supplementary Figure S3A) was evaluated prior to normalization through analytical exploratory analysis. Assessment of the unnormalized mRNA raw data analysis utilizing a PCA plot reveals no significant batch effect or clear group cluster separation (Supplementary Figure S3B,C). To prevent inaccurate normalization due to genes with low expression and background noise, we removed 314 mRNA targets (as explained in Section 4 Materials and Methods) from the analysis. Moreover, based on the interquartile range method (1.5 IQR rule), two out of sixty samples were identified as possible outliers (Supplementary Figure S3D). Additionally, these samples also presented aberrant values for binding density and positive control linearity; therefore, they were excluded from subsequent data processing. Since an optimal normalization of the data is key for precise and consistent outcomes, we compared two different approaches: edgeR and DESeq2. Based on the RLE analysis, DESeq2 was found to perform better than edgeR in normalizing the mRNA data (DESeq2 R2 = 0.002 (Figure 4a) and edgeR R2 = 0.036 (Supplementary Figure S3E)). Differential expression analysis between lung cancer and the control group revealed a total of 25 significantly differentially expressed mRNA (|FC| > 0.5 and p-adj < 0.05), of which 15 were upregulated and 10 downregulated in lung cancer patients (Figure 4b). The circRNA raw count data (Supplementary Figure S4A) have been processed following the same filtering and normalization procedure as previously performed for mRNA data. The PCA plot evaluation reveals no apparent class grouping or substantial batch impact (Supplementary Figure S4B,C). Only five of the seventy-eight circRNA targets were excluded due to low expression (see Section 4 Materials and Methods). Two samples were flagged by IQR analysis as potential outliers (Supplementary Figure S4D). Since neither of them deviated from the main cluster in the PCA plot or showed any anomalies on the standard control metrics supplied by NanoString, both samples were kept in the dataset for further analysis. Similarly for the mRNA data, the DESeq2 package was found to obtain a more precise normalization of the data (DESeq2 R2 = 0.002 (Figure 4c) and edgeR R2 = 0.023 (Supplementary Figure S4E)). Differential expression analysis identified only one circRNA (circFUT8) as significantly upregulated in the lung cancer group (|FC| > 0.5 and p-adj < 0.05, Figure 4d). Interestingly, this circRNA was previously reported to be one of the 10 most upregulated circRNA in lung cancer tissue [43]. To evaluate the potential use of the human immunology v2 panel as platelet signature for lung cancer detection, we employed ML approaches (as explained in Materials and Methods). The RFECV algorithm selected a final 28 mRNAs signature (Supplementary Figure S5A and Supplementary Table S2). To investigate the performance of different ML algorithms, two ML classifiers were tested (ETC and RF) using 5CV method. RF classifier testing on the 28-mRNA signature leads to the highest ROC AUC of 0.88 ± 0.1 and an accuracy of 76% compared with ETC algorithm. Sensitivity and specificity were respectively 77% and 75%, resulting in 44 out of 58 cases being correctly classified (Figure 5a, Supplementary Figure S5b,c). Classification scores were significantly different between the lung cancer group and the control group (Mann–Whitney U test p < 0.0001, Figure 5b). The same ML approach was applied to investigate the diagnostic potential of the 78 circRNA custom panel. The RFECV method selected a signature of 21 circRNAs (Supplementary Figure S5D and Supplementary Table S2). Both RF and ETC classifiers resulted in a final AUC of 0.81 ± 0.08 and an accuracy of 72% (Figure 5c and Supplementary Figure S5E). The two models differ in sensitivity and specificity; the RF model shows a higher sensitivity (Sensitivity RF: 77%) compared with ECT (Sensitivity ETC: 70%), but a lower specificity (Specificity RF: 67% and Specificity ETC: 73%) (Supplementary Figure S5F). The classification scores of both models were confirmed to be significantly different between the two groups (Mann–Whitney U test p < 0.0001, Figure 5d). Combinatorial analysis of different types of molecular biomarkers has not yet been investigated in platelets. Our unique cohort of samples allows the exploration of both platelet mRNA and circRNA derived from the same source. Using the same ML approach applied before, we built a new predictive model using features derived from both the mRNA and circRNA panel (total features = 338) and excluding the two previously identified outlier samples (Supplementary Figure S3D). The RFECV algorithm selected a signature of six mRNAs (BTK, IRAK2, PSMB9, RUNX1, SYK, and LILRB1) and two circRNA (circSLC8A1 and circCHD9) (Supplementary Figure S6A and Supplementary Table S2). Once again, the RF classifier yielded the predictive model with the highest ROC AUC (0.92 ± 0.06) and accuracy (81%) (Figure 6a and Supplementary Figure S6B). Sensitivity and specificity were 77% and 87%, respectively (negative predicted value (NPV) = 0.77 and positive predicted value (PPV) = 0.85), resulting in 47 out of 58 samples being correctly classified (Figure 6b). The classification scores of the cancer and control groups showed statistically significant differences (Mann–Whitney U test, p-value < 0.0001, Figure 6c). In terms of AUC, accuracy, and specificity, this model outperforms the results seen in the previous models using an independent signature of mRNA or circRNA, suggesting a potential synergistic role of the combinatorial use of these two RNA types as molecular biomarkers. The outcome of the combinatorial mRNA-circRNA analysis suggests that the inclusion of different RNA types from the same biosource provides a biomarker signature for the detection of lung cancer. Based on these results, we sought to design a computational method for identifying a specific early-stage disease signature. For the identification of this signature, we employed and re-analyzed the 20 early-stage lung cancer samples (stage IA to IIIA) together with the control cohort (n = 30) (Supplementary Figure S7A–C). The combinatorial analysis of mRNA and circRNA panel was run through the ML algorithm, which selected a signature of only five features including two circRNAs (circSLC8A1 and circCHD9) and three mRNAs (PSMB9, RUNX1, and LILRB1). Based on this new signature, the algorithm was able to classify early-stage lung cancer samples and controls with an AUC of 0.96 ± 0.03 and an accuracy of 86% (Supplementary Figure S8A). The sensitivity and specificity reached by this early-stage predictive model were 85% and 86%, respectively. Although we observed three false negative samples, which were derived from two patients with stage IIIA and one stage IA (Supplementary Figure S8B), the classification score analysis showed a significant separation of the two groups of interest (Mann–Whitney U test, p < 0.0001, Supplementary Figure S8C). Cumulatively, our data strongly suggest that combinatorial analysis of different RNA types found in blood platelets enables optimal classification of lung cancer patients and demonstrates the potential for early-stage detection. Platelet transcriptome is a rich source of cancer biomarkers. In this study, we developed a novel and reliable methodology for the interrogation of platelet mRNA and circRNA repertories in order to discover and assess the diagnostic value of each individual RNA type. However, most current liquid biopsy tests rely on the use and analysis of one single type of molecular biomarker, which may often lack the sensitivity and specificity required to obtain clinically reliable information. Therefore, we investigated whether combinatory analysis of platelet mRNA and circRNA derived from the same source may help us to improve the detection of lung cancer patients compared to using the single signature of both types of biomarkers. Most of the current studies on platelet transcriptome have been based on RNA sequencing data. Although RNA-seq represents a powerful tool to perform high-throughput analysis, its clinical use is limited by the long turnaround time, high cost, and the complex computational analysis. NanoString nCounter technology represents a valid alternative for the clinical implementation of LB tests. Different from the qPCR and NGS assays, this methodology permits a robust and reliable quantification of the RNA molecules without the bias introduced by reverse transcription or amplification. The automated processing minimalizes in-between steps handling errors. The time from sample preparation to data results requires only three days. However, this technology has not yet been largely utilized for liquid biopsy profiling. Clinical samples, specifically liquid biopsy specimens, often suffer from a limited amount of RNA material for subsequent gene expression analysis. We investigated whether direct usage of platelet RNA in the analysis could provide adequate gene expression profile with the least amount of input. Our findings led us to the conclusion that no pre-amplification step is required to assess gene expression in platelets from as little as 1 ng of total RNA. However, a minimum of 6 ng of RNA is recommended as initial input to reduce intrasample variability and increase the reproducibility of the assay. In this proof-of-concept study, mRNA and circRNA profiles of human platelets derived from lung cancer patients (n = 30) and non-cancer individuals (n = 30) were investigated using two different gene panels. The human immunology v2 panel includes 594 genes involved in the immune response such as cytokines, enzymes, interferons, and their receptors [37]. Out of the 594 mRNAs present in the panel, 435 mRNAs were detected in platelet samples analyzed, whereas 18 were exclusively expressed in the control group and 15 in the cancer samples. The second custom-made panel comprised 78 circRNA targets, including circRNA candidates described to be differentially expressed in lung cancer tissues, cell lines, or body fluids [38]. All 78 targets were detected in platelet samples investigated. Three of them appear to be present exclusively in the cancer group. These three circRNAs were previously found dysregulated in lung cancer tissues with an important role in cancer progression and regulation [39,44,45]. They function as a sponge and regulate the activity of important miRNA, controlling tumorigenesis, cancer progression, and proliferation processes [39,40,41,42]. In order to analyze and determine the diagnostic potential of platelet transcriptome, we developed a complete computational workflow based on nCounter data analysis and machine learning. This bioinformatic pipeline can be divided essentially into four main parts (Figure 2). In the first part, the quality controls and the filtering of possible sample and gene outliers are performed. This step is particularly important to improve and correct the data to obtain an optimal normalization and reduce bias due to the intra-variability of the samples. Based on these criteria, only two samples processed with human immunology v2 panel were excluded from downstream analysis (Control-3 and Control-5). In the second and third parts, we used and assessed two different biostatistical packages for normalization and DE analysis. Based on RLE plot analysis, DESeq2 outperformed edgeR normalization for both panels studied. DE analysis of the mRNA panel resulted in a total of 25 DE mRNA (Figure 4b). According to gene ontology (GO) analysis, the upregulated genes are mostly involved in inflammatory pathways mediated by chemokine and cytokine signaling, oxidative stress response, and cell signaling. While the downregulated genes are mainly associated with B cell and T cell activation, EGF, TGFβ, Wnt, PDGF signaling pathway, and inflammatory response. The circRNA DE analysis indicates only one significant differentially expressed circRNA between the cancer and control group (Figure 4d). Previous studies confirmed hsa_circRNA_101367 (circFUT8) as one of the most upregulated circRNA in lung cancer [43]. This circRNA can regulate the proliferation, invasion, and apoptosis of lung cancer cells by sponging miR-145 or controlling miR-944/YES1 axis [46,47]. The fourth section of this dry lab workflow employs machine learning approaches to generate prediction models. ML can be considered a novel method for developing predictive signatures that typically outperforms individual biomarkers identified by differential expression analysis. Using individual mRNA and circRNA data profiles, the ML prediction models generated reached an AUC of 0.88 using a selected signature of 28-mRNA and an AUC of 0.81 using a 21-circRNA signature (Figure 5a,c). However, the combinatorial analysis performed by combined data derived from both RNA types outperforms the results obtained with the single signature. The RFECV algorithm identified a signature of only eight biomarkers (six mRNA and two circRNA), six of which (BTK, PSMB9, RUNX1, SYK, LILRB1, and circSLC8A1) were previously selected in the individual mRNA and circRNA signatures, while IRAK2 and circCHD9 were newly included. Using these features, the prediction model showed an AUC of 0.92 with a sensitivity of 77% and a specificity of 87% using the RF classifier (Figure 6a). Combinatorial analysis not only reduces the number of features of the predictive model, but it also increases the AUC, improving the classification of the two groups of interest. These results indicate that a combination of different types of biomarkers possibly enhances the prediction value over that of single ones. Despite improvements in terms of AUC, accuracy, and specificity, an increase in the sensitivity of the test is not observed. Post-analysis examination of incorrectly classified samples indicated that six out of the seven false negative samples originated from patients diagnosed with stage III (n = 3) and stage IV (n = 3). This implies that the selected biomarkers from our prediction model most likely reflect the gene expression signature of the earlier stages of the disease. This hypothesis was further supported by the combinatorial analysis performed only with samples diagnosed as surgically resectable tumors (stages Ia–IIIa). This model, indeed, confirmed that five out of the eight biomarkers previously selected (circSLC8A1, circCHD9, PSMB9, RUNX1, and LILRB1) generated a predictive model specifically for early-stage cancer detection reaching an AUC of 0.96, sensitivity of 85%, and specificity of 86% (Supplementary Figure S8A). Taken together, current findings suggest that these biomarkers may be sensitive to detecting lung cancer at early stage. Although the restricted number of platelet samples used in our current study imposes a limitation, our proof-of-concept results seem encouraging. This also includes the results from a small group of individuals diagnosed with lung nodules, as a control for non-cancerous disease, that were correctly classified by all our prediction models. A larger cohort of samples for the training and an independent validation group is needed to confirm the clinical efficacy of the combinatorial mRNA-circRNA signatures identified. Platelet transcriptome is a promising liquid biopsy biosource of cancer-related biomarkers. Although the methodology for generating platelets-derived transcriptome analysis is available [21], the implementation of platelet-derived tests in routine practice is currently hampered by a lack of standardized automated procedures for collecting and processing large numbers of clinical samples in multicenter settings and clinical validation. In this study, our goal was to design and establish, for the first time, a workflow for the nCounter analysis of mRNA and circRNA from platelets for the development of a liquid biopsy test for the detection of lung cancer. We have demonstrated the feasibility of using nCounter for the investigation of both platelet-derived mRNAs and circRNAs, including differential expression analysis, and the development of an ML predictive model. Importantly, our results, using a first multi-analytical approach for combinatorial analysis of mRNA and circRNA signature derived from blood platelets, emphasizes that the combination of the different types of RNAs may help to improve the detection of early-stage lung cancer patients. Whole blood samples from lung cancer patients (n = 30), asymptomatic individuals (n = 27) and people with benign lung nodules (n = 3) were provided by the Amsterdam UMC (VU University Medical Center, Amsterdam, The Netherlands) and Maastricht University Medical Center (Maastricht, The Netherlands). Whole blood was drawn at the Amsterdam UMC into EDTA-coated BD Vacutainer tubes. At the Maastricht University Medical Center, BD Vacutainer tubes containing 3.2% buffered sodium citrate were used for blood-sample collection. Both collection protocols guarantee minimal platelet activation [10,21,48,49]. Patients with cancer had their blood drawn at the time of diagnosis or, in the event of surgically treatable (resectable) tumors, one day before surgery. Histological analysis of the tumor tissue biopsy was performed to determine the diagnosis. Asymptomatic individuals had no prior or current medical records of any kind of cancer during the time of blood collection and no additional examinations were carried out to verify the absence of cancer. Clinical information about the patients was gathered, including their age, gender, type of tumor, and level of metastasis (Supplementary File S1). For the current study, age- and gender-matching was done by incorporating samples of non-cancer controls and cancer patients with comparable median ages and gender distributions between the two groups. Clinical follow-up of asymptomatic controls was not available due to the anonymization of these samples in accordance with the ethical guidelines of the hospitals. The Declaration of Helsinki’s guiding principles were followed in the conduct of this investigation. This study has received approval from the medical ethics committees of the two participating hospitals (approval code: 11-4-117.4/pl, 2016.268 and 2017.545). The informed permission form for blood collection and blood platelet analysis was given to and signed by each participant. Platelets isolation from the whole blood sample was performed as previously described [21]. Briefly, to separate platelet-rich plasma (PRP) and nucleated blood cells, collected blood was spun at 120× g for 20 min, followed by PRP centrifugation at 360× g for 20 min at room temperature. Resulting platelets pellet was re-suspended in RNAlater (Thermo Scientific, Waltham, MA, USA), incubated at 4 °C over-night, and stored at −80 °C until use. At the Maastricht University Medical Center, PRP was obtained by centrifuging blood sample at 240× g for 15 min. PRP was supplemented with iloprost (50 nM) to reduce ex vivo platelet activation. PRP was centrifuged for two minutes at 1600× g to pellet the platelets, followed by the addition of RNAlater and storage at −80 °C until use. Both procedures guarantee the isolation of highly pure platelet pellets with minimal leukocyte contamination and platelet activation. There were no discernible deviations detected in downstream analyses between the two methods [21,48,49]. Total RNA isolation was carried out using the mirVana RNA isolation kit according to the manufacturer’s instructions (Ambion, Thermo Scientific, cat. no. AM1560). Extracted RNA was eluded in 30 μL of mirVana buffer and the quantity and quality were assessed by RNA 6000 Picochip (Bioanalyzer 2100, Agilent, Santa Clara, CA, USA). RNA samples with RIN values higher than 7 and/or with distinguishable rRNA peaks were considered for further analysis. The assays were performed using the NanoString nCounter Flex System (NanoString Technologies, Seattle, WA, USA) with two different nCounter panels for the analysis of platelet-derived RNA. The human immunology v2 panel (NanoString Technologies) targets 594 genes involved in the immune response such as cytokines, enzymes, interferons, and their receptors [37]. For each sample, 6 ng of total platelet RNA was hybridized with the biotinylated capture probe and the reporter probe attached to color-barcode tags for 18 h at 65 °C. The second panel was a custom-made panel targeting 78 circRNAs (78-circRNA panel), 6 linear reference genes and 4 mRNAs [38]. For this analysis, 8 ng of total platelet RNA from each sample was hybridized with the capture and reporter probes for 18 h at 67 °C. The automated nCounter® Prep Station was used to process the samples. The samples were purified and immobilized in a sample cartridge for data collection, where the target mRNA and circRNA in each hybridized sample were quantified, using the nCounter® Digital Analyzer. Output data in the report code count (RCC) format was exported into the nSolver analysis software (version 4.0.70). The background of each sample was computed using the geomean of the counts of the negative probe (negative controls, NCs) plus two times the standard deviation. Raw counts below the negative background value were excluded from further analysis. Pre-processing and normalization of the data were performed using R (version 4.0.3) and RStudio as graphical interface (version 2022.02.2). The quality of the raw RCC proprietary format data was initially assessed by using the NanoStringQCPro (version 1.22.0) package. Standard control metrics embedded by NanoString, such as imaging, binding density, positive control linearity, and limit of detection, were used to search for any potential outlier samples. Additionally, all samples were also subjected to supplementary exploratory examination, including the principal component analysis (PCA) and inter quartile range (IQR) method for outlier detection. Samples higher than the upper bound (Q3 + 1.5 × IQR) or lower than the lower bound (Q1 − 1.5 × IQR) were excluded from subsequent analysis. Prior to normalization, negative control probes embedded to each panel were used to filter out targets with poor expression and high background noise. Consequently, the background values were firstly calculated, by taking the mean of each sample’s negative controls increased by two times the standard deviation, and then removed from each sample. Any transcript that indicated a score of less or equal to 0 in more than 75% of the examined samples was excluded from further examination. After these filtering steps, the data was again evaluated using a PCA plot. Two different packages were compared for the normalization of the data: DESeq2 (version 1.30.1) and edgeR (version 3.32.1). The normalization performance was assessed using the standard relative log expression (RLE) plot. DESeq2 was chosen as the default to perform the normalization of the data. Differential expression (DE) analysis was performed to find significantly differentially (|FC| > 0.5 and p-adj < 0.05) expressed genes between the cancer and control groups. The machine learning approach was implemented in Python (v3.9.13) using the Scikit-learn (v1.1.0) library. Initially, the DESeq2-normalised data, along with each sample’s classification label, were imported into the python environment. For combinatorial analysis, the mRNA and circRNA normalized datasets were merged together with previous analysis. Highly correlated (higher than 0.95), as well as quasi-constant features, were excluded from further analysis. The recursive feature elimination with cross-validation (RFECV) algorithm was then utilized along with the random forest (RF) classifier to perform the feature selection in addition to the leave-one-out cross-validator (LOOCV). RFECV determined automatically the number and the composition of the most relevant features. This subset of genes, which composes the prognostic gene signature, would further be used as an input to our classification models. Two different supervised machine learning algorithms, RF and extra trees classifiers (ETC), were selected along with the selected features to perform this classification problem. In our case, the 5-fold cross-validation (5CV) was used. In a more detailed manner, the dataset was randomly divided into 5 folds, with 4/5 of the data being used to train the model and the remaining 1/5 being used to test its behavior. This process was repeated 5 times. The use of k = 5 was chosen to reduce the bias in the testing set due to the limited number of samples available. The classifier with the highest mean AUC ROC value was then selected. Probability scores for each sample were obtained from the final classifier. Finally, additional statistical metrics such as sensitivity, specificity, accuracy, PPV, and NPV were also calculated.

PMC10003256

Fengyan Meng,Yuping Wu,Yu Yu,Guixian Bu,Xiaogang Du,Qiuxia Liang,Xiaohan Cao,Anqi Huang,Xianyin Zeng,Linyan Huang,Fanli Kong,Yunkun Li,Xingfa Han

Spexin2 Is a Novel Food Regulator in Gallus gallus

02-03-2023

Spexin2,appetite regulation,hypothalamus,chicken

Spexin2 (SPX2), a paralog of SPX1, is a newly identified gene in non-mammalian vertebrates. Limited studies in fish have evidenced its important role in food intake and energy balance modulation. However, little is known about its biological functions in birds. Using the chicken (c-) as a model, we cloned the full-length cDNA of SPX2 by using RACE-PCR. It is 1189 base pair (bp) in length and predicted to generate a protein of 75 amino acids that contains a 14 amino acids mature peptide. Tissue distribution analysis showed that cSPX2 transcripts were detected in a wide array of tissues, with abundant expression in the pituitary, testis, and adrenal gland. cSPX2 was also observed to be ubiquitously expressed in chicken brain regions, with the highest expression in the hypothalamus. Its expression was significantly upregulated in the hypothalamus after 24 or 36 h of food deprivation, and the feeding behavior of chicks was obviously suppressed after peripheral injection with cSPX2. Mechanistically, further studies evidenced that cSPX2 acts as a satiety factor via upregulating cocaine and amphetamine regulated transcript (CART) and downregulating agouti-related neuropeptide (AGRP) in hypothalamus. Using a pGL4-SRE-luciferase reporter system, cSPX2 was demonstrated to effectively activate a chicken galanin II type receptor (cGALR2), a cGALR2-like receptor (cGALR2L), and a galanin III type receptor (cGALR3), with the highest binding affinity for cGALR2L. Collectively, we firstly identified that cSPX2 serves as a novel appetite monitor in chicken. Our findings will help clarify the physiological functions of SPX2 in birds as well as its functional evolution in vertebrates.

Spexin2 Is a Novel Food Regulator in Gallus gallus Spexin2 (SPX2), a paralog of SPX1, is a newly identified gene in non-mammalian vertebrates. Limited studies in fish have evidenced its important role in food intake and energy balance modulation. However, little is known about its biological functions in birds. Using the chicken (c-) as a model, we cloned the full-length cDNA of SPX2 by using RACE-PCR. It is 1189 base pair (bp) in length and predicted to generate a protein of 75 amino acids that contains a 14 amino acids mature peptide. Tissue distribution analysis showed that cSPX2 transcripts were detected in a wide array of tissues, with abundant expression in the pituitary, testis, and adrenal gland. cSPX2 was also observed to be ubiquitously expressed in chicken brain regions, with the highest expression in the hypothalamus. Its expression was significantly upregulated in the hypothalamus after 24 or 36 h of food deprivation, and the feeding behavior of chicks was obviously suppressed after peripheral injection with cSPX2. Mechanistically, further studies evidenced that cSPX2 acts as a satiety factor via upregulating cocaine and amphetamine regulated transcript (CART) and downregulating agouti-related neuropeptide (AGRP) in hypothalamus. Using a pGL4-SRE-luciferase reporter system, cSPX2 was demonstrated to effectively activate a chicken galanin II type receptor (cGALR2), a cGALR2-like receptor (cGALR2L), and a galanin III type receptor (cGALR3), with the highest binding affinity for cGALR2L. Collectively, we firstly identified that cSPX2 serves as a novel appetite monitor in chicken. Our findings will help clarify the physiological functions of SPX2 in birds as well as its functional evolution in vertebrates. Chicken is a popular domestic poultry species and its appetite regulation is closely associated with food consumption and growth performance [1]. However, feed intake is a complex process influenced by both individual and environmental variables [2]. These signals are mainly received and integrated in the hypothalamus, wherein the proopiomelanocortin (POMC), neuropeptide Y (NPY), and agouti-related peptide (AGRP) neurons respond to release their corresponding neuropeptides, and subsequently regulate feeding behavior and energy expenditure [3]. Over the last three decades, research in this field has largely improved our understanding of the appetite regulation with the ongoing identification of new appetite regulatory peptides, such as cocaine and amphetamine regulated transcript (CART) [4], orexin [5], and ghrelin [6]. Further investigation and the identification of novel food intake regulators will not only shed light on the appetite regulation mechanisms, but also provide potential strategies in dealing with abnormal food consumption in chickens [1,7]. Spexin (SPX), a novel neuropeptide composed of 14 amino acids, is highly conserved from fish to mammals [8], suggesting its essential physiological roles in vertebrates. Consistent with its wide tissue distribution, SPX has been confirmed to participate in multiple physiological functions, such as food intake [9,10,11,12,13,14], reproduction [15,16,17,18], and anxiety [19,20]. It is worth noting that SPX can serve as a satiety factor universally in mice [11,12], chickens [13,14,21], goldfish [9], zebrafish [10], and Siberian sturgeon [22], implicating that its function of food regulation is well-conserved across vertebrates. Further research shows that SPX suppresses appetite through the modulation of central orexigenic and anorexigenic signals, such as NPY, AgRP, and POMC [9,12,21,23]. SPX, as a tetradecapeptide, exerts its biological functions via activating its cell-surface receptors, such as galanin receptor 2 (GALR2) and GALR3, but not GALR1 [8,16]. Interestingly, apart from the above, two more GALR-like receptor (i.e., GALR1L and GALR2L) subtypes were identified to exist in chicken [24,25]. Our recent studies showed that chicken (c-) SPX (cSPX) had the highest affinity for GALR2L to stimulate the MAPK/ERK cascade in chickens [21]. These studies strongly evidenced that GALR2L is a key functional receptor of SPX as well. Recently, an SPX paralog, namely SPX2, has been identified in non-mammalian vertebrates, therefore the original SPX is now designated as SPX1 [8,26,27]. Compared with SPX1, little information is available regarding either the expression pattern or the physiological roles of SPX2. To the best of our knowledge, so far there are only a few studies regarding SPX2 which are all limited to fish. Similar to SPX1, zebrafish SPX2 is also able to specifically activate human, Xenopus, and zebrafish GALR2 or GALR3 [8], suggesting that the two different peptides possibly share some similarity in their physiological functions. Using whole-mount in situ RNA hybridization, SPX2 was evidenced to be restrictively expressed in the hypothalamic preoptic area of zebrafish [28]. Subsequently, using qRT-PCR, SPX2 was detected to be widely expressed in tissues including the central nervous system and peripheral tissues [26,27], with high expression in testes and the brain [27]. Intriguingly, the expression of SPX2 in hypothalamus was altered under different feeding states in zebrafish [27], implying its potential role in feeding control. Indeed, intraperitoneal injection of SPX2 inhibited food intake, while the disruption of this gene via TALENs markedly increased food consumption in zebrafish [27]. Similarly, the brain SPX2 was also reported to be regulated by food deprivation in half-smooth tongue sole [26], reinforcing the concept that SPX2 is a novel moderator of appetite. However, whether SPX2 has similar function in birds is unknown. Unlike SPX1, the functioning of SPX2 has not yet been fully elucidated, and the prior research has only focused on fish. Though SPX2 has been verified to exist in chickens, its gene structure, expression pattern, and functionality are all largely unknown. Thus, in this study, we aimed to clone the full-length cDNA of SPX2 and investigate its tissue distribution and potential functions, especially appetite regulation in chickens. According to the partial cDNA sequence of cSPX2 (GenBank accession No.: KF601213) deposited in GenBank, we cloned its full-length cDNA from an adult chicken brain using RT- and RACE-PCR. As shown in Figure 1A, the cloned cSPX2 has 1189 nucleotide bases, and its 5′-untranslated region (5′-UTR), CDS, and 3′-UTR are 293 bp, 228 bp, and 668 bp, respectively, in length. It was predicted to encode a precursor protein of 75 amino acids (aa), which could generate a 14-aa mature peptide after proteolytic processing at putative cleavage sites (R33, G48R49R50). Comparison of the cSPX2 cDNA sequence with chicken genomes (https://asia.ensembl.org/Gallus_gallus/Info/Index (accessed on 8 January 2023), cSPX2 consists of four exons separated by three introns (Figure 1B). Sequence alignment revealed that the precursors of SPX2 shares high sequence similarity in birds, but comparatively lower identities among different other vertebrate classes, with an obvious sequence variation noted at its NH2-terminal and COOH-terminal region (Figure 2). It is noteworthy that cSPX2 mature peptide displays a high degree of amino acid sequence identity to that of ring-necked pheasant (100%), rock ptarmigan (100%), greater sage-grouse (100%), green anole (92.86%), Xenopus laevis (78.57%), coelacanth (92.86%), and zebrafish (78.57%). Despite the fact that the sequence of cSPX2 mature peptide is four amino acids different from cSPX1, they are highly conserved (64.29%). To confirm whether the cloned cSPX2 is orthologous to the gene identified in other vertebrate species, we performed synteny analysis by searching its neighboring genes in the genomic regions of chicken and other vertebrate species. As shown in Figure 3, SPX2 is located on a syntenic region conserved in chicken, green anole, Xenopus laevis, coelacanth, and zebrafish, suggesting the cloned gene is an ortholog of SPX2. In addition, SPX2 and GAL are on the same chromosome in these species. However, SPX2 is absent in mammals, such as humans and mice. To explore the physiological functions of SPX2 in chickens, we detected its tissue distribution in adult chickens using qRT-PCR. As shown in Figure 4, cSPX2 was widely expressed in all tissues except gizzard. It was abundantly expressed in the anterior pituitary, testis, and adrenal gland, and moderately expressed in the jejunum, ileum, and pancreas. In the central nervous system (CNS), cSPX2 was found to be ubiquitously expressed in the spinal cord and all the brain regions examined, with the highest expression in the hypothalamus. The mature peptide of cSPX2 shares high sequence similarity with cSPX1, which can act as a satiety factor in chicken [14,21]. We thus speculated that cSPX2 also has the anorexigenic properties. In order to verify this hypothesis, we detected its transcriptional response to fasting in the hypothalami of two-week-old chicks. As shown in Figure 5A, 24- or 36-h fasting could obviously elevate (p < 0.01) the levels of cSPX2 mRNA in the chick hypothalamus. Then, the feed consumption was measured after cSPX2 injection. The cumulative feed intake of chicks did not alter (p > 0.05) by three different doses of cSPX2 after 6 h treatment, but it was effectively inhibited (p < 0.05) at 12 h post-injection (Figure 5B). Moreover, after 24 h post-injection, a moderate (50 ng/g BW) and a high (100 ng/g BW) dosage of cSPX2 could still markedly decrease (p < 0.05) the food intake in chicks. To elucidate the mechanism of cSPX2 in feeding regulation, we monitored the expression of appetite-regulating factors in the hypothalamus. As shown in Figure 6A, cSPX2 could visibly inhibit (p < 0.05) AGRP mRNA levels at 6 h post-injection. Oppositely, the expression of a pro-melanin-concentrating hormone (PMCH) was stimulated (p < 0.05) by cSPX2 administration. CART mRNA levels exhibited downward tendencies, and no significant difference was examined after 6 h injection with cSPX2. Conversely, transcripts of CART in hypothalami of three-week-old chicks were obviously elevated (p < 0.05) after cSPX2 administration for 24 h, and the expressions of NPY, AGRP, POMC, and PMCH were not regulated (p > 0.05) by cSPX2 (Figure 6B). To investigate whether cSPX2 is a natural ligand for galanin receptors in chickens, each receptor was transfected into HEK293 cells, and subjected to peptide treatment. Receptor activation was examined by pGL4-SRE-luciferase reporter system. As shown in Figure 7, cSPX2 could not efficiently stimulate luciferase activity in HEK293 cell expressing cGALR1 (accession No.: NP_001121534) and cGALR1L (accession No.: NP_001121533). On the contrary, cGALR2 (accession No.: ACB22016), cGALR2L (accession No.: ACD99708) and cGALR3 (accession No.: ACE60644) could be initiated by cSPX2 in a dose-dependent manner, and the EC50 values are 218 nM, 53 nM, and 110 nM, respectively. Among them, cSPX2 exhibited the highest binding ability with cGALR2L. As a paralog of SPX1, SPX2 has been discovered in non-mammalian species [8,26,27], but little is known about its physiological functions. In this study, using chicken as an animal model, we firstly cloned the full-length cDNA encoding SPX2. Synteny analysis revealed that it is orthologous to the SPX2 of anole lizards, Xenopus, coelacanths, and zebrafish. Concurring with the previous report that SPX2 is found in a variety of vertebrate species but not in mammals [8,26,27]. We found that cSPX2 and cGAL are closely localized on the same chromosome and possibly coevolutionary in vertebrates, as reported previously [8]. Similar to SPX1, cSPX2 can generate a 14-aa mature peptide flanked by cleavage sites, and the mature peptide is highly conserved, suggesting SPX2 may play similar important physiological roles as SPX1 in non-mammalian vertebrates. Tissue distribution analysis revealed that cSPX2 mRNA was widely detected in various tissues of a chicken, which is similar with the tissue expression profiles reported in both tongue sole [26] and zebrafish [27]. Remarkably, we found that in chickens the pituitary had the highest expression of cSPX2. As a master hormone secretion center, the pituitary gland controls metabolism, growth, sexual maturation, and reproduction as well as many other vital physiological functions and processes [29]. Therefore, it is likely that the pituitary will operate as a key mediator for SPX2 to regulate various physiological processes in non-mammalian vertebrates. Indeed, it was reported that an intraperitoneal injection of SPX2 could largely alter the expression of the gonadotropin α subunit, the luteinizing hormone β (LHβ), and the follicle-stimulating hormone β subunit (FSHβ) in the pituitary in half-smooth tongue sole [30], and that the knockout of SPX2 could greatly promote body growth in zebrafish by enhancing the expression of pituitary growth hormone (GH) [27]. High amounts of cSPX2 mRNA were also observed in chicken testes and adrenal glands, suggesting it may also directly regulate the functions of these organs, such as the sexual/adrenal steroid secretion, spermatogenesis, etc. Of note, cSPX2 was also moderate in various brain regions, with the highest expression in the hypothalamus, suggesting that SPX2 may be involved in the regulation of food intake in chickens. Taken together, SPX2 is widely distributed in chickens and potentially exerts pleiotropic functions. To better understand its pleiotropic functions in each individually expressed tissue of chickens, more extensive and in-depth investigations are required. To explore the putative roles of cSPX2 in feeding control in chickens, we firstly detected its hypothalamic mRNA expression in response to food deprivation. Consequently, fasting remarkably increased cSPX2 expression in the hypothalamus, which is analogous to findings reported in half-smooth tongue sole [26]. Conversely, in zebrafish SPX2 mRNA was downregulated by fasting [27]. Despite discrepancies, changes in SPX2 expression under different feeding status conditions across species suggest its potential role in appetite regulation. To further validate its putative roles in feeding control, we performed in vivo SPX administration in chicks. Consequently, SPX2 administration greatly decreased the food intake of chicks, and similar findings were also reported in zebrafish [27]. Fish with SPX2 knockout also exhibited higher food consumption than WT fish [27]. All these results strongly suggest that, like SPX1, SPX2 acts as a novel appetite regulator in chickens as well as some other non-mammalian vertebrates. To elucidate the underpinning mechanism of cSPX2 in appetite regulation, we further detected its regulatory influence on the expression of key feeding control factors in the hypothalamus of chicks. Following intravenous cSPX2 injection, AGRP, a well-known orexigenic gene, was visibly downregulated at 6 h post injection, whereas the anorexigenic factor, CART, was notably upregulated at 24 h post injection. In parallel, the cumulative food consumption of chicks were substantially reduced onward from 12 h post injection. Consistently, both in vivo SPX2 injection and SPX2 knockout evidenced that SPX2 controls food intake in zebrafish by regulating hypothalamic AGRP and CART expression as well [27]. Unexpectedly, the expression of PMCH, a potential orexigenic factor [31], was increased after cSPX2 treatment for 6 h, similar to what was seen with SPX1 in goldfish [8]. Thus, it appeared that SPXs (both SPX1 and SPX2) could exert an early and quick action on the expression of PMCH in the hypothalamus. However, this early and quick action of SPX2 on PMCH expression cannot essentially change the pattern of chicks’ decreased food consumption. SPX2-induced changes of AGRP and CART were still dominant over PMCH to control food intake. Therefore, in chickens, SPX2 acts as a satiety factor to inhibit food intake mainly by downregulating AGRP and upregulating CART in the hypothalamus. SPX2 exerts its physiological functions by activating its receptors. Previous studies indicated that SPX2 could elevate SRE-luc activity in cells expressing GALR2 and GALR3, but not in cells expressing GALR1 [8,16]. A little surprisingly, in the present study we found cSPX2 could not only activate cGALR2 and cGALR but also cGALR2L. Among them, cSPX2 exhibited the highest binding ability with cGALR2L. Accordingly, it is likely that cSPX2 exerts its feed regulation mainly through binding and activating cGALR2L. Interestingly, cSPX1 [21], but not cSPX2 could inhibit the food intake of chicks after 6 h post-injection at the same treatment dosage, suggesting that cSPX2 is potentially not as effective as cSPX1 in inhibiting the appetite of chicks. This is possibly attributed to the differential potency of SPX1 and SPX2 in activating galanin receptors. In both chickens [21] and humans [8] it has been evidenced that SPX1 has a higher potential to activate GALR2 and GALR3 than SPX2. In summary, we cloned the full-length cDNA of chicken SPX2 and investigated its expression patterns and functionality. cSPX2 can generate a conserved mature peptide with 14-aa, which can activate GALR2, GALRL2L, and GALR3. Tissue distribution analyses show that cSPX2 is widely expressed in chickens, with abundant expression in the pituitary, testis, and adrenal glands, and its expression in hypothalamus was upregulated by fasting. In vivo administration of cSPX2 could effectively inhibit the feed intake of chickens, by modifying the expression of hypothalamic AGRP and CART. Collectively, our results firstly evidenced that cSPX2 serves as a novel appetite monitor in chickens, which will facilitate the understanding of the physiological functions of SPX2 in birds as well as its functional evolution in vertebrates. All chemicals were purchased from Sigma-Aldrich (Shanghai, China) unless stated otherwise. Chicken SPX2 mature peptide (cSPX2, NWGPQSILYLKGRY-NH2) with amidated C-terminus was synthesized by GL Biochem Ltd. (Shanghai, China), and its structure was verified by mass spectrometry. Dulbecco’s Modified Eagle Medium (DMEM), fetal bovine serum (FBS), and penicillin-streptomycin were all obtained from Hyclone (Cytiva, Shanghai, China). JetPRIME® transfection reagent was purchased from Polyplus (Illkirch, France). All primers used in this study were synthesized by Chengdu Tsingke Biotechnology and listed in Supplementary Table S1. Adult chickens (3 males and 3 females, 31-week-old) or chicks (Lohmann layer) used in the present study were obtained from Muxing company in Sichuan, China. Chickens were sacrificed to collect various tissues including different brain regions. All samples were snap-frozen in liquid nitrogen and then stored at −80 °C before RNA extraction. All procedures involving animals were approved by the Ethics Committee of Sichuan Agricultural University. Total RNA was isolated from various chicken tissues with RNAzol (Molecular Research Center, Cincinnati, OH, USA) according to the manufacturer’s instructions, and then 1 μg of total RNA was used as template to reverse transcription by using the PrimeScript® RT reagent kit with gDNA eraser (Takara, Dalian, China). The generated cDNA samples were diluted and then used as template for subsequent PCR or quantitative real-time PCR (qRT-PCR) for detecting the expressions of target genes. According to the predicted partial coding sequence (CDS) of cSPX2 (GenBank No.: KF601213), the gene-specific primers were designed to amplify the 5′-cDNA and 3′-cDNA ends by using SMART-RACE cDNA amplification kit (Clontech, Palo Alto, CA, USA). The amplification products were detected by agarose gel electrophoresis, and then ligated into pTA2 vector (Toyobo, Shanghai, China) for sequencing. The potency of cSPX2 on activating chicken galanin receptors was evaluated by pGL4-SRE-Luciferase system according to our previously established methods [21]. Using JetPRIME® transfection reagent, HEK293 cells were, respectively, transfected by five galanin receptor subtypes, including GALR1, GALR1L, GALR2, GALR2L, and GALR3, and then were treated with different doses of cSPX2 for an additional 6 h. Whereafter, 1× Passive lysis buffer (Promega, Beingjing, China) was added into cells and the luciferase activity was determined with the luciferase assay kit (Promega). According to our previously established method [21], qRT-PCR was conducted on the CFX96 Real-time PCR Detection System (Bio-Rad, Hercules, CA, USA), and PCR procedures consisted of 40 cycles of 94 °C for 20 s, annealing for 15 s, 30 s extension at 72 °C. To assess the specificity of PCR amplification, melting curve analysis was performed at the end of the reaction. Finally, the mRNA levels of target genes were normalized against β-actin, calculated with the 2−ΔΔCT method, and then expressed as the fold change relative to the chosen tissue or control. Primer sequences of target and reference genes are shown in Supplementary Table S1. Given that cSPX1 plays a significant role in appetite regulation, its paralog, cSPX2, may perform a similar physiological function. Thus, starvation experiment was conducted in this study. Two-week-old male chicks were divided equally into three groups (n = 24): one control group and two experimental groups. Chicks in control group were fed at regular times, and chicks in the two experimental groups were fasted for 24 and 48 h, respectively. After fasting, chicks were sacrificed and hypothalami were collected for determining cSPX2 expression response to fasting. To further investigate the effect of cSPX2 on feed intake, similar-weight chicks (~180 g/chick) were randomly assigned to four groups (n ≥ 8), and then were deprived of food for 12 h. Then, chicks in control group were intravenously injected with PBS, and chicks in the three experimental groups were injected with 10 ng/g, 50 ng/g and 100 ng/g body weight of cSPX2, respectively. After that, chicks were re-fed with the pre-weighed diet, and the residual diets were collected and weighed at 6 h, 12 h, and 24 h post-injection, respectively. Food consumption was counted by the total input of food minus the leftover. Three-week-old male chicks were randomly divided into two groups (n ≥ 4), and then were intravenously injected with PBS (control) or cSPX2 (50 ng/g body weight). After 6 h of administration, the chick hypothalami were collected, and the mRNA expression levels of neuropeptide Y (NPY), agouti gene-related protein (AGRP), cocaine- and amphetamine-regulated transcript (CART), proopiomelanocortin (POMC), and pro-melanin-concentrating hormone (PMCH) were detected by qRT-PCR. We also evaluated the expression of the above appetite-related genes in the chick hypothalamus after 24 h injection with cSPX2 by using the same treatment procedure. All statistical analysis was performed with GraphPad Prism 9 software (La Jolla, CA, USA). The two-tailed Student’s t test was conducted to compare two groups. For comparison between more than two groups, a one-way ANOVA followed by Turkey’s test was used. Data were expressed as means ± SEM, and statistical significance was set at p < 0.05.

PMC10003262

Kai Wang,Ling Qin,Junhan Cao,Liping Zhang,Ming Liu,Changfeng Qu,Jinlai Miao

κ-Selenocarrageenan Oligosaccharides Prepared by Deep-Sea Enzyme Alleviate Inflammatory Responses and Modulate Gut Microbiota in Ulcerative Colitis Mice

28-02-2023

heterologous expression,enzymatic preparation,κ-selenocarrageenan oligosaccharides,structural characterization,ulcerative colitis,gut microbiota

κ-Selenocarrageenan (KSC) is an organic selenium (Se) polysaccharide. There has been no report of an enzyme that can degrade κ-selenocarrageenan to κ-selenocarrageenan oligosaccharides (KSCOs). This study explored an enzyme, κ-selenocarrageenase (SeCar), from deep-sea bacteria and produced heterologously in Escherichia coli, which degraded KSC to KSCOs. Chemical and spectroscopic analyses demonstrated that purified KSCOs in hydrolysates were composed mainly of selenium-galactobiose. Organic selenium foods through dietary supplementation could help regulate inflammatory bowel diseases (IBD). This study discussed the effects of KSCOs on dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in C57BL/6 mice. The results showed that KSCOs alleviated the symptoms of UC and suppressed colonic inflammation by reducing the activity of myeloperoxidase (MPO) and regulating the unbalanced secretion of inflammatory cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-6 and IL-10). Furthermore, KSCOs treatment regulated the composition of gut microbiota, enriched the genera Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus and inhibited Dubosiella, Turicibacter and Romboutsia. These findings proved that KSCOs obtained by enzymatic degradation could be utilized to prevent or treat UC.

κ-Selenocarrageenan Oligosaccharides Prepared by Deep-Sea Enzyme Alleviate Inflammatory Responses and Modulate Gut Microbiota in Ulcerative Colitis Mice κ-Selenocarrageenan (KSC) is an organic selenium (Se) polysaccharide. There has been no report of an enzyme that can degrade κ-selenocarrageenan to κ-selenocarrageenan oligosaccharides (KSCOs). This study explored an enzyme, κ-selenocarrageenase (SeCar), from deep-sea bacteria and produced heterologously in Escherichia coli, which degraded KSC to KSCOs. Chemical and spectroscopic analyses demonstrated that purified KSCOs in hydrolysates were composed mainly of selenium-galactobiose. Organic selenium foods through dietary supplementation could help regulate inflammatory bowel diseases (IBD). This study discussed the effects of KSCOs on dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in C57BL/6 mice. The results showed that KSCOs alleviated the symptoms of UC and suppressed colonic inflammation by reducing the activity of myeloperoxidase (MPO) and regulating the unbalanced secretion of inflammatory cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-6 and IL-10). Furthermore, KSCOs treatment regulated the composition of gut microbiota, enriched the genera Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus and inhibited Dubosiella, Turicibacter and Romboutsia. These findings proved that KSCOs obtained by enzymatic degradation could be utilized to prevent or treat UC. Carrageenan is a sulfated linear polysaccharide extracted from the cell wall of red algae. Based on the difference in the number of sulfate groups and the presence of 3,6-anhydro-α-D-galactopyranosyl (3,6-AG), carrageenans are further classified into κ-, ι- and λ-carrageenans [1]. κ-Carrageenan is alternately composed of 4-linked-α-D-3,6-anhydrogalactose (DA) and 3-linked-4-O-sulfated-β-D-galactopyranose (G4S), which has been recognized as safe by the U.S. Food and Drug Administration [2,3]. However, its application is limited due to poor solubility and low bioavailability [4]. κ-Carrageenan oligosaccharides obtained by κ-carrageenan degradation can greatly improve these properties. Moreover, κ-carrageenan oligosaccharides exhibited antioxidant [5], anticoagulation [6] and antitumor effects [7]. It is well known that Se is an indispensable trace element for human health and can only be obtained from food. KSC is a kind of Se polysaccharide made from natural κ-carrageenan, in which Se partially replaces sulfur (S) [8]. It is reported that KSC had an immunomodulatory function and inhibited tumor growth in H22 tumor-bearing mice [9]. Theoretically, low molecular weight KSCOs hydrolyzed by KSC possess remarkable bioactivity. At present, KSCOs were created chemically using sodium selenite and κ-carrageenan oligosaccharides, but the unstable structure of products makes this process unsuitable for large production. In contrast, enzymatic hydrolysis yields products with a controlled structure and no contamination, which is now the preferred method for oligosaccharides production. However, the enzyme hydrolyzing KSC to KSCOs has rarely been researched. In the previous study, we described a potential κ-selenocarrageenase isolated from the cold seep in the South China Sea [8]. Here, this κ-selenocarrageenase was expressed in Escherichia coli and its degradation activity was demonstrated. Therefore, a novel and easy strategy for the utilization of KSC to produce functional KSCOs was provided. UC is a chronic and recurrent inflammation of the intestine with a high incidence in Western countries [10,11]. The pathogenesis of UC is thought to be related to genetic susceptibility, immunity, environment and intestinal mucosal barrier loss [12]. The main clinical symptoms of UC include abdominal pain, diarrhea, bloody mucus and purulent stools [13,14]. It is worth noting that UC increases the risk of colorectal cancer, the third most common malignant tumor in the world [15]. Nevertheless, current drugs used to treat UC, such as aminosalicylate and mesalazine, tend to decline in response to treatment over time and lead to disease complications [11]. In addition, such drugs may induce adverse reactions, such as dilated cardiomyopathy and severe heart failure [16]. Therefore, it is urgent to develop new therapeutic drugs. In fact, nutrition plays a crucial role in preventing IBD [17]. Nutritional deficiencies, including micronutrients, are common in patients with IBD [18,19]. It has been demonstrated that dietary Se supplementation enhanced intestinal antioxidant function and relieved inflammation [20]. On the other hand, previous studies have shown that carrageenan oligosaccharides had potent effects on inhibiting the release of inflammatory cytokines [21,22,23]. However, the beneficial effects of KSCOs remain unclear for IBDs, such as UC. In this work, we heterologously expressed and characterized a κ-selenocarrageenase from a marine bacterium named Bacillus sp. N1-1. The structure of KSCOs obtained from κ-selenocarrageenase hydrolysis of KSC was analyzed. KSCOs possess the activity of both selenium and κ-carrageenan oligosaccharides. Thus, we speculated that KSCOs may have effects on the treatment of UC. DSS is a polymer of anhydroglucose that induces UC when introduced through drinking water in rodents, such as guinea pigs, rabbits and mice [24,25]. This chemical compound is now widely used in basic research related to colitis. In this study, we aimed to explore the effects of KSCOs on DSS-induced UC in mice and investigated the underlying mechanism of action. As our previous study mentioned, a deep-sea bacterium Bacillus sp. N1-1 has been preliminarily demonstrated to degrade κ-selenocarrageenan [8]. The SeCar gene (GenBank accession number: MW366920) from N1-1 genome was predicted as a candidate κ-selenocarrageenase as it was noted to be coding a putative glycoside hydrolase 16 (GH 16) protein. The open reading frame (ORF) of this gene consisted of 2184 bp and encoded 728 deduced amino acid residues, the first 25 amino acid residues of which were identified as a signal peptide sequence. The theoretical molecular weight of the mature protein was 79.51 kDa and the predicted isoelectric point was 4.40. It was predicted to be a stable hydrophilic protein with mean hydrophilicity (gravy) of −0.735, fat coefficient of 66.46 and instability index of 33.46. According to the conserved domain analysis (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 16 August 2020), the complete sequence of SeCar is mainly composed of four domains, of which the amino acid residues Arg153-Lys353 belongs to the GH16 family domain. GH16 family is concluded as a polyspecific glycoside hydrolase family and contains different enzymes, including κ-carrageenase, β-agarase, β-porphyranase, licheninase and laminarinase [26,27]. Multiple sequence alignment was carried out between SeCar and other reported GH 16 family κ-carrageenases (Figure S1). On the basis of alignment results, SeCar contained the conserved region ExDxxE, which is responsible for the double displacement mechanism in κ-carrageenase catalysis [28,29]. The above bioinformatics analysis elucidated the characteristics of SeCar as a κ-carrageenase. Additionally, the BLASTP analysis showed that SeCar shared the highest sequence identity of 28.12% with the κ-carrageenase of Pseudoalteromonas tetraodonis JAM-K142 among all characterized proteins [30]. For better characterization, the SeCar gene was cloned and expressed successfully in Escherichia coli. It was shown that the purified κ-selenocarrageenase was analyzed by SDS-PAGE in Figure S2. After the gene fused with (His)6-tag was expressed, the molecular weight of the purified recombinant protein was approximately 80 kDa, which was larger than the theoretical molecular weight (79.51 kDa). The activity of purified recombinant SeCar was 133 U/mg, which was much higher than that of the wild enzyme (18.58 U/mg). Figure 1A shows that the optimal temperature of purified SeCar was 40 °C. In addition, its activity remained stable at 20 °C, and 80% of its initial activity was maintained at 30 °C for up to 2 h (Figure 1B). The thermal stability of SeCar facilitates its storage and biotransformation in industrial production. The effects of various metal ions and chemical reagents on SeCar activity are shown in Figure 1C. K+ and Mn2+ slightly stimulated the enzyme activity. Cu2+, Fe2+ and Fe3+ inhibited the enzyme activity, among which Cu2+ had the greatest inhibitory effect, causing 80% of the enzyme activity impaired. The kinetic parameters of purified SeCar were determined using κ-selenocarrageenan as the substrate. The Vmax and Km values were 12.0048 mg/(mL·min) and 0.2389 mg/mL, respectively (Figure 1D), indicating that the κ-selenocarrageenase SeCar showed high affinity to the κ-selenocarrageenan. According to the high-performance gel permeation chromatography (HPGPC) spectra (Figure S3A) and the detailed values (Table S1), the KSCOs were mainly distributed below 1500 Da, among which 37.14% were 1379.49 Da and 31.69% were 816.82 Da. To clarify the structure of KSCOs, MS analysis at negative ESI mode was conducted. The MS image of KSCOs (Figure S3B) revealed peaks at m/z 437 and m/z 546, corresponding to [(DA-G4Se)]− and [(DASe-G4Se)]−, respectively. The over selenated disaccharide units of DASe-G4Se are attributed to the mixing of ι-carrageenan in commercial κ-carrageenan [31,32]. The disaccharide unit in ι-carrageenan contains two sulfate groups, which might be replaced by selenate. Combined with the result of thin layer chromatography (TLC) analysis (Figure S4), we speculated that the peaks at m/z 341.1, m/z 665.2 and m/z 989 were representative of (DA-G4)−, [(DA-G4)2]− and [(DA-G4)3]−, respectively, without carrying the selenate group. This deselenylation was possibly caused by the high cone voltage in the mass spectrometer [31,33]. The FTIR spectra analysis of KSCOs was shown in Figure 2. The intense peak at 3283 cm−1 was ascribed to the stretching vibration of O-H. The weak stretching band near 2925 cm−1 was ascribed to the stretching vibration of C-H. The peak at approximately 1598 cm−1 was associated with the stretching vibration of C=O. In addition to characteristic absorption peaks of polysaccharides, the peak near 1250 cm−1 was ascribed to the stretching vibration of S=O, indicating that the sulfate groups in κ-selenocarrageenan were not completely replaced. However, due to the selenylation modification, the absorption peaks near 1375 cm−1 and 762 cm−1 were attributed to the Se=O asymmetric stretching and C–O–Se symmetric vibrations, respectively [34]. Additionally, a strong absorption near 1024 cm−1 was assigned to the stretching vibration of the C–O–C glycosidic bond, indicating a pyranose unit in the carrageenan basic structure [35]. In the 1H NMR spectrum of the KSCOs (Figure 3A), there were signals of α and β configurations at the reducing end of G4S. The signal at δ 5.39 ppm was attributed to G4S-H-1α, while the chemical shift signal of G4S-H-1β appeared at δ 4.67 ppm [36]. Since selenylation occurred at C-4, the chemical shift of H-4 after selenite moved to the low field near δ 4.86 ppm. However, due to the overlap with the hydrogen signal in the solvent HOD, the chemical shift was not obvious. It has been reported that the signal δ 5.25 ppm was attributed to the H-1 of DA [37]. In this study, DA-H-3 and DA-H-5 were located in the region of δ 4.67 ppm and δ 4.17 ppm, respectively, due to the dehydration reaction at C-3 and C-6 of DA. As shown in Figure 3B, there were four anomeric carbon signals, which were 101.6, 101.3, 97.4 and 93.5 ppm, respectively. κ-Carrageenan is an alternating galactan of 1,3-linked β-D-galactopyranose 4-O-sulfate and 1,4-linked 3,6 anhydro-α-D-galactopyranose [2]. The anomeric carbon of β-D galactose was more than 100.0 ppm, while the terminal carbon of α-D galactose was less than 100.0 ppm. Therefore, the signals at 101.6 and 101.3 ppm were attributed to →3)-β-G4s-(1→ and →3)-β-G4Se-(1→ anomeric carbon. At 97.4 ppm, it was →4)-α-DA (1→ anomeric carbon signal; 93.5 ppm was →3)-G4Srα reducing anomeric carbon signal. The high field 62.1 ppm was →3)-β -G4s -(1→ C-6 signal. All chemical shifts were summarized in Table 1 and Table 2. The 1H and 13C spectra of KSCOs were analyzed, and it was found that selenylation had no significant influence on the basic structure of κ-carrageenan, which was consistent with the previous report [38]. Since no substitution of the C-6 position was found in the DEPT 135° spectrum, we speculated that selenylation did not occur in position C-6 of →4)-α-DA-(1→. Therefore, combining ESI-MS, FTIR and NMR data, the selenium oligosaccharides in KSCOs were mainly composed of selenium-galactobioses and the predicted structure was shown in Figure S3C. The degree of UC in mice was assessed through body weight, disease activity index (DAI) and colon length. There was a significant decrease in the body weight of the DSS mice in this study (p < 0.001) (Figure 4A). KSCOs exhibited significant improvement in body weight loss (p < 0.001). Additionally, as shown in Figure 4B, mice treated with KSCOs exhibited an improved health status compared to mice with only DSS according to DAI. Furthermore, compared with DSS only, KSCOs treatment reduced the shortening of the colon significantly in mice (p < 0.01) (Figure 4C,D). According to the morphological examination (Figure 5A), colon tissues of the DSS group showed obvious erosion, goblet cell disappearance and inflammatory cell infiltration compared with the intact inner wall of the normal group, while KSCOs treatment alleviated these pathological changes of colonic tissue in colitis. The above phenomenon revealed that KSCOs relieved the systemic (weight loss and DAI) and local (CL shortened and HDS) symptoms of UC. As shown in Figure 5B, MPO activity was significantly activated in the colon tissue of the DSS group (p < 0.001), indicating an excessive inflammatory response. However, KSCOs reduced MPO activity dramatically (p < 0.001) compared with the DSS group. In addition, we measured the contents of proinflammatory cytokines including TNF-α and IL-6 and the anti-inflammatory cytokine IL-10 in serum. As shown in Figure 5C,D, compared to the normal group, DSS exposure increased the contents of TNF-α (p < 0.01) and IL-6 (p < 0.001) significantly, while it reduced the content of IL-10 (p < 0.001). A total of 713,927 sequences were obtained from 18 samples among the normal group, DSS group, and KSCOs group. Richness (Ace index) and diversity (Shannon and Simpson indices) of microbial communities were shown by alpha-diversity analysis (Figure S5A–C). The Ace, Shannon, and Simpson indices in the DSS group all displayed a decline when compared to the normal group. Although the Ace, Shannon, and Simpson indices did not significantly increase following the administration of KSCOs in comparison to the DSS group, the increase in gut microbial richness and diversity was partially explained. The rarefaction curves tended to be saturated platforms (Figure S5D), which indicated that the majority of the microbial diversity had been collected and the sequencing coverage was adequate. As shown in Figure 6A, gut microbiota of mice in the three groups were mainly composed of Firmicutes and Bacteroidota at the phylum level. However, administration of KSCOs decreased the relative abundance of Firmicutes while increasing the relative abundance of Bacteroidota in DSS-induced colitis mice. In general, compared with the normal group, DSS significantly increased the ratio of Firmicutes to Bacteroidota (F/B) (p < 0.05), while this phenomenon was significantly reversed by KSCOs (p < 0.05) (Figure 6C). To further assess the predominant bacterial communities in the intestine across the three groups, linear discriminant analysis (LDA) and effect size (LefSe) was carried out. The generated cladogram reflected different gut microbiota compositions among mice from all groups (Figure 7A). The LDA discriminant histogram counted the microbial taxa with significant effects in multiple groups. Greater relative species abundance is represented by higher LDA scores. Via LDA scores, the findings revealed that Bifidobacterium, Lachnospirace-ae NK4A136 group, and Ruminococcus were prevalent in the KSCOs group while Dubosiella, Turicibacter and Romboutsia were prominent in the DSS group (Figure 7B). Specific differences between groups were evaluated at the genus level to further illustrate how KSCOs treatment affected the composition of gut microbiota (Figure 6B). At the genus level, compared to DSS group, KSCOs administration significantly enhanced the relative abundance of Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus (Figure 7D–F). Additionally, compared to the normal group, the relative abundance of Dubosiella (p < 0.001), Turicibacter (p < 0.01) and Romboutsia (p < 0.01) increased significantly in the DSS group, while this increase was inhibited by KSCOs administration (Figure 7G–I). Acetate, propionate, butyrate and total SCFA concentrations were all considerably lower after receiving DSS without treatment, as shown in Figure 8 (p < 0.001, p < 0.05, p < 0.01 and p < 0.001, respectively). However, compared with the DSS group, KSCOs increased the concentration of butyrate significantly (p < 0.05) and tended to promote the biosynthesis of acetate and propionate. KSC is a marine selenium polysaccharide synthesized by selenization modification of κ-carrageenan, which has been included in the national safety standard for the use of the food nutrition fortification standard [39]. However, KSC has a high molecular weight and low bioavailability. The chemical or physical degradation process of KSC is uncontrollable, and the structure of degradation products is unstable. To date, there have been few studies on the hydrolysis of KSC by κ-selenocarrageenanase. In this study, we prepared KSCOs from a κ-selenocarrageenanase named SeCar. The novelty of the SeCar sequence suggests that it may exhibit properties distinct from other κ-carrageenases. It is worth noting that this is the first demonstration of KSC degradation by a κ-carrageenase. There are multiple factors contributing to the pathogenesis of IBD, including the influence of micronutrients [40]. Summarizing recent reviews, Se exhibited an important role in the pathogenesis of IBD and Se deficiency was common in IBD patients [20,41]. Hence, the essential trace element Se has been drawn more attention for IBD prevention and treatment. Compared with inorganic Se, organic Se possesses lower toxicity and higher bioavailability. Here, we investigated the effects of KSCOs on DSS-induced colitis. According to the acceptable upper limit of adult Se intake (400 μg/d) recommended by WHO (2004) and Chinese Nutrition Society (2013), the doses of KSCOs were designed as 1.6, 3.2 and 6.4 mg/kg, which were equivalent to 25.5, 51 and 102 μg/kg of oral Se in mice, respectively [42]. The results showed that KSCOs relieved the systemic (weight loss and DAI) and local (CL shortened and HDS) symptoms of UC. MPO is a proinflammatory oxidase secreted by neutrophils and macrophages, which can destroy intestinal mucosal cells and cause inflammatory responses; therefore, it usually shows high activity in UC patients [43]. Additionally, after the occurrence of colitis, proinflammatory cytokines, such as TNF-α, IL-6 and IL-1β, are secreted and accumulated in large quantities due to the excessive activation of immune cells. These cytokines directly caused mucosal and tissue damage, triggering disease-specific inflammatory responses in colitis [44]. Regulating the secretion of these cytokines is extremely important for alleviating the inflammatory responses in colitis. Therefore, KSCOs could reduce inflammatory responses in UC mice via ameliorating neutrophil infiltration and regulating the level of inflammatory cytokines (TNF-α, IL-6 and IL-10). The gut microbiota is considered as an important factor influencing the occurrence and severity of DSS induced colitis [45]. The positive effects of dietary Se supplementation on intestinal inflammation have been well demonstrated [40,46]. Moreover, as previously reported, at least part of the mechanism was due to Se altering the gut microbiota rather than directly affecting the gut [47]. To identify whether KSCOs regulates gut microbiota, 16S rRNA sequencing in fecal bacteria DNA was conducted and the high dose (6.4 mg/kg) group of KSCOs was selected to be sequenced. In this research, it can be found that dietary selenium KSCOs regulated the diversity and composition of gut microbiota in the DSS-induced mice, consistent with previous reports [48,49]. Specifically, KSCOs showed a function of reducing the ratio of Firmicutes to Bacteroidota (F/B). F/B is commonly denoted as the degree of dysbiosis in IBD [50,51], and a high proportion of Bacteroidota is associated with the resistance to inflammation [52]. Thus, it can be indicated that KSCOs could restore intestinal homeostasis by regulating the abundance of Firmicutes and Bacteroidota. At the genus level, KSCOs enhanced the abundance of Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus. Bifidobacterium is recognized as a probiotic, promoting intestinal health in the following aspects. In the intestine, Bifidobacterium can synthesize exopolysaccharides as the fermentation substrate of microbiota, which is beneficial to intestinal health [53,54]. Additionally, Bifidobacterium can enhance intestinal epithelial barrier function through metabolites and inhibit the inflammatory responses [55,56]. Furthermore, Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus were reported to promote the production of SCFAs, which were capable of maintaining epithelial health and immune balance of the intestine [57,58,59]. KSCOs administration inhibited the growth of harmful bacteria, such as Dubosiella, Turicibacter and Romboutsia. The trends in the relative abundance of Dubosiella between groups were consistent with previous reports about UC [60,61,62]. However, more research is needed to determine the effect of Dubosiella on colitis. Increases in both Turicibacter and Romboutsia are associated with the development of colitis. It has been reported that Turicibacter with high abundance aggravated intestinal damage and led to serious complications [63]. Moreover, Romboutsia is considered as a pathogen, and its abundance is increased in many diseases, such as neurodevelopmental disorders [64], irritable bowel syndrome [65] and gastric cancer [66]. It can be found that the abundance of Romboutsia was increased in the intestine of DSS-induced colitis mice compared with that of healthy mice in this study, consistent with views in relevant studies [67,68,69]. SCFA has also been reported to ameliorate colitis through suppressing proinflammatory cytokines, such as TNF-α and IL-6 [70,71]. The reason for the higher SCFA content in the KSCOs group compared with the DSS group might be due to enriched Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus. Moreover, a previous report found that organic sources of Se promoted the biosynthesis of propionate and butyrate [72]. There have been many studies on the remodeling of gut microbiota by different Se sources, such as selenium-enriched yeast [72], selenium-enriched probiotics [49] and selenium-containing tea polysaccharides [73]. The mechanism, however, is complex and few studies have clarified it. In this study, we described the effects of KSCOs on the gut microbiota in mice for the first time, but the role of Se in gut microbiota needs to be further explored in subsequent research. Taken together, KSCOs might alter the composition and metabolites of gut microbiota to relieve DSS-induced colitis. The κ-selenocarrageenase (SeCar) gene (Locus_tag: N1.1_GM000361) was obtained from the whole genome of Bacillus sp. N1-1 (GenBank accession number: CP046564). κ-Selenocarrageenan was purchased from Qingdao Pengyang Biological Engineering Co., Ltd., Qingdao, China. Bioinformatics prediction and analysis of the amino acid sequence were carried out online. Physicochemical properties of amino acids were predicted using ExPASyProtparam (https://web.expasy.org/protparam/, accessed on 16 August 2020). The hydrophobicity of protein was predicted by ExPASyScale (https://web.expasy.org/protscale/, accessed on 16 August 2020). The prediction of signal peptide sequence was used by SignalP 5.0 Server (http://www.cbs.dtu.dk/services/SignalP/, accessed on 16 August 2020). Alignments of the amino acid sequences and other κ-carrageenases in NCBI database were performed using ClustalX (Version 1.8). Genomic DNA of Bacillus sp. N1-1 was extracted using the FastPure Bacteria DNA Isolation Mini Kit (Vazyme Biotech, Nanjing, China). The gene SeCar without the predicted signal sequence was amplified by PCR using the forward and reverse primers 5′-CACGAAAAAGAAAAAGATAATAATAAAAGTGAAC-3′ and 5′-CGTTACGCCTTCAATCGTAAC-3′. SeCar was cloned and ligated into pEASY-blunt E2 vector (TransGen Biotech, Beijing, China) to conduct recombinant plasmid. The constructed plasmid was transformed into BL21(DE3) competent cells (TransGen Biotech, Beijing, China) and then screened on Luria-Bertani (LB) medium supplemented with ampicillin. After incubation for 10 h, the positive colony was selected and cultured in LB medium with ampicillin in a shaker at 180 rpm at 37 °C until the absorbance value of bacterial solution reached OD600 = 0.8. The enzyme was prepared by adding isopropyl-beta-D-thiogalactopyranoside into recombinant Escherichia coli culture and then shaken at 150 rpm for 12 h at 16 °C. Cells were pelleted (7500× g; 15 min), resuspended in 50 mL of phosphate buffered saline (PBS), and lysed on ice by sonicating (300 w, 20 min). The supernatant after centrifugation was the crude enzyme of SeCar and was purified by Ni-affinity chromatography. The methods of gene expression and protein purification refer to the previous description [74,75]. Coomassie brilliant blue binding method was used to determine the total protein concentration. The enzyme activity was determined by 3,5-dinitrosalicylic acid (DNS) method with galactose as standard [76]. The amount of enzyme releasing 1 µmol galactose per minute under standard conditions is defined as one unit (U) of enzyme activity. The optimum reaction temperature was determined by measuring the activity of SeCar in the range of 20 °C to 80 °C with 0.1% κ-selenocarrageenan as substrate. SeCar was incubated in PBS buffer at 20–60 °C for 0–24 h, and the residual activity was detected to assess thermostability. The optimal pH for SeCar activity was determined using different buffers, such as sodium citrate buffer (pH 3.0–6.0), phosphate buffer (pH 6.0–8.0), Tris-HCl buffer (pH 8.0–9.0) and glycine buffer (pH 9.0–11.0), at 40 °C with 0.1% (w/v) κ-selenocarrageenan as the substrate. SeCar was preincubated with the above buffers at 20 °C for 2 h, and the residual enzyme activity was detected to assess pH stability. In order to evaluate the effects of metal ions and chemical reagents on SeCar, the enzyme assay was performed in the presence of 5 mM Na+, K+, Cu2+, Mg2+, Mn2+, Ca2+, Fe2+, Fe3+ and EDTA. Enzyme activity was measured at 40 °C and pH 7.0. The reaction without adding metal ions and chemical reagents was used as the control. For the values of Km and Vmax, the purified enzyme reacted with 0.025–0.2% κ-selenocarrageenan as substrate at 40 °C for 30 min, which were calculated by double reciprocal plotting. All of the above activity assays were performed in 3 replicates. The KSCOs were prepared and isolated according to the previously described method with modifications [77,78]. The reaction system, containing 6 U of purified SeCar and 25 mM KSC, was conducted at 40 °C for 12 h. The lysate was boiled for 10 min to inactivate κ-selenocarrageenase and centrifuged for 15 min at 6000 r/min to remove impurities. Finally, four volumes of 95% ethanol (v/v) were added to precipitate the undegraded KSC. After centrifugation at 10,000 r/min, the supernatant was concentrated using a rotary evaporator at 60 °C and then lyophilized under vacuum at −60 °C to obtain crude KSCOs. The molecular weight (MW) of KSCOs was evaluated by HPGPC [79]. The analysis was performed on a high-performance liquid chromatography (HPLC) instrument equipped with a TSK G2500PW column and eluted with deionized water, which filtered through a filter membrane (pore size 0.22 μm) at a flow rate of 0.3 mL/min. A total of 20 μL of 1% sample solutions in deionized water was injected. The molecular weight was evaluated with maltose (MW: 342, 668, 990 Da) and dextran (MW: 2000, 5900, 9600 Da) as standards. KSCOs were purified by chromatography using a modified method previously described [80]. The freeze-dried samples were dissolved in 0.02 mol/L NH4HCO3, and the supernatant after centrifugation (4000 rpm, 10 min) was purified by Bio-Gel P4 chromatography eluting with 0.02 mol/L NH4HCO3 at a flow rate of 3.0 mL/h. The components collected by the automatic collector were desalted with Bio-GEL P4 column, eluted with 3.0 mL/h distilled water, and freeze-dried after concentration. In order to further analyze the structure, KSCOs were analyzed by ESI-MS in negative ion mode [33]. KSCOs (2.0 mg) were dissolved in acetonitrile: water (1:1, v/v) to make the concentration within the range of 5–10 pmol/L, and the sample volume was 5 µL. In the process of mass spectrometry, N2 was used as the solvent of blow-drying gas and spray gas, and the flow rates were 250 and 15 L/h, respectively. The mobile phase was acetonitrile: water (1:1, v/v). Driven by the pump, the sample was injected at a flow rate of 10 µL/min. The parameters involved a capillary voltage of 3 kV, a cone-hole voltage of 50 eV, an ionic element volatilization temperature of 80 °C and a solvent volatilization temperature of 150 °C. The hydrolysate of KSC was analyzed by TLC plate developed with n-butane: ethanol: water (3:2:2, v/v/v) according to the previous description [75]. After drying, the plate was stained with a mixture of vitriol: ethanol (3:17, v/v; with 0.2% resorcinol, w/v) and heated until the appearance of clear bands. FTIR and NMR assays were carried out according to previous methods [80,81]. For FTIR spectra, KSC and its oligosaccharides (2.0 mg) were mixed with KBr (200 mg) powder, ground and pressed, and then measured on a Nicolet Nexus 470 spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). For NMR spectra, KSC (50 mg) was dissolved in 500 μL 99% of the D2O, freeze-dried and repeated 3 times. The sample was then redissolved in 500 μL D2O and transferred to an NMR tube. Finally, 1H-NMR/13C-NMR with Agilent DD2 500 MHz NMR spectrometer was performed with acetone as the internal standard. A total of 40 male C57BL/6 mice (20–22 g) were purchased from Pengyue experimental animal breeding Co., Ltd. (Jinan, China). All animals were raised under the conditions of 20–25 °C, 60–70% relative humidity and 12/12 h light/dark cycle. They were randomly divided into six groups after a one-week acclimatization period (n = 8 per group). All animal experiments were in line with the National Laboratory Animal Ethics Committee of China and were approved by the Animal Care Review Committee (approval number SYXK2020-0422), Qingdao University of Science and Technology, China. In the normal group, the mice drank water freely from day 0 to day 14. In the DSS group, the mice drank water freely from day 0 to day 7, followed by administration of 3.0% (w/v) DSS (36 kDa-50 kDa, MP biomedicals) for 7 days. In the KSCOs intervention groups, low-dose (LS, 1.6 mg/kg), medium-dose (MS, 3.2 mg/kg) and high-dose (HS, 6.4 mg/kg) KSCOs were given by gavage every day throughout the experimental cycle and DSS was added to the drinking water from day 7 to day 14. The grouping and respective treatments are detailed in Figure 9. The weight of mice was recorded daily. DAI was determined by assessing clinical symptoms including weight loss, fecal traits and hematochezia in mice, then the average of these scores was calculated, as previously described [82]. The specific scoring rules are shown in Table 3. The proximal colon of each group was fixed with 4% paraformaldehyde and embedded in paraffin, which were stained with hematoxylin−eosin (H&E) for histopathological observation. Colon tissues (~0.1 g) were ground in cold normal saline to prepare 10% homogenate. The activity of MPO was measured using homogenate according to the kit (Nanjing Jiancheng, Nanjing, China) instruction. The concentrations of interleukin (IL)-6, TNF-α and IL-10 in serum were measured using enzyme-linked immunosorbent assay (ELISA) kits (MultiSciences, Hangzhou, Zhejiang, China) following the manufacturer’s protocol. Fecal samples (25 mg) were dissolved in 500 μL of water containing 0.5% phosphoric acid and then were frozen and ground for 3 min (50 HZ), followed by ultrasound for 10 min and centrifugation at 13,000× g for 15 min. After that, all of supernatant was removed and n-butanol (0.2 mL) was added to extract SCFAs. Finally, the extract was analyzed by gas chromatograph–mass spectrometer (GC-MS) [59]. The methods of DNA extraction, PCR amplification and 16S rRNA sequencing were performed as previously described [83]. Genomic DNA was extracted from fecal sample using OMEGA kit and detected by 1% agarose gel electrophoresis. Primers (338F-5′-ACTCCTACGGGAGGCAGCAG-3′ and 806R-5′-GGACTACHVGGGTWTCTAAT-3′) with barcode were synthesized for V3-V4 region amplification of 16S rRNA. Miseq library was constructed and sequenced. PE reads were firstly spliced according to overlap, then the sequence quality was controlled and filtered (Majorbio Bio-Pharm Technology Co. Ltd., Shanghai, China). Operational taxonomic unit (OTU) clustering was performed for nonrepeating sequences according to 97% similarity. Ribosomal database project (RDP) classifier (version 2.13) was used to classify OTU representative sequences. Alpha diversity and Beta diversity were assigned using QIIME software 1.9.1 (Rob Knight, CA, USA). The principal coordinate analysis (PCoA), principal component analysis (PCA) and community structure differences among groups were analyzed with QIIME software and R software 3.5.3 (UoA, AKL, NZ). The results were expressed as mean ± standard deviation (SD). Data were analyzed via one-way ANOVA with Tukey’s test to determine the statistical significance (p < 0.05) using SPSS version 22.0 and GraphPad Prism version 7.0 software (Inc., La Jolla, CA, USA). In this study, a κ-selenocarrageenase from the deep-sea bacterium Bacillus sp. N1-1 was characterized and expressed in Escherichia coli. The reaction temperature was optimized to facilitate the preparation of KSCOs. KSC could be efficiently hydrolyzed by SeCar and yielded a large proportion of small molecular KSCOs (<1500 Da). Spectral analysis showed that selenium oligosaccharides in the hydrolysate of κ-selenocarrageenan were mainly composed of selenium-galactobiose. At present, the application of KSCOs in the treatment of UC is still limited. In this study, the effects of KSCOs administration (1.6 mg/kg, 3.2 mg/kg, 6.4 mg/kg) on UC mice were evaluated. It was suggested that the administration of KSCOs significantly mitigated symptoms of UC, ameliorated neutrophil infiltration and improved inflammatory cytokines dysregulation. We speculated that KSCOs alleviated UC by suppressing inflammatory responses and modulating the composition of gut microbiota. Above all, the κ-selenocarrageenase SeCar could be a potential tool for hydrolyzing κ-selenocarrageenan, and the products of KSCOs were expected to be promising candidates for UC. This study expands the application of organic Se in the treatment of inflammatory diseases.

PMC10003264

Jiali Wu,Ke Shi,Fang Zhang,Xiaodong Sun

A 3-miRNA Risk Scoring Signature in Early Diabetic Retinopathy

23-02-2023

diabetic retinopathy,differentially expressed gene,miRNA,risk score signature

Purpose: The aim of our study was to investigate a comprehensive profile of streptozotocin (STZ)-induced early diabetic retinopathy (DR) mice to identify a risk scoring signature based on micorRNAs (miRNAs) for early DR diagnosis. Methods: RNA sequencing was performed to obtain the gene expression profile of retinal pigment epithelium (RPE) in early STZ-induced mice. Differentially expressed genes (DEGs) were determined with log2|fold change (FC)| > 1 and p value < 0.05. Functional analysis was carried out based on gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein–protein interaction (PPI) network. We predicted the potential miRNAs via online tools and ROC curves were then conducted. Three potential miRNAs with AUC > 0.7 were explored via public datasets and a formula was further established to evaluate DR severity. Results: In total, 298 DEGs (200 up-regulating and 98 down-regulating) were obtained through RNA sequencing. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 were three predicted miRNAs with AUC > 0.7, suggesting their potential to distinguish healthy controls from early DR. The formula of DR severity score = 19.257 − 0.004 × hsa-miR-217 + 5.09 × 10−5 × hsa-miR-26a-5p − 0.003 × hsa-miR-129-2-3p was established based on regression analysis. Conclusions: In the present study, we investigated the candidate genes and molecular mechanisms based on RPE sequencing in early DR mice models. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 could work as biomarkers for early DR diagnosis and DR severity prediction, which was beneficial for DR early intervention and treatment.

A 3-miRNA Risk Scoring Signature in Early Diabetic Retinopathy Purpose: The aim of our study was to investigate a comprehensive profile of streptozotocin (STZ)-induced early diabetic retinopathy (DR) mice to identify a risk scoring signature based on micorRNAs (miRNAs) for early DR diagnosis. Methods: RNA sequencing was performed to obtain the gene expression profile of retinal pigment epithelium (RPE) in early STZ-induced mice. Differentially expressed genes (DEGs) were determined with log2|fold change (FC)| > 1 and p value < 0.05. Functional analysis was carried out based on gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein–protein interaction (PPI) network. We predicted the potential miRNAs via online tools and ROC curves were then conducted. Three potential miRNAs with AUC > 0.7 were explored via public datasets and a formula was further established to evaluate DR severity. Results: In total, 298 DEGs (200 up-regulating and 98 down-regulating) were obtained through RNA sequencing. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 were three predicted miRNAs with AUC > 0.7, suggesting their potential to distinguish healthy controls from early DR. The formula of DR severity score = 19.257 − 0.004 × hsa-miR-217 + 5.09 × 10−5 × hsa-miR-26a-5p − 0.003 × hsa-miR-129-2-3p was established based on regression analysis. Conclusions: In the present study, we investigated the candidate genes and molecular mechanisms based on RPE sequencing in early DR mice models. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 could work as biomarkers for early DR diagnosis and DR severity prediction, which was beneficial for DR early intervention and treatment. Diabetic retinopathy (DR) is one of the leading causes of vision impairment and even blindness in the working-age population. It is estimated that there are more than 90 million DR patients worldwide [1]. Clinically, DR is divided into two stages: non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). NPDR is the early stage of DR without severe symptoms; therefore, most patients are not vigilant about being diagnosed. However, many pathological alterations, including increased vascular permeability and capillary occlusion, begin to occur at this stage [2]. Once NPDR progresses to PDR, vision dramatically decreases, posing a massive medical and economic burden on both patients and society. Therefore, a comprehensive study of early-stage DR is indispensable for early diagnosis and timely intervention. Traditionally, DR was classified as a microvascular complication of diabetes. With the development of modern technologies, researchers gradually realized that DR not only affects the retina, but also influences the RPE and neuronal units in the early stage [3,4]. RPE has vital physiological functions, including the formation of the outer blood retinal barrier (oBRB), transportation of nutrients to photoreceptors (PRs), absorption of scattered light, recycling of retinoid and phagocytosis of shed PR outer segment membrane [5]. Therefore, depicting the gene profile of RPE and studying their function could help enrich the understanding of early DR and further develop novel diagnosis and treatment strategies [6,7]. In our study, we carried out the RNA sequencing for RPEs from early DR mice models. Potential miRNAs were predicted based on the DEGs in RPE and subsequently validated via a public dataset. A formula was then constructed to score the DR risk with potential miRNAs. Male C57BL/6J mice aged 6–8 weeks were purchased from Shanghai Laboratory Animal Center. Intraperitoneal injection of 55 mg/kg of STZ was performed for 5 consecutive days to induce diabetes while PBS was utilized as a control. Blood glucose levels were tested via tail vein blood after one week, and animals with blood glucose concentrations of ≥ 200 mg/dL were considered to be successful models. Optical coherent tomography (OCT) was performed to observe the retinal structure before sacrifice. All animal experiments were approved by the Ethics Committee of Shanghai Jiao Tong University, China, and were in accordance with the requirements of the Association for Research in Vision and Ophthalmology Statement for the Use of Animals in Ophthalmic and Vision Research. The approval number of Animal Ethical Committee is 2019AW055. Gene expression profile in the RPEs was identified by RNA sequencing. RPE–choroid complexes were separated along the corneal limbus and transferred to 1.5 mL tubes with RNA protect Cell Reagent (QIAGEN, Dusseldorf, Germany) to enrich RPE cells. TRIzol (Invitrogen, Carlsbad, CA, USA) was subsequently used to extract total RNA. The genes with log2|fold change (FC)| > 1 and p values < 0.05 were defined as differentially expressed genes (DEGs) and visualized by volcano plots and heatmaps using R3.5.0 (R Foundation for Statistical Computing, Vienna, Austria). The expression pattern was available in Table S1. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using Metascape (https://metascape.org/gp/index.html#/main/step1 accessed on 9 December 2022). GO, KEGG and reactome terms with p values < 0.05 were presented. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) (https://string-db.org/ accessed on 9 December 2022) was utilized to evaluate the protein–protein interaction (PPI) of DEGs. Cytospace (version 3.8.2) was further applied to construct the network with Cytohubba plug-in unit and the genes were ranked according to MCC algorithm. The redder gene represented the higher rank. miRNet (https://www.mirnet.ca/ accessed on 9 December 2022) tool was utilized to predict miRNAs targeting DEGs, and Cytospace (version 3.8.2) was used to visualize the network. Electroretinogram (ERG) recording was carried out with a scotopic Ganzfeld ERG system (Phoenix Research Labs, New York, NY, USA). The mice were anesthetized by intraperitoneally injecting 1.5% sodium pentobarbital (100 μL/20 g) and the pupils were dilated with tropicamide after dark adaptation overnight. The reference needle electrode was placed behind the ears while the ground one was plunged into the tail. As described below, the ERG was measured with four different stimulus intensities, 1.0, 2.0, 3.0 and 4.0 log cd s/m2 with intermittent intervals of 10, 20, 20 and 30 s. A-wave and B-wave values were recorded and analyzed. Eyeballs were enucleated and fixed in eyeball fix solution (Servicebio, Wuhan, China) after sacrifice. After wax embedding, eyeball cross sections were prepared (5 μm). The slides were stained in Hematoxylin solution for 5 min, followed by Hematoxylin differentiation solution and water rinse. Then, the slides were treated with Hematoxylin Scott Tap Bluing and rinsed with water again. Lastly, the slides were dehydrated and sealed with neutral gum. Raw data of the public datasets utilized in our study were acquired from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/ accessed on 9 December 2022). GSE1603086, based on GPL20301 platform, was a smallRNA profile consisting of retina samples from 43 donors. GSE1409597 was an miRNA profile with three different biological fluids, including aqueous humor, vitreous and plasma from 27 patients, which was established on GPL16384 platform. Data were shown as the mean ± SD. All the experiments were performed for at least three biological replicates and differences between the two groups were analyzed by a Student’s t-test. Linear regression analysis was used for analyzing relationships among miRNAs and DR severity. p values < 0.05 were considered statistically significant. Statistical analysis in our study was performed with SPSS Statistics 26 (IBM, Armonk, NY, USA). To our knowledge, there are no published sequencing data on RPEs in STZ-induced early DR models yet. Therefore, we established early DR mice models by STZ intraperitoneal injections. After 2-month STZ induction, diabetic mice showed lighter weight and higher blood glucose than control ones (Figure 1A,B). Electroretinograms (ERGs) were carried out to evaluate functional alterations. A wave of ERG represented the function of photoreceptors, while B wave indicated the function of the outer retina. ERG was taken with four different stimulus intensities, 1.0, 2.0, 3.0 and 4.0 log cd s/m2 with intermittent times of 10, 20, 20 and 30 s. As the stimulus increased, amplitudes gradually increased. As shown in the recordings, amplitudes of the B wave declined significantly in early diabetic mice while A waves showed no significant change. This finding suggested detectable functional damage to the retina instead of RPE at this stage (Figure 1C–F). Morphology changes were evaluated via H & E staining, from which we could observe a slight decrease in the outer nuclear layer. This thinning trend was consistent with that in OCT in vivo, both demonstrating retinal alterations in STZ-induced early diabetic models (Figure 1G,H). We further performed RNA sequencing with STZ-induced early diabetic models, in an attempt to demonstrate a comprehensive gene profile (n = 3). PCA plot showed the reproducibility of our data within two groups (Figure 2A). Further, results of the sequencing were relatively uniform, seen by a distribution boxplot (Figure 2B). Genes with log2|FoldChange| > 1 and p value < 0.05 were identified as RPE-DEGs in our study. A total of 200 up-regulating and 98 down-regulating DEGs are shown by the volcano plot and heatmap (Figure 2C,D). Metascape tool was utilized to carry out GO and KEGG analysis for RPE-DEGs. Neurotransmitter transport, ion transmembrane transport and regulation of amine transport were clustered in GO analysis for up-regulating DEGs (Figure 3A). Nicotine addiction, neuroactive ligand–receptor interaction, heparan sulfate metabolism and N-Glycan biosynthesis were enriched in KEGG pathways. Transmission across chemical synapses, neuronal system, neurotransmitter receptors and postsynaptic signal transmission and glycosaminoglycan metabolism were the top enriched reactome gene sets. When analyzing down-regulating genes, response to reactive oxygen species, inflammatory responses, regulation of cytokine production and fatty acid biosynthetic process were significantly enriched (Figure 3B). The PPI networks were constructed for up-regulating and down-regulating DEGs separately via STRING database and further Cytoscape software. For the up-regulating DEGs, in total, 88 genes were identified. SLC32A1, KCNA1, CPNE6, OPCML, SLC6A7, SYN2, CBLN4, NCAN, NRXN2 and RBFOX3 were the top 10 genes ranked by the MCC method (Figure 4A). The Molecular Complex Detection (MCODE) algorithm was utilized to identify densely connected network components and 14 gene lists were gathered (Figure 4B). As for the down-regulating DEGs, MAG, MOG, MOBP, 0LIG1, PLP1, BFSP1, GJA3, GRIFIN, CRYGD and CRYGB were tagged as the top ten genes among 28 genes ranked (Figure 4C) and 5 individual gene sets were identified via the MCODE algorithm (Figure 4D). To further investigate the regulatory profile of these DEGs, we predicted and constructed miRNA–mRNA networks using the miRNet tool. In an attempt to search for the most promising miRNAs, we set the threshold of miRNAs targeting to at least 10% of DEGs. Thus, 15 miRNAs were mined targeting at least 9 up-regulating DEGs (Figure 5A) while 43 miRNAs were identified targeting at least 3 down-regulating DEGs (Figure 5B). miRNA–mRNA networks were further formed by Cytoscape. Among them, hsa-mir-27a-3p had potential to sponge with 37 up-regulating genes, and hsa-mir-146a-5p was the top miRNA, with the ability to target 14 down-regulating DEGs. After establishing the candidate miRNAs in early DR mice models, we further explored them in early-stage DR patient samples. GSE160308 was made up of 20 healthy control samples, 20 samples from diabetic patients without ocular manifestations, 19 non-proliferative DR patient samples and 5 DME patient samples. ROC curve analysis was performed for potential miRNAs. AUC > 0.7 was set as a meaningful cut-off value and AUC values of miR-129-2-3p (AUC = 0.797, 95%CI 0.654–0.941), miR-217 (AUC = 0.724, 95%CI 0.557–0.890) and miR-26a-5p (AUC = 0.708, 95%CI 0.540–0.875) were higher than 0.7, suggesting that they had potential to distinguish healthy controls from NPDR patients (Figure 6A–C). What’s more, miR-129-2-3p and miR-217 decreased along with the severity of DR while miR-26a-5p had an increasing trend (Figure 6D). The PCA plot also demonstrated that these three miRNAs could well distinguish NPDR from healthy controls (Figure 6E). GSE140959 was included for verification and miR-217 expression in this dataset also represented a decreasing tendency in aqueous, vitreous and plasma (Figure 6F). Association of these three miRNAs and severity of DR were further analyzed by regression analysis (Table 1). Results demonstrated that miR-129-2-3p (B = −0.003, β = −0.37, p = 0.002) and miR-217 (B = −0.004, β = −0.325, p = 0.028) were negatively related to DR progression. miR-26a-5p (B = 5.09 × 10−5, β = 0.584, p = 0.000) was positively associated with the risk of DR. This linear association could be calculated by: DR severity score = 19.257 − 0.004 × hsa-miR-217 + 5.09 × 10−5 × hsa-miR-26a-5p − 0.003 × hsa-miR-129-2-3p. DR is one of the leading causes of vision impairment in the working-age population. As a complex and multifactorial disorder, current therapies for DR, such as laser photocoagulation and anti-vascular endothelial growth factor injection, are not effective for all patients 4. The progression of NPDR to PDR is a vision-threatening turning point, and it is also the key point physicians should consider. By analyzing the gene expressions that change significantly in early DR, we predicted and constructed an miRNA-based risk signature for early DR diagnosis and therapy. The role of RPE in DR is not well studied currently. RPE was a metabolically active tissue responsible for glucose trans-epithelial transport into the outer retina via GLUT1. Glucose was then utilized for synthesis of phospholipids via tricarboxylic acid cycle and oxidative phosphorylation. Therefore, RPE functioned as a bridge between choroid and photoreceptors to efficiently utilize glucose [8]. Diabetes not only disrupted RPE structure but also hampered the function of RPE cells. To the best of our knowledge, no sequencing study for RPE in diabetic mice has been reported yet. Therefore, we carried out RNA sequencing to investigate the gene profile in RRE cells. Further, 200 up-regulating and 98 down-regulating DEGs were identified in our study. Functional analysis suggested that up-regulating DEGs played a vital role in neurotransmitter transport, ion transmembrane transport and regulation of amine transport. RPE was able to transport iron and iron was a necessary component in biological processes. However, excessive iron contributed to various pathological events, such as oxidative stress and lipid peroxidation. Iron accumulation was detected in postmorten human diabetic patients. With an HFE knockout (KO) mice model of genetic iron overload, researchers found that iron overload during diabetes exacerbated DR progression [9]. Excessive intracellular iron could be a fuse of ferroptosis, which was featured with mitochondrial atrophy and mitochondrial cristae structure change. In human retinal pigment epithelial (ARPE 19) cells treated with high glucose, intracellular ferrous iron increased and ferroptosis took place [10]. Neural deficits involving the GABA signaling pathway have been detected. GABA increases in the vitreous of PDR patients [11,12]. Hyperglycemia interferes with GABA signaling in the inner retina and rod-bipolar cells. It directly influences the GABA ρ subunit composition of GABAC receptors on retinal neurons [12,13,14,15]. When the GABAB receptor is activated, it can alleviate apoptosis and oxidative stress in neuronal cells via the PI3K-Akt signaling pathway in Alzheimer’s disease [16]. We further studied potential miRNAs targeting DEGs via the miRNet online tool and dozens of miRNAs were established. The public dataset GSE160308 was utilized for miRNA ROC curve exploration. Hsa-miR-217, hsa-miR-26a-5p and hsa-miR-129-2-3p were identified with AUC > 0.7, suggesting their potential to diagnose early DR. What’s more, miR-129-2-3p and miR-217 decreased along with the severity of DR while miR-26a-5p had an increasing trend. GSE140959 was then included and only one of three miRNAs, miR-217, was detected. Expression of miR-217 in this dataset represented a decreasing tendency in aqueous, vitreous and plasma of proliferative DR patients, which was consistent with that in GSE160308. All results suggested the vital roles of these three miRNAs in early DR. miR-26a-5p was reported as a circulating biomarker for early-stage retinal neurodegeneration via plasma RNA sequencing from NPDR patients [17]. Mechanically, miR-26a-5p delayed thinning of neuroretinal layers by regulating PTEN expression. Further, miR-26a-5p up-regulation significantly decreased IL-1beta, NF-kapaB and VEGF expression [18]. Effects of miRNA-217 were investigated in high-glucose-treated ARPE-19 cells. miR-217 down-regulation augmented cell viability and alleviated cell apoptosis by sponging SIRT1. In addition, miR-217 inhibitor significantly reduced the expression of IL-1beta, IL-6 and tumor necrosis factor α [19]. miR-129-2-3p has not been reported in DR yet, but it was found to be beneficial to diabetic wound healing. Overexpression of miR-129-2-3p could accelerate wound healing by regulating inflammation and apoptosis directly [20]. Notably, the functions of most miRNAs we predicted have not yet been thoroughly elucidated, especially in early DR. Thus, further investigations are meaningful for prospective value validation. In our results, these three miRNAs were all dis-regulated in DR. ROC curve analysis suggested their potential as early biomarkers for DR. What’s more, we found that the expression of three miRNAs was negatively or positively correlated with DR severity. Therefore, we further carried out regression analysis for them. miR-129-2-3p (B = −0.003, β = −0.37, p = 0.002) and miR-217 (B = −0.004, β = −0.325, p = 0.028) were negatively related to DR progression. miR-26a-5p (B = 5.09 × 10−5, β = 0.584, p = 0.000) was positively associated with DR severity. DR severity score could then be calculated by this three-miRNA risk scoring signature (F = 9.066, R = 0.516) as 19.257 − 0.004 * hsa-miR-217 + 5.09 × 10−5 * hsa-miR-26a-5p − 0.003 * hsa-miR-129-2-3p. Our study identified a comprehensive gene profile in early diabetic mice models via RNA sequencing analysis, which expanded our understanding of pathological processes in DR. A three-miRNA risk scoring signature was further established for early diagnosis of DR. Further studies are warranted to explore and extend our findings for potential diagnosis and therapy development.

PMC10003267

Aleksandr V. Ivanov,Irina V. Safenkova,Sergey F. Biketov,Anatoly V. Zherdev,Boris B. Dzantiev

Engineering of DNA Structures Attached to Magnetic Particles for Effective Trans- and Cis-Cleavage in Cas12-Based Biosensors

24-02-2023

CRISPR-Cas12,magnetic particles,cis-cleavage,trans-cleavage,DNA amplification

Sequence-specific endonuclease Cas12-based biosensors have rapidly evolved as a strong tool to detect nucleic acids. Magnetic particles (MPs) with attached DNA structures could be used as a universal platform to manipulate the DNA-cleavage activity of Cas12. Here, we propose nanostructures of trans- and cis-DNA targets immobilized on the MPs. The main advantage of the nanostructures is a rigid double-stranded DNA adaptor that distances the cleavage site from the MP surface to ensure maximum Cas12 activity. Adaptors with different lengths were compared by detecting the cleavage by fluorescence and gel electrophoresis of the released DNA fragments. The length-dependent effects for cleavage on the MPs’ surface were found both for cis- and trans-targets. For trans-DNA targets with a cleavable 15-dT tail, the results showed that the optimal range of the adaptor length was 120–300 bp. For cis-targets, we varied the length and location of the adaptor (at the PAM or spacer ends) to estimate the effect of the MP’s surface on the PAM-recognition process or R-loop formation. The sequential arrangement of an adaptor, PAM, and a spacer was preferred and required the minimum adaptor length of 3 bp. Thus, with cis-cleavage, the cleavage site can be located closer to the surface of the MPs than with trans-cleavage. The findings provide solutions for efficient Cas12-based biosensors using surface-attached DNA structures.

Engineering of DNA Structures Attached to Magnetic Particles for Effective Trans- and Cis-Cleavage in Cas12-Based Biosensors Sequence-specific endonuclease Cas12-based biosensors have rapidly evolved as a strong tool to detect nucleic acids. Magnetic particles (MPs) with attached DNA structures could be used as a universal platform to manipulate the DNA-cleavage activity of Cas12. Here, we propose nanostructures of trans- and cis-DNA targets immobilized on the MPs. The main advantage of the nanostructures is a rigid double-stranded DNA adaptor that distances the cleavage site from the MP surface to ensure maximum Cas12 activity. Adaptors with different lengths were compared by detecting the cleavage by fluorescence and gel electrophoresis of the released DNA fragments. The length-dependent effects for cleavage on the MPs’ surface were found both for cis- and trans-targets. For trans-DNA targets with a cleavable 15-dT tail, the results showed that the optimal range of the adaptor length was 120–300 bp. For cis-targets, we varied the length and location of the adaptor (at the PAM or spacer ends) to estimate the effect of the MP’s surface on the PAM-recognition process or R-loop formation. The sequential arrangement of an adaptor, PAM, and a spacer was preferred and required the minimum adaptor length of 3 bp. Thus, with cis-cleavage, the cleavage site can be located closer to the surface of the MPs than with trans-cleavage. The findings provide solutions for efficient Cas12-based biosensors using surface-attached DNA structures. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas (CRISPR associated protein) systems are actively used as tools for bio-sensor developments [1]. Among the large Cas family, Cas12a is the most requested one for programmable and high specific recognition of DNA followed by cleavage at a certain point. In biosensors, the CRISPR-Cas comprises Cas12a and engineered guide RNA (gRNA). The gRNA contains a 5′ stem-loop and spacer region of DNA recognition [2]. The holo-enzyme recognizes a sequence complementary to the gRNA spacer and cuts each strand of target double-stranded (ds) DNA [3]. In addition, an activated Cas12a is able to facilitate the non-specific trans-cleavage of single-stranded (ss) DNA [4]. The assembled holoenzyme starts scanning dsDNA until identifying a protospacer adjacent motif (PAM) for which 5′-TTTV-3′ is the most typical sequence [2]. When the PAM is found, Cas12a unwinds 20 bp of the PAM downstream region (R-loop), and gRNA forms a complementary complex with the target strand (TS) of the R-loop [3]. Once a correct R-loop has been formed, Cas12a rapidly digests a phosphodiester bond in the non-target strand (NTS) near 3′ of the NTS spacer, which is +15–+19 nt away from PAM [3,4]. After conformation rearrangements, Cas12 digests TS at a position +22–+23 nt [2,3]. After NTS cleavage, the Cas12a active center opens to digest any ssDNA interacted with the Cas12a complex that determines trans-cleavage activity [4]. In addition, ssDNA complementary to gRNA can be recognized without PAM and cis-cleaved followed by the unspecific trans-cleavage of any ssDNA [5]. The trans-cleavage activity of Cas12a is heavily used for detecting DNA by different approaches. The first and the most widespread among them is DETECTR [4]. The number of test systems utilizing DETECTR is rising dramatically [1,6]. No less common in Cas12-based biosensors is the method called HOLMES, which was proposed almost simultaneously with DETECTR and differs mainly in the way amplicons produce before the reaction with Cas12a [7]. In Cas12-based biosensors, the recognition of DNA by Cas12-gRNA causes a trans-cleavage of the ssDNA probe being in solution or attached to the carrier surface and followed by detection of fluorescence, lateral flow assay, etc. [8]. Using an ssDNA target in a solution is a common method for Cas12-biosensors, in which the optimal ssDNA length and nucleotide composition for the most efficient trans-cleavage are known [9]. At the same time, many promising Cas12-biosensors are being designed based on different ssDNA attached to various surfaces. The parameters of biosensors with attached ssDNA are not optimized. Thus, the question about the choice of structures for surface-attached ssDNA is still open. Biosensors were constructed using a short (10–35 nt) ssDNA immobilized on gold nanoparticles (GNPs) [10], a combination of magnetic particles (MPs) and platinum nanoparticles bound with 200 nt poly-dT ssDNA [11], a combination of MPs and catalase bound with 43 nt poly-dA ssDNA [12], 29 nt ssDNA conjugated with protein (human chorionic gonadotropin) [13], the composite dsDNA–ssDNA–protein (IgG) probe attached to polystyrene microplate [14], 10–30 nt ssDNA modified by methylene blue (electrochemical tag) immobilized on the gold surface of the chip [15], and DNA hairpin (17 ds helix and 8 nt loop) with methylene blue [16]. The attachment to the surface in Cas12-biosensors is also useful for DNA cis-targets to monitor non-nucleic acid analytes [1]. Particularly, signal transduction between the recognition of an analyte and CRISPR/Cas12 amplification was realized to detect insulin [17] and prostate-specific antigen [18]. Therefore, the variety of ssDNA-attached approaches demonstrates a strong potential for the emergence of biosensors with greater sensitivity and flexible adaptation to new analytes. Herein, we focused on MPs as universal carriers to attach to the DNA targets, which are widespread in biosensing and nanotechnology for concentration, purification, separation, directed transport, cell-transferring, etc. [19]. An obvious advantage of combining MP- and Cas12a-based approaches is the convenient manipulation with non-cleaved and released DNA. Some studies using magnetic particles and Cas of different types at the same time confirm the promise of this combination [11,12]. However, there are no comparative studies directed to the selection of optimal constructs of DNA targets immobilized on the MP surface that could be more effectively used in reactions with the cis- and trans-activity of Cas12. In this study, we sought the universal DNA constructers conjugated with MPs for the most efficient trans- and cis-cleavage. We added a rigid dsDNA-adaptor to the DNA-target that regulated the position of the cleavage site varying adaptor length. For cis-targets, we additionally studied the location of the adaptor (at the PAM or spacer ends) in DNA–MP conjugates. For all experiments, we assembled a holoenzyme Cas12 with gRNA and added a cis-target, which comprised a recognition site (PAM and spacer) for the Cas12a–gRNA complex. The DNA targets for trans- and cis-cleavage activity of Cas12a were conjugated with MPs. The conjugation of DNA targets and MPs was realized via interaction between biotin at the 5′-end and streptavidin, which covalently covered the MP surface. We used model DNAs without non-canonic structures (homogenous tracts, palindrome repeats forming crucifix, extremely low or high GC content, G-quadruplex structures) (see Supplementary Information, Tables S2 and S4). The cis-targets were constructed based on the IGS fragment of Dickeya solani (the bacterial pathogen that causes blackleg and soft rot in potato crops). We chose two sites for cis-cleavage: site 1 (gRNA1) and site 2 (gRNA2). The gRNA1 and gRNA2 were used for comparison of the different trans-targets and cis-targets, correspondingly. The DNA probes had different lengths of the dsDNA-adaptor (20, 40, 80, 120, 160, 300, 500, and 1000 bp; these values in nanometers are presented in Table S3, Supporting Information) and had the same ss-15-dT tail connected through a PEG linker (C3). The ssDNA could be cleaved by Cas12 at multiple sites. The dsDNA part of the probe was a tool for tuning the distance between the MP surface and ss trans-cleavage site. To detect the probe’s cleavage, the 5′-end of ss-15-dT was labeled with FAM as a fluorophore. The FAM/biotin-labeled ss-15-dT without any dsDNA portion was called an eGFP-0 fragment. The scheme of trans-DNA targets conjugated with MPs for trans-cleavage is presented in Figure 1A,D. The rigid dsDNA adaptors with different lengths have a different inclination for the terminal part. As found, the dsDNAs with that are longer than 150–180 bp are more flexible and strongly inclined [20,21]. However, we have considered the impact of the length of the dsDNA adaptor (see Table S3, Supplementary Information) to find the optimal distance between the ssDNA cleavage site and the MP surface. To investigate the Cas12a activity for cis-targets at the MP surface, we proposed two groups of cis-targets (IGS constructs) differing in the sequential location of the PAM and spacer relative to the MP surface. Cas12 is an asymmetric enzyme with parts recognizing PAM and cleaving TS and NTS. Its two functional centers are arranged along a bound DNA–cis-target. Different activities could require different optimum distances. We determined optimum distances for both functional centers of Cas12 using ds-adaptors with different lengths located at the PAM or spacer ends. For the first group of cis-targets (IGS(I)), we assumed that the sequential location was the PAM, spacer, ds-adaptor, and MP surface. In this group, a ds-adaptor with varying lengths from 0 to 478 bp (values are presented in Table S5, Supporting Information) of an IGS fragment following a 20 bp spacer was attached to the MPs through the 5′-biotin of TS. As Cas12 cleaves the cis-target in multiple sites of NTS and TS, the distance between the spacer and MP surface could affect the cleavage. The scheme of DNA targets from the first group conjugated with MPs for cis-cleavage is presented in Figure 1B,E. The distal FAM labeled dsDNA (97 bp) was the same for all cis-targets in this group. The recognition and cleavage of the MP-bound IGS construct by Cas12 led to the release of the FAM-labeled dsDNA fragment (Figure 1E). For the second group of cis-targets (IGS(II)), we assumed that the sequential location was the spacer, PAM, the adaptor, and the MP surface. For this group, the position of PAM was close to the edge of the MP surface and could be crucial for Cas12-recognition and the following cis-cleavage. The ds-adaptor was located between the first T of PAM and 5′-biotin of NTS and had varying lengths (0, 3, 10, 30, or 100 bp of IGS fragments; these values in nanometers are presented in Table S5, Supporting Information). The distal FAM-labeled fragment had a fixed length of 126 bp. The constant fragment was released from the cis-DNA-MP conjugate upon Cas12 cleavage, while Cas12-gRNA remained bound to cis-DNA-MP (Figure 1F). The scheme of DNA targets from the second group conjugated with MPs for cis-cleavage is presented in Figure 1C,F. The detection of trans-cleavage was performed based on the fluorescence of the released FAM. Three methods were used for cis-cleavage detection: (1) direct registration of the fluorescence of the released FAM, (2) gel electrophoresis of cleaved cis-fragments, and (3) indirect registration of the fluorescence of the cleaved FAM-dT15 BHQ1 probe when Cas12a was activated by cis-target DNA. Two preparations of streptavidin–MPs differing in the shape and structure of the surface were used. According to TEM data, the streptavidin–MPs-1 particles had a symmetrical and spherical shape with a diameter equal to 800–1000 nm (typical particles are presented in Figure 2A); we called these particles symmetrical MPs (SMPs). The streptavidin–MPs-2 were identified as non-symmetrical particles with cavities on their surface and diameter in the range of 300–500 nm (typical particles are presented in Figure 2B); we called these particles asymmetrical MPs (AMPs). The conjugation providing the saturation of binding biotinylated DNA targets with streptavidin-MPs was already achieved at 10 min incubation (Figure S5, Supporting Information). This optimal time was used for all conjugations. Based on both streptavidin–MPs, their conjugates were obtained with trans-targets (nine conjugates) and cis-targets (nine conjugates for the first group, five conjugates for the second group). The hydrodynamic diameters (Dh) distribution for the streptavidin–MPs and their conjugates with DNA targets were characterized with DLS and showed homogeneity of the preparations (Figure 2C–F). The average Dh for SMPs was 1062 nm, and for AMPs, it was 1207 nm. For AMPs and their conjugates, the Dh distributions were quite narrow (Figure 2F), which corresponds to the similar hydrodynamic behavior of these particles in solution. Possibly, the irregular shape of AMPs provided an even greater influence on their behavior in solution and average translational diffusion coefficient than geometric dimensions. The fluorescence of the conjugates was estimated, and their fluorescence quenching was found (12–65% for different adaptors, Table S6, Figures S6 and S7, Supporting Information). Therefore, further evaluations were performed based on the fluorescence of unbound and released DNA targets. For all trans-targets, we determined the percentage of bound DNA targets by MPs (loading). The loadings were in the range of 80% (eGFP-300)-96% (eGFP-0) regardless of the MP type (Table S7, Figure S8 (gray columns), Supporting Information). SMPs bound up to 54% of eGFP-500 or 34% of eGFP-1000 targets. AMPs bound to 51% of eGFP-500 or 33% of eGFP-1000 targets. Similar loadings were shown for IGS(I)-cis-targets (Table S8, Supporting Information). The effective concentration of DNA in the conjugates was estimated based on the loading that was used for further calculations. The obtained DNA–streptavidin–MP conjugates with different lengths of ds-adaptor were used as probes for trans-cleavage by Cas12a. The trans-cleavage activity of gRNA1–Cas12a complex activated by the IGS cis-target was proven with the ROX-dT15-BHQ2 probe as an internal control (Figure S10, Supporting Information, Section S7). The conjugates with a FAM-labeled ds-adaptor without ss-dT15 did not release FAM (Figure S11, Supporting Information, Section S7). Therefore, all cleavage events of the DNA–streptavidin–MPs should be a result of the cleavage of the ss-dT15 terminal part. Before trans-cleavage experiments, we checked the effect of trans-targets: MP ratio on the trans-cleavage. The variation of the surface density of DNA (Figure S12, Supporting Information, Section S7) or the concentration of MPs (Figure S13, Supporting Information, Section S7) did not change the trans-cleavage of the conjugated targets. Therefore, we approved that the chosen concentration conditions (100 nM of trans-targets and 0.0625% of MPs) for investigation of the length-dependent regularities for trans-cleavage were in the optimal range. For conjugates with SMPs, the efficiency of FAM released after trans-cleavage raised gradually with an increase in the ds-adaptor length (Figure 3A and Figure S14A,C, Supporting Information, Section S7). To control trans-cleavage results, we used MP conjugates and gRNA1–Cas12a complex without IGS activation (negative control) (see Figure 3). The results for eGFP-0 and eGFP-20 did not show a significant difference that is relative to the negative control. For eGFP-40, a reliable difference was obtained between reactions with activated gRNA1-Cas12a complex and negative control. Cleavage efficiency in the range of eGFP-0 -eGFP-120 did not exceed 15%, and the differences between reactions with activated gRNA1–Cas12a complex and without were no more than two-fold. The results for eGFP-160 and eGFP-300 showed 20% and 30% of FAM release and a 5–7-fold difference with corresponding negative controls. The cleavage for eGFP-500 and eGFP-1000 demonstrated a 55–60% of FAM release that was the most effective trans-cleavage. However, negative controls of eGFP-500 and eGFP-1000 had higher FAM release (%) than others. This fluorescence for negative controls could be the result of the potential dissociation of long eGFP fragments from MPs or partial destruction of MPs under temperature, shaking and magnet separation, resulting in the release of low-affine bound DNA targets. The cleavage of ROX-dT-BHQ2 internal control probe led to equivalent fluorescent signals (65–90%) for each reaction with activated Cas12a (Figure 3C). The absence of significant difference for trans-cleavage of ROX–dT15-BHQ2 occurring in the presence of conjugates with different trans-targets means that the type of trans-target in conjugate has no impact on trans-nuclease activity. Therefore, the efficiency of cleavage of eGFP-0–eGFP-120 immobilized on the MPs was far inferior to cleavage in a solution (see Figure 3). The longer adaptor (>120 bp) and the corresponding increment of the distance between the cleavage site and the MP surface (conjugates with eGFP-160–1000) increased the efficiency of cleavage. For conjugates with AMPs, the efficiency of FAM releases after trans-cleavage was higher for each ds-adaptor (Figure 3B and Figure S14B,D, Supporting Information) than the corresponding one in the case of SMPs. The high fluorescence was registered even for negative controls; the FAM release % for negative controls for all ds-adaptor lengths was close to FAM release % for negative controls for SMPs with eGFP-500, -1000 (Figure 3A). This non-specific release for AMPs could be caused by the partial formation of their conjugates with DNA by less-affine adsorption forces without biotin–streptavidin interactions. For AMPs conjugates, the dependence of trans-cleavage efficiency on ds-adaptor length had a bell curve character with a maximum at 160–500 bp range (Figure 3B and Figure S14B,D). The incomplete cleavage of the surface-attached DNAs (that the Cas12a showed) is an effect that deserves attention. The question arises as to whether such incomplete cleavage is a common feature for surface-attached DNAs that are substrates of nucleases. To clarify this, we carried out experiments with widely used DNaseI, which has endonuclease activity to ds- and ss-DNA substrates [22]. The treatment with DNAseI of ds-ssDNA–streptavidin–MP conjugates caused the release of FAM for all conjugates, but no complete cleavage was observed (Section S8, Figure S15, Supporting Information). These results showed that the effect of length-dependent cleavage for the Cas12a was determined by the specific features of Cas12a. We propose three possible reasons for these observed length-dependent effects: The close position of cleavable ssDNA to the surface could cause steric hindrance to contact with the enzyme. Local cavities could facilitate this effect. The surface charge of MPs could affect the enzyme activity nearby the surface. The lower trans-cleavage efficiency for long adaptors could be caused by coiling the long dsDNA. The dsDNAs with lengths longer than 150–180 bp are more flexible and more strongly inclined [21]. This dsDNA shape could mask the ssDNA-dT15 from the Cas12a-gRNA. Summarizing the results, we concluded that the efficiency of Cas12 trans-cleavage varied depending on the distance of the ssDNA cleavage site from the MP surface (Figure 3D). The trans-targets without or with a short adaptor had a small percentage of the cleavage. For SMPs, the maximal efficiency of the cleavage was 60% for the ds-adaptor with 500 bp, while for the ds-adaptor with 1000 bp, the efficiency decreased. For AMPs, the maximal efficiency of the cleavage was 40–50% within 120–500 bp. Simultaneously, the conjugates with 500–1000 bp adaptors have significantly lower binding with both MPs than the conjugates with other proposed adaptors (Figure 3D). Therefore, the optimal lengths of the adaptors in the ds-ssDNA trans-targets were similar for conjugates based on SMPs and AMPs: 160–300 (54–102 nm, see Table S3) and 120–300 bp (40–102 nm, see Table S3), respectively. These results can be used in Cas12-biosensors, in which an important step is to separate the cleaved parts of the ssDNA-probe in space. That will be important to realize when the ssDNA connects the carrier and the enzyme label or ligand, which are released after trans-cleavage. New possibilities in the design of the surface-attached probes will further advance the progress of Cas12-based biosensors. The effect of the distance between cleavage sites of cis-target and conjugation point was investigated for the conjugates with different adaptor lengths (0–478 bp); the adaptor was located between a spacer and the MP surface, and the connection of the adaptor to the MP surface was ensured due to 5′-biotin of TS (IGS(I)-cis-targets). The calculated length from the MP surface and the adaptor end is presented in Table S5, Supporting Information. The exact positions of cis-cleavages vary for Cas12a in the range of +15–+19 for NTS (the sequence number of the nucleotide after PAM) and of +22–+23 for TS [2,3]. The multiple digestions (“trimming” activity) at sites near the canonical were described, mainly for TS [23]. That is an additional factor of uncertainty for cis-cleavage location. Therefore, direct attachment of the spacer (20 nt) to the MP surface without an adaptor could provide only NTS cleavage. The ds-adaptor with a length >3 bp could provide the NTS and TS cleavages. The cis-cleavage and release of cleaved IGS-FAM occurred at both NTS and TS cleavages. The corresponding PAM and spacer positions were determined for gRNA2-Cas12a. The gRNA1-Cas12a was used as a negative control because the used ds-IGS fragments had no complete gRNA1 recognition site. The cis-cleavage was performed for all proposed constructs. The results of cis-cleavage detected by the fluorescence and gel electrophoresis of released IGS-FAM fragments are presented in Figure 4 and Figure S16, Supporting Information, Section S9. The cis-cleavage of the IGS(I)-cis-target immobilized on both types of MPs had the same features. The shortest IGS(I)-0 had no significant difference from negative controls. The IGS(I)-3 and IGS(I)-6 differed from the control, but the efficiency of the cleavage was quite small and did not exceed 5% for SMPs and 10% for AMPs (Figure 4A,B). The non-cleavage of IGS(I)-0 was associated with the impossibility of the cleavage of the TS, whereas for the IGS(I)-3 and IGS(I)-6, the possible reason was the interference of the location of the biotin–streptavidin linkage near the cleaved TS region. The IGSs with ds-adaptor lengths in the range of 10–478 bp were cleaved with an efficiency of 20–40% with high statistic deviations. Therefore, cis-cleavage efficiency did not depend on the distance between PAM and the MP surface when it exceeds 10 bp. The direct detection of cis-cleavage by the electrophoresis of cleaved 97 bp of IGS-FAM fragments confirmed the absence of released fragments for IGS(I)-0, -3, -6 (see Figure 4 and Figure S16A–C). The FAM-containing fragment (97 bp) was very slightly released in the supernatant in the case of IGS(I)-10 (Figure 4A and Figure S16D). The released 97 bp IGS-FAM from the longer IGS fragments was more visible in gels (Figure 4 and Figure S16H,I). Gel analysis reveals similar tendencies as fluorescent measurements. However, the minimal adaptor length for effective cis-cleavage was found to be longer than the fluorescent detected one and accorded to values between 10 and 26 bp. That could be the result of the lower sensitivity of SYBR detection. In all cases, the conjugates of AMP with DNA were cleaved less effectively according to band color brightness than the conjugates of SMP with DNA. At the same time, cis-cleavage efficiency in a solution without MPs was higher than in the case of the DNA-MP conjugates. The binding of MPs with cis-targets in the region (+23)–(+26) significantly decreased the cis-cleavage efficiency, despite that both cleavages (TS and NTS) could be realized. However, cis-cleavage proceeded with similar efficiency since (+30) position binding. We estimated the location of the DNA targets in the cleavage region of Cas12a using PDB data (6I1K) of the crystal structure of catalytically inactive FnCas12a in a complex with a crRNA and a dsDNA target [24]. According to the evidence that the cis and trans- activity of different Cas proteins are similar, we extrapolate features of a FnCas12 to the tested LbCas12a. Based on this structure, we proposed that Cas12 lobes cause steric obstacles for DNA sites located downstream of the R-loop. The lobes form a cavity that covers DNA within +26 to +29 nt from PAM (Section S10, Supporting Information). This consideration clarifies our fluorescent and electrophoretic data (Figure 4 and Figure S16) where the efficient cis-cleavage was reached when the 3′-end of PAM at NTS occurred for 30 bp or longer distances from the conjugation point. The increase in the distance between PAM 3′-end and the conjugation point up to 500 bp did not affect the cleavage efficiency in accordance with both experimental data (Figure 4) and consideration of the PDB model (Figure S18, Supporting Information). Finally, we investigated how close PAM can be located to the MP surface. We measured the cis-cleavage activity depending on PAM recognition at a different distance from the MP surface. The cis-cleaved IGS(II) fragment comprised two parts: (1) the same 5′-FAM-labeled distal region including an elongated spacer for gRNA2 recognition and PAM (126 bp), and (2) varied proximal region (adaptor with 0–100 bp length) following PAM and labeled with 5′-biotin attached to streptavidin–MP (Figure 1C). When Cas12 recognized and cleaved this DNA, FAM-labeled DNA was released and separated in the liquid phase. The results of cis-cleavage detected by fluorescence and gel electrophoresis of released IGS-FAM fragments are presented in Figure 5 and Figure S17, Supporting Information, Section S9. We are using the adaptor length, since 3 bp provided cis-cleavage with 20–30% for both MPs types (Figure 5A,B) according to fluorescence. We did not find any difference in cleavage efficiency for different DNA lengths. The kinetic measurements of cis-cleavage for conjugates of SMP with 3 and 30 bp length of the proximal region demonstrated saturation after 5 min (Figure 5C). The efficiency of cleavage was similar to end-point measurements. The same results were obtained through direct gel visualization of the released DNA fragments (Figure 5A,B and Figure S17). Thus, when the PAM end of the cis-target was attached to the MP, the MP’s surface did not interfere with the Cas12a in recognizing PAM adjoining the MP surface and subsequent cis-cleavage. The conjugates with adaptors >3 bp from (-4)T of PAM demonstrated identical results of cis-cleavage. To visualize the effects of changing the adaptor length, we also considered the PDB data 6I1K for the triple complex. The visualization showed that the (-7) DNA pair position that equals 3 bp from PAM is located beyond the Cas12a globule and thus is available for interactions (Figure S18A,D, Supporting Information). These results showed that the influence of the close location of the MP surface on PAM recognition was less than that on the cis-cleavage site close to the MP surface (Figure 4A). However, the cis-cleavages for both cis-targets groups showed the sharp change in the efficiency upon reaching an appropriate distance from the MP surface and similar constant efficiency (20–40%) for longer lengths. Summarizing all results about cis-cleavage, we concluded that the arrangement in the direction of the MP surface, PAM, and spacer was preferred for binding the cis-target to MPs. The minimal adaptor length following PAM required for this binding corresponded to 3 bp. The orientation of cis-targets on the MP surface affects the trans-cleavage efficiency. The conjugation point caused different locations of the activated Cas12a:gRNA:DNA-cis-target complex (Figure 1E,F). We compared the trans-cleavage of an FAM-dT15-BHQ1 probe for cis-targets attached to MPs through the spacer end (IGS(I))–streptavidin–MP conjugates) and PAM end (IGS(II))–streptavidin–MP conjugates) using the minimal ds-adaptor length for both (IGS(I)-10 and IGS(II)-3) (Section S11, Supporting Information). As a result, we found that both orientations of Cas12 were able to trans-cleave the FAM–dT15–BHQ1 target (Figure S19, Supporting Information). Wherein, the trans-cleavage activity of the Cas12a-complex which was released from the MP surface (corresponded DNA (IGS(I))–streptavidin–MP conjugates) was slightly but statistically significant and exceeded the activity of the Cas12a complex that remained bound to MPs (corresponded DNA (IGS(II))–streptavidin–MP conjugates. The revealed effectiveness of cis-cleavage of DNA attached to MPs could be useful for the design of an assay with a magnetic concentration of target dsDNA to increase assay sensitivity. Moreover, the obtained results are a reliable basis for the development of Cas12-based biosensors to detect non-DNA/RNA analytes. That can be realized when the MP–cis-target conjugate also carries a recognition receptor (for example, an antibody or an aptamer). In this case, the conjugate will be a transmitter between analyte recognition due to the receptor and signal generation due to trans cleavage to trans-cleavage by cis-activated Cas12a. Information about used materials is presented in Section S1, Supporting Information. A set of DNA probes with different lengths of the dsDNA adaptor (40, 80, 120, 160, 300, 500, and 1000 bp) and the same ss-15-dT tail connected through a PEG linker (C3) was synthesized through PCR (used primers are presented in Table S1, Figure S1, Supporting Information). The dsDNA adaptors were constructed on the base of the enhanced green fluorescent protein (eGFP) gene (the sequence data are presented in Section S2, Supporting Information) encoded in pGFP-N1 plasmid. The DNA probe with a 20 bp adaptor length was obtained by annealing. The detailed protocols of DNA probes production, purification, and characterization are presented in Section S2, Supporting Information. The DNA cis-target for recognizing gRNA-Cas12a was ribosomal intergenic spacer (IGS) from Dickeya solani (sequence of the fragment is presented in Section S3, Supporting Information). The cis-target with 596 bp length contained fragments of full-length IGS (342 bp), and flanked regions came from the pGEM-T-IGS plasmid [25]. Two groups of cis-targets with different lengths of the IGS fragment and FAM, biotin labels at the opposite 5′-ends. For the first group (IGS(I)), we assumed that the streptavidin–MP surface, 5′-biotinylated ds-adaptor, spacer for gRNA recognition, and PAM fragment were sequentially located. In this group, the length of the ds-adaptor was varied and comprised of 3, 6, 10, 26, 78, 178, 278, and 478 bp fragments (Section S3, Supporting Information). The IGS(I)-0 was constructed without the ds-adaptor, and the 5′-end of TS of the spacer was biotinylated for attachment to the streptavidin–MP surface. For the second group (IGS(II)), we assumed that the streptavidin–MP surface, 5′-biotinylated ds-adaptor, PAM fragment, and spacer were sequentially located. The length of the ds-adaptor was varied and comprised 3, 10, 30, and 100 bp (Section S3, Supporting Information). The IGS(II)-0 was constructed without the ds-adaptor, and the 5′-end of NTS of the PAM was biotinylated for the attachment to the streptavidin–MP surface. For both cis-target groups, detailed synthesis, purification and characterization are described in Section S3, Supporting Information, integrity and length were verified by electrophoresis (Figure S2, Supporting Information). The design of gRNAs was performed by CHOPCHOP version 3 online non-profit software [26] in the area of the IGS fragment. To obtain the designed gRNAs (gRNA1, gRNA2) recognizing the IGS, in vitro transcription was performed according to Lu et al. [27] with modifications. The sequences, detailed protocol, and characterization of the obtained gRNAs are described in Section S4, Supporting Information. Length and integrity of the gRNA were verified by electrophoresis (Figure S3, Supporting Information). Activity of the gRNA was confirmed by fluorescent trans-cleavage assay (Figure S4, Supporting Information). Primarily, the commercial streptavidin–MPs were characterized by transmission electronic microscopy (TEM) and dynamic light scattering (DLS) (Section S5, Supporting Information). These MPs were conjugated with biotin/FAM labeled DNA targets with different concentrations (25–200 nM for trans-targets and 20 or 1 nM for cis-targets). Un-bound DNA molecules were removed during the magnetic separation of the MPs. Saturation of the conjugated MPs was estimated by measurement of FAM fluorescence in both bound and unbound DNA fractions. The detailed protocol of the conjugation is described in Section S6.1, Supporting Information). Obtained conjugates were estimated by DLS. The loading of MPs was estimated within each set of measurements of trans and cis-activity and then calculated statistically. A premix of gRNA-Cas12a was made according to the NEB protocol with modifications: –66 nM of gRNA1 and 66 nM of EnGene LbCas12a (NEB, Ipswich, MA, USA) in NEB2.1 buffer were mixed and incubated at 25 °C for 10 min. Then, 3.3 nM of full-length IGS cis-target was added and incubated for 30 min at 37 °C to activate the LbCas12a. Subsequently, a 500 nM ROX-dT15-BHQ2 probe (1 µL) was added as an internal control of Cas12a activity. The reaction mix with activated Cas12 (30 µL) was added to the pellet of the DNA–streptavidin–MP conjugate (2 µL, 1% MPs, 100 nM DNA). The reaction continued with shaking at 37 °C for 30 min. The cis- and trans-cleavages were stopped by the addition of EDTA up to 50 mM. The DNA–streptavidin–MP conjugate and cleave-off ss-dT-FAM were separated using the magnetic holder. The pellet with conjugate was resuspended in 25 mM Tris-HCl, pH 9.0 with 50 mM NaCl. The supernatant with cleave-off ss-dT-FAM was mixed with 70 µL of the same buffer. The fluorescence of FAM (extinction 498 nm, emission 517 nm) and ROX (excitation 578 nm, emission 604 nm) of the samples were measured using a black microplate and measurement was completed by an EnSpire multimode plate reader (PerkinElmer, Waltham, MA, USA). The direct assessment of cis-cleavage was through the fluorescence of the cleaved cis-target DNA attached to MPs after interaction with gRNA-Cas12a. The premix of gRNA-Cas12a (30 µL, 66 nM gRNA1 (or gRNA2), 66 nM EnGene LbCas12a, incubation at 25 °C for 10 min) was added to the pellet of the cis-target DNA–streptavidin–MP conjugate (20 nM cis-targets DNA, 2 µL of 1% MP suspension). Cis-cleavage was at 37 °C for 60 min upon shaking. The reaction was stopped by the addition of 40 mM EDTA. The fluorescence of FAM in the MP pellet (bound cis-target) and the supernatant (cleaved cis-target) separated by the magnet was measured as described in Section 3.6. “Trans-cleavage of DNA attached to MPs by Cas12a” with a slight modification: using 3000 flashes to count the value of fluorescence. Additionally, the supernatants after cis-cleavage reactions were analyzed by gel electrophoresis in 2% agarose. The gels were stained by SYBR Gold and visualized by a GelDoc XR+ System (BioRad, Hercules, CA, USA) (gel scans are presented in Figures S16 and S17). The densities (D) of the lanes were estimated by TotalLab Quant (TotalLab Ltd., Great Britain, Newcastle upon Tyne, UK) and normalized by the relative density of the 100 bp lane of the ladder. All cis- and trans-cleavage reactions were performed at least 3 times. Mean values, standard deviations (SD), and relative SD were calculated by OriginProLab 11 (OriginLab, Northampton, MA, USA). Unpaired t-tests were performed for each MP conjugate (between gRNA1 and gRNA2-dependent reaction) by GraphPad (GraphPad Software, Boston, MA, USA). The full scheme of the data processing is presented in Figure S9, Supplementary Information. We proposed the structures of trans- and cis-DNA targets based on the rigid dsDNA adaptor that distances the cleavage site (ss-15dT) from the MP surface. We found the dependence of cleavage efficiency on dsDNA adaptor lengths. The efficiency of trans-cleavage of the ss-15dT is directly correlated with the length of dsDNA adaptor in the case of SMPs. The use of AMPs demonstrated the bell-curve dependence of trans-cleavage efficiency on the dsDNA adaptor length. The second found effect refers to the influence of the orientation of cis-targets on the MP surface for the recognition by Cas12a–gRNA complexes. The conjugation of the cis-DNA target in the upstream or downstream direction from a PAM affects the different stages of cis-activation, namely scanning of dsDNA or TS/NTS cleavage. The sequential arrangement of an adaptor, PAM, and a spacer was found to be preferable in providing the minimum length of the adaptor (3 bp). The optimum of trans-targets conjugated with MPs and cleaved by Cas12a starts at 40 nm (120 bp). That is greater than the found optimum for cis-cleavage, which starts at 3.4 nm (10 bp) for the IGS(I)) cis-target and 1.02 (3 bp) for the IGS(II)) cis-target. Perhaps one reason for this difference is that the presence of the cis-target in a complex with Cas12a–gRNA makes the complex bigger and more charged. The DNA cis-target can confine the access of the active site to a trans-target located near the surface of the MP. The revealing optimal structures of DNA immobilized on the MPs for Cas12-based biosensors will assist in designing other dispersed carriers. The found optimal structures for DNA trans-targets can be used in Cas12 biosensors combined with MPs to detect any DNA analyte that will be a cis-target or RNA analyte after its reverse transcription. Additional advantages can be obtained by changing fluorescein at the end of the trans-target to a label detectable in lower concentrations that provides greater sensitivity of the assay, for example, a quantum dot, or nanozyme others. The found optimal structures for the DNA cis-target can be effectively used in hybrid assay formats when the MP-cis-target conjugate arises as a response to some reaction (for example, the specific recognition of an analyte by antibody or aptamer) and triggers Cas12 trans-activity. Therefore, the obtained results provide more opportunities for the Cas12-based biosensors with surface-attached DNA targets.

PMC10003272

Haiyang Yu,Jing Pan,Siyue Zheng,Deyang Cai,Aixiang Luo,Zanxian Xia,Jufang Huang

Hepatocellular Carcinoma Cell-Derived Exosomal miR-21-5p Induces Macrophage M2 Polarization by Targeting RhoB

27-02-2023

HCC-derived exosomes,miR-21-5p,macrophages,polarization,RhoB

M2-like polarized tumor-associated macrophages (TAMs) are the major component of infiltrating immune cells in hepatocellular carcinoma (HCC), which have been proved to exhibit significant immunosuppressive and pro-tumoral effects. However, the underlying mechanism of the tumor microenvironment (TME) educating TAMs to express M2-like phenotypes is still not fully understood. Here, we report that HCC-derived exosomes are involved in intercellular communications and exhibit a greater capacity to mediate TAMs’ phenotypic differentiation. In our study, HCC cell-derived exosomes were collected and used to treat THP-1 cells in vitro. Quantitative polymerase chain reaction (qPCR) results showed that the exosomes significantly promoted THP-1 macrophages to differentiate into M2-like macrophages, which have a high production of transforming growth factor-β (TGF-β) and interleukin (IL)-10. The analysis of bioinformatics indicated that exosomal miR-21-5p is closely related to TAM differentiation and is associated with unfavorable prognosis in HCC. Overexpressing miR-21-5p in human monocyte-derived leukemia (THP-1) cells induced down-regulation of IL-1β levels; however, it enhanced production of IL-10 and promoted the malignant growth of HCC cells in vitro. A reporter assay confirmed that miR-21-5p directly targeted Ras homolog family member B (RhoB) 3′-untranslatedregion (UTR) in THP-1 cells. Downregulated RhoB levels in THP-1 cells would weaken mitogen-activated protein kinase (MAPK) axis signaling pathways. Taken together, tumor-derived miR-21-5p promote the malignant advance of HCC, which mediated intercellular crosstalk between tumor cells and macrophages. Targeting M2-like TAMs and intercepting their associated signaling pathways would provide potentially specific and novel therapeutic approaches for HCC treatment.

Hepatocellular Carcinoma Cell-Derived Exosomal miR-21-5p Induces Macrophage M2 Polarization by Targeting RhoB M2-like polarized tumor-associated macrophages (TAMs) are the major component of infiltrating immune cells in hepatocellular carcinoma (HCC), which have been proved to exhibit significant immunosuppressive and pro-tumoral effects. However, the underlying mechanism of the tumor microenvironment (TME) educating TAMs to express M2-like phenotypes is still not fully understood. Here, we report that HCC-derived exosomes are involved in intercellular communications and exhibit a greater capacity to mediate TAMs’ phenotypic differentiation. In our study, HCC cell-derived exosomes were collected and used to treat THP-1 cells in vitro. Quantitative polymerase chain reaction (qPCR) results showed that the exosomes significantly promoted THP-1 macrophages to differentiate into M2-like macrophages, which have a high production of transforming growth factor-β (TGF-β) and interleukin (IL)-10. The analysis of bioinformatics indicated that exosomal miR-21-5p is closely related to TAM differentiation and is associated with unfavorable prognosis in HCC. Overexpressing miR-21-5p in human monocyte-derived leukemia (THP-1) cells induced down-regulation of IL-1β levels; however, it enhanced production of IL-10 and promoted the malignant growth of HCC cells in vitro. A reporter assay confirmed that miR-21-5p directly targeted Ras homolog family member B (RhoB) 3′-untranslatedregion (UTR) in THP-1 cells. Downregulated RhoB levels in THP-1 cells would weaken mitogen-activated protein kinase (MAPK) axis signaling pathways. Taken together, tumor-derived miR-21-5p promote the malignant advance of HCC, which mediated intercellular crosstalk between tumor cells and macrophages. Targeting M2-like TAMs and intercepting their associated signaling pathways would provide potentially specific and novel therapeutic approaches for HCC treatment. HCC is the most common form of primary liver cancer, with rapid progression, poor prognosis, and a high risk of resistance and recurrence [1]. Although great advances have been made in surgical resection, liver transplantation, radiofrequency ablation, and other non-surgical interventions, the prognosis of most HCC patients remains unsatisfactory, with a 5-year survival rate of approximately 20% [2]. Thus, new therapeutic approaches for HCC are still in urgent need. In recent years, immunotherapy has exhibited a great potential in treating malignant tumors. It is considered an effective and safe approach for precision medicine-based treatment of HCC. However, only a small portion of patients benefit from these anti-HCC therapies, which are accompanied by resistance and several immune-related adverse events [3]. For large, solid tumors, it is hard for effector lymphocytes to enter the tight spaces between tumor tissues. Moreover, TME can weaken the effect of effector lymphocytes by secreting a series of inhibitors. TME is a complex assembly of a variety of cell types, including macrophages and monocytes, among the tumor-associated myeloid cell infiltrates, which mediate the function of immunotherapy [2]. Macrophages are an important part of innate immunity and a key factor of adaptive immunity initiation. Compared with normal macrophages, TAMs are imperfectly differentiated macrophages prone to immunosuppressive phenotypes [4]. Under the effect of multi-factors, macrophages are recruited into tumor tissue and educated to be important accomplices in promoting malignant progression of tumor. Various cytokines in TME are extremely important for the recruitment of macrophages. Chemokine axes such as C-C motif chemokine ligand 2 (CCL-2)/C-C motif chemokine receptor 2 (CCR2) and CCL-5/CCR5 can recruit monocytes/macrophages from the blood to the tumor region. IL-10 and macrophage colony stimulating factor (M-CSF) secreted by tumor cells can also promote the migration of macrophages to tumor sites [5]. Furthermore, in the latest reports, exosomes are thought to be involved in this process, which has been demonstrated in a variety of tumors [6,7,8]. Exosomes, measuring from 30 to 150 nm in diameter, are microvesicles formed in multivesicular bodies, which release exosomes into the extracellular milieu by fusing with cytomembranes [9,10]. Exosomes can be produced by various types of cells and serve as mediators in intercellular communications by transporting information cargo, such as proteins, lipids, and nucleic acids [11]. Specific proteins highly enriched in exosomes, such as Tsg101, CD63, Hsp70, CD9, and CD81, are usually used as markers to identify exosomes [12]. Numerous research reports have pointed out that exosomes mediate regulation of the phenotypes of TAMs in TME [6,7,8]. In our study, we investigated the effect of tumor cell-derived exosomes on macrophages and identified the critical tumor-derived exosomal miRNA’s function in the polarization of M2-like macrophages on the basis of an analysis of databases and in vitro studies. It offers new opportunities for potential therapeutic strategies of targeting TAM in HCC. TAMs are a highly heterogeneous population with different functions in HCC, which poses the challenge to the therapeutic approaches targeting TAMs. The emergence of single-cell RNA sequencing (scRNA-seq) provides us with a powerful tool for the investigation of TAM subtypes and their interaction in TME. We utilized the online tool at “http://cancer-pku.cn:3838/HCC/ (accessed on 25 August 2022)”, provided by Zemin Zhang lab at Peking University, to identify the biomarkers of macrophage subpopulation, which are specifically distributed in normal or tumor tissues of HCC. Referring to the analysis of datasets, we identified three representative marker genes of a subpopulation of TAMs in HCC, including CD68, CD5L, and mannose receptor C-type 1 (MRC1). The heatmaps of marker expression on the reduced dimensions showed that CD68 is the classical biomarker that is highly expressed by a large majority of macrophages; however, CD5L and MRC1 are differentially distributed with specific expression in adjacent non-malignant or tumor tissue (Figure 1A,B). CD5L is a secreted protein mainly expressed by macrophages in lymphoid and inflamed tissues [13]. It is considered an innate immune effector response to foreign infection [14]. MRC1 is recognized as a marker of M2-like polarized macrophages, which are highly expressed in TAMs in HCC [15,16]. Further, MRC1+ macrophages are much more abundant in tumor than in normal tissues, which is consistent with previous studies [17]. We then used the publicly available dataset from the Tissue and Pathology sections of the Human Protein Atlas “https://www.proteinatlas.org/ (accessed on 25 August 2022)”to analyze the correlation between the infiltration of TAM subtypes and the prognosis of patients. In most tumor tissue, we observed high level CD68+ and MCR1+ macrophage infiltration, and both of these are associated with an unfavorable prognosis of HCC. In some of the HCC tissues, we found much CD5L+ macrophage infiltration; however, the density of CD5L-positive macrophages is normally associated with a better prognosis (Figure 1C). Therefore, we believe that the accumulation of M2-like macrophages in HCC is most likely the efficient factor for the malignant progression of tumors. In light of the fact that exosome secretion is an important way for tumors to shape the TME, it rationally leads one to question whether exosomes participate in promoting the changes of macrophage polarity. We isolated and purified exosomes from conditioned media of tumor cell lines (HepG2 and Huh7) through the standard exosome isolation method of ultrafiltration concentration and precipitation. The shapes of the structures and size distributions of the isolated exosomes were identified using electron microscopy and a Mastersizer (Figure 2A,C). In addition, the detection of characteristic Hsp70 and TSG101 further verified that the isolated particles were exosomes (Figure 2B). In in vitro study, we treated the THP-1 cells with phorbol 12-myristate 13-acetate (PMA) to differentiate into macrophages (Figure 2D,E) and co-cultured these with tumor-derived exosomes interferon-γ (IFN-γ)/lipopolysaccharide (LPS) or IL-4. qPCR results indicated that the effect of tumor-derived exosomes is very similar to that of IL-4, which efficiently increased the immunosuppressive factors, including TGF-β1 and IL-10 (Figure 2F). Moreover, we also observed exosomal dependence of associated cytokine production. It suggests that tumor-derived exosomes are potential effectors of promoting M2-like polarization of macrophages in TME. To understand how tumor-derived exosomes regulate macrophage polarization by their cargoes, we analyzed associated data from The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. Firstly, we screened the top 30 highly expressed miRNAs from the database (GSE106452) by heatmap, in which all of the exosomal miRNA are derived from the culture supernatants of HCC cell lines (CSQT-2, HCC-LM3, HepG2, and MHCC-97L) (Figure 3A). We then analyzed the differentially expressed miRNAs in tumor and adjacent tissue in the TCGA Liver Hepatocellular Carcinoma (LIHC) dataset (Figure 3B). Combining the result sets of two queries by intersection, we found two potential efficient factors in the induction of macrophage polarization: mir-21-5p and mir-1915-3p (Figure 3C). According to the TCGA LIHC dataset, there is a proof that mir-21-5p is highly expressed in HCC tumor tissue with a worse prognosis (Figure 3D,E). Therefore, we hypothesized that mir-21-5p probably plays a key role in regulating macrophage M2-like polarization. To further verify the prediction, we treated THP-1 cells with Huh-7 exosomes that were labeled with PKH67. We observed that tumor-derived exosomes accumulated in macrophages, and the levels of mir-21-5p were significantly upregulated (Figure 4A,B). To understand the effects of mir-21-5p in macrophages, we transfected mir-21-5p mimics into THP-1 cells, and a supernatant was used to co-culture with hepatic tumor cells. The results indicated that overexpressed mir-21-5p can induce the production of IL-10 in a high level and promote the proliferation of tumor cells (Figure 4C,D), consistent with our previous studies. In order to identify the target of miR-21-5p in M2-like polarization of TAMs in HCC, we made a prediction using bioinformatics tools. The expression data of genes were downloaded from TCGA LIHC project. We used a Pearson correlation coefficient analysis to identify associated genes that are highly correlated with miR-21-5p in HCC. These genes were further confirmed by calculating the specific binding sequence of associated genes with miRanda. We then intersected the results with the data that we retrieved from starBase 3.0 “https://starbase.sysu.edu.cn/index.php (accessed on 6 September 2022)”. There are nine potential target genes we obtained, including CPEB3, NIPAL1, RhoB, PPP1R3B, CFL2, SLC39A14, KLHL15, SLC31A1, and KLF9 (Figure 5A). On the other hand, we performed analysis of differently expressed genes (DEGs) between M1 and M2 subtypes of macrophage groups in two publicly available datasets (GSE66805, GSE95405). A total of 204 DEGs were identified in both of the datasets, including 110 upregulated genes and 94 downregulated genes (Figure 5B). Gene ontology (GO) enrichment analysis showed that most of these differentially expressed genes were related to inflammation and immune responses (Figure 5C), which is consistent with previous studies [18,19]. To further declare the exact target of exosomal miR-21-5p in regulating macrophage polarization. We used the STRING to construct the network relevant to the lists of target genes and DEGs, and the hub genes were identified in Cytoscape. The results indicated that SRC, a tyrosine kinase involved in macrophage-related inflammatory responses, is most likely a key hub gene in macrophage polarization. SRC is related to tumor suppressor factors, monocyte-macrophages and T cell chemokines by interacting with IL-15, colony stimulating factor 1 (CSF1), C-C motif chemokine ligand 5 (CCL-5), etc. (Figure 5D). Meanwhile, we found that RhoB is closely related to SRC and may be a potential target for mir-21-5p in macrophage M2 polarization. To confirm our prediction, we transfected miR-21-5p mimics into THP-1 cells and examined expression of RhoB using Western-blot analysis. Comparing with a control group, we observed that RhoB’s level was significantly downregulated after transfection (Figure 6B). To determine whether miR-21-5p targets RhoB directly, we performed a reporter assay. The wild type and the mutated binding site of miR-21-5p of RhoB were cloned into luciferase vectors (Figure 6A). The result revealed that luciferase activity decreased markedly in THP-1 cells, carrying the wild type binding site vector, in the presence of miR-21-5p. However, cells containing the mutated binding site vector did not show such repression (Figure 6C). These results reveal that RhoB is a direct target of miR-21-5p in M2-like polarization of macrophages. To understand the function of RhoB in macrophage polarization, we knocked down RhoB with small interfering RNAs (siRNAs) in THP-1 cells, and the effect was identified using immunoblotting analysis. As shown in Figure 6D, the expression of RhoB was inhibited in THP-1 cells by treatment with siRNAs. Moreover, we found that the levels of SRC were decreased. We also detected the activation of the MAPK pathway, which is involved in the regulation of IL-10 production. Phosphorylation of MAPK signaling in macrophages is considered important for tumor-promoting cytokine production, and macrophage migration [20]. Therefore, we detected the phosphorylation of an extracellular signal-regulated kinase (Erk). The result revealed that the activation of Erk signaling upregulated in response to the suppression of RhoB. These data suggested that RhoB is a direct downstream target of miR-21-5p in regulating macrophage polarization. To further confirm that HCC-derived exosomal miR-21-5p is the predominant effector in macrophage M2 polarization in TME, we designed a miR-21-5p sponge to suppress the levels of miR-21-5p. A miR-21-5p sponge sequence was constructed in lentivector. The construction virus was produced by transfecting lentiviral transfer and packaging plasmids into 293T cells, and the supernatant was harvested to treat THP-1 cells for 48 h before they were seeded on upper transwells. Meanwhile, HCC tumor cells were seeded on 24well plates. Subsequently, the two kinds of cells were co-cultured for 48 h. The effects on THP-1 cells were identified by immunoblotting analysis. To confirm the function of the sponge, we detected the expression level of B-cell lymphoma-2 (Bcl-2) and phosphatase and tensin homolog (PTEN), which were reportedly the targets of miR-21-5p in previous studies [21,22]. The results showed that downregulation of miR-21-5p in hepatic tumor cells limited the decrease in RhoB in macrophages. Similar results were also observed in the miR-21-5p sponge group (Figure 7B,C). It indicated that HCC-derived exosomal miR-21-5p played a key role in promoting M2-like polarization of macrophages in TME. Blocking exosomal miR-21-5p signaling will help attenuate the education of TME to macrophages and slow the malignant progression of HCC. In our study, we have shown that a large majority of HCC cases are with unfavorable prognosis in the background of accumulated M2-like TAM infiltration. TAMs are the most abundant immune cells in tumor tissues and M2-like macrophages are the predominant subtype. TAMs have been proved to exhibit significant immunosuppressive effects and promote tumor growth, angiogenesis, invasion, and metastasis by acting as a driver of M2-polarized macrophages [23]. It is commonly believed that TAMs are mainly derived from circulating monocytes. Blood monocytes are recruited into the tissue where they differentiate into macrophages or dendritic cells. However, recent research has showed that up to 50% of TAMs originate from resident macrophages in mouse models. Recent studies have proven that TAMs derived from hematopoietic stem cells (HSCs) are involved in immunosuppression and antigen presentation, while embryo-derived TAMs are responsible for angiogenesis in TME [24,25,26]. However, a growing number of studies show that TAM phenotypes are not fixed and that their dynamic alterations are implicated in hepatocarcinogenesis and its progression. The polarization of macrophages into M1 or M2 macrophages depends on the microenvironments [4,27,28]. In recent years, exosomes have been implicated in the regulation of this process. To certify our hypothesis, we treated macrophages with tumor-derived exosomes in vitro. We found that tumor-derived exosomes lead to the up-regulation of mir-21-5p in macrophages and promoted M2-like macrophage cytokines production. miR-21-5p, an anti-apoptotic regulator [29], is widely present in HCC tissues and is closely associated with poor clinical prognosis [30]. Previous studies report that miR-21-5p promotes the differentiation of myeloid monocytes into immunosuppressive-like macrophages [31]. In our study, we noted that modulating the level of miR-21-5p will affect the macrophage polarization. Emerging evidence supports the key roles of miRNA in macrophage polarization during HCC pathogenesis, including miR155, miR-149-5p, TUC339, miR-125a, etc. [32,33,34,35]. In addition, Li et al. found that exosomal miR-21-5p secreted by lung stromal cells could inhibit M1 polarization of alveolar macrophages and down-regulate the expression levels of IL-8, IL-1β, IL-6 and TNF-α, reducing the inflammatory response in the lungs [36]. In the study of Sahraei et al., they downregulated the expression of miR-21 in TAMs by carrier peptides, and found that tumor growth was inhibited and the anti-tumor immune response was reactivated [37]. We then predicted the target genes of miRNAs using bioinformatics and demonstrate that mir-21-5p regulates the MAPK signaling pathway in macrophages by targeting RhoB. RhoB is a member of the Rho subfamily of small GTPases, which switch the molecular cycle between an inactive GDP-bound form and active GTP-bound form [38]. RhoB has a high turnover rate, and it is a key regulator of diverse cellular processes, including the response to epidermal growth factor TGFβ, SRC activation [39]. Previous studies have shown that RhoB can affect macrophage morphology, adhesion, and migration by reducing the expression of β2 and β3 integrins on cell surfaces [40]. This may be one of the reasons for the massive infiltration of TAMs in tumor tissues. Recently, increasing evidence suggests that RhoB plays a role in the immune and inflammatory responses. One group of researches demonstrated that, upon LPS stimulation, the expression of RhoB increased and regulated toll-like receptor (TLR) activation via binding to major histocompatibility complex class II (MHCII) in macrophages, but they did not demonstrate whether RhoB affected MHCII expression at endosomal membranes [41]. In future, we will detect the relationship between RhoB and MHC II in macrophages, and this could give new insights into the underlying mechanism of RhoB in regulating antigen presentation. In conclusion, our study demonstrated that RhoB serves as a potent target of HCC-derived miR-21-5p signaling pathways by interacting with Erk in M2-like macrophages and enhancing the production of pro-tumorous cytokines. Therefore, targeting M2 macrophages and intercepting their associated signaling pathways is a potential specific and novel therapeutic approach for HCC treatment. Antibodies against human HSP 70, β-Actin, Tubulin, and GAPDH were from Santa Cruz Biotechnology (Dallas, TX, USA). The TSG 101 and RhoB antibodies were from Protein-tech (Wuhan, Hubei, China). The SRC, Bcl-2, PTEN (138G6), Erk, and pErk (Thr202/Tyr204) antibodies were from Cell Signaling Technology (Danvers, MA, USA). Horseradish peroxidase (HRP)-conjugated secondary antibodies were from CWBIO (Changping, Beijing, China). Protease inhibitor cocktail was from Thermo Scientific (Waltham, MA, USA). PMA was from Sigma-Aldrich (St. Louis, MO, USA). PHK67 was from Umibio-tech (Shanghai, China). The human THP-1 monocytic cell line was provided by Procell Life Science & Technology Co, Ltd. (Wuhan, Hubei, China). The human hepatocellular carcinoma cell lines HepG2, Hep3B, and HuH7 were obtained from American Type Culture Collection (ATCC, Manassas, VA, USA). THP-1 cells were cultured in RPMI-1640 medium supplemented with 10% FBS, 1% penicillin/streptomycin, and 0.05mM β-mercaptoethanol. Hepatocellular carcinoma cell lines were cultured in DMEM medium supplemented with 10% FBS and 1% penicillin/streptomycin. THP-1 cells (1 × 106) were incubated with 200 ng/mL PMA for 48 h to induce them into macrophages. These cells were maintained in an incubator with 5% CO2 at 37 °C. Cells were lysed on ice with RIPA buffer and protease and phosphatase inhibitor for 20 min. Lysate was centrifuged at 13,000 rpm for 15 min at 4 °C and the supernatant was transferred to a fresh tube. Protein concentration was qualified by a BCA Protein Assay kit (CWBIO, Beijing, China). Approximately 10 mg of protein per sample was loaded onto 12% SDS–PAGE gels and then transferred onto nitrocellulose membrane. The membrane was blocked with 5% non-fat dry milk in Tris-buffered saline for 1 h, and then incubated with primary antibodies at 4 °C for overnight, following by incubation with the horseradish peroxidase–conjugated secondary antibody at room temperature. Finally, the membranes were visualized with COMPLEXTM 2000. mRNA: Total RNA was extracted from cell lines using TRIzol reagent (CWBIO, Beijing, China) and reverse transcribed into cDNA using a Hifair® III 1st Strand cDNA Synthesis Kit (YEASEN, Shanghai, China). Real-time PCR was performed using NovoStart® SYBR High-Sensitivity qPCR SuperMix (Novoprotein Scientific Inc., Suzhou, Jiangsu, China). All of the primers were purchased from Tsingke Biotechnology Co., Ltd. (Beijing, China). The primers for amplification were: TNF-α, forward: 5′-CCTCTCTCTAATCAGCCCTCTG-3′, reverse: 5′-GAGGACCTGGGAGTAGATGAG-3′; IL-1β, forward: 5′-ATGATGGCTTATTACAGTGGCAA-3′, reverse: 5′-GTCGGAGATTCGTAGCTGGA-3′; IL-10, forward: 5′-GACTTTAAGGGTTACCTGGGTTG-3′, reverse: 5′-TCACATGCGCCTTGATGTCTG-3′; TGF-β1: forward: 5′-CTAATGGTGGAAACCCACAACG-3′, reverse: 5′-TATCGCCAGGAATTGTTGCTG-3′; GAPDH: forward: 5′-GGAGCGAGATCCCTCCAAAAT-3′, reverse: 5′-GGCTGTTGTCATACTTCTCATGG-3′. CCL4: forward: 5′-CTGTGCTGATCCCAGTGAATC-3′ reverse: 5′-TCAGTTCAGTTCCAGGTCATACA-3′. Quantitative PCR was performed with Bio-Rad C1000 Thermal Cycler. Each amplification reaction was checked for the absence of nonspecific PCR products using melting curve analysis. The threshold cycle numbers obtained from qPCR were compared to generate the relative copy number as described by Livak and Schmittgen (2001) [42]. Data were normalized against GAPDH. miRNA: After total RNA extraction, a tailing reaction was performed using E. coli Poly(A) Polymerase (NEB# M0276, Ipswich, MA, USA) and incubated at 37 °C for 30 min. Reverse transcription was performed using miRNA random primers. Real-time PCR was performed like mRNA. Data were normalized against U6. The primers for amplification were: mir-21-5p: forward: 5′-GCAGTAGCTTATCAGACTGATG-3′, reverse: 5′-GGTCCAGTTTTTTTTTTTTTTTCAAC-3′; U6: forward: 5′-CTCGCTTCGGCAGCACATA-3′, reverse: 5′-AACGATTCACGAATTTGCGT-3′. The miR-21-5p mimics (Gene Pharma, Suzhou, Jiangsu, China) were transfected into macrophages with Lipofectamine 2000 reagent (Invitrogen, Grand Island, NY, USA) at a final concentration of 40 nM according to the manufacturer’s instructions. The miR-21-5p mimic sequences were: sense: 5′-UAGCUUAUCAGACUGAUGUUGA-3′; antisense: 5′-AACAUCAGUCUGAUAAGCUAUU-3′. After transfection for 48 h, we collected whole-cell lysates for Western Blot or qPCR. Cells were seeded in 24-well plates at a density of 2 × 104 cells per well in 500 μL. The medium was changed to a medium of macrophages followed by miRNA transfection after cells were attached. Cell viability was assessed by Cell Counting Kit-8 (CCK-8) (APExBIO, Shanghai, China) after 1 day or 2 days. THP-1 cells (1 × 104) were seeded into 24-well plates and transiently transfected with the different expression vectors together with complex of reporter plasmids and pCMV-β-galactosidase (β-Gal) using Lipofectamine 2000 (Invitrogen, Grand Island, NY, USA). Twenty-four hours after transfection, the cells were transfected with mir-21-5p mimics. Cells were then harvested and lysed on ice. Centrifuged supernatant (10,000 r.p.m, 10 min) was used to measure luciferase according to the manufacturer’s protocol (Promega, Madison, MI, USA). The exosomes were separated from the cell culture supernatant by ultrafiltration concentration and an ultracentrifugation method. To eliminate the effect of debris on the isolation of exosomes, the samples including cell culture supernatant were centrifuged at 300× g for 10 min, then 2000× g for 10 min. The supernatant were filtered with a 0.22 μm filter, then concentrated with 100 kDa ultrafiltration tube (Millipore, Billerica, MA, USA). The collected supernatants were centrifuged at 100,000× g for 70 min by ultra-centrifuge (Beckman, Indianapolis, IN, USA) twice. The precipitate was resuspended by particle-free PBS. After that, transmission electron microscopy was used to visualize the appearance of exosomes at a proportional scale of 0.2 μm. Furthermore, the exosomes’ size was detected using a Mastersizer 3000 (Malvern, Worcs, UK). The protein content of exosomes was qualified by a BCA Protein Assay kit (CWBIO, Beijing, China). Data of HCC cell-derived exosomal miRNA were downloaded from the database GSE106452. We listed the top 30 highly expressed miRNAs by heatmap. TCGA LIHC data were analyzed by DESeq2 to identify differentially expressed miRNA genes between tumor and normal tissues in HCC (log2 FC > 1, FDR < 0.05). We determined the miRNAs that were highly expressed in both datasets by combining the results. The TCGA LIHC data were used to test the correlation of miR-21-5p and patient survival. The gene expression data and the clinical data were downloaded from UCSC Xena “http://xena.ucsc.edu/ (accessed on 12 September 2022)”. The differentiations of miR-21-5p expression have been shown by violin plot in normal and primary tumor tissues (Welch’s t-test, p = 2.064 × 10−26, t = −16.39). The primary tumor tissue samples were grouped into high and low expression groups by the mean value (log2 [RPM + 1] = 17.85). Kaplan–Meier survival curves were plotted to show differences in survival time (log-rank test statistics = 5.352, p = 0.02). Functional enrichment analysis of DEGs was performed by DAVID (The Database for Annotation, Visualization and Integrated Discovery) to identify GO (Gene Ontology) annotation. The data were download from GES 66805 and GES 95405. The results of DEGs were showed by heatmaps (log2 FC > 1, FDR < 0.05), and scatter plots was drawn using ggplot2 packages. The protein–protein interaction (PPI) network of the target genes of mir-21-5p and DEGs was constructed using the online database STRING “https://string-db.org/ (accessed on 12 September 2022)”, and the functional interactions between proteins were analyzed. The combined score ≥ 0.400 is considered significant. We used Cytoscape to analyze hub genes, which are important nodes for visualization of PPI networks with many interactions. Data analysis was performed using the Graphpad Prism software version 7. Each experiment was carried out in triplicate, at least, and all results were presented as mean ± s.d. χ2-Test and Student’s t-test were used to assess statistical significance. A value of p < 0.05 was considered significant.

PMC10003297

Naoko Honma,Tomio Arai,Yoko Matsuda,Yosuke Fukunaga,Masaaki Muramatsu,Shinobu Ikeda,Yuri Akishima-Fukasawa,Noriko Yamamoto,Hiroshi Kawachi,Yuichi Ishikawa,Kengo Takeuchi,Tetuo Mikami

Estrogen Receptor-β Gene Cytosine-Adenine (ESR2-CA) Repeat Polymorphism in Postmenopausal Colon Cancer

24-02-2023

age,colon cancer,estrogen,estrogen receptor-β,ESR2-CA repeat polymorphism,postmenopausal women,mismatch repair protein

The pathobiological role of estrogen is controversial in colorectal cancer. Cytosine-adenine (CA) repeat in the estrogen receptor (ER)-β gene (ESR2-CA) is a microsatellite, as well as representative of ESR2 polymorphism. Though its function is unknown, we previously showed that a shorter allele (germline) increased the risk of colon cancer in older women, whereas it decreased it in younger postmenopausal women. ESR2-CA and ER-β expressions were examined in cancerous (Ca) and non-cancerous (NonCa) tissue pairs from 114 postmenopausal women, and comparisons were made considering tissue types, age/locus, and the mismatch repair protein (MMR) status. ESR2-CA repeats <22/≥22 were designated as ‘S’/‘L’, respectively, resulting in genotypes SS/nSS (=SL&LL). In NonCa, the rate of the SS genotype and ER-β expression level were significantly higher in right-sided cases of women ≥70 (≥70Rt) than in those in the others. A decreased ER-β expression in Ca compared with NonCa was observed in proficient-MMR, but not in deficient-MMR. In NonCa, but not in Ca, ER-β expression was significantly higher in SS than in nSS. ≥70Rt cases were characterized by NonCa with a high rate of SS genotype or high ER-β expression. The germline ESR2-CA genotype and resulting ER-β expression were considered to affect the clinical characteristics (age/locus/MMR status) of colon cancer, supporting our previous findings.

Estrogen Receptor-β Gene Cytosine-Adenine (ESR2-CA) Repeat Polymorphism in Postmenopausal Colon Cancer The pathobiological role of estrogen is controversial in colorectal cancer. Cytosine-adenine (CA) repeat in the estrogen receptor (ER)-β gene (ESR2-CA) is a microsatellite, as well as representative of ESR2 polymorphism. Though its function is unknown, we previously showed that a shorter allele (germline) increased the risk of colon cancer in older women, whereas it decreased it in younger postmenopausal women. ESR2-CA and ER-β expressions were examined in cancerous (Ca) and non-cancerous (NonCa) tissue pairs from 114 postmenopausal women, and comparisons were made considering tissue types, age/locus, and the mismatch repair protein (MMR) status. ESR2-CA repeats <22/≥22 were designated as ‘S’/‘L’, respectively, resulting in genotypes SS/nSS (=SL&LL). In NonCa, the rate of the SS genotype and ER-β expression level were significantly higher in right-sided cases of women ≥70 (≥70Rt) than in those in the others. A decreased ER-β expression in Ca compared with NonCa was observed in proficient-MMR, but not in deficient-MMR. In NonCa, but not in Ca, ER-β expression was significantly higher in SS than in nSS. ≥70Rt cases were characterized by NonCa with a high rate of SS genotype or high ER-β expression. The germline ESR2-CA genotype and resulting ER-β expression were considered to affect the clinical characteristics (age/locus/MMR status) of colon cancer, supporting our previous findings. Estrogens have attracted attention as factors affecting the risk and outcome of colorectal cancer (CRC) [1,2,3,4,5,6]. A large number of in vitro and in vivo studies have suggested the inhibitory role of estrogens against CRC [1,2,4,7,8], whereas a fewer, but significant, number of studies have reported unfavorable effects on CRC [6]. CRC characteristics are affected by sex, age, and tumor locus. The proportion of right-sided colon cancer increases as age increases, and is consistently higher in women than men regardless of age [6]. Histologically, the proportion of medullary/mucinous carcinoma (Med/Muc), which frequently locate right-sided, increases with age. Microsatellite instability (MSI), a representative carcinogenic mechanism caused by deficiency of mismatch repair protein (dMMR), is associated with CRC of women, right-sidedness, or Med/Muc histology. Further, the concentration of estrogens drastically fluctuates throughout a woman’s lifetime: much higher in premenopausal women, but much lower in postmenopausal women than men. In such context, a systematic study considering sex, age, tumor locus, or MMR status is needed to appropriately understand the pathobiological role of estrogens in CRC. In normal colorectal epithelium, estrogen receptor (ER)-β, the second ER, is the main ER, suggesting that estrogen exerts its function through ER-β. ER-β expression has been reported to decrease according to canceration or cancer progression, suggesting that the estrogen-ER-β signaling malfunction is related to the carcinogenesis/development of CRC [1]. Further, expression of ER-β1, a wild type ER-β, has been reportedly higher in MSI-positive than MSI-negative CRC [1,9]. In an epidemiological study, estrogen has been suggested to reduce MSI-negative or ER-β-positive CRC, but not MSI-positive or ER-β-negative CRC [10,11]. These findings suggest that estrogen affects the tumor types generated, as well as behaves differently according to the status of MSI or ER-β. We recently examined the estrogen concentration and expression of the estrogen receptor (ER)-β (the main ER in colorectum) in pairs of colon cancerous/non-cancerous tissues (Ca/NonCa) from postmenopausal women. In such a study setting, we could avoid the effect of gender difference or menopausal status, and could focus on the effect of age, tumor locus, or tumor type. ER-β reduction in Ca compared with its NonCa counterpart, which has been repeatedly reported, was observed only in left-sided cases involving patients younger than 70 y/o, cases with a non-medullary/mucinous (Med/Muc) histology, or MMR-proficient (pMMR) cases, suggesting that the inhibitory role of estrogens is limited to these types of tumors. By contrast, ER-β-positivity, higher estradiol (E2) concentration, dMMR, and Med/Muc histology were closely related to right-sided tumors in women 70 y/o or older (≥70Rt), and those factors were also closely related to each other, suggesting a promotive role of estrogens in these tumors [12]. Groups including ours previously reported that ER-β gene (ESR2) cytosine-adenine (CA) repeat polymorphism (ESR2-CA) [13] in the germline affected the colon cancer risk in postmenopausal women, but not rectal cancer risk, or colon cancer risk in men and premenopausal women [14,15,16]. Further, the risk of this polymorphism in postmenopausal colon cancer has been shown to invert with age: a shorter allele (S) was associated with a higher risk in older women, but a lower risk in younger postmenopausal women [14,15,16], suggesting a divergent pathogenic role of this polymorphism in postmenopausal colon cancer according to age. ESR2-CA is one of the microsatellites. Microsatellites instability (MSI), a change in the repetition number of microsatellites in tumors, is caused by a deficiency of MMR. Lynch syndrome, or hereditary non-polyposis colorectal cancer (HNPCC), is well-known for its germline mutation; however, MMR-deficiency is also frequently noted in non-hereditary colon cancer in older women, with a right-sided locus, or with Med/Muc histology. Although the germline ESR2-CA and risk of colon cancer have been associated, as described above, the instability of this microsatellite in colon cancerous tissue has never been reported. The purpose of this study was to elucidate whether and how ESR2-CA or its instability affects colon cancer pathogenesis, considering the background of patients and tumors. We also examined the association between ESR2-CA and ER-β expression, which has also never been reported. The association between the MMR status and patient/tumor background considering age and tumor locus is summarized in Table 1. The rate of dMMR was significantly different among four groups (≥70Rt, <70/right (<70Rt), ≥70/left (≥70Lt), and <70/left (<70Lt). p = 0.0023), and higher in ≥70Rt than in the other three groups, suggesting the specificity of ≥70Rt. These groups other than ≥70Rt were combined as Non(≥70Rt). The rate of dMMR was again significantly higher in ≥70Rt than in Non(≥70Rt) (p = 0.0005). Additionally, taking tissue categories (Ca and NonCa) and the MMR status (dMMR and pMMR) into consideration, we further categorized samples into eight groups, and comparisons were made among these groups in the following analyses. The distribution of the ESR2-CA allele frequency in NonCa and Ca is shown in Figure 1. In both tissue categories, the number of ESR2 CA repeats was distributed from 14 to 26 with two major peaks at 18 and 23, which is largely consistent with the results of other studies in the Japanese population (Figure 1) [14,15,17]. Using the same cutoff as in previous Japanese studies [14,15,17], we designated the allele with CA repeats <22 as the ‘S’ allele and ≥22 as the ‘L’ allele (Figure 1), resulting in three genotypes, SS, SL, and LL. To simplify this, SL and LL were combined as ‘nSS’, and the subjects were divided into two genotype categories, ‘SS’ and ‘nSS’. A change in the number of CA repeats between NonCa and Ca was significantly more frequent in dMMR cases (14/18, 78%) than in pMMR cases (16/96, 17%) (p < 0.0001). In more detail, 10 of 14 ≥70Rt/dMMR (71%), 2 of 31 ≥70Rt/pMMR (6.4%), four of four Non(≥70Rt)/dMMR (100%), and 14 of 65 Non(≥70Rt)/pMMR (22%) exhibited change in the number of CA repeats between NonCa and Ca, yielding a significant difference among the four categories (p < 0.0001). To examine more precisely, we added the number of two ESR2-CA repeats in each sample to yield ‘total ESR2-CA repeat number’, and compared it between the pairs (NonCa and Ca) of each patient. The distribution of the difference of ‘total ESR2-CA repeat number’ between pairs was compared among the four categories (Figure 2). In ≥70Rt/dMMR, 10 of 14 exhibited −9 to +3, whereas only one each of ≥70Rt/pMMR showed +1 and −1. All 4 Non(≥70Rt)/dMMR exhibited a decrease in CA repeat number in tumors (−9 to −3), whereas 14 of 65 Non(≥70Rt)/pMMR showed various differences between pairs. The ESR2-CA genotype was compared among four groups categorized by the age/locus and MMR status in NonCa and Ca (Table 2). In NonCa, the proportion of SS was larger in ≥70Rt than in Non(≥70Rt) (p = 0.0007) irrespective of the MMR status. In Ca, the proportion of SS was also higher in ≥70Rt than in Non(≥70Rt); however, the difference was much less in Ca than in NonCa (p = 0.0515) because of cases with changes of the ESR2-CA genotype in Non(≥70Rt) tumors (nSS in NonCa to SS in Ca). The ESR2-CA genotype was also compared between Ca and NonCa among the same group categorized by age/locus and the MMR status. The proportion of SS was same between NonCa and Ca in ≥70Rt (p = 1.0000), but was insignificantly higher in Ca than NonCa among Non(≥70Rt) (p = 0.1096) (Table 2, Figure 3, above). Immunohistochemical ER-β expression (total score) was compared among eight groups categorized by tissue type, age/locus, and the MMR status (Figure 4). Among NonCa, ≥70Rt/dMMR and ≥70Rt/pMMR exhibited significantly higher ER-β expression than Non(≥70Rt)/pMMR. Among Ca, ≥70Rt/dMMR and ≥70Rt/pMMR again exhibited significantly higher ER-β expression than Non(≥70Rt)/pMMR, and furthermore, ER-β expression in ≥70Rt/dMMR was significantly higher than in ≥70Rt/pMMR. As for the comparison between NonCa and Ca, a significant decrease in Ca was observed in ≥70Rt/pMMR and Non(≥70Rt)/pMMR, but not in ≥70R/dMMR or Non(≥70Rt)/dMMR (Figure 3 (below) and Figure 4). Immunohistochemical ER-β expression (total score, TS) was compared between SS and nSS in NonCa and Ca. ER-β expression was significantly higher in SS than in nSS among NonCa, which was not true among Ca (Figure 5). In the present study, we examined the ESR2-CA and ER-β expression in NonCa and Ca of surgical materials from postmenopausal colon cancer patients, taking the patients’ age, tumor locus, and MMR status into consideration. This is the first study to systematically compare ESR2-CA, one of the microsatellites, between NonCa and Ca, and to compare it with ER-β expression. We observed that: (1) in NonCa, the rate of the ESR2-CA SS genotype and ER-β expression level were significantly higher in ≥70Rt than in Non(≥70Rt) irrespective of the MMR status (Table 2, Figure 3 and Figure 4). (2) In NonCa, ER-β expression was significantly higher in SS than in nSS, which was not true in Ca (Figure 5). (3) The ESR2-CA repeat number frequently differed between NonCa and Ca in dMMR, but not in pMMR, although the ESR2-CA genotype did not significantly differ between them irrespective of MMR status (Table 2, Figure 2 and Figure 3). We previously showed that germline SS increased the risk of colon cancer in older women as opposed to younger postmenopausal women, in whom SS decreased the risk [14,15]. We also showed that most colon cancers in older women with the germline SS genotype were right-sided, and exhibited higher ER-β expression in Ca, as well as in NonCa, although the sample size was small [14]. These previous findings are consistent with the present results, whereby the frequency of the SS genotype and ER-β expression levels were high in ≥70Rt than Non(≥70Rt) irrespective of the tissue category (Table 2, Figure 3 and Figure 4). In NonCa, ER-β expression was significantly higher in SS than in nonSS (Figure 5), suggesting that ESR2-CA determines ER-β expression, which leads to estrogen activity, at least partly, in normal colon epithelium. An association between shorter ESR2-CA alleles and higher estrogen activity has been suggested by studies on bone mineral density or systemic lupus erythematosus (SLE) [18,19]. The biological role of ESR2-CA, which exists in intron 5 of the ESR2 locus, is not known at present; however, intronic microsatellite repeats have been suggested to alter gene transcription, mRNA splicing or translation, gene silencing, or interaction with coregulators [20]. Several isotypes are known for ER-β. Ligand binding domain (LBD) is coded by alternatively spliced exon 8 of ESR2, resulting in five different forms of ER-β: ER-β1 to ER-β5 [21,22]. ER-β1, the wild-type, can bind to estrogens and transduces their signals; however, ERβ2-5 variants, with a truncated form of this domain, lack binding ability and dominant negatively regulate estrogen signaling [23]. One of the attractive hypotheses is that, in NonCa, ESR2-CA SS (but not nSS) facilitates the alternative splicing of exon 8, increasing the expression of wild-type ER-β (ER-β1), which is recognized by clone PPG5/10 used in this study as the primary antibody against ER-β [18,24]. By contrast, in Ca, ER-β expression was not related to ESR2-CA, suggesting a disordered relation between them (Figure 5). In Ca with pMMR, despite unchanged ESR2-CA, ER-β expression was significantly lower than in NonCa irrespective of patients’ age, which was not true in Ca with dMMR where ER-β expression was stable. The finding that the ESR2-CA repeat number frequently changed in Ca with dMMR but not in Ca with pMMR is reasonable because ESR2-CA is one of the microsatellites, which are used as indicators of the MMR status (MSI). The change in the ESR2-CA repeat number, however, did not affect the ESR2-CA genotype in ≥70Rt/dMMR. Although the mechanisms of how ER-β expression is regulated in Ca is unclear, a decrease in the estrogen action may be pathogenically important in pMMR tumors, but not in dMMR tumors. In pMMR, a carcinogenic mechanism other than MMR might cause an abnormality which disturbs the normal transcription of ESR2. Why was the rate of the ESR2-CA SS genotype or ER-β expression high in NonCa in ≥70Rt? One hypothesis is that the germline SS genotype and resulting higher ER-β expression predisposes NonCa in ≥70Rt to cancerization, which means SS/ER-β promotes carcinogenesis in ≥70Rt. The right-sided colon is generally thought to be affected by the environment more than the left-sided colon or rectum. NonCa in ≥70Rt is likely to be most affected by the environment because of longtime exposure according to age. We previously showed that the estrogen concentration was high in Ca in ≥70Rt. Longtime exposure to a high estrogen concentration, which also contributes to increased nuclear ER-β expression, may be pathogenically important for cancer in ≥70Rt. In an experimental study using a colon cancer cell line with low ER-β expression, compulsory ER-β expression decreased MMR [25]. The dMMR tumor in ≥70Rt is an attractive candidate to explain this hypothesis because it has the background of NonCa with the ESR2-CA SS genotype, high ER-β expression, and a high estrogen concentration. Another hypothesis is that SS/ER-β lowers the risk of ‘usual’ cancer at a younger age by delaying the onset or suppressing proliferation until an advanced age when cancer is finally diagnosed. The pMMR tumor in ≥70Rt is a candidate to explain the second hypothesis. Alternatively, both of these hypotheses may work in coordination to develop Ca in ≥70Rt (Figure 6). By contrast, in women with the nSS genotype, low ER-β expression and menopausal estrogen decreases may increase the risk of ‘usual’ type colon cancer soon after menopause, suggesting the protective role of estrogen against colon cancer as generally believed (Figure 6) [1,2,4,7,8]. We speculate that the SS genotype is prone to develop dMMR tumors in ≥70Rt through active estrogen-ER-β signaling, as described above. Estrogen was suggested to promote dMMR through hMLH1 promoter methylation in prostatic/ovarian carcinogenesis [26,27]; however, the mechanism by which estrogen promotes hMLH1 promoter methylation is unclear. The relationship between ESR2-CA repeat and methylation status is also unknown. It deserves further study to clarify these associations because dMMR-related CRC in older patients is mostly caused by hMLH1 promoter methylation. Is a change of the ESR2-CA repeat number, one of MSI, important in the pathogenesis of colon cancer? In the present study, this MSI seems to be the result of MMR, and not pathogenically important for the disease, because it neither significantly affected ESR2-CA genotype nor related with ER-β expression in tumors. In the present study, the germline ESR2-CA genotype and resulting ER-β expression/estrogen activity was suggested to affect the type of colon cancer generated or patients’ age. Further studies to clarify the precise mechanism are needed to control colon cancer by manipulating estrogen. Pathological materials and frozen samples (pairs of Ca and NonCa) from 114 postmenopausal Japanese women (≥70 y/o, n = 72; <70 and ≥55 y/o, n = 42) who underwent curative surgery for colon cancer without preoperative therapy between 2006 and 2013 were available for this study at the Department of Pathology, Tokyo Metropolitan Geriatric Hospital and Cancer Institute Hospital, Japanese Foundation for Cancer Research (Tokyo, Japan). Histological classification was based on the Japanese Classification of Colorectal, Appendiceal, and Anal Carcinoma [28]. Immunostaining was performed for representative sections of formalin-fixed and paraffin-embedded tissue using an autostainer, BOND III (Leica Microsystems Ltd., Shanghai, China), as described elsewhere [12]. Briefly, an anti-ER-β1 mouse monoclonal antibody was used to detect ER-β (mouse, clone PPG5/10; Bio-Rad Laboratories, Hercules, CA, USA. X20). MMR was detected by monoclonal antibody for MLH1 (rabbit, clone EPR3894; Abcam plc., Cambridge, UK. X1000), MSH2 (mouse, clone G129-1129; BD Pharmingen, San Jose, CA, USA. X500), MSH6 (rabbit, clone EPR3945; GeneTex, Los Angeles, CA, USA. X200), and PMS2 (mouse, clone A16-4; BD Pharmingen. X100). Antigen retrieval was conducted using citrate buffer pH 6.0 for MLH1 and EDTA pH 9.0 for the others (100 °C, 20 min). Nuclear immunoreactivity for each antibody was evaluated by NH and TM, independently. As there is no standard method for assessing ER-β expression in CRC, the Allred score routinely used in clinical practice for breast cancer was adopted for evaluation. Briefly, nuclear immunoreactivity for ER-β is estimated independently by summing the percentage score, PS, and intensity score, IS, of positively-stained cells (PS: 0%, 0; <1%, 1; <10%, 2; <33%, 3; <67%, 4; ≥67%, 5. IS: weak, 1; medium, 2; strong, 3). For MMR, the loss of the nuclear staining for each antibody (anti-MLH1, anti-MSH2, anti-MSH6, and anti-PMS2) was evaluated. Deficient-MMR (dMMR) was defined as the loss of at least one MMR. Discrepancies were resolved by joint review of the slides. Deoxyribonucleic acid (DNA) samples were extracted from the pairs of Ca and NonCa frozen tissues from each patient by the phenol/chloroform method. ESR2-CA was determined by polymerase chain reaction (PCR) using fluorescein-labeled oligonucleotide primers designed to amplify the polymorphic (CA)n repeat in intron 5 of ESR2, as described elsewhere [14]. Briefly, the forward primer was labeled with hexachloro-6-carboxy fluorescein and used together with the tailed reverse primer (5′-FAM-GGT AAA CCA TGG TCT GTA CC-3′, 5′-tail-AAC AAA ATG TTG AAT GAG TGG G-3′). An ABI PRISM 3130 Genetic Analyzer (Applied Biosystems, INC., Foster City, CA, USA) was used for the analyses. Alleles of ESR2-CA are presented with the number of CA repeats. Using the same cut-off used in the previous studies, alleles with CA repeats <22 and ≥22 were designated as ‘S’ and ‘L’, respectively, resulting in genotypes SS, LS, and LL [14,15]. To simplify, genotypes ‘SL’ and ‘LL’ were combined as ‘nSS’, and the subjects were finally divided into two genotype categories, ‘SS’ and ‘nSS’. ESR2-CA (repeat number or genotype) was compared among each tissue pair (Ca vs. NonCa) or with ER-β expression, considering the background of patients/tumors. The Tukey–Kramer method was used to compare the Allred score (total score, TS) for ER-β between tissue categories classified by tissue type (Ca or NonCa), age/locus category (≥70/right, ≥70Rt; or Non(≥70Rt)), or the MMR status (dMMR or pMMR). Fisher’s exact test using a contingency table was used to compare various nominal variables (ESR2-CA genotype or tissue/patient background). In all instances, the statistical software JMP version 12 (SAS Institute, Cary, NC, USA) was used. p < 0.05 was considered significant. The ≥70Rt cases were characterized by NonCa with a higher rate of the ESR2-CA SS genotype or higher ER-β expression compared with Non(≥70Rt) cases. The germline ESR2-CA genotype and resulting ER-β expression/estrogen activity seem to affect the type of colon cancer generated or the age of onset/diagnosis of the disease. These may be a clue to resolving the controversy regarding the pathobiological role of estrogen in colorectal cancer.

PMC10003299

Junming Zhou,Zeyuan Li,Yue Li,Qiuzhu Zhao,Xinchao Luan,Lixue Wang,Yixuan Liu,Huijing Liu,Jun Zhang,Dan Yao

Effects of Different Gene Editing Modes of CRISPR/Cas9 on Soybean Fatty Acid Anabolic Metabolism Based on GmFAD2 Family

01-03-2023

soybean,fatty acids,CRISPR/Cas9,GmFAD2,editing vector

Δ12-fatty acid dehydrogenase (FAD2) is the essential enzyme responsible for catalyzing the formation of linoleic acid from oleic acid. CRISPR/Cas9 gene editing technology has been an essential tool for molecular breeding in soybeans. To evaluate the most suitable type of gene editing in soybean fatty acid synthesis metabolism, this study selected five crucial enzyme genes of the soybean FAD2 gene family—GmFAD2-1A, GmFAD2-1B, GmFAD2-2A, GmFAD2-2B, and GmFAD2-2C—and created a CRISPR/Cas9-mediated single gene editing vector system. The results of Sanger sequencing showed that 72 transformed plants positive for T1 generation were obtained using Agrobacterium-mediated transformation, of which 43 were correctly edited plants, with the highest editing efficiency of 88% for GmFAD2-2A. The phenotypic analysis revealed that the oleic acid content of the progeny of GmFAD2-1A gene-edited plants had a higher increase of 91.49% when compared to the control JN18, and the rest of the gene-edited plants in order were GmFAD2-2A, GmFAD2-1B, GmFAD2-2C, and GmFAD2-2B. The analysis of gene editing type has indicated that base deletions greater than 2bp were the predominant editing type in all editing events. This study provides ideas for the optimization of CRISPR/Cas9 gene editing technology and the development of new tools for precise base editing in the future.

Effects of Different Gene Editing Modes of CRISPR/Cas9 on Soybean Fatty Acid Anabolic Metabolism Based on GmFAD2 Family Δ12-fatty acid dehydrogenase (FAD2) is the essential enzyme responsible for catalyzing the formation of linoleic acid from oleic acid. CRISPR/Cas9 gene editing technology has been an essential tool for molecular breeding in soybeans. To evaluate the most suitable type of gene editing in soybean fatty acid synthesis metabolism, this study selected five crucial enzyme genes of the soybean FAD2 gene family—GmFAD2-1A, GmFAD2-1B, GmFAD2-2A, GmFAD2-2B, and GmFAD2-2C—and created a CRISPR/Cas9-mediated single gene editing vector system. The results of Sanger sequencing showed that 72 transformed plants positive for T1 generation were obtained using Agrobacterium-mediated transformation, of which 43 were correctly edited plants, with the highest editing efficiency of 88% for GmFAD2-2A. The phenotypic analysis revealed that the oleic acid content of the progeny of GmFAD2-1A gene-edited plants had a higher increase of 91.49% when compared to the control JN18, and the rest of the gene-edited plants in order were GmFAD2-2A, GmFAD2-1B, GmFAD2-2C, and GmFAD2-2B. The analysis of gene editing type has indicated that base deletions greater than 2bp were the predominant editing type in all editing events. This study provides ideas for the optimization of CRISPR/Cas9 gene editing technology and the development of new tools for precise base editing in the future. Soybean is one of the important oil crops in China, providing major vegetable protein for human food, animal feed, and industrial use. Soybean contains 17–22% of seed oil, is also widely used for industrial applications and bio-diesel production [1,2], and has an important role in food security, ecological security, and sustainable and stable agricultural development in China [3]. The soybean is a self-pollinated crop with a natural heterosis rate of 0.5–1.0% [4], and there are many limitations in traditional breeding to improve the oil and oleic acid content of soybean seeds [5]. Therefore, the application of genetic engineering to improve the oil content in soybean seeds based on the understanding of the molecular mechanisms regulating plant oil metabolism is of great importance for food supply, industrial production, and new energy utilization [6,7]. CRISPR/Cas9 gene editing technology is a hot tool for molecular breeding in recent years [8], which is low cost, is more accurate, is easy to use, and allows targeted gene manipulation at multiple locations throughout the genome and simultaneous editing to achieve efficient genome editing in various plants [9]. However, it still faces limitations such as off-target and low gene editing efficiency [10,11]. In recent years, scientists have used different promoter assemblies to drive Cas9 or multiple gRNAs in editing vectors to guide Cas9 to target multiple genes to optimize the effect of gene editing breeding [12]. However, in different studies reported we found that the pattern of gene editing occurring with Cas9 was different, and the achieved effect was also different, which shows that the pattern of gene editing occurred is an essential factor affecting the breeding effect [13]. In 2018, Ryosuke et al. generated multiple mutation types by designing different promoters to drive Cas9 in pMgPsef1-gRNA1/2#1 and #4 lines with more than 1000 bp base deletions with low-level chimeras, achieving good breeding results [14]. In 2019, Phat T. et al. used double gRNA to simultaneously knock out FAD2-1A and FAD2-1B to create a double allele mutant high oleic acid low linoleic acid mutant resource with editing types including deletions, insertions, and inversions [15]. In 2020, Chen et al. designed a double allele editing vector for editing GhFAD2-1A and GhFAD2-1D based on CRISPR/Cas9 gene editing technology, and 69.57% of the 19 positive plants with correct editing were of the base deletion type. Most of them were “C“ deletion (86.84%). The oleic acid content of M20-2 seeds that were successfully edited by fatty acid analysis was 5.58 times higher than the wild type, and the linoleic acid content decreased from 58.62% to 6.85% [16]. In 2021, Naoufal Lakhssassi et al. used EMS mutagenesis to identify multiple types of mutations in the GmFAD2 gene, with 74% of the substitutions from G to A and from C to T [17]. In 2021, Cai et al. designed two sgRNAs to target and edit the GmJAG1 gene, and sequencing results showed that base deletions in gene-editing positive plants resulted in the knockout of the start codon of GmJAG1 and GmJAG2 and partial deletion in the second exon [18]. In 2021, Wang et al. successfully created double and quintuple mutants with 1 to 60 single base insertions or deletions, resulting in changes in the amino acid sequence of the corresponding GmAITR protein, by designing multiple gene editing vectors. They found by sequencing that the GmFAD2-1A gene had a G to A mutation and resulted in a change in the tryptophan codon (TGG) at amino acid 293 to a premature stop codon, leading to an increase in oleic acid content [19]. Different types of mutation patterns produce different effects, and most of the key mutations and agronomically important genetic variants are single base polymorphisms (single nucleotide polymorphisms) that require precise genome editing tools to correct the sequence [20,21]. Utilizing the CRISPR/Cas9 gene editing system, we knocked out five key enzyme genes of the GmFAD2 gene family and compared the phenotypic changes in gene editing-positive soybean that produced different types of editing, to identify the optimal germplasm traits. This study aims to optimize the application of the CRISPR/Cas9 gene editing system in molecular breeding and base editing. The CRISPR-P online program (http://crispr.hzau.edu.cn/CRISPR2/) was used to design gRNA target sequences for GmFAD2-1A, GmFAD2-1B, GmFAD2-2A, GmFAD2-2B, and GmFAD2-2C based on sequence specificity and high GC content in exon sequences. The gRNA target sequences are listed in Table 1. Five single gene editing vectors were constructed for GmFAD2-1A, GmFAD2-1B, GmFAD2-2A, GmFAD2-2B, and GmFAD2-2C using the Hangzhou Baige (Hangzhou, China) CRISPR/Cas9 vector BGK015. Sequencing of the PCR amplicons indicated that the target gene size and sequence were as expected, which confirmed that the single gene editing vectors were successfully constructed (Figure S1). Analysis was conducted after the creation of gene editing positive plants according to the breeding process in Figure 1. Genetic transformation of soybean was obtained by using the Agrobacterium-mediated method (Figure S2). PCR amplification of the herbicide resistance marker genes Bar and Cas9 identified 72 T1 transgenic plants, which included 17 transgenic plants of GmFAD2-1A (designated JN18-CR1AT1-1 to JN18-CR1AT1-17), 15 of GmFAD2-1B (designated JN18-CR1BT1-1 to JN18-CR1BT1-15), 18 of GmFAD2-2A (designated JN18-CR2AT1-1 to JN18-CR2AT1-18), 14 of GmFAD2-2B (designated JN18-CR2BT1-1 to JN18-CR2BT1-14), and 8 of GmFAD2-2C (designated JN18-CR2CT1-1 to JN18-CR2CT1-8) (Figure 2 and Figure 3). Following the sowing of the T1 transgenic plant seeds, the resulting plants were grown to maturity and later harvested. Subsequently, the T2 generation lines were procured. The partial PCR amplification results are shown in Figure 4 (Figures S3–S5). To determine whether the exogenous gene was integrated into the genomes of the T2 plants, Cas9 was used as a probe to perform Southern blotting detection on some of the T2 generation editing plants. The results showed that the non-transformed negative plants had no hybridization signals, while the editing plants showed that foreign genes had been integrated into the genome in the form of a single copy, and the hybridization signals between individuals were slightly different (Figure 5). In this study, 72 transgene-positive plants were identified by PCR amplification of T1 generation transgenic plants using target-specific primers. Sanger sequencing was performed and the Cc-qPCR method reported in the study was used to determine the mutation types in the gene-editing positive plants and to count the editing efficiency [22]. A total of 43 gene editing positive plants with correct editing events were obtained based on sequencing results and analysis of qPCR results. Of the 18 independent positive plants obtained for GmFAD2-2A, 16 had mutated sequences (mutation efficiency of 88.9%), of which 10 were homozygous mutants, and 6 were heterozygous mutants. The 14 independent positive plants obtained for GmFAD2-2B included 9 plants with mutant sequences (mutation efficiency of 64.2%), of which 6 were homozygous mutants, and 3 were heterozygous. Of the 17 independent positive plants obtained for GmFAD2-1A, 7 had mutant sequences (mutation efficiency of 41.1%), 3 were homozygous mutants, and 4 were heterozygous. A total of 15 independent positive plants were obtained for GmFAD2-1B, including 6 plants with mutant sequences (mutation efficiency of 40%), of which 3 were homozygous, and 3 were heterozygous. The eight independent positive plants obtained for GmFAD2-2C included five plants with mutant sequences (mutation efficiency of 62.5%), of which three were homozygous mutants and two were heterozygous mutants. Part of the sequencing results and graphical analysis results are shown in Figure 6 and Figure 7. Analysis of the mutation types in the target sequences revealed eight types, including base deletions greater than 2 bp, single base G substitutions, single base A substitutions, single base T substitutions, single base A insertions, single base G insertions, single base T deletions, and single base G deletions (Figure 7). Subsequent amino acid sequence comparisons and raw signal analysis showed that the mutants that produced the correct editing events all had significantly altered amino acid sequences and the protein structures were predicted to be significantly different (Figure 8). Mutant individuals exhibited early termination of transcription, with significant differences in secondary and tertiary structure predictions. Most mutations were localized to key protein structural domains, including enzyme catalytic activity, homodimer interfaces, or substrate binding, suggesting that isolated mutations may negatively affect protein activity or dimerization (Figure S6). Of all plants with correct editing events, those with base deletions greater than 2 bp had the highest average editing efficiency of 48%. Single base T deletions had an average editing efficiency of 18%. Single base G deletions had an average editing efficiency of 11%. Single base R substitutions had an editing efficiency of 7%. Single base A insertions had an editing efficiency of 5%. Single base A substitutions had an editing efficiency of 4%. Single base G insertions had an editing efficiency of 3%. Single base T substitution editing efficiency was 2% (Figure 9). Quantitative real-time PCR analysis was performed using a β-actin-encoding gene (LOC100798523) as a reference control. The generated data showed that compared to the control (JN18), the three lines with the most significant relative expression decrease for each target gene were chosen for phenotypic identification and further functional analysis of T2 transgenic plants (Figure 10). The fatty acid content of seeds from some T2 transgenic soybean lines was analyzed. In contrast to the seeds of the control Jinong 18, the oleic acid content of the five transgenic lines of editing vectors was significantly higher, with the GmFAD2-1A gene having the greatest increase of 91.49%, then GmFAD2-1B (89.21%), GmFAD2-2A (82.31%), GmFAD2-2C (78.87%), and GmFAD2-2B (75.70%). On the contrary, the linoleic acid content of all lines that tested positive for the editing vector was found to be lower by 7.1–10.3% when compared to the control, while no significant differences were observed for other quality traits (Figure 11, Table 2). Further investigation indicated that the oleic acid content in the seeds of transgenic lines with different editing types of vectors was substantially increased compared to the control JN18. The average increase of editing lines with base deletion greater than 2 bp was up to 105.51%. The oleic acid content of seeds with single base G substitution increased by 95.77% on average. The oleic acid content of seeds with single base A substitution increased by 93.66% on average. The oleic acid content of seeds with single base T substitution increased by 90.16% on average. The oleic acid content of seeds with single base A insertion increased by 84.87%. Seed oleic acid content increased by 79.92% for single base G insertion. Seed oleic acid content increased by 75.81% for single base T deletion, and seed oleic acid content increased by 74.25% for single base G deletion. Contrarily, we observed a 7.5–14.0% reduction in linoleic acid content in all gene editing positive plants in the different editing types compared to the control, while no significant differences were observed for other quality traits (Figure 12, Table 3). The research results confirm that GmFAD2, a soybean fatty acid dehydrogenase, is the essential enzyme for regulating oleic acid to linoleic acid. The analysis results of main agronomic traits indicated that in comparison to the control JN18, there were no major differences in other major traits such as flower color, hairy, leaf type, plant height, the number of effective branches, and nodes between different editing vectors; however, there were three phenotypic traits related to yield traits, such as the number of pods per plant, the total number of grains, and the weight of the grains per plant, that showed significant differences. Moreover, analysis results of different editing types showed similarity to those of editing vectors, with the exception of significant differences in pod number per plant, grain number per plant, and grain weight per plant when compared to the control. There were not significant differences in other major agronomic traits (Table 4 and Table 5). In this study, we obtained gene editing positive plants by the transformation of soybean through the Agrobacterium-mediated method, in which we found the highest editing efficiency of GmFAD2-1A among the five key enzyme genes, reaching 88%. Compared with previous reports on soybean and peanut, the editing efficiency was improved by 10–20% [15,16,17]. In plant molecular breeding, the gene editing efficiency of CRISPR/Cas9 is an essential factor affecting the effectiveness of molecular breeding, and improving the editing efficiency of target genes is the basis for creating more excellent traits in plants. To explore the different effects of different gene editing models on the phenotypes of crops, we selected five essential enzyme genes of the FAD2 gene of the soybean fatty acid dehydrogenase family, which have been widely reported in previous studies, and used the most popular tool for gene editing breeding, the CRIPSR/Cas9 gene editing system, to explore and compare the editing options with the most significant impact on the phenotypes of agronomic traits [22,23]. The genetic principle of CRISPR/Cas9 is to use Cas9 to induce DSB at target sites on a plant-specific genome under gRNA guidance [24,25]. With insertions or deletions, and although NHEJ-mediated mutagenesis is highly effective in plants, it is commonly used to generate knockouts and alter promoter or enhancer strengths necessary to achieve precise genome editing to develop new agronomic traits [26]. Although the new base editing technology BE was reported in 2016 and has improved the efficiency and the accuracy of base editing and major editing compared to the traditional CRISPR/Cas9 technology, the impact of targeting different target sites and the different approaches that occur on gene editing efficiency and editing effectiveness is still significant and is a major problem to be addressed in future plant gene editing [27,28]. In 2017, Naoufal Lakhssassi et al. used mutagenesis to identify one C to G, three C to T mutations in the GmFAD2-1A gene, and one C to T mutation in GmFAD2-1B, resulting in a 30% to 50% increase in oleic acid content, similar to the effect achieved with our gene editing vector, where replacement mutations did not exist [29]. In 2020, Nan et al. identified a G substitution in FAD2-1A that caused a Trp mutation at position 254 to become a stop codon, increasing in oleic acid content [30]. In 2020, Wu et al. constructed two gene editing and one gene editing vectors for the GmFAD2-1A and GmFAD2-1B genes. Two gene editing and one double gene editing vectors were constructed, in which a single gene editing vector with a 2bp deletion and a base T deletion occurred, the oleic acid content was increased by 87.55% and 141.5%, and a double gene editing vector with both a 7bp deletion and a 2 deletion at both targets increased the oleic acid content by 329.3%, showing that two essential enzyme genes with simultaneous large block deletions can exert a powerful gene editing for breeding [31]. Efficient gene editing is also one of the key factors that affect breeding performance, and stable genetic transformation of soybeans remains one of the most difficult challenges to overcome [32]. In recent years, scientists have been optimizing the CRISPR/Cas9 system to improve its editing efficiency [33]. In 2019, Ren et al. compared the effects of sgRNA-CG content and SpCas9 expression levels on gene editing efficiency to optimize CRISPR/Cas9 editing efficiency. In 2020, Zheng et al. used the ubiquitin-related structural domain (UBA) to enhance Cas9 protein stability to improve editing efficiency [34]. In 2020, multiple gRNA-CRISPR/Cas9 vectors were constructed using multiple cis-trans tRNA-gRNA approaches targeting the Medicago Sativastay-green (MsSGR) gene. Replacement of the CaMV35S promoter with the anthocyanin promoter (AtUBQ10) to drive Cas9 expression in the multiple gRNA systems resulted in a significant increase in genome editing efficiency [35]. In 2022, Zhang et al. found that the MaU6c promoter was approximately four times more active than the OsU6a promoter in banana protoplasts, and the application of this promoter in CRISPR/Cas9 and banana codon-optimized Cas9 resulted in a fourfold increase in mutational efficiency compared to the previous banana CRISPR/Cas9 [36]. In 2022, Patrick et al. engineered an improved temperature-tolerant variant of Cas12a from the bacterium Lachnospiraceae ttLbCas12a, which at a standard incubation temperature of 22 °C in Arabidopsis showed significantly improved editing efficiency over LbCas12a [37,38,39]. There are relatively few reports on the optimization of the CRISPR/Cas9 technology in soybeans [40]. This study further optimizes CRISPR/Cas9 technology by comparing the effects of gene editing modes on phenotypes, which will further facilitate basic molecular research and molecular breeding techniques in various plant species, including useful crops, and is one of the most useful genome editing tools in plant genome engineering. We explore the effects of different editing modes. The impact of editing modes on agronomic traits will lay the foundation for future optimization of the optimized CRISPR/Cas9 technology, the development of base editors, and their widespread use in molecular breeding [41,42,43,44,45]. This study explores the different effects of different editing types on plant phenotypes by comparing the changes in the oleic acid content of transgenic soybeans undergoing different editing patterns, and develops ideas for future precise base editing. The “Jinong 18” soybean variety (Jishendou 2006 was carefully chosen from the foreign-sourced initial generation lines by the Agricultural College of Jilin Agricultural University in 2006, and it is a high-oil soybean variety) selected as recipient material in this study was provided by the Jilin Provincial Key Laboratory of Plant Molecular Breeding. High-scoring gRNA sequences were selected from the CRISPR-P website at http://cbi.hzau.edu.cn/cgi-bin/CRISPR (accessed on 22 January 2021), and in vitro activity was tested to identify gRNAs with >90% activity. The gRNA targets designed above were sequenced on the website at http://www.biogle.cn/ (accessed on 14 May 2021). Oligo sequences were generated from the kit by dissolving the synthesized oligo in water at 10 µM, mixing buffer anneal 18 µL, UP oligo 1 µL, and low oligo 1 µL; adding ddH2O to a total volume of 20 µL; heating at 95 °C for 3 min; and then slowly reducing to 20 °C at approximately 0.2 °C/S. The components were mixed on ice according to CRISPR/Cas vector 2 μL, oligo dimer 2 μL, enzyme mix 1 μL, plus ddH2O to a total volume of 10 μL, mixed and reacted at room temperature (20 °C) for 1 h, and transformed into E. coli. The DNA from the recombinant plasmid was extracted for PCR validation, and 50 μL of plasmid DNA was sequenced by Sanger and subsequently compared by DNAMAN software (V6.0) to verify whether the gRNA was successfully ligated into the vector (Tables S1 and S2). The cotyledon node of soybean “JN18” was utilized as the receptor material, and the five constructed CRISPR/Cas9 editing vectors were transferred into the receptor by Agrobacterium tumefaciens-mediated method, thereby obtaining the transgenic soybean plants. Genomic DNA from the T0 soybean plants was amplified by PCR using primers Cas9-1F/Cas9-1R and Bar-1F/Bar-1R (Table S3). The PCR amplifications were completed in a final reaction volume of 20 μL. The PCR conditions for amplifying the Bar gene were as follows: 94 °C for 5 min; 30 cycles of 94 °C for 30 s, 60 °C for 30 s, and 72 °C for 1 min. The PCR conditions for amplifying the Cas9 gene were as follows: 94 °C for 5 min; 30 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 1 min; 72 °C for 10 min (Table S4). Specific primers were designed to include the target site. Genomic DNA was extracted from the positive plants for PCR amplification. The amplicons were sequenced by Changchun Kumei (Changchun, China). The generated sequences were compared and analyzed using DNAMAN (v6.0). The base changes within the gRNA sequence indicated that the target gene was successfully edited. Statistics on the efficiency of transformation and gene editing in soybeans were obtained. The amino acid sequences of the transgenic positive plants obtained by Sanger sequencing were used as templates. The SWISS-MODEL website (http://swissmodel.expasy.org/, accessed on 19 October 2021) was opened, and the amino acid sequences were submitted for template identification. To confirm whether the exogenous gene has been integrated into the positive plant genome, genomic DNA from the transgenic plant leaves was extracted and double-digested with restriction endonucleases Hind III and BamH I. Utilizing an exogenous gene Cas9 as a probe, Southern blot analysis was conducted with the DIG-HIGH Prime DNA Labeling and Detection Starter Kit I (C58-11745832910, Roche company, Shanghai, China). Total RNA extracted from confirmed T2 transgenic plants was used as the template for synthesizing cDNA. The q-RT PCR analysis was completed in a final reaction volume of 20 μL, which included 10 µL TB Green Premix Ex Taq (Tli RNaseH Plus), 0.4 μL PCR forward primer (10 μM), 0.4 μL PCR reverse primer (10 μM), 0.4 μL ROX Reference Dye (50×), 2 μL cDNA template, and 6.8 μL RNase-free water. The q-RT PCR analysis was performed using the Agilent MX3000P PCR instrument, with the following program: 95 °C for 3 min; 40 cycles of 95 °C for 5 s and 60 °C for 30 s (Table S4). This was followed by a melting curve analysis involving the following program: 95 °C for 15 s, 60 °C for 1 min, and 60 °C for 30 s. Relative gene expression values were calculated using the 2−ΔΔCt method, and analysis of plant mutation types by Cc-qPCR [22]. Three separate biological replicates were performed with each treatment. Variance analysis was performed using GraphPad Prism (8.0). The NIRS DS2500 NIR quality analyzer (FOSS, Stockholm, Sweden) was used to determine the protein, oil, and major fatty acid content of mature soybean seeds, selecting full, insect-free, uniformly sized seeds to be placed in the measuring cup, laying them flat, and placing them in the NIR sample tank. The number of seeds needed to fill the measuring cup (approx. 60 g) is covered over the infrared sensing area and collected by the operating software Operator according to the collection library previously established in the laboratory. Each measurement setting was repeated three times, and the results were automatically saved to a computer. The data were analyzed by IBM SPSS Statistics (27.0.1). The positive seeds obtained from the T1 generation were sown in the experimental field of Jilin Agricultural University, with each strain planted in a row of 4.5 m in length, 10 cm between plants, and 65 cm between rows, double-spaced, and managed in the field under natural rainfall conditions. When the plants were fully mature, three plants of each line were randomly selected for indoor testing of the main agronomic traits. The agronomic traits of the soybean variety were assessed by the “China Soybean Variety Records”. The criteria for yield traits included the number of pods per plant, the grain weight per plant, and the 100-grain weight. The number of pods was determined by measuring an average of three plants per line. The grain weight was determined by measuring the average of three plants, and the 100-grain weight was determined by measuring the weight of 100 grains of uniform size from a single plant, repeated three times (g). Other agronomic traits assessed included plant height, the number of branches, and the number of nodes. Plant height was measured from the cotyledon node to the top of the main stem in the laboratory (cm). The number of branches and nodes on the main stem was counted. The data were analyzed by IBM SPSS Statistics (27.0.1). The data are expressed as the mean ± SD of the values obtained in the repeated experiments. For statistical analysis, variance analysis was performed using IBM SPSS Statistics (27.0.1). Tukey ‘s multiple comparison tests were performed, and then multiple comparison tests and calculations of LSD were performed. Differences with p values less than 0.05 were considered statistically significant. In summary, we constructed five GmFAD2 gene editing vectors, created mutant strains with 62.15–100.65% higher oleic acid content than the control JN18, and achieved 88% editing efficiency of the GmFAD2-1A gene. Comparing the effects of different editing patterns in the GmFAD2 gene family on the oleic acid content of positive transgenic plants, we found that mutations with base deletion types greater than 2 bp resulted in large changes in amino acid sequence caused by the premature functioning of the stop codon, which affected the production of linoleic acid catalyzed by soybean fatty acid dehydrogenase, resulting in elevated oleic acid content in seeds. The knockout of large segments in the coding region of the target gene tended to produce more pronounced breeding effects. Our research opens up new ideas for further development of gene editing breeding technologies.

PMC10003303

Alfonso Torres-Sánchez,Alicia Ruiz-Rodríguez,Pilar Ortiz,Margarita Aguilera

Key Stratification of Microbiota Taxa and Metabolites in the Host Metabolic Health–Disease Balance

24-02-2023

microbiota,taxa,metabolites,detoxification,pathways

Human gut microbiota seems to drive the interaction with host metabolism through microbial metabolites, enzymes, and bioactive compounds. These components determine the host health–disease balance. Recent metabolomics and combined metabolome–microbiome studies have helped to elucidate how these substances could differentially affect the individual host pathophysiology according to several factors and cumulative exposures, such as obesogenic xenobiotics. The present work aims to investigate and interpret newly compiled data from metabolomics and microbiota composition studies, comparing controls with patients suffering from metabolic-related diseases (diabetes, obesity, metabolic syndrome, liver and cardiovascular diseases, etc.). The results showed, first, a differential composition of the most represented genera in healthy individuals compared to patients with metabolic diseases. Second, the analysis of the metabolite counts exhibited a differential composition of bacterial genera in disease compared to health status. Third, qualitative metabolite analysis revealed relevant information about the chemical nature of metabolites related to disease and/or health status. Key microbial genera were commonly considered overrepresented in healthy individuals together with specific metabolites, e.g., Faecalibacterium and phosphatidylethanolamine; and the opposite, Escherichia and Phosphatidic Acid, which is converted into the intermediate Cytidine Diphosphate Diacylglycerol-diacylglycerol (CDP-DAG), were overrepresented in metabolic-related disease patients. However, it was not possible to associate most specific microbiota taxa and metabolites according to their increased and decreased profiles analyzed with health or disease. Interestingly, positive association of essential amino acids with the genera Bacteroides were observed in a cluster related to health, and conversely, benzene derivatives and lipidic metabolites were related to the genera Clostridium, Roseburia, Blautia, and Oscillibacter in a disease cluster. More studies are needed to elucidate the microbiota species and their corresponding metabolites that are key in promoting health or disease status. Moreover, we propose that greater attention should be paid to biliary acids and to microbiota–liver cometabolites and its detoxification enzymes and pathways.

Key Stratification of Microbiota Taxa and Metabolites in the Host Metabolic Health–Disease Balance Human gut microbiota seems to drive the interaction with host metabolism through microbial metabolites, enzymes, and bioactive compounds. These components determine the host health–disease balance. Recent metabolomics and combined metabolome–microbiome studies have helped to elucidate how these substances could differentially affect the individual host pathophysiology according to several factors and cumulative exposures, such as obesogenic xenobiotics. The present work aims to investigate and interpret newly compiled data from metabolomics and microbiota composition studies, comparing controls with patients suffering from metabolic-related diseases (diabetes, obesity, metabolic syndrome, liver and cardiovascular diseases, etc.). The results showed, first, a differential composition of the most represented genera in healthy individuals compared to patients with metabolic diseases. Second, the analysis of the metabolite counts exhibited a differential composition of bacterial genera in disease compared to health status. Third, qualitative metabolite analysis revealed relevant information about the chemical nature of metabolites related to disease and/or health status. Key microbial genera were commonly considered overrepresented in healthy individuals together with specific metabolites, e.g., Faecalibacterium and phosphatidylethanolamine; and the opposite, Escherichia and Phosphatidic Acid, which is converted into the intermediate Cytidine Diphosphate Diacylglycerol-diacylglycerol (CDP-DAG), were overrepresented in metabolic-related disease patients. However, it was not possible to associate most specific microbiota taxa and metabolites according to their increased and decreased profiles analyzed with health or disease. Interestingly, positive association of essential amino acids with the genera Bacteroides were observed in a cluster related to health, and conversely, benzene derivatives and lipidic metabolites were related to the genera Clostridium, Roseburia, Blautia, and Oscillibacter in a disease cluster. More studies are needed to elucidate the microbiota species and their corresponding metabolites that are key in promoting health or disease status. Moreover, we propose that greater attention should be paid to biliary acids and to microbiota–liver cometabolites and its detoxification enzymes and pathways. Gut microbiota is considered a complex ecosystem with a wide array of microorganisms linked to host health. Multiple studies suggested that the structure and composition of the gut microbiota in metabolic-related diseases, such as atherosclerosis, colitis, diabetes, hyperlipidemia, hypertension, metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), obesity, and steatosis, exhibit significant changes compared to healthy individuals and that those changes are related to host physiopathology. In this context, the analysis and description of trends in microbial populations associated with disease and health status become a key issue to elucidate possible signatures of metabolic-related diseases. The gut microbiota of patients with metabolic-related diseases shows differences at different taxonomic levels. Many studies showed that Parabacteroides, Bifidobacterium, Oscillospira, and Bacteroides were decreased in patients with obesity [1,2,3,4,5,6,7,8,9,10,11,12,13]. Moreover, Faecalibacterium and Bifidobacterium were decreased [14,15,16,17,18,19,20,21] and species from Lactobacillaceae family [22] and Blautia were increased [7,13,19,20,21,22,23,24,25,26,27] in diabetic patients. Other metabolic diseases related to intestinal diseases seem to be related to increased Escherichia and decreased Faecalibacterium [28,29,30,31,32,33,34,35,36,37]. Recently, the combination of metagenomics and metabolomics has received extensive attention due to the growing number of studies that establish positive and negative correlations between gut microbiota taxa, metabolites, and health status. Therefore, future studies will contribute to elucidate the essential role of gut microbiota in metabolite synthesis, metabolite modifications, and metabolic pathway regulations. In this sense, metabolites such as short-chain fatty acids (SCFA), amino acids (AA), or bile acids (BA) can play a crucial role in maintaining metabolic functions or, on the contrary, they might be involved in disease development, such as choline derivatives in the case of cardiovascular diseases [38,39,40,41]. Metabolite influences are not restricted to the intestine and distribution to other physiological locations has been described through different axes, such as the gut–liver axis, in which the gut microbiota is related to liver diseases, including NAFLD, NASH, fibrosis, or liver cancer [42]. Gut microbiota partially impacts the host BA profile as it is involved in primary bile acid transformation into secondary free bile acids, such as deoxycholic acid, lithocholic acid, and ursodeoxycholic acid, contributing to the modulation of host total bile acid production [43]. The chemical structure of many endogenous compounds, including gut microbiota metabolites, can be modified, resulting in changes in their bioactivity and half-life [44]. This kind of modifications are related to the development of complex metabolic networks between host and gut microbiota, where final substances could be potentially more toxic than the original ones [45]. Traditional probiotics, mainly consisting of species from Lactobacillaceae and Bifidobacteria and a few from other genera, have been largely applied as a useful strategy in the context of clinical intervention in metabolic-related diseases [46,47]. However, the development of new procedures using Next Generation Probiotics (NGP) opens a new world of possibilities due to the beneficial effects that have already been described in murine models and, to a lesser extent, in humans. In this context, murine models show Akkermansia muciniphila, Faecalibacterium prausnitzii, Bacteroides uniformis, Bacteroides acidifaciens, Clostridium butyricum, and Prevotella copri as interesting microorganisms with potential applications in obesity [48,49,50,51,52,53], liver diseases [52,54,55,56,57,58,59], diabetes [48,49,50,51,52,53,58,60,61], colitis [62], and hyperlipidemia [53,58]. This work will contribute to finding out microbial and metabolite patterns and their correlation with diseases that have been studied independently or not yet extensively studied. Therefore, the principal aim of this work is to identify and describe the association between human gut microbiota taxa changes in metabolic-related diseases, incorporating the correlations with metabolites, and how they can modulate host health. Gut microbial taxa differences in diabetes, obesity, metabolic syndrome, and liver and cardiovascular diseases, highlight links between gut microbiota and host health status. In this context, Figure 1 summarizes updated and available information about gut microbial taxa changes in these metabolic-related diseases. Increased and decreased trends in gut microbiota taxa were assessed through an extensive literature search including information about metabolic diseases investigated by different authors. In this context, the approach we followed offered some drivers of specific changes in gut microbiota composition that could be related to host health. The analysis of 75 studies involving changes of the main taxa altered in patients suffering metabolic-related diseases disclosed 121 differentially abundant microbial genera (complete data are available in Supplementary Material S1). Figure 2 shows representative genera count value comparison obtained in metabolic diseases after microbial taxa variation analysis. Gut microbiota genera such as Oscillibacter, Butyricicoccus, Odoribacter, and Paraprevotella were exclusively decreased in individuals affected by metabolic diseases. On the other hand, Faecalibacterium, Bifidobacterium, Ruminococcus, Parabacteroides, Roseburia, Akkermansia, Alistipes, Coprococcus, and Oscillospira were both decreased and increased in metabolic-related diseases. However, overall, these microbial genera showed a negative association with the metabolic diseases studied here. Microbial genera such as Klebsiella, Collinsella, and Enterococcus were exclusively present in those cases in which individuals were affected by metabolic diseases. However, taxa belonging to Escherichia, Lactobacillaceae, Blautia, Streptococcus, and Dorea were also identified in patients without metabolic-related diseases. These microbial genera showed an upward trend in metabolic-related diseases studied here. Figure 3 shows the distribution of representative microbial taxa linked to metabolic-related diseases. In a previous study exploring next generation probiotics for metabolic and microbiota dysbiosis linked to xenobiotic exposure [63], we tried the first approach to describe changes in gut microbial taxa associated to metabolic-related disease. As a result, potential associations between bacterial genera and metabolic diseases were described despite the lesser number of analyzed studies. In this case, Table 1 shows an expansion of the current knowledge available in this field, including the relevant information identified in the previous study. The analysis of the 16 selected studies involving correlations between gut microbiota taxa altered in patients suffering from metabolic diseases, metabolites, and host health status allowed us to shed light on potential critical pathways to modulate homeostatic processes (complete data are available in Supplementary Material S2 [103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118] Figure 4 summarizes available information about gut microbiota–metabolite correlations and host health status. Several gut microbiota taxa showed a high metabolite count linked to disease or health status. In that regard, increased microbial metabolite counts in health status were obtained in gut microbiota genera such as Holdemania, Porphyromonas, and Dialister; further, they were also higher for Bacteroides, Clostridium, and Alistipes, but with more similar counts in both groups. Figure 5 shows representative genera differential values associated to health-related metabolite count analysis. Increased metabolite counts related to disease status were linked to gut microbiota taxa such as Ruminococcus, Eubacterium, Blautia, Roseburia, Oscillibacter, Subdoligranulum, Gemmiger, Butyricicoccus, Akkermansia, Veillonella, Dorea, Coprococcus, Escherichia, Parabacteroides, Enterobacter, Lachnospira, Gemella, and Fusobacterium. Figure 6 shows representative genera differential values associated to disease-related metabolite count analysis. According to the total metabolites linked to disease and health status, 171 metabolites were associated with metabolic-related diseases; among these, 143 were exclusively associated with this group and 28 were shared with health status. Moreover, 63 metabolites were related to health status, and 35 were exclusively associated with this group. A qualitative metabolite analysis was performed considering total disease/health-related metabolites. Table 2 shows disease/health-related metabolites classified according to three main chemical groups: fatty acids and conjugates, amino acids and derivatives, and bile acids and derivatives. A further association analysis of the number of studies where a specific association between a metabolite and a bacterial genus was found showed very interesting clustering patterns. For instance, butyrate-producer genera when present in a healthy status associated with bile acid metabolites and, to a lesser extent, with essential amino acids; however, when they are overrepresented in metabolic diseases, they are associated with lipid metabolism, clustering in two distinct groups. We also observed that essential amino acids clustered together, and they might have an important role for the metabolism of Bacteroides in health status, according to Figure 7. We performed a comprehensive literature search covering the period from 1995 to November 2022 using Scopus, Web of Science, and PubMed databases, using the search strategies showed in systematic review and dividing this review into two main study issues: gut microbial taxa variations in metabolic-related diseases and gut microbiota–metabolite correlations in metabolic-related diseases. Studies involving changes in gut microbial taxa in atherosclerosis, colitis, diabetes, hyperlipidemia, hypertension, metabolic syndrome, NAFLD, NASH, obesity, and steatosis and studies involving microbiota–metabolite correlations in metabolic-related diseases were assessed, screened, and selected according to PRISMA 2020 flow diagrams (Figure 1 and Figure 4) [111]. In the microbial taxa variation analysis, gut microbial taxa identified in selected studies were divided into two groups: decreased in metabolic-related diseases and increased in metabolic-related diseases, based on research findings. Metabolite counts were calculated for each microbial genus. To determine representative gut microbiota taxa, an arbitrary criterion was applied. Microbial genera were considered representative if the absolute frequency difference between decreased–increased counts was greater than three. In the gut microbiota–metabolite correlation analysis, gut microbiota, microbial metabolites, and host status correlations were assessed. First, gut microbial genera were classified into increased in health status or increased in diseases, according to metabolite absolute frequencies displayed for each genus. Second, considering metabolites related to representative genera in health or disease status, a qualitative metabolite analysis was performed. Metabolites correlated with health or disease status were classified into three main groups: fatty acids and conjugates (FA), amino acids and derivatives (AA), and bile acids and derivatives (BA), according to PubChem and related chemical database classification. Furthermore, a bioinformatics analysis was performed to establish potential biomarkers, which revealed the association between specific disease/health balances. Heatmap shows the analysis where a specific association between a metabolite and bacterial genera was found in a health and/or a disease stage (as indicated by “_H” or “_D”, respectively). For simplicity, only the representative genera and the most found metabolites (metabolites that appeared least five times either associated with health or disease in the studies analyzed here) were included. First, we selected only the genera with more than 10 metabolites associated and then we kept only the metabolites that appeared at least five times, either associated with health or disease, in the studies analyzed here. Figure 7 shows the performance of R (version 4.1.1.) using the package “pheatmap” [112]. There is a growing interest in the analysis of the gut microbiome and its metabolome [113,114]. However, integrating data from both fields to understand how gut microbiota, microbial metabolites, and host status are correlated not always provide concise information. Thus, it can hinder researchers in establishing clear links between the presence of a particular gut bacterial taxa and/or metabolites and disease or health status. This task is especially challenging in the context of searching gut microbial biomarkers that allow predicting future phenotypes or classifying individuals into disease and non-disease status. This is mainly due to the fact that contradictory results about microbial taxa abundance and metabolites related to disease or non-disease status can be found in the literature. In this case, this approach showed that Faecalibacterium, Bifidobacterium, Ruminococcus, Parabacteroides, Roseburia, Akkermansia, Alistipes, Coprococcus, Oscillospira, Oscillibacter, Butyricicoccus, Odoribacter, and Paraprevotella could represent a downregulated microbial cluster in metabolic-related disease patients and, on the contrary, Escherichia, species from Lactobacillaceae family, Blautia, Streptococcus, Klebsiella, Collinsella, Dorea, and Enterococcus cluster upregulation could be involved in metabolic-related disease status. Due to relevant information underlined by many authors and results obtained in this review, Ruminococcus and Bifidobacterium, as well as taxa belonging to Lactobacillaceae family, Blautia, and Dorea should be identified at the species level to establish similarities with the results already available in the microbiological databases. According to metabolite absolute frequencies in disease and health status and representative gut microbiota taxa, we tried to search for possible trends between those elements and host physiopathology. When we compared representative metabolites and microbial taxa results, only Alistipes, from the down-regulated proposed cluster, showed high counts in both gut microbial taxa variation analysis and metabolite count analysis related to health. In the same way, Escherichia, Blautia, Streptococcus, Collinsella, Dorea, and Enterococcus, from the proposed upregulated cluster, showed high counts in both gut microbial taxa analysis and metabolite count analysis in disease/disorder group. Following this approach, Faecalibacterium and Akkermansia genera [115,116], frequently described as key microorganisms related to health status, were decreased in metabolic-related diseases, indicating a possible relationship with health status. However, a link with disease status could be identified according to metabolite absolute frequencies described for both genera Faecalibacterium and Akkermansia. A similar result can be observed in other microorganisms frequently associated with metabolic diseases [117], where microbial taxa analysis showed links with obesity-related diseases. However, metabolite absolute counts showed links with health status. Interestingly, preliminary data results derived from the biomarker search have demonstrated the positive association of essential amino acids with health in the genera Bacteroides, and conversely, benzene derivatives have been related to disease and the genera Clostridium. We also observed that lipid metabolites grouped several taxa overrepresented in diseases, but it will be necessary to determine the results to the species level. These results showed which bacterial taxa of the gut microbiota and their derived metabolites could be related to host status manifestations. However, study limitations and lack of available data in some fields make it impossible to establish final and solid conclusions in this way. Human health is not only affected by gut microbiota composition and its derived metabolites but also many exogenous and endogenous factors, which can also impact in genotypic and phenotypic manifestations. Recently, the holistic concept of the One Health approach and the exposome include multidisciplinary analysis of a complex reality that affect different but linked items [118]. Nowadays, solid evidence about specific microbial and metabolite signatures in cases of metabolic-related disease is still limited and more concrete information on the correlations between gut microbiota, gut metabolites, and host health status is needed. This synergic approach will lead to a better management of well-known microbiota–metabolic related diseases. To increase the availability of scientific data on the interaction between gut microbiota taxa in different health contexts, metabolite synthesis, and metabolite modification and impact on the host health, integrated metagenome and metabolome analysis should be continually reviewed, since it seems to be a possible cornerstone involved in the determination of potential microbial and metabolite signatures related to physiological alterations. Despite the existence of microbial taxa–metabolite-health correlations, there is no evidence of a clear gut microbiota and derived metabolite patterns into healthy or metabolic-related disease status that is able to predict or classify patients into one or the other. Most of the taxa and metabolites did not show representative oscillations between disease and health groups, so bacterial genera with potential interest should continue to be monitored as new information on their abundance in metabolic-related disease appearance. Implementation of the One Health holistic approach combined with exposome principles can provide new perspectives and evidence about how endogenous and exogenous substances interact with gut microbiota and microbial-derived substances and how the pull of interactions finally affects human homeostasis.

PMC10003306

Julia Sutter,Peter J. Bruggeman,Brian Wigdahl,Fred C. Krebs,Vandana Miller

Manipulation of Oxidative Stress Responses by Non-Thermal Plasma to Treat Herpes Simplex Virus Type 1 Infection and Disease

28-02-2023

oxidative stress,immunomodulation,reactive oxygen and nitrogen species,redox homeostasis,antioxidant,innate immunity,adaptive immunity,antiviral therapy,plasma

Herpes simplex virus type 1 (HSV-1) is a contagious pathogen with a large global footprint, due to its ability to cause lifelong infection in patients. Current antiviral therapies are effective in limiting viral replication in the epithelial cells to alleviate clinical symptoms, but ineffective in eliminating latent viral reservoirs in neurons. Much of HSV-1 pathogenesis is dependent on its ability to manipulate oxidative stress responses to craft a cellular environment that favors HSV-1 replication. However, to maintain redox homeostasis and to promote antiviral immune responses, the infected cell can upregulate reactive oxygen and nitrogen species (RONS) while having a tight control on antioxidant concentrations to prevent cellular damage. Non-thermal plasma (NTP), which we propose as a potential therapy alternative directed against HSV-1 infection, is a means to deliver RONS that affect redox homeostasis in the infected cell. This review emphasizes how NTP can be an effective therapy for HSV-1 infections through the direct antiviral activity of RONS and via immunomodulatory changes in the infected cells that will stimulate anti-HSV-1 adaptive immune responses. Overall, NTP application can control HSV-1 replication and address the challenges of latency by decreasing the size of the viral reservoir in the nervous system.

Manipulation of Oxidative Stress Responses by Non-Thermal Plasma to Treat Herpes Simplex Virus Type 1 Infection and Disease Herpes simplex virus type 1 (HSV-1) is a contagious pathogen with a large global footprint, due to its ability to cause lifelong infection in patients. Current antiviral therapies are effective in limiting viral replication in the epithelial cells to alleviate clinical symptoms, but ineffective in eliminating latent viral reservoirs in neurons. Much of HSV-1 pathogenesis is dependent on its ability to manipulate oxidative stress responses to craft a cellular environment that favors HSV-1 replication. However, to maintain redox homeostasis and to promote antiviral immune responses, the infected cell can upregulate reactive oxygen and nitrogen species (RONS) while having a tight control on antioxidant concentrations to prevent cellular damage. Non-thermal plasma (NTP), which we propose as a potential therapy alternative directed against HSV-1 infection, is a means to deliver RONS that affect redox homeostasis in the infected cell. This review emphasizes how NTP can be an effective therapy for HSV-1 infections through the direct antiviral activity of RONS and via immunomodulatory changes in the infected cells that will stimulate anti-HSV-1 adaptive immune responses. Overall, NTP application can control HSV-1 replication and address the challenges of latency by decreasing the size of the viral reservoir in the nervous system. As a prevalent pathogen and global health concern, herpes simplex virus type 1 (HSV-1) is among one of the most studied human herpesviruses. HSV-1 has long served as a useful research tool in providing information that has enhanced the understanding of viruses. It also has a large global footprint in which more than 70% of the world’s population under the age of 50 harbors an HSV-1 infection [1]. Most individuals who are infected with HSV-1 are asymptomatic because the viral genome remains transcriptionally dormant within the peripheral nervous system during latent infection, allowing lifelong persistence of the virus. Replication of this latent virus can be reactivated by external and internal stress stimuli, resulting in productive infection in neurons and re-infection of epithelial cells in the mucosal epithelium innervated by the infected neuron. Reactivation results in clinical signs of infection in the form of cold sores around the mouth, eyes, and genitalia. Although these lesions can be discomforting to the patient, most cases of HSV-1 infection are mild [2,3]. In rare cases, HSV-1 can cause serious disease by spreading to the brain to cause encephalitis [4] and to the eye to cause keratitis [5]. There is also increasing evidence that chronic HSV-1 infection can contribute to the development of neurodegenerative diseases such as Alzheimer’s Disease later in life [6,7,8] (Figure 1). For patients who experience severe clinical symptoms of HSV-1 infection, treatment options, while available, are limited and sometimes ineffective. Antiviral therapies are typically administered upon the appearance of clinical symptoms after the initial acquisition of the virus or when the virus is reactivated from latency. The first line of defense against these symptoms is nucleoside analogs, the most common being acyclovir. As a prodrug, acyclovir becomes activated through phosphorylation by virus-encoded thymidine kinases (TK) to the monophosphate form and further phosphorylation by other thymidylate kinases, converting it to acyclovir trisphosphate [9,10,11]. This form of acyclovir then competes with guanine nucleotides and binds the growing DNA strand during viral DNA replication in the nucleus, thus inhibiting the synthesis of the viral DNA. This leads to the selective inhibition of the viral DNA polymerase [11]. Penciclovir is another nucleoside analog prodrug prescribed to patients with a similar mechanism of action as acyclovir, but with an even higher affinity for the viral DNA [10,11]. Due to their mechanism of action, nucleoside analogs are effective during acute infection but do not affect the latent virus residing in neurons, allowing HSV-1 to persist in its host. This persistence can lead to the development of viral mutants upon reactivation, which give rise to drug-resistant strains [9,11,12]. Additionally, by failing to eliminate the virus, these antiviral therapies do not prevent future recurrent acute infection and transmission of HSV-1 that occurs through direct contact with the resulting lesions [1,3]. These limitations highlight the need for new therapeutic approaches that effectively address viral latency and reactivation by targeting other available viral and cellular components involved in HSV-1 pathogenesis. These include structural components of the virion structure and cellular processes manipulated by HSV-1 to facilitate productive infection of the cell. Reduction-oxidation (redox) homeostasis, which involves the maintenance of intracellular reactive oxygen and nitrogen species (RONS), is one of these processes that is significantly disrupted during HSV-1 infection in both epithelial cells (host cells for lytic infection) and neurons (latently infected cells). Disruption of redox homeostasis by HSV-1 in both cell types allows the increase in RONS generation, leading to greater RONS concentrations in spite of secondary reactions and enzymatic pathways. This increase in RONS, as a result, contributes to their activity in modulating cellular signaling pathways, the downregulation of cellular antiviral responses, and the promotion of an environment favorable for HSV-1 infection [13]. This review discusses how the development and progression of HSV-1 to chronic infection is closely tied to the alteration of the redox state in the host cell and subsequent reductions in the cell’s antiviral defense against HSV-1. Since maintaining redox homeostasis is critical in cells, we discuss how alterations in cellular redox by the virus may be harnessed as a therapeutic target for HSV-1 infections. RONS are potent intracellular signaling molecules with abilities to stimulate various cell signaling pathways, including those that regulate cell proliferation and apoptosis [14,15,16,17,18,19]. RONS also modulate immune responses against invading pathogens through the manipulation of cell signaling, or by influencing the production of proinflammatory mediators to promote an antiviral environment in and around the cell. Cellular RONS often participate in antimicrobial killing of invading pathogens during phagocytosis [20]. These functions of RONS are designed to maintain the health and integrity of the cell. HSV-1 is an obligate intracellular pathogen that relies heavily on host cellular machinery for its replication. To create an intracellular environment that favors productive replication (or sustained latent infection), HSV-1 affects multiple cellular processes, including redox homeostasis. To maintain redox homeostasis, RONS are constantly produced and destroyed in a healthy cell. The functions of RONS are attributed to their abilities to react with macromolecular structures. RONS are reactive species derived from oxygen and/or nitrogen-containing compounds, some containing an unpaired electron in the outer shell [21,22]. Therefore, these species can modify macromolecules leading to the modulation of signaling pathways. These actions are characteristic of primary RONS such as nitric oxide, hydrogen peroxide, and superoxide [15]. In the cell, primary RONS are reactive species that are typically generated during normal metabolic processes that occur in the mitochondria [23,24,25,26,27,28,29,30], endoplasmic reticulum (ER) [31,32], and peroxisome [33,34]. Alternatively, these RONS can be generated via specialized enzymes present in the cell such as nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOX) [35,36,37] or nitric oxide synthases (NOS) [38,39,40]. These primary RONS may alter signaling cascades by reversible modifications on target macromolecular structures. Overall, primary RONS exhibit a weak damaging potential. Due to their metastable nature, primary RONS can participate in reactions with one another to form secondary RONS (e.g., peroxynitrite and hypochlorous acid). Unlike primary RONS, secondary RONS are not tightly regulated by the cell and can inflict damage when they accumulate [41,42]. This accumulation and subsequent damage of the cell by RONS is referred to as oxidative stress. Oxidative stress is often induced by viruses to overwhelm the infected cell and create an environment that favors its replication. For example, respiratory syncytial virus (RSV) upregulates RONS in airways, while simultaneously diminishing the host’s antioxidant system [21,43]. Similarly, upregulation of serum markers of lipid peroxidation in human immunodeficiency virus type 1 (HIV-1)-infected patients suggests increased oxidative stress and a link between RONS dysregulation and viral pathogenesis [44,45]. Oxidative stress in infected cells can damage cellular macromolecules and impair immune responses against the virus. However, the viral genome is also at risk for modification and mutation, leading to the formation of viral variants that may have enhanced virulence [46]. Like RSV and HIV-1, HSV-1 induces intracellular oxidative stress conditions during infection [47,48]. HSV-1 infection results in two distinct outcomes: lytic infection and latent infection. Lytic infection is characterized by active viral gene expression and results in the assembly of progeny virions that are released into the extracellular environment to infect nearby uninfected cells. During a lytic infection, the high level of replication results in the destruction of the host cell. This type of HSV-1 infection occurs in mucosal epithelial cells, usually at the site of infection or reactivation. During a period of acute infection characterized by lytic replication, patients present with cold sores and are responsive to antiviral drugs administered to alleviate these clinical symptoms [2,3]. Lytic infection depends on multiple viral and cellular components to establish and sustain infection in epithelial cells, impacting the entire cell and utilizing cellular processes to create an environment suitable for productive HSV-1 replication. One way this occurs is through the manipulation of oxidative stress responses by the virus, generating RONS that can interfere with cellular signaling and responses. HSV-1 is an enveloped virus, composed of an encapsulated genome surrounded by a host cell-derived lipid bilayer decorated with glycoproteins [49,50]. In the initial steps of a lytic infection, these envelope glycoproteins facilitate attachment and subsequent entry into target epithelial cells through interactions with cellular heparan sulfate (HS) [5,51,52,53], a cell surface proteoglycan involved in signaling, host defense, and metabolic processes [54]. Upon glycoprotein-receptor binding, cytoskeletal rearrangements are triggered to allow membrane fusion between the viral envelope and host cell membrane, facilitating the release of the protein capsid and the enclosed viral genome into the cytoplasm [5,51,52,53,55]. In establishing a redox environment that favors HSV-1 replication, two envelope proteins have secondary roles in recalibrating oxidative stress responses in the cell. Glycoprotein B (gB), which mediates attachment to HS, also induces ER stress by interacting with the ER lumen domain protein kinase R-like ER kinase (PERK), a signaling transducer involved in the ER stress response to misfolded proteins during viral infections. To prevent ER-mediated oxidative stress and subsequent apoptosis, gB interacts with PERK to maintain homeostasis in the ER [56]. HSV-1 glycoprotein J (gJ), which does this during binding and entry, is also implicated in viral-induced oxidative stress by promoting RONS accumulation through the adenosine triphosphate (ATP) synthase molecule [57,58]. Following fusion of the viral and cellular membranes, compartmentalization of the encapsulated viral genome into host endosomes allows trafficking of the viral contents through the cytoplasm toward the nucleus in a pH-dependent process. The lower pH of the endosome facilitates the release of the capsid into the cytosol [59]. HSV-1 tegument proteins, which are packaged in the virion, are simultaneously released into the cytoplasm where they can regulate cellular processes in favor of HSV-1 replication and subsequent pathogenesis [55,60,61,62]. Like the envelope proteins, HSV-1 tegument proteins influence the redox state of the cell to prevent clearance of the virus. Virus protein 16 (VP16), a tegument protein released into the cytoplasm following viral entry, manipulates HSV-1 by downregulating nuclear factor-κB (NF-κB) immune signaling, which is known to be responsive to RONS [60,63]. HSV-1 can also manipulate oxidative stress responses in the cell through infected cell protein 0 (ICP0), which is expressed as an immediate-early (IE) protein but is also packaged in the virus. By acting as an ubiquitin ligase, ICP0 can selectively target host cell signaling proteins to promote their degradation and loss of function [64]. The actions of these tegument proteins are critical in downregulating the antiviral response toward HSV-1, creating an intracellular environment suitable for productive replication. HSV-1 continues to hijack cellular machinery, such as the endocytic pathway, to allow the trafficking of the viral genome into the nucleus through the nuclear pore complex (NPC). Additionally, tegument proteins facilitate the shedding of the viral protein capsid and release of the genome into the nucleus [55,60,62,65,66,67,68]. Upon entry into the nucleus, the HSV-1 genome is still at risk of detection and subsequent clearance by the cell. Therefore, HSV-1 continues to employ tactics to dodge these attempts at cellular immune detection by manipulating redox homeostasis. By upregulating the production of RONS in the cell, HSV-1 can modify key cell signaling proteins to dampen and negate innate detection mechanisms. For example, HSV-1 interferes with the cyclic GMP-AMP synthase/stimulator of interferon genes (cGas/STING), a nuclear DNA sensing pathway that induces potent type 1 interferon (IFN) responses. By directly modifying the STING protein via RONS production, HSV-1 can dampen the IFN response [69]. HSV-1 also depletes the cellular antioxidant glutathione peroxidase 4 (GPX4) during infection. Since GPX4 is an activator of cGAS/STING, its depletion by HSV-1 can prevent the activation of this detection pathway. Without detection of HSV-1 by the cell, viral-induced oxidative stress accumulates, which can be in the form of lipid peroxidation by-products, and further overwhelms cellular machinery that maintains redox balance [70]. This control that HSV-1 holds over antioxidant concentrations can further be imposed through the Nrf2-antioxidant response element (Nrf2-ARE) pathway, which mediates expression of antioxidant genes. Through its ability to modify the Nrf2 transcription factors, HSV-1 can control the redox state in the cell to favor its replication [71]. As a DNA virus, HSV-1 diverts the cellular machinery in the nucleus to replicate its own viral genome and produce new progeny viruses. Once the cell replication machinery is taken over by HSV-1, the virus begins to express its genes in three distinct but overlapping phases: immediate early (IE), early (E), and late (L). All phases of viral gene expression involve viral and cellular factors [9,72]. First, IE genes encode α proteins, which play important roles in enhancing HSV-1 infection by promoting virus replication and dampening antiviral responses in the host cell [50,73,74,75]. The IE phase includes the expression of the E3 ubiquitin ligase ICP0 (also packaged in the virus as a tegument protein), which induces oxidative stress and targets host cell proteins involved in the antiviral defense for degradation [64]. ICP27 is also encoded by IE genes and inhibits cell protein translation alongside tegument protein virion host shutoff (vhs) [63]. IE gene products also initiate a transcriptional cascade, resulting in the expression of downstream E genes that mediate HSV-1 DNA replication [73,76,77,78,79] and L genes that encode protein components used to assemble new viral particles [65,72,73]. L genes also encode ICP34.5 that further modulates the oxidative stress responses in cells by directly binding to Beclin 1, an autophagy-stimulating protein. Through this interaction, ICP34.5 can directly prevent autophagy of the cell, which is often activated by virus-induced oxidative stress as a means to eliminate HSV-1 from the cell [55,80]. During the later events in viral replication, HSV-1 must evade cell detection mechanisms and interfere with signaling to negate anti-HSV-1 immune responses [81]. Interference with antiviral responses is achieved by the manipulation of redox homeostasis in the cell by HSV-1. Specifically, HSV-1 can induce oxidative stress conditions to modify key signaling proteins, resulting in their degradation or loss of function [13,82]. In addition to the ubiquitin activity of ICP0, carbonylation is another type of post-translational modification that can divert cellular proteins from their roles in signal transduction. Carbonylation is described as the introduction of ketones and aldehydes to amino acid side chains. These modifications are recognized as indicators of oxidative stress during viral infections. Proteins with these modifications are inactivated and targeted for degradation in the proteasome. As a result, HSV-1 has adopted carbonylation to target key host cell proteins, such as apoptotic proteins, that would otherwise interrupt productive replication [46,64,83,84]. Cellular mechanisms are also manipulated by HSV-1 to promote virus assembly. Cellular proteins are preferentially degraded over viral proteins by HSV-1 induced expression of virus-induced chaperone-enriched (VICE) domains in the nucleus. In addition, heat shock protein 27 (Hsp27), a molecular chaperone that aids in protein folding, was found to be associated with VICE domains in the nucleus during HSV-1 infection. It is likely that the increased presence of Hsp27 is correlated with promoting viral protein folding in preparation for assembly [64,85]. Following HSV-1 genome replication, the virus begins the transcription of L genes that encode structural viral components required to assemble progeny virions. This assembly process is complex, requiring several viral proteins to form the capsid structure and initiate insertion of the newly replicated genome into the nascent virus particle [86,87,88,89]. Once the genome is packaged into the viral capsid, viral tegument proteins assist the progeny virion in budding from the inner nuclear membrane into the perinuclear space to gain a temporary lipid envelope [87,89]. Virions then de-envelope as they bud into the cytoplasm and are most likely taken up by the trans-Golgi network (TGN) where they are assumed to obtain their tegument protein layers. The TGN is proposed to serve as the site of secondary envelopment, in which virion envelopes derive from vesicles that bud from the TGN to the plasma membrane. The assembled viruses then use the host cell microtubule system for transport to the plasma membrane where the fully assembled virions egress the host cell via exocytosis [90,91,92,93] (Figure 2). The alternative outcome of HSV-1 replication is a latent infection. Latency is a state in which virus gene expression and replication are silenced to escape cellular immune detection and clearance, and to allow for long-term persistence of the viral genome in the infected cell. During acute HSV-1 infection, progeny viruses produced by lytic infection of epithelial cells leave the mucosal epithelium, enter the trigeminal nerve, and latently infect the cell bodies of sensory neurons. Since genes associated with replication and viral assembly are expressed to a much lesser extent, patients exhibit no clinical symptoms of HSV-1 infection [50]. The ability of HSV-1 to remain transcriptionally dormant and evade immune system surveillance contributes to viral persistence, allowing lifelong infection with HSV-1 and its continued spread in the general population. While the exact mechanisms by which HSV-1 establishes and maintains latency are not fully understood, evidence suggests HSV-1 can manipulate redox homeostasis within the neurons to promote their survival and continue to escape immune detection [47,82]. Latent infection of neurons begins with mechanisms that parallel those involved in lytic infection but quickly diverges as the virus enters the neuron. Like lytic infection of epithelial cells, initial attachment of the HSV-1 virion to neurons involves interactions between the envelope glycoproteins and cell surface proteoglycans, including HS and nectin-1 [66,94]. Following attachment to these molecules, entry into the neuron occurs via a pH-independent manner that results in the fusion of the virus envelope with the neuronal plasma membrane, a process mediated by the host cell meshwork of filamentous actin [94]. Rather than trafficking via endocytic pathways, the released encapsulated genome uses the neuronal cytoskeleton to initiate retrograde axonal transport from the entry point on the axon. This transport mechanism involves microtubule networks running along the axon to the cell body where latency is established [61,94]. When HSV-1 reaches the cell body of the neuron, its genome rapidly condenses into heterochromatin via epigenetic mechanisms, making genes associated with lytic infection inaccessible to the host transcription machinery. Instead, the condensation of the genome facilitates the expression of a single transcript, the latency-associated transcript (LAT), expressed under a neuron-specific promoter [55,65,95,96,97,98,99,100]. In addition to silencing replication-associated genes [101], LAT expression is responsible for upregulating cellular genes that promote neuron survival and HSV-1 persistence [97,102]. The nervous system, where HSV-1 resides during latency, is highly susceptible to oxidative stress. In particular, the trigeminal ganglia at the base of the brain are characterized by high oxygen uptake and generally low levels of antioxidants [8,103]. Therefore, during HSV-1 latency, cellular genes induced by the LAT may promote the onset of oxidative stress. Because the brain is rich in polyunsaturated fatty acids, oxidative stress may cause lipid peroxidation reactions, which are known to interfere with cell signaling pathways [15,16]. In fact, HSV-1 infection of neurons is correlated with the release of hydroxynonenal (HNE) and malondialdehyde (MDA), which are by-products of RONS-mediated lipid peroxidation. During HSV-1 establishment of latency, these products can contribute to the downregulation of immune pathways such as NF-κB to negate host innate immune responses and upregulate pathways such as c-Jun N-terminal kinase/mitogen-activated protein kinase (JNK/MAPK) to promote survival of the infected cell [47,104]. Manipulation of these cellular processes contributes to reduced immune visibility and neuron survival, which facilitates the persistence of HSV-1 in the latent stage. To further promote persistent infection, LAT offers protection to the condensed and mostly silent genome of HSV-1 within a circularized episome in the neuron until its eventual reactivation [66,96,105]. Persistence of HSV-1 in the neuron and the associated chronic oxidative stress can result in damage to infected neural tissues. Although latency allows the evasion of HSV-1 from immune clearance, the host still tries to protect itself. Dissemination of HSV-1 to neural tissues can lead to oxidative stress from microglia cells, a common cell type in the nervous system involved in protective immune responses. They are cited as being major cytokine producers and influencing excessive inflammatory responses to HSV-1 infection. Over time, these stressful conditions, in some cases, can lead to serious disease such as encephalitis in the brain, resulting in neuronal death and irreversible brain tissue damage [4,47,106,107,108]. Although the exact mechanisms for disease development are unknown, Alzheimer’s Disease and other neurodegenerative conditions have been associated with HSV-1 infection [6,7,8]. These potential disease outcomes highlight the importance of redox homeostasis and how critical it is in determining the fate of HSV-1 infection and efficiency of the cell to overcome it. Reactivation from latency is a hallmark of HSV-1 infection and occurs periodically throughout the lifetime of an infected patient. This process involves the escape of HSV-1 virions from neurons and re-infection of the innervated epithelial cells within the mucosal epithelium via anterograde transport. Upon re-infection of epithelial cells, the ensuing productive infection of epithelial cells results in the re-appearance of clinical symptoms [2,65,105]. The process of reactivation has long been associated with an individual’s response to external and internal stress stimuli that trigger the escape of HSV-1 from neurons. Regardless of the stimulus, HSV-1 takes advantage of the stress stimuli to escape immune detection in order to re-infect epithelial cells within the mucosal epithelium, resulting in the re-emergence of clinical symptoms [105]. While stimuli involved in cellular stress are known to trigger reactivation, the exact mechanisms by which this process occurs are poorly understood. Overall, reactivation is critical for the lifecycle and persistence of HSV-1. Due to the involvement of oxidative stress conditions in maintaining latency and triggering reactivation, the latently infected neurons are subjected to long-term oxidative damage [8,109]. Both in vitro and in vivo models of HSV-1 infection have been used to demonstrate the effects of external stimuli in HSV-1 reactivation from latency. Many of these external stimuli are tied to the induction of oxidative stress responses that push the potential of reactivation of latent HSV-1. Early studies of HSV-1 reactivation focused on the delivery of electrical stimulation of the trigeminal nerve [110]. A commonly used reactivation stimulus is ultraviolet (UV) light, which causes oxidative stress responses in cells through the generation of RONS [111]. High intensities of UV-B light were found to be sufficient to reactivate HSV-1 replication in a coculture system involving HaCaT cells (a neurofibrillary keratinocyte cell line susceptible t1o HSV-1 in vitro), and PC12 neuronal cells (a cell line susceptible to HSV-1 in vitro) [112]. UV light has also been a tool for reactivation in latently infected mice [113]. Relative to mechanism of action, damage to cellular macromolecules by UV light exposure can impact enzyme functions, create lipid peroxidation by-products, and damage nucleic acids [114,115,116]. However, oxidative stress was also shown to aid in reactivation through the administration of sodium arsenite, an inducer of heat shock, and gramicidin D, a toxin that interacts with membrane lipids, both of which are inducers of oxidative stress. Using ICP0-null mutant strains of HSV-1, these agents were capable of reactivating replication in absence of the ICP0 tegument protein, which is implicated in promoting lytic gene expression [117]. Other triggers have been attributed to emotional stress or hormonal imbalances [105,110,118]. This includes adrenergic hormones involved in the body’s stress response such as epinephrine and norepinephrine, which have been shown to reactivate HSV-1 in vivo using a latent rabbit infection model [110]. These studies demonstrate that exposure to harmful stress stimuli can cause the re-emergence of infection and clinical disease via the reactivation of acute HSV-1 infection. The reactivation of HSV-1 replication can also be affected by the onset of oxidative stress caused by intracellular stimuli. Reductions in the temperature or superinfection with cytomegalovirus (another member of the Herpesviridae family known to induce oxidative stress) can activate HSV-1 infection from latently infected cells [119,120,121,122]. Overall. the redox state of cells involved in HSV-1 replication can contribute to reactivation of HSV-1 replication. RONS have dual roles in cells. RONS are naturally produced by the cell and aid in the maintenance of homeostasis. When tightly controlled, RONS are beneficial to the cell, aiding in cell survival, signaling, and immune responses. However, when this control of RONS concentrations is lost, which occurs during HSV-1 infection, RONS can damage cellular macromolecules and dysregulate cellular processes. To regulate the concentrations of RONS and protect the cell from oxidative damage, cells utilize an antioxidant system composed of enzymatic and non-enzymatic defenses. These defenses are typically used to prevent the accumulation of primary RONS by converting them into less reactive molecules [21,42,44]. For instance, superoxide dismutases (SOD) remove superoxide radicals that are produced during metabolism, generating hydrogen peroxide (another primary RONS and an important signaling molecule) and molecular oxygen, both of which can readily be used by the cell [14,42,123]. Then, to prevent the subsequent accumulation of hydrogen peroxide, catalases convert hydrogen peroxide to water and oxygen [14,41,57]. In addition, glutathione (GSH), in conjunction with other non-enzymatic antioxidants, also controls RONS concentrations in the cell as one of its numerous functions. As a co-substrate for glutathione peroxidase (GPx), GSH limits peroxides through the formation of glutathione disulfide (GSSG), which is then reduced back to GSH, making the balance between GSH and GSSG a useful indicator of the antioxidant capacity in a cell [44,69,124]. Other non-enzymatic scavengers for RONS include vitamins, carotenoids, flavonoids, and melatonin [46] (Figure 3). The tightly regulated generation and destruction of RONS in the cell contributes to the antiviral defense mechanisms employed by the cell against HSV-1. In response to HSV-1 infection, cells try to maintain a stable redox environment to prevent the virus from hijacking the cell. RONS can serve as potent signaling molecules by modifying key cellular proteins involved in signaling pathways and making them integral components of the cellular innate immune system. NOX enzymes, involved in RONS production, influence many toll-like receptor (TLR)-stimulated pathways that can activate or inhibit cellular responses to a pathogen [42]. TLRs are pattern recognition receptors (PRRs) located on the plasma membrane, within endosomes, and in the cytoplasm of cells. TLRs recognize conserved motifs within pathogen structures and upregulate innate immune responses that promote pathogen clearance from a cell. Specifically, TLR2 and TLR4 reside on the plasma membrane of cells, while TLR9 is located in endosomal compartments [42,55,69]. TLR pathogen recognition upregulates innate immune responses that promote pathogen clearance from a cell. Upon stimulation of these TLRs by binding viral components, NOX expression is reported to be upregulated, inducing the production of RONS [42]. Additionally, TLRs promote mitochondrial reactive oxygen species (mROS) generation to aid in immune responses [125]. Lastly, retinoic acid inducible gene 1 (RIG-1)-like receptors, another class of PRRs, have been implicated in their ability to mediate NOX expression by directly sensing foreign DNA and RNA molecules in the cytoplasm [42]. PRRs play active roles in sensing and activation of the host cell immune response, including the generation of RONS. HSV-1 envelope glycoproteins are recognized by PRRs such as TLR2 and αvβ3 integrin on the plasma membrane. Specifically, gH/gL glycoprotein heterodimer was sufficient for this activation and subsequent immune response [126,127]. Intracellularly, endosomal TLR3 and TLR9, located on the ER, have also been shown to recognize HSV-1 structural components and synergize with TLR2 to elicit an inflammatory response and produce RONS [104,128]. In the cell, DNA/RNA sensors such as cGas, RIG-1, and γ-interferon inducible protein 16 (IFNI16) sense HSV-1 during the replication cycle to trigger RONS production and promote innate immune responses [104,127,128,129]. RONS produced during viral infection can lead to oxidative damage to cellular macromolecules, which can prompt immune responses toward the invading virus. Mitochondrial DNA (mtDNA) is a nucleic acid susceptible to RONS-mediated damage from virus-induced oxidative stress due to the lack of DNA repair mechanisms present in the mitochondria. DNA packing proteins that bind the mtDNA to maintain its structure and control the accessibility of genes can also be subjected to oxidative damage by RONS. Overall, damage to mtDNA serves as an antiviral sensor during infection and promotes the stimulation of innate immune responses [130] (Figure 4). Following recognition of HSV-1 by innate sensors, the cell is prompted to create an antiviral environment to prevent efficient viral replication and assembly. Activation of the NF-κB pathway, known to be influenced by RONS, results in the production of proinflammatory mediators, primarily type 1 IFN, which promote inflammation and T cell responses. These molecules are important mediators in antiviral defenses [126,127,130,131]. While not a direct inducer of NF-κB, micromolar concentrations of hydrogen peroxide are shown to be sufficient for NF-κB activation and function [132]. In the absence of stimulation, NF-κB resides in the cytoplasm bound to the IκBα inhibitor to prevent its translocation into the nucleus. The dynein motor complex protein, LC8, is a protein that can bind and modulate the activity of the IκBα inhibitor bound to NF-κB. Following activation of NF-κB by TNF-α, subsequent RONS production was found to oxidize LC8, releasing it from IκBα, which is then subjected to phosphorylation and ubiquitination [133]. As a result, NF-κB is released, allowing the transcription factor to translocate into the nucleus and promote expression of its target genes. NF-κB responsive genes are known to induce proinflammatory responses including the production of cytokines [15,132,134]. Thioredoxin, a group of redox proteins with a known role in signaling, was also found to modulate NF-κB activation through increased DNA binding activity in bone marrow dendritic cells [135]. Additionally, NF-κB knockout experiments demonstrated that HSV-1 replication and production of viral-induced RONS increased in the absence of NF-κB, highlighting the efficiency of the pathway as an immediate immune response toward HSV-1 while also implicating its susceptibility to redox signaling [81]. Additionally, NF-κB and Nrf2-Keap1 pathways have been shown to counteract each other by competing for the same co-activator during transcription. This is a mechanism used by the cell to regulate these pathways and to control redox levels and inflammatory responses to maintain cellular homeostasis [136,137]. As HSV-1 infection progresses, accumulation of RONS can result in the activation of inflammasomes [127] and autophagy [80] within the infected cell. Intracellular accumulation of RONS in response to HSV-1 infection activates the NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome, resulting in the secretion of proinflammatory cytokines interleukin (IL)-1 β and IL-18, along with caspase-8 [42,125]. Once PRRs within the infected cell recognize HSV-1 components, immune signaling cascades are activated to promote the expression of proinflammatory mediators to attract innate immune cells. These recruited cell types mediate the destruction of pathogens during phagocytosis by phagocytes (e.g., neutrophils and macrophages). These cell types are capable of engulfing viruses or viral components into intracellular phagosomes. Within these phagosomes, oxidative stress conditions, via upregulation of RONS generation, are created to mediate destruction of the phagocytosed pathogen. To generate sufficient quantities of RONS for this function, mitochondria are recruited to the phagosome through signaling cascades to produce mROS and supply electrons in the form of NADPH [138]. As a result, NOX2 can generate superoxide radicals in large quantities, which then dismutate into hydrogen peroxide. Hydrogen peroxide is then consumed by phagosomal myeloperoxidase (MPO) to produce hypochlorous acid, a secondary RONS, through secondary reactions. Other reactive species, such as hydroxyl radicals and singlet oxygen, are also involved in this process [139,140]. This process is commonly referred to as a respiratory burst, known to mediate destruction to the pathogen structure and activate additional signaling cascades that can promote the pathogen’s clearance [22,42,140]. Immune-associated RONS also have roles in the induction of adaptive immune responses. As a novel sensor for HSV-1, TLR3 is linked to the induction of antigen presentation by dendritic cells, which are involved in the induction of a robust CD8+ T cell response against HSV-1. TLR3-deficient mice demonstrate impaired HSV-1-specific CD8+ T cell responses and loss of control over HSV-1 infection in epithelial cells [127]. TLR3 is a sensor that can become activated by oxidative stress induced during viral infections [141]. Therefore, its role in promoting CD8+ T cell responses could be influenced by RONS. Nitric oxide was also observed to modulate the adaptive immune response by regulating the proliferation of lymphocytes in response to HSV-1, while also recruiting immune cells for antigen presentation [39]. These findings indicate that RONS can facilitate adaptive antiviral responses and are critical mediators of the cell-based immune response against HSV-1. The potent antiviral capabilities of RONS have garnered interest in the development of RONS cocktails as antiviral therapies. RONS have demonstrated roles in the cellular antiviral response, and some species are currently utilized as the basis of disinfectant agents for the decontamination of surfaces. By itself, ozone inactivates a multitude of viruses. For example, ozone application to cell-free poliovirus-1, which is a single-stranded RNA virus, was shown to modify the protein sequences within the viral capsid, resulting in the impairment of viral adsorption. Furthermore, ozone damaged the viral RNA genome, leading to its inactivation [142]. Similarly, a 3-h application of ozone to cell-free HSV-1 resulted in 90% inhibition of viral infection. Not only did ozone treatment reduce viral infectivity, it was also shown to induce cytokine expression in the infected cell that promoted an innate immune response [143]. Ozone can enter the liquid phase and interact with other RONS such as nitrogen dioxide to further enhance its antiviral effect. Specifically, the concurrent presence of ozone and nitrogen dioxide in liquid media coincided with the enhanced generation of secondary RONS, such as dinitrogen pentoxide [144]. As a secondary species, dinitrogen pentoxide can rapidly accumulate and contribute to the oxidative damage of viruses. Like ozone, dinitrogen pentoxide acts as an antiviral agent in plants by decreasing viral lesions and inducing antiviral immunity in plants [145]. As a common disinfectant, hydrogen peroxide is known to be a powerful antimicrobial agent against viruses and microorganisms. Hydrogen peroxide has antiviral effects against both cell-free and intracellular viruses. Specifically, hydrogen peroxide is virucidal against many viruses spread through contaminated surfaces in healthcare, veterinary, and public facilities. These include feline calicivirus (FCV), transmissible gastroenteritis coronavirus (TGEV), avian influenza virus (AIV), and swine influenza virus (SwIV) [146]. Additionally, hydrogen peroxide was effective for decontamination of human severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), with enhanced viral inactivation under acidic conditions through the co-presence of acidic compounds [147]. In a study involving the surface decontamination of influenza virus, a 2-min exposure to hydrogen peroxide vapor resulted in 99% viral inactivation [148]. The virucidal action of hydrogen peroxide was also reported to increase with the co-application of other RONS like sodium nitrite against FCV. This was mostly mediated through the formation of peroxynitrite, a secondary RONS. The activity of peroxynitrite was confirmed with a reduction in the pH of the exposed medium and reduced virucidal activity following the administration of ascorbic acid, a scavenger for peroxynitrite [149]. Hydrogen peroxide can also result in the formation of hypochlorous acid, a reactive chlorinated species, in a reaction catalyzed by MPO. Hypochlorous acid is commonly produced in leukocytes to cause oxidative stress conditions during phagocytosis [150]. Hypochlorous acid is also used as a disinfectant and is shown to inactivate viruses [151]. Some studies have also investigated hydrogen peroxide as a possible vaccine supplement, given its potent signaling capabilities. Interestingly, in a hydrogen peroxide-inactivated west nile virus (WNV) vaccine, specific CD8+ T cell and antibody-mediated responses were observed, resulting in immune memory upon re-infection with WNV [152]. Singlet oxygen is a short-lived RONS known to directly oxidize lipids containing carbon double bonds. Singlet oxygen is most effective against enveloped viruses (viruses enclosed by lipid envelopes). Singlet oxygen inactivates viruses by disrupting the viral envelope, which compromises its capacity to mediate entry into a target cell. In a singlet oxygen inactivated pseudorabies virus (PRV) vaccine, oxidized lipids within the virion structure also elicited a strong antibody-mediated response, while reducing PRV infectivity [153]. Singlet oxygen has also been reported to modify key amino acids in protein structures within the FCV capsid. This includes amino acids that contain double bonds in their side chains and are susceptible to disulfide bond formation [149]. As a therapy, singlet oxygen generation is typically seen during photodynamic therapy (PDT) to inactivate viruses like SARS-CoV-2. However, it must be delivered to target cells immediately after generation for maximum therapeutic effect [154]. Endogenously, nitric oxide is a primary RONS involved in cellular antiviral defense. Following viral sensing by cellular PRRs, immune signaling pathways (e.g., NF-κB) are activated to promote the expression of proinflammatory cytokines that enhance the recruitment of innate immune cells to the site of viral infection. Additionally, immune signaling pathways involved in antiviral defense can further upregulate the expression of iNOS to promote nitric oxide generation [155]. Nitric oxide also has a critical role in modulating immune responses during early HSV-1 infection as inhibition of nitric oxide resulted in higher levels of HSV-1 replication and increased disease pathology in brain tissues [156]. Given its role in the antiviral defense, some studies have explored the use of exogenous nitric oxide as an antiviral therapy. Recently, this activity was demonstrated through the application of nitric oxide plasma activated water (NO-PAW), which allowed the delivery of gaseous nitric oxide into water, to samples of SARS-CoV-2 infected cells. Treatment of infected cells with NO-PAW resulted in the suppression of spike protein expression, the entry protein for SARS-CoV-2, along with other key viral proteins. In addition, NO-PAW was also able to upregulate the antiviral gene response in cells [157]. Although RONS are produced by and used by the cell in its antiviral defense, these species are often not produced in quantities sufficient to effectively control viral infections. Therefore, strategies that boost RONS and their effects have been explored as stand-alone antiviral therapies against viral infections. Many of the potentially therapeutic RONS cannot be produced artificially due to their stringent generation requirements and short half-lives. Furthermore, clinical approaches that use chemistry-based methods to generate RONS are often limited by the short half-lives of chemically active products and the identification of effective means to deliver them. These limitations can be addressed in therapeutic approaches involving the application of non-thermal plasma (NTP). The field of plasma medicine is defined by explorations of NTP as a tool for the controllable delivery of RONS to biological targets. Also referred to as cold atmospheric plasma (CAP), gas plasma, or low temperature plasma (LTP), NTP has emerged as a relatively safe therapeutic tool with applications in wound healing, cancer, and infectious disease [158]. As the fourth state of matter, NTP is defined as a partially ionized gas composed of chemical, electrical, radiative, and thermal components (Figure 5). During the generation of NTP, the ionized gas produced at ambient temperature and pressure, with the application of electric fields, can excite and ionize electrons to produce RONS [158,159,160,161]. The quantities of RONS produced are regulated by changing applied electric fields, voltage, frequency, duty cycle, time, and distance of application, depending on the device. With their controllable delivery via NTP, these highly reactive species have the ability to modify macromolecular structures, induce intracellular signaling cascades, cause immunogenic cell death (ICD), and induce immune responses in a biological target [162]. While NTP is composed of multiple components, the ability to generate multiple species of RONS (some of which cannot be produced naturally by the cell or synthesized by chemical-based approaches) is critical to its ability to cause biological effects, including the inactivation of many types of viruses [163]. Redox homeostasis is an important determinant in the survival of cells. During viral infections, this homeostasis is challenged by oxidative stress induced by the cell to protect itself and by the virus to promote its replication and pathogenesis. Therefore, the redox state of the cell during a viral infection determines the likelihood of the cell being able to control the viral infection. Given the effective hijacking mechanisms of viruses, infections usually overwhelm the cell and allow the virus to utilize its machinery for its replication, which downregulates cellular DNA replication. With NTP and its controllable delivery of antiviral RONS, this redox state can be shifted back in the cell’s favor to promote interference with virus replication. While RONS are important mediators of antiviral activity, other components of NTP also contribute to its antiviral activity. By themselves, electric fields and UV radiation can kill microorganisms and can act as stand-alone therapies for treating infections [164,165,166,167]. UV light also induces oxidative stress [111,168,169] and can promote the generation and delivery of RONS to an infected cell. Additionally, cells exposed to electric fields and UV light induce the generation of RONS, activating key cellular signaling pathways in response to macromolecular damage and apoptosis [160,170,171]. Pulsed electric fields, which cause membrane permeabilization and are the basis of electroporation, also induce both extracellular and intracellular RONS in cells [172]. Although NTP can sometimes cause slightly elevated temperatures in biological targets, the negligible temperature increases caused by NTP application have little to no impact on virus inactivation [173]. It is important to note that no single component is produced in enough quantities to have a stand-alone effect. It is hypothesized that the different components of NTP work synergistically to produce the observed antiviral response. Therefore these subtherapeutic amounts of each component, working together, make NTP a unique tool for inactivating viruses [160]. NTP is generated and delivered to a biological sample through specialized devices. In research and clinical settings, two main types of devices are used. Dielectric barrier discharges (DBD) devices allow the direct application of NTP to samples. These devices consist of at least one electrode encased in a dielectric material to which a high voltage is applied. The counter electrode could be the biological substrate as shown in Figure 5 for the example of a so-called floating DBD. NTP-generated RONS are directly deposited onto samples across small gap distances between the sample and the DBD electrode [158,174,175]. In addition to RONS, the direct interaction between the plasma and the sample delivers ions, UV photons, and high electric fields to the biological sample. In contrast, plasma jets are designed with a tube-like configuration that houses an electrode. Unlike DBD devices, plasma jets generate NTP at a larger distance from the target. The components of NTP are directed onto the target by the flow of typical inert gases such as helium or argon [158,176]. Plasma jets can operate in two modes: with and without direct contact of the plasma to the biological sample. When there is direct contact with the biological substrate, the interactions with a plasma jet are similar to interactions with DBD plasma as shown in Figure 5. When there is no direct interaction of plasma with the substrate, the substrate is not subjected to high electric fields and ionic species and biological interactions are mainly due to RONS. Although both types of NTP devices generate RONS, the composition of RONS delivered to the sample varies considerably between devices. Furthermore, the composition and quantity of NTP-generated RONS can be altered in a device-specific manner through adjustments in voltage, frequency, exposure time, electrode distance to the target, and type of working gas. The parameters that mediate the delivery of RONS are specific to the type and design of the device and application modality [160,163]. The composition of the RONS generated is also highly dependent on the power supply utilized to generate the NTP, as well as the sample being exposed. In the gas phase, the working gas and the parameters that result in NTP generation can influence the composition of RONS produced. As these species are delivered to a target, the interactions with the liquid-phase (typically cell culture medium or interstitial fluids in in vitro or in vivo applications) can result in the formation of secondary species [177]. Among the various RONS that can be produced, ozone (O3), singlet oxygen (1O2), hydroxy radicals (OH), hydrogen peroxide (H2O2), nitric oxide (NO), nitrogen dioxide (NO2−), peroxynitrite (ONOO−), and dinitrogen pentoxide (N2O5) have been implicated in pathogen inactivation [149,163]. The capability to generate and deliver these RONS controllably makes NTP a potential antiviral agent that can be used effectively to treat infections by viruses such as HSV-1. The antiviral activity of NTP-associated RONS has been clearly documented and summarized by Mohamed et al. [163]. Due to NTP’s ability to inactivate viruses and reduce their infectivity, NTP can be a promising therapeutic preventative measure for infections by human and non-human viral pathogens. NTP also has the ability to inactivate the plant virus, Potato Virus Y, which is a common drinking water contaminant. Studies involving NTP and this virus demonstrated NTP-mediated viral inactivation and proved NTP to be an environmental-friendly and safe decontamination tool for use in irrigation systems [178]. NTP was also shown to be an effective decontamination tool for foodborne viruses such as norovirus (NoV), a single-stranded nonenveloped virus found in fecal-contaminated produce and drinking fluids. Not only was its inactivation found to be consistent with increasing exposure times to NTP, but RONS were speculated to be the dominant effectors in its antiviral mechanism [179]. The animal virus FCV, a surrogate for human NoV, has also been the focus of research to test the antiviral efficacy of NTP. Using an argon plasma jet, FCV inactivation was more apparent with shorter exposure distances and increasing power. A correlation between NTP exposure and the oxidation of FCV viral capsid mediated by the presence of NTP-generated RONS was suggested. Specifically, modifications of the capsid and viral inactivation were proposed to be influenced by the presence of RNS, ozone, singlet oxygen, and the formation of peroxynitrite [173]. The antiviral effect of NTP against FCV has been shown using a variety of plasma devices and operational conditions, including remote plasma treatments with the effluent of a 2-dimensional (2D)-DBD plasma, which delivered mainly long-lived RONS to the virus. When NTP was applied directly, FCV inactivation could be induced by the actions of ozone in the gas-phase. In contrast, when NTP exposure was indirect, through application of liquid enriched in NTP RONS, NOx species were the dominant effectors. Additionally, pH changes secondary to peroxynitrite formation played a role in FCV inactivation [180]. Other studies that focused on FCV inactivation also highlighted ozone and peroxynitrite as the key antiviral agents in NTP function by producing oxidative damage to key amino acid residues within the viral capsid of FCV [144,181]. Few studies have investigated NTP as a potential therapeutic alternative for viruses that infect humans and cause chronic disease. Hepatitis B virus (HBV), a viral pathogen associated with a chronic liver disease, is spread through contact with bodily fluids. NTP, generated by a DBD device, was applied to blood samples infected with HBV. Key HBV antigens were susceptible to RONS-mediated damage following NTP exposure, leading to inactivation of the virus that increased with longer durations of exposure to NTP [182]. The antiviral effect of NTP was also studied using cells infected with HIV-1. NTP exposure of HIV-1-infected cells reduced HIV-1 infectivity, and impaired virus-cell fusion and viral assembly. Additionally, it was speculated that NTP exposure induced cellular factors that promoted an antiviral environment in macrophages, preventing further viral entry [183]. Similarly, viral entry mechanisms were abolished by NTP application to SARS-CoV-2. Specifically, the viral spike protein was found to be altered in its conformation and impaired in its ability to bind to cellular receptors. NTP exposure decreased the infectivity of SARS-CoV-2, and even resulted in the disruption of cell membranes which led to oxidative damage of viral RNA inside the cell [184]. The antiviral effect of NTP on HSV-1 was investigated in a model for herpes keratitis, in which explanted HSV-1-infected human cornea cells were indirectly exposed to NTP. In these experiments, cell culture medium was exposed to NTP and then applied to the HSV-1-infected cells, resulting in an 80% reduction in viral infectivity and increased antiviral activity with longer durations of NTP exposure. Importantly, minimal host cell cytotoxicity was observed [185]. An increase in 8-oxodeoxyguanosine (8-OHdg), a marker for oxidative DNA damage correlated with increased virus inactivation without damage to cells [186]. Oral, ocular, and genital lesions are considered hallmarks for HSV-1 infection and appear when the virus is actively replicating in mucosal epithelial cells [2,3]. In an envisioned NTP-based therapeutic approach, NTP will be applied directly to lesions produced by active HSV-1 infection. The application of NTP to HSV-1 lesions will deliver NTP effectors to the local area of the epithelium that includes cell-free virus, cells undergoing productive infection, and uninfected cells that may be targets for HSV-1 infection. Direct application of NTP to these lesions will likely reduce virus infectivity through oxidative damage to virus components, including envelope proteins and the DNA genome. NTP may also indirectly have an antiviral effect by altering a host cell’s capacity to support productive infection and preventing infection of uninfected cells by altering cell surface molecules that participate in viral binding and entry. Studies to date have focused on the short-term antiviral effects of NTP using cell-free HSV-1 and HSV-1 infected cells, with changes in viral infectivity as the measure of the antiviral effect of NTP. The in vitro antiviral effect of NTP on HSV-1 infection was demonstrated through the application of NTP-treated cell culture medium to HSV-1-infected cells (indirect NTP) [185]. There are multiple mechanisms through which NTP could directly affect HSV-1. NTP is proposed to act as an antiviral agent through the controllable delivery of RONS, which are known to interact and modify macromolecular structures. Proteins, lipids, and nucleic acids in enveloped viruses such as HSV-1 are likely susceptible to RONS-mediated damage. For example, cysteine, a sulfur-containing amino acid, is prone to disulfide bond modification by RONS [187]. Additionally, MPO, an enzyme produced by cells during phagocytosis, can convert hydrogen peroxides into ions that have been implicated in the oxidation of tyrosine residues [20,188]. Given the abundance of proteins within the HSV-1 virion structure (e.g., envelope, capsid, and tegument proteins), RONS generated by NTP likely impair HSV-1 infectivity through protein modification. RONS can also affect carbon double bonds in lipid-based structures, resulting in lipid peroxidation. The viral envelope, which is important for protecting HSV-1 from the extracellular environment and for mediating fusion with target cells, can be disrupted by oxidative stress conditions through lipid modification [153]. Lastly, nucleic acids are prime targets for RONS-mediated damage. Specifically, RONS-induced modifications are typically observed within the sugar backbone of RNA and DNA molecules. Base pairing can also be disrupted by RONS, leading to the introduction of mutations in the viral genome that can impair HSV-1 infectivity [20]. Although not proven, some studies have alluded to RONS-mediated damage of viral macromolecules as the mechanism underlying the antiviral activity of NTP. This conclusion was supported by measurements of 8-OHdg, which is a marker for oxidative DNA damage. Following NTP exposure of HSV-1-infected ocular cells, increases in 8-OHdg correlated with the inactivation of HSV-1 [186]. Given the complexity of the HSV-1 structure, many viral components can be targets for damage caused by NTP RONS. As previously described, this damage will take the form of modifications to viral macromolecular components, leading to impairment of their functions. Due to the location of the envelope and envelope proteins on the exterior of the virus particle, reductions in virus infectivity attributable to NTP exposure are most likely to result from oxidative damage to the viral glycoproteins that mediate viral entry and modifications of lipids within the viral envelope that protect the encapsulated genome. Due to its chemical stability and hydrophilicity, hydrogen peroxide is an example of a RONS that can penetrate membranes [189]. As a result, hydrogen peroxide may have the ability to pass through the HSV-1 lipid envelope and gain access to the interior of the HSV-1 virion structure, causing oxidative damage to viral proteins and DNA contained within. These effects may also contribute to reductions in infectivity. Redox control in a cell is important for cellular homeostasis and preventing damaging oxidative stress conditions. In the context of HSV-1, there is a clear correlation between infection and the induction of oxidative stress [85]. Part of this stress response is created by the cell. RONS are often produced to trigger intracellular signaling cascades that result in the promotion of an antiviral environment that is unfavorable for HSV-1 infection [104,127,128]. Meanwhile, HSV-1 can induce its own oxidative stress response that overcomes the cell’s immune defense and enhances its own pathogenesis. This often involves the degradation of host proteins, recruitment of cellular machinery for its replication, and interference with signaling pathways through the modification of macromolecules [44,47,57,69]. Overall, HSV-1-induced oxidative stress aims to impair the cell’s ability to promote its immune clearance, allowing it to replicate or persist in a dormant state within the infected cell. Induction of oxidative stress by HSV-1 can be observed through the recruitment of VICE domains, the localization of heat shock proteins, and the activation of the unfolded protein response (UPR) in the ER. To promote the assembly of proteins for viral replication, HSV-1 induces ER stress to target cellular proteins for degradation to promote the proper assembly of virions [64,85]. This results in the accumulation of oxidized proteins and causes further dampening of the immune response towards HSV-1. In a model for diet-induced obesity, proteins associated with ER stress and the activation of the UPR were downregulated in NTP-exposed adipocytes, both in vitro and in vivo, suggesting that NTP may inhibit ER stress [190]. This ability of NTP to inhibit ER stress may allow the restoration of redox homeostasis in cells subjected to HSV-1 infection. NTP is also implicated in the increased expression of antioxidants that detoxify accumulating RONS concentrations, contributing to efforts in normalizing cellular redox levels. NTP exposure of HaCaT cells upregulated Nrf2 signaling, a transcription factor in the Nrf2-Keap1 pathway involved in the transcription of antioxidant genes as early as 20 s post-exposure to NTP and up to 24 h later [191,192]. Additionally, hydrogen peroxide, a key component of NTP, partially decreases Keap1, a negative regulator for Nrf2 expression [191]. Furthermore, NTP increases GSH levels, another antioxidant important in hydrogen peroxide neutralization [193]. This suggests that application of NTP has the potential to promote regulation of RONS concentrations in the cell, compromising the ability of HSV-1 to manipulate oxidative stress in the host cell. Although NTP has a demonstrated antiviral effect on HSV-1, the mechanism by which RONS generated by the application of NTP to infected cells contributes to the antiviral effect of NTP is unclear. Based on reports cited above, it may be speculated that NTP exposure of HSV-1-infected cells could potentially stabilize the redox balance in a cell, diminishing oxidative stress mechanisms that favor replication. In addition to its antiviral activity, NTP has potential as an immunotherapy for HSV-1 infection. RONS, as one of the main effectors of NTP, have demonstrated immunomodulatory effects on cancer cells, inducing immunogenic cell death (ICD), characterized by cell death that elicits an immune response [194,195]. The induction of ICD is normally accompanied by the display of stress-associated molecular patterns (SAMPs) on the cell surface [194,195,196,197,198,199]. These include calreticulin (CRT) and molecular chaperones such as Hsp90. In particular, Hsp90 was cleaved following exposure to NTP, and kinases that aid in its normal function were degraded [197]. Additionally, there is release of other molecules including ATP, high mobility group box protein 1 (HMGB1), and proinflammatory cytokines in response to NTP exposure. The emission of these SAMPs enhanced the functions of innate immune cells, including antigen presentation, facilitated phagocytosis, and promoted an inflammatory response within tumor environments [194,195,196,198]. This resulted in T helper cell activation as evidence of stimulated adaptive immune responses [200]. Literature regarding immunomodulatory changes, or SAMPs, caused by NTP in virus-infected cells is sparse. Our work in this area demonstrated the immunomodulatory effect of NTP in the context of HIV-1 infection using J-Lat cells. These cells, which contain an integrated latent HIV-1 genome that is not capable of supporting multiple rounds of replication, serve as a model for latently-infected T lymphocytes. NTP exposure of J-Lat cells resulted in emission of molecules, characteristic of SAMPs that are typically associated with ICD in tumor cells. Furthermore, there was upregulated phagocytosis by antigen presenting cells, suggesting an adjuvant effect of NTP. There was also evidence of neoepitope generation that may increase the breadth of adaptive immune responses [201]. Similar mechanisms may be activated in HSV-1-infected cells that trigger signaling pathways involved in the cellular immune defense [162]. Innate and adaptive immune responses play integral roles in the host defense against HSV-1 infection. As previously mentioned, TLRs recognize viral components within the HSV-1 virion on the plasma membrane and within the cytoplasm [126,127,128,202]. Upon sensing HSV-1 components, TLRs induce immune signaling pathways that promote the transcription of antiviral mediators by the infected cell. These mediators include type 1 IFNs and other proinflammatory cytokines that are typically induced during viral infections. Type 1 IFNs, in particular, induce the expression of interferon stimulated genes (ISG), the products of which attract patrolling innate immune cells to the site of acute HSV-1 infection [13,55,63,126,128]. This trafficking of immune cells (e.g., neutrophils, macrophages, and dendritic cells) elicits their effector innate functions, which include phagocytosis and subsequent antigen presentation to adaptive immune cells (e.g., T cells, B cells) [203,204,205]. As a result, both T cells and B cells become activated, stimulating specific adaptive responses toward HSV-1. Specifically, CD8+ T cells, which we propose will be the main mediators of the NTP-stimulated immune response, can secrete antiviral cytokines toward invading pathogens and directly kill infected cells to inhibit viral replication [205]. Additionally, activation of B cells promotes the production and secretion of antibodies against HSV-1 antigens to prevent spread to neighboring susceptible cells [206]. To evade these immune responses, HSV-1 may escape the mucosal epithelium to establish latency in neurons. By silencing its genome expression, HSV-1 avoids sensing by the host immune system [4]. With the application of NTP to HSV-1 lesions, these responses can be stimulated or enhanced, shortening the course of acute infection and forcing HSV-1 into viral latency. Due to this shortened replication cycle in the epithelium from HSV-1′s evasion tactics and the stimulated adaptive immune response, fewer virions will be produced that can travel into the nervous system, decreasing the number of latently infected cells. Over time, this can decrease the frequency and number of reactivation events leading to the recurrence of acute replication or viral reactivation. HSV-1 has developed many ways to overcome the cellular sensing and immune clearance tactics to persist in its host. As previously mentioned, this includes the manipulation of the cell’s redox state which can influence immune signaling and responses toward HSV-1. Application of NTP may be effective in overcoming viral evasion strategies through the generation of NTP-associated RONS that will enhance and stimulate more robust antiviral responses in the cell. Signaling pathways, such as NF-κB, which induce type 1 IFN responses, are upregulated by NTP exposure [104,126,127,128]. In addition, the application of NTP allows the emission of SAMPs on the cell surface that recruit innate immune cells [201]. These changes can lead to the aforementioned cellular innate and adaptive immune responses directed against HSV-1. The presence of NTP-generated RONS overcomes HSV-1′s mechanisms of suppressing host cell responses. By controlling the cellular redox environment, NTP could prove to be an effective immunotherapy against HSV-1 infection. The use of NTP as a treatment for HSV-1 infection will require an integrated understanding of the roles played by oxidative stress during infection and treatment. Oxidative stress has multiple functions and effects in immune responses mounted by cells against infection, in HSV-1 replication in host cells, and in cellular and viral responses to NTP application (Figure 6). Some of the effects of RONS and modulated oxidative stress are unique to immunomodulation, infection, or NTP application. However, some roles are common to two or all three aspects of a putative treatment. Overlapping roles for RONS and oxidative stress may be advantageous or detrimental to treatment effectiveness. For example, the boost in cellular RONS by NTP application to an infected cell may augment RONS-mediated cellular mechanisms already promoting effective innate and adaptive immune responses to infection. On the other hand, oxidative damage to macromolecules and organelles during productive HSV-1 infection may be further increased by NTP application. The application of an NTP-based treatment of HSV-1 infection (or other infections or diseases) will need to be conducted at a dose that comprehensively considers the beneficial and detrimental effects of RONS and oxidative stress. Once considerations of NTP dose are satisfied, the potential net effects of immunomodulation induced by NTP application to an HSV-1-associated lesion are the promotion of more effective innate antiviral responses in infected cells, induction of innate protective responses in nearby uninfected cells, and recruitment of immune cells that will participate in a more effective adaptive response to infection (Figure 7). By controlling the cellular redox environment and modulating both innate and adaptive responses against HSV-1, NTP could prove to be an effective immunotherapy against HSV-1 infection. HSV-1 continues to be a global health concern, with high infection rates worldwide and its ability to cause lifelong infection. Although the current antiviral therapies are effective in moderately reducing the severity of symptoms associated with acute infection, they are ineffective with respect to curing a patient after primary HSV-1 infectious due to their inability to address viral latency. Therefore, HSV-1 persists in its host, risking dissemination of the virus to other organs and causing other acute and chronic diseases. For HSV-1, the manipulation of redox homeostasis is an evasion strategy to overcome immune clearance from the cell and to craft a cellular environment favorable for viral replication. On the other hand, maintenance of redox homeostasis by the cell is crucial in controlling the immune response directed toward HSV-1 and preventing damaging oxidative damage by RONS. Therefore, control over the redox balance within an infected cell is one of the key factors involved in determining the outcome of HSV-1 infection. Given the antiviral properties of RONS in the cell and in commercial disinfectant agents, RONS have the potential to be harnessed as antiviral therapies. NTP technology is an inexpensive, innovative method of producing RONS responsible for inducing desired biological effects. It has the potential to act as a multi-faceted therapy effective against HSV-1 disease. Decreases in HSV-1 infectivity attributed to the direct antiviral effect of NTP on cell-free virus will decrease the overall viral burden in the lesion, thereby decreasing the clinical symptoms of infection and accelerate resolution of the lesion. An added benefit of reduced titers in the lesion will be a smaller pool of latently infected neurons that serve as reservoirs of long-term infection. The immunomodulatory effects of NTP exposure will augment local innate antiviral effects and boost adaptive immune responses involving HSV-1-specific CD8+ T lymphocytes. The combined antiviral and immunomodulatory activities of NTP are hypothesized to provide short-term relief for acute infection as well as long-term immunological control over reactivation from latently infected neurons, as indicated by reductions in or full control of recurrent lesions in HSV-1-infected individuals. Of course, the potential of an NTP-based therapy must be fully explored along a developmental path that leads to clinical use. Future studies of the use of NTP as a therapy for HSV-1 infection will include examinations of how NTP can be used to treat lesions, a common manifestation of human HSV-1 infection. Using a preclinical murine model of HSV-1 infection, the antiviral and immunomodulatory effects of NTP on HSV-1 infection will be examined in the context of innate and adaptive, HSV-1-specific immune responses. These models will provide the insights necessary to develop this novel therapeutic as a non-invasive, pain-free, and effective clinical approach against HSV-1 infection.

PMC10003308

Gang Ouyang,Le Yuan,Xiao-Qin Xia,Wanting Zhang,Mijuan Shi

Transcriptomes of Zebrafish in Early Stages of Multiple Viral Invasions Reveal the Role of Sterols in Innate Immune Switch-On

23-02-2023

early stage of viral infection,stress,steroids,switch-on innate immune

Although it is widely accepted that in the early stages of virus infection, fish pattern recognition receptors are the first to identify viruses and initiate innate immune responses, this process has never been thoroughly investigated. In this study, we infected larval zebrafish with four different viruses and analyzed whole-fish expression profiles from five groups of fish, including controls, at 10 h after infection. At this early stage of virus infection, 60.28% of the differentially expressed genes displayed the same expression pattern across all viruses, with the majority of immune-related genes downregulated and genes associated with protein synthesis and sterol synthesis upregulated. Furthermore, these protein synthesis- and sterol synthesis-related genes were strongly positively correlated in the expression pattern of the rare key upregulated immune genes, IRF3 and IRF7, which were not positively correlated with any known pattern recognition receptor gene. We hypothesize that viral infection triggered a large amount of protein synthesis that stressed the endoplasmic reticulum and the organism responded to this stress by suppressing the body’s immune system while also mediating an increase in steroids. The increase in sterols then participates the activation of IRF3 and IRF7 and triggers the fish’s innate immunological response to the virus infection.

Transcriptomes of Zebrafish in Early Stages of Multiple Viral Invasions Reveal the Role of Sterols in Innate Immune Switch-On Although it is widely accepted that in the early stages of virus infection, fish pattern recognition receptors are the first to identify viruses and initiate innate immune responses, this process has never been thoroughly investigated. In this study, we infected larval zebrafish with four different viruses and analyzed whole-fish expression profiles from five groups of fish, including controls, at 10 h after infection. At this early stage of virus infection, 60.28% of the differentially expressed genes displayed the same expression pattern across all viruses, with the majority of immune-related genes downregulated and genes associated with protein synthesis and sterol synthesis upregulated. Furthermore, these protein synthesis- and sterol synthesis-related genes were strongly positively correlated in the expression pattern of the rare key upregulated immune genes, IRF3 and IRF7, which were not positively correlated with any known pattern recognition receptor gene. We hypothesize that viral infection triggered a large amount of protein synthesis that stressed the endoplasmic reticulum and the organism responded to this stress by suppressing the body’s immune system while also mediating an increase in steroids. The increase in sterols then participates the activation of IRF3 and IRF7 and triggers the fish’s innate immunological response to the virus infection. The primary and important line of defense against viral invasion in fish is the innate immune system, which is made up of cellular, humoral, and physical barriers [1]. As the sentinels in innate immunity, the pattern recognition receptor (PRR) genes have attracted the most attention in immunology research, which has been heavily focused on changes in major innate immunity-related genes in fish triggered by a particular viral infection through PRRs [2,3,4,5]. The detection of the non-self is the first and most important stage in the induction of the innate immune response. However, in virus-infected fish, does the PRR actually represent the first stage of the immune response? Is there another system that controls this procedure? If so, does this system recognize viruses differently than PRR? All of these issues have yet to be researched. For example, the immune system in fish can be controlled by the neuroendocrine system [6,7]. Numerous studies have shown that the neuroendocrine system regulates the synthesis of specific substances, such as hormones, in the body under stressful conditions, influencing fish immunity [8,9,10]. This modulation depends on the stress time course and is multifaceted, not just immune-suppressive or immune-enhancing [11,12]. Research on the substances involved in this intricate regulatory process is likewise scarce, concentrating only on catecholamines and a few other sterol hormones, such as adreno-corticotropic hormone, corticosteroid-releasing hormone, and glucocorticoids [11,12,13]. The hypothalamus–pituitary–gonadal axis and the hypothalamus–pituitary–interrenal axis regulate steroid production in teleost fish. According to Tokarz et al. (2015) [14], all genes associated with steroidogenesis have been found in different species, demonstrating the significance and universality of these tiny molecules. These substances are engaged in numerous critical fish life processes. In reality, in addition to steroid hormones, different types of cholesterol have a role in viral resistance as non-hormonal steroids. For instance, 25-hydroxycholesterol (25HC) can increase the body’s viral resistance by suppressing the fusion of numerous viruses’ membranes with host cells. Cholesterol 25-hydroxylase, which converts cholesterol to 25HC, is also one of the interferon (IFN) target genes [15,16]. Furthermore, 7-dehydrocholesterol (7-DHC) can increase IFN-I production by promoting the phosphorylation of interferon regulatory factor 3 (IRF3) [17]. This study suggests that sterols may play a role in activating the innate system. In our study, zebrafish at 3 days post-fertilization (dpf) were chosen as samples [18] to eliminate the effects of acquired immunity. They were infected with four viruses including two DNA viruses (crucian carp herpesvirus (CAHV) [19] and Cyprinid Herpesvirus 2 (CyHV2) [20]) and two RNA viruses (spring viraemia of carp virus (SVCV) [21] and grass carp reovirus II (GCRV II) [22]). Most of the important freshwater fish farmed in China are cyprinids, such as grass carp, common carp, and crucian carp. These four viruses are the pathogenic viruses of the major viral diseases of these economically-important fish. The expression profile of fish infected with each virus for 10 h revealed that at the start of viral infection, a generalized system may exist in fish to turn on innate immunity. This system recognizes the virus before PRRs and may be activated by excessive protein synthesis. This mechanism then promotes the synthesis of sterol molecules to mediate the overexpression of IRF3 and IRF7 [23] and thus provide protection against viruses. Four viruses were used to immerse zebrafish larvae, which lack the acquired immune system, in order to study the first immune response of fish to infections by various viruses. In total, 15 zebrafish samples consisting of 3 replicates from each of the 5 zebrafish groups (4 treatments and a control) were subjected to RNA-seq. The mapping rate is 93.27 ± 0.11% and the clean data are 43.59 ± 6.24 M reads. The data were reduced to 32.41 ± 4.28 M reads after clustering by unique molecular identifiers (UMIs). Evidently, the standard deviation of readings for each sample was also lowered (Table S1). Reads were assembled into a transcriptome of 107,348 transcripts from 62,671 genes using NCBI’s most recent GFF file (GRCz11). In total, 26,370 of these genes only encode ncRNA (non-coding RNA), while 4146 mRNA-coding genes were transcribed at a very low level. The count matrix of the remaining 32,155 genes was used for differential expression analysis after these genes were removed. Two comparisons were done between the gene expression levels of the five groups: (1) comparisons between each of the four viral treatment groups and the control; and (2) comparisons between the treatments of two DNA viruses (CaHV vs. CyHV2) and two RNA viruses (GCRV II vs. SVCV). Comparisons with a 0.05 level of significance yielded DEGs. CyHV2 produced the fewest DEGs of the four viruses, while SVCV produced the most. The GCRV II-induced DEGs were highly imbalanced, with up to 91.88% being downregulated. Furthermore, there are only 45 DEGs between the treatments of two DNA viruses, whereas there are 1656 between the treatments of two RNA viruses (Figure 1A). In the four treatments, 1493 genes appear as DEGs at least once (Figure 1B). In all four treatments, the expression of 900 genes (60.28%) among these DEGs showed the same expression trend vs. control. In this study, these 900 genes were identified as potential basic genes (PBGs). The proportion of PBGs in each Venn diagram region of Figure 1B ranges from 50% to 100%. The PBGs are commonly found in overlapping regions of multiple treatments. For example, there are 102 genes that are differentially expressed in all four treatments, and all of them are PBGs. Based on the 900 PBGs, fourteen pathways were enriched (Figure 1C). These pathways are roughly divided into two groups: metabolism and immunity. The upregulated PBGs were mostly found in metabolic pathways. All PBGs were upregulated, particularly in the “steroid biosynthesis” and “protein digestion and absorption” pathways. A higher proportion of downregulated PBGs were found in immune-related pathways, with the complement and coagulation cascades pathway having the most distinct enrichment. For the pathway-enriched analysis, both PBGs and other DEGs (non-PBGs) for each virus were used to study the impacts. For each virus, the p-value and the number of PBGs and non-PBGs in each enriched pathway were displayed separately (Figure 2). CyHV2 induces very few non-PBGs, which are only enriched in the steroid biosynthesis pathway. The SVCV induced most non-PBGs, and notably, the aminoacyl–tRNA biosynthesis pathway only has DEGs during SVCV infection. Then, the number of common genes and pathway-specific genes was used to gauge the link between these enriched pathways because many genes are shared across multiple pathways. According to their biological function, the pathways are divided into six groups (groups A through F) (Figure 3). Group A, a subset of group B, is the main set of immune system pathways. It consists of five pathways that have several genes in common. With the exception of three DEGs in CaHV infection and six in SVCV infection, DEGs in group A were generally downregulated (Figure 3). Group B was an immune-related pathway set that included group A and six other pathways (arachidonic acid metabolism, glutathione metabolism, antigen processing and presentation, cytokine–cytokine receptor interaction, ferroptosis, and PPAR signaling pathway). Other DEGs in group B, like those in group A, were mostly downregulated during viral infection. The DEGs of the arachidonic acid metabolism pathway, in particular, were all downregulated without regard for virus specificity. Except for the antigen processing and presentation pathway, most of the upregulated genes in group B were enriched in SVCV infection. The upregulated genes in group C, which consists of the two insulin-signaling pathways, were also enriched in SVCV infection. Group D is a collection of pathways involved in the transmission of nerve signals. CaHV, CyHV2, and SVCV infections downregulated most of the genes in this group to varying degrees, while GCRV II infection slightly upregulated most of the same genes. In the initial phase of viral infection, the majority of platelet and complement pathway genes (group E) were downregulated. On the other hand, after infection with various viruses, the genes in intercellular communication pathways (group F) were mostly upregulated at various levels. Genes of the collagen family, in particular, were upregulated in all viral infections and even expressed significantly differently in CaHV infection. The MAPK signaling pathway and the phagosome pathway are the hub pathways in the pathway network, and they share genes with many other pathways. The majority of genes in these two pathways were downregulated. Steroid biosynthesis and aminoacyl–tRNA biosynthesis, on the other hand, share no genes with any other pathway enriched in this study. The number of upregulated DEGs in the steroid biosynthesis pathway in all treatments was ranked as SVCV > CyHV2 > CaHV > GCRV II, where no DEG was detected in GCRV II infection. Genes in the aminoacyl–tRNA biosynthesis pathway were all significantly upregulated in SVCV infection, but not in the other three viral infections. First, only two DEGs were identified following a comparison of DNA viruses (CaHV and CyHV2) and RNA viruses (GCRV II and SVCV). The expression levels of these two genes remained relatively constant across individuals during DNA virus infections but fluctuated more in control and RNA virus infections (Figure 4A). Second, the profiles of two RNA viruses, GCRV II (dsRNA) vs. SVCV (ssRNA), differ significantly, with a total of 1656 DEGs, including 815 upregulated DEGs and 841 downregulated DEGs. In total, 28 pathways were enriched based on these DEGs (p ≤ 0.05, Figure 4B). The enriched pathways were classified into four categories based on their functions: immune-related pathways, signal transduction pathways, nerve signal transmission pathways, and metabolic-related pathways. Across these categories, the proportions of upregulated and downregulated genes change. Downregulated DEGs are more prevalent in metabolic- and immune-related pathways than upregulated DEGs. The proportions of upregulated and downregulated DEGs in signal transduction pathways are not significantly different. However, in the neural signaling pathways, upregulated DEGs are significantly more common than downregulated DEGs. Third, only 45 DEGs were found between the infections caused by the two DNA viruses (CaHV and CyHV2), and two of these have no homologs in the nr database. Eleven of the remaining DEGs were upregulated, while 32 were downregulated (Figure 4 (C1)). The first 15 GO terms with the lowest p-value in biological process (BP) enrichment were classified into three groups: sterol biosynthesis, muscle tissue development, and coenzyme A metabolism (Figure 4 (C3)). In total, 13 DEGs are linked to the top 15 enriched GO terms. Additionally, the number of genes associated with various GO terms within a single category is typically the same. However, the organic cyclic compound biosynthetic process (GO: 1,901,362) stands out as an obvious exception because it has more DEGs than other GO terms in the same category (sterol biosynthesis) (Figure 4 (C2)). As a result, GO: 1901362 had been divided into a different category (Figure 4 (C3)). Each category of the 13 DEGs contains two copies of the enzyme 3-hydroxy-3-methylglutaryl-CoA reductase (hmgcra), which is involved in the production of terpenoid backbones. After gene co-expression analysis, all genes were grouped into 39 classes (Table S2), with class 1 to class 6 having significantly more genes than the other classes (Figure 5A). The enrichment of each of these six gene classes was examined independently (Figure 5B). The genes of class 1 are concentrated in neural signaling-related pathways, but the genes of these pathways are enriched in several classes, not just class 1. The ribosome and oxidative phosphorylation pathways are significantly enriched in class 2 genes. Protein synthesis and sterol-related pathways are enriched in class 3 genes. The class 4 genes are clearly associated with cellular innate immunity, and they are enriched in signaling pathways such as NF-kappa B, toll-like receptor, and TNF, among others. Class 5 is thought to be associated with RNA degradation, while class 6 is found in the complement system and intercellular junctions. It is worth noting that the two most important IFN regulators, IRF3 and IRF7, are both members of class 3. These two genes’ expression patterns did not correlate with nearly all PRRs (Figure 5C, upper triangle), and were even completely negative correlated with RIG-I. Despite this, these two genes were found to be positively associated with the majority of genes involved in aminoacyl–tRNA biosynthesis, protein processing in the endoplasmic reticulum (ER), lysosome, terpenoid backbone biosynthesis, and steroid biosynthesis (Figure 5C, lower triangle). We used RT-qPCR to test 12 genes on this pathway in light of the importance of the sterol biosynthesis pathway following viral infection in order to confirm the alterations regarding sterol biosynthesis genes of the zebrafish larvae. The RT-qPCR results were in line with the transcriptome, and in particular, dhcr7, hsd17b7, and tm7sf2 showed greater than 100-fold upregulation (Figure 6). Both previous studies [24,25,26,27,28] and our preliminary experiments showed that all four viruses can infect zebrafish. In our study, juvenile zebrafish were infected with these viruses and their expression profiles were analyzed at early stages of infection. The activation of type-I IFN pathway after infection in the results and the symptoms of the remaining zebrafish after sampling indicated that the infection experiments were successful. However, we compared our RNA-seq data to the genomes of all published strains of these four viruses, and no reads were mapped to any references. This may be related to the early sampling time when the viruses have not made enough copies to be detected. We wanted to address two key questions through the data analysis. The first question was whether fish have a unified response to virus infection during the early stage and whether this response relies on the PRRs to switch on innate immunity. Second, do fish have different response systems to different viruses during the early phases of infection? Specifically, are there different responses to DNA and RNA viruses in fish? Regardless of differences in the magnitude of gene expression change, the distribution of PBGs in all DEGs of the four viral infections (Figure 1B) demonstrates that different viral infections cause similar changes in fish. These changes involve a significant number of genes with highly consistent expression trends before and after virus infection. These genes function in the sterol-related pathways, protein metabolism, and innate immune system (Figure 1C), and the nervous system was enriched when virus-specific DEGs were also taken into account (Figure 3). Virus invasion in the infected fish we sampled was in its early stages. Surprisingly, no known PRR was upregulated, and nearly all were downregulated or unchanged. We suspect that at this point, the viruses had not yet been recognized by the host PRRs, and they were hosting the host cells in a frenzy to synthesize the proteins they required. We are unable to determine whether the elevated expression of genes involved in protein synthesis (Figure 3, group F) is due to viral hostage taking or the body’s antiviral reaction. Even though the majority of the genes in the “protein processing in endoplasmic reticulum” pathway were upregulated to reduce this stress, the abundance of newly generated proteins unavoidably stresses the host ER and causes the organism to go into stress mode. The interaction of stress and the immune system in fish is obvious, as is the response of fish to various stressors. It is now widely accepted that chronic stressors suppress fish immune systems, both innate and acquired [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]. The neuroendocrine system most likely regulates this process via several hormones or other small molecules [11]. In response to chronic stimulation, for example, the body generally downregulates the inhibitory neurotransmitter γ-aminobutyric acid (GABA), which causes high cortisol levels and immunosuppression [30]. Our study’s systemic changes were highly consistent with fish responding to chronic stress. DEGs on neural signaling pathways, including GABA receptors, were mostly downregulated (Figure 3, group D). Furthermore, many important innate immune-related pathways were suppressed. For example, after four viruses’ infections, all DEGs in the arachidonic acid pathway were downregulated, and prostaglandin, an arachidonic acid metabolite, is strongly associated with immune activation [13]. Furthermore, large proportions of DEGs in complement and other cellular innate immune pathways were downregulated, including key genes in these pathways, such as C3 and RIG-I. (Figure 3, group B). In contrast, genes in the steroid biosynthesis pathway (Figure 3), which provides precursors for steroid hormones, were significantly upregulated. It is suggested that during the early stages of virus infection, the fish may be stressed, resulting in immunosuppression. When the expression profiles of SVCV and GCRV were compared, it was discovered that the high production of sterols and their derivatives likely rescued the suppressed immune system. According to the distribution of DEGs of both viruses in the three gene blocks of the nervous system (Figure 3, group D), sterol biosynthesis (Figure 3), and innate immune system (Figure 3, group B), SVCV downregulated neural signaling pathways, including GABA, while upregulating sterol biosynthesis-related genes, and also activated the initial immune response, including high expression of IRF3 and IRF7. GCRV, on the other hand, did not appear to be activated in either neural signaling pathways or sterol biosynthesis, and even showed a slightly opposite expression trend compared to the other viruses, despite having the most downregulated DEGs in its innate immune system. It is hypothesized that stress mediated the high production of sterols and their derivatives as well as the occurrence of immunosuppression through the neuroendocrine system, but the former does not appear to be the cause of the latter; instead, the high production of sterols and derivatives may have rescued the suppressed immune system. Some immune activators are likely present in the high yield of sterols and their derivatives, in the same way that 7-DHC improves the effects of IFN production in mice [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]. The co-expression network analysis was used to classify all genes into 39 classes based on their expression patterns in order to further identify the pathways associated with IRF3 and IRF7, the key genes of the initial immune response. The first six classes contained significantly more genes than the other classes (Figure 5A), accounting for 70.54% of the total genes (22,700/32,177), with classes 1–3 containing more than 5000 genes per class and the remaining three classes containing around 2000 genes per class. The enrichment analysis revealed that each class’s function was distinct (Figure 5B). The upregulated PBGs were grouped into class 3, which is the focus of our study. While IRF3 and IRF7, two of the first key immune genes to be activated, were also members of class 3, these two genes were barely or negatively correlated with the PRRs (Figure 5C, upper triangle), and these PRRs were not clustered in class 4, the immune-related class (Figure 5C, upper triangle, Y-axis tags), implying that at the early infection stage, the PRRs in fish did not yet initiate the downstream immune response, but the organism had already begun to produce IFN to defend against the viruses. Additionally, IRF3 and IRF7, which belong to the same gene cluster, have a strong positive correlation with the majority of the genes in the top five enriched pathways of class 3. Two metabolic pathways, aminoacyl–tRNA biosynthesis and protein processing in ER, are involved in protein synthesis. In some studies, the defect of tRNA synthetase in zebrafish can cause excessive ER stress, which in turn leads to neuronal apoptosis [32]. The terpenoid backbone biosynthesis pathway is located upstream of steroid biosynthesis, and the lysosome pathway participates in the transmembrane transport of sterols [33,34]. In our study, this result demonstrates a positive correlation between protein, sterol, and IFN synthesis systems. The results of differential expression, co-expression analysis, and RT-qPCR indicate that in the early stages of viral infection, fish have a universal response system that recognizes the virus before the PRRs. This system is most likely activated by the stress of ER overload, and it causes a surge in the production of sterols and their derivatives via the neuroendocrine system, ultimately increasing the synthesis of IFN to defend against virus invasion. Additionally, we think that this system does not distinguish between DNA and RNA viruses when it comes to recognition, and that flcn and trive2 (Figure 4A) are considered to be DEGs of DNA vs. RNA virus infections because the two DNA viruses are herpesviruses, which cause these two genes to express themselves in a manner that is more similar to that of controls and RNA viruses. The fact that there were so few DEGs between these two herpesviruses further demonstrates how similarly the fish responded to infection. Interestingly, despite the low number of DEGs, they were almost enriched in sterol synthesis-related GO terms, including the most highly upregulated gene, cyp1a, which is also a sterol-related gene [35], and the significantly differential expression of sterol-related genes in the organism responding to two RNA viruses previously discussed. All of these findings lead us to further hypothesize that variations in how this system responds to viral infections are most likely caused by the degree of activation of sterol-related pathways, and that this variability may be connected to the type of virus or the infectivity of the strain used in an experiment, though this is not yet proven. In this investigation, two virus challenge trials were carried out, with the testing samples being 3 dpf zebrafish larvae at 10 h after infection. For the former, the transcriptome sequencing was done with larvae infected by the four viruses CaHV, CyHV2, GCRV, and SVCV respectively and with physiological saline as control. Each group had three replicates and each replicate consisted of 40 larvae. As for the latter, samples for RT-qPCR were obtained via SVCV infection and physiological saline immersion of larvae. Each sample also contained 40 zebrafish larvae. The previously reported protocol was followed in all viral challenge trials [36]. Total RNA was extracted using RNAiso Plus (TaKaRa Bio, Beijing, China) according to the manufacturer’s protocol. The mRNA was enriched with Oligo(dT) magnetic beads and fragmented with fragmentation buffer after being assessed for purity and integrity with NanoDrop (Thermo Fisher Scientific, Wuhan, China) and Agilent 2100 (Agilent, Beijing, China). The first strand cDNA was synthesized using random hexamers, and during the second strand cDNA synthesis, dTTP was replaced by dUTP to indicate strand specificity. The library was built after purification (AMPure XP beads), adaptor (including barcode) ligation, UDG degradation, and PCR amplification. The Agilent 2100 was used to inspect the quality of these libraries before they were used for paired-end sequencing on the HiSeqTM4000 (Illumina, Beijing, China). Under the accession number CRA004201, the clean data were uploaded to the GSA database: http://bigd.big.ac.cn/gsa (accessed on 18 February 2023) [37]. Using the default settings, NGSQCToolkit (v 2.3.3) [38] eliminated the adapters and the subpar data. To eliminate the potential bias introduced by PCR during the library construction process, the clean reads were clustered using barcodes by gencore (v 0.16.0) [39]. The reads were then mapped to the zebrafish genome (GRCz11) by HISAT2 (v 2.1.0) [40] and assembled by StringTie (v 1.3.5) [41]. Due to StringTie’s propensity for producing fusion genes during assembly, the fusion genes in the new GTF file were divided in accordance with the original zebrafish genome GFF file. Transcriptomic data were quantized by Salmon (v 1.3) [42]. The reference sequences used by Salmon consisted of all transcripts and decoy sequences, which are similar to transcripts in the zebrafish genome [43]. The index of reference sequences was built with the parameters “-k 23—keepDuplicates.” Salmon’s “quant” command with the parameters “—mimicBT2—useEM” was used to calculate the number of transcripts and genes. The non-coding transcripts were predicted using CPC2 (v 1.2.2) [44] and CPAT (v 0.1) together [45,46]. Genes lacking mRNA transcripts were excluded. By using BLAST and the nr database (e-value ≤ 1e-5), the novel ones in the remaining genes were annotated. The low expression genes with a total count of fewer than 10 in 15 samples were eliminated. The differential expression analysis of the remaining genes was performed using DESeq2 (v 1.24.0) [47]. DEGs were identified in this study using p-values (≤0.05) adjusted for false discovery rate (FDR) and fold changes (≥2) in expression level. For GO enrichment analysis, TopGO [48] was used. The KEGG database was downloaded via its API interface, and the statistical test (Fisher’s exact test) for enrichment analysis was run using the R statistical language at the significance level of 0.05. The same genes were used in the co-expression analysis as in the differential expression analysis using the R package WGCNA (v 1.69) [49]. The Revert Aid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA, USA) was used to synthesize cDNA, which were used as templates for RT-qPCR. The MonAmp SYBR Green qPCR Mix (high ROX) (Monas Bio., Shanghai, China) for RT-qPCR on the CFX Connect Real-Time PCR System (Bio-Rad Laboratories, Wuhan, China) was used. The fold change of the gene relative expression was obtained through the ΔΔCT treatment using the beta actin gene as calibrators. The primers for RT-qPCR are listed in Supplemental Table S3.

PMC10003309

Yu-Fen Lin,Ching-An Chen,Fang-Yu Hsu,Ya-Hsin Hsiao

Elevated Hippocampal CRMP5 Mediates Chronic Stress-Induced Cognitive Deficits by Disrupting Synaptic Plasticity, Hindering AMPAR Trafficking, and Triggering Cytokine Release

03-03-2023

chronic unpredictable stress,cognitive deficits,collapsin response mediator proteins,AMPA receptor trafficking,synaptic atrophy

Chronic stress is a critical risk factor for developing depression, which can impair cognitive function. However, the underlying mechanisms involved in chronic stress-induced cognitive deficits remain unclear. Emerging evidence suggests that collapsin response mediator proteins (CRMPs) are implicated in the pathogenesis of psychiatric-related disorders. Thus, the study aims to examine whether CRMPs modulate chronic stress-induced cognitive impairment. We used the chronic unpredictable stress (CUS) paradigm to mimic stressful life situations in C57BL/6 mice. In this study, we found that CUS-treated mice exhibited cognitive decline and increased hippocampal CRMP2 and CRMP5 expression. In contrast to CRMP2, CRMP5 levels strongly correlated with the severity of cognitive impairment. Decreasing hippocampal CRMP5 levels through shRNA injection rescued CUS-induced cognitive impairment, whereas increasing CRMP5 levels in control mice exacerbated memory decline after subthreshold stress treatment. Mechanistically, hippocampal CRMP5 suppression by regulating glucocorticoid receptor phosphorylation alleviates chronic stress-induced synaptic atrophy, disruption of AMPA receptor trafficking, and cytokine storms. Our findings show that hippocampal CRMP5 accumulation through GR activation disrupts synaptic plasticity, impedes AMPAR trafficking, and triggers cytokine release, thus playing a critical role in chronic stress-induced cognitive deficits.

Elevated Hippocampal CRMP5 Mediates Chronic Stress-Induced Cognitive Deficits by Disrupting Synaptic Plasticity, Hindering AMPAR Trafficking, and Triggering Cytokine Release Chronic stress is a critical risk factor for developing depression, which can impair cognitive function. However, the underlying mechanisms involved in chronic stress-induced cognitive deficits remain unclear. Emerging evidence suggests that collapsin response mediator proteins (CRMPs) are implicated in the pathogenesis of psychiatric-related disorders. Thus, the study aims to examine whether CRMPs modulate chronic stress-induced cognitive impairment. We used the chronic unpredictable stress (CUS) paradigm to mimic stressful life situations in C57BL/6 mice. In this study, we found that CUS-treated mice exhibited cognitive decline and increased hippocampal CRMP2 and CRMP5 expression. In contrast to CRMP2, CRMP5 levels strongly correlated with the severity of cognitive impairment. Decreasing hippocampal CRMP5 levels through shRNA injection rescued CUS-induced cognitive impairment, whereas increasing CRMP5 levels in control mice exacerbated memory decline after subthreshold stress treatment. Mechanistically, hippocampal CRMP5 suppression by regulating glucocorticoid receptor phosphorylation alleviates chronic stress-induced synaptic atrophy, disruption of AMPA receptor trafficking, and cytokine storms. Our findings show that hippocampal CRMP5 accumulation through GR activation disrupts synaptic plasticity, impedes AMPAR trafficking, and triggers cytokine release, thus playing a critical role in chronic stress-induced cognitive deficits. Stress arises from various sources, including work, health, family, relationships, and the economy, and these stressors can affect human health [1,2,3]. Stress includes acute stress and chronic stress. Although we often view the effects of stress negatively, the effects of stress are not always harmful. Research shows that acute stress is often beneficial for memory formation. Acute stress increases the brain’s ability to encode and recall traumatic events [4,5]. These memories are stored in the part of the brain responsible for survival and serve as warning and defense mechanisms against future trauma. However, stress can have devastating effects if it persists for a long time. Brain regions may become overstimulated during a chronic stress response, affecting cognition [6]. Acute stress can alert us and make us fight or flee from dangerous events [7,8]. Conversely, chronic stress may impair physical health and increase the risk of mental health problems, such as depression [9]. In addition, chronic stress also triggers brain inflammation, impairs memory, and impedes cognitive function, including problem solving and decision making [10,11,12]. These findings suggest that chronic stress is detrimental to cognition. The hippocampus, a memory-related area of the brain that forms long-term memory, is involved in working memory processing and can support rapid learning [13,14]. Furthermore, the hippocampus is part of the limbic system and is particularly important in regulating stress and emotional responses [15,16]. The hippocampus is essential for spatial and episodic memory. Previous research has shown that chronic and acute stress differs in how they affect behavior and the structural integrity of the hippocampus [17]. In this study, the authors compared the effects of acute and chronic stress on neural activity in the CA1 subregion of male mice subjected to a chronic immobilization stress paradigm and observed that the spatial information encoded in the mouse hippocampus became clearer after the first exposure to stress (acute stress). However, mice exposed to chronic stress had poorer spatial attunement and decreased power of slow gamma (30–50 Hz) and fast gamma (55–90 Hz) oscillations into regions associated with excitatory input. These results show that acute and chronic stress affect hippocampal circuits differently, suggesting that acute stress may improve cognitive processing. In contrast, chronic stress causes long-term changes in the brain. Animal experiments have also found that prolonged exposure to high pressure can cause the volume of the hippocampus to shrink, which in turn affects these abilities [18,19]. However, which factor is involved in chronic stress-induced cognitive deficits is unclear. Collapsin protein-responsive mediator proteins (CRMPs), also known as the dihydropyrimidinase-like protein (DPYSL), are a family of five intracellular phosphoproteins (CRMP1-5) with similar molecular sizes (60–66 kDa) [20,21]. Furthermore, all CRMPs consist of heterophilic oligomers that bind to tubulin and can be phosphorylated by all kinases to regulate its activity [22,23]. Studies have shown that CRMPs are highly present in the nervous system during development and in specific neuronal plasticity brain regions during adulthood, such as the hippocampus [24,25]. They play essential roles in the formation of neurite axons, the guidance of growth cones, and the interaction with microtubules. Among the five CRMPs, CRMP1 targets RhoA signaling contributes to cytoskeletal reorganization during axonal pathfinding and is associated with neurodegeneration [26,27]. While CRMP2 regulates the stability of actin filaments, phosphorylated CRMP2 is also involved in the pathological process of Alzheimer’s disease [28]. CRMP3 is essential for dendritic elongation in neuronal differentiation and lamellipodia formation early in neurite initiation [24]. CRMP4 can bind to and regulate F-actin binding and is implicated in the neuropsychiatric field [24,29]. Furthermore, the CRMP5 protein is located on the dendrites of neuronal populations and is highly expressed during brain development. Its function is related to regulating apoptosis and differentiation, and it regulates neuronal filopodia and growth cone states [30]. Among the family members, CRMP1, 2, 3, and 4 show 75% homology, while CRMP5 has only 50% homology [31]. CRMP5 is involved in brain tumorigenesis and neurodevelopmental regulation [32,33] and is associated with several neuropsychiatric diseases [34,35]. CRMP5 expression has been reported to be increased in mouse models of stress and to accelerate memory loss in animal models of Alzheimer’s disease [24,36]. Our previous study found higher hippocampal CRMP5 expression in stress-susceptible mice than in nonstressed control and stress-resilient mice, suggesting CRMP5 can modulate susceptibility to chronic social defeat stress in mice [37]. Overall, CRMP5 is remarkable compared to other CRMP members. However, the specific role of CRMP5 in stress-induced memory impairment remains unclear. The CRMP family (CRMP1-5; CRMPs) is abundantly expressed in the brain, especially in the hippocampus, which modulates stress responses [24,38]. Recent studies have highlighted that CRMPs are associated with neuropsychiatric diseases, including schizophrenia [39], bipolar disorders, severe major depression, autism, and alcohol dependence [39,40,41]. Thus, we measured hippocampal CRMP protein levels in the control and CUS groups to investigate whether CRMPs are involved in CUS-induced memory impairment. The Western blot data showed hippocampal CRMP1-5 protein levels were higher than in control mice. Interestingly, among CRMPs, CRMP2 and CRMP5 levels were significantly higher in CUS mice than in nonstressed controls (Figure 1). In the experiment scheme with the timeline as Figure 2A, we also calculated an association between CRMP2 or CRMP5 expression and memory performance scores of nonstressed control and CUS mice in the object location and Y-maze tests. The results showed that compared to that of CRMP2 (Figure 2B,C), CRMP5 levels had a negative linear relationship with the DI value of the object location test (Figure 2D) and the percentage of time spent in the novel arm in the Y-maze test (Figure 2E). We further confirmed that the expression of other CRMPs, CRMP1, CRMP3, or CRMP4, had no significant correlation with cognitive functions in CUS mice (Figure S1), suggesting that CRMP5 may play a critical mediator in the regulation of chronic stress-induced cognitive deficits. Next, a loss-of-function strategy was used to determine whether CRMP5 is implicated in CUS-induced memory loss. We bilaterally injected lentivirus expressing a nonspecific control shRNA (scramble) or an shRNA targeting mouse CRMP5 (shCRMP5) into the control or CUS mouse hippocampus. The data showed that the protein levels of hippocampal CRMP5 were significantly reduced in CUS mice injected with shCRMP5 compared to CUS mice injected with scrambled shRNA (Figure 3A). In addition, we also utilized the open field test to analyze mouse walking distance and velocity to check further whether the lentivirus injections would not influence mouse locomotor activity. The heatmaps and accompanying analysis data showed that scrambled- and shCRMP5-treated mice exhibited no statistical difference in distance traveled or velocity in control and CUS mice (Figure 3B). We then utilized an object location test to measure mouse memory performance. The trajectory and data of the object location test showed that shCRMP5-treated CUS mice exhibited more significant spatial memory improvement than scrambled shRNA-injected CUS mice (Figure 3C). These phenomena were confirmed by the modified Y-maze test, showing that decreased CRMP5 levels rescued memory loss in CUS mice compared to those of scrambled shRNA-treated CUS groups (Figure 3D). Furthermore, we also knocked down hippocampal CRMP2 levels to determine whether reducing CRMP2 expression would affect memory performance in CUS mice with lentivirus expressing an shRNA targeting mouse CRMP2 (shCRMP2) or scrambled control shRNA. CUS mice transduced with shCRMP2 exhibited significantly decreased hippocampal CRMP2 protein levels, as confirmed by Western blotting (Figure S2A). In addition, there was no difference in walking distance or velocity between scrambled and shCRMP2-treated control and CUS groups (Figure S2B), showing no motor deficiency affected by virus injections. Notably, the heatmaps and accompanying analysis of object location and Y-maze test data showed that the knockdown of CRMP2 expression did not alter CUS-induced memory impairments (Figure S2C,D). The above findings highlighted that CRMP5 is indeed involved in CUS-induced cognitive deficits. To further confirm whether CRMP5 is involved in chronic stress-induced cognitive impairments, hippocampal CRMP5 overexpression by a lentivirus transduction strategy was applied. First, the CRMP5 cDNA clone was injected into the nonstressed mouse hippocampus to overexpress CRMP5. One month later, nonstressed mice with/without lenti-CRMP5 injection were exposed to subthreshold social defeat stress and subjected to behavioral tests. Our previous results found that the subthreshold social defeat stress could trigger social avoidance behavior but did not affect the control mice. Immunoblotting results illustrated that lenti-CRMP5-treated mice displayed higher hippocampal CRMP5 protein expression than lenti-control mice (Figure 4A). We also used the open field test and found that lenti-control and lenti-CRMP5-treated mice showed no difference in locomotor activity (Figure 4B). The trajectory analysis of the object location test and the Y-maze test showed that lenti-CRMP5-treated mice displayed memory deficits compared to lenti-control groups (Figure 4C,D), suggesting that increased hippocampal CRMP5 levels could mimic CUS-induced memory impairment in nonstressed mice. Current theories support spinal plasticity as an integrative neurochemical structural basis for memory storage and maintenance [42,43,44]. Notably, previous studies revealed that CRMP5 is a critical factor in regulating spine plasticity [24,33]. Based on our above finding, CRMP5 expression affects CUS-induced cognitive deficits. Therefore, we evaluated whether CRMP5 alters dendritic morphology and synaptic plasticity using a Golgi staining protocol. First, we examined the impact of hippocampal CRMP5 suppression by shRNA injection on dendritic architecture. As shown in Figure 5A, dendritic branching in neurons from CUS-treated mice with shCRMP5 infusion was significantly higher than that in neurons from CUS-treated mice with scrambled shRNA injection. Branch lengths, the number of dendritic branches, and spines were also markedly higher in shCRMP5-treated CUS mice than in scrambled shRNA-treated CUS controls (Figure 5B–D), suggesting that hippocampal CRMP5 inhibition with shCRMP5 infusion alleviated CUS-induced dendritic atrophy and spine loss. We next analyzed the effect of CRMP5 overexpression on dendrite structure in the non-CUS mouse hippocampus. Representative images and quantitative analysis of hippocampal dendritic branching are shown in Figure 5E, with more branching intersections of 40–80 μm from the neuronal soma from lenti-CRMP5-treated mice than from the lenti-control groups. In neurons overexpressing CRMP5, the total branch lengths and dendritic and spine density markedly differed from those in the lenti-control group (Figure 5F–H). These observations suggest that CRMP5 plays a role in dendritic spine remodeling. α-Amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) trafficking is proposed to be linked to maintaining dendritic spine morphogenesis [45,46,47]. Furthermore, our previous study revealed that CRMP5 could regulate surface GluA2 and GluA2 S880 phosphorylation in Alzheimer’s disease-related memory impairment [36]. Thus, to further examine the underlying mechanism by which CRMP5 regulates dendritic spine remodeling, we first tested whether CRMP5 suppression rescues CUS-induced dendritic spine loss by affecting AMPAR trafficking. As illustrated in Figure 6A, there were decreased cell surface levels of the AMPAR GluA2 subunit in hippocampal neurons from CUS-treated mice. Inhibiting CRMP5 expression with shCRMP5 infusion increased surface GluA2 in hippocampal neurons from CUS-treated mice. These findings are consistent with the Western blotting results that CUS treatment promoted GluA2 S880 phosphorylation, which is involved in GluA2 endocytosis [48,49] and could be reversed with hippocampal shCRMP5 infusion (Figure 6B). Next, we analyzed how CRMP5 overexpression causes dendritic spine loss by affecting cell surface GluA2 and pGluA2-S880 expression. The Western blotting results indicated that mice with hippocampal lenti-CRMP5 infusion exhibited lower surface GluA2 and higher pGluA2-S880 protein expression than the lenti-control group (Figure 6C,D). In addition, we also verified whether manipulation of hippocampal CRMP5 levels would alter GluA1 expression. Quantitative Western blotting showed no significantly different in surface GluA1 levels among scramble- and shCRMP5-treated control and CUS mice (Figure S3A) or between lenti-control- and lenti-CRMP5-treated mice (Figure S3B). Taken together, the above immunoblotting results indicate that CRMP5 is a critical factor in mediating GluA2 trafficking. To elucidate the underlying mechanisms of the involvement of CRMP5 in CUS-induced cognitive impairment, we also determined whether CUS triggers inflammatory responses that could be reduced by CRMP5 inhibition. Therefore, mouse serum from control or CUS-treated animals without/with hippocampal shCRMP5 infusion was analyzed by a mouse cytokine/chemokine panel. Consistent with our previous findings, CUS treatment may increase IL-6 and IL-13 levels [37]. Conversely, hippocampal shCRMP5 injection reversed CUS-induced proinflammatory IL-6 and IL-13 secretion (Figure 7A–C). We further studied the influence of CRMP5 overexpression on the inflammatory response, and serum from lenti-control or lenti-CRMP5 mice was analyzed. Hippocampal lenti-CRMP5 infusion triggered proinflammatory IL-6 and IL-13 cytokine release (Figure 7D–F). These findings suggest that hippocampal CRMP5 modulation systemically reduces CUS-induced proinflammatory cytokine exaggeration. We used qRT-PCR to detect mRNA expression of CRMP5 in nonstressed control and CUS-exposed mice. Dpysl5 (CRMP5) mRNA levels in the hippocampus were higher in the CUS mice than in control mice (Figure 8A). Moreover, we identified which factor could cause the CRMP5 increase to trigger memory impairment in CUS mice. We utilized the transcription factor binding databases to screen the Dpysl5 promoter for possible binding sites of transcriptional regulators and identified a well-conserved glucocorticoid receptor 1 (GR1, also known as NR3C1) recognition element in the proximal promoter region of Dpysl5. In addition, Serine (S) 211 is closely related to the activated form of GR1 (pGR1-S211) [50]. Thus, glucocorticoid and pGR1-S211 levels and the binding activity of pGR1 to the Dpysl5 promoter were examined by Western blotting and pGR1-ChIP analysis. The immunoblotting results showed that CUS mice increased hippocampal GR phosphorylation more than the control group (Figure 8B). Next, the ChIP experiment demonstrated that the binding of GR to the promoter region of Dpysl5 was significantly increased in the CUS-treated mice compared to the nonstressed control mice, indicating that CUS treatment increased GR transcription factor binding to the Dpysl5 promoter, which encodes CRMP5 (Figure 8C). Chronic stress is a source of danger for the development of various psychiatric disorders, including depression [51,52], memory impairment [53,54,55], and even brain aging [56,57]. However, which factors cause chronic stress-induced memory deficits is still unclear. We recently demonstrated that CUS-enhanced CRMP5 expression increases in the hippocampus. To determine whether CRMP5 is involved in chronic stress-induced cognitive impairments, we manipulated CRMP5 levels by gain-of-function and loss-of-function strategies. The results showed that changes in CRMP5 expression could alter the memory performance of mice. Furthermore, modification of hippocampal CRMP5 also affects synaptic growth. Increased CRMP5 expression led to a loss of dendrites and spines. In contrast, suppression of hippocampal CRMP5 augmented the number of dendrites and spines in CUS-treated mice, which indicated that chronic stress causes hippocampal dendritic atrophy through CRMP5 regulation. The above finding aligns with previous studies showing that CUS-induced dendritic atrophy and spine loss in hippocampal neurons eventually leads to long-term potentiation (LTP) dysfunction, which is critical for learning and memory, thereby impairing memory [58,59,60]. Why was this line of mice chosen? Different strains of mice did respond differently to chronic unpredictable stress. A previous study used ICR and C57BL/6 strains of mice for comparison because they are widely used strains in behavioral tests. It was found that using the forced swimming test and novelty-suppressed feeding test, only C57BL/6 mice exhibited depression- and anxiety-like behaviors after the chronic stress procedure [61]. Thus, based on this, we also chose C57BL/6 mice for the CUS study. Chronic unpredictable stress (CUS) is the most widely used animal model for inducing depression-like phenotypes [62]. Our previous study found that using a forced swimming test, CUS-exposed mice have depression-like behavior. We also used the chronic social defeat stress (CSDS) model, which can exhibit a pronounced depressive behavior in mice. Among the CRMP family members, we observed higher hippocampal CRMP5 expression in stress-susceptible (SS) mice than in control and stress-resilient (RES) mice [63], suggesting hippocampal CRMP5 was involved in the stress-induced depression-like behavior. In addition, chronic stress is responsible for developing many psychopathological syndromes in humans, including depression and anxiety disorders [37,64]. Previous studies revealed that rodent models of chronic unpredictable stress might induce anxiety-like behaviors [65,66]. In our tests, we did find that CUS mice also exhibited anxiety-like behaviors. Still, no correlation existed between anxiety-like behaviors and hippocampal CRMP5 expression in mice, suggesting CRMP5 expression is not associated with CUS-induced anxiety-like behaviors. This study’s essential issue is how chronic stress could trigger CRMP5 increase to induce memory deficits. Emerging evidence has revealed that chronic stress can accelerate memory decline via the regulation of glucocorticoid receptor signaling [67,68]. Stress-induced glucocorticoid release activates the glucocorticoid receptor (GR) as a transcription factor. Phosphorylated GR (pGR) enters the nucleus and binds to the site of glucocorticoid response elements (GREs), driving gene transcription [69]. Phosphorylated GR (pGR) enters the nucleus and binds to the site of glucocorticoid response elements (GREs), driving gene transcription [69]. GR phosphorylation has been reported to negatively impact mediating morphology and function [70,71]. To confirm whether GR regulated CRMP5 expression, we measured pGR expression using Western blotting. The data revealed that pGR expression was increased after CUS treatment. We next investigated the binding activity between pGR and Dpysl5 (CRMP5) by a chromatin immunoprecipitation (ChIP) assay and found that pGR binding to Dpysl5-GRE was significantly increased in CUS-treated mice, suggesting that chronic stress could induce an increase in pGR binding activity to trigger Dpysl5 (CRMP5) gene expression. Furthermore, previous studies have shown that chronic stress could promote the release of proinflammatory cytokines and chemokines [72]. To investigate whether CRMP5 affects cytokine release, CUS-treated mouse serum was collected and analyzed for inflammatory cytokines and chemokines. The serum analysis suggested that a decrease in CRMP5 levels altered the levels of proinflammatory factors. We found that CUS treatment resulted in the upregulation of proinflammatory factors, such as IL-6 and IL-13, which were then downregulated by shCRMP5 treatment. To further confirm the interaction of CRMP5 and cytokine release, we collected the Lenti-control- and lenti-CRMP5-treated mice serum to analyze many proinflammatory cytokines and chemokines. Serum analysis revealed that proinflammatory cytokines and chemokines, including IL-6 and IL-13, were upregulated in lenti-CRMP5-treated mice. Notably, hippocampal shCRMP5 injection in control mice might increase serum anti-inflammatory cytokines, such as IL-4. Modulation of CRMP5 expression can affect CUS-induced cytokine release. However, the causal relationship between CRMP5 and inflammatory factors under chronic stress remains to be elucidated. In summary, we found that (1) chronic stress significantly increases the expression of CRMPs, especially CRMP2 and CRMP5. (2) Markedly, only the expression level of CRMP5 was closely related to the severity of memory impairment. (3) Reducing CRMP5 expression with hippocampal lentivirus delivery can rescue memory impairment in CUS-treated mice. Conversely, increasing hippocampal CRMP5 expression impairs memory in nonstressed mice. (4) Mechanistically, we also found that glucocorticoid receptor (GR), as a transcription factor, can increase the triggering of CRMP5 transcription. (5) Furthermore, regulating the expression of CRMP5 can affect synaptic atrophy and cytokine release induced by CUS. These findings suggest that chronic stress-increased CRMP5 expression is one of the leading causes of memory impairment. Eight-week-old male C57BL/6 mice were obtained from BioLASCO Taiwan and housed with 3 to 5 mice per cage under standard conditions (21 ± 2 °C, 12 h:12 h light cycle) with access to food and water. Experimental procedures were approved by the Institutional Animal Care (IACUC number 109017, 110004) and Use Committee of the College of Medicine, National Cheng Kung University. Chronic unpredictable stress (CUS) is the most widely used animal model for inducing depression-like phenotypes [62]. The CUS procedure was performed as described [61,73] with slight modifications. CUS, a one-month stress model, consists of 10 stressors, such as food/water restriction, physical restraints, social defeat, and sleep deprivation, as our previous study described [37]. Experimental stressed mice were randomly assigned to one of the stressors every day. In the subthreshold social defeat stress paradigm, male C57BL/6 mice, as intruders, were repeatedly exposed to a novel CD1 aggressor mouse for 5 min and then returned to the home cage for 15 min. The above steps were repeated three times. After subthreshold social defeat stress, the mice were triggered by social avoidance behavior but did not affect the control mice. The open field test was used to assess the locomotor activity of mice. We placed the experimental mouse into a 46 × 46 × 46 cm3 black open field box for 10 min and cleaned the box with 70% ethanol between tests. Mouse trajectory and travel distance were recorded and analyzed by EthoVision XT software (Noldus Inc., Wageningen, The Netherlands). The object location test is a 5-day task for assessing mouse spatial memory. First, mice were habituated into a 30 × 30 × 30 cm3 box for 10 min/day for 3 days. The next day, during the training phase, experimental mice were placed into the same box with two identical objects on the same side and allowed to explore for 10 min freely. On day 5, one of these two objects was placed on the opposite side of the box. Subsequently, the mice were subjected to freely exploring the objects for 10 min. Between separate trials, 70% ethanol was used to eliminate odor cues in the objects and the box in the package. The time spent exploring each object was recorded and depicted as a discrimination index (DI) value as follows: DI = (tnovel − tfamiliar)/(tnovel + tfamiliar). The Y-maze recognition test, one of the short-term spatial memory tests, was also used. First, one arm of the Y-maze was closed off, and the mice were subjected to freely explore the other two arms for 5 min. After 1 h, the closed arm opened, and the mouse was placed back into the Y maze and freely explored total arms for 5 min. The time spent in the novel arm was calculated as a percentage of the time in all three arms of the Y maze. % Time in Novel arm = [(time spent in the novel arm/total time spent in all arms) × 100]. The hippocampus of mice was dissected and sonicated in a lysis buffer. SDS—PAGE separated the extracts. The transferred membrane was blocked with 3% bull serum albumin and then incubated in primary antibodies (CRMP1 (GTX114940; GeneTex, Irvine, CA, USA), CRMP2 (ab129082; Abcam, Cambridge, UK), CRMP3 (ab36217; Abcam), CRMP4 (13661-1-AP; Proteintech, Rosemont, IL, USA), CRMP5 (GTX19352; GeneTex, Irvine, CA, USA), GluR1 (CST#13185; Cell Signaling Technology, Beverly, MA, USA), GluR2 (CST#13607; Cell Signaling Technology, Beverly, MA, USA), p-GR (CST4161; Cell Signaling Technology, Beverly, MA, USA), and NR3C1 (GR) (A2162; ABclonal, Woburn, MA, USA), and β-Actin (MAB1501; Millipore, Burlington, MA, USA) used as internal control) overnight at 4 °C. Next, after three times washing with TBST for 10 min, the membrane was incubated with secondary antibodies for 1 h at room temperature. Protein levels were detected and quantified by a BioImaging System (UVP Inc., Upland, CA, USA). After the CUS challenge and behavioral test, the mice were deeply anesthetized and rapidly decapitated. Mouse brain tissues were collected, impregnated in Golgi–Cox solution for 2 days, and immersed in cryoprotectant buffer for 2 days. These tissues were sectioned into 200 μm sections, washed with 0.01 M PBST (pH = 7.4, 0.5% Triton X-100), and incubated in ammonia solution for 7 days at room temperature in the dark. The brain sections were washed with PBST, transferred to gelatin-coated slides, dehydrated with a gradient ethanol solution, and cover-slipped with a mounting medium. The synaptic and dendritic images were taken using an Olympus microscope and analyzed by ImageJ software for dendritic spine morphology. The plasmid for intrahippocampal delivery was inserted with short hairpin RNA (Dpysl5 shRNA and Dpysl2 shRNA or scrambled control shRNA) or lentiviruses (Lenti-control or Lenti-CRMP5 and Lenti-CRMP2) and cotransfected into HEK293 cells using Lipofectamine 2000 (Life Technologies, Carlsbad, CA). CRMP5 shRNA (Dpysl5 shRNA) and CRMP2 shRNA (Dpysl2 shRNA) clones were obtained from the National RNAi Core Facility (Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan). Dpysl5 and Dpysl2 cDNA were purchased from GeneScript and Protech. Lentiviruses were collected after transfection for 48 h and then purified and concentrated to obtain 1 × 108 per mL of infectious particles. The mice were mounted on a stereotactic apparatus, and two μL of lentivirus was implanted into the ventral hippocampus (anterior–posterior: −3.4 mm; medial–lateral: ± 3.4 mm; dorsal–ventral: −4.0 mm). Blood samples were collected from sacrificed mice and centrifuged for 5 min at 2000× g and room temperature. The supernates from these samples were carefully collected and stored at −80 °C. For further quantifying cytokine and chemokine levels, serum samples were performed with the Multiplex Bead-Based assays following the manufacturer’s procedures (EMD Millipore; Cat: # MHSTCMAG-70KPMX, Billerica, MA, USA). Next, serum cytokine and chemokine levels were detected by Luminex® (Austin, TX, USA), and the median fluorescence intensity (MFI) values of samples were assessed to calculate concentrations. The mouse hippocampus was harvested and fixed with 1% formaldehyde. Chromatin immunoprecipitation (ChIP) assays were performed using a ChIP kit (Abcam, Cas: # ab500). The tissue samples were sonicated as chromatin fragments and incubated with antibodies overnight with rotation at 4 °C. Next, the chromatin/antibody samples were centrifuged (14,000× g, 10 min) to remove the insoluble material. Then, 250 µL of supernatant was removed, protein beads were added, and the samples were rotated at 4 °C for 1–2 h. Then, the pellet beads were precipitated by centrifugation, and the supernatant was carefully discarded. The pellet beads were treated with proteinase-K and heated to separate protein from the DNA fragments. Real-time PCR was performed using the SYBR Green-based detection system with PCR primers to measure the binding activity. All data analyses were displayed using GraphPad Prism 9. The statistical significance of differences was measured with Student’s t-test between two groups and with ANOVA for three or more groups. The values are presented as the mean ± SEM. The values are presented as the mean ± SEM, and the statistical significance was defined as p < 0.05.

PMC10003311

Dietmar Krex,Paula Bartmann,Doris Lachmann,Alexander Hagstotz,Willi Jugel,Rosa S. Schneiderman,Karnit Gotlib,Yaara Porat,Katja Robel,Achim Temme,Moshe Giladi,Susanne Michen

Aurora B Kinase Inhibition by AZD1152 Concomitant with Tumor Treating Fields Is Effective in the Treatment of Cultures from Primary and Recurrent Glioblastomas

06-03-2023

glioblastoma,TTFields,Aurora B kinase,AZD1152,primary cultures

Tumor Treating Fields (TTFields) were incorporated into the treatment of glioblastoma, the most malignant brain tumor, after showing an effect on progression-free and overall survival in a phase III clinical trial. The combination of TTFields and an antimitotic drug might further improve this approach. Here, we tested the combination of TTFields with AZD1152, an Aurora B kinase inhibitor, in primary cultures of newly diagnosed (ndGBM) and recurrent glioblastoma (rGBM). AZD1152 concentration was titrated for each cell line and 5–30 nM were used alone or in addition to TTFields (1.6 V/cm RMS; 200 kHz) applied for 72 h using the inovitro™ system. Cell morphological changes were visualized by conventional and confocal laser microscopy. The cytotoxic effects were determined by cell viability assays. Primary cultures of ndGBM and rGBM varied in p53 mutational status; ploidy; EGFR expression and MGMT-promoter methylation status. Nevertheless; in all primary cultures; a significant cytotoxic effect was found following TTFields treatment alone and in all but one, a significant effect after treatment with AZD1152 alone was also observed. Moreover, in all primary cultures the combined treatment had the most pronounced cytotoxic effect in parallel with morphological changes. The combined treatment of TTFields and AZD1152 led to a significant reduction in the number of ndGBM and rGBM cells compared to each treatment alone. Further evaluation of this approach, which has to be considered as a proof of concept, is warranted, before entering into early clinical trials.

Aurora B Kinase Inhibition by AZD1152 Concomitant with Tumor Treating Fields Is Effective in the Treatment of Cultures from Primary and Recurrent Glioblastomas Tumor Treating Fields (TTFields) were incorporated into the treatment of glioblastoma, the most malignant brain tumor, after showing an effect on progression-free and overall survival in a phase III clinical trial. The combination of TTFields and an antimitotic drug might further improve this approach. Here, we tested the combination of TTFields with AZD1152, an Aurora B kinase inhibitor, in primary cultures of newly diagnosed (ndGBM) and recurrent glioblastoma (rGBM). AZD1152 concentration was titrated for each cell line and 5–30 nM were used alone or in addition to TTFields (1.6 V/cm RMS; 200 kHz) applied for 72 h using the inovitro™ system. Cell morphological changes were visualized by conventional and confocal laser microscopy. The cytotoxic effects were determined by cell viability assays. Primary cultures of ndGBM and rGBM varied in p53 mutational status; ploidy; EGFR expression and MGMT-promoter methylation status. Nevertheless; in all primary cultures; a significant cytotoxic effect was found following TTFields treatment alone and in all but one, a significant effect after treatment with AZD1152 alone was also observed. Moreover, in all primary cultures the combined treatment had the most pronounced cytotoxic effect in parallel with morphological changes. The combined treatment of TTFields and AZD1152 led to a significant reduction in the number of ndGBM and rGBM cells compared to each treatment alone. Further evaluation of this approach, which has to be considered as a proof of concept, is warranted, before entering into early clinical trials. Glioblastoma (GBM) is the most devastating primary malignancy of the central nervous system in adults. Current standard treatment consists of maximal and safe surgical resection followed by loco-regional radiotherapy (RT) with concomitant daily temozolomide (TMZ) chemotherapy, and then maintenance treatment with TMZ for 6 to 12 months [1]. Tumor Treating Fields (TTFields) are an anticancer modality that disrupt critical processes in cancer cells, including cell division, by delivering low-intensity, intermediate-frequency (200 kHz for GBM) alternating electric fields [2,3,4]. In a phase III clinical trial (EF-14, ClinicalTrials.gov identifier NCT00916409), the efficacy of TTFields used with TMZ maintenance treatment after maximal safe resection and chemo-radiation therapy for patients with newly diagnosed GBM (ndGBM) was reported. Median overall survival (OS) from randomization in the intent-to-treat population was 20.9 months versus 16.0 months for the TTFields-TMZ group and the TMZ–alone group, respectively, with a hazard ratio of 0.63 (95% CI, 0.53–0.76; p < 0.001). The significant improvement in OS was seen across all patient subgroups regardless of age, extent of resection, performance status, gender, geography or promoter methylation status of O6-methylguanine-DNA methyltransferase (MGMT) gene encoding a ubiquitous nuclear enzyme involved in the repair of alkylated DNA [5]. In contrast, the phase III clinical trial EF-11 (ClinicalTrials.gov identifier NCT00379470) investigated the effect of TTFields application as the sole therapy for recurrent GBM (rGBM) compared to the physician’s choice of chemotherapy. Although a significant prolongation of overall survival was not observed, non-inferiority of the treatment-arm was demonstrated [6]. Nevertheless, the benefit of TTFields treatment outweighed the benefit of chemotherapy, due to a comparable survival and improved quality of life of the patients [7]. The anti-tumor effect of TTFields is not yet fully understood. One model is based on the principle that TTFields exert directional forces on polar microtubules and interfere with the assembly of the normal mitotic spindle. Such interference with microtubule dynamics results in abnormal spindle formation and subsequent mitotic arrest or delay. As a result, cells die while in mitotic arrest or progress to cell division [4]. This can lead to the formation of either normal or abnormal aneuploid progeny. The formation of tetraploid cells can occur due to mitotic exit through slippage or as a result of improper cell division. Abnormal daughter cells either die in the subsequent interphase, undergo a permanent arrest, or proliferate through additional rounds of mitosis where they will be subjected to further TTFields assault [2]. Another model is based on the effects of TTFields on membrane potential and ion channels. Li et al. recently showed in a theoretical study that the effect of TTFields on thermal energy, and thus elevated Brownian motion, is larger than the effect on tubulin dimer orientation. In addition, they calculated that the dielectric forces also do not have a net-effect as commonly thought, because these forces are counteracted by Stokes forces. Alternatively, they suggest that cell membrane potential is elevated over 10% of the resting cell state and that this effects ion channels and membrane pumps, resulting in an influx of Ca2+ into the cell, which in turn affects microtubule polymerization [8]. A promising approach to enhance the efficiency of TTFields is the use of drugs, which synergistically act together with TTFields and prolong metaphase-anaphase transition and telophase. In particular, an extended period in metaphase and during cytokinesis most likely increases DNA damage and subsequent events, leading to mitotic catastrophe and apoptosis of tumor cells. In this regard, inhibitors or drugs interfering with components of the chromosomal passenger complex (CPC), in particular affecting Aurora B kinase [9], are prime candidates for combinatorial use with TTFields. The CPC is of central importance for mitosis as a regulator of chromosome division and cytokinesis. In addition to the enzymatic component Aurora B kinase, it consists of the three regulatory and targeting components: Survivin, Borealin, and inner centromeric protein (INCENP). Aurora B kinase activity is critically involved in correcting syntelic microtubule-kinetochore connections and therefore guarantees bi-orientation of sister chromatids to opposing spindle poles before the onset of anaphase [10,11]. Therefore, inhibition of Aurora B kinase leads to defective mitosis, polyploidy, and finally to mitotic catastrophe [12]. AZD1152-HQPA (barasertib) is a highly selective Aurora B kinase inhibitor [13] with efficacy on a wide variety of tumor entities, including acute myeloid leukemia, advanced solid tumors, and diffuse large B-cell lymphoma, which has already been investigated and validated in phase I and II studies [14,15,16]. Furthermore, in vitro and in vivo studies showed that AZD1152 caused polyploidy and non-apoptotic cell death in glioma cell lines regardless of their p53 status [17,18,19]. This is beneficial because the p53 status of GBM patients is closely related to disease progression and survival during chemoradiotherapy [20,21]. Although, there had been evidence that the p53/p73 status might be important for the type of cellular response to selective Aurora B inhibition, we have shown that together with its essential role in the execution of cytokinesis, Aurora B, in cooperation with its partners of the CPC, safeguards segregation and chromosomal integrity independently of p53 mutational status and therefore is critical for the survival of cells [19]. In the present study, we investigate whether the combination of TTFields with the chemical Aurora B kinase inhibitor AZD1152 enhances the anti-tumor effect on glioblastoma cells by additionally inhibiting cytokinesis. To evaluate the efficiency of this combined treatment, both established long-term glioblastoma cell lines U87-MG and p53-deficient U87-MGshp53, as well as primary cultures of ndGBM and rGBM, are used. To examine whether enhanced anti-tumor effects occur independently of p53 when AZD1152 and TTFields are combined, we initially used the p53 wild-type, long-term-established glioma cell line U87-MG and its stable p53-deficient counterpart U87-MGshp53. U87-MG proved to be highly sensitive to treatment with AZD1152 alone with a half-maximal inhibitory concentration (IC50) around 25 nM (Figure 1A). Response to TTFields application alone (200 kHz, 1.6 V/cm RMS) for 72 h led to a reduction in cell number of 49.0% (±2.8%), similar to previous reports. The p53-deficient U87-MGshp53 cell line was less sensitive to treatment with AZD1152 than the p53 wild-type U87-MG cell line, with an IC50 around 50 nM. Similarly, TTFields application alone resulted in a slightly lower cell number reduction of 40.5% (±10.6%) in U87-MGshp53 compared to p53 wild-type U87-MG. The combined treatment of TTFields and AZD1152 led to a reduction in the number of U87-MG and U87-MGshp53 cells relative to treatment with AZD1152 alone (Figure 1A, and Supplementary Figure S1). Although there is a difference between U87 and U87-MGshp53 cell lines we performed a test of significance but could not substantiate a statistically significant difference, either for the single treatment with AZD1152 or in combination with TTFields. Furthermore, cell morphological changes were observed with increasing AZD1152 concentration in both cell lines. These were intensified when AZD1152 and TTFields were combined (Figure 1B). Microscopy images of U87-MG and U87-MGshp53 cells stained with crystal violet after treatment revealed a slight increase in the number of multinuclear cells following TTFields application (Figure 1B, first row). A higher prevalence of multinuclear cells (marked by black arrows) was observed in U87-MG and U87-MGshp53 cells exposed to TTFields and low concentration of AZD1152 (25 nM) compared to cells treated with AZD1152 (25 nM) alone (Figure 1B, second row). Cells treated with TTFields and higher doses of AZD1152 (50–100 nM) demonstrated increased rates of pyknosis (marked by blue arrows) (Figure 1B, third and fourth rows; enlarged views are provided in Supplementary Figure S2). To verify the enhanced anti-tumor effects of concomitant treatment with AZD1152 and TTFields observed in U87-MG and U87-MGshp53 in a more clinically relevant model, primary glioblastoma cultures were used. For this purpose, primary ndGBM and rGBM cell cultures were established from fresh tumor tissue from patients. As tumor tissue from patients with rGBM was pretreated with alkylating chemotherapy (temozolomide) and radiotherapy, the cytotoxic effect of additional therapy with Aurora B kinase inhibition and TTFields on these primary cultures might be different from those of ndGBMs. Therefore, we not only established primary cultures from ndGBM patients but from rGBM patients as well and treated them identically. Tumor tissues were thoroughly analyzed at the Department of Neuropathology, University Hospital Carl Gustav Carus, TU Dresden according to the current World Health Organization (WHO) classification system at the day of surgery, and reconfirmed according to current criteria of the version from 2021. The Ki-67 proliferation index varied between 5% and 60%. Furthermore, the glial origin of the tumors was confirmed by identification of glial fibrillary acid protein (GFAP) by immunohistochemistry. Moreover, all tumors had no mutation of IDH1 R132H locus. In addition, both of the ndGBM and one of the rGBM tumors (HT16360-1) are MGMT promoter methylated (Table 1A). The established primary glioblastoma cultures were further characterized and verified before treatment (Table 1B). All primary glioblastoma cultures showed 91.2–99.3% expression of the cancer cell marker CD44, which is overexpressed in GBM [22], and 6.8–61.6% expression of GFAP, which is expressed by astrocytes and in astrocytic brain tumors [23]. Furthermore, ndGBM culture HT12347 and rGBM culture HT16360-1 overexpressed EGFR (78.4% and 73.2%), which occurs in approximately 60% of glioblastoma patients [24]. The ndGBM culture HT18584 and rGBM culture HT16360-1 showed an increased expression of ErbB2 (95.9% and 76.3%), which like EGFR belongs to the ErbB family of receptor tyrosine kinases. In addition, p53 status was determined, with ndGBM cultures found to be p53 mutant and rGBM cultures found to be p53 wild-type. Initially, the response of primary glioblastoma cultures to treatment with AZD1152 alone was investigated. Cells showed variable sensitivity to AZD1152 treatment regardless of their p53 status or whether they were established from ndGBM or rGBM samples. (Figure 2A). While HT18584 (ndGBM, p53mut) and HT18816 (rGBM, p53wt) cells exhibited high sensitivity with IC50 around 14 nM and 18 nM, HT16360-1 (rGBM, p53wt) and HT12347 (ndGBM, p53mut), cells were less sensitive with IC50 around 50 nM and 75 nM. The IC50 of HT18328-3 (rGBM, p53wt) was in the middle range of 30 nM. Moreover, increasing AZD1152 concentrations led to only minor changes or a slight decrease in p53 in p53 mutant ndGBM cultures HT12347 (20 nM: 1.1×, 50 nM: 0.9×) and HT18584 (20 nM 0.6×, 50 nM: 0.8×) (Figure 2B). However, p53 wild-type rGBM cultures showed either increased accumulation (HT16360-1, 30 nM: 2.4×, 100 nM: 3.2×) or no p53 expression (HT18816 and HT18328-3) at all. To investigate enhanced anti-tumor effects of combined treatment with AZD1152 and TTFields of primary glioblastoma cultures, cell viability assays were performed (Figure 3). Thereby, primary glioblastoma cultures and U87-MG responded similarly to TTFields treatment alone (200 kHz) with a reduction in cell number to a median of 49.6–58.8%. An exception was HT18584 (ndGBM, p53mut), which was much more resistant with a median reduction in cell number to only 79.2% (47.1–94.3%). Furthermore, HT18328-3 (rGBM, p53wt) exhibited high variability in cell reduction from 14.6% to 88.3% (median 56.7%). Therefore, for these two primary glioblastoma cultures, AZD1152 concentrations were chosen that reduced cell count to a median of 50% living cells (HT18584 (ndGBM, p53mut): 49.8% with 20 nM AZD1152; HT18328-3 (rGBM, p53wt): 52.5% with 15 nM AZD1152). For the other primary glioblastoma cultures and U87-MG, AZD1152 concentrations were used that resulted in a reduction in cell number to a median of 75% (68.3–80.6%) of living cells. These low effective doses of AZD1152 were selected with consideration for potential clinical translation to reduce the risk of toxicity, as AZD1152 was associated with frequent adverse events, including myelotoxicity, in clinical studies [14,15]. Moreover, it was expected that in combination with TTFields even low effective doses of AZD1152 lead to increased cytotoxic effects. Compared to TTFields treatment alone, combined treatment of AZD1152 and TTFields resulted in significantly enhanced anti-tumor effects with a median reduction in cell number in U87-MG cells of 57.8% to 40.4% (Mann–Whitney U test, p < 0.01) as well as in all primary glioblastoma cultures (59.6–79.2% to 26.9–44.1%, Mann–Whitney U test) regardless of their p53 status or whether they were established from ndGBM or rGBM tissue samples, although further studies are needed to elucidate the exact involvement of the p53 pathway and the effect of the well-known heterogeneous molecular composition of glioblastoma. In addition to the enhanced anti-tumor effects of concomitant treatment with TTFields and AZD1152 relative to each treatment alone, increased cell morphological changes were also observed in confocal laser-scanning microscopic images (Figure 4). HT18584 (ndGBM, p53mut), HT16360-1 (rGBM, p53wt) and HT18816 (rGBM, p53wt) exhibited slight increases in the number of multinuclear cells following AZD1152 treatment (Figure 4, second column). This was also observed in HT12347 (ndGBM, p53mut), HT18584 (ndGBM, p53mut) and HT18816 (rGBM, p53wt) following TTFields application (Figure 4, third column). A higher prevalence of multinuclear cells was detected in all primary glioblastoma cultures exposed to AZD1152 and TTFields compared to cells treated with TTFields or AZD1152 alone (Figure 4; quantification shown in Supplementary Figure S3 and enlargements for AZD1152 only and TTFields only treatment, respectively, in Supplementary Figure S4). Thereby, HT18584 (ndGBM, p53mut), HT16360-1 (rGBM, p53wt) and HT18328-3 (rGBM, p53wt) showed particularly large cell nuclei. Concomitant treatment further resulted in an increase in cell size, especially in HT12347 (ndGBM, p53mut), HT16360-1 (rGBM, p53wt) and HT18328-3 (rGBM, p53wt). Since treatment with TTFields and the Aurora B kinase inhibitor AZD1152 leads to impaired mitosis and polyploidy, the DNA content was further examined using propidium iodide staining of treated U87-MG and primary glioblastoma cell cultures (Figure 5). In U87-MG and the ndGBM cell cultures HT12347 (ndGBM, p53mut) and HT18584 (ndGBM, p53mut), concomitant treatment of AZD1152 and TTFields significantly increased the percentage of cells with DNA content of 4n and >4n in comparison to control or TTFields treatment alone, while the percentage of cells with 2n DNA content significantly decreased. Similar effects were observed with AZD1152 treatment alone compared to the control. In contrast, the rGBM cell cultures showed some characteristics: HT16360-1 (rGBM, p53wt) and HT18328-3 (rGBM, p53wt) had a very low proportion of cells with a DNA content of 2n in the untreated state (HT16360-1: 6.4% ± 1.7%; HT18328-3: 10.1% ± 2.2%), indicating that these are predominantly tetraploid cell cultures. In HT18328-3 (rGBM, p53wt), the concomitant treatment of AZD1152 and TTFields significantly increased the proportion of cells with DNA content of >4n (48.5% ± 4.1%) compared with control (28.4% ± 2.4%, p < 0.001) and TTFields treatment alone (36.6% ± 6.0%, p < 0.001), while the fraction of cells with 4n DNA content significantly decreased (45.5% ± 3.4% vs. 61.4% ± 2.3% and 53.5% ± 6.2%, p < 0.01). For HT16360-1 (rGBM, p53wt), similar significant effects were observed only with combination treatment (4n: 46.6% ± 5.5%; >4n: 45.3% ± 7.5%) compared with control (4n: 53.5% ± 4.1%, p < 0.001; >4n: 37.2% ± 3.6%, p < 0.05), but not compared with TTFields treatment alone (4n: 48.2% ± 9.0%; >4n: 40.5% ± 7.2%). HT18816 (rGBM, p53wt), in turn, exhibited a very stable DNA content of 2n, both with the single treatments (5 nM AZD1152: 79.0% ± 2.4%; TTFields: 77.5% ± 2.4%) and with the concomitant treatment (76.9% ± 6.1%). The aim of this study was to investigate the preclinical efficacy of the concomitant treatment of TTFields and Aurora B kinase inhibition by AZD1152 in glioblastoma cells. We demonstrated that in the established long-term GBM cell lines, U87-MG and U87-MGshp53,, and, importantly, in primary cultures from ndGBM and rGBM tissue samples, the cytotoxic effect of TTFields plus AZD1152 was significantly higher than the effect of each treatment alone. In addition to surgery, radiation- and chemotherapy, treatment with electric fields, is increasingly incorporated into cancer therapy [25,26]. The EF-14 trial (ClinicalTrials.gov identifier NCT00916409) demonstrated that using TTFields in addition to adjuvant TMZ chemotherapy after combined chemo-radiation for ndGBM patients led to a significant prolongation of overall survival and double the rate of two-year survivors [27]. However, there is still a need to improve glioblastoma treatment, as nine out of ten patients do not survive five years past diagnosis [25]. In addition to varying the start and duration of TTFields treatment, which is being tested in ongoing clinical trials (EUDAMED-No. CIV-18-08-025247 and ClinicalTrials.gov identifier NCT03705351), identifying substances that might enhance the effects of TTFields on mitotic cells is an attractive strategy to improve treatment. Early in vitro data have shown that adding TTFields to anti-mitotic agents such as paclitaxel significantly reduces the median effective dose of the chemotherapy. Consequently, paclitaxel concomitant with TTFields was translated to clinical trials as a promising signal for safety and efficacy was seen [28] and evaluated in a phase II clinical trial for pancreatic cancer [29]. Aurora kinases are critical enzymes in the process of chromosomal segregation and cytokinesis in every cell type. Overexpression of Aurora kinases A and B is associated with malignant cell growth in various solid tissues and in myeloid cells, and can lead to acute myeloid leukemia (AML) [30,31]. Therefore, Aurora kinases are an ideal target for oncotherapy aiming at the selective inhibition of single kinase expression or function [32]. In gliomas, an overexpression of Aurora B kinase is associated with giant and multinucleated cells [17,33]. Inhibition of Aurora B kinase, in turn, results in a dysregulated connection between kinetochore and microtubule during mitosis, affecting the orientation of sister chromatids to opposite spindle poles and disrupting cytokinesis [19]. Inhibition of the CPC may lead to polyploidy, mitotic arrest, and cell death [34,35,36]. Xenograft experiments in mouse models have shown a tumor reduction after AZD1152 treatment in colon-, lung-, and hematological cancer [37]. Alafate et al. have identified Aurora B kinase as a therapeutic target in temozolomide resistant glioblastoma cells [38]. Clinical trials revealed that treatment with the selective Aurora B kinase inhibitor AZD1152 in patients with advanced solid tumors or AML was associated with an improved progression-free survival [39,40,41]. Frequent adverse events were myelotoxicity, particularly neutropenia, stomatitis, and mucositis [14,15,42]. To reduce the frequency and severity of associated toxicities, a lower effective dose of AZD1152 is desirable, which might be achieved by adding TTFields to AZD1152 treatment. Our data support the potential effectiveness of this approach; however, this finding and any impact on toxicities requires confirmation in a clinical setting. For in vitro experiments with leukemia, colon- or lung-carcinoma cell lines, a wide range of AZD1152 concentrations (3–5300 nM) was defined as the half-maximal inhibitory concentration [34,43]. In our experiments, as we expected an augmented or, ideally, an additive or even synergistic effect, we needed to define an AZD1152 concentration high enough to render a cytotoxic effect while leaving enough cells alive to detect the potential effect of adding TTFields. For proof of principle, we started our experiments with the established cell lines U87-MG and U87-MGshp53, as our group has shown previously that selective Aurora B kinase inhibition leads to polyploidy and non-apoptotic cell death independent of p53 [19], while others have shown an interaction between Aurora kinase expression and p53 status [44]. For U87-MG, we determined an IC50 of 25 nM AZD1152, whereas U87-MGshp53 was less sensitive with an IC50 of 50 nM AZD1152. However, the combined treatment of AZD1152 and TTFields not only led to a reduction in the number of U87-MG and U87-MGshp53 cells but also to enhanced morphological changes, such as an increased number of cells with multiple nuclei, compared to each treatment alone. For the treatment of primary GBM cultures, titration experiments were performed to identify the most suitable AZD1152 dose for each. IC50 was in the range between 14 nM and 75 nM AZD1152. However, a low effective dose of AZD1152 between 5 nM and 30 nM was selected because the use of low doses of the drug allows a better evaluation of concomitant treatment with TTFields. With regard to a possible clinical trial, based on the high efficacy of the combined treatment of TTFields with AZD1152, lower doses of Aurora B kinase inhibitor could be used, which would be associated with a reduced risk of toxicities. Furthermore, we searched for mutations in exon 5–9 of the TP53 gene and evaluated p53 expression in our ndGBM and rGBM cultures by western blot analysis. We identified TP53 C275F mutation, which lies within the DNA-binding domain of the TP53 protein [45]. C275F has been identified in the scientific literature [46,47,48] but has not been biochemically characterized, therefore its effect on TP53 protein function is unknown. Furthermore, we detected TP53 D208V mutation. To the best of our knowledge, there are no data about the TP53 D208V mutation, or its biochemical function, respectively. Various p53 statuses were identified with mutations in exons 6 and 8, respectively, of the TP53 gene in ndGBM and loss of p53 expression in two out of three rGBM cultures. The reason for that needs to be determined. In a previous study, we have shown that p53 accumulates in U87 cells [19]. This was also shown for the human colon carcinoma cell line HCT-116 by others [49]. The p53 protein decrease seems to be the result of other yet to be determined effects. One possible mechanism may be an amplification and overexpression of the negative p53 regulator MDM2, which occurs only in p53 wild-type GBM cells and leads to increased degradation of p53 [50]. In HT16360-1 (rGBM, p53wt), no mutation was found in the analyzed hot-spot areas and p53 expression was detected, which is in line with the strong EGFR and ErbB2 expression and polyploid state of that culture, suggesting an alternative route of malignization. TP53 regulates the postmitotic checkpoint after Aurora B inhibition. It might be speculated that an increase in HT16360-1 (rGBM, p53wt) cell line AZD1152 concentration leads to an increase in DNA damage. Increasing the number of p53 keeps cells in checkpoint arrest for a longer period of time, allowing damages to be repaired and cells to respond to AZD1152 to a lesser extent. Regardless of p53 status, we demonstrated a pronounced cytotoxic effect in all five primary glioblastoma cultures after treatment with TTFields and a low effective dose of AZD1152, supporting our data from the analysis of U87-MG and U87-MGshp53 cells. Interestingly, the primary rGBM culture HT18816 (rGBM, p53wt), which like all rGBM cultures had been pretreated by radiation and temozolomide-based chemotherapy, had a high proportion of diploid cells (76.5% ± 3.0%), while HT16360-1 (rGBM, p53wt) and HT18328-3 (rGBM, p53wt) had an average of only 6.4–10.1% of diploid cells. This cannot be explained by the MGMT methylation status. HT18816 (rGBM, p53wt) might be protected by its unmethylated MGMT promoter against the destabilizing effect of alkylating TMZ treatment, while HT16360-1 (rGBM, p53wt) is MGMT-methylated and thus polyploid. However, HT18328-3 (rGBM, p53wt) is MGMT-unmethylated and polyploid, suggesting that the observed ploidy is independent of the MGMT-status in those primary rGBM cultures. Treatment with either AZD1152 or TTFields, or both, led to only a minor increase in ploidy in primary cultures of rGBM compared to those of ndGBM. However, the cytotoxic effect observed in all three primary rGBM cultures was comparable with each other, suggesting that cellular instability due to polyploidy might not be the only reason for the observed cytotoxic effect. Further studies are needed to elucidate the underlying molecular pathways associated with our observed effects of a concomitant treatment with AZD1152 and TTFields on glioma cells. Recently, our group reported that AZD1152 treatment leads to a mitotic catastrophe and cell death via a caspase-3 independent pathway, irrespective of the p53 status of the cell. Knowing that TTFields induces several modes of cell death such as immunogenic death, autophagy, necroptosis, and others (reviewed by Tanzhu et al. [51]), which are not yet fully understood, we only can assume which molecular cascades are affected by a combination treatment with a drug also affecting cytokinesis. In view of the wide variety of genetic defects found in GBM, the number of primary cultures analyzed in our study might be too small to allow for a generalized statement. We consider our study to be a proof of principle for the hypothesis that Aurora B kinase inhibition, together with TTFields, could be effective in glioblastoma treatment, and potentially also allow for dose-reduced concentrations of the inhibitor. However, we do not know whether the Aurora B kinase inhibitor sufficiently penetrates the blood–brain barrier, particularly in combination with TTFields, where local pharmacokinetics might be altered. This should be investigated in subsequent animal studies. In addition, further experiments using glioblastoma stem cell organoids as recently shown for the combination of a Mammalian Target of Rapamycin (mTOR) inhibitor and TTFields might validate our findings [52]. The permanent glioma cell line U87-MG was authenticated by single nucleotide polymorphism (SNP) characterization (Multiplexion GmbH, Heidelberg, Germany). Its stable p53-deficient counterpart U87-MGshp53 was generated by transduction with the retroviral small hairpin (sh)RNA vector pRVH1-shp53-Hygro and has been described previously [36]. The use and further molecular analysis of primary cultures of ndGBM and rGBM from patients was approved by the local ethical committee (#EK 323122008) of the Medical Faculty Carl Gustav Carus, TU Dresden. After obtaining oral and written consent, primary glioblastoma cultures HT12347, HT18584, HT16360-1, HT18816 and HT18328-3 were prepared by using the Brain Tumor Dissociation Kit (P) (Miltenyi Biotec GmbH, Bergisch Gladbach, Germany). All cell lines were cultivated in DMEM, containing 4.5 g/L glucose supplemented with 10% v/v heat-inactivated FBS, 10 mM HEPES, 100 U/mL penicillin, and 0.1 mg/mL streptomycin (all from Life Technologies, Carlsbad, CA, USA) at 37 °C and 5% CO2 in a humidified incubator. U87-MGshp53 cells were maintained under selection with 400 mg/mL geneticin. Mutational analysis of coding regions of p53 known to contain the DNA-binding domain and the hot spot mutation sites in exon 5–9 has been described previously [53]. Amplification of exons 5, 6, 7 and 8/9 were performed by Phusion DNA polymerase. PCR products were subsequently purified using the GeneJET PCR Purification Kit (Thermo Fisher Scientific, Waltham, MA, USA) and sequenced by Microsynth AG, Balgach, Switzerland. Sequencing data were compared with sequence of wild-type p53 using ApE—A Plasmid Editor v2.0.47 (University of Utah, Salt Lake, UT, USA). For treatment with TTFields alone or in combination, the inovitro™ system (Novocure®, Root, Switzerland) was used as described previously [2]. The inovitro™ system comprises a TTFields generator and base plate containing eight ceramic dishes per plate. Next, 5 × 104 glioblastoma cells were plated in triplicate on 22 mm round, poly-L-lysine coated coverslips, which were placed inside the ceramic dishes. Following overnight incubation, the dishes were filled with 2 mL medium. TTFields (1.6 V/cm RMS, 200 kHz) were applied for 72 h, where the orientation of the TTFields was switched 90° every 1 s, thus covering many of the orientation axes of cell divisions, as previously described by Kirson et al. [4]. Medium was changed every 24 h. For titration of AZD1152-HQPA (AbMole BioScience, Houston, TX, USA) or the combined treatment with TTFields, AZD1152 was added to the medium after overnight incubation of plated cells at concentrations of 5-100 nM. Treatment was applied for 72 h, with medium changes, including fresh addition of AZD1152 every 24 h. Subsequently, inhibition of cell growth was quantitatively analyzed based on cell counting after propidium iodide (PI; Miltenyi Biotec GmbH, Bergisch Gladbach, Germany) staining, using flow cytometer EC800 (Sony Biotechnology, San Jose, CA, USA) or MACSQuant Analyzer 10 (Miltenyi Biotec). For immunophenotyping of generated primary glioblastoma cultures, cells were stained with anti-CD44-VioBlue, anti-EGFR-APC, and anti-ErbB2 (CD340)-PE (Miltenyi Biotec GmbH, Bergisch Gladbach, Germany) and with anti-GFAP-PE (Miltenyi Biotec) using the Inside Stain Kit (Miltenyi Biotec) according to the manufacturer’s instructions. Appropriate isotype controls were included in each measurement. For analysis of DNA content, treated glioblastoma cells were fixed with 70% ice-cold ethanol overnight and stained for 30 min with PI (1:50, Invitrogen, Waltham, MA, USA) in PBS containing 0.5% BSA. Stained cells were measured by MACSQuant Analyzer 10 flow cytometer (Miltenyi Biotec) and analyzed by FlowJo software version 10.6.2 (FlowJo, Vancouver, BC, Canada). Untreated and AZD1152-treated primary glioblastoma cells were lysed in lysis buffer (10 mM Tris-HCl, pH 8.0; 140 mM NaCl; 1% Triton X-100; 1× Halt Protease and Phosphatase Inhibitor Cocktail (Thermo Fisher Scientific, Waltham, MA, USA)). Then, 50 µg protein/lane were subjected to SDS-PAGE under reducing conditions and blotted on PVDF membrane using semidry Western Blotting. After blocking the PVDF membrane with 5% BSA, p53 was detected using a monoclonal rabbit anti-human p53 (7F5) antibody (1:1000, Cell Signaling, Danvers, MA, USA), followed by HRP-conjugated anti rabbit IgG secondary antibody (1:1000; Dako, Hamburg, Germany). To demonstrate equal loading, PVDF membranes were subsequently stained using an HRP-conjugated anti-GAPDH (0411) antibody (1:200; Santa Cruz, Dallas, TX, USA). Visual capturing of proteins was performed by Luminata Forte Western HRP substrate (Merck Millipore, Burlington, MA, USA) and G:Box Chemi XX9 (Syngene, Cambridge, UK). Data were analyzed by Fiji software (ImageJ 1.53c, National Institutes of Health, Bethesda, MD, USA). To detect morphological changes, treated U87-MG and U87-MGshp53 cells in comparison to untreated cells were fixed with 100% methanol, stained with 0.5% crystal violet (Sigma-Aldrich, St. Louis, MO, USA), and analyzed by an inverted light microscope (Nikon eclipse TS100, Nikon, Tokio, Japan). Treated glioblastoma cells were fixed using 4% paraformaldehyde in PBS. Subsequently, cell membranes or cytoskeleton were stained with Alexa Fluor 647 conjugated Wheat Germ Agglutinin (WGA; 1:200, Life Technologies, Carlsbad, CA, USA) or anti α-tubulin antibody (1:500, Sigma-Aldrich, St. Louis, MO, USA), respectively, followed by a secondary anti-mouse IgG-FITC antibody (1:200, Jackson ImmunoResearch, Ely, UK) according to the manufacturer’s protocols. DNA was stained using Hoechst 33342 (1:50,000, Invitrogen). The coverslips were placed upside down in a drop of Vectashield mounting medium (Vector Laboratories, Burlingame, CA, USA) on a microscope slide. The images were captured by a confocal laser scanning microscope (Leica SP5, Leica, Wetzlar, Germany) and analyzed by Fiji software (ImageJ 1.53c, National Institutes of Health, USA). The plugin “Cell Counter” of the Fiji software (ImageJ 1.53c, National Institute of Health, USA) was used to count cell nuclei in 4–7 confocal laser-scanning-microscope pictures per preparation. Data are expressed as mean ± SD, and the statistical significance of differences was assessed using GraphPad Prism 6 (GraphPad Software, Boston, MA, USA) or IBM SPSS Statistics 25 (IBM, Armonk, NY, USA). Differences between groups were compared using the Mann–Whitney U test, and were considered significant at values of * p < 0.05, ** p < 0.01, and *** p < 0.001. All experiments were performed in triplicates and repeated at least two times. We demonstrated that treatment with selective Aurora B kinase inhibition by AZD1152 and TTFields has a more pronounced cytotoxic effect than either treatment alone, not only in ndGBM but also in rGBM cells. This is encouraging, even just for the treatment of rGBM, as effective treatments are still a long way off.

PMC10003312

Hannes Jacob,Pauline Braekow,Rebecca Schwarz,Christian Höhm,Uwe Kirchhefer,Britt Hofmann,Joachim Neumann,Ulrich Gergs

Ergotamine Stimulates Human 5-HT4-Serotonin Receptors and Human H2-Histamine Receptors in the Heart

01-03-2023

ergotamine,human atrium,mouse atrium,mouse ventricle

Ergotamine (2′-methyl-5′α-benzyl-12′-hydroxy-3′,6′,18-trioxoergotaman) is a tryptamine-related alkaloid from the fungus Claviceps purpurea. Ergotamine is used to treat migraine. Ergotamine can bind to and activate several types of 5-HT1-serotonin receptors. Based on the structural formula of ergotamine, we hypothesized that ergotamine might stimulate 5-HT4-serotonin receptors or H2-histamine receptors in the human heart. We observed that ergotamine exerted concentration- and time-dependent positive inotropic effects in isolated left atrial preparations in H2-TG (mouse which exhibits cardiac-specific overexpression of the human H2-histamine receptor). Similarly, ergotamine increased force of contraction in left atrial preparations from 5-HT4-TG (mouse which exhibits cardiac-specific overexpression of the human 5-HT4-serotonin receptor). An amount of 10 µM ergotamine increased the left ventricular force of contraction in isolated retrogradely perfused spontaneously beating heart preparations of both 5-HT4-TG and H2-TG. In the presence of the phosphodiesterase inhibitor cilostamide (1 µM), ergotamine 10 µM exerted positive inotropic effects in isolated electrically stimulated human right atrial preparations, obtained during cardiac surgery, that were attenuated by 10 µM of the H2-histamine receptor antagonist cimetidine, but not by 10 µM of the 5-HT4-serotonin receptor antagonist tropisetron. These data suggest that ergotamine is in principle an agonist at human 5-HT4-serotonin receptors as well at human H2-histamine receptors. Ergotamine acts as an agonist on H2-histamine receptors in the human atrium.

Ergotamine Stimulates Human 5-HT4-Serotonin Receptors and Human H2-Histamine Receptors in the Heart Ergotamine (2′-methyl-5′α-benzyl-12′-hydroxy-3′,6′,18-trioxoergotaman) is a tryptamine-related alkaloid from the fungus Claviceps purpurea. Ergotamine is used to treat migraine. Ergotamine can bind to and activate several types of 5-HT1-serotonin receptors. Based on the structural formula of ergotamine, we hypothesized that ergotamine might stimulate 5-HT4-serotonin receptors or H2-histamine receptors in the human heart. We observed that ergotamine exerted concentration- and time-dependent positive inotropic effects in isolated left atrial preparations in H2-TG (mouse which exhibits cardiac-specific overexpression of the human H2-histamine receptor). Similarly, ergotamine increased force of contraction in left atrial preparations from 5-HT4-TG (mouse which exhibits cardiac-specific overexpression of the human 5-HT4-serotonin receptor). An amount of 10 µM ergotamine increased the left ventricular force of contraction in isolated retrogradely perfused spontaneously beating heart preparations of both 5-HT4-TG and H2-TG. In the presence of the phosphodiesterase inhibitor cilostamide (1 µM), ergotamine 10 µM exerted positive inotropic effects in isolated electrically stimulated human right atrial preparations, obtained during cardiac surgery, that were attenuated by 10 µM of the H2-histamine receptor antagonist cimetidine, but not by 10 µM of the 5-HT4-serotonin receptor antagonist tropisetron. These data suggest that ergotamine is in principle an agonist at human 5-HT4-serotonin receptors as well at human H2-histamine receptors. Ergotamine acts as an agonist on H2-histamine receptors in the human atrium. Ergotamine (Figure 1B), tested in this work, is currently mainly used in the clinic for the treatment of migraine [1,2]. Ergotamine can bind to and activate 5-HT1-receptors and 5-HT2A-receptors in the brain [2]. Ergotamine can lead to hallucinations probably via these 5-HT2A-receptors [3,4]. Ergotamine can cause vasoconstriction probably because ergotamine stimulates peripheral vascular 5-HT2A-receptors and peripheral vascular α1-adrenoceptors [4]. Ergotamine is found in fungi like Claviceps pururea (Secale cornutum). Secale cornutum can be found in cereals (e.g., rye grain) and causes arterial constrictions (via stimulation of α-adrenoceptors), but possibly also hallucinations (e.g., [5,6,7,8]). Ergotamine is formed in fungi from lysergic acid, to which, alanine, proline and phenylalanine are covalently linked [9]. No inotropic effect of ergotamine was found in isolated paced cat papillary muscle [10]. However, that might be a species problem, as H2-histamine- and 5-HT4-receptors are functionally absent in the cat heart [11,12,13]. A close derivative of ergotamine, called ergometrine (lysergic acid β-propanolamide), has, in contrast, been shown to elicit an increase in force in the guinea pig heart [14], which contains functional H2-histamine receptors [13]. The increase in force of contraction caused by ergometrine was antagonized by cimetidine, which convincingly suggested a H2-histamine receptor-mediated effect of ergometrine in the guinea pig heart [14]. Similarly, lysergic acid diethylamide (LSD) increased force of contraction in isolated guinea pig and rabbit cardiac preparations [15]. Hence, ergotamine might increase force of contraction in those species that contain functionally active H2-receptors in the heart. To the best of our knowledge, a positive inotropic cardiac effect by ergotamine in any mammalian species has never been published before. As ergotamine binds to some isoforms of peripheral serotonin-receptors [16], we hypothesized that ergotamine might stimulate human serotonin receptors in the heart. In the human heart, all inotropic and chronotropic effects of serotonin are mediated via 5-HT4-receptors [17,18]. These 5-HT4-receptors are lacking, in a functional manner, in mouse heart: serotonin failed to alter the force of contraction in isolated mouse cardiac preparations from wild type mice (WT, [19,20,21,22,23]). To facilitate the study of human 5-HT4-receptors, we had previously produced and characterized intensively transgenic mice (5-HT4-TG) with cardiac expression of this receptor only in the heart, which responded with an increase in force and frequency to serotonin [14,19,21,22]. Therefore, we decided to test the hypothesis that ergotamine would exert positive inotropic and positive chronotropic effects in these 5-HT4-TG (Figure 1A). In the heart, four histamine receptor subtypes have been found [13]. However, species differences, regional differences and cellular differences in histamine receptor function exist in the heart [13]. In the mouse heart, histamine can only release noradrenaline [22,23,24,25,26,27,28]. Similar to the mouse, the rat, dog and cat experienced the effects of histamine resulting from a release of endogenous catecholamines [11,15,29,30,31,32]. In humans, H2-histamine receptors are present in both the atrium and ventricle (radioligand binding: [33], antibody and RNA expression: [34]). The cardiac H2-histamine receptors mediate the positive inotropic effects of histamine in isolated human atrial cardiac preparations [35,36,37]. Therefore, we have generated transgenic mice that overexpress the H2-histamine receptors only in the heart (H2-TG), wherein histamine increases force of contraction [22,23,24,25,26,27,28]. Hence, we tested the following hypotheses: ergotamine might increase force of contraction in 5-HT4-TG and/or in H2-TG, and in human atrial preparations via HT4- and/or H2-receptors. Progress reports have been published in abstract form [38]. We noticed that ergotamine time- and concentration-dependently increased force of contraction in H2-TG. A typical original recording is seen in Figure 2A. For comparison, we studied WT. In WT, ergotamine failed to increase force of contraction (Figure 2B). In H2-TG additionally applied histamine, force of contraction further failed to increase (Figure 2A), while additionally applied histamine was ineffective in left atrium from WT (Figure 2B). Summarizing the results, one can see that ergotamine concentration-dependently increased force of contraction in left atrial preparations (Figure 2C). Moreover, ergotamine concentration-dependently shortened the time to peak tension (Figure 2D). This shortening was so extensive that additionally applied histamine could not shorten time to peak tension any further. In a similar fashion, ergotamine hastened time of relaxation concentration-dependently (Figure 2E) and additionally applied histamine was not more effective to shorten time of relaxation (Figure 2E). In addition, ergotamine also concentration dependently enhanced the absolute value of the rate-of-tension development (Figure 2F) and the rate-of-tension relaxation, and this effect of ergotamine was maximal because additionally applied histamine augmented these parameters no further. Hence, ergotamine acted as a full agonist at H2-histamine receptors under these conditions (Figure 2G). In right atrial preparations from H2-TG, ergotamine increased the beating rate as seen in an original recording (Figure 3A). Additionally applied histamine did not increase the beating rate any further (Figure 3A). Ergotamine failed to increase the beating rate in WT. Several such experiments are summarized in Figure 3B. We noticed that ergotamine time- and concentration-dependently increased force of contraction in 5-HT4-TG left atria. A typical original recording is seen in Figure 4A. For comparison, we studied WT: here, ergotamine failed to increase force of contraction (Figure 4B). In 5-HT4-TG, additionally applied 5-HT increased force of contraction further (Figure 2A), while ergotamine and 5-HT were ineffective in left atrium from WT (Figure 4B). Summarizing the results, one can see that ergotamine concentration-dependently increased force of contraction in left atrial preparations from 5-HT4-TG (Figure 4C). Moreover, ergotamine concentration-dependently shortened the time of tension in 5-HT4-TG (Figure 4D). This shortening was so extensive that additionally applied serotonin could not shorten time to peak tension any further. In a similar fashion, ergotamine hastened time of relaxation concentration-dependently (Figure 4E) and additionally applied histamine was not more effective to reduce time of relaxation (Figure 4E) in 5-HT4-TG. In addition, ergotamine also concentration-dependently enhanced the absolute value of the rate-of-tension development (Figure 4F) and the rate-of-tension relaxation (Figure 4G) in 5-HT4-TG. In right atrial preparations from 5-HT4-TG, ergotamine increased the beating rate as seen in an original recording (Figure 5A). Additionally applied serotonin hardly increased the beating rate any further in 5-HT4-TG (Figure 5A). Ergotamine failed to increase the beating rate in WT. Several such experiments are summarized in Figure 5B: Ergotamine concentration-dependently increased the beating rate in isolated right atrial preparations (Figure 5B). This effect was also antagonized by subsequently applied tropisetron. It was interesting to study whether ergotamine might affect left ventricular function, because in the mouse and human heart, the left ventricle is decisive for the perfusion of the organs of the body. Therefore, we perfused retrogradely isolated spontaneously beating whole hearts (Langendorff procedure) from H2-TG, 5-HT4-TG and WT with ergotamine. In brief, ergotamine (10 µM) increased left ventricular force of contraction and the rate-of-tension relaxation in the apex of hearts from H2-TG, 5-HT4-TG but not from WT (Table 1). Thus, the effects of ergotamine are not confined to the atrium but also present in the ventricle of the transgenic animals studied here. In separate experiments, we tested the effects of ergotamine on the phosphorylation state of phospholamban in left auricular heart samples from H2-TG and 5-HT4-TG. These left atrial samples were electrically stimulated, and at the end of the concentration–response curves (10 µM ergotamine), the atria were frozen in liquid nitrogen. It turned out that ergotamine increased the phosphorylation state of phospholamban at the amino acid serine 16 in H2-TG and 5-HT4-TG compared to WT atrial preparations (Figure 6), suggesting a stimulation of cAMP-dependent protein kinases (Figure 1A). To find out whether our data are relevant in the human heart and thus clinically relevant, we performed the next contraction experiments in human cardiac preparations. In isolated electrically driven right atrial preparations, cilostamide, a phosphodiesterase III inhibitor, raised force of contraction to some extent. After this pre-stimulation, additionally applied ergotamine increased force of contraction further. This is exemplified in the original recording depicted in Figure 7. The mean data are put together in Figure 8 and depict this increase. Thereafter, the question arose whether the H2- or the 5-HT4-receptor mediated these effects. Therefore, we additionally applied first tropisetron to block 5-HT4- and thereafter cimetidine to block H2-receptors. As depicted in Figure 7 and summarized in Figure 8, the positive inotropic effect of ergotamine was not sensitive to tropisetron, but sensitive to additionally applied cimetidine. Based on these data, we would regard the positive inotropic effect of ergotamine in the human right atrium as H2-receptor-mediated. The main new findings in this report as per the observation is that ergotamine can act as a functional agonist at both human 5-HT4- and human H2-receptors in the heart of appropriate transgenic mouse models. Importantly, ergotamine only uses H2-receptors to increase contractility in the human heart, specifically the human isolated atrium. Looking at the chemical structure of ergotamine and knowing that it was synthesized from ergot constituents [9], knowing also that ergotamine can act on 5-HT2A-receptors in the periphery, we hypothesized that ergotamine might stimulate human cardiac serotonin receptors. In the human heart, serotonin only increases force via 5-HT4-receptors. Hence, we thought that ergotamine might stimulate 5-HT4 receptors in the human heart. As a first step, we used as a model our 5-HT4-TG [19]. Indeed, we noted a positive inotropic effect of ergotamine in the atrium and ventricle of 5-HT4-TG. In atrial preparations, we could show that ergotamine is less effective than serotonin and is thus functionally a partial agonist at 5-HT4-receptors because additionally applied serotonin raised the force further. The observations were different in right atrium, here, ergotamine was of similar efficacy as serotonin, and thus can be viewed as a full agonist. The reason for this discrepancy is unclear. One attractive hypothesis is that the overexpression of 5-HT4-receptors is higher in the sinus node than in the left atrium. However, this issue was beyond the scope of the present work. It might be asked why we chose to study H2-TG. In other words, why should ergotamine stimulate cardiac histamine receptors? One could argue from a chemical point of view. If you look carefully at the structural formula of ergotamine (Figure 1B), you might discern an azole ring similar to the imidazole ring in histamine. In addition, we noted that ergometrine, a closely related lysergic acid derivative, can activate cardiac H2-receptors in guinea pig Langendorff-perfused hearts [14]. Moreover, LSD, or lysergic acid diethylamide, the well-known hallucinogenic drug also closely related to ergotamine, can stimulate rabbit H2-receptors and guinea pig H2-receptors in cardiac preparations [15]. Hence, we thought it worthwhile to test ergotamine in our H2-TG model system [23]. We noted that in H2-TG, as in guinea pig hearts and rabbit hearts [15], ergotamine acted as a partial functional agonist with regard to force of contraction. Moreover, as additionally applied histamine in atrial preparations from H2-TG hardly increased force or frequency above values reached by ergotamine itself, we would regard ergotamine as a fully functional agonist—with respect to force and beating rate at human H2-receptors expressed in the heart of H2-TG. Our assumption is that ergotamine acts as an agonist at cardiac human H2-histamine receptors because ergotamine increases force and beating rate only in atrium from H2-TG and not in WT. Likewise, we suggest ergotamine increases force and beating rate as an agonist at cardiac human 5-HT4-receptors because ergotamine only increases contractility in atrium from 5-HT4-TG and not in WT. Clearly, under our experimental conditions, ergotamine is a dual agonist at two receptors. One might hypothesize that the tryptamine ring of ergotamine binds to the binding pocket for tryptamine at the human 5-HT4-receptor. On the other hand, it can be claimed that the azole ring of ergotamine binds at the appropriate pocket of the human H2- receptors. There is sound evidence from crystallographic studies that ergotamine can bind with different functional groups to different receptors, but, in this case, to 5-HT2A-receptors and 5-HT2B-receptors [39]. Hence, there is precedence for our hypothesis. Moreover, there are data on a functional interaction of H2-receptors and 5-HT4 receptors in human atrial tissue. Even the order of drug application was relevant. In more detail, when we first applied an increasing concentration of 5-HT, a positive inotropic effect followed. When we subsequently deposited histamine in increasing concentrations to the organ bath, the force declined. We speculated that this might mean that H2-receptors, context-dependently, can couple to first inhibitory and then stimulatory GTP-binding proteins, leading to a decrease and then increase in cAMP levels and therefore force of contraction [22]. One might speculate that such an effect might also be induced by ergotamine. Any sufficiently large H2-receptor stimulation or 5-HT4-receptor stimulation leads to an increase in the phosphorylation state of regulatory proteins that are substrates for the cAMP-dependent protein kinase [18,26]. Indeed, we described similar to others that histamine acting via H2-receptors in the heart can increase the phosphorylation state of phospholamban [40] in H2-TG and the human atrium [13]. Likewise, we and others reported that serotonin via 5-HT4-receptors can increase protein phosphorylation in 5-HT4-TG and human atrium [19,41,42]. For instance, serotonin increased the phosphorylation state of phospholamban in the isolated human atrial strips [42]. We extend here our previous studies by showing the ergotamine increase in H2-TG and in 5-HT4-TG the phosphorylation state of phospholamban. These phosphorylations can explain, at least in part, why ergotamine increased the relaxation rate in atrial and ventricular preparations from H2-TG and 5-HT4-TG. Interestingly, ergotamine acted only as an agonist at H2-agonist and not at 5-HT4-receptors in the isolated human atrium. One hypothetical explanation would be that the density of the overexpressed receptors is very high for 5-HT4-serotonin receptors in transgenic mouse atrium (5-HT4-TG), much higher than in the human heart. Usually, if the receptor is more highly expressed in a cell, less agonist is needed to stimulate this receptor. In other words, 5-HT4-TG is a very sensitive system to detect actions of drugs on human 5-HT4-receptors. Alternatively, if a drug does not stimulate 5-HT4-receptors in 5-HT4-TG, this drug is unlikely to increase human cardiac force via 5-HT4-receptors. We have mRNA data that indicate a thousand-fold overexpression of the 5-HT4 receptor in the heart from 5-HT4-TG [22]. However, these were non-failing mouse hearts and we do not know how the H2-receptor or 5-HT4 receptor expression might change in failing mouse hearts, as has been reported for failing rat hearts; in these failing rat hearts the mRNA for the 5-H4 receptor increased over time [43]. Indeed, binding is hardly detectible with radioligands of 5-HT4-receptors in human hearts, whereas expression of H2 in human hearts is easily measurable with ligand binding and is quite high [17,33]; thus, this is a plausible, albeit hypothetical, explanation for our data in the human atrium. Another explanation would be the partial agonistic effect of ergotamine on force of contraction in atrial preparations from 5-HT4-TG. In other words, the intrinsic activity of ergotamine for 5-HT4-receptors is lower than that of 5-HT. This second observation might also contribute to the missing effect of ergotamine in human atrium via 5-HT4-receptors. Hence, we tentatively conclude that in vivo effects of ergotamine in the human heart on force of contraction are more likely mediated by H2-histamine and not by 5-HT4–receptors. We would predict that a tachycardia after treatment with ergotamine in patients could be blocked by cimetidine, an approved drug. However, this prediction needs to be confirmed in a clinical study. Peak therapeutic plasma levels of ergotamine around 0.69 nM have been cited [44]. In intoxications in humans, much higher plasma levels of ergotamine, such as 0.015 µM, have been communicated [5]. Moreover, ergotamine is degraded by CYP2D6. Drugs that inhibit the activity of CYP2D6 could thus increase plasma levels of ergotamine. Indeed, some cases of ergotamine intoxication have been reported when patients were also given in addition to ergotamine other drugs that are inhibitors of CYP2D6 [45]. In addition, high ergotamine levels in plasma should occur in patients with a defective polymorphism of CYP2D6, because then less ergotamine will be degraded. In summary, there are various clinical situations where high plasma concentrations of ergotamine are reached. Under these high concentrations of ergotamine, H2-receptors in the heart might be stimulated by ergotamine. This stimulation of H2-receptors can lead to cardiac arrhythmias [13]. There are case reports that ergotamine taken in dosage to treat migraine can lead to an acute coronary syndrome and to arrhythmias in patients [46,47]. Based on our data, and with confidence, one could try cimetidine in such patients to terminate arrhythmias, namely atrial fibrillation. We have not tested the effects on the sinus node of man directly. Such a study would require access to the human pacemaker or corresponding stem cells. Such studies were beyond the scope of this initial study. We did not have the opportunity to study contractility in human left ventricular tissue for lack of access to that tissue. However, we argue that our studies in Langendorff-perfused hearts make it at least likely that ergotamine is also an agonist in the human left ventricle. Moreover, we cannot provide molecular information in which parts of the ergotamine molecule can interact with the H2-receptor or the 5-HT4-receptor. To this end, crystallographic studies would be required in subsequent work. The investigation conforms to the Guide for the Care and Use of Laboratory Animals published by the National Research Council (2011) [48]. Animals were maintained and handled according to approved protocols of the animal welfare committees of the University of Halle-Wittenberg, Germany. The generation and initial characterization of the transgenic mice were described before [19,23]. In brief, the human H2–histamine-receptor cDNA or the human 5-HT4-serotonin-receptor cDNA together with a C-terminal 6xhistidine tag were cut from the parent plasmid and inserted into the Eco ICR site of a mouse cardiac α-myosin heavy chain promoter expression cassette. For all experiments, 12–30 weeks-old transgenic mice and WT littermates of both sexes were used. As reported often before, right or left atrial preparations from mice were isolated and mounted in organ baths (e.g., [20]). The buffer in the 10 mL-organ baths contained 119.8 mM NaCI, 5.4 mM KCI, 1.8 mM CaCl2, 1.05 mM MgCl2, 0.42 mM NaH2PO4, 22.6 mM NaHCO3, 0.05 mM Na2EDTA, 0.28 mM ascorbic acid and 5.05 mM glucose. The solution was continuously gassed with 95% O2 and 5% CO2 and maintained at 37 °C and pH 7.4 [20]. Spontaneously beating right atrial preparations from mice were used to study the intrinsic beating rate. The drug application was as follows. After equilibration was reached, ergotamine was cumulatively added to left atrial or right atrial preparations to establish concentration–response curves. Then, where indicated, either serotonin or histamine were additionally applied to the preparations (Figure 1B). The contractile studies on human preparations were done using the same setup and buffer as used in the mouse studies (see Section 2.2). The samples were obtained from sixteen patients. Fifteen patients were male and one patient was female. The mean age was 71 ± 10 years. Patient suffered from three vessel coronary heart disease and underwent bypass surgery. Drug therapy included metoprolol, furosemide, apixaban and acetyl salicylic acid. Our methods used for atrial contraction studies in human samples have been previously published and were not altered in this study [27]. As described repeatedly from our group [19,23], isolated whole mouse hearts were retrogradely perfused with the same buffer as in Section 4.2 above. Hearts were allowed to beat by themselves. Force was monitored from the apex cordis by a hook connected to an electronic force monitor and digitized. Perfusion with drugs took place with a syringe connected to a pump. This pump was connected as a bypass to the aorta. At the end of the experiments, hearts were rapidly brought to the temperature of liquid nitrogen to stop any phosphorylation or dephosphorylation reactions. Frozen samples were kept at −80 °C until biochemical analysis. The homogenization of the samples, protein measurements, electrophoresis, primary and secondary antibody incubation and quantification were performed following our previously established protocols [23]. First antibodies were anti-calsequestrin (CSQ) antibody, Santa Cruz #sc390999 (diluted 1:20,000) and anti-phospholamban (pSer16) antibody, Badrilla A-010-12 (diluted 1:5000). Data shown are means ± standard error of the mean. Statistical significance was estimated using the analysis of variance followed by Bonferroni’s t-test or the Student’s t-test as appropriate. A p-value < 0.05 was considered to be significant. The ergotamine was in dissolved dimethylsulfoxide (DMSO), serotonin and histamine were dissolved in water and were purchased from Sigma-Aldrich (Germany). All other chemicals were of the highest purity grade commercially available. Deionized water was used throughout the experiments. Stock solutions were prepared fresh daily. We can now answer the questions raised in the introduction in the following way: ergotamine increases force of contraction in both 5-HT4-TG and in H2-TG. In human atrial preparations, ergotamine increases force of contraction via the H2-receptors and not via 5-HT4-receptors.

PMC10003314

Payel Sen,Bachuki Shashikadze,Florian Flenkenthaler,Esther Van de Kamp,Siyu Tian,Chen Meng,Michael Gigl,Thomas Fröhlich,Daphne Merkus

Proteomics- and Metabolomics-Based Analysis of Metabolic Changes in a Swine Model of Pulmonary Hypertension

02-03-2023

pulmonary hypertension,proteomic analysis,metabolomic analysis

Pulmonary vein stenosis (PVS) causes a rare type of pulmonary hypertension (PH) by impacting the flow and pressure within the pulmonary vasculature, resulting in endothelial dysfunction and metabolic changes. A prudent line of treatment in this type of PH would be targeted therapy to relieve the pressure and reverse the flow-related changes. We used a swine model in order to mimic PH after PVS using pulmonary vein banding (PVB) of the lower lobes for 12 weeks to mimic the hemodynamic profile associated with PH and investigated the molecular alterations that provide an impetus for the development of PH. Our current study aimed to employ unbiased proteomic and metabolomic analyses on both the upper and lower lobes of the swine lung to identify regions with metabolic alterations. We detected changes in the upper lobes for the PVB animals mainly pertaining to fatty acid metabolism, reactive oxygen species (ROS) signaling and extracellular matrix (ECM) remodeling and small, albeit, significant changes in the lower lobes for purine metabolism.

Proteomics- and Metabolomics-Based Analysis of Metabolic Changes in a Swine Model of Pulmonary Hypertension Pulmonary vein stenosis (PVS) causes a rare type of pulmonary hypertension (PH) by impacting the flow and pressure within the pulmonary vasculature, resulting in endothelial dysfunction and metabolic changes. A prudent line of treatment in this type of PH would be targeted therapy to relieve the pressure and reverse the flow-related changes. We used a swine model in order to mimic PH after PVS using pulmonary vein banding (PVB) of the lower lobes for 12 weeks to mimic the hemodynamic profile associated with PH and investigated the molecular alterations that provide an impetus for the development of PH. Our current study aimed to employ unbiased proteomic and metabolomic analyses on both the upper and lower lobes of the swine lung to identify regions with metabolic alterations. We detected changes in the upper lobes for the PVB animals mainly pertaining to fatty acid metabolism, reactive oxygen species (ROS) signaling and extracellular matrix (ECM) remodeling and small, albeit, significant changes in the lower lobes for purine metabolism. Pulmonary hypertension (PH) due to pulmonary vein stenosis (PVS) is a life-threatening disease, which mainly affects the pediatric population [1]. This type of PH, which ultimately results in a left ventricular inflow tract obstruction, is classified under type II PH [2]. PVS presents mostly with congenital heart defects (univentricular heart disease, ventricular septal defect, atrial septal defect or persistent arterial duct), lung disease (bronchopulmonary dysplasia) or Down syndrome or other trisomy [3,4]. In rare cases, PVS can also occur in adults because of radiofrequency ablation therapy after atrial fibrillation [5]. This particular type of PH is characterized by an initial passive increase in pulmonary artery pressure brought on by increased resistance due to the banding. The increased mean pulmonary artery pressure results in vascular remodeling, which further raises pulmonary vascular resistance and causes an additional increase in pressure. Surgical interventions and/or stenting of the lesions in patients with PVS frequently lead to restenosis, and the use of vasodilators comes with the risk for pulmonary edema [6]. The complex molecular mechanisms involved in PH are limiting factors in the development of novel therapeutic interventions. Previous work by our group has shown that endothelial factors are important in the development of PH in a swine model using pulmonary vein banding (PVB) of the lower lobes for 12 weeks to induce type II PH [7]. This procedure results in areas of the lung with a varied hemodynamic profile within the lung; the lower lobes experience high pressure and low flow (HF/LF) whereas the upper lobes experience high pressure and high flow (HP/HF). High and low shear stress have very striking effects on the endothelial cells of the lung vasculature. Endothelial cells typically respond to high shear stress with strong nitric oxide synthesis, but they “activate” a pro-inflammatory profile at low shear stress, characterized by low nitric oxide production [8]. In this study, we conducted a quantitative LC-MS/MS-based proteomic analysis of lung samples along with untargeted metabolomics from swine with PVB and control (Cntrl) swine. We analyzed tissues from the upper and lower lobes to investigate how different hemodynamic profiles impact protein and metabolite expression due to PH in the lobes. Pulmonary vein banding in the PVB group animals resulted in significant stenosis in the inferior pulmonary confluence as shown in the angiogram (Figure 1A). Twelve weeks after banding, this resulted in a significantly higher mean pulmonary artery pressure (38 ± 8 mmHg) in the PVB animals compared to the control (mean of 20 ± 4 mmHg, p < 0.05) (Figure 1D) as well as an increased pulmonary vascular resistance and reduced pulmonary artery compliance (Figure 1E,F). Histology of the lung tissue revealed more picrosirius red staining in the PVB animals in the upper and lower lobe, depicting more fibrosis compared to the Cntrl (Figure 1B,C). To explore the chronic effects of flow and pressure alterations in the lung tissue, we performed a label-free liquid chromatography–tandem mass spectrometry analysis (LC-MS/MS) of PVB vs. Cntrl samples from the upper as well as the lower lobes (n = 6 for PVB; n = 7 for Cntrl). Using LC-MS/MS-based proteomics, we identified 5112 proteins with high confidence (false discovery rate < 0.01) (Supplementary Data 1, Table S1). The dataset has been submitted to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD038982 [9]. Differential abundance analysis revealed significant differences between groups. The principal component analysis showed clustering of the PVB animals compared to the Cntrls in the upper (HP/HF) lobe, whereas similar clustering was absent in the lower lobe (HP/LF) (Figure 2A,B). In total, 104 proteins were found to be differentially abundant (Benjamini–Hochberg corrected p-value < 0.05 and fold change ≥ 1.5) between PVB and Cntrl in the upper lobes (Supplementary Data S1, Table S2). In the lower lobes, 52 proteins differed significantly in abundance between PVB and Cntrl (Supplementary Data S1, Table S3). Volcano plots were used to visualize proteome alterations between conditions (Figure 3A,B). In the upper lobe, several apolipoproteins (APOF, APOA, APOC3), complement cascades (C6, C7, C8, C9) and coagulation proteins (Serpins, HRG, PROC) were found to be downregulated in the PVB animals, while several membrane transport proteins (SCGB1A1, SFTPA1) were found to be upregulated. In the lower lobe, DNA binding and ribosomal proteins (H1-2, H1-1, RPS6) were upregulated, while membrane remodeling proteins (GMPR, ALF1, SIGLEC1) were downregulated. We performed a STRING preranked functional enrichment analysis of proteome profiles from the upper and lower lobe to reveal lobe-specific signatures for PVB and Cntrl animals. From the Gene Ontology (GO) biological processes database, 67 and 7 significantly enriched terms were found in the upper and lower lobe, respectively (enrichment factor >1) (Figure 3C, Supplementary Data S1, Tables S4 and S5), PVB upper lobes showed a distinct downregulation of proteins related to humoral immune regulation, lipoprotein particle organization, cholesterol esterification and triglyceride homeostasis and an upregulation of proteins related to platelet degranulation, coagulation, cholesterol efflux and intermembrane lipid transport. Proteins related to the extracellular matrix were found to be both up- as well as downregulated in PVB animals, indicating altered matrix turnover. In the lower lobe, PVB showed fewer enriched pathways compared to the upper lobe. The majority of the pathways were related to blood coagulation, extracellular matrix reorganization, actin cytoskeletal organization and carbohydrate metabolism. Since ECM-related proteins were altered in both lobes, we also compared the proteins in this pathway in both upper and lower PVB lobes with the established lung matrix gene set and found several proteins (collagens, serpins, etc.) that were differentially regulated (Supplementary Figure S1A) [10]. Next, we performed untargeted metabolomics on these lung tissues to better understand the ongoing metabolic alterations caused by variations in flow and pressure. To detect the relevant metabolites, we used statistical analysis with XCMS and MetaboAnalyst 5:0 software. Supplementary Data S2, Table S1 lists the metabolites that were detected in the HILIC-negative mode MS. On the MetaboAnalyst platform, a 3D PCA analysis (Figure 4A,B) and a supervised orthogonal partial least squares discriminant analysis (OPLS-DA) (Figure 4C,D) were performed for both the upper and lower lobes. In the upper lobe, 3D PCA and OPLS-DA analysis revealed separation between the PVB and Cntrl groups. Similar to the case for our proteomics findings, the lower lobe groups did not show a clear separation in metabolomics either. The OPLS-DA analysis also allowed for the identification of the metabolites that contributed the most to group segregation, known as variable importance in the projection (VIP) scores, and they were ranked accordingly (Figure 5A). Metabolites with a VIP score of ≥1 were interpreted as highly influential (Supplementary Data S2, Tables S2 and S4), and we performed an enrichment analysis of metabolites with p < 0.05 to differentiate control from PVB animals (Figure 5B). In comparison to Cntrl, we found 82 such metabolites in the PVB upper lobe (Supplementary Data S2, Table S3) and 29 metabolites in the PVB lower lobe (Supplementary Data S2, Table S5). Enrichment analysis for the PVB upper lobe revealed 25 metabolic pathways, of which the following six pathways had a p-value of <0.05: linoleic acid metabolism, ubiquinone biosynthesis pathway, transfer of acetyl groups into mitochondria, arginine, proline metabolism and glycerolipid metabolism. The lower lobe showed enrichment of 11 pathways, but none were significantly altered (p < 0.05). We detected the pathway for purine metabolism (p = 0.06) to be the most differentially regulated (Supplementary Figure S2). A combined analysis of the two omics datasets was carried out in order to identify commonly altered pathways and to provide additional insight into the process of pulmonary vascular remodeling. The metabolite–metabolite and the gene–metabolite interaction networks provide an overview of functionally related metabolites and proteins found to be most differentially abundant in metabolomics and proteomics. The metabolite–metabolite pathway interaction network derived from the KEGG database is shown in Figure 6A and highlights functional interactions among the top altered metabolites such as oleic acid, linoleic acid, palmitic acid, prostaglandin E2 and L-malic acid, butyric acid, NADP, proline, threonine, S-adenosylhomocysteine and arachidonic acid. Next, the most significantly altered proteins and metabolites identified were mapped to the gene–metabolite molecular interactions to create a network (Figure 6B). The network includes 31 nodes (protein, metabolites) and shows that the metabolites (squares) are upregulated whereas the proteins (filled circles) are downregulated. The metabolite chondroitin sulfate, a major component of the extracellular matrix (ECM), is upregulated in the upper lobe of the PVB group and formed a network with proteins important for wound healing such as serpinc1, serpinD1, F12, PROC, VTN, AMBP and TNC. Plasminogen (PLG), another prominent protein involved in wound healing and ECM remodeling, is functionally linked to both chondroitin sulfate and oleic acid. The PVB upper lobe was enriched in oleic acid, linoleic acid, palmitic acid, butyric acid and arachidonic acid, which formed a network with downregulated proteins in the PVB group such as ApoA1, ApoB, AdipoQ and ALB. These proteins and metabolites together participate in fatty acid metabolism. Prostaglandin E2, a common byproduct of arachidonic acid, is also upregulated in the PVB upper lobe and has formed a network with complement cascade members C8A and C3 as well as the chemokine PPBP, which are involved in inflammation. Finally, the monosaccharide metabolite glucose was downregulated in the upper lobe and functionally linked with the surfactant protein SFPTD and the blood coagulation protein HBB, indicating altered glucose metabolism. The PVB lower lobe presented with a metabolite–metabolite interaction network involving only four metabolites: guanosine monophosphate, inosinic acid, glyceric acid and dodecanoic acid (Supplementary Figure S3A). The gene metabolite network showed a simple network involving only guanosine monophosphate and inosinic acid (Supplementary Figure S3B). They functionally connected with the downregulated the enzyme guanosine monophosphate reductase (GMPR) and HPRT1 in the PVB lower lobe. Furthermore, the metabolite guanosine monophosphate was connected to the interferon-induced guanylate binding protein (GBP1). The protein abundance of members of apolipoproteins in the upper lobe as well as the lower lobe was further compared in dot plot analysis, and members of this fatty acid uptake pathway were validated at a transcriptional level (Figure 7A–C, Supplementary Figure S4A). ApoE was found to be significantly altered in both proteomics as well as at the transcriptional level in the upper lobe of the PVB group. In addition, further transcripts coding for proteins important for fatty acid uptake such as CD36 (p = 0.1) showed a trend toward a decrease in the PVB upper lobe compared to Cntrls along with significant upregulation of the LDLR (low-density lipoprotein receptor). In contrast, we did not see similar changes at the mRNA level for these proteins in the lower lobe of PVB compared to Cntrls. The main findings in this study were that (i) chronic alterations in flow and pressure induced by PVB impact the proteomic and metabolomic profile in the lung tissue and result in increased ECM and collagen production in lobes with both HP/HF and HP/LF; (ii) upper lung lobes with HP/HF adapt by altering the fatty acid metabolism as well as ROS signaling and (iii) the lower lobes with HP/LF increase their purine metabolism in order to cope with the increased demand of cellular proliferation (Figure 8). We have previously demonstrated that PH caused by pulmonary vein stenosis results in a progressive increase in pulmonary vascular resistance, which is accompanied by functional (increased contribution of endothelin, phosphodiesterase 5) as well as structural (increased media thickness) pulmonary vascular remodeling [7,11]. Banding of the confluence of veins from the lower lobes results in areas of the lungs with distinct hemodynamic profiles: HP/HF in the unbanded upper lobes and HP/LF in the banded lobes. This model is, therefore, well suited for the study of mechano-metabolic coupling and its role in pulmonary vascular remodeling in PH, as it has been demonstrated that metabolic and structural changes are coupled to each other [12]. Here, we present a thorough proteome and metabolome profile analysis of lung tissue with these distinct mechanical profiles. Pathway enrichment analysis in PVB animals demonstrated changes in several pathways that have been associated with the progression of PH. Thus, alterations were observed for extracellular matrix proteins involving integrins, matrix metalloproteases, collagen, vitronectin, serpins and others observed in both lobes of the animals. This is in accordance with our histological data, suggesting increased ECM deposition around the vessels. We also detected high amounts of phosphatidylcholine (PC) as well as prostaglandins, which indicate plasma membrane break and inflammatory signaling due to high shear stress [13]. In line with these findings, the comparison with the lung matrix database revealed that further extracellular matrix proteins were altered in the upper and lower lobes of PVB swine (Supplementary Figure S1A). ECM proteins such as FGB, COL1A and COL15A1 were significantly upregulated in the PVB lower lobe, whereas in the upper lobe, the analysis revealed synergistic downregulation of extracellular proteolytic proteins such as MMP9 and serpins [14,15]. Strikingly, proteins of the apolipoprotein family were significantly altered in abundance in PVB animals. The key protein component of HDL-C, apolipoprotein A (APOA), which was downregulated in the upper lobe, was not shown to be differentially regulated in the lower lobe. Downregulation of APOA1 is in accordance with data showing that ApoA-1 is less prevalent in PH, which contributes to oxidative stress and endothelial dysfunction [16]. Furthermore, administration of a peptide mimetic of ApoA-1 reduced pulmonary hypertension in rodent models with PH [17]. Along with ApoA, we also detected significantly reduced levels of ApoE at the proteomics as well as at the transcription level in the PVB upper lobe. The metabolomics data in the upper lobe further point to an ongoing alteration of lipid homeostasis and detected increased fatty acids such as oleic acid, linoleic acid, arachidonic acid and palmitic acid in the PVB group, indicating a reduced uptake of fatty acids due to decreased levels of apolipoproteins [18]. High amounts of linoleic and oleic acids have been found to significantly lower nitric oxide (NO) levels in endothelial cells and exert their deleterious effects via ROS [11,19,20]. It has been shown that HIF-1α activation, a common dysregulated pathway in PH and lung diseases, can inhibit β-oxidation of long-chain fatty acids leading to accumulation of fatty acids [21]. However, we did not detect increased accumulation of carnitine and acyl-carnitine, which reflects inhibition of mitochondrial fatty acid β-oxidation and has been previously shown to be involved in the development of PH [22]. In keeping with studies from Umar et al. who showed higher oxidized LDL in the lungs and plasma in PH with a decrease in CD36, our proteomic analysis did detect modifications of pathways regulating cholesterol levels consisting primarily of the downregulation of fatty acid transporters such CD36 and LDLRAP1 [23]. Along with this, we detected significant upregulation of the protein LDLR in the PVB upper lobe. LDLR mainly binds to apolipoprotein B100 (APOB) and APOE to clear cholesterol from the blood [24]. Both ApoB and ApoE are high-affinity ligands for LDLR and are expressed in various immune and vascular cells [24,25]. Negative feedback inhibition from transcriptional and posttranscriptional mechanisms closely controls the LDLR pathway, and disruption of this tightly controlled pathway can influence lipid and cholesterol regulation [26]. These data are also in accordance with integrated proteomic and metabolomics data on HUVECs presented by Venturini et al., showing that high shear stress upregulates the lipoprotein metabolism and increases the expression of LDLR [27]. Additionally, we found metabolites such as oxaloacetic acid and L-malic acid, both intermediate products of the TCA cycle, to be enriched in the PVB upper lobe along with decreased glucose. These metabolites take part in anaplerotic reactions in which the intermediate metabolites exit the TCA cycle and are used by proliferating cells due to an increased demand for protein and fatty acids in PH [12]. These data support the presence of the Warburg effect, showing that glucose metabolism is increased in PH [28,29,30,31]. Further evidence for this Warburg effect is the lower amount of NADP in the PVB upper lobe. NADP maintains the redox balance in the cells and supports the biosynthesis of the fatty acids and is essential for maintaining a large number of biological processe [32]. In agreement with this finding, Nukula et al. reported a lower NADPH/NADP ratio in CTEPH patients’ endothelial cells compared to healthy subjects, implying increased oxidative stress and endothelial cell dysfunction [30]. A key metabolite that was downregulated in the PVB upper lobe and deemed important from our network analysis was S-adenosylhomocysteine (SAH). Asymmetric dimethyl arginine (ADMA), a negative regulator of endothelial nitric oxide synthase, is formed by the hydrolysis of methylated proteins, and the methylated proteins are derived when S-adenosyl methionine (SAM) is converted to SAH. We also simultaneously observed increased aspartic arginine (VIP > 1, Supplementary Data S2, Table S2), which is a source of NO in endothelial cells, in the upper lobe of the PVB group [23,24]. In our previous work, we have shown that NO production is increased in HP/HF areas, likely as a compensatory mechanism to maintain vasodilation [33]. Our current data suggest that low SAH, and hence low ADMA, in combination with high arginine, the substrate for endothelial NO synthesis, facilitates NO synthesis in the PVB upper lobe vasculature. Notably, proteomic and metabolic alterations were less pronounced between PVB and Cntrls in the lower lobes. The STRING analysis points to reduced glucose synthesis in the PVB lower lobes, which supports the notion that glycolysis predominates over other metabolic activities in PH in the lower lobes as well [22]. Another intriguing observation was that the purine pathway metabolites adenosine monophosphate (AMP) and guanosine monophosphate (GMP) were significantly enriched, and the enzyme guanosine monophosphate reductase (GMPR), which converts GMP to inosine monophosphate (IMP), was downregulated. Additionally, our proteome data revealed that the PVBs had a decreased abundance of the enzyme HPRT, which transforms hypoxanthine into IMP and is crucial for the salvage pathway for recycling nucleotides [34]. We also found more inosine in the metabolome of PVB lower lobes, which indicated that the cells increased de novo purine production rather than using the standard active salvage pathway. These data are consistent with the study by Hautbergue et al., wherein modifications to the purine metabolic pathway in the right ventricle and plasma of PH rats were shown [35]. The purine metabolite levels in endothelial cells from PAH patients have also been found to be higher, the same was true for the serine to glycine ratio, which is mediated by the mitochondrial enzyme serine hydroxymethytransferase (SHMT) [36]. Although SHMT was unchanged in our lung tissue samples, we did observe an increase in the metabolite serine (VIP > 1) in the PVB lower lobes (Supplementary Data 2, Table S4). Moreover, in atherosclerosis models, it has been shown that vessels with low flow and shear stress have decreased endothelial nitric oxide synthase (eNOS) along with increased cell proliferation and collagen deposition [31]. Lung tissue was used from experiments that have previously been published [7,11,33]. These experiments followed the guiding principles in the care and use of laboratory animals, which are endorsed by the Council of the American Physiological Society, and the protocol was approved by the Animal Care Committee at Erasmus University Medical Center (EMC3158, 109-13-09). For all surgical procedures, swine were sedated with an intramuscular injection of a mixture of tiletamine/zolazepam (5 mg kg−1, Virbac, Barneveld, The Netherlands), xylazine (2.25 mg kg−1, AST Pharma, Oudewater, The Netherlands) and atropine (0.5 mg) and intubated and ventilated (O2:N2 (1:2)). Isoflurane (2% vol/vol, Pharmachemie, Haarlem, The Netherlands) was added to the gas mixture to induce anesthesia. Post-surgical analgesia was administered by means of an i.m. injection (0.3 mg buprenorphine i.m. Indivior, Slough, UK) and a fentanyl slow-release patch (6 or 12 μg h−1 depending on body weight, 72 h). Crossbred Landrace x Yorkshire pigs of either sex (8 ± 2 kg) underwent non-restrictive inferior pulmonary vein banding (n = 6) via the third right intercostal space or a sham procedure (n = 7). All 13 animals, underwent chronic instrumentation 4 weeks later, enabling hemodynamic assessments on awake animals. Following a left-sided thoracotomy in the fourth intercostal space, fluid-filled catheters (Braun Medical Inc., Bethlehem, PA, USA), were inserted in the aorta, the pulmonary artery, the left and right ventricle and the left atrium for the measurement of blood pressure. A flow probe (20PAU, Transonic systems, Ithaca, NY, USA) was placed around the ascending aorta for the measurement of cardiac output. Aorta flow was indexed to bodyweight. The total pulmonary vascular resistance index was calculated as the ratio of mean PAP and cardiac index, while pulmonary vascular compliance was calculated as stroke volume index/(systolic PAP − diastolic PAP). Hemodynamics were recorded (WinDaq, Dataq Instruments, Akron, OH, USA) in the awake state, with swine standing quietly, and analyzed offline using a custom written program (Matlab, version R2007b, The MathWorks). Twelve weeks after the PVB procedure, swine were re-anesthetized; the thorax was opened using sternotomy, and the heart and lungs were excised, snap-frozen in liquid nitrogen and processed for further analysis. Lung tissue was snap-frozen and 30 mg of tissue was homogenized, and mRNA was extracted using the RNeasy Fibrous Tissue Mini kit (Qiagen, Hilden, Germany). cDNA was synthesized using 500 ng of mRNA and the SenSi FAST cDNA synthesis kit (Bioline, London, UK). Target genes were normalized against beta-actin and cyclophilin using the CFX manager software 3.1 (BioRad, CA, USA). Relative gene expression was calculated using the delta–delta Ct method. Frozen lung tissue samples were placed into precooled tubes and cryopulverized in a CP02 Automated Dry Pulverizer (Covaris, Woburn, MA, USA) with an impact level of 5 according to the manufacturer’s instructions. Tissue lysis was performed in 8 M urea/0.5 M NH4HCO3 with ultrasonication (18 cycles of 10 s) using a Sonopuls HD3200 (Bandelin, Berlin, Germany). Total protein concentration was quantified using a Pierce 660 nm Protein Assay (Thermo Fisher Scientific, Rockford, IL, USA). Fifty micrograms of protein were digested sequentially, firstly with Lys-C (FUJIFILM Wako Chemicals Europe GmbH, Neuss, Germany) for 4 h and, subsequently, with modified porcine trypsin (Promega, Madison, WI, USA) for 16 h at 37 °C. 1 μg of the digest was injected on an UltiMate 3000 nano-LC system coupled online to a Q Exactive HF-X instrument operated in the data-dependent acquisition (DDA) mode. Peptides were transferred to a PepMap 100 C18 trap column (100 µm × 2 cm, 5 µM particles, Thermo Fisher Scientific) and separated on an analytical column (PepMap RSLC C18, 75 µm × 50 cm, 2 µm particles, Thermo Fisher Scientific) at a 250 nL/min flow rate with a 160 min gradient of 3–25% of solvent B followed by a 10 min ramp to 40% and a 5 min ramp to 85%. Solvent A consisted of 0.1% formic acid in water and solvent B of 0.1% FA in acetonitrile. MS spectra were acquired using a top-15 data-dependent acquisition method on a Q Exactive HF-X mass spectrometer. Protein identification was carried out using MaxQuant (v.1.6.7.0) [37] and the NCBI RefSeq Sus scrofa database (v.7-5-2020). All statistical analyses and data visualization were performed using R (https://www.r-project.org/) (accessed on 29 December 2022). Prior to statistical analysis, potential contaminants, only identified by site and reverse hits were excluded. Proteins with at least two peptides detected in at least three samples of each condition were quantified using the MS-EmpiRe algorithm as previously described [38,39]. The R script used for quantitative analysis is available at https://github.com/bshashikadze/pepquantify (accessed on 7 September 2022). Proteins with a Benjamini–Hochberg corrected p-value ≤ 0.05 and fold change ≥ 1.5 were regarded as significantly altered. Preranked gene set enrichment analysis using STRING was employed to reveal biological processes related to differentially abundant proteins [40]. Signed (based on fold change) and log-transformed p-values were used as ranking metrics and the false discovery rate was set to 1%. The redundancy of the significantly enriched biological processes was minimized using REVIGO tool [41]. Approximately 50 mg of sample material was weighed in a 2 mL bead beater tube (CKMix, Bertin Technologies, Montigny-le-Bretonneux, France) filled with 2.8 mm and 5.0 mm ceramic beads. Then, 1 mL of a methanol/water mixture (70/30, v/v) was added, and the samples were extracted with a bead beater (Precellys Evolution, Bertin Technolgies, Montigny-le-Bretonneux, France) supplied with a Cryolys cooling module 3 times each for 20 s with 15 s breaks in between at 10,000 rpm. After centrifugation at 13,000 U/min for 10 min, the supernatants were dried by vacuum centrifugation, suspended in 150 µL of methanol/water (70/30, v/v) and subjected to MS analysis. Untargeted analysis was carried out on a Nexera UHPLC system connected to a Q-TOF mass spectrometer (TripleTOF 6600, AB Sciex, MA, USA). Chromatographic separation was achieved by using a HILIC UPLC BEH Amide 2.1 × 100, 1.7 µm column with a 0.4 mL/min flow rate. The mobile phase consisted of 5 mM ammonium acetate in water (eluent A) and 5 mM ammonium acetate in acetonitrile/water (95/5, v/v) (eluent B). The following gradient profile was used: 100% B from 0 to 1.5 min, 60% B at 8 min, 20% B at 10 min to 11.5 min and 100% B at 12 to 15 min. Aliquots of 5 µL per sample were injected into the UHPLC-TOF-MS. The autosampler was cooled to 10 °C, and the column oven was heated to 40 °C. A quality control (QC) sample was pooled from all samples and injected after every 10 samples. MS settings in the positive mode were as follows: gas 1 55, gas 2 65, curtain gas 35, temperature 500 °C, ion spray voltage 5500, declustering potential 80. The mass range of the TOF-MS scans was 50–2000 m/z, and the collision energy was ramped from 15 to 55 V. MS settings in the negative mode were as follows: gas 1 55, gas 2 65, cur 35, temperature 500 °C, ion spray voltage −4500, declustering potential −80. The mass range of the TOF-MS scans was 50–2000 m/z, and the collision energy was ramped from −15 to −55 V. The “msconvert” tool from ProteoWizard [42] was used to convert raw files to mzXML (denoised by centroid peaks). The bioconductor/R package xcms [43] was used for data processing and feature identification. More specifically, the matched filter algorithm was used to identify peaks (full width at half maximum set to 7.5 s). Then the peaks were grouped into features using the “peak density” method. The area under the peak was integrated to represent the abundance of features. The retention time was adjusted based on the peak groups presented in most samples. To annotate features with the names of metabolites, the exact mass and MS2 fragmentation pattern of the measured features were compared to the records in HMBD [44] and the public MS/MS spectra in MSDIAL [45], referred to as MS1 and MS2 annotation, respectively. Missing values were imputed with half of the limit of detection (LOD) methods, i.e., for every feature, the missing values were replaced with half of the minimal measured value of that feature in all measurements. To confirm that an MS2 spectrum was well annotated, we manually reviewed our MS2 fragmentation pattern and compared it with records in the public database or previously measured reference standards to evaluate the correctness of the annotation. The MetaboAnalyst 5.0 platform was utilized to conduct multivariate data analysis, for PCA and OPLS-DA. The contribution of each variable to the classification was indicated by the VIP value that was calculated in the OPLS-DA model after Pareto scaling. The Student’s t-test at the univariate level was further employed to measure the significance of metabolites with VIP > 1.0. Metabolites with a p-value < 0.1 were considered as differential metabolites, while those with a p-value < 0.05 were recognized as statistically significant differential metabolites. Enrichment analysis and network analysis was performed using only the significant metabolites and significant genes using the KEGG pathway database. In conclusion, our combined omics study showed PVB-related key metabolic alterations in a compartment-specific manner. The combination of a model of PH, with specific changes in shear stress in different areas of the lung, with proteome and metabolomic data shows that particular metabolic pathways, including fatty acid absorption and purine synthesis, are altered in early PH. Such a deeper understanding of the metabolic changes in lung tissue may provide new targets for therapy and may, thereby, pave the way for new avenues in precision medicine for PH.

PMC10003324

Roxana Jijie,Emanuela Paduraru,Ira-Adeline Simionov,Caterina Faggio,Alin Ciobica,Mircea Nicoara

Effects of Single and Combined Ciprofloxacin and Lead Treatments on Zebrafish Behavior, Oxidative Stress, and Elements Content

03-03-2023

ciprofloxacin,lead,combined effects,behavior,biomarkers

Even though the toxic effects of antibiotics and heavy metals have been extensively studied in the last decades, their combined adverse impact on aquatic organisms is poorly understood. Therefore, the objective of this study was to assess the acute effects of a ciprofloxacin (Cipro) and lead (Pb) mixture on the 3D swimming behavior, acetylcholinesterase (AChE) activity, lipid peroxidation level (MDA—malondialdehyde), activity of some oxidative stress markers (SOD—superoxide dismutase and GPx—glutathione peroxidase), and the essential elements content (Cu—copper, Zn—zinc, Fe—iron, Ca—calcium, Mg—magnesium, Na—sodium and K—potassium) in the body of zebrafish (Danio rerio). For this purpose, zebrafish were exposed to environmentally relevant concentrations of Cipro, Pb, and a mixture for 96 h. The results revealed that acute exposure to Pb alone and in mixture with Cipro impaired zebrafish exploratory behavior by decreasing swimming activity and elevating freezing duration. Moreover, significant deficiencies of Ca, K, Mg, and Na contents, as well as an excess of Zn level, were observed in fish tissues after exposure to the binary mixture. Likewise, the combined treatment with Pb and Cipro inhibited the activity of AChE and increased the GPx activity and MDA level. The mixture produced more damage in all studied endpoints, while Cipro had no significant effect. The findings highlight that the simultaneous presence of antibiotics and heavy metals in the environment can pose a threat to the health of living organisms.

Effects of Single and Combined Ciprofloxacin and Lead Treatments on Zebrafish Behavior, Oxidative Stress, and Elements Content Even though the toxic effects of antibiotics and heavy metals have been extensively studied in the last decades, their combined adverse impact on aquatic organisms is poorly understood. Therefore, the objective of this study was to assess the acute effects of a ciprofloxacin (Cipro) and lead (Pb) mixture on the 3D swimming behavior, acetylcholinesterase (AChE) activity, lipid peroxidation level (MDA—malondialdehyde), activity of some oxidative stress markers (SOD—superoxide dismutase and GPx—glutathione peroxidase), and the essential elements content (Cu—copper, Zn—zinc, Fe—iron, Ca—calcium, Mg—magnesium, Na—sodium and K—potassium) in the body of zebrafish (Danio rerio). For this purpose, zebrafish were exposed to environmentally relevant concentrations of Cipro, Pb, and a mixture for 96 h. The results revealed that acute exposure to Pb alone and in mixture with Cipro impaired zebrafish exploratory behavior by decreasing swimming activity and elevating freezing duration. Moreover, significant deficiencies of Ca, K, Mg, and Na contents, as well as an excess of Zn level, were observed in fish tissues after exposure to the binary mixture. Likewise, the combined treatment with Pb and Cipro inhibited the activity of AChE and increased the GPx activity and MDA level. The mixture produced more damage in all studied endpoints, while Cipro had no significant effect. The findings highlight that the simultaneous presence of antibiotics and heavy metals in the environment can pose a threat to the health of living organisms. In recent years, a wide and increasing variety of hazardous chemical compounds has been identified in water bodies due to different anthropogenic activities, such as industrial, agricultural, domestic, and healthcare processes [1]. Both inorganic and organic contaminants, such as heavy metals [2,3], pharmaceutical substances [4,5,6,7,8], personal care products [5,8,9], agrochemicals [10], microplastics [11,12], and nanoparticles [13] are often present in surface, ground, and drinking water. The presence of these pollutants in water systems is recognized worldwide as a serious threat to aquatic ecosystems and human health, and reducing their release into the environment is a priority for international actions. Although some metals are essential elements (e.g., Fe, Na, K, Cu, Zn, Ca, and Mg) necessary for the normal biological functioning of organisms, most of these elements may be toxic even at low concentrations [14]. Thus, because of their high degree of toxicity, bioaccumulation tendency, and chemical stability, Pb, arsenic (As), cadmium (Cd), chromium (Cr), and mercury (Hg) have been included in the priority list of hazardous substances. For instance, the World Health Organization included Pb, As, Cd, and Hg within its ten chemicals of major public health concern [15]. Various studies have shown that chronic or acute Pb exposure can elicit detrimental effects on neurological, gastrointestinal, cardiovascular, hematologic, immunologic, and renal systems [16]. Despite significant progress in reducing Pb levels around the world, significant sources still exist. For example, high Pb levels ranging from 17 to 400 μg/L have been reported in Guiyu (South China), near an electronic waste area [17,18]. Concentrations of Pb in the Guangzhou segment of the Pearl River were in the 5–15 μg/L range [19,20]. Lead in amounts ranging from 32 to 3340 ppm has been measured in the bottom sediments of water bodies in the Upper Silesia region in southern Poland [21]. Rajaratnam et al. [22] evaluated Pb concentrations in the tap water of 95 new houses in the Sydney metropolitan area and found that 60% of homes tested above the Australian Drinking Water Guideline (10 μg/L) at the first draw sampling. A survey of lead content of tap water at the National Taiwan University campus revealed that approximately 10% of the samples collected showed Pb levels greater than 10 μg/L, with the highest value at 62.6 μg/L [23]. Recently, DeForest et al. [24] proposed acute and chronic biotic ligand model- (BLM) based ambient water quality criteria (AWQC) for Pb in freshwater, taking into account the influence of three water quality parameters: hardness, dissolved organic carbon, and pH. The acute toxic range was from 20 to 1000 μg/L, whereas the concentration of Pb with chronic toxicity ranged from 0.3 to 40 μg/L. It is worth highlighting that the prediction of metal toxicity in aquatic systems is mainly based on basic indicators, such as growth, reproduction, and survival, while their neurotoxicity has been rarely considered in risk assessment. Thus, it is necessary to address the neurotoxic effects induced by Pb exposure at environmentally relevant concentrations. Chen et al. [25] showed that exposure of embryos to lead acetate from 6 to 96 h post-fertilization (hpf) induces behavioral changes in zebrafish larvae (hyperactivity) and learning/memory impairments in adult zebrafish. Similar results were reported by Xu et al. [26], who found that the learning deficits produced by embryonic exposure to Pb persisted for at least three generations. Developmental Pb exposure (30 mM) significantly reduced the response rate to stimuli, inducing startle and escape behavior deficits in adult zebrafish [27]. Chronic exposure of adult zebrafish to a low concentration of lead chloride (PbCl2) induced memory deficit and abnormal exploratory behavior, characterized by elevated freezing and reduced exploration [28]. Moreover, biochemical assays revealed a reduction in AChE activity, serotonin and melatonin levels, as well as an increase in SOD activity and cortisol level in the brain in response to Pb treatment when compared with the control group. In agreement with a previous study, Zhu et al. [29] showed that Pb exposure at a concentration of 20 μg/L may enhance anxiety levels characterized by reduced locomotor activity. Li et al. [30] demonstrated that chronic exposure of adult male zebrafish to Pb at environmental concentration levels (1 μg/L, 10 μg/L, and 100 μg/L) impaired exploratory behaviors, inhibited spatial working memory, and disturbed light/dark preference. In addition, the produced effects on zebrafish locomotion were concentration-dependent and were associated with disturbed expression patterns of mRNA levels of key genes involved in neurodevelopment (gap43, syn2a, th, dat, and drd1b), neurotoxic effects (c-fos and gfap), and stress responses (tap, mt1, hsp70, and hsp90). In general, environmental contaminants do not occur alone; both inorganic and organic compounds often coexist in water bodies, affecting organisms. For example, recent studies have reported the occurrence of both heavy metals and antibiotics in the environment [31,32]. In spite of antibiotics’ toxicity to aquatic life and their possible contribution to the spread and persistence of antimicrobial resistance, there are no standards for the regulation of antibiotics discharge in water systems. For instance, the macrolide antibiotics (e.g., erythromycin, clarithromycin, and azythromycin), amoxicillin, ciprofloxacin, sulfamethoxazole, and trimethoprim have been recommended to be included in the Watch Lists from European Union monitoring (Decision 2015/495/EU of 20 March 2015, Decision 2018/840/EU of 5 June 2018, Decision 2020/1161/EU of 4 August 2020, and Decision 2022/1307/EU of 22 July 2022). Ciprofloxacin (Cipro), an antibiotic of the fluoroquinolone class, is one of the most widely prescribed antibiotics in the USA, with an annual prescription rate of 173 per 1000 beneficiaries [33]. In Europe, consumption of ciprofloxacin, expressed as DDD per 1000 inhabitants per day, accounted for 48.6% in 2017 and 50.8% in 2009 of the total quinolone amount [34]. As a result of its widespread use, it is not surprising that Cipro reached the aquatic environment. The concentration of Cipro detected in surface waters varied between 7.7 and 5528 μg/L, while in wastewater treatment plant (WWTP) effluents the antibiotic was detected up to 341 μg/L [35]. According to published results, acute and chronic exposure of zebrafish at various stages of development (embryos, larvae, and adults) to antibiotics can induce behavioral impairments, oxidative stress, and histological alterations [36,37,38,39,40]. Tissue alterations in the liver of adult zebrafish were observed after 96 h exposure to low concentration of ciprofloxacin alone and in combination with paracetamol [38]. Shen et al. [39] revealed that high doses of Cipro (156–1949 mg/L) can induce cardiovascular toxicity. In addition, when zebrafish larvae were exposed to 2.34 and 9.38 mg/L of β-diketone antibiotics (DKAs), they had a higher basal swim rate than control groups at 120 hpf in both light and light-to-dark photoperiod experiments [40]. While the zebrafish exposed to 6.25 mg/L of β-diketone antibiotics (including ofloxacin, ciprofloxacin, enrofloxacin, doxycycline, chlortetracycline, and oxytetracycline) exhibited an anxiolytic behavior, characterized by increased travel distance, time spent in the upper portion of the test tank, and line crossings, the 25 mg/L DKAs treatment led to anxiety-like behavior [36]. A recent study has demonstrated that acute exposure to antibiotics by zebrafish may result in cognitive impairment and enhanced aggression behavior [41]. On the other hand, Plhalova et al. [42] reported no significant effects on growth and no histological changes in groups with Cipro concentrations up to 3 mg/L. Results have demonstrated that metallothionein (MT) plays an important role in ameliorating the inter-cellular toxicity of metals, whereas the oxidative stress, apoptosis, tissue damage, and variations of trace element levels were identified to be involved in response to chemicals treatments [43,44,45,46]. The majority of toxicological studies have focused on effects induced by individual chemical exposure, rather than chemical mixtures. However, compared to single exposure, mixed contaminants may elicit combined toxic impacts on organisms, including additive, antagonistic, and synergistic effects. Therefore, further understanding of the joint toxic impacts of chemical mixtures is needed. For example, combined exposure to 10 mg/L Pb and paraquat triggered synergetic behaviour on ethoxyresorufin-O-deethylase (EROD), 7-benzyloxy-4-trifluoromethyl-coumarin-O-debenzyloxylase (BFCOD), glutathione-S-transferase (GST), and UDP-glucuronosyltransferase (UGT) activities in goldfish (Carassius auratus) livers [47]. Compared to the toxicities of individual metals, Cd and manganese (Mn) showed antagonistic effects, whereas the mixture of Cd + Pb, Mn + Pb, and Cd + Mn + Pb induced synergistic effects in C. elegans [48]. In contrast, an antagonistic effect on behavioral pattern was observed when co-exposing zebrafish larvae to lead and cadmium [49]. These results suggest that Pb treatment impaired locomotor activity, whereas Cd disrupted behavioral rhythms. Exposure to both Pb and decabromodiphenyl ether elicited synergistic effects on thyroid hormone levels in zebrafish [50] and impaired neuronal development in zebrafish larvae [29]. Combination treatment with Pb and repeated heat pulse has been proven to have synergistic effects on developmental neurotoxicity in zebrafish [51]. The concentration addition and independent action models are commonly used to evaluate and predict the effects of mixed contaminants [45,52]. The results have revealed that uptake of metals in a mixture with other chemicals may be suppressed or enhanced. For example, the ionic liquid M8OI suppressed Pb absorption in the fish brain [53], and Pb toxicity was ameliorated due to the competitive binding of Cd to active enzymes [43]. Meanwhile, the uptake of Cd was enhanced in the presence of Ni at concentrations above 0.1 μM [54]. A similar result was found by Miao et al. [20], who noted that titanium dioxide nanoparticles enhanced the bioconcentration of Pb, leading to the disruption of the endocrine and neuronal systems in zebrafish larvae. Moreover, the chemical structure of the organic pollutants may be altered in the presence of heavy metals, mediating their degradation or transformation. For example, by forming a Pb2+—cypermethrin complex through the CN group of insecticides [55] or an atrazine—Cd complex through five electron-donor atoms of herbicide [52], the bioavailability of chemicals may be reduced, acting together in an antagonistic manner. Consequently, to determine the impairments induced by various chemical compounds against organisms, behavioral assays (e.g., light/dark preference test, novel tank test, T-maze test, 3D locomotion test, predator avoidance test, etc.) alongside biochemical, histological, and transcriptomic assays have been successfully applied [14,28,30]. According to the literature, the frequency and severity of alterations increased with enhancing exposure time and concentration [30,39]. In addition, interest in applying 3D tracking techniques to toxicology is growing, because it can identify subtle behavioral changes that may be neglected by 2D approaches. For example, Macrì et al. [56] showed that 2D results are flawed by under- and over-reporting of behavioral differences compared with 3D data. Several 3D tracking systems have been developed by using one camera and one mirror [57], or two mirrors [58], or two cameras positioned orthogonally [14] in order to create 3D swim paths and to analyze the behavioral endpoints (e.g., total distance traveled, average velocity, turn angle, angular velocity, meandering, freezing duration, time spent in the top/bottom, etc.). Among vertebrate models, over the past few years, zebrafish (Danio rerio) have gained increasing popularity for assessing the effects of environmental contaminants due to easy maintenance and manipulation, small size, high fecundity, rapid development, embryo transparency, and high sensitivity to chemical stressors. The strength of zebrafish is their complex behavior, including learning and memory, decision making, social interaction, and aggressive responses [59,60,61]. In this study, we aimed to evaluate the combined adverse impact Cipro and Pb may induce on zebrafish behavior, oxidative stress, and body elements content. For this purpose, adult wild-type, mix-gendered zebrafish were exposed to environmentally appropriate doses of Cipro and Pb as single chemicals and as a mixture for 96 h. To the best of our knowledge, the combined toxicity induced by Pb and Cipro exposure in adult zebrafish was not previously reported. In addition, although the toxicity of these contaminants alone was previously studied in aquatic organisms, little information is available concerning their behavioral effects. The individual and joint effects of lead and ciprofloxacin on zebrafish behavior have been assessed by three-dimensional (3D) locomotion tracking. Because animal behavior is an integrated response to various biochemical and physiological processes, behavioral changes may be observed early, a short time after exposure, and at low concentrations; this can also provide a better understanding of joint toxicity between multiple contaminants. As shown in Figure 1a, exposure to Pb alone and in combination with ciprofloxacin significantly impaired zebrafish exploratory behavior by diminishing their swimming activity in the top part of the tank as compared with the control and Cipro groups. The administration of both nano-silica and reserpine [62], and of caffeine and fluoxetine alone [63], induced similar effects, decreasing zebrafish swimming activity in the upper part. In addition, a preference for staying near tank walls has been observed for zebrafish exposed to the binary mixture, known as thigmotaxis behavior. Similarly, treatment of zebrafish larvae with low concentrations of deltamethrin increased the time spent in close proximity to test tank walls [64]. In line with our results, Thi et al. [28] found that zebrafish locomotor activity and entries into the upper zone are reduced after the administration of 50 μg/L Pb, followed by a higher freezing time movement ratio. According to the literature, a longer time spent at the bottom of the tank and less time in the upper portion of the aquarium, preference for staying close to walls, and increased freezing behavior and counter-clockwise rotation illustrate a high anxiety level in zebrafish [37,65]. There are no significant differences between the control and Cipro groups during the 96 h exposure period (Figure 2a–c), which is consistent with Petersen et al.’s results [41]. Changes in the swimming activity of zebrafish have been reported after 10 days of exposure to 10 mg/L ciprofloxacin [66]. In contrast, significant differences in all investigated behavioral endpoints have been observed for treated groups with Pb alone and in combination with an antibiotic, with more pronounced effects associated with the mixture. Exposure for 72 h to Pb alone and in combination with Cipro decreased the total distance moved in the side (YZ) plane by 26% and 59%, respectively, in contrast with the control, and by 12.8% and 30%, respectively, in the top (XY) plane. In addition, the behavioral impairments induced by lead seem to ameliorate from day 3 of the treatment. Similarly, Sehonova et al. [67] reported the ability of zebrafish juveniles to adapt to enrofloxacin in a short time period. On the other hand, both acute treatments increased the immobile mean time from an average of 10% of the time for the control to an average of 12% for the Pb-exposed group and 20% of the time for the mixture-treated group, respectively. These results are in agreement with previous findings related to triclosan [68] and alarm pheromone [63] treatments, which elevated freezing behavior and reduced exploration of zebrafish. Moreover, after 6 days of exposure to Pb (5–30 μg/L) with titanium dioxide nanoparticles (0.1 mg/L), the zebrafish showed slower locomotor behavior than those from control and single-exposure groups [20]. Similarly, common carp movement has been altered by chronic exposure of Pb at lower concentrations [53]. The authors linked neurobehavioral changes with increases in neurotransmitter dopamine levels and fish brain injuries. As illustrated in Figure 2c, combined administration of Pb and Cipro during the test significantly enhanced counter-clockwise rotation. Elements, such as Ca, K, Mg, Na, Cu, Fe, and Zn, are essential for the functioning of cellular enzymes and proteins involved in many physiological and metabolic processes [46]. For example, cations, such as Ca, K, Mg and Na, are essential elements for ensuring the homeostasis of intracellular and extracellular balance in the fish organism [69,70,71,72]. As can be observed in Figure 3a–g, the mixture of Cipro and Pb interfered with the fish’s ability to efficiently uptake the essential macro-elements Ca, K, Mg, and Na. The co-administration of contaminants decreased the concentration of Ca by 36%, of K by 26.8%, of Mg by 22%, and of Na by 25%, respectively, in the zebrafish body, a fact that clearly highlights the enhanced toxicity of the binary mixture. In line with our results, You et al. [73] reported an additive toxicity between florfenicol and Cu(II)/Cd (II) on Synechocystis sp. owing to a lack of interactions between them. In the case of the group exposed to antibiotics, it was found that Ca (4963.5 ± 71.3 μg/g) and Mg (355.8 ± 12.7 μg/g) had the highest concentration in the zebrafish body, but no significant difference was registered when compared with the control group. In cells, mitochondria are responsible for Ca and Mg regulation [74,75], and in some studies, it has been reported that antibiotic substances have the capacity to improve mitochondrial function [75]. Nevertheless, Kozieł et al. demonstrated in their study that exposure to 25 µg/L of ciprofloxacin limits the cells’ capacity to uptake Ca2+ [74]. However, the effect of antibiotics is dependent not only on their dosage but also on their type [76]. Cu and Fe are essential microelements involved in hemoglobin formation [77]. At the same time, it is well known that SOD activity relies on a specific catalytic metal ion, which could be copper (Cu/ZnSOD) [78,79]. As can be seen in Figure 3e–g, concomitant exposure to Pb and Cipro alleviated the concentration of Fe by 39%, of Zn by 41.3%, and of Cu by 21.8%, but the only significant difference when compared with the control group was found for Zn. This phenomenon can be associated with an intense SOD activity, which also registered the highest value in the binary mixture-exposed group, in order to cope with the generated oxidative stress. In addition, Fe overload in fish organisms has been previously reported as a response to oxidative stress [59]. Recently, Shaw et al. [80] showed a significant increase in the hepatic content of chromium, selenium, iron, manganese, calcium, sulfur, and magnesium but depletion of zinc, copper, and cobalt in a group treated with hexavalent chromium. After exposure to Zn under different pH values for 30 days, a decrease in Fe content and increase in Cu level were recorded in fish livers [81]. In summary, significant deficiencies of Ca, K, Mg, and Na contents, as well as an excess of Zn level, were observed in fish tissues after exposure to the Pb and Cipro binary mixture. Furthermore, these changes can potentially interfere with cellular antioxidant balance and trigger oxidative damage, which can be linked to the observed zebrafish exploratory behavior impairments. Oxidative stress occurs when the sensitive balance between the generation of reactive oxygen species (ROS) and ROS scavenging is disturbed by various stressors [12,82,83,84]. It has been reported that exposure to environmental contaminants may increase the production of ROS, leading to oxidative damage [82,85]. A relationship between the imbalance in the activities of enzymatic antioxidants (e.g., GPx, SOD, CAT, etc.) and histological, behavioral, and morphological alterations upon exposure to contaminants has been reported in the literature [14,35,86]. Likewise, the alteration of acetylcholinesterase (AChE) activity has been related to behavioral impairments [87]. In our study, exposure to lead alone and in combination with ciprofloxacin induced an oxidative stress response in zebrafish and a decrease in AchE activity in the brain over the 4-day exposure period, with more pronounced alterations with mixture treatment. As shown in Figure 4, the GPx activity and MDA level increased in both Pb alone and Pb + Cipro-treated groups, whereas a significant increase in SOD activity was obtained only for zebrafish exposed to the Pb—Cipro mixture. Ciprofloxacin treatment had no effect on biomarkers studied, which is consistent with behavioral results. In agreement with our results, Ramirez et al. [35] found an augmentation of SOD, CAT, and GPx activities, MDA level, protein carbonyl, and hydroperoxide contents in zebrafish embryos at 72 and 96 hpf for the binary mixture of ciprofloxacin and paracetamol. Similarly, treatment with Pb of the bivalve (Chlamys farreri) significantly reduced SOD, CAT, and GPx activities and induced high levels of MDA content [88]. Plhalova et al. [42] reported no significant differences between the control group and ciprofloxacin-treated groups (0.7–3000 μg/L) with respect to lipid peroxidation. Moreover, acute exposure to Pb alone and in mixture with Cipro reduced AChE activity in the zebrafish brain, also reported by other researchers [28,68,89,90]. Velázquez et al. [38] indicated that binary mixtures of ciprofloxacin and paracetamol caused more damage in all investigated endpoints in contrast with Cipro treatment. Overall, our results contribute to a better understanding of the toxicity of heavy metals and antibiotics, individually and in a mixture. It can be concluded that the presence of heavy metals alone or in combination with antibiotics in water bodies may be harmful to aquatic species and their simultaneous presence may produce more damage. Cheng et al., based on the self-adaptive ability of organisms to polluted environments, hypothesized that Cd may impair defense capacity, therefore allowing more erythromycin bioaccumulation in tissues in the presence of metals [44]. However, further investigations are necessary to explain the mechanism that underlies the behavioral and biochemical responses to coexisting heavy metals and antibiotics. Lead standard solution Certipur (Pb, 1000 mg/L, 119,776), nitric acid 65% Suprapur® (HNO3, 100,441), hydrogen peroxide 30% Perhydro® (H2O2, 107,210), multi-element standard solution Certipur (111,355), acetylhiocholine iodide (ATCh, A5751), 5,5-dithio-2,2-nitrobenzoic acid (DTNB, 322,123), Bradford Reagent (B6916), Bovine Serum Albumin (A8022), ethanol EMSURE® (159,010), phosphate buffered saline (P4417), tris hydrochloride solution (T2819), Lipid Peroxidation Assay Kit (MDA, MAK085), Superoxide Dismutase Assay Kit (SOD, 19,160), and Glutathione Peroxidase Cellular Activity Assay Kit (GPx, CGP1) were bought from Merk, Darmstadt, Germany. The ciprofloxacin liquid form (Cipro, 10 mg/mL) was obtained from a local pharmacy. The product was selected to simulate a real-life exposure situation and to avoid any possible conflict of interest by ensuring the manufacturer brand remains anonymous. The wild-type adult zebrafish (Danio rerio, AB strain, 8–12 month old, mass = 0.45 ± 0.05 g, body length = 28 ± 1 mm) were obtained from a local supplier. They were maintained in 65 L glass tanks at 26 ± 1 °C with a 12 h light/12 h dark cycle (lights on at 8:00 a.m.). The fish were fed twice daily with TetraMin Tropical Flakes, receiving a daily ration of ~1% of body weight. The aquarium was equipped with trickling filters and constantly aerated. The water parameters were determined and kept constant in all aquaria during the fish housing and treatment: pH 7.28 ± 0.1, conductivity 540 ± 3 μS/cm, salinity 0.25 ± 0.1, TDS 260 ± 5 mg/L, nitrite 0.03 ± 0.005 mg/L, nitrate 2.5± 0.5 mg/L. Toxicity tests complied with OECD Guidelines for the Testing of Chemicals, Section 2: Effects on Biotic Systems, fish acute toxicity test No. 203. After acclimatization for 2 weeks, the zebrafish (n = 10 per group) were randomly separated into four groups, including a control group (fish were exposed to standard tank water), Cipro group (5 mg/L), Pb group (50 μg/L), and mixture group (5 mg/L of Cipro + 50 μg/L of Pb), as illustrated in Figure 5. The zebrafish were housed in trapezoid glass tanks (30 cm long × 16.5 cm wide × 20 high) with 5 L exposure solutions renewed daily and they were not fed 24 h prior to or during treatment. The concentration of lead and ciprofloxacin was selected based on previous studies [17,18,21,28,35,41]. In addition, the real concentration of Pb and Cipro following the single and combined treatments was determined with an atomic absorption spectrometer (HR-CS GF-AAS, ContrAA 700, Analytik Jena, Jena, Germany) following the method described by Jijie et al. [14] and with Specord 210 Plus spectrophotometer (Analytik Jena, Germany), as shown in Table 1. Briefly, the concentration of Pb and Cipro was evaluated from constructed calibration curve (y = 0.0085 + 0.0148 × for Pb and y = 0.0274 + 0.0247 × for Cipro), as shown in Figure S1 (Supplementary Materials). Three replications per sample were conducted for validating the nominal concentrations. The UV-Vis analysis revealed that there was no change in absorption bands intensities or positions from 0 to 24 h of treatments with 5 mg/L of Cipro alone or in mixture with 50 μg/L of Pb (Figure S2). Furthermore, for the mixture, within 24 h new peaks cannot be observed, indicating that the compounds did not interact with one another to form a new product. Similarly, Ding et al. [53] have shown that Pb and ionic liquid M8OI do not react within one day. In order to acclimate them to handling stress, before starting the 3D locomotion test, during 96 h the animals were gently hand-netted from their experimental tank to a temporary tank. No mortality was recorded during the experimental period. Once the behavioral testing was completed, zebrafish from the control and the exposed groups were euthanized using hypothermic shock method (2–4 °C), according to animal welfare regulations [91]. For the three-dimensional locomotion test, zebrafish (n = 10 per group) were placed individually in a temporary glass tank (30 cm long × 16.5 cm wide × 20 high) filled with 6 L of dechlorinated tap water. Then, following a 60 s habituation period, the locomotor activity was recorded with the Track3D module of EthoVisionXT 16 video tracking software (Noldus Information Technology, Wageningen, The Netherlands) for 4 min. The 3D tracking system has been described in our previous study [14]. The 3D locomotion tracking was recorded at t = 0 h (after the accommodation of animals to experimental conditions for 96 h) to set the baseline behavior of fish (presented as initial behavior), 6 h, 12 h, 24 h, 48 h, 72 h, and 96 h for each individual and each experimental condition (5 mg/L of Cipro, 50 μg/L of Pb and their mixture). In order to gain insight into the acute toxicity induced by Cipro and Pb alone and in combination, the following behavioral endpoints were analyzed: the total distance traveled (m), freezing duration (s), and counterclockwise rotation. Briefly, frozen tissues were placed into a KIMBLE Dounce tissue grinder set (Sigma) with 10 volumes of ice-cold phosphate buffered solution and then centrifuged at 5500 rpm for 15 min (4 °C). Then, the supernantants were used for evaluation of oxidative stress. On evaluation of oxidative stress, the following antioxidant enzymes were determined: SOD and GPx, as well as the lipid peroxidation (MDA) level. Activities of SOD and GPx and MDA levels were determined colorimetrically using kits (Merck, Darmstadt, Germany) following the manufacturer’s instructions. The results were normalized to the total protein content determined with the Bradford method using bovine serum albumin as standard, while MDA level was normalized as percentage of control values. AChE activity was measured according to a previously reported protocol [87]. Before analysis, all samples (n = 5 per group) were previously digested (~1 g) in a microwave-assisted pressure digestion system (TOPwave, Analytik Jena, Germany), by using a mixture of 5 mL nitric acid (HNO3 65% Suprapur, Merck, Germany) and 2 mL hydrogen peroxide (H2O2 30% Emsure, Merck, Germany). Further on, the mineralized samples were transferred in clean polyethylene flasks (50 mL volume) and diluted with ultrapure water. Calcium, potassium, magnesium, sodium, iron, and zinc were quantified by using the flame atomic absorption spectrometry (FAAS) technique. In case of copper determination, the graphite furnace atomic absorption spectrometry technique was used. All measurements were carried out by using ContrAA 700 by Analytik Jena Germany. For the calibration of the equipment, a multi-element standard solution (1000 mg L−1) was used. The methods’ accuracy was validated by using a reference material for fish muscle (ERM-BB422), certified by the EU Joint Research Center Institute for Reference Materials and Measurements. All concentrations were expressed as μg/g wet weight ± SD. Initially, the distribution of the data was evaluated for normality by the Shapiro–Wilk test. Afterward, one-way ANOVA followed by Tukey’s or Dunnett’s post-hoc tests were used, depending on the need to compare each exposure group to the control group or the mean of each column with the mean of every other column. All statistical analyses were conducted with Graph Pad Prism v.9.0 (GraphPad Software, San Diego, CA, USA). The results were presented as mean ± standard deviation (SD) and for all comparisons, p ≤ 0.05 was considered significant. Plots were generated in both Graph Pad Prism v.9.0 and OriginPro v.9.3 (2016, OriginLab Corporation, Northampton, MA, USA). In summary, the short-term exposure of adult zebrafish to Pb alone and in combination with Cipro at environmentally appropriate doses induced abnormal behavior, characterized by elevated freezing duration and reduced swimming activity. Moreover, a significant depletion in the zebrafish body content of Ca, K, Mg, and Na, as well as an augmentation of Zn, have been determined in the treated group with Pb and Cipro mixture. Likewise, the biochemical assays revealed a reduction in AChE activity in the zebrafish brain and an increase of GPx activity and MDA level in the skeletal muscle, following treatment with Pb alone and in combination with Cipro. In all investigated endpoints, the mixture treatment produced more damage, while no significant differences were measured for the Cipro group. Therefore, the chronic or acute evaluation of a single pollutant does not give a realistic view, and the combined effects of various stressors against aquatic organisms should be assessed. Future in-depth investigations are required to illuminate the mechanisms underlying single and joint toxic effects.

PMC10003331

Qiang Zong,Katrin Bundkirchen,Claudia Neunaber,Sandra Noack

Are the Properties of Bone Marrow-Derived Mesenchymal Stem Cells Influenced by Overweight and Obesity?

02-03-2023

overweight,obesity,BMSCs,proliferation,clonogenicity,surface antigen,senescence,apoptosis,differentiation

Bone marrow-derived mesenchymal stem cells (BMSCs) are promising candidates for cell-based therapies. Growing evidence has indicated that overweight/obesity can change the bone marrow microenvironment, which affects some properties of BMSCs. As the overweight/obese population rapidly increases, they will inevitably become a potential source of BMSCs for clinical application, especially when receiving autologous BMSC transplantation. Given this situation, the quality control of these cells has become particularly important. Therefore, it is urgent to characterize BMSCs isolated from overweight/obese bone marrow environments. In this review, we summarize the evidence of the effects of overweight/obesity on the biological properties of BMSCs derived from humans and animals, including proliferation, clonogenicity, surface antigen expression, senescence, apoptosis, and trilineage differentiation, as well as the underlying mechanisms. Overall, the conclusions of existing studies are not consistent. Most studies demonstrate that overweight/obesity can influence one or more characteristics of BMSCs, while the involved mechanisms are still unclear. Moreover, insufficient evidence proves that weight loss or other interventions can rescue these qualities to baseline status. Thus, further research should address these issues and prioritize developing methods to improve functions of overweight- or obesity-derived BMSCs.

Are the Properties of Bone Marrow-Derived Mesenchymal Stem Cells Influenced by Overweight and Obesity? Bone marrow-derived mesenchymal stem cells (BMSCs) are promising candidates for cell-based therapies. Growing evidence has indicated that overweight/obesity can change the bone marrow microenvironment, which affects some properties of BMSCs. As the overweight/obese population rapidly increases, they will inevitably become a potential source of BMSCs for clinical application, especially when receiving autologous BMSC transplantation. Given this situation, the quality control of these cells has become particularly important. Therefore, it is urgent to characterize BMSCs isolated from overweight/obese bone marrow environments. In this review, we summarize the evidence of the effects of overweight/obesity on the biological properties of BMSCs derived from humans and animals, including proliferation, clonogenicity, surface antigen expression, senescence, apoptosis, and trilineage differentiation, as well as the underlying mechanisms. Overall, the conclusions of existing studies are not consistent. Most studies demonstrate that overweight/obesity can influence one or more characteristics of BMSCs, while the involved mechanisms are still unclear. Moreover, insufficient evidence proves that weight loss or other interventions can rescue these qualities to baseline status. Thus, further research should address these issues and prioritize developing methods to improve functions of overweight- or obesity-derived BMSCs. Overweight and obesity are conditions in which a person’s total body weight exceeds what is considered healthy [1]. Body mass index (BMI) is widely used as an indicator to evaluate weight status. Based on BMI, adults are usually categorized as underweight (<18.5 kg/m2), normal (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), and obese (≥30 kg/m2) [2,3]. BMI percentile can be used to evaluate the overweight/obese status of children and adolescents [4]. Over the past few decades, the global prevalence of overweight/obesity has reached a pandemic level [5,6]. The World Health Organization (WHO) reported that worldwide obesity has nearly tripled since 1975 [7,8]. As troubling as these numbers are, future trends are even more alarming. Up to 45% of the global population is predicted to be overweight and 16% obese by 2050 [9]. Overweight and obesity are recognized as major global public concerns resulting in significant medical and economic burdens on nations and individuals. They increase the risk of numerous health problems including diabetes, hypertension, stroke, and heart failure [10,11,12,13,14]. It was reported that the general mortality rate increases by 30% for every increase of 5 kg/m2 in BMI among individuals with a BMI greater than 25 kg/m2 [15]. Bone marrow-derived mesenchymal stem cells (BMSCs) are one of the most attractive seed cells in tissue engineering and regenerative medicine [16,17,18]. They are capable of self-renewal and proliferate as plastic-adherent cells in vitro with fibroblast-like morphology [19]. Additionally, these cells can form colonies in vitro while retaining the potential to differentiate into multiple mesenchymal lineages, such as osteoblast, adipocyte, and chondrocyte [20]. Current studies have revealed that BMSCs are able to promote tissue repair, modulate inflammation and immunity, and support hematopoiesis [21,22,23,24,25,26,27]. Benefiting from their prominent properties and functions, a great number of clinical trials based on BMSCs are in progress around the world. With the unprecedented increase in the incidence of overweight and obesity, the overweight and obese population will inevitably become potential BMSC donors. This could be a problem as many researchers believe that the increase in unhealthy body weight can lead to abnormal properties and functions of BMSCs. Therefore, it is important to evaluate the quality of overweight/obesity-derived BMSCs to ensure their safety and efficacy. However, current findings from animal and human studies on the effects of overweight/obesity on BMSCs are inconsistent. Several studies demonstrate that excess body weight leads to undesirable proliferation, differentiation, and self-renewal of BMSCs [28,29], yet some other studies fail to provide support for these conclusions [30,31,32]. In short, the potential impact of overweight and obesity on BMSCs is still unclear and controversial. Therefore, this review summarizes the influence of overweight or obesity on human or animal BMSC biology, including proliferation, clonogenicity, surface antigen expression, senescence, apoptosis, trilineage differentiation, and the underlying mechanisms (included studies are shown in Table 1 and Table 2). It will provide researchers with more insight into the changes in the biological properties of BMSCs under overweight/obese conditions and give valuable references for subsequent clinical translation. The number of mesenchymal stem cells in the bone marrow is very low, ranging from 0.001–0.01% of nucleated cells [53]. The in vitro proliferative capability of BMSCs is very important because a high number of cells are required for clinical use. Clonogenicity is a common method to assess the self-renewal of mesenchymal stem cells (MSCs) [54]. Nowadays, colony formation efficiency is often employed to evaluate the quality of MSC preparations for preclinical studies and clinical trials [55,56]. In animal research, high-fat diet (HFD)-induced obesity best mimics the physiological functions of the obese human body [33,57]. These animals have typical features of human obesity such as central adiposity, hyperinsulinemia, and insulin resistance [58,59]. Benova et al. [48] demonstrated that the short-term proliferation ability between BMSCs from obese and lean mice is not significantly different. Wu et al. [30] found a similar result in BMSCs cultured through five passages under hypoxic conditions. However, da Silva et al. [36] observed a higher proliferative activity in BMSCs from obese mice than BMSCs from lean mice when the cells were unstimulated at baseline. In contrast, stimulation with fibroblast growth factor-2 (FGF-2, 3 ng/mL) for 48 h significantly enhances the proliferation of lean BMSCs but does not lead to a further increase in the proliferation capacity of obese BMSCs. This seems to indicate that the proliferative responses of obese BMSCs have reached a plateau, which is reasonably speculated to be associated with the long-term stimulation of the high concentration of FGF-2 caused by obesity [60,61,62]. A study has shown that the proliferative ability of human BMSCs (hBMSCs) stimulated with FGF-2 (3 ng/mL) for a long time exhibits a biphasic response—rising first and then falling [63]. Zhu et al. [64] found that a long-term high-fat diet downregulated the level of FGF-2 in mouse BMSCs. FGF-2 has been reported to promote the proliferation of BMSCs [63,65], while low-expressed FGF-2 induced by a 6-month high-fat diet did not harm the abundance and proliferative rate of BMSCs in the study of Zhu et al. [64], suggesting that BMSCs proliferation is subject to multifaceted regulatory pathways. However, Alessio et al. [42] reported that the proliferation potential of BMSCs from obese mice is impaired. The cell cycle analysis of this study also shows that obesity decreases the proportion of BMSCs in the S phase. The S phase is the period of DNA replication during cell proliferation, which occurs between the G1 and G2 phases [66]. The reduced ratio of cells in the S phase usually reflects suppressed cell proliferative capacity. Consistent with this, the levels of cell cycle inhibitors p16 and p53 proteins in obese BMSCs markedly increased compared with those in the lean BMSCs [42]. These results were bolstered by another study, in which Bi et al. [44] presented that BMSCs from female Sprague–Dawley (SD) rats with significantly increased body weight induced by 4- or 6-month HFD have a longer doubling time along with G1/G0 arrest than BMSCs from female SD rats fed a normal diet. Likewise, Tencerova et al. [38] observed inhibited proliferation capacity in obese mouse BMSCs. Furthermore, they reported that obese BMSCs exhibit attenuated colony-forming potential compared with lean BMSCs [38]. In the study of Li et al. [41], the inhibitory effect of obesity on the clonogenicity of mouse BMSCs was also noted, which can be reversed by the knockout of the interleukin 6 (IL-6) gene. However, there are still animal experiments manifesting that obesity does not interfere with the colony-forming ability of BMSCs [32,35,42,48]. To our knowledge, studies on the effects of high BMI (overweight/obesity) on the proliferation and colony-forming ability of hBMSCs are limited. Real-time cell analysis employed by Ulum et al. [28] shows that the proliferation rate of hBMSCs from donors with high BMI (BMI > 30 kg/m2) is slower than that of hBMSCs from donors with normal BMI (BMI < 25 kg/m2). In a study focusing on obesity increasing bone fragility, Tencerova et al. [29] compared obese and overweight hBMSCs with lean hBMSCs. They found that both obesity and overweight attenuate the short-term proliferation potential of hBMSCs. However, Di Bernardo et al. [52] obtained a different result in a pilot study when they determined the role of overweight on the proliferation from the aspect of a circulating signaling molecule. hBMSCs from three male donors (aged 10, 12, 13 years) were co-cultured with serum from overweight (BMI > 25 kg/m2) and healthy (BMI < 25 kg/m2) adults, which displayed a comparable proliferation rate [52]. This finding is inconsistent with the results of the study by Tencerova et al. [29], which might be attributed to the difference in sample size, culture conditions, or cell sources. As for the colony-forming ability, Tencerova et al. [29] found that the colony number of obese hBMSCs significantly decreases compared with that of lean hBMSCs, which is in line with the diminished stemness of obese hBMSCs suggested by RNA sequencing. Nevertheless, overweight was not found to be detrimental to the clonogenic potential of hBMSCs [29]. This discrepancy might reflect different bone marrow microenvironments created by overweight and obesity. In another study, McCann et al. [51] investigated hBMSCs from adult patients undergoing hip replacement surgery. Interestingly, they found that total colony area and mean colony area significantly rise with increasing BMI in all human participants. After grouping by gender, however, total colony amount and mean and total colony area are positively correlated with BMI in males but not females. Moreover, linear regression analysis reveals that BMI can strongly predict colony area and number in males. This indicates that the effect of BMI on colony-forming efficiency may be gender-specific. Therefore, it must be recognized that the adult stem cell population can be simultaneously influenced by various aspects such as gender, BMI, and age when considering hBMSC-based therapies. If necessary, any point needs to be analyzed independently. The expression of surface antigens on BMSCs reflects cellular biological functions and basic characteristics such as cell differentiation, proliferation, clonogenicity, and aging [67]. Therefore, elucidating the alteration of the surface antigen profile on BMSCs under obese/overweight conditions helps understand the underlying mechanisms of changes in cellular properties. Several studies have shown that BMSCs from animals or humans with excess weight normally express common cell surface antigens [29,36,40,42]. However, Wu et al. [30] found that obese mice have a reduced percentage of BMSCs expressing CD105 (CD: Cluster of Differentiation) and the percentage expressing platelet-derived growth factor receptor α (PDGFRα, CD140a) increased compared with lean mice. These alterations may contribute to impaired chondrogenesis of obese BMSCs [30]. In contrast, Tencerova et al. [38] demonstrated that the percentage of CD73+ and Sca1 (Stem cells antigen-1)/CD140a+ cells is decreased in obese mouse BMSC cultures, suggesting that the percentage of progenitor cell populations might have changed [68]. Picke et al. [32] found that BMSCs from obese mice express less CD90 than those from lean mice, which might be associated with increased tumor necrosis factor-α induced by obesity. Compared with wild-type BMSCs, CD90-deficient BMSCs display enhanced adipogenic but inhibited osteogenic differentiation potential [32]. The attenuated osteogenesis has been linked to the disturbed Wnt signaling pathway led by CD90 loss [32]. Moreover, CD90-depleted BMSCs have increased proliferation and cell growth but a trend toward diminished apoptosis, which illustrates that CD90 regulates the properties of BMSCs through multiple directions. In humans, Ulum et al. [28] compared hBMSCs from high-BMI (BMI > 30 kg/m2) and normal-BMI (BMI < 25 kg/m2) donors. They also found reduced CD90 expression on hBMSCs in the high BMI group. Yet these hBMSCs exhibit suppressed proliferation ability, which might be due to more molecular changes involved because the expressions of CD73, CD105, CD29, CD44, and CD166 are downregulated but CD31 is upregulated on the surface of hBMSCs from donors with high BMI [28]. By contrast, Tencerova et al. [29] found no significant differences in the expressions of CD44, CD90, and CD105 between obese or overweight patient- and lean patient-derived hBMSCs. On the other hand, obese patients have an increased number of cells expressing leptin receptor (LEPR), insulin receptor (IR), and C-X-C chemokine receptor (CXCR4) compared with lean patients. These antigens are related to cell proliferation, clonogenicity, lineage commitment, and aging [29,69,70,71]. However, no significant change was detected in the proportion of LEPR+, IR+, and CXCR4+ cells between overweight and lean participants. Therefore, differential effects of overweight and obesity on BMSCs are also reflected in the expression of surface antigens, which needs to be further studied. The influence of obesity and overweight on the aging phenotype of BMSCs is a critical issue that has not been fully clarified. Cellular senescence, a state of irreversible growth arrest, can limit the regeneration potential of MSCs [72,73]. Clinically applying senescent MSCs may not yield the expected results and even lead to undesirable consequences [74,75,76,77,78]. An animal experiment reports that HFD-induced obesity does not result in the aging phenotype of mouse BMSCs, as the number of senescence-associated β-galactosidase-positive (β-gal+) cells and levels of senescence-related markers p16 and p21 mRNA in obese BMSC cultures are similar with those in lean BMSC cultures [38]. However, most experiments still suggest that obesity accelerates the senescence of BMSCs. Alessio et al. [42] demonstrated that obese mice have a higher percentage of senescent BMSCs than normal mice. As the classic hallmarks of cellular aging [79,80], a high level of intracellular reactive oxygen species (ROS) was detected in obese BMSC cultures [42]. Moreover, obesity also upregulates the protein expression of canonical senescence makers p53 and p16 (Rb and p21 proteins unchanged) in obese BMSCs [42]. In a recent study, Li et al. [41] did not find a difference in the level of p16 mRNA between obese and control wild-type (WT) mouse BMSCs, while p53 and p21 proteins significantly increased in obese cells. Meanwhile, obesity elevates the concentration of IL-6 in the WT mouse-derived BMSC supernatant [41]. IL-6 is one of the most prominent cytokines of the senescence-associated secretory phenotype [81]. The increase in IL-6 suggests obesity-induced BMSC senescence, which might be associated with the IL-6/STAT3 pathway [41]. In another study on female SD rats, Bi et al. [44] found that higher body weight contributes to BMSC aging accompanied by high ROS levels and increases the serum level of C-X-C motif chemokine ligand 2 (CXCL2). These BMSCs exhibit a typical sign of aging that the cells remain halted at the G1 phase [82]. An in vitro experiment proves that CXCL2 can lead to BMSC senescence by enhancing oxidative stress [44]. By means of RNA sequencing, Ali et al. [47] found enrichment of MAPK and JAK–STAT target genes in BMSCs of obese ovariectomized (OVX) female mice, which are involved in cellular senescence. In humans, Di Bernardo et al. [52] investigated the potential effects of circulating factors from overweight subjects (BMI > 25 kg/m2) on the senescence process of hBMSCs. The β-galactosidase assay shows that hBMSCs treated with overweight serum have a similar senescence rate with cells treated with healthy (BMI < 25 kg/m2) serum. However, Ulum et al. [28] demonstrated that the senescence level in hBMSCs is significantly higher in high BMI (BMI > 30 kg/m2) samples than in normal BMI (BMI < 25 kg/m2) controls. In terms of morphology, they found that hBMSCs from donors with high BMI are more cubiform and larger compared with cells from donors with normal BMI [28]. Generally, senescent MSCs often exhibit enlarged or flattened morphology [82]. However, this morphological alteration under high BMI conditions has not been verified in laboratory animal models. A few animal experiments report that the overall morphology of BMSCs derived from HFD-induced obese mice and lean mice is similar, exhibiting a typical spindle-shaped phenotype [30,36]. Tencerova et al. [29] also presented that obesity can promote hBMSCs’ aging confirmed by increased senescent β-gal+ cells, higher β-gal activity, an elevated level of ROS production, and upregulated expression of senescence-associated genes and oxidative stress markers in obese cell cultures [83,84]. The senescence phenotype is characterized by enriched IR+ and LEPR+ hBMSCs and is associated with enhanced insulin signaling. This phenotype can be reversed by blocking insulin signaling in obese hBMSCs, which may become a promising treatment in suppressing obesity-induced aging. Additionally, the above studies in humans signify that aging-related changes in hBMSCs might differ between overweight and obesity. This possibility should be explored by assessing the senescence of hBMSCs derived directly from overweight subjects in future studies. Apoptosis is a primary cellular mechanism to maintain tissue homeostasis [85]. Both insufficient and excessive apoptosis can lead to a series of diseases [86]. An animal experiment conducted by de Oliveira et al. [45] shows that HFD-induced obesity has a pro-apoptotic effect on Swiss mouse-derived bone marrow cells including BMSCs. Insulin-like growth factor-1 (IGF-1) treatment significantly improves the survival of obese BMSCs, and the apoptosis rate is close to normal. However, Alessio et al. [42] found no distinct difference in the apoptotic rate of BMSCs between the control and the obese mice. This result seems to suggest that obesity does not interfere with the apoptotic process of BMSCs. Similar results were also observed in the study on rats. Following the findings of Bi et al. [44], 4-month HFD-induced significantly increased body weight does not change the percentage of apoptotic BMSCs from female SD rats. Moreover, extending HFD to 6 months still has no effect on cell apoptosis. Interestingly, a study might even indirectly suggest that the apoptosis level of BMSCs in obese mice shows a trend to decrease [32]. In humans, insufficient studies focus on the apoptotic phenotype of overweight and obese hBMSCs. Only one study compares the effect of serum from overweight (BMI > 25 kg/m2) and healthy (BMI < 25 kg/m2) individuals on hBMSCs apoptosis, but no significant difference was detected [52]. Cellular senescence and apoptosis are two possible fates of BMSCs. Based on the current research, BMSCs under obesity conditions seem to be more inclined to senescence (obesity-related cellular senescence and apoptosis are shown in Figure 1). However, it is still unknown what mechanisms drive obesity-derived BMSC senescence instead of apoptosis. The ability to differentiate into osteoblast, adipocyte, and chondrocyte in vitro is one of the most basic characteristics of BMSCs [87]. However, the trilineage differentiation potential of BMSCs under overweight and obesity conditions is also controversial. Alessio et al. [42] demonstrated that BMSCs from obese and normal mice have similar mRNA levels of osteogenic markers (i.e., osteopontin (OPN), osterix (OSX)) when proliferating in vitro. In the absence of external differentiation cues, this finding might imply that obesity does not affect the osteoblast lineage commitment of BMSCs. Additionally, undisturbed in vitro osteogenic differentiation was also observed in obese BMSCs [42]. The same result can also be acquired from the study of Li et al. [50]. Based on alkaline phosphatase (ALP) expression and the level of mineralization in vitro, no significant change is induced by obesity in the osteogenic ability of BMSCs derived from normal and OVX female mice [50]. In contrast, several animal experiments show that obesity enhances the osteogenic potential of BMSCs. Compared with control mice, Cao et al. [31] found that obese mice have an increased number and total area of alkaline phosphatase-positive colonies (CFU-ALP+) and a higher level of ALP mRNA (no significant change in alpha 1 collagen (COL1A1) and osteocalcin (OCN) mRNA levels) in BMSCs after osteoinduction in vitro. These results are associated with the increased number and proliferation ability of osteogenic progenitors [31]. Moreover, obese BMSCs also show increased mineralization capacity, measured by the increased number and area of mineralized calcium nodules [31]. However, Shu et al. [35] reported that CFU-ALP+ colony number and mRNA levels of ALP in BMSCs do not show differences between obese and lean mice. Even so, obese BMSCs still possess higher transcription levels of runt-related transcription factor 2 (RUNX2), OSX and OCN, and enhanced ability to produce calcium nodules in vitro. In another study, the increased expression of RUNX2, the master regulatory gene of osteogenesis, is substantiated at the protein level in BMSCs derived from obese Wistar rats [34]. Lv et al. [33] also found that obese mice have elevated mRNA transcripts of RUNX2 in BMSCs (no significant change in OSX and distal-less homeobox 5 (DLX5) mRNA levels) compared with normal control mice. Moreover, the number of alizarin red-stained colonies formed by obese BMSCs significantly increases after in vitro osteogenic induction [33]. The results from the level of stem progenitor cells and molecules suggest that obesity increases the ability of BMSCs to differentiate into osteoblasts. Additionally, this study also explores the role of free fatty acids (FFAs)—a critical bridge between HFD and obesity—in the differentiation of BMSCs [88]. Direct treatment of FFAs (palmitic acid and oleic acid) on lean BMSCs has no significant effect on the expressions of osteogenesis-related genes. However, lean BMSCs exposed to conditioned medium from FFA-treated adipocytes exhibit increased expressions of osteogenic genes and elevated mineralization, which is consistent with the result of osteogenesis of obese BMSCs in vitro. These findings might reveal an underlying mechanism by which HFD-induced obesity promotes the osteogenic process of BMSCs. However, several other animal studies show that obesity inhibits the osteogenic potential of BMSCs [30,37,39,44,47,48,49]. Adhikary et al. [39] demonstrated that HFD-induced obesity severely impaired the mouse BMSCs’ mineralization ability with a 20% reduction of calcium nodules. In the study of Gautam et al. [37], obesity induced a decreased number of calcium nodules, even reaching approximately 50%. The ALP activity and mRNA level of COL1A1, RUNX2, and OCN in BMSCs of obese mice are suppressed as well [37]. However, the attenuated osteogenic ability can be improved by formononetin [37]. Recently, Benova et al. [48] and Chen et al. [49] also discovered that MSDC-0602K and asiatic acid can ameliorate the osteogenic ability of obese mouse-derived BMSCs, supported by increased mineralization, ALP activity, and osteogenic gene expression. Besides demonstrating diminished in vitro mineralization of BMSCs in obese mice, Wu et al. [30] further simulated an obese environment through adding high concentrations of palmitic acid, stearic acid, and oleic acid to the differentiation medium of lean BMSCs. However, the cells display significantly increased osteogenic ability, which does not fully reproduce the in vitro differentiation potential of obese BMSCs. Moreover, the phenotypic change under FFAs treatment is not the same as the result of lean BMSCs directly stimulated by FFAs in another experiment [33]. The different compositions of FFAs and research methods might be responsible for this discrepancy. By gene ontology pathway analysis, Ali et al. [47] found that obesity downregulates the expression level of osteoblast differentiation-related genes in BMSCs of OVX female mice. As for the reason for inhibited osteogenesis under obese conditions, Wang et al. [43] demonstrated that obesity can reduce the secretion of BMSC-derived exosomes and the level of carried LncRNA H19, thereby affecting the miR-467/HoxA10 axis and ultimately inhibiting the osteogenic process. Additionally, decreased chemerin in the bone marrow of obese mice is also associated with the suppressed osteogenesis of BMSCs [46]. In humans, McCann et al. [51] found that the percentage of the number and area of CFU-ALP+ formed by hBMSCs has no relationship with BMI, irrespective of females or males. These findings might imply that the proportion and proliferation of osteogenic progenitors are not affected by BMI. Tencerova et al. [29] demonstrated that obese hBMSCs have increased osteogenic ability in vitro, evidenced by increased ALP activity, matrix mineralization, and tissue-nonspecific alkaline phosphatase (ALPL) mRNA levels. Despite that, RNA sequencing and other experiments confirm that the molecular phenotype of obese hBMSCs shifts toward committed adipogenic progenitors. In contrast, Ulum et al. [28] found that high BMI (BMI > 30 kg/m2) reduces the mineralization capacity and ALPL transcript level of hBMSCs during in vitro osteoinduction. The abnormal osteogenesis is associated with elevated endoplasmic reticulum stress (ERS) and impaired unfolded protein response [28]. The administration of ERS inhibitors tauroursodeoxycholic acid (TUDCA) and 4-phenylbutyrate (4-PBA) can partially rescue osteogenic ability [28]. Compared with lean participants, Tencerova et al. did not find a significant change in mineralized nodule formation, ALP activity, and ALPL mRNA level of hBMSCs in overweight participants [29]. Nevertheless, after comparing hBMSCs treated by overweight (BMI > 25 kg/m2) and healthy (BMI < 25 kg/m2) serum, Di Bernardo et al. [52] believed that circulating signaling molecules from overweight serum partially damage osteogenic differentiation of BMSCs via changing the expression pattern of osteogenic genes (i.e., OPN and OSX), even though no significant difference was detected in the mineralized matrix. Alessio et al. [42] demonstrated that the ability of obese BMSCs to differentiate into adipocytes in vitro is comparable with the cells from normal mice. Moreover, they also found that the expressions of adipogenic markers lipoprotein lipase and peroxisome proliferator-activated receptor γ (PPARγ) are not significantly changed in proliferating obese BMSCs, suggesting unaffected adipogenic lineage commitment under obesity status [42]. However, Cortez et al. [34] found that obesity downregulates the protein level of PPARγ in BMSCs of obese Wistar rats, which was considered to be associated with increased NF-κB expression. Likewise, the study by Lv et al. [33] also shows that obese mice have dramatically reduced mRNA and protein expressions of PPARγ in BMSCs compared with control mice. Moreover, the expression of preadipocyte factor-1 (PREF-1) mRNA is downregulated as well. Interestingly, the number of colonies stained by Oil Red O (ORO) in their differentiation experiments is not altered by obesity [33]. This discrepancy might indicate that inhibited adipogenic differentiation under obesity is from the molecular level instead of the stem progenitor cell level. Additionally, they also explored the direct and indirect effects of FFAs (palmitic acid and oleic acid) on the adipogenesis of BMSCs from mice [33]. Lean BMSCs directly treated with FFAs only exhibit decreased mRNA expression of PPARγ, yet the expressions of adipogenesis-related genes (PPARγ, CCAAT enhancer binding protein α (C/EBPα), and PREF-1) are suppressed in lean BMSCs when exposed to conditioned medium from FFA-treated adipocytes. Combined with the previously mentioned effects of FFAs on osteogenesis-related genes, obesity may regulate the differentiation of BMSCs through factors secreted by FFA-treated adipocytes [33]. In another study, Wu et al. [30] found that BMSCs from obese mice produce less fat in vitro than cells from lean mice. They also described the change in adipogenesis of lean BMSCs treated by increased FFAs (palmitic acid, stearic acid, and oleic acid). A high concentration of FFAs enhances the adipogenic ability of lean BMSCs, in disagreement with the findings of Lv et al. [30,33]. Culture methods might explain the inconsistent trend. In female SD rats, impaired adipogenesis of BMSCs induced by excess weight was also observed by Bi et al. [44], which is related to the upregulation of serum CXCL2. Further in vitro mechanism analysis shows that CXCL2 inhibits the adipogenic ability of BMSCs through Rac1 activation [44]. Nonetheless, some studies do not support the above conclusions and present opposite results. For instance, Adhikary et al. [39] demonstrated that obesity increases the fat production of mouse BMSCs after induction in vitro. At the molecular level, Tencerova et al. [38] found upregulated mRNA levels of adipogenic genes (e.g., PPARγ, leptin (LEP), adiponectin) in BMSCs of obese mice compared with BMSCs of lean mice, which indicates that obesity drives BMSCs toward adipogenic lineage commitment [38]. These phenotypes have been reproduced in several animal studies [35,37,48,49]. Furthermore, MSDC-0602K and asiatic acid contribute to the inhibition of enhanced adipogenesis induced by obesity [48,49]. In humans, Tencerova et al. [29] demonstrated that obesity enhances the in vitro adipogenesis of hBMSCs and shifts the fate of these cells towards adipocytic progenitors. These phenotypes associate with the enrichment of IR+ and LEPR+ cells which have high adipocyte differentiation capacity. In contrast, Ulum et al. [28] observed almost normal in vitro adipogenesis in BMSCs from donors with high BMI (BMI > 30 kg/m2), and no clear correlation exists between increasing BMI and adipogenic potential. Yet the change in mRNA levels of adipogenic genes (e.g., PPARγ, LEP) during differentiation proves a relative defect of high-BMI hBMSCs in adipogenesis [28]. TUDCA and 4-PBA are found to facilitate adipogenic differentiation [28]. Compared with hBMSCs of lean donors, Tencerova et al. [29] proposed that hBMSCs of overweight donors have similar in vitro adipogenic ability. However, Di Bernardo et al. [52] showed that overweight serum (BMI > 25 kg/m2) enhances the adipogenic potential of BMSCs as evidenced by increased mature adipocytes and upregulated adipogenesis-related markers (e.g., PPARγ, C/EBPα). SRY-box transcription factor 9 (SOX9) is the critical regulator committing BMSCs to the chondrogenic lineage. Compared with low diet-fed mice, Shu et al. [35] demonstrated that the SOX9 mRNA level of BMSCs increases (no significant change in type II collagen mRNA level) in HFD-induced obese mice. However, Lv et al. [33] found that the mRNA level of SOX9 in BMSCs is not significantly different between normal control and obese mice. Interestingly, the expression of SOX9 mRNA in BMSCs of lean mice is also not changed after being directly treated by FFAs (palmitic acid and oleic acid), while conditioned medium from FFA-treated adipocytes upregulates SOX9 expression in lean BMSCs [33]. In another study, Alessio et al. [42] did not find significant effects of obesity on the protein levels of chondrogenic markers (e.g., aggrecan) and in vitro chondrogenesis of BMSCs in mice. By comparison, Wu et al. [30] proposed that obesity inhibits the chondrogenic ability of mouse BMSCs in vitro, exhibiting a reduced glycosaminoglycan (GAG)/DNA ratio and production of GAGs and type II collagen. The findings might imply that obesity limits the application of BMSCs in cartilage repair. Additionally, Wu et al. [30] also confirmed no impact of FFAs (palmitic acid, stearic acid, and oleic acid) on the chondrogenic property in vitro of BMSCs harvested from lean mice. In contrast to animal study, there are no data for chondrogenesis of hBMSCs under overweight/obese status, which are required in the future. In this review, the effects of overweight and obesity on the proliferation, clonogenicity, surface antigen expression, senescence, apoptosis, and trilineage differentiation of BMSCs were summarized. Currently, more evidence originates from HFD-induced obese animal models. The results, however, are inconsistent partly due to different methodological approaches. Likewise, different reports also exist in studies on human BMSCs. The reasons may come from overweight or obesity itself and interference from other comorbidities. Moreover, animal models cannot fully capture the complex pathophysiological environment of the human body. Therefore, it is difficult to identify the exact mechanisms underlying the phenotypes. Although the positive impacts of overweight and obesity on BMSCs in some respects cannot be completely denied, their side effects are still an inevitable huge challenge for future clinical applications. Thus, rigorous evaluation is needed for BMSCs from overweight and obese donors to minimize the impact of unexpected consequences, and allogeneic BMSC therapies might be better for overweight and obese patients. In addition, there is insufficient research to explore how to reverse the unhealthy state of BMSCs caused by overweight and obesity. In other words, it is urgent to elucidate whether weight loss or ameliorating obesity-related metabolic disorders can improve the functions of BMSCs. Therefore, more high-quality research and evidence are required to further understand the influence of overweight and obesity on the properties of BMSCs, optimize BMSC products, and develop new treatment strategies.

PMC10003333

Dorota Wronka,Anna Karlik,Julia O. Misiorek,Lukasz Przybyl

What the Gut Tells the Brain—Is There a Link between Microbiota and Huntington’s Disease?

24-02-2023

Huntington’s disease,neurodegeneration,gastrointestinal microbiome,gut-brain axis,dysbiosis,immune

The human intestinal microbiota is a diverse and dynamic microenvironment that forms a complex, bi-directional relationship with the host. The microbiome takes part in the digestion of food and the generation of crucial nutrients such as short chain fatty acids (SCFA), but is also impacts the host’s metabolism, immune system, and even brain functions. Due to its indispensable role, microbiota has been implicated in both the maintenance of health and the pathogenesis of many diseases. Dysbiosis in the gut microbiota has already been implicated in many neurodegenerative diseases such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). However, not much is known about the microbiome composition and its interactions in Huntington’s disease (HD). This dominantly heritable, incurable neurodegenerative disease is caused by the expansion of CAG trinucleotide repeats in the huntingtin gene (HTT). As a result, toxic RNA and mutant protein (mHTT), rich in polyglutamine (polyQ), accumulate particularly in the brain, leading to its impaired functions. Interestingly, recent studies indicated that mHTT is also widely expressed in the intestines and could possibly interact with the microbiota, affecting the progression of HD. Several studies have aimed so far to screen the microbiota composition in mouse models of HD and find out whether observed microbiome dysbiosis could affect the functions of the HD brain. This review summarizes ongoing research in the HD field and highlights the essential role of the intestine-brain axis in HD pathogenesis and progression. The review also puts a strong emphasis on indicating microbiome composition as a future target in the urgently needed therapy for this still incurable disease.

What the Gut Tells the Brain—Is There a Link between Microbiota and Huntington’s Disease? The human intestinal microbiota is a diverse and dynamic microenvironment that forms a complex, bi-directional relationship with the host. The microbiome takes part in the digestion of food and the generation of crucial nutrients such as short chain fatty acids (SCFA), but is also impacts the host’s metabolism, immune system, and even brain functions. Due to its indispensable role, microbiota has been implicated in both the maintenance of health and the pathogenesis of many diseases. Dysbiosis in the gut microbiota has already been implicated in many neurodegenerative diseases such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). However, not much is known about the microbiome composition and its interactions in Huntington’s disease (HD). This dominantly heritable, incurable neurodegenerative disease is caused by the expansion of CAG trinucleotide repeats in the huntingtin gene (HTT). As a result, toxic RNA and mutant protein (mHTT), rich in polyglutamine (polyQ), accumulate particularly in the brain, leading to its impaired functions. Interestingly, recent studies indicated that mHTT is also widely expressed in the intestines and could possibly interact with the microbiota, affecting the progression of HD. Several studies have aimed so far to screen the microbiota composition in mouse models of HD and find out whether observed microbiome dysbiosis could affect the functions of the HD brain. This review summarizes ongoing research in the HD field and highlights the essential role of the intestine-brain axis in HD pathogenesis and progression. The review also puts a strong emphasis on indicating microbiome composition as a future target in the urgently needed therapy for this still incurable disease. The intestinal microbiome is the largest and most active group of microorganisms in the human body. It plays an essential role in health and disease, but due to its complexity, it is challenging to elucidate the specific interactions between the bacterial species and the impact on host metabolism. The large intestine (colon) is the main place inhabited by microbiota. It is built up by several tissue types, including lumen-facing colonocytes that form the inner epithelial layer. A healthy microbiome is advantageous to the host due to its ability to digest various large molecules, like long plant-derived polysaccharides, into smaller nutrients, like short chain fatty acids (SCFA), that can be absorbed and utilized by the host. It also produces various other molecules, such as amino acids, vitamins, and neurotransmitters, that contribute to the host’s health [1,2]. Over 1000 different bacterial species colonize the human gut, the vast majority of which have yet to be functionally characterized. The microbiota composition is dynamic and influenced by a variety of environmental factors such as diet, physical activity, host genetics, age, and antibiotic treatment, all of which contribute to the great diversity observed in healthy individuals. It is thus a challenge to accurately characterize a healthy microbiome [3]. We took a closer look at several large-scale studies that point to the genera Bacteroides and Clostridium as being the most prevalent, with Clostridium being less abundant than Bacteroides in the human intestine. Several genera, including Bifidobacterium, Eubacterium, Lactobacillus, Streptococcus, and Escherichia, were also present but in much lower abundance [3]. Determining a clear definition of a “healthy” microbiome is challenging, and many various factors need to be considered. The microbiome composition is dependent on a multitude of factors that may seem insignificant at first glance. In 2010, studies conducted by the MetaHIT consortium made an attempt to quantify microbiome diversity. According to the obtained results, there are 3.3 million non-redundant genes in the human gut microbiome [4], however, it had been known until early 2000s that the human genome consists of about 22,000 genes [5]. Further research confirms that the diversity of the microbiome is enormous between individuals and can differ by up to 90% in terms of microbiome localization (e.g., those found on the hands vs. those present in the gut) [6,7]. These findings drive scientists and physicians towards developing a highly personalized treatment plan. The profile and microbiota composition changes with the host’s lifespan, starting from embryos which were thought to be sterile till now. The microbiota colonizes newborns’ intestines, but studies have also revealed the microbiome’s presence in semen, placenta, amniotic fluid, umbilical cord blood, and meconium [8]. Moreover, factors such as delivery and feeding methods are essential for microbiota composition in infants and adults. Further, when children start to ingest solid food, their intestinal microbiome becomes more diversified, and during puberty, the release of sex hormones also contributes to microbiome maturation [9]. Next, diversification of the microbiome occurs naturally with the physiological development of the organism, i.e., the increase in length and volume of the intestines provides the microbiome with appropriate niches. Numerous studies indicate that there is a correlation between aging and microbiome composition. In 2011, a pioneering study was conducted to compare the composition of the microbiome in fecal samples from people aged 64 to 102 (study group) and young adults with an average age of 36 (control group). The results showed that the “core” microbiome—defined as the specific species found in the microbiome of at least 50% of study participants—was significantly different between the groups [10,11]. So far, the main function of the intestinal microbiome has been identified as maintaining body homeostasis. Researchers emphasize that despite the fact that technological progress is at a high level, the individual composition of the microbiome, functional characteristics, or interactions between the host and microbes have not yet been established [12]. Data collected by the Human Microbiome Project [13,14] and MetaHIT [4,15] report that 2776 species of prokaryotic microorganisms isolated from human feces have been identified (data for 2019) [16]. They have been classified into 11 different phyla, including Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes, which make up over 90% of the microbiome, [15,17,18], while Fusobacteria and Verrucomicrobia are present in trace amounts [19]. As mentioned earlier, microbiota are essential for the proper function and homeostasis of the intestines. Interactions between gut colonocytes, immune cells, and microbiota are heavily involved in shaping the immune response throughout the body [20]. In support of this, gut microbiota transplants from healthy individuals have been found to alleviate symptoms and reduce inflammation in disorders like ulcerative colitis, irritable bowel syndrome (IBS), and hepatic encephalopathy [21,22]. Key end products of microbial fermentation in the large intestine are short chain fatty acids. They are saturated carboxylic acids containing less than six carbons in their chain structure. The main sources of SCFAs are dietary macromolecules, especially fiber-rich plant-derived polysaccharides that are indigestible to humans due to the lack of enzymes required for breaking the glycosidic bonds. Thus, they are available to microbes in the intestinal lumen, which ferment them and make them available to the host. SCFAs are transported into the colonic epithelial cells by solute transporters or by simple diffusion across the membranes [23]. 95% of the total SCFAs in the human gut are acetate, propionate, and butyrate, and their levels are largely dependent on the diet and the amount of fiber, which affect the microbiota composition. The main species involved in the production of acetate are Akkermansia muciniphila, Bacteroidetes spp., and Prevetolla spp. Propionate is mostly produced by Bacteroidetes and Firmicutes, with the latter also producing butyrate. SCFAs are an important energy source for colonocytes and hepatocytes, but they also enter the systemic circulation and act as signaling molecules to exert a variety of regulatory functions. The presence of SCFAs is closely linked to gut integrity, not only through increased expression of tight junction (TJ) proteins but also through modulation of the host immune system. They act as ligands for G-protein-coupled receptors (GPR), their main targets being GPR43 and GPR41, also called free fatty acid receptor-2 (FFAR2) and free fatty acid receptor-3 (FFAR3), respectively. It has also been reported that butyrate can interact with GPR109/HCA2 (hydroxycarboxylic acid receptor 2). These receptors are involved in the glucose metabolism, lipid regulation, and gut homeostasis, as well as being expressed on immune cells, where they can influence the inflammation. Indeed, acetate has been implicated in resolving enteritis through GPR43 signaling [24]. Propionate, butyrate, and valerate can influence gene transcription by inhibiting histone deacetylase (HDAC) and thus making chromatin more accessible to transcription factors. Butyrate has been shown to be a potent suppressor of CD4+ T cell activation, acting through GPR43 and HDAC inhibition to decrease proliferation and production of proinflammatory cytokines (IFN-γ, IL-17) [25,26]. Studies show that butyrate-mediated inhibition of class II HDAC in the gut CD4+ T cells epigenetically induces the transcription of genes responsible for regulatory T cell (Treg) function [27]. There are many examples of the anti-inflammatory roles of SCFAs, but some studies report a dual effect, inducing both Treg and cytotoxic effector T cells, which points out the need for further studies [23]. Importantly, SCFAs can also cross the blood-brain barrier and affect the brain, which renders them as a potential target in neuroinflammatory diseases [20]. Supplementation of sodium butyrate has been tested on the R6/2 mouse model of HD, yielding positive results. When compared to untreated controls, the supplemented group showed improved motor performance, increased brain weight, and decreased striatal neuronal atrophy. However, sodium butyrate supplementation had no effect on the formation of mutant huntingtin (mHTT) aggregates or weight loss [28]. The study conducted on the YAC128 mouse HD model has also shown a beneficial effect of sodium butyrate supplementation, as the treated group displayed improved learning and motor skills, as well as improved cortical energy levels and increased histone 3 acetylation, suggesting that butyrate acting as an HDAC inhibitor can improve mitochondrial and transcriptional dysfunctions present in HD [29]. Tryptophan is an essential amino acid, since in mammals it is mainly derived from diet and used for protein synthesis or converted through two main pathways: serotonin or kynurenine. In the body, there are two pools of serotonin: the brain and the gut. In the brain, serotonin is synthesized in the midbrain by neurons of the raphe nucleus, although the vast majority of serotonin is produced in the gut and can impact the brain through the stimulation of the vagus nerve. Other microbial metabolites, such as butyrate, can also impact serotonin production by stimulating the activity of the tryptophan hydroxylase 1 (TPH1) enzyme. The serotonin pathway can also lead to the synthesis of melatonin, which regulates the biological rhythm and can have antioxidant and anti-inflammatory effects [30]. The kynurenine pathway utilizes the vast majority of available tryptophan and leads to the synthesis of NAD+, which is essential for the proper functioning of the cells. There are two enzymes responsible for the conversion of tryptophan into kynurenine: IDO1 and IDO2. The IDO1 enzyme has been implicated as a key molecule regulating the host-microbiome symbiotic relationship and immune responses. L-kynurenine acts as a ligand for the aryl hydrocarbon receptor (AhR), which is expressed in lymphoid tissues and has been linked to promoting Treg development in the periphery, thus stimulating homeostasis and immune tolerance. AhR signaling is also responsible for promoting IL-22 expression in gut-resident type 3 innate lymphoid cells (ILC3) [31]. There are two major metabolites synthesized along this pathway that have neuroactive properties: kynurenic acid (KYNA) and quinolinic acid (QUIN). KYNA has a neuroprotective function and is mainly produced by astrocytes, while QUIN has neurotoxic effects and is synthesized by microglia. The presence of IFN-γ and a proinflammatory environment has been found to promote QUIN production and skew the balance towards neurotoxicity. Additionally, the gut microbiome can metabolize tryptophan along the indole pathway. Escherichia coli, Clostridium spp., and Bacteroides spp. are known to utilize this pathway. About 5% of ingested tryptophan is used by microbes for a variety of physiological processes, like biofilm formation, drug resistance, virulence, and others, which are required for the maintenance of a variable microbial community, but indole and its derivatives also influence the host [30,32]. Similar to kynurenine, several indole derivatives can act as ligands for AhR and have been linked to promoting IL-22 expression. A study has shown that regulation of gut IL-22 expression by indole-3-aldehyde allows for the survival of a varied microbial community while providing resistance to opportunistic fungi (C. albicans) infection [31]. The gut-brain axis is the main link between the digestive tract and the central nervous system (CNS). It is a specific two-way communication system consisting of neural pathways such as the enteric nervous system (ENS), the sympathetic and spinal vagus nerves, and the humoral pathways involving cytokines, hormones, and neuropeptides [33]. The factors regulating the work of the axis include cortisol, SCFAs, neurotransmitters, neuromodulators, and the intestinal microbiota, which has been recognized relatively recently and is still gaining popularity. For a long time, the gut-brain axis has been known to play a role in maintaining homeostasis in the body. Disturbances of the brain-gut axis are believed to lead to systemic disorders, such as dysregulation of the intestinal system and CNS disorders, e.g., depression [34,35]. The direct impact of the microbiome on the CNS is still poorly understood. The gut microbiome is known to produce neurotransmitters such as gamma-aminobutyric acid (GABA), histamine, dopamine, norepinephrine, and serotonin, as well as most likely other neuroactive molecules [16]. The ENS is the internal nervous system of the gastrointestinal tract, where neurons organized in microarrays enable modulation of gastrointestinal function independently from the CNS, although the systems are interconnected and interact with each other [36]. This combination is also believed to allow the neurodegenerative diseases to progress. In 80% of individuals affected by Parkinson’s disease, the symptoms of neurodegeneration were preceded by digestive system symptoms. It has been suggested that alpha-synucleopathy of the gastrointestinal nervous system is an early indicator of Parkinson’s disease. The regular expression of the APP gene in the ENS indicates that it is also involved in the pathogenesis of Alzheimer’s disease [37,38]. Two of the most prevalent neurodegenerative diseases are Parkinson’s disease (PD) and Alzheimer’s disease (AD), with the latter being more common. They are both progressive and associated with advanced age, but their exact causes are not fully understood, although it is believed that a combination of both genetic and environmental factors play a role in their development and progression. AD is mostly associated with memory loss, disorientation, and behavioral issues. In the brain, there is a progressive loss of neurons and the formation of amyloid plaques and neurofibrillary tangles originating from the amyloid-beta (Aβ) precursor protein (APP). PD is characterized by abnormal accumulation and aggregation of alpha-synuclein in the form of Lewy bodies and loss of dopaminergic neurons in the substantia nigra, which causes dopamine deficiency. The most common motor symptoms are tremors, stiffness, bradykinesia, and loss of coordination, with accompanying cognitive disorders such as depression, anxiety, and apathy [39,40]. The composition of the intestinal microbiota is not only important for maintaining the proper health of the body but can also affect the physiological, behavioral, and cognitive functions of the brain. There is ample evidence for differences in the microbiome between healthy individuals and PD patients. Patients suffering from PD were characterized by a reduced presence of Prevotellaceae bacteria and an increased number of Enterobacteriaceae bacteria. Currently, it is difficult to clearly define the role of SCFAs in the pathogenesis of neurodegenerative diseases. However, the vast majority of publications indicate pathological SCFA activity in PD patients. Studies in mice overexpressing alpha-synuclein demonstrate the effect of a microbial-free environment on the elimination of the PD phenotype, and oral feeding of SCFAs to the same mice restores the neuropathology associated with PD. Counterintuitively, SCFA administration to patients increases motor dysfunction and inflammation [41,42,43]. According to a study published in 2019, bacteria from the Prevotellaceae family have been found to provide high levels of health-promoting neuroactive SCFAs, which in turn contribute to a healthy environment in the gut [44]. Decreased Prevotella abundance has also been linked to multiple sclerosis (MS), type 1 diabetes, and autism spectrum disorders. Furthermore, the presence of Prevotella is significantly influenced by a plant-based diet. Increased abundance of Lactobacillus has been associated with type 2 diabetes and constipation, suggesting that the prognostic value of Lactobacillus is not specific to PD. Multiple bacterial taxa have been reported to be altered in individuals with PD. Potential interactions between them indicate that the effects of altered gut microbiota in PD may be the result of many complex cascades of events within the entire gut microbiota as well as relationships with the host [45]. Recent results suggest a strong link between the pathogenesis of AD and intestinal microbiota dysfunctions. Studies conducted on the ADLPAPT mouse model of AD show that changes in the composition of the intestinal microflora led to a loss of intestinal epithelial integrity, which in turn caused systemic inflammation. Intestinal abnormalities coincided with Aβ deposition, Tau protein pathology, progressive gliosis, and cognitive impairment in the animals. It was also noted that the transplantation of microbiota from healthy animals into animals suffering from AD significantly attenuated the progression of AD pathogenesis [46]. A number of studies indicate significant changes in the composition of the gut microbiota during the course of AD. There was an increase in Firmicutes/Bacteroidetes and a decrease in Actinobacteria and SCFA-producing bacteria in AD mice [47,48]. A large body of research supports the idea that the gut microbiome in mouse models of AD is less diverse than in wild type (WT) mice [48,49,50,51,52]. Some association has also been noted between the presence of butyrate- and lactate-producing bacteria. Furthermore, a decrease in the number of butyrate-producing Faecalibacterium and an increase in the number of lactate-producing bacteria of the Bifidobacterium family were found using the sequencing of 16S rRNA from stool samples [50]. Metagenomic studies have proven the relationship between Lachnospiraceae and type 2 diabetes. The aforementioned family of bacteria contributes to the development of diabetes, which, along with insulin resistance, is one of the risk factors for AD [53,54,55]. Functional studies show that Pseudomonas aeruginosa infection can increase endothelial Tau phosphorylation and permeability, a common pathophysiological mechanism in the genesis of Alzheimer’s disease [56,57]. To date, little has been established about the interactions between pathogenic and non-pathogenic Pseudomonas strains in the bodies of patients with AD. Future research should focus on further understanding the role of specific bacterial clusters in the gut microbiome in the pathogenesis of AD [58]. A study where the young WT mice received a gut microbiota transplant from old AD mice has shown that this intervention significantly impaired the recovery from a traumatic brain injury. The study has also shown increased activation of microglia and macrophages and reduced motor recovery. In addition, there was a higher relative count of Muribaculum bacteria and a decrease in Lactobacillus johnsonii in WT mice transplanted with a microbiome derived from old AD mice. Another study confirms that the microflora derived from AD mice has a significant effect on the deterioration of the neurological response [59]. The expansion of microsatellite repeats is the cause of several neurodegenerative diseases. They are usually caused by replication errors such as polymerase dissociation or arrest, or sliding of the 5′ and or 3′ ends of the Okazaki fragment, which results in the formation of a hairpin structure [60,61]. Neurodegenerative diseases that are classified as trinucleotide repeat expansion disorders (TREDs) are caused by the repetition of the CNG sequence (where N is one of the 4 nucleotides) in certain genes. These disorders can further be subclassified as PolyQ (where the repeated sequence CAG encodes glutamine), like Huntington’s disease (HD), and Spinocerebellar Ataxia types 1, 2, 3, 6, 7, 12, 17, and non-PolyQ (where other triplets are repeated), like myotonic dystrophy (DM) or Friedreich’s ataxia (FRDA) [62,63]. Huntington’s disease is a rare disorder of the CNS. It affects 5–10 in 100,000 people [64]. It is the most common disorder in Europe and USA, and the least in Asia [65,66,67]. HD symptoms include uncontrolled body movements, weight loss, facial grimaces, psychological disorders, personality changes, and apathy. First non-specific symptoms can start 10 years before full manifestation of HD, which usually occurs between 35 and 40 years of age. The disease can also affect juveniles, but it is extremely rare in patients under the age of 10 and over the age of 70. The life expectancy after first symptoms is 15–20 years, with the most common causes of death being aspiration pneumonia, heart disease, and suicide [68,69,70]. The mutation that causes HD is located in the first exon of the HTT gene and is inherited in an autosomal dominant manner. In healthy individuals, the first exon contains between 10 and 35 CAG repeats, and the disease severity varies depending on the number of repeats: 27–35 repeats do not cause the disease but increase the probability of HD manifestation in progeny; 36–38 repeats cause the disease with incomplete penetrance; and more than 39 repeats cause the disease with complete penetrance, where the first symptoms occur in patients at the age of 40–55. More than 60 repeats cause the juvenile form, where the first symptoms occur before the age of 21 [71]. This specific mutation in HTT leads to the expression of mutant HTT (mHTT) protein, which tends to form intracellular insoluble aggregates that are the pathologic hallmark of HD [72]. The longer the polyQ repeats, the more aggregates it forms. In the brain, the disease pathology is linked to neuronal loss in the striatum, which is responsible for control of motor functions and the reward center. Medium spiny neurons make up the structure of the striatum, and these cells are mainly affected by pathogenic mHTT aggregates, which lead to neuronal loss and secondary gliosis. The other hallmarks of HD pathology are weight loss, gastritis, esophagitis, and nutritional deficiencies, all of which point to a strong link with dysfunction of the digestive tract. mHTT has been found to be expressed in the majority of tissues, including the gastrointestinal tract. Interestingly, studies performed on mouse models have shown that mHTT forms aggregates in the enteric nervous system even before neurological and motoric symptoms appear. It has also been reported that HD affects the functions of the gastrointestinal (GI) system through impaired gut motility, diarrhea, and malabsorption of food, and even influences the gut anatomy by reducing mucosal thickness and villus length, as well as the loss of various neuropeptides that stimulate or inhibit gut motility [73]. There are also pathological changes in gene transcription—mHTT aggregates have been found to interact with several proteins involved in various transcriptional pathways. They have been found to interact with specificity protein 1 (SP1), CREB-binding protein (CBP), peroxisome proliferator-activated receptor-γ coactivator 1α (PGC1α), Nuclear factor κ light-chain-enhancer of activated B cells (NF-κB), and Repressor element 1 (RE1)-silencing transcription factor (REST) [74]. Altered transcription in HD is also linked to mitochondrial dysfunction. Diminished transcription of PGC1α negatively impacts energy metabolism and mitochondrial biogenesis. The mHTT has also been found to have a strong association with the translocase of mitochondrial inner membrane 23 (TIM23) complex, which impairs protein import and disrupts mitochondrial function [74,75,76]. Chronic inflammation is a hallmark of HD. Inflammatory responses predate motor and psychiatric symptoms, suggesting that chronic inflammation contributes to disease progression. mHTT is highly expressed in immune cells, and its aggregates have been found to have a proinflammatory effect [77]. Even in premanifest patients, peripheral inflammation is characterized by elevated plasma levels of IL-6, and IL-8, IL-4, IL-10, and TNF-α levels rise as the disease progresses. The increase of both IL-6 and IL-8 in the early stages suggests, that it is the innate immunity that drives the initial immunopathology in HD. Indeed, monocytes, macrophages, and microglia isolated from HD patients were found to be hyperreactive to stimulation [78]. The mHTT has been found to drive up the release of IL-6 by upregulating the NF-κB pathway in mice [79]. Interestingly, a study has shown that the presence of mHTT does not directly impact the function of T cells, as their frequencies and functions did not differ from healthy controls [80]. Central inflammation in HD is characterized by chronic activation of microglia and astrocytes. Microglia are the primary mediators of neuroinflammation and in their activated state they release proinflammatory cytokines, such as IL-6, IL-1β, and TNF-α, as well as cytotoxic factors, such as reactive oxygen species (ROS), nitric oxide (NO) and QUIN. Prolonged microglial activation can lead to chronic neuroinflammation and tissue damage [81]. The number of activated microglial cells has been shown to positively correlate with the degree of neuronal loss in the striatum and cortex [82]. It has also been found that activation of microglia is present in very early stages of disease prior to the onset of symptoms [83]. Unlike microglia, the activation of astrocytes occurs in later stages of disease, when neurodegeneration is already present [81]. Reactive astrocytes can contribute to the proinflammatory environment through the production of pro-inflammatory cytokines, such as IL-12 and TNF-α; however, they can also contribute to neuroprotection by expressing anti-inflammatory cytokines, such as IL-10 and TGF-β [84]. Several studies have found a link between T helper 17 (Th17) cells and immunopathology in HD. In premanifest gene expansion carriers, it has been found that Th17.1 cells are activated while the number of Tregs is diminished. IL-17 is a proinflammatory cytokine that plays a role in communication between immune cells and tissue. In animal models, it has been shown to interact with endothelial cells, which induces the breakdown of the blood-brain barrier. The presence of IL-17 in cerebrospinal fluid (CSF) activates microglia, astrocytes, and oligodendrocytes, causing neuroinflammation. Early therapeutic intervention targeting Th17 cells might be beneficial and delay the onset of symptoms [85]. HD—mouse model studies There are several commercially available mouse models of HD. They differ in the genetic background, the structure of the transgene, and the disease phenotype. The most commonly used lines are R6/1 and R6/2, which are characterized by early symptoms and rapid progression of the disease, compared to the BACHD line. The BACHD mouse model shows the first symptoms of the disease between 2 and 6 months of age, but their severity appears after about a year. The BACHD line shows somatic stability in embryos [86]. Studying the microbiome is an increasingly emerging trend in HD research. One study showed an impact of the transplantation of a microbiome derived from WT mice into a mouse model of HD on its phenotype. The results show that especially the females responded positively to this procedure, as improvements in cognitive function have been observed in animals suffering from HD. The same study proved the ineffectiveness of this approach in males. Researchers speculated that the possible reasons for that phenomenon might be more extensive changes in structure, instability in the gut microbiome and the imbalance in acetate immune profiles [87]. In order to characterize the gut microbiome in a mouse model of HD, 16S RNA sequencing was performed. The research was carried out on R6/1 mice. Sequencing results revealed significant differences in the composition of the microbiome. Furthermore, the amount of water in the feces of HD mice at 12 weeks of age was significantly changed. Most notably, there was an increase in Bacteroidetes and a proportional decrease in Firmicutes. Interestingly, an increase in microbiome diversity was also observed in HD males compared to WT control mice, but these differences were not observed in females. The changes coincided with an increased food intake and a simultaneous decrease in body weight [88]. It has been proven that PD is characterized by a decrease in the expression of TJ proteins, which under physiological conditions maintain the integrity of the intestinal barrier [89]. Björkqvist and coauthors evaluated whether the same mechanism is responsible for the pathologies occurring in another mouse model of HD (R6/2). The results showed a significant decrease in body weight and body length in these mice. They were also accompanied by a decrease in colon length compared to WT mice, but TJ protein levels showed no statistically significant changes between groups. Moreover, along with the observed changes, differences in the composition of the gut microbiota were also found in the R6/2 mice. Increased amounts of Bacteroidetes and Proteobacteria and decreased amounts of Firmicutes, relative to levels maintained in the control group were demonstrated [90]. A very interesting and detailed study was performed by Gubert et al. They focused on comparing the study group (R6/1 mouse line), which consisted of 3 subgroups: animals with standard living conditions, mice with additional environmental enrichment, and groups of animals with increased physical activity, with WT mice as controls. The results indicated a possible modulation of the gut microbiome by the environment. Therapeutic effects on psychomotor symptoms and the brain have been reported in groups of animals with an enriched environment and greater activity compared to the control group. Changes in the composition of the microbiome at the level of orders such as Bacteroidales, Lachnospirales, and Oscillospirales have also been demonstrated. The results obtained in this experiment show higher alpha diversity for all HD mice compared to WT mice. There was no difference in food intake, but there was a previously expected decrease in body weight in the HD mice compared to the control group. Increased water intake by animals from the test groups was shown, which was associated with the increase in alpha diversity. With the aging of the HD animals, increased fecal excretion was noted. Post-mortem analysis showed a statistically significant decrease in the brain weight of HD mice. There were also significant differences between males and females. The brain weight of females was lower in the group of mice with standard living conditions. Based on the study of the concentration of SCFAs and branched chain fatty acids (BCFAs) in the feces, an attempt was made to check what role these metabolites may play in living condition changes. Male mice from the group with increased physical activity were characterized by a decrease in the concentration of butyrate and valerate. There was no correlation between the concentration of substances, such as acetate and propionate, and the living conditions, genotype, or gender. Statistically significant differences were found between HD and WT mice in the alpha diversity index. The test groups showed increased alpha diversity indices in contrast to the control group. The results of the beta diversity analysis showed differences between the sexes of the animals. Certain orders of microbial bacteria have been identified as those that play the greatest role in microbiome changes under different animal housing conditions. These include the orders Bacteroidales, Lachnospirales, and Oscillospirales [91]. Early pathological features associated with HD are molecular deficits in myelination and progressive neurodegeneration. Experiments conducted on germ-free (GF) animals suggested that there is a two-way communication between the microbiome, gut, and brain [11,92]. Research conducted on the BACHD mouse model was intended to answer the question of what impact the microbiome has on myelin plasticity and oligodendrocyte dynamics. The experiment compared GF, specific pathogen-free (SPF), and WT mice. Animals of both sexes were used in the experiment. Analysis of myelin in the corpus callosum revealed changes in myelin thickness in BACHD GF mice compared to SPF mice, while no intergroup changes were observed in WT mice. However, significant differences in myelin density were noted in all groups compared to WT SPF mice. In the GF conditions, a reduced level of myelin-associated proteins, such as myelin basic protein (MBP), proteolipid protein (PLP), and Ermin (Ermn), and a lower number of mature oligodendrocytes in the prefrontal cortex were observed compared to the SPF conditions, regardless of the mouse genotype. Slight differences in family and genus were also observed in the commensal bacteria of the gut microbiome in the BACHD and WT groups maintained under SPF conditions. However, the differences were not statistically significant. Researchers concluded that the HTT mutation in BACHD mice does not cause profound disturbances in the intestinal microflora, and thus plasticity defects are not associated with disturbances in the structure of the microbiome. Analysis of the brain structures of GF animals showed that then environment had a greater effect on the myelination caliber of callosum axons in BACHD animals compared to WT controls, while a possible distribution of myelin plaques was observed in both genotypes. The axons of mice maintained under GF conditions were characterized by a reduced diameter and a lower g-ratios, which could suggest thicker myelin. Examination of the myelin membranes, however, showed that the observed features may have been due to the decompaction of the laminae and not an increase in their number. A similar trend of increased periodicity, suggesting decompaction, was also observed in BACHD mice under SPF conditions compared to WT, prompting the conclusion that the HTT mutation in BACHD animals causes this pathology. Supportive is the observation of a trend towards lower levels of the cortical myelin-associated proteins MBP and PLP, which play a key role in myelin compaction. The researchers did not observe significant changes in the gut bacterial community. Slight disparities were observed in BACHD mice at 3 and 6 months of age compared to WT mice, with reduced numbers of Prevotella and Bacteroides at the genus level and part of the Bacteroidetes type [93]. More reports indicate the importance of the intestinal microbiome in the communication between the digestive system and the brain and its impact on the pathologies of neurodegenerative diseases. Subsequent studies involved shotgun sequencing of the gut microbiome from R6/1 mice, aged 4–12 weeks (from early adolescent to adult stages). Metabolomic analyses, in addition to those performed on fecal samples, were also performed on blood plasma collected from 12-week-old animals. The results showed an upregulation of bacterial gene expression, which may indicate potential early effects of the HTT protein mutation in the gut. In addition, mice at 12 weeks of age were found to have disturbed gut microbiome function. In particular, the researchers’ attention was drawn to the increase in the butanoate metabolic pathway, which leads to increased production of SCFA playing a protective role. This increase was not observed when analyzing plasma from 12-week-old mice. Statistical analysis of the results obtained in metagenomic and metabolomic studies allowed for the observation of a negative correlation of several species of Bacteroides with ATP and pipecolic acid in plasma. During the experiment, feces were collected at five different time points. No statistically significant differences in the composition of the microbiome were observed when comparing the mice from the study group and the control WT group. The dominance of two phyla, Bacteroidetes and Firmicutes, was observed, followed by the Proteobacteria, Actinobacteria, and Verrucomicrobia phyla. It was determined that at the family level, the most numerous group was Lachnospiraceae, followed by similar numbers in the groups of Bacteroidaceae, Porphyromonadaceae, Prevotellaceae, and Clostridiaceae. No statistically significant differences were found between bacterial families at any timepoint when comparing WT mice. At 12 weeks of age, which corresponds to the timepoint before the onset of overt motor symptoms in HD mice, differences in 30 bacterial species were observed between HD and WT mice. These included Clostridium mt 5, Treponema phagedenis, Clostridium leptum CAG: 27, Desulfatirhabdium butyrativorans, Plasmodium chabaudi, Defulfuribacillus alkaliarsenatis, Plasmodium yoelii, and Chlamydia abortus. No differences in the abundance of butyrate producers such as Roseburia intestinalis, Clostridium symbiosum, and Eubacterium rectale were found when comparing samples from HD and WT mice [94]. HD—human studies Studies were also performed on a diverse group of people suffering from HD. Participants were clinically characterized using a battery of cognitive tests, and 16S RNA sequencing was performed on stool samples. The study involved healthy individuals (control group; n = 36) and carriers of the expanded mutated gene (n = 42). Nineteen of them were previously diagnosed with HD, and the rest were pre-symptomatic. The groups were matched by gender and age. Microbiome evaluation showed differences between the control group and the study group in the composition of the microbial community (beta diversity) as well as significantly lower species richness (alpha diversity). The results of the sequencing analysis show statistically significant differences at the phylum level (differences apply only to the group of men) in Euryarchaeota, Firmicutes, and Verrucomicrobia. Further changes were also observed at the family level, including: Acidaminococcaceae, Akkermansiaceae, Bacteroidaceae, Bifidobacteriaceae, Christensenellaceae, Clostridiaceae, Coriobacteriaceae, Eggerthellaceae, Enterobacteriaceae, Erysipelotrichaceae, Flavobacteriaceae, Lachnospiraceae, Methanobacteriaceae, Peptococcaceae, Peptostreptococcaceae, and Rikenellaceae, concerned only men. No significant changes at the phylum and family levels were observed in women. The obtained results confirmed the researchers’ assumptions and showed changes in the composition of the microbiome between the test and control groups. In addition, the observations made provide evidence that the composition of the intestinal microbiome affects the cognitive abilities of patients. However, the results obtained in this study should be interpreted with caution. According to the authors, the study and control groups were too small to make adequate statistical analyses. Nevertheless, the information provided is essential for further research [95]. Another study conducted on patients suffering from HD indicates a correlation between changes in the composition of the gut microbiome and the immune response. The study included 33 HD patients and 33 healthy individuals; the groups were matched in terms of sex and age. In addition to assessing the fecal microflora in terms of microbial richness, structure, and diversity of abundance of individual taxa, IFN-γ, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, and TNF-α concentrations in patients’ plasma were measured. The results obtained in both experiments were correlated with each other to find connotations between them. It was shown that HD patients were distinguished by increased richness and altered microbiome structure. The analysis showed that the higher number of Intestinimonas bacteria is positively correlated with the Total Functional Capacity score (measured in HD patients to evaluate disease progression). It is also positively correlated with the level of the anti-inflammatory cytokine IL-4. The study also showed that the genus Bilophila is negatively correlated with pro-inflammatory IL-6 levels. In addition, negative correlations between Oscillibacter, Gemmier, and IL-6; Clostridium XVIII, TNF-α and IL-8; and positive correlations between Porphyromonas and IL-4, IL-10, and IL-13 were also noted. The results obtained in these experiments clearly indicate the relationship between the composition of the intestinal microbiome and the immune response in HD patients [96]. All results described in the paragraph are summarized in Table 1. Increasing advancement in research on neurodegenerative diseases indicates that these pathologies are very complex processes with often forgotten microbiome- and immune-related components. The publications and studies mentioned in this review present evidence for the relationship between neurodegenerative diseases, mainly HD, and the intestinal microbiome. So far, the focus has been on understanding the pathology of the disease based on molecular biomarkers, which hopefully could effectively contribute to the development of future therapies [97]. Recent studies on the effect of the intestinal microbiome and its metabolites also pave the way for new branches in the field of HD. Microbial metabolites have the potential to modulate the pathogenesis of HD. SCFAs can influence the immune system and ameliorate inflammation, both in the CNS and the peripheral nerves. Studies on mouse models that were supplemented with sodium butyrate showed a beneficial effect on their motor skills, mitochondrial and transcriptional dysfunction [28,29]. This suggests that therapeutic interventions promoting butyrate production by patients’ microbiota have the potential to ameliorate disease symptoms. However, there are still many open questions regarding the bacteria inhabiting healthy and diseased digestive systems. The results of research involving microbiota carried out so far are still not entirely conclusive due to microbiome complexity and numerous contributing factors. Therefore, there is still a long way to go to fully understand the communication in the gut—brain axis, including in pathological conditions like HD. Moreover, the microbiome results are not always consistent. The large amount of data generated in experiments is hard to compile, and one needs to be attentive when analyzing and drawing conclusions based on it. Insufficiently known taxonomies of species inhabiting the intestines and inaccurate and non-standardized terminology related to the subject of the microbiome are often misleading and generate mistakes when classifying individual bacteria into appropriate classes, groups, or families. Furthermore, the choice of mouse model, its strain, sex, or age is essential in the studies concerning the microbiome. For example, two studies in a mouse model of HD confirm an increase in Bacteriodetes and a decrease in Firmicutes [88,90]. The first one was carried out on the R6/1 line, and the second on the R6/2 mouse model. Additionally, the study conducted on another HD model contradicts these results. At 3 months of age, BACHD mice exhibit the opposite trend of increased Firmicutes and decreased Bacteriodetes. Interestingly, re-analysis on 6-month-old mice showed the opposite, which rather confirms the results of the previous two studies [93]. The presented results display certain consistency, despite the use of different models, but only when using older mice from the BACHD line. It can be assumed that the microbiome diversity changes in the same fashion as organisms mature. It is also worth noting that some of the results show statistical significance only in the group of males, both in animal and human studies [88,95]. On the other hand, only female mice showed a positive reaction to the transplant of a healthy microbiome [87]. These findings also indicate the effect of female hormones on microbiome composition. In the study conducted by the Hannan group, the body weight of WT and HD mice differed significantly, as HD mice lost weight with age. This could be due to differences in the composition of the microbiome and the level of food absorption, which is inversely proportional to body weight [98]. Increased thirst was also noted, possibly due to xerostomia, which both patients and HD mice suffer from, or hypothalamic degeneration, which is associated with increased thirst [99]. Interestingly, increased water intake by the animals did not change the water content of the feces. The reason could be the microbiological environment in the intestines. This result may suggest a very precise regulation of water absorption [100]. Some of the cited studies indicate an increased level of alpha diversity compared to other groups [88,91,96]. A higher level of this index is believed to indicate a healthier and more resilient microbial environment [101]. Studies in other models of neurodegenerative diseases, such as AD and PD, have also linked movement deficits with lower levels of alpha diversity in patients compared to controls [102,103,104]. Human HD studies have shown lower [95] and higher [96] values of alpha diversity in CAG repeat overexpressors compared to healthy controls. Recent extensive meta-analyses have found no associations between alpha diversity and neurological disorders, particularly in PD and MS [105]. Interestingly, there are also studies that prove that increased diversity does not always correlate with better patient conditions [106,107]. According to Coyte et al., a decrease in the stability of the microbiome environment may also result in higher alpha diversity [108]. Research also shows that the alpha level of diversity may also be related to diet, body weight, and gastrointestinal physiology [109]. Another essential factor that should be considered when conducting experiments related to the microbiome and neurodegeneration in humans is the environment. Each of the mentioned experiments was performed under slightly different conditions, especially in humans. Environmental changes are noticeable among the participants of a project, despite the fact that the control group was chosen from the close family members of the patients [96]. The composition of the gut microbiome is also influenced by various factors, such as physical activity [110,111]. The difference in this respect between healthy and disease-affected individuals certainly existed during the project. This proves how difficult it is to compose appropriate groups in experiments assuming the study of the microbiome. In addition to differences in physical activity, each person has different nutritional preferences, which certainly influence the composition of the microbiome and are a burden for bioinformaticians to be leveled in statistical analyses [112,113]. In addition, the quoted research was performed on distinct continents, which results in diametrically different environmental conditions such as climate or local food accessibility that affect diet [114]. Sampling for testing is an extremely important point in the whole experiment. Typically, the collected samples are snap frozen to eliminate the adverse effect of air on aerophobic bacteria in the samples. In both of these experiments [95,96], the samples were obtained in a different way, and the patients were responsible for collecting and delivering the samples to the laboratory, which might have affected the composition of the microbiome in the samples. Conducting research on mouse models can be better standardized and reproducible by applying a specific sampling and storage protocol. Collection should be as quick as possible, with a caution not to contaminate the sample with other DNA or with bacteria residing on fur. Animal experiments also have the advantage of breeding in more standardized conditions, typically SPF, though the microbiome may vary slightly. On the other hand, the place of origin of the animal, lineage, strain, age, disease model, maintenance method, or even environmental enrichment in the cages are all aspects that should be considered when studying the microbiome. Mice are also known to be coprophages to reabsorb essential nutrients such as vitamins; thus, when housing a few mice in the same cage, one should consider the natural microbiome transfer between them and dodge the “cage effect” [91]. Additionally, all existing mouse models of HD differ from each other by the dynamics of disease progression or the degree of interference in the animal’s genome [115,116]. At this point, it is worth considering at what age and on what model such tests should be carried out. The studies we quoted were based on various models and were carried out on animals of different ages. As with human studies, comparing results obtained in mouse experiments is equally problematic, although the experiments were more standardized. Animal models of HD provide us with tools to study the mammalian microbiome and its possible implications for disease progression in a highly controlled environment. Most studies presented in this review used R6/1 or R6/2 models, which are well established for HD; however, they are characterized by early onset, rapid disease progression, and premature death. As previously mentioned, in humans, the symptoms of HD occur well into adulthood, at 35–40 years of age, with continuous progression for the next 10–15 years, which points to a need for other models with slower disease progression, such as YAC128, Hu128/21, or BACHD. Aging is also closely linked to changes in microbiome composition, so these models might be more applicable for long term studies of changes in microbiome composition and possible dietary or therapeutic interventions that might better translate to humans. There was only one study utilizing the BACHD model that showed pronounced differences in microbiota composition at different ages [93]. Long-term studies on both pre- and post-symptomatic animals are important for a better understanding of the microbiome and HD pathology, but they also have the unique ability to find the most suitable timepoints for therapeutic interventions. Using these models might also be relevant in fecal microbiota transfer studies, as the R6/2 model used by Gubert and colleagues has shown that the engraftment was unsuccessful in male mice [87]. Using models with slower disease progression might provide the researchers with a variety of timepoints and disease phenotypes to choose from, which might impact the success of the microbiota transplant. There is also a fruit fly model of HD (FL-HD) that exhibits similar symptoms such as motor deficits, mHTT aggregates, disrupted gene expression, and dysbiosis in the gut. The Drosophila microbiome is, however, much less complex than the mammalian microbiome, which can help in analyzing single species and their impact on dysbiosis. A study conducted on female fruit flies has found that gut colonization by E. coli worsened the HD symptoms, as there was an increase in aggregate buildup and earlier death. A therapy using crocin was used in Drosophila with beneficial effects. This therapy ameliorated motor deficits and extended the lifespan, but what is more interesting is that it provided resistance to E. coli colonization and had positive effects on the microbiome [117]. Crocin is a carotenoid exhibiting anti-inflammatory, antioxidant, and neuroprotective properties. Crocin, or its major byproduct, crocetin, has been suggested to act in the gut and modulate the gut microbiome. Another study has shown that oral administration of crocin was beneficial for cerebral ischemic/reperfusion (I/R) injuries in rats, while the intravenous route of administration was not. It suggests that the therapeutic effects are mediated through the gut microbiota [118]. As such, crocin might provide beneficial effects in HD, ameliorating inflammation, oxidative stress, and gut dysbiosis, which makes it a promising target for further studies. Interestingly, a few studies have found that prion infection can also lead to dysbiosis and significant changes in microbial metabolites. The microbial richness (alpha diversity) was higher in healthy controls, and the microbiome structure was significantly different between healthy and infected groups. Prion diseases are linked to neuroinflammation, and while the mechanism underlying the gut dysbiosis in this type of disease is not well understood, it is nonetheless an interesting topic to further examine the relationship between the gut and the brain [119,120]. According to the latest research, taking pro- and pre-biotics can help with nervous system diseases. So far, the effect of taking these substances on the progression of HD has not been proven, but it has been studied in other neurodegenerative diseases. There are several studies confirming the psychophysiological effect of prebiotics on the body. Chitosan oligosaccharide (COS) has been shown to have a positive effect on cognitive deficits in a rat model of AD by reducing oxidative stress and neuroinflammatory responses [121]. In studies on amyotrophic lateral sclerosis, it was proven that the use of galactooligosaccharides (GOS) reduced the activation of microglia and astrocytes and caused less death of motor neurons [122]. Other studies conducted in a mouse model of PD showed that long-term intake of probiotics resulted in a neuroprotective effect on dopaminergic neurons, effectively counteracting motor disorders in animals [123]. Unfortunately, few similar studies have been conducted in humans so far. The examples of research cited above prove that the use of products containing both pro- and prebiotic bacterial strains could act as an effective supporting therapy in the treatment of neurodegenerative diseases. Perhaps in the future, effective and personalized drugs based solely on these compounds will be developed.

PMC10003335

Alessio Cesaretti,Eleonora Calzoni,Nicolò Montegiove,Tommaso Bianconi,Martina Alebardi,Maria Antonietta La Serra,Giuseppe Consiglio,Cosimo Gianluca Fortuna,Fausto Elisei,Anna Spalletti

Lighting-Up the Far-Red Fluorescence of RNA-Selective Dyes by Switching from Ortho to Para Position

02-03-2023

fluorescent probe,push-pull dye,intramolecular charge transfer,RNA-selectivity,deep-red emission,fluorescence microscopy,nucleolar RNA,mitochondrial RNA,bioimaging,theranostics

Fluorescence imaging is constantly searching for new far-red emitting probes whose turn-on response is selective upon the interaction with specific biological targets. Cationic push-pull dyes could indeed respond to these requirements due to their intramolecular charge transfer (ICT) character, by which their optical properties can be tuned, and their ability to interact strongly with nucleic acids. Starting from the intriguing results recently achieved with some push-pull dimethylamino-phenyl dyes, two isomers obtained by switching the cationic electron acceptor head (either a methylpyridinium or a methylquinolinium) from the ortho to the para position have been scrutinized for their ICT dynamics, their affinity towards DNA and RNA, and in vitro behavior. By exploiting the marked fluorescence enhancement observed upon complexation with polynucleotides, fluorimetric titrations were employed to evaluate the dyes’ ability as efficient DNA/RNA binders. The studied compounds exhibited in vitro RNA-selectivity by localizing in the RNA-rich nucleoli and within the mitochondria, as demonstrated by fluorescence microscopy. The para-quinolinium derivative showed some modest antiproliferative effect on two tumor cell lines as well as improved properties as an RNA-selective far-red probe in terms of both turn-on response (100-fold fluorescence enhancement) and localized staining ability, attracting interest as a potential theranostic agent.

Lighting-Up the Far-Red Fluorescence of RNA-Selective Dyes by Switching from Ortho to Para Position Fluorescence imaging is constantly searching for new far-red emitting probes whose turn-on response is selective upon the interaction with specific biological targets. Cationic push-pull dyes could indeed respond to these requirements due to their intramolecular charge transfer (ICT) character, by which their optical properties can be tuned, and their ability to interact strongly with nucleic acids. Starting from the intriguing results recently achieved with some push-pull dimethylamino-phenyl dyes, two isomers obtained by switching the cationic electron acceptor head (either a methylpyridinium or a methylquinolinium) from the ortho to the para position have been scrutinized for their ICT dynamics, their affinity towards DNA and RNA, and in vitro behavior. By exploiting the marked fluorescence enhancement observed upon complexation with polynucleotides, fluorimetric titrations were employed to evaluate the dyes’ ability as efficient DNA/RNA binders. The studied compounds exhibited in vitro RNA-selectivity by localizing in the RNA-rich nucleoli and within the mitochondria, as demonstrated by fluorescence microscopy. The para-quinolinium derivative showed some modest antiproliferative effect on two tumor cell lines as well as improved properties as an RNA-selective far-red probe in terms of both turn-on response (100-fold fluorescence enhancement) and localized staining ability, attracting interest as a potential theranostic agent. Nucleic acids fully deserve the epithet of molecules of life. All genetic information residing in the DNA sequences is transferred from DNA to the RNA molecule for its translation into proteins which carry out vital functions in the organisms. The possibility of following nucleic acids inside a cell has always attracted vivid interest, and the use of fluorescence imaging is the natural answer to this demand [1]. The number of fluorescent probes able to interact with nucleic acids is ever-increasing, and research is constantly looking at the identification of novel small molecules which possess the finest properties for their fluorescence response to be aptly tuned [2,3,4]. As a rule, a staining dye to be used in bioimaging has to exhibit some essential characteristics [5,6]: (a) the ability to cross cell membranes, which is granted by a specific balance between hydrophilicity, for stability in an aqueous environment, and lipophilicity, for easy passage through phospholipid bilayers; (b) high binding affinity for their biological targets; (c) emission turn-on upon complexation with biomolecules inside the cell to visualize specific organelles and reduce background fluorescence from free dye molecules; (d) large Stokes shifts to avoid self-quenching and fluorescence in the deep-red to ensure better tissue penetration and avoid both photo-damage and the contribution of autofluorescence from the surrounding environment. Some structural motifs have proved effective in boosting the affinity for nucleic acids: aromatic portions can favor interactions with nucleobases, while positive charges allow electrostatic attraction with the negatively charged phosphate backbone [7,8,9,10]. This may result in either intercalation of the probe between adjacent nucleobases or binding in the major and minor grooves of the nucleic acids [11,12,13,14]. These structural properties can be combined in molecules endowed with push-pull character, where electron acceptor (A) and electron donator (D) portions are linked by a π-conjugated bridge in a basic A-π-D arrangement or more articulate A-π-D-π-A and D-π-A-π-D structures. This allows, on the one hand, shifting the optical properties to the visible up to the far-red by increasing conjugation and, on the other hand, fostering a turn-on behavior. In fact, push-pull molecules undergo intramolecular charge transfer (ICT) transitions upon photoexcitation, with their excited state being stabilized in a polar environment, where its deactivation to the ground state takes place mainly by internal conversion. Under these conditions, to favor the charge separation and the following stabilization, a push-pull A-π-D molecule can undergo a 90-degree rotation around the π-bridge leading to a nearly non-fluorescent twisted ICT (TICT) state [15,16,17]. When these dyes are instead confined in a rigid environment, like that provided by a nucleic acid or an increase in viscosity, the restriction of molecular motion prevents the ICT state from reaching a fully-relaxed TICT state with a consequent enhancement of its fluorescence [16,18,19]. However, selectivity, the capability of a molecule to stain particular organelles or interact preferentially with a specific biological target over others, is another highly required feature a good probe should exhibit [20,21,22,23]. When it comes to RNA, selectivity allows RNA domains to be visualized either inside the cell nuclei, within the nucleoli, or in the cytoplasm, where it amasses in specific organelles such as mitochondria and ribosomes [24,25]. The interest in RNA imaging derives from the implication of this nucleic acid in a number of cell processes, which include, besides common protein synthesis, post-transcriptional and gene expression regulations being fundamental in the cell vital cycle [26]. Further to this, RNA is involved in the replication of so-called RNA viruses, which represent a very current healthcare issue [16]. The use of selective fluorescence probes specifically interacting with RNA could thus become a powerful tool not only to perform imaging for localization and diagnostic purposes but also to monitor and interfere with cell viability or virus replication for the treatment of diseases, whether tumors or infections, respectively [5]. As of today, SYTOTM RNASelectTM is one of the few fluorescent dyes available in the market for RNA staining [25]. It exhibits a bright fluorescence in the green upon binding to RNA, as opposed to a weak fluorescence for its DNA-bound form, allowing RNA to be visualized in nucleoli and cytoplasm. A lot of research study has been running rampant to look for other small molecules that could be used as an alternative to SYTOTM RNASelectTM, with the deliberate aim to outdo its performances in terms of selectivity and emission properties [27,28,29,30,31]. In our long-term research concerning the interaction between small organic molecules and biological targets [32,33,34,35], we have recently come across some push-pull styryl compounds which indeed show certain RNA selectivity [5,36]. In particular, a recent work of ours [36] deals with a series of three A+-π-D dyes, where D is a dimethylamino-phenyl group, A+ is either a methyl pyridinium or methyl quinolinium, and the π-bridge is a simple ethylene or extended butadiene. These probes, studied in a tumor cell line by confocal fluorescence, were found to mostly stain nucleoli as a consequence of the interaction with RNA, as proven by the ribonuclease A (RNase) digest test. Further to this, in another study [5], we scrutinized a series of A+-π-D-π-A+ dyes and found that a greater affinity for RNA over DNA was exhibited for the compound with an electron donor methyl quinolinium attached in the para position relative to the π-bridge. On the basis of the previous findings, two push-pull dyes (shown in Scheme 1) were designed. They are the analogs of compounds already studied in ref. [36] and obtained by switching from ortho to para position the A+ moiety in the A+-π-D dimethylamino-phenyl, and investigated for their application as deep-red RNA-selective fluorescent probes. By doing so, the turn-on response guaranteed by the strong electron donor dimethylamino-phenyl was combined within the same molecular structures with the selectivity granted by the attachment in the para position. As a matter of fact, while developing this project, we came across a recent work by Zhang et al. [37] where one of the two para isomers here presented (i.e., the quinolinium derivative, pQ-π2) had already been tested as a far-red fluorescent probe both in vitro and in vivo. Its turn-on response was interpreted as due to the increased viscosity sensed within the cells, but the possible interaction with nucleic acids, which represent an obvious biological target for these positively-charged aromatic small molecules, was completely overlooked and left out of the discussion. In this work, a thorough spectroscopic investigation was carried out for the two para isomers as a function of solvent polarity, allowing the push-pull character of the two dyes to be described in terms of dipole moment variation upon excitation (Δµ) and hyperpolarizability coefficients (β), as derived from their solvatochromic behavior; the role of photoinduced ICT in the excited-state dynamics of the two compounds was also deduced from careful analyses of ultrafast transient absorption and fluorescence up-conversion measurements. In addition, their binding affinities with nucleic acids as well as the photophysical properties of the free dyes compared to their bound forms, were evaluated ex cellula by spectrophotometric and fluorimetric titrations (with both tRNA and ct-DNA) and femtosecond-resolved spectroscopies; while the effective selectivity towards RNA was assessed in vitro through fluorescence microscopy. In particular, the two dyes were found to localize in the nucleoli and the mitochondria, driven by the explicit interaction with RNA, with better performances revealed for the quinolinium derivative. The two investigated compounds were first studied for their photophysical behavior to evaluate the entity of their push-pull character. The spectral properties of pPy-π2 had already been analyzed in previous work [38], while pQ-π2 was here studied in a wide range of solvent polarities for the first time. A marked negative solvatochromic behavior was observed for the absorption spectrum of both dyes (Table 1 and Figure 1 and Figure S1), whose maximum shifts to higher energy as the polarity increases as a result of the greater stabilization of the more polar ground state relative to the excited state reached upon excitation. The emission spectrum is instead almost insensitive to the polarity of the medium, as expected for a relaxed excited state with an ICT nature [38], but when it comes to pQ-π2, its emission is somewhat affected by viscosity, which causes a modest enlargement of the spectrum on the blue side of the band (Figure 1B), supposedly because of the contribution of different excited-state configurations. On the basis of Reichardt theory [39], solvatochromism was used to derive the difference in dipole moments between the ground and the Franck-Condon excited state (Δμexp) from the slope of the linear fitting obtained by plotting the Stokes shift vs. the parameter, which accounts for the polarity of the solvent (Figure S2). The Δμexp absolute values proved to be higher than 10 D for both compounds (Table S1). This analysis also allowed the first hyperpolarizability coefficient (β0), which is an indicator of the push-pull character of the molecule, to be deduced through the solvatochromic method, as reported in Table S1 [38,40]. The highest values (Δμexp = −13.2 D and β0 = 200 × 10−30 esu−1 cm5) were found for pPy-π2, likely because it features a highly conjugated linear structure which extends along the direction of the charge transfer from the dimethyl-phenyl group to the methyl pyridinium, while the additional ring in pQ-π2 is placed outside of the CT direction. In fact, quantum mechanical calculations, previously performed on pPy-π2 [38] and here carried out for pQ-π2 at the same TD-DFT level of theory to optimize the ground state geometry and describe the lowest singlet excited states, revealed a greater effect on the electron density displacement upon absorption in the case of pPy-π2 (Figures S3–S6 and Tables S2 and S3). The ICT nature of the relaxed excited state was instead experimentally evidenced by the quenching of the fluorescence quantum yields (Table 1) with increasing solvent polarity by more than one order of magnitude when going from a sparingly polar solvent, i.e., DCM, to an aqueous environment (ΦF,DCM/ΦF,water = 45 and 26 for pPy-π2 and pQ-π2, respectively). The conclusive proof, however, was provided by the excited state dynamics investigated by fs-transient absorption (fs-TA) and fs-fluorescence up-conversion (fs-FUC). The former was performed in DCM, MeOH, and W to assess the effect of polarity (Figure 2 and Figure S7 and Table 2). Although fs-TA experiments had already been carried out in the case of pPy-π2 [38], its measurements were repeated for this work. The new data fairly reproduced the published dynamics, but their thorough analysis, assisted by the comparison with the new fs-FUC measurements, led to a slightly modified interpretation. The time-resolved transient absorption spectra are characterized by positive excited-state absorption signals and negative bands due to either ground-state bleaching (GSB), matching the steady-state absorption region, or stimulated emission (SE). The evolution of the SE band, sensitive to stabilization of the excited state, reveals important dynamics at short delays in all the media analyzed, suggesting the presence of some ICT process, with SE overlapping the steady-state fluorescence only at longer times. In fact, the time associated with the longer transient, corresponding to the lifetime of the S1 state, was found to greatly reduce as the polarity increases (τS1,DCM = 840 ps and τS1,w = 73 ps for pPy-π2 and τS1,DCM = 82 ps and τS1,w = 5.6 ps for pQ-π2) as it is typical of ICT states mainly decaying by internal conversion in a polar environment. In particular, shorter times are peculiar to pQ-π2 supposedly because of a better ability to separate the charge in the relaxed ICT state. Femtosecond fluorescence up-conversion (fs-FUC) measurements, carried out in polar MeOH, disclosed the ICT dynamics of the two investigated push-pull dyes (Figure 3 and Figure S8). The time-resolved emission spectra follow the stabilization of the emissive excited state with time (Figure 3 and S8, left), which could be related to either solvation or the population of different states. In the case of pPy-π2, the Global Analysis returned four transients (in line with the results of fs-TA, cf. Table 2), three matching the canonical solvation times of MeOH (τ = 0.64 ps, 2.2 ps, and 23 ps) [41] and the longest one τS1 = 190 ps assigned to the relaxed emissive state. The time-resolved emission spectra were then processed to give TRANES (time-resolved area-normalized emission spectra) [18,42], which revealed the existence of a three-state dynamic masked by solvation, as evidenced by the presence of two distinct isoemissive points in their evolution (Figure 3, right). In analogy with what has previously been observed for other push-pull methylpyrydinium derivatives [18], the dynamics can be interpreted as an ultrafast charge transfer process from the locally-excited (LE) state, happening together with inertial solvation (τLE→ICT = 0.64 ps), and a rotation around the π-bridge that favors the charge separation to form a twisted ICT (TICT) state (τICT→TICT = 2.2 ps) during diffusive solvation, which later undergoes a second diffusive solvation step (τsolv. = 23 ps) before returning to the ground state with a lifetime of 190 ps. The twisted geometry of the TICT state is also corroborated by a reduction of the full width at half maximum during the spectral evolution, as it is common for an emissive state whose population distribution narrows around the equilibrium twisted position [43]. These dynamics account for both the large bathochromic shift of the emission up to the far-red region (ICT character) and the scarce fluorescence in polar media (twisted geometry). As for pQ-π2 (Figure S8), because of its faster dynamics and owing to the reduced temporal resolution of the fs-FUC setup, the first transient ascribable to the LE state (τLE = 0.46 ps from the fs-TA experiment) could not be detected, and therefore the TRANES evolution only revealed the transition from the ICT state to the TICT state (τICT→TICT = 1.5 ps), followed by diffusive solvation (τsolv. = 4.9 ps) and excited-state deactivation (τTICT→S0 = 15 ps). The absorption spectra of the two molecules in buffered water at pH 7.4, mimicking a biological environment, feature a broad band centered at 447 and 511 nm for pPy-π2 and pQ-π2, respectively, with a trend that parallels the increased conjugation given by the substitution of the pyridine rings with a quinolinium. The emission is instead observed in the deep red with maxima at 709 and 688 nm, resulting in very large Stokes shifts of 8270 and 5000 cm−1 for pPy-π2 and pQ-π2, respectively. The fluorescence quantum yields are very low, with the quinolinium derivative (ΦF = 0.002) being less fluorescent than the pyridinium one (ΦF = 0.056). The affinity for nucleic acids was evaluated through spectrophotometric and fluorimetric titration by adding increasing amounts of calf thymus DNA (ct-DNA) and tRNA up to a ratio r = [dye]/[nucleic acid] < 0.005, as shown in Figure 4 and Figure S9. The interaction of both compounds with either ct-DNA or tRNA caused the absorption spectra to undergo significant redshifts as a consequence of the exclusion of water molecules from the vicinity of the probe upon complexation. In the case of pPy-π2, the spectrophotometric titrations reveal a clear isosbestic point implying the existence of one predominant mode of binding, which is likely to be intercalation owing to the net hypochromicity detected for the absorption band [9]. As for pQ-π2, the spectral evolution showed deviations from the isosbestic point: as the concentration of nucleic acids increases, a first hypochromic effect is recorded, followed by an important enhancement of the absorbance (hyperchromic effect), which could instead be related to interaction by different modes of binding, possibly within the grooves of the polynucleotide chains. When it comes to spectrofluorimetric titrations, both dyes were found to light up by enhancing their emissive capability: pPy-π2 showed a more than 10-fold increase in quantum efficiency (QE) with both nucleic acids (QEF,ct-DNA = 0.084 and QEF,tRNA = 0.073), while pQ-π2 experienced a greater turn-on response, with a 42-fold fluorescent enhancement when bound to ct-DNA (QEF,ct-DNA = 0.084) and an almost 100-fold increase after complexation with tRNA (QEF,tRNA = 0.18). The huge change in the emission intensity allowed the processing of the titration data by the Scatchard equation to obtain the binding constants reported in Table 3 (Figure S10). As a rule, pQ-π2 showed greater affinity (by almost one order of magnitude) as opposed to the pyridinium derivative, likely because of the more extended aromaticity. The dye/nucleic acid complexes were also characterized by the fs-TA measurements reported in Figure 5 for pQ-π2 and in Figure S11 for pPy-π2. The signals recorded for the two dyes in an aqueous buffer at pH 7.4 in the presence of nucleic acid (r = 0.02) showed signs of the interaction by virtue of the red-shift of the GSB band, in line with the spectral changes observed during the spectrophotometric titrations, and the significant lengthening of the overall excited-state dynamics, which parallels the fluorescence enhancement achieved upon binding. The Target Analysis, whose results are listed in Table 4, confirmed these observations, always revealing a transient with a lifetime far exceeding that of the free dyes in water. The shortest components are assigned to solvation processes, but in the case of pPy-π2, a species characterized by a lifetime and a spectral profile resembling those of the free molecule in an aqueous solution can also be recognized. Such species are not present in the excited-state deactivation of pQ-π2 under these conditions, thus validating the higher binding affinity assessed for the quinolinium derivative. More interestingly, pQ-π2 features a longer lifetime when bound to tRNA (τpQ-π2+tRNA = 500 ps) compared to its bound form with ct-DNA (τpQ-π2+ct-DNA = 320 ps), in a parallel trend with the fluorescence enhancement. The fluorescence quantum yields and excited-state lifetimes allowed the fluorescence rate constants to be determined. They were found to be 0.77 × 108 s−1 and 3.6 × 108 s−1 in the buffer for pPy-π2 and pQ-π2, respectively, and they did not change appreciably upon complexation, meaning that the ICT character of the emissive state is not altered by the interaction; hence, the lighting-up of the fluorescence response is mainly due to the protection-action played by the nucleic acids which shield the probes from the bulk aqueous environment, thus hindering their twisting, but still allowing a far-red emitting ICT state to be reached. The possibility of using the two dyes for staining purposes is subject to their ability to pass the cellular outer membrane, which was proved by treating human tumor cells in vitro (A549 and HT-29) with micromolar concentrations of the two molecules. The dyes, featuring the right balance between lipophilic and hydrophilic portions, were efficiently and rapidly internalized by the cells. The effect of the two compounds on cell viability was then evaluated by the MTT test performed after 24 h of incubation (Figure S12). Both molecules proved to be tolerated by the cells at concentrations ≤ 1 µM, while they exerted some antiproliferative effect at higher concentrations, especially toward HT-29 cells. In particular, pQ-π2 exhibited moderate cytotoxicity, with an IC50 (IC50 = dye concentration inducing 50% inhibition of cell growth) of about 90 and 60 µM for A549 and HT-29 cells, respectively. As for pPy-π2, its IC50 against both cell lines was larger than 100 µM, and it can thus be regarded as noncytotoxic. To understand the reasons for such an antiproliferative effect and assess the possibility of resorting to the two dyes as effective staining agents, their peculiar localization within A549 cells was investigated by fluorescence microscopy. After fixing the cells after 2 h of incubation, the bright and red emission of the two compounds was found not to be randomly diffused inside the cellular environment but specifically localized in certain organelles (Figure 6 and Figure 7). In particular, the perinuclear portion of the cytoplasm was lighted up, as well as some punctuate structures within the nuclei, which appeared particularly bright in the case pQ-π2. By co-staining the cells with the nuclear blue dye DAPI (Figure 6), the red dots in the nucleus, characterized by a signal which is spatially complementary to the blue fluorescence of DAPI, can be recognized as the nucleoli, proving the two investigated molecules to be permeant to the two lipid bilayers constituting the nuclear membrane. This finding envisages a certain RNA-selectivity for both compounds, inasmuch as nucleoli are rich in RNA, particularly ribosomal RNA (rRNA), while DNA has a three-fold higher concentration in the remaining nucleoplasm, being expressly illuminated by DAPI [12]. To validate the RNA selectivity of the two molecules and their localization in the nucleoli, ribonuclease (RNase) and deoxyribonuclease (DNase) digestion experiments were carried out on fixed and permeabilized A549 cells. Figure 7 reports representative fluorescence microscopy images of cells stained with the two probes before and after treatment with RNase and DNase. In the first case, as a consequence of the degradation of RNA, the emission loses its characteristic confinement in punctuate structures, while the fluorescence signal is practically not affected by the digestion of DNA following the action of DNase. This finding confirms that the punctuated bright emission comes from a specific interaction with the RNA within the nucleoli. Moreover, in order to understand the origin of the red emission in the perinuclear region, colocalization experiments were carried out with a commercial dye specific for mitochondria staining, namely MitoTracker™ Green FM Dye. By virtue of the anticipated RNA selectivity, the two styryl dyes were expected to light up cellular compartments particularly rich in RNA, and mitochondria could indeed be a target for the investigated molecules, also because quaternary ammonium is a recurring motif in mitochondria probes [44,45]. The analysis of the fluorescence microscopy images, merged into yellow as reported in Figure 8, gave Pearson’s coefficients (Rr, describing the spatial colocalization) of 0.67 and 0.73 for pPy-π2 and pQ-π2, respectively, implying moderate colocalizations [46,47,48]. In fact, the red emission of the dyes and the green emission of MitoTracker™ do not overlap in the nucleolar region, where only the push-pull dimethylamino-phenyl dyes can be spotted. This is supported by the computation of Manders’ coefficients (m1 and m2) for red-green colocalization, which indicates the fraction of red pixels overlapping with green (m1) and vice versa (m2) [47,49]. By doing so, a strong degree of colocalization can be found for the green (m2 = 0.98 and 0.99 for pPy-π2 and pQ-π2, respectively), while the presence of the red fluorescence inside the nuclei is discriminated by the reduced m1 coefficient, which is 0.78 for pPy-π2 and 0.90 pQ-π2. However, if only the perinuclear region is considered for the analysis of the images, the overlapping is strong for pPy-π2 (with Rr = 0.88, m1 = 0.800, and m2 = 0.994) and almost complete for pQ-π2 (with Rr = 0.94, m1 = 0.986, and m2 = 0.996). Two push-pull A+-π-D dyes, where D is a dimethylamino-phenyl group and A+ is either a methyl pyridinium or methyl quinolinium attached in the para position relative to the butadiene π-bridge, were investigated as far-red fluorescent probes to be compared to their ortho positional isomers, which had previously been studied in our laboratory [36]. Switching from the ortho to the para position causes the absorption spectrum recorded in water to shift bathochromically by about 10 nm, likely because of the more conjugative position of attachment. As for the fluorescence emission, it is always found in the deep-red region with broad bands centered around 700 nm. This results in huge Stokes shifts, larger in the case of the pyridinium derivatives (greater than 8000 cm−1), which is desirable for bioimaging applications. The fluorescence quantum yields are instead small (<1%) and not affected by the attachment position for the pyridinium derivatives (ΦF = 0.0056 and 0.0064 for pPy-π2 and oPy-π2, respectively); however, when it comes to the quinolinium-substituted molecules, the para position allows a five-fold increase in the ΦF value (ΦF = 0.0020 and 0.0004 for pQ-π2 and oQ-π2, respectively). The large Stokes shift and reduced fluorescence were explained by invoking important excited-state dynamics with the population of twisted ICT states mainly decaying by non-radiative internal conversion, as proven by fs-TA and fs-FUC measurements. These dynamics are favored by the presence of the strong electron-donor moiety dimethylamino phenyl, implying a great push-pull character for these dyes. The push-pull nature of the investigated compounds was quantified by the computation of their first hyperpolarizability coefficients (β0) deduced from the straightforward negative solvatochromic behavior. The β0 values were found to enhance by switching from ortho to para position for the attachment of the pyridinium ring (β0 = 120 × 10−30 esu−1 cm5 for oPy-π2 vs. 200 × 10−30 esu−1 cm5 for pPy-π2) [38], but not to change upon position changes in the case of the quinolinium derivatives (β0 = 160×10−30 esu−1 cm5 for both oQ-π2 and pQ-π2), supposedly because the additional aromatic ring in pQ-π2 is not placed in the direction of the CT vector. These photophysical properties (ICT dynamics, large Stokes shifts, far-red emissions) are alluring for a fluorescent probe as long as they are combined with a high affinity for biological targets. Spectrophotometric and fluorimetric titrations with ct-DNA and tRNA revealed the favorable interactions of the dyes with nucleic acids. In particular, pQ-π2 exhibited one-order of magnitude higher associations constants than pPy-π2 (Kass,tRNA = 2.4 × 104 M−1 vs. Kass,tRNA = 4 × 103 M−1, and Kass,ct-DNA = 1.8×105 M−1 vs. Kass,ct-DNA = 3.0 × 104 M−1), probably by virtue of the increased condensed aromatic surface. The greater affinity of pQ-π2 also implies more pronounced changes in both the absorption spectrum (marked red-shift and hyperchromic effect) and the emission spectrum (sharp fluorescence enhancement). Moreover, by comparing these results with those already published for the ortho isomers with tRNA (Kass,tRNA = 1.6 × 103 M−1 for oPy-π2 and Kass,tRNA = 7 × 103 M−1 for oQ-π2) [36], a peculiar greater affinity can be identified in the only case of pQ-π2. This finding is also accompanied by the highest emission turn-on response (almost 100-fold fluorescence enhancement) shown by the para isomer of the quinolinium derivative when bound to RNA, reaching a high quantum efficiency (QE) of 0.18, as opposed to the other compounds of the series (QEpPy-π2+RNA = 0.073, QEoPy-π2+RNA = 0.025, and QEoQ-π2+RNA = 0.073) and competitive with the fluorescence ability of other RNA fluorescent probes [16,24]. In addition, unlike pPy-π2, the fs-TA analysis of the pQ-π2-tRNA complex revealed a greater lifetime lengthening relative to that experienced by pQ-π2 when associated with DNA molecules (τpQ-π2+RNA/τpQ-π2+DNA = 1.6), accounting for the higher emission efficiency (QEpQ-π2+RNA/QEpQ-π2+DNA = 2.1). Given that selectivity is the result of both greater affinity and higher switch-on response upon the interaction with a specific biological target over the others, these results can anticipate an improved RNA-selectivity for the pQ-π2 relative to either the pyridinium derivative and the ortho isomers, which had already proved to show a certain preference to bind RNA in vitro [36]. Fluorescence microscopy images indeed revealed the cell permeability of the dyes and the selective localization of their fluorescent signal in both the nucleolar region and the perinuclear portion of the cytoplasm. Bright red dots associated with RNA-rich nucleoli can be identified within the nuclei, with a sharper definition in the case of pQ-π2. The assignment of this emission to the specific interaction with nucleolar RNA was corroborated by RNase and DNase digestion tests, which demonstrated how the degradation of RNA causes the fluorescence signal to lose its brightness and peculiar localization while it remains almost unaltered when DNA is digested. Analogously, confocal microscopy measurements performed on the ortho isomers had previously revealed a similar nucleolar localization but also a diffused fluorescence signal in the entire cellular body, which is an index of poor selectivity [36]. In the case of the para isomers, the background fluorescence in the nucleoplasm is reduced when resorting to pQ-π2, resulting in an improved contrast when lighting up the nucleoli. Moreover, the red signal outside the nucleus is not randomly diffused but limited to a portion of the cytoplasm recognizable as the mitochondria, as evidenced by colocalization experiments with MitoTrackerTM Green, giving Pearson’s coefficients of 0.94 and 0.88 for pQ-π2 and pPy-π2, respectively. The specific localization in the mitochondria could be again related to the interaction with RNA since mitochondria possess their genomes with their own set of RNAs, whose functionality can be dysregulated under pathological conditions, like in cancer cells [50], and thus might need to be monitored. This behavior is similar to that of the cell-permeant SYTOTM RNASelectTM green fluorescent probe, which is the only commercially available dye for live cell staining of RNA-rich regions associated with nucleoli and mitochondria [25,51]. However, while SYTOTM RNASelectTM exhibits green fluorescence with an emission maximum around 530 nm, the investigated dyes have an uncommonly intense fluorescence in the far-red, centered at 700 nm, which represents a remarkable feature for a fluorescent probe as it allows better tissue penetration and helps to cut off the contribution of endogenous autofluorescence [6]. As for pQ-π2, in a recently-published paper [37], its bright fluorescence had already been visualized in the mitochondria of HeLa cells through laser confocal microscopy and assigned to the experienced greater viscosity, which restricts the excited-state twisting of the molecule, inhibiting the population of the scarcely emissive TICT state. However, the interaction of the probe with nucleic acids, readily available within the cells, was not taken into consideration. As a matter of fact, when dealing with positively-charged aromatic small molecules, their binding to nucleic acids is destined to happen in a cellular environment and is essential to describe their in vivo behavior. Hence, in agreement with the previous literature, the fluorescence switch-on of pQ-π2 can indeed be assigned to a restriction of molecular motion preventing the probe from reaching the fully-relaxed TICT state, but this new study unraveled how the reason beyond this is its distinct binding with RNA. These results, together with the moderate antiproliferative effect exhibited by the quinolinium derivative at micromolar concentrations, supposedly following the interference with the cell life cycle and metabolism by specific and stronger interactions with nucleic acids, imply the potential use of this molecule for theranostic applications. In conclusion, this study demonstrated the superior properties of the far-red emitting pQ-π2 fluorophore as an in vitro RNA-selective probe relative to its pyridinium analogs and ortho isomers. The results revealed how small changes in the molecular structure (para vs. ortho; quinolinium vs. pyridinium) could fine-tune the performance of the dye, thus guiding the synthesis of novel compounds. The molecular structures of the two investigated cations pPy-π2 and pQ-π2 are reported in Scheme 1. Their synthetic procedure is described in the following. 4-((1E,3E)-4-(4-(dimethylamino)phenyl)buta-1,3-dien-1-yl)-1-methylpyridin-1-ium iodide (pPy-π2): to a solution of (E)-3-(4-(dimethylamino)phenyl)acrylaldehyde (88 mg, 0.5 mmol) and 1,4-dimethylpyridin-1-ium iodide (118 mg, 0.5 mmol) in methanol (15 mL), piperidine was added (4.95 mL, 0.05 mmol). The resulting solution was refluxed for 4 h under a dinitrogen atmosphere in the dark. After cooling, the dark solution was evaporated to a volume of 5 mL and left to stand in the dark. The crystals were collected by filtration and washed with ether. After drying under vacuum at 80 °C, the needles obtained weighed 59 mg. Yield: 0.059 g. 30%, dark purple needles. 1H NMR ([D6]DMSO): δ = 3.01 (s, 6 H, N(CH3)2), 4.17 (s, 3 H, N+CH3), 6.72 (m, 3 H, CH= + ArH), 7.00 (m, 2 H, CH=), 7.46 (d, 3JH-H = 8.5 Hz, 2 H, ArH), 7.79 (m, 1 H, CH=), 8.01 (d, 3JH-H = 7.0 Hz, 2 H, PyH), 8.68 (d, 3JH-H = 7.0 Hz, 2 H, PyH); MS (positive ESI): m/z = 265.2 [M − I]+. HRMS (positive ESI): calculated for C18H21N2+ 265.1699, found 265.1101. 4-((1E,3E)-4-(4-(dimethylamino)phenyl)buta-1,3-dien-1-yl)-1-methylquinolin-1-ium iodide (pQ-π2): to a solution of (E)-3-(4-(dimethylamino)phenyl)acrylaldehyde (200 mg, 1.14 mmol) and 1,4-dimethylquinolin-1-ium iodide (233 mg, 0.82 mmol) in methanol (10 mL), piperidine was added (7.93 mL, 0.08 mmol). The resulting solution was refluxed for 4 h and stirred at room temperature overnight under a dinitrogen atmosphere in the dark. After cooling, the dark suspension was filtered and washed with ether. After drying under vacuum at 80 °C, the needles obtained weighed 25 mg. Yield: 0.025 g. 7%, black needles. All spectroscopic measurements are identical to those already reported in the literature [37]. ESI-MS spectra were recorded on a Thermo Fisher API 2000 mass spectrometer. High-resolution mass spectra were acquired on a Waters® SYNAPT® G2-S/Si mass spectrometer (Waters, Wilmslow, UK). NMR experiments were achieved at 27 °C using a Varian Unity S 500 (499.88 MHz for 1H) spectrometer. Tetramethylsilane (TMS) was the internal reference for all NMR experiments. Spectral and photophysical measurements were performed in various solvents (Fluka, spectroscopic grade): chloroform (CHCl3), dichloromethane (DCM), 1,2-dichloroethane (DCE), 2-propanol (2-PrOH), ethanol (EtOH), methanol (MeOH), water (W), and their mixtures. With the aim being to carry out experiments in aqueous media at known concentrations, the two compounds were first dissolved in dimethyl sulfoxide (DMSO) of spectroscopic grade (Sigma-Aldrich, Saint Louis, MO, USA) to prepare concentrated stock solutions (1 mM) to be later diluted in ETN (1 mM EDTA, 10 mM Tris-HCl, 10 mM NaCl) aqueous buffer solutions, pH 7.4. Ethylenediaminetetraacetic acid (EDTA), tris(hydroxymethyl)aminomethane hydrochloride (Tris-HCl), and NaCl were purchased from Sigma-Aldrich (Saint Louis, MO, USA). Baker’s yeast tRNA was purchased from Roche (Mannheim, Germany), and calf thymus DNA (ct-DNA) from Sigma-Aldrich (Saint Louis, MO, USA); they were used after dissolution in sterile ETN. The ct-DNA was additionally sonicated and filtered through a 0.45 µm filter. The concentration of the polynucleotides’ stock solutions was determined spectrophotometrically by recording the incremental absorbance at 258 nm for tRNA (ε = 6900 M−1 cm−1) and 260 nm for ct-DNA (ε = 6600 M−1 cm−1). Dulbecco’s modified Eagle’s medium (DMEM), fetal bovine serum (FBS), Trypsin, and Penicillin/Streptomycin were purchased from Euroclone (Pero, Italy). Dimethyl sulfoxide (DMSO) for biological experiments, Trypan Blue powder, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), Deoxyribonuclease I (DNase I) from bovine pancreas, and Ribonuclease A (RNase A) from bovine pancreas were purchased from Sigma-Aldrich (Saint Louis, MO, USA) and Becton, Dickinson and Company (Franklin Lakes, NJ, USA). MitoTracker™ Green FM Dye was purchased from Thermo Fisher Scientific Inc. (Waltham, MA, USA). Vectashield® Vibrance™ Antifade Mounting Medium containing 4′,6-diamidino-2-phenylindole (DAPI) was purchased from Vector Laboratories Inc. (Newark, CA, USA). Absorption spectra were recorded with a Cary 4E (Varian, Palo Alto, CA, USA) spectrophotometer, choosing a spectral bandpass of 2 nm and using cuvettes with 1 cm path length. Fluorescence emission and excitation spectra were detected by a FluoroMax-4P (HORIBA Scientific, Jobin Yvon, France) spectrofluorimeter and analyzed by the FluorEssence software with appropriate instrumental response correction files. The path length of the cuvette was 1 cm, and the acquisition of the spectra was conducted in right-angle geometry. The spectral bandpass was always set at 2 nm for the excitation monochromator, while in emission, the spectral bandpass ranged from 10 to 20 nm, depending on the system under investigation. The fluorescence quantum yields (ΦF, experimental error ± 10%) of dilute solutions (A at λexc < 0.15) were obtained by exciting each sample at the relative maximum absorption wavelength by employing tetracene in air-equilibrated cyclohexane (ΦF = 0.17) [52]or rhodamine 6G in ethanol (ΦF = 0.94) [53] as reference compounds. The experimental setup for the femtosecond transient absorption (fs-TA) and fluorescence up-conversion (fs-FUC) measurements have been widely described elsewhere [54,55,56]. Briefly, the 400-nm excitation pulses of about 60 fs were generated by an amplified Ti:Sapphire laser system (Spectra Physics, Mountain View, CA, USA). The fs-TA spectrometer (Helios, Ultrafast Systems, Sarasota, FL, USA) is characterized by a time resolution of 150 fs and a spectral resolution of 1.5 nm. Probe pulses are produced in the 450–800 nm range by passing a small fraction of the 800 nm excitation radiation through an optical delay line (time window of 3200 ps) and focusing it onto a 2-mm thick Sapphire crystal to generate a white-light continuum. In the fs-FUC setup (Halcyone, Ultrafast System, Sarasota, FL, USA), the 400-nm pulse excites the sample, whereas the fundamental laser beam acts as the “gate” light. After passing through the delay line, the “gate” reaches the Sapphire crystal, where it combines through the up-conversion process with the fluorescence emitted by the sample with the same time delay. The time resolution is about 300 fs, while the spectra resolution is 1.5 nm. All the ultrafast measurements were carried out under the magic angle condition, stirring the solution in a 2 mm cuvette (0.5 < A < 1.0 at λexc = 400 nm) during the experiments to avoid the occurrence of photoreactions. Photodegradation was, however, checked by recording the absorption spectra before and after each time-resolved measurement. The experimental data matrixes were first analyzed by using the Surface Xplorer PRO (Ultrafast Systems, Sarasota, FL, USA) software, where it was possible to perform SVD of the 3D matrix to derive the principal components (spectra and kinetics) [57,58]. Successively, the Global Analysis through GloTarAn software was performed to obtain the lifetimes and the Evolution-Associated Spectra (EAS) of the detected transient [59]. When carrying out the measurements of pPy-π2 in the presence of nucleic acids, Target Analysis was performed to consider a parallel decay accounting for the independent deactivation of free dye molecules and their bound form with polynucleotides. The results of the Target Analysis are the Species-Associated Spectra (SAS) of the transients with their lifetime. Quantum mechanical calculations were performed by using the Gaussian 16 package (Wallingford, CT, USA) [60]. DFT with the CAM-B3LYP functional was chosen as the method to optimize the ground state geometry of these small organic push-pull systems and derive their properties [61]. Meanwhile the lowest singlet excited states were investigated through TD-DFT excited-state calculations, again resorting to the CAM-B3LYP functional. Calculations were submitted, setting 6-31g+G(d) as the basis set, including the solvent effect (DCM) according to the conductor-like polarizable continuum model (CPCM) [62]. All spectrophotometric and fluorimetric titrations were conducted in ETN aqueous buffer solutions, pH = 7.4, prepared by diluting concentrated stock solutions of the two dyes (DMSO, c = 1.0 mM) in the buffer, allowing to reach a concentration in the micromolar range (1–2 µM) and keep the final DMSO concentration (v/v) < 1%. In the case of spectrofluorimetric titrations, neutral grey filters were put in the excitation line to dampen the intensity of light and avoid the possible photoisomerization of the investigated compounds subject to repeated irradiation. The excitation wavelength was chosen as the maximum of the absorption spectrum of the free molecule (Aλexc < 0.15). Titrations were then performed by adding increasing amounts of nucleic acid stock solutions (c ≈ 2 mM, added volumes in the µL range) to the aqueous solution of the studied dye having a starting volume of 2 mL. The total volume of nucleic acids added at the end of the titration was 1.4 mL. After mixing polynucleotides with the investigated compounds at every addition, spectra were recorded after waiting a standard time of 5 min allowing the equilibrium to be reached in the cuvette. The saturation and establishment of a dominant mode of binding were reached in excess of tRNA or ct-DNA r ≤ 0.005 (r = [compound]/[nucleic acid]). Each absorption spectrum was multiplied for the relative dilution factor, while emission spectra were corrected by taking into account the changes in absorbance at the excitation wavelength after every addition. Fluorescence data were processed employing non-linear fitting to the Scatchard equation (McGhee–von Hippel formalism) [63], giving values of the ratio of n = [bound compound]/[polynucleotide phosphates] in the range of 0.1–0.2. For a straightforward comparison, all Kass values were re-calculated at fixed n = 0.2, allowing satisfactory correlation coefficients (>0.99) to be calculated. The appraisal of fluorescence quantum efficiencies (QE) for the tRNA/compound or ct-DNA/compound complexes was then carried out by comparison of the emission spectra of the free ligand (AreaF,free ligand), used as internal standard, and that of the bound molecule recorded in excess of nucleic acid at the end of the titration corrected for the fraction of absorbed light (AreaF,complex), according to the following equation: . A549 (CCL-185™) human alveolar basal epithelial adenocarcinoma cells and HT-29 (HTB-38™) human colorectal adenocarcinoma cells (ATCC, Manassas, VA, USA) were cultured in a DMEM medium containing 10% (v/v) heat-inactivated FBS and Penicillin 10,000 U per mL/Streptomycin 10 mg per mL. The cell concentration was monitored by Trypan blue dye staining using an automated cell counter (Invitrogen™ Countess™, Thermo Fisher Scientific, Waltham, MA, USA). The MTT assay was used to study the effect of the pPy-π2 and pQ-π2 compounds on cell proliferation. 2 × 103 A549 and HT-29 cells were seeded in Falcon® 96-well clear flat-bottom microplates (Becton, Dickinson and Company, Franklin Lakes, NJ, USA) with 200 µL of DMEM medium. After 24 h of incubation, the medium was replaced with 198 µL of fresh DMEM, and 2 µL of different dilutions of the pPy-π2 and pQ-π2 compounds stock solution (10 mM in DMSO) were added into each well to reach concentrations ranging from 10 to 0.001 μM in quadruplicate. A quadruplet was kept as control (200 µL of DMEM medium), and another quadruplet was used to take into account the contribution of DMSO (vehicle control 198 µL of DMEM medium + 2 µL of DMSO). After 72 h of incubation in a humidified atmosphere with 5% CO2 at 37 °C, 20 µL of a 5 mg/mL MTT dye solution was added to each well to reach a final concentration of 0.5 mg/mL. The cells were then incubated in a humidified atmosphere with 5% CO2 at 37 °C for 3 h to allow the formation of formazan crystals, which were subsequently dissolved in 150 µL of DMSO at 37 °C for at least 30 min. After a brief mechanical shaking of the microplates, the optical density at 570 nm was determined using a microplate reader (Beckman Coulter DTX880, Beckman Coulter, Inc., Brea, CA, USA). Cell viability was expressed as the optical density percentage in treated cells compared with vehicle controls, assuming the absorbance of controls was 100% (absorbance of treated wells/absorbance of control wells × 100). All measurements were performed in two independent experiments. A total of 1500 A549 cells were seeded on round glass coverslips previously sterilized by 30 s of immersion in 70% ethanol, rinsed with sterile phosphate buffer saline (PBS), and placed in a Falcon® 24-well clear flat-bottom multiwell cell culture plates (Becton, Dickinson and Company, Franklin Lakes, NJ, USA). The cells were then incubated for 45 min in a humidified atmosphere with 5% CO2 at 37 °C, and subsequently, 500 µL of DMEM medium was gently added to each well. After that, cells were incubated for 24 h under canonical culture conditions (humidified atmosphere with 5% CO2 at 37 °C). Then, 2 µL of compound solution diluted in 1000 µL of DMEM at the final concentration of 10 μM was then administered to the cells and incubated for 2 h in a humidified atmosphere with 5% CO2 at 37 °C. In the case of the DNase and RNase digestion experiments, stained cells were then rinsed with PBS, fixed in 4% paraformaldehyde for 20 min in the dark, and afterward permeabilized by 0.5% Triton X-100 for 2 min at room temperature. After rinsing again twice with PBS, one-third of the wells were treated with 100 μg mL−1 RNase A and one-third with 100 μg mL−1 DNase I, while PBS was added to the remaining cells to set up a control experiment. All of the cells were then incubated at 37 °C in 5% CO2 for 1 h. After one last washing with PBS, coverslips were mounted onto slides with Vectashield® Vibrance™ Antifade Mounting Medium (Vector Laboratories Inc., Newark, CA, USA). As for the colocalization experiments, cells on round glass coverslips stained with the investigated compounds were then rinsed with PBS, and 1000 µL of MitoTracker™ Green FM Dye in PBS at a final concentration of 200 nM was administered to the cells and incubated for 30 min. After this time, cells were rinsed twice with PBS and fixed in 4% paraformaldehyde for 20 min at room temperature. After washing with PBS, samples were mounted, and nuclei were stained with Vectashield® Vibrance™ Antifade Mounting Medium containing 4′,6-diamidino-2-phenylindole (DAPI) (Vector Laboratories Inc., Newark, CA, USA). Image acquisition was performed by using a fluorescence microscope (Eclipse TE2000-S, Nikon, Tokyo, Japan) equipped with the F-View II FireWire camera (Olympus Soft Imaging Solutions GmbH, Münster, Germany) and using CellF Imaging Software (Olympus Soft Imaging Solutions GmbH, Münster, Germany). Merged images of the compounds and MitoTracker™ Green FM Dye were analyzed using the ImageJ software (version 1.53t) utilizing the JACoP plugin to calculate Pearson’s and Manders’ Coefficients [49].

PMC10003337

Fátima Carvalho,Manuel Aureliano

Polyoxometalates Impact as Anticancer Agents

06-03-2023

polyoxometalates,polyoxovanadates,polyoxotungstates,cell viability,cell cycle,drugs,cancer

Polyoxometalates (POMs) are oxoanions of transition metal ions, such as V, Mo, W, Nb, and Pd, forming a variety of structures with a wide range of applications. Herein, we analyzed recent studies on the effects of polyoxometalates as anticancer agents, particularly their effects on the cell cycle. To this end, a literature search was carried out between March and June 2022, using the keywords “polyoxometalates” and “cell cycle”. The effects of POMs on selected cell lines can be diverse, such as their effects in the cell cycle, protein expression, mitochondrial effects, reactive oxygen species (ROS) production, cell death and cell viability. The present study focused on cell viability and cell cycle arrest. Cell viability was analyzed by dividing the POMs into sections according to the constituent compound, namely polyoxovanadates (POVs), polyoxomolybdates (POMos), polyoxopaladates (POPds) and polyoxotungstates (POTs). When comparing and sorting the IC50 values in ascending order, we obtained first POVs, then POTs, POPds and, finally, POMos. When comparing clinically approved drugs and POMs, better results of POMs in relation to drugs were observed in many cases, since the dose required to have an inhibitory concentration of 50% is 2 to 200 times less, depending on the POMs, highlighting that these compounds could become in the future an alternative to existing drugs in cancer therapy.

Polyoxometalates Impact as Anticancer Agents Polyoxometalates (POMs) are oxoanions of transition metal ions, such as V, Mo, W, Nb, and Pd, forming a variety of structures with a wide range of applications. Herein, we analyzed recent studies on the effects of polyoxometalates as anticancer agents, particularly their effects on the cell cycle. To this end, a literature search was carried out between March and June 2022, using the keywords “polyoxometalates” and “cell cycle”. The effects of POMs on selected cell lines can be diverse, such as their effects in the cell cycle, protein expression, mitochondrial effects, reactive oxygen species (ROS) production, cell death and cell viability. The present study focused on cell viability and cell cycle arrest. Cell viability was analyzed by dividing the POMs into sections according to the constituent compound, namely polyoxovanadates (POVs), polyoxomolybdates (POMos), polyoxopaladates (POPds) and polyoxotungstates (POTs). When comparing and sorting the IC50 values in ascending order, we obtained first POVs, then POTs, POPds and, finally, POMos. When comparing clinically approved drugs and POMs, better results of POMs in relation to drugs were observed in many cases, since the dose required to have an inhibitory concentration of 50% is 2 to 200 times less, depending on the POMs, highlighting that these compounds could become in the future an alternative to existing drugs in cancer therapy. The application of metals such as platin (Pt), lithium (Li), tungsten (W), gold (Au), and vanadium (V), among others, within chemical species, complexes, compounds and/or nanoparticles in biology has been a rapidly growing branch of science [1,2,3,4,5,6,7]. Besides platinum compounds, bio-active metal-based complexes, clusters such as gold compounds and polyoxometalates (POMs), and metal-based nanoparticles have shown anticancer, antiviral, and antibacterial activities, among others [1,2,3,4,5,6,7,8,9,10,11,12,13]. Regarding biomedical applications, the number of articles on POMs has tripled in the last decade [10], as illustrated by the well-studied polyoxovanadates (POVs) [14,15,16,17,18]. In fact, POMs are known to target several proteins such as aquaporins and P-type ATPases [11,13], although many other proteins and/or enzymes involved in many biochemical processes have been proposed to be affected [14,15,16,17,18,19]. The isopolyoxovanadate decavanadate (V10) is perhaps the most widely studied POV in biology, affecting several biochemical and cellular processes [14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]. Polyoxometalates (POMs) are oxoanions of transition metal ions, such as V, Mo, W, Nb, and Pd, forming a variety of structures with a wide range of applications [10,12,15,16]. They may also include other elements in their structure such as P (phosphorus) or As (arsenic), among others, and may have one of the main metallic oxoanions absent and/or replaced by other metals, such as Co (cobalt) or Mn (manganese), resulting in versatile structures (Figure 1), which give them a wide variety of chemical and physical properties [21]. From the structure of a type of POM (polyoxometalate), such as Keggin or Dawson, (Figure 1D1–3,E1), it is possible to find lacunar derivatives, through the removal of one or more metal oxoanions. There are other compounds that can be formed from the structure of a type of Keggin POM, e.g., the sandwich type (Figure 1E2), which generally have two trilacunar anions separated by a belt of metallic cations. In addition to the wide variety of chemical and physical properties, as mentioned before, this diversity of structures gives polyoxometalates numerous applications in several areas, such as environmental, chemical and industrial. Their effects are well known, mainly in catalysis, prevention of corrosion, and macromolecular crystallography, among others. Their usefulness in biomedicine [17,34,35] is also highlighted, namely through their antiviral [36,37,38] activity, where in the last two years, in the face of the world pandemic due to the SARS-CoV virus (severe acute respiratory syndrome coronavirus), studies have been carried out in an attempt to use POMs to help in fighting COVID-19 [39]. They are still useful in antitumor activities [40,41,42,43,44], and are antibacterial [16] and anti-inflammatory [45]. Additionally, they can also be used in biomedical engineering [46,47] in order to improve and develop innovative approaches to be applied in the prevention, diagnosis and therapy of diseases such as Alzheimer’s [48,49,50] and diabetes [51], where they tend to be demonstrated as potential drugs. In fact, the pharmacological action of POMs has sparked interest in them being potential candidates for therapeutic applications. Since the beginning of the 21st century, and particularly recently, Aureliano’s research group and collaborators have been publishing review papers, editorials, chapters and regular papers regarding metal complexes and/or POMs biological functions and their applications [10,15,16,18,19,21,22,23,26,52,53,54,55,56]. Herein, POMs biological effects were further highlighted as possible anticancer agents in the near future. Among these effects, even though studies are scarce and the mechanisms of action are unclear, the cell cycle is particularly focused on. Still, POMs may thus be used as a potential strategy in the future as antitumor drugs with specific actions, which suggest the blockage of various cellular mechanisms such as the cell cycle. Of the selected articles, 18 compounds were found under study, belonging to four types of POMs, depending on their fundamental compound: POVs (polioxovanadates, polyoxometalates containing vanadium); those containing molybdenum (POMos, polyoxomolybdates); the POMs containing palladium (POPds, polyoxopaladates); and finally those containing tungsten (POTs, polyoxotungstates). Starting with the POVs it was found that: (1) compounds with the molecular formula Na4Co6V10O28.18H2O (abbreviation CoV10), Na3(12H2O)H3V10O28.2H2O (abbreviation NaV10) an isopolyoxometalate with a decavanadate (V10) a well known type of structure [57]; (2) the POV with the formula K12[V18O42(H2O)]·6H2O (abbreviation V18) being a vanadium [58] with a Keggin structure; and (3) the compound 6{V5O9Cl(COO)4} (abbreviation VMOP-31) [59] with a Lindqvist’s type of structure. Following the molybdenum compounds, we found the compound with the molecular formula K2Na[AsIIIMo6O21(O2CCH2NH3)3]·6H2O, also designated in the article by compound 1, in order to facilitate [60], better known as arsenomolybdate with an Anderson–Evans structure, involved in a silica nanosphere (K2Na[AsIIIMo6O21(O2CCH2NH3)3]·6H2O (abbreviation POM@SiO2) [61]; K2Na2[γ-Mo8O26(O2CCH2NH3)2]·6H2O, designated as compound 2, which are heteropolymolybdates [62]; with a Strandberg structure the [{4,4′-H2bpy}{4,4′-Hbpy}2{H2P2Mo5O23}].5H2O [63]; and finally, the [(Cu(pic)2)2(Mo8O26)]·8H2O [64]. There are also PONMs or polyoxopaladates, with the molecular formulas and respective abbreviations: Na8[Pd13As8O34(OH)6]·42H2O (abbreviation Pd13), Na4[SrPd12O6(OH)3(PhAsO3)6(OAc)3]2NaOAc·32H2O (abbreviation SrPd12), Na6[Pd13(PhAsO3)8]·23H2O (Pd13L), Na12[SnIVO8Pd12(PO4)8]·43H2O (abbreviation SnPd12), Na12[PbIVO8Pd12(PO4)8]·38H2O (abbreviation PbPd12) [65]. Lastly, the POMs that have the compound tungsten (POTs). We started with K7Na3[Cu4(H2O)2(PW9O34)2]20H2O (abbreviation PW9Cu) which has a Dawson structure [33]. Following a homochiral polyoxometalate {CoSb6O4(H2O)3[Co(hmta)SbW8O31]3}15−(1, hmta = hexamethylenetetramine) [66]; a tri-organic germanotungstate polyoxometalate-tin-substitute [67] {(n-Bu)Sn(OH)}3GeW9O34]4−·26H2O PAC-320 that has been shown to be an inhibitor of histone deacetylase (HDACi) [68] and has a Keggin structure. Finally, the POT {[Na(H2O)4][Na0.7Ni5.3(imi)2(Himi)(H2O)2(SbW9O33)2]} 10H2O, designated as compound 1 and H3[(CH3)4N]4[Na0.7Co5.3(imi)2(Himi)(H2O)2(SbW9O33)2] 12H2O, also known as compound 2 [67], whose structure is a hybrid Keggin sandwich. The 18 compounds are represented below, in the form of a table, with the division of the POMs by main component and in the order in which they appear in the periodic table, i.e., vanadium (V); molybdenum (Mo); palladium (Pd) and tungsten (W), according to their increasing atomic number, as presented above. Each compound is presented in Table 1 with its designation, that is, its molecular formula or abbreviation when existing; the structure with the respective illustration; the type of structure; bibliographic reference and POM of the 13 selected articles (Table 1). In these articles, several types of cancer were studied, and sometimes an article analyzed more than one type of cancer. These were namely gastric, colon, liver, lung, ovary, breast, prostate, leukemia, osteosarcoma, neuroblastoma and human hepatocellular carcinoma (Figure 2). Through the analysis of Figure 2, it can be observed that the most studied types of cancer were lung and breast cancer, with six articles each, followed by liver cancer, covered in four articles. In the 13 articles, various effects of the selected POMs were analyzed, such as protein expression, mitochondrial effects, reactive oxygen species (ROS) production, cell cycle arrest, cell death, cell viability and anticancer activity, in vivo, or the antibacterial activity (Figure 3). As seen in Figure 3, not all articles addressed all the effects of POMs, and there were effects addressed only in one article, such as antibacterial activity, analyzed in Escherichia coli (E. coli) regarding the effects of [(Cu(pic)2)2(Mo8O26)].8H2O, where it was shown to be quite effective with a minimum inhibitory concentration of approximately 135 μg/mL, which is the lowest value reported so far for any octamolybdate-based POM [64]. ROS production was also analyzed, as well as mitochondrial effects and protein expression in two, three and eight articles, respectively (Figure 3). The production of ROS was verified in two articles, one of them with compounds containing noble metals (PONMs) [65]. The determination of the levels of superoxide ion produced was verified after 2 and 4 h of treatment. For this purpose, the dihydroethidium (DHE) method was used to detect cytosolic O2, which is not fluorescent but, being oxidized to O2−, emits fluorescence. Through the method presented above, it was observed that the polyoxopaladate Pd13 induced about 30% of increased production of superoxide ion (O2−) at 4h after treatment. Furthermore, the polyoxopaladates Pd13, SnPd12 and PbPd12 induced oxidative stress of HL-60 cells (human leukemia cells) resulting in an increase in the total production of reactive oxygen species [65]. Among the three articles selected for those that studied mitochondrial effects, the present study focused on the use of PAC-320. It was observed that with its use, in DU145 cells (human prostate tumor cells) there was a loss of MMP (mitochondrial membrane potential—ΔΨm). Consequently, cytochrome c is released in the cytosol, stimulating caspases that are associated apoptosis. Hence, it was deduced that apoptotic cell death was caused by the mitochondria-mediated pathway [68]. The same compound discussed above was one of the eight that referred to the study of protein expression. PAC-320 also inhibits the enzymatic activity of HDAC (histone deacetylases) 1, 2, 4, 5 and 6, but to a lesser extent HDAC 3 [68]. Only three articles performed in vivo studies in order to confirm or refute the anticancer activity of POMs. Of these three studies, Mus musculus (mice) were selected as an animal model. In one of these articles, nude mice with DU145 lineage (human prostate cancer cell line) were selected [68]. After this, these mice were divided into groups where each group was injected with a different compound. One group received a solution containing the compound PAC-320 (50 mg/kg) and another NaB (sodium butyrate) (1 g/kg). Others received SAHA (suberoylanilide acid, Vorinostat, an HDACi inhibitor, which was approved in October 2006 by the US Food and Drug Administration (FDA) for the treatment of cutaneous manifestations of T-cell lymphoma (CTCL) in patients with progressive, persistent or recurrent disease after two systemic therapies) [70], with a concentration of 40 mg/kg. All groups were injected daily for 16 days [68]. Through the results obtained, it was observed that the group treated with PAC-320 did not show a noticeable effect on body weight. In this group, the inhibition of the growth of prostate tumors was on average 69.2% compared to the control, treated with the vehicle alone (DMSO), while treatment with the drug SAHA or the compound NaB was inhibited by 55.5% and 64.2%, respectively. The weight of the tumors was reduced on the 17th day, when they were dissected [68]. To our knowledge, the precise mechanism of action responsible for the prostate tumor inhibition is yet to be clarified. In fact, although several putative mechanisms against cancer were recently reviewed [10,15,18], how the POM chemistry is specifically affecting the growth inhibition of prostate tumors needs further understanding. In another study, over 12 consecutive days, mice with H22 liver tumor (Hepatoma-22, mouse liver tumor cell line) were administered treatments intraperitoneally, one with a saline solution (negative control group); cisplatin (CDDP or cis-diaminodichloroplatinum or cis-Pt) was used as the positive control group at a dose of 3 mg/kg. CDDP is a well-known platinum-based chemotherapy drug that is used to treat many types of cancer, including sarcomas, some carcinomas (e.g., small cell lung cancer and ovary cancer), lymphomas and germ cell tumors. Others received the studied compound, VMOP-31, at a dose of 12.5, 25 and 50 mg/kg [59]. On the 14th day, when they were excised, VMOP-31 led to a decrease in tumor weight compared to the saline group, but similar to that of the cisplatin group. Tumor inhibition rates of VMOP-31 at doses of 12.5, 25 and 50 mg/kg were determined to be 32.7, 39.6 and 56.4%, respectively [59]. Cisplatin has a tumor inhibition rate of 58.4%, which is comparable to the VMOP-31 tumor inhibition rate at 50 mg/kg. In this study, it was also observed that the body weight of the mice increased continuously, except for those in the cisplatin group, where the weight decreased continuously, which indicates that cisplatin has side effects [59]. Finally, we identified a study where 10 mice were randomly assigned and injected with mouse liver tumor cells (Hep-A-22) on their backs [57]. After 7 days of tumor cell administration, the mice were treated by intraperitoneal injections of CoV10 solutions with increasing concentrations (2, 6 and 12 mg/kg) [57], which were continued for 14 days. On the other hand, control mice were treated with saline solution for 2 weeks, under the same conditions that were used for animals treated with the CoV10 compound. As a result, it was observed that the average tumor weight with a concentration of 2 mg/kg with the CoV10 solution was 1.750 g [57], about 1.40-times lower than the average weight of the control group (2.440 g). As for the control group, compared with the value obtained (1.490 g) at a concentration of 12 mg/kg, a value about 1.6-times lower was observed. Comparing the control to a dose of 20 mg/kg of the approved drug, 5-Fu (fluorouracil is a widely used medicine in oncology, being therefore a base for a large part of current chemotherapy regimens to treat a wide spectrum of cancers), the mean tumor weight value was 0.477 g, i.e., 5.1-times lower. Note that here the dose used is higher than the dose used with the POM. Perhaps the higher dose of the drug justifies it being more harmful in reducing the weight of the mice, proving to be more toxic [57]. Furthermore, from the animal body weight data, it was found that CoV10 could decrease body weight less than the 5-Fu dose, thus showing less toxicity. It can also be seen that the inhibiting effect of the medium dose is better than that of the higher dosage (12 mg/kg). The reason may be that higher dosages of CoV10 can affect the function of immune organs, leading to decreased immune capacity [57]. However, several studies demonstrate that the oral administration of POMs is presumed safe and poses a low risk of potential health risks. Furthermore, for potential antidiabetic POTs it was concluded that the hepatotoxic and nephrotoxic effects could be considered as mild. Thus, besides POMs presenting higher antitumor activity and lower toxicity in in vitro and in vivo experiments, they have also been described as promising agents in the treatment of infectious diseases, diabetes and Alzheimer’s disease [69,71,72,73]. As discussed above, it was found that 13 articles analyzed cell death and that all selected articles refer to the effects of POMs on cell viability, and where cell cycle arrest was given (Figure 3). In these articles, the IC50 values (POM concentration that inhibits 50% of cell viability) of the various POMs selected in each article in the respective cell lines studied were analyzed. To understand which POM had the lowest IC50, a comparison was made, through a table containing the IC50 of the various compounds and the strains in which each one was applied, after exposure of 24, 48 and 72 h to POVs, POMos, POPds and POTs. The cell lines within each division were ordered alphabetically from A–Z (Table 2). Five vanadium POMs were studied, from three POVs that were analyzed in eight cell lines (Table 2, Figure 4). Among these POVs, it was observed in the MCF-7 lineage (human breast cancer cell line) that the best IC50 was 0.53 µM at 72 h, achieved with the POV VMOP-31 [59] and corresponding to the best value of the polyoxovanadates. When comparing this value to V18 (45.95 µM) [58], in the same strain, whether at 24, 48 or 72 h, it always presents better results, being about 30 times (more potent) for 24 h. With CoV10, the SMMC-7721 lineage (human papillomavirus-related endocervical adenocarcinoma cell line) resulted in a value of <0.26 µg/mL [57], which proved to be about 73- to 196-times more efficient than NaV1O compounds (18.90 µg/mL) and Co(Ac)2 (50.90 µg/mL) [57], such as in SK-OV-3 (human ovarian cancer cell line). For this strain, the best value is <0.24 µg/mL, when compared to the compounds NaV10 (9.56 µg/mL) and Co(Ac)2 (44.90 µg/mL), that is, CoV10 [57] was about 40- to 187-times more efficient than these compounds. These values cannot be compared with those of other vanadium compounds, since the measurement units are not the same. In polyoxometalates containing molybdenum, six compounds were analyzed in six cell lines (Figure 4). It is observed in Table 2 that the A549 line (human lung cancer cell line) showed the best IC50 value to be 25 µM at 24 h, with the hybrid compound of structure Anderson–Evans (Figure 1G) and formula [(Cu(pic)2)2(Mo8O26)]·8H2O (Table 1). This same compound also showed a similar value (21.56 µM) in the HepG2 lineage (Human liver cancer cell line) at 48 h. Furthermore, in breast cancer, this compound showed a similar inhibition potency (24.24 µM) [71]. In the MCF-7 lineage, the compound K2Na[AsIIIMo6O21(O2CCH2NH3)3]·6H2O (POM@SiO2) with the same structure as the previous one, but inserted in silica nanoparticles (see structure in Table 1), presented the best IC50 value (1.70 µg/mL) at 72 h [61], however this cannot be compared, as they have different measurement units. Of the five palladium-containing PONMs [65], all were studied in the same cell line SH-SY5Y (three times cloned subline from neuroblastoma cell line SK-N-SH (ATCC HTB-11). It was verified that the PONM that showed a better value both at 24 and 48 h was Pd13 (Table 1), with values of 7.20 and 4.40 µM, respectively, when compared to their hybrids containing phenyl groups (63.80 and 21.40 µM for Pd13L, 75.80 and 76.70 µM for SrPd12) [65], i.e., between 5 and 9 times for the first and between 11 and 17 times for the second, as the first was less efficient. Regarding tungsten-containing compounds with effects on cell viability, eight compounds addressed in 15 different cell lines were found (Table 2, Figure 4). With POTs, in the A2780 and A2780cis lineage (human ovarian cancer cell line and the same lineage but resistant to cisplatin), the best values were obtained at 72 h with the compound [Co(H2O)6{CoSb6O4(H2O)3[Co(hmta)SbW8O31]3}]13− which presents a homochiral, sandwich-like structure (Table 1), and were, respectively, 0.77 and 4.35 µM [66]. This was 6-times more efficient in the non-resistant cell line when compared with lines resistant to cisplatin treatment. In the AGS lineage (human stomach cancer cell line), the best value was 1.42 µM [67], for the hybrid compound that is a part of the sandwich, C25N10Na0.7Co5.3O76Sb2W18, and was the best result in this group of POMs. On the other hand, on the BGC-823 cell line (human papillomavirus-related endocervical adenocarcinoma cell line), the best IC50 was found at 48 h with the pure inorganic compound {Sb8W36} [67]. For the transformed human embryonic kidney cell line (HEK293T), the hybrid C25N10Na0.7Co5.3O76Sb2W18 had the value of 103.09 µM at 48 h [67] and in the line OVCAR-3 (human ovarian cancer cell line), the best value was obtained at 72 h with POM [Co(H2O)6{CoSb6O4(H2O)3[Co(hmta)SbW8O31]3}]13− being 1.78 µM [66]. Comparing the effects of tungsten-containing POMs on the AGS, BGC-823 and HEK293T cell lines, studied at 48h, it was found that the POTs are more efficient (in ascending order) in the AGS (1.42 µM), BGC-823 (8.68 µM) and HEK293T (103.09 µM) [67]. Thus, compound 2 is 73-times more potent in the transformed human embryonic kidney cell line when compared to the human stomach cancer cell line. Relative to the first POM referred to, at 72 h, a 2-fold greater efficacy was observed in the human ovarian cancer cell line A2780 (0.77 µM), compared to OVCAR-3 (1.78 µM) [66]. It was also found in the A549 lineage (human lung tumor lines) that the most effective compound was [Co(H2O)6{CoSb6O4(H2O)3[Co(hmta)SbW8O31]3}]13− with a value of 12.75 µM [66] at 72 h, which was lower when compared to a value of 39.75 µM [67], found at 48 h, with the compound C25N10Na1.7Ni5.3O82Sb2W18. However, as previously observed in studies where they tested at 24, 48 and 72 h (increasing incubation time), the IC50 value tends to decrease. In order to analyze whether antitumor drugs or POMs would be the most efficient, it was verified which drugs were tested in these strains and their respective IC50 values (Table 3). In Table 3, the lowest value among the approved drugs was 14.85 µM in the U937 strain, at 24 h, using the drug ATRA. While in relation to compounds, the lower value belongs to NaB, being 1.20 µM in the DU145 strain, at 72 h, which is about 14-times lower than the lowest value of the tested drugs. As for the cell viability of medically approved drugs or compounds, only cell lines of human origin were used. When comparing the cell viability of clinically approved drugs and POMs, it was observed, for example, a value of 49.79 µM using the drug MTX [60] (Table 3), and a value of 1.53 µM using the compound VMOP-31 [59], in the MCF-7 strain (breast cancer cell line) at 24 h (Table 2). It was verified that the IC50 value of the POM is lower, suggesting that the effects of POMs can overcome those of drugs. In fact, the dose necessary to have an inhibitory concentration of 50% is about 33-times lower than the dose that will be needed with a clinically approved drug. Some drugs were tested in the strains mentioned above, such as ATRA (all-trans retinoid, also known as tretinoin), which is a drug used for the treatment of acne and acute promyelocytic leukemia (PML), having been tested in the HL-60 and U937 [60]. CDDP was tested on SH-SY5Y [65], MG-63 [33], AGS and BCG-823 [67] strains. The drug MTX (methotrexate), formerly known as amethopterin, a chemotherapeutic agent and immune system suppressor, used to treat cancer (cancer of the breast, leukemia, lung cancer, lymphoma, gestational trophoblastic disease and osteosarcoma), autoimmune diseases (i.e., psoriasis, rheumatoid arthritis and Crohn’s disease) and in ectopic pregnancy and for medical abortions, was analyzed here in the lines HepG2, A549 and MCF-7 [63]. It was found with the drug ATRA that the lowest IC50 value was 14.85 µM in the U937 strain, whereas a value of 20.76 µM was found in the HL-60 strain [60], both at 24 h. Cisplatin, at 24 h, is more effective in the SH-SY5Y strain (28.40 µM) [65], when compared to MG-63 (43.00 µM) [33]. On the other hand, at 48 h the lowest value was 5.78 µM in BCG-823 [67], conversely to the SH-SY5Y (11.60 µM) and AGS (17.44 µM) strains [67]. Finally, for the drug MTX at 24 h, the effect in the lines by order of increasing IC50 were A549 (26.93 µM), HepG2 (42.03 µM) and MCF-7 (49.79 µM) [63]. When comparing TSA (trichostatin A, an organic compound that serves as an antifungal antibiotic and selectively inhibits the histone deacetylase (HDAC) enzyme families of class I and II mammals) with NaB, in the LNCaP and DU145 strains at 72 h, it is concluded that in both strains the NaB compound has the advantage, showing values of 3.46 and 1.20 µM, compared to 98.14 and 59.45 µM [68] for TSA, for the same strains. It was also found that the antitumor activity of V18 was stronger than that of 5-Fu at 48 h for concentrations of 250 and 500 µM [58]. Moreover, taking in consideration the high IC50 values for POMs at normal cells compared to cancer cells, it is established that these compounds showed high selectivity towards the cancer cell lines [69]. Therefore, POMs selectively target cancer cells while sparing healthy cells, showing themselves to be promising agents in the treatment of cancer. In fact, POMs are expected to develop into the next generation of anticancer drugs [15,73]. Similarly to the cell viability discussed above, the effects of POMs on the cell cycle were also discussed in all articles selected (Figure 5). Particularly within the effects of compounds on the cell cycle, we wanted to highlight where each one interrupts the cycle. In Figure 5, the percentage of numbers of articles in which each phase of the cell cycle stagnated was summarized, referring to each POM and lines in which they were tested. Table 4 shows a better precision of the action of POMs in the arrest of the cell cycle of the different lineages studied. It was also verified that there are lines in which, depending on the POM used, the cell cycle phase where they stop can be different, such as the SMMC-7721 and MCD-7 cell lines, which are in the G2/M phase and in the S phase, respectively. Globally, 56% of the POMs stopped the cell cycle in the S phase (red), which is during DNA synthesis, whereas 36% blocked the G2/M phase (green), that is, when the transition from interphase to onset of mitosis occurs. While the G1 phase is characteristic of the maturation in proteins and RNA (ribonucleic acid) synthesis, it was still only 8% of the POMs, namely in the compound K2Na[AsIIIMo6O21(O2CCH2NH3)3]6H2O [60], represented with the color yellow, that arrested the cell cycle at this stage. It is also verified that different POMs can stop the cell cycle in several phases (Figure 5). In order to analyze in detail which type of POM affected the different phases of the cell cycle in the respectively studied lines, a table was prepared, with the division of the phases of the cell cycle that were blocked by corresponding POMs and respective cell lines (Table 4). It should be noted that in the articles where several POMs were studied, cell cycle arrest was only tested for the compound that showed the greatest efficacy. Likewise, of the cell lines analyzed, only those that had presented the best efficacy values were focused on, to verify cell arrest. Therefore, in Table 4, when in relation to Table 2, we verified a smaller number of POMs and cell lines analyzed, namely, three POVs in two cell lines and six POMos in four lines, with the majority being the study of the A549 line, human lung cancer cell line. There were only three POPds for the neuroblastoma line (SH-SY5Y), and finally we found four POTs for seven cell lines, all distinct from each other (Table 4). As estimated, in these studies the concentrations at which compounds have an effect on the cell cycle are close or below the IC50 previously determined and are described in Table 2. As can be seen, the S phase is predominant under the action of the POMs with 14 of them, followed by the G2/M phase with nine polyoxometalates, and two in the G1 phase. It is also verified that VMOP-31 is the only one that has the ability to stop the cell cycle of SMMC-77221 cells in two distinct cell phases, namely S and G2/M [59]. On the other hand, it is also clear that the breast cancer cell line (MCF-7) on several compounds has its arrest in the G2/M phase, with the exception of the molybdenum compound involved in silica nanoparticles (K2Na[AsIIIMo6O21(O2CCH2NH3 )3]·6H2O (POM@SiO2)), stopping in the S phase [61]. Most of the proposed modes of action for antitumor POMs were recently reviewed [15]. Among these mechanisms, it was shown that POMs are able to affect DNA by interacting directly with it [15,58]. POMs were also suggested to cleave the phosphodiester bond and to affect DNA synthesis [15,74]. However, to our knowledge the processes responsible for the POMs effects that cause cell cycle arrest, as well as the effects in the cell cycle checkpoints, are unknown. For instance, the precise mechanism of action responsible for the POMs effects in DNA synthesis and/or in mitosis during the cell cycle process still needs to be deduced and needs further clarification. In this review paper, bibliographic research was carried out with the keywords “polyoxometalates” AND “cell cycle”. Thirteen articles were selected on the effect of POMs with anticancer activities, namely in gastric, colon, liver, lung, ovary, breast, prostate, leukemia, osteosarcoma, neuroblastoma and human hepatocellular carcinoma. The types of cancer in which the articles most focused on were lung and breast cancer, with six articles each, followed by liver cancer, covered in four articles. The effects of POMs on cancer cells can be diverse, such as their interaction in the cell cycle, protein expression, mitochondrial effects, ROS production and cell viability. In the present study, we focused mainly on cell viability and cell cycle arrest, since all selected articles analyzed these two effects. Cell viability was analyzed by dividing the POMs into sections according to the constituent compound, namely POVs, POMos, POPds and POTs. When the IC50 values were compared and sorted in ascending order, it was found that the POV (VMOP-31) at 24, 48 and 72 h presented, respectively, the lowest values of 1.52, 0.63, and 0.53 µM, in the MCF-7 (human breast cancer cell line). In clinically approved drugs, the lowest IC50 value was found to be 5.78 µM in the BCG-823 lineage at 48h using cisplatin. When comparing drugs and POMs, better results of POMs were observed. In many cases, the POMs dose required to have an inhibitory concentration of 50% is 2- to 200-times lower than the dose that would be necessary with a clinically approved drug. Therefore, POMs are future potential candidates for cancer therapeutic applications. In addition to the cell viability, the effect of POMs on cell cycle arrest is highlighted. For the majority of the POMs, cell cycle arrest occurs mostly in the S phase (56%), where DNA synthesis occurs, whereas 36% blocks the G2/M phase. Fewer POMs interfere with the G1 phase (8%), that is, at the beginning of the cell cycle. Although the mechanism of action, directly and/or indirectly, responsible for the POMs cell cycle arrest is still to be deduced and clarified, the scientific evidence described above strengthens the potential use of such metallodrugs in anticancer therapy in the near future.

PMC10003340

Chenggang Wang,Jiajie Zhou,Shengnan Zhang,Xun Gao,Yitao Yang,Jinfeng Hou,Guohu Chen,Xiaoyan Tang,Jianqiang Wu,Lingyun Yuan

Combined Metabolome and Transcriptome Analysis Elucidates Sugar Accumulation in Wucai (Brassica campestris L.)

02-03-2023

wucai (Brassica campestris L.),D-galactose,β-D-glucose,sugar accumulation pathway,interact network

Wucai (Brassica campestris L.) is a leafy vegetable that originated in China, its soluble sugars accumulate significantly to improve taste quality during maturation, and it is widely accepted by consumers. In this study, we investigated the soluble sugar content at different developmental stages. Two periods including 34 days after planting (DAP) and 46 DAP, which represent the period prior to and after sugar accumulation, respectively, were selected for metabolomic and transcriptomic profiling. Differentially accumulated metabolites (DAMs) were mainly enriched in the pentose phosphate pathway, galactose metabolism, glycolysis/gluconeogenesis, starch and sucrose metabolism, and fructose and mannose metabolism. By orthogonal projection to latent structures-discriminant s-plot (OPLS-DA S-plot) and MetaboAnalyst analyses, D-galactose and β-D-glucose were identified as the major components of sugar accumulation in wucai. Combined with the transcriptome, the pathway of sugar accumulation and the interact network between 26 DEGs and the two sugars were mapped. CWINV4, CEL1, BGLU16, and BraA03g023380.3C had positive correlations with the accumulation of sugar accumulation in wucai. The lower expression of BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C promoted sugar accumulation during the ripening of wucai. These findings provide insights into the mechanisms underlying sugar accumulation during commodity maturity, providing a basis for the breeding of sugar-rich wucai cultivars.

Combined Metabolome and Transcriptome Analysis Elucidates Sugar Accumulation in Wucai (Brassica campestris L.) Wucai (Brassica campestris L.) is a leafy vegetable that originated in China, its soluble sugars accumulate significantly to improve taste quality during maturation, and it is widely accepted by consumers. In this study, we investigated the soluble sugar content at different developmental stages. Two periods including 34 days after planting (DAP) and 46 DAP, which represent the period prior to and after sugar accumulation, respectively, were selected for metabolomic and transcriptomic profiling. Differentially accumulated metabolites (DAMs) were mainly enriched in the pentose phosphate pathway, galactose metabolism, glycolysis/gluconeogenesis, starch and sucrose metabolism, and fructose and mannose metabolism. By orthogonal projection to latent structures-discriminant s-plot (OPLS-DA S-plot) and MetaboAnalyst analyses, D-galactose and β-D-glucose were identified as the major components of sugar accumulation in wucai. Combined with the transcriptome, the pathway of sugar accumulation and the interact network between 26 DEGs and the two sugars were mapped. CWINV4, CEL1, BGLU16, and BraA03g023380.3C had positive correlations with the accumulation of sugar accumulation in wucai. The lower expression of BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C promoted sugar accumulation during the ripening of wucai. These findings provide insights into the mechanisms underlying sugar accumulation during commodity maturity, providing a basis for the breeding of sugar-rich wucai cultivars. Wucai (Brassica campestris L. ssp. chinensis var. rosularis Tsen), a subspecies of non-heading Chinese cabbage, is widely grown in the Yangtze-Huai River Basin [1]. Wucai is rich in vitamin C, vitamin B1, and carotene, resulting in it being referred to as a “vitamin vegetable” [2]. Wucai leaves become sweet after undergoing autumn and winter growth, satisfying consumer preference due to their nutritional value and taste [3]. The sweetness of vegetables and fruit depends not only on the total amount of sugar but also on the sugar composition [4]. Sweetness is mainly conferred by sucrose, glucose, and fructose, which contribute differently to the sweetness of vegetables and fruit [4]. In Chinese cabbage, the leafy head is the storage organ and the internal midrib (IM) is the main tissue of sugar accumulation, which possesses the highest content of soluble sugar at harvest [5]. Fructose is the major sugar that accumulates in the internal tissues of Chinese cabbage, followed by glucose [5]. Differences in the sweetness of Cucurbita moschata were attributed to the content and composition ratio of sucrose [4,6]. As fructose tastes sweeter than sucrose and glucose, sucrose metabolism and the ratio of fructose/glucose were promoted in tomato fruits in order to improve the flavor quality [7,8]. The accumulation pattern and concentration of sugar vary with species and are regulated by fruit development [9]. Glucose is the main soluble sugar in mature pitaya fruit, whereas in ripened apricot fruits, glucose and sucrose are the major sugars [10,11]. The contents of sucrose, glucose, and fructose are high in harvested watermelon and mango fruit [12,13]. In melon fruit and sugarcane, sucrose was found to increase steadily with fruit development [14,15]. Sugar accumulation comes mainly from the transport of photosynthetic products, with sucrose being the form of transport in most plants, and a number of key enzymes can be involved in regulating sugar metabolism and, thus, the composition and content of sugars [16]. Sucrose phosphate synthase (SPS), one of the key enzymes in plant sucrose synthesis, catalyzes the production of sucrose as an irreversible reaction and is the rate-limiting enzyme for the synthesis of sucrose [17]. SPS activity is positively correlated with sucrose accumulation [18]. Transcript levels of SPS increased with sucrose accumulation during ripening in watermelon and banana [19,20]. In addition, the expression pattern of SPS in pineapple and potato all showed that its expression was related to sucrose metabolism [21,22]. Sucrose synthase (SUS) catalyzes both the breakdown of sucrose to UDP glucose and the synthesis of sucrose [17]. SUS is also one of the key enzymes for the entry of sucrose into various metabolic pathways, regulating the ability of the crop to metabolize sucrose and the amount of sucrose input [23]. During the development of apple fruit, with the accumulation of sucrose, the expression of MdSUSY2, MdSUSY3, and MdSUSY4 decreased obviously, indicating that SUS mainly played a major role in the decomposition of apple sucrose [24]. The expression of CitSus5 was increasing while that of CitSus6 was gradually decreasing during fruit development in citrus, suggesting that SUS was involved in reversible reactions in citrus, possibly both synthesizing and breaking down sucrose [25]. Invertase (INV), also called sucrase, can hydrolyze sucrose into glucose and fructose. According to the site where the enzyme is present on the cell, INV mainly consists of cell wall convertase (CWINV), vesicle convertase (VINV), and cytoplasmic convertase (CINV) [26]. Based on the optimum PH of the enzyme, CWINV and VINV can be classified as acid convertase (AI), while CINV is a neutral invertase (NI) [26]. Numerous studies showed that there is a significant negative correlation between the activity of INV and sucrose accumulation in fruits [12,22,26,27]. In tomato fruits, CWINV and VINV are encoded by LIN and VI, respectively. LIN5, LIN7, LIN8, LIN9, and VI were upregulated by silencing SWEET7 (Sugars Will Eventually be Exported Transporters) and SWEET14 to increase CWINV and VINV activity [28]. It can be seen that the upregulation of CWINV and VINV increases the activities of AI, thereby promoting the hydrolysis of sucrose. CWINV is typically considered as a sink-specific enzyme, and its activity is usually low in source leaves [29]. However, both MdCWINVs (MdCWINV2 and MdCWINV3) identified in apple had lower expression levels in the fruit than in the leaves, and the transcript levels of MdCWINV2 and MdCWINV3 declined dramatically during maturation [24]. Hexokinase (HK) could catalyze the phosphorylation of hexose, which could catalyze the conversion of glucose into glucose -6- phosphate (glucose -6P), and then enter the glycolytic pathway [30]. Overexpression of the HK was able to cause a significant reduction in the sugar content of plants [31]. Besides INV, SPS, and SUS, another enzyme related to sugar accumulation and metabolism in watermelon fruits is α -galactosidase [32]. Stachyose and raffinose are the main transportation forms of photosynthetic products in Cucurbitaceae plants, which can be decomposed by α -galactosidase to produce sucrose and galactose [33,34]. Cellulase (CL) is an important enzyme complex, mainly consisting of endoglucanase (EG), exoglucanase (CBH), and β-glucosidase (BGL), which hydrolyze cellulose to form glucose [35,36,37]. In previous studies, cellulose was considered to be related to the softening of crops during development [38,39]. Nevertheless, in biomass utilization, CL is employed to hydrolyze cellulose in multiple steps to generate glucose [40]. In studies of sugar accumulation in Chinese cabbage that is more closely related to wucai, it was noted that BraA01gHT4 and BraA03gHT7 were positively correlated with the soluble sugar content (mainly fructose and glucose) of the inner lobe, while BraA03gFRK1, BraA09gFRK3, BraA06gSPS2, and BraA03gHT3 were negatively correlated with sugar content [41]. Furthermore, the high expression of SUS1 was considered to promote the accumulation of fructose and glucose in leaf balls of Chinese cabbage [42]. Sweetness is a typical indicator and characteristic of maturation in wucai. In recent years, metabolomics (including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS)) and transcriptomics (RNA sequencing (RNA-Seq)) have been successfully applied to reveal the mechanism of sugar accumulation in ripening fruits, such as Chinese cabbage, ponkan, and kiwifruit [41,43,44]. However, there are no studies that have reported on sugar accumulation during wucai maturation. A biomarker is a characteristic biochemical index, which can be objectively measured to provide information about the biological process of the organism [45]. Metabonomics pays attention to the changes in small-molecule metabolites in organisms, which provides the possibility for identifying objective biomarkers. Scholars established and analyzed the OPLS-DA model or OPLS-DA-Splot map, and then potential biomarkers could be found in the project based on variable importance in the projection (VIP) score > 1 [46,47]. ROC (receiver operating characteristic curve) and AUC (area under ROC curve) diagnostics were performed using the online software MetaboAnalyst to identify potential biomarkers [46,47]. Combined analyses of the transcriptome and metabolome by LC-MS/MS and GC-MS/MS were conducted herein to investigate the molecular mechanism of sugar transformation in wucai during the maturation process, and the DAMs and related genes were identified. This is the first report on sugar biomarkers and the mechanisms of sugar accumulation with the maturity process of wucai. The results provide a valuable basis and reference for commercial applications and breeding programs for wucai. A growth chamber was used for simulating the growth environment of wucai. To investigate the changes in soluble sugar content in wucai leaves during the growth period, we determined the soluble sugar content at nine sampling periods (Supplementary Figure S1). The results showed that the soluble sugar increased gradually with the growth of wucai from 34 DAP and peaked at 46 DAP (Figure 1A). The time points of 34 DAP and 46 DAP were selected for the determination of D-galactose, glucose, fructose, and sucrose. It was found that the contents of D-galactose, glucose, and fructose increased significantly during the wucai maturation process (Figure 1B,C). The contents of D-galactose, fructose, and sucrose at 46 DAP were 1.40-, 1.16-, and 1.39-fold higher than those at 34 DAP, respectively (Figure 1B,D,E). There were significant differences in glucose between the two periods, reaching 3.58-fold (Figure 1C). Interestingly, at 46 DAP, the ratio of glucose/soluble sugar increased to 5.75% from 2.49% at 34 DAP, compared to D-galactose (Figure 1F,G). Therefore, we considered that these sugars, especially glucose, play vital roles in sugar transformation in wucai. According to the sugar change trend, 34 DAP and 46 DAP were selected as the two periods for further study. To further understand the changes in metabolites in the wucai leaves during sugar transformation, the metabolites at 34 DAP and 46 DAP were detected by LC-MS/MS and GC-MS/MS. The PCA of the metabolomic profiles of the 12 samples showed that the first principal component explained 46% (LC-MS/MS) and 47.2% (GC-MS/MS) of the total variance and distinguished the samples based on the two periods (34 DAP and 46 DAP) (Supplementary Figure S2). A total of 650 and 111 DAMs were identified with p < 0.05 and VIP >1 from the LC-MS/MS and GC-MS/MS analysis, respectively (Supplementary Figure S3). In the LC-MS/MS analysis, compared to 34 DAP, a total of 385 DAMs were upregulated (fold change, log2(FC) > 0) and 265 DAMs were downregulated (log2(FC) < 0) at 46 DAP (Supplementary Figure S3A). The proportion of organooxygen compounds/total DAMs was 12.923%, which was the maximum in any class category (Supplementary Table S1). The organooxygen compounds mainly included 66 carbohydrates and carbohydrate conjugates, nine phenols and polyols, six carbonyl compounds, and three ethers (Figure 2A). The proportion of carbohydrates and carbohydrate conjugates/total DEMs accounted for 10.15%, which was significantly higher than those of the other metabolites according to the sub-class category (Supplementary Table S1). The metabolomic analysis showed that the DAMs were mainly enriched in carbohydrates and carbohydrate conjugates. There were 35 upregulated and 31 downregulated DAMs (Figure 2B). The GC-MS/MS analysis showed that there were 43 upregulated and 68 downregulated DAMs at 46 DAP compared to at 34 DAP (Supplementary Figure S3B). Only 13 DAMs (seven upregulated and six downregulated) were classified as carbohydrates and carbohydrate conjugates (Supplementary Table S2 and Figure 2C). To identify the major pathways of DAMs related to sugar accumulation in wucai leaves, KEGG enrichment analysis was conducted. The p-value in the pathways indicates the significance and Rich factor derived from ratio of DAMs/total metabolite number in the pathway. The LC-MS/MS analysis showed that DAMs related to sugar accumulation were notably enriched in the pentose phosphate pathway (ath00030), galactose metabolism (ath00052), glycolysis/gluconeogenesis (ath00010), and fructose and mannose metabolism (ath00051) pathways (Figure 3A). In the GC-MS/MS analysis, DAMs related to sugar accumulation were notably enriched in galactose metabolism (ath00052) and starch and sucrose metabolism (ath00500) (Figure 3B). It was interesting that the enrichment pathways in LC-MS/MS and GC-MS/MS were somewhat distinct. The reason could be due to the variation in quantities of other DAMs detected in the LC-MS/MS and GC-MS/MS analyses. In the DAM analysis, we found that many carbohydrates and carbohydrate conjugates were upregulated. However, the major sugars involved in sugar accumulation in wucai were still unclear. OPLS-DA, a supervised discriminant analysis statistical method, was used to intuitively identify the differences between samples. The VIP score was obtained according to the OPLS-DA model, and potential biomarkers were distinguished with VIP > 1. We found that the numbers and fold-change of the DAMs related to sugar accumulation in the GC-MS/MS analysis were generally lower than those of the LC-MS/MS analysis. Consequently, OPLS-DA S-plot analysis based on the LC-MS/MS data was performed to identify significant DAMs and potential biomarkers. A total of 17 DAMs identified as biomarker candidates were filtered in the OPLS-DA S-plot (Supplementary Figure S4 and Supplementary Table S3). Of the candidates, the differential accumulation of β-D-glucose, D-galactose, and trehalose was significant (Supplementary Table S3). β-D-glucose and D-galactose, which are carbohydrates and carbohydrate conjugates, were upregulated (Supplementary Table S3). In order to more rigorously assess the results and their accuracy, further analysis of biomarkers was conducted using MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/, accessed on 27 August 2021). Thirteen biomarkers were screened based on log2(FC), t-tests, and AUC (Table 1). This showed that β-D-glucose and D-galactose had excellent AUC and log2(FC) values (Figure 4). The result validated that β-D-glucose and D-galactose could indeed be the major sugars in sugar accumulation in wucai and had positive effects on the sweetness. D-galactose also participates in amino sugar and nucleotide sugar metabolism (ath00520), and this pathway was screened for further analysis. We found that DAMs involved in enrichment pathways in the GC-MS/MS analysis were also present in the LC-MS/MS data. Thus, the DAMs in the pentose phosphate pathway (ath00030), galactose metabolism (ath00052), glycolysis/gluconeogenesis (ath00010), fructose and mannose metabolism (ath00051), starch and sucrose metabolism (ath00500), and amino sugar and nucleotide sugar metabolism (ath00520) were analyzed by making a heatmap based on the LC-MS/MS data (Figure 5A). The metabolites that accumulated significantly in these enrichment pathways were D-glycoldehyde3-phosphate, D-fructose, D-(+)-raffinose, Galactonic acid, N-acetyl-D-glucosamine, β-D-fructose 6-phosphate, β-D-Glucose, Gluconolactone, Fucose 1-phosphate, levan, and Glucose 6-phosphate. Six mixed replicates of wucai leaves at two periods (34 DAP and 46 DAP) were subjected to RNA-Seq analysis in order to identify the potential molecular mechanisms responsible for sugar accumulation in wucai. After filtering, a total of 39.70 G of clean data were obtained from the wucai leaves. The Q30 (sequences with sequencing error rates lower than 0.1%) content of the six cDNA libraries were more than 92.63%, and the average GC content was 48.07% (Supplementary Table S4). Overall, the data indicated that the Illumina sequencing data were of high quality and could be used for further analysis (Supplementary Table S5). All 4761 unigenes were searched in the Gene Ontology (GO) and KEGG databases, with 3431 and 1110 corresponding annotated unigenes. The GO term analysis of the wucai leaf transcriptome showed that 21 terms were related to the biological process category, of which “biological regulation,” “cellular process,” “metabolic process,” and “single-organism process” were the main GO terms (Supplementary Figure S5). Thirteen terms were correlated with the cellular component category, of which “cell,” “cell part,” and “organelle” were the most abundant GO terms. Twelve terms were included in the molecular function category, of which “binging” and “catalytic activity” made major contributions. In addition, 18 KEGG pathways were annotated, among which “carbohydrate metabolism,” “translation,” and “signal transduction” were the most abundant KEGG pathways (Supplementary Figure S6). The major sugars involved in sugar metabolism in wucai are D-galactose and β-D-glucose. To explore the metabolic differences in the two sugars at the sugar transformation periods, the accumulation of the two sugars was analyzed by combined transcriptome and metabolome analysis. D-galactose and β-D-glucose were mainly involved in the galactose metabolism (brp00052), glycolysis/Gluconeogenesis (brp00010), and starch and sucrose metabolism (brp00500) pathways, and, thus, we focused on DEGs related to these three metabolic pathways. It was found that most genes related to starch degradation and synthesis, trehalose synthesis, and phosphorylating D-fructose, D-glucose, and β-D-glucose were downregulated (Figure 5B). The downregulated DEGs mainly included BAM (β-amylase), DPE (4-alpha-glucanotransferase), PHS (α-glucan phosphorylase), SS (starch synthase), SBE (1,4-alpha-glucan-branching enzyme), TPS (α-, α-trehalose-phosphate synthase), TPP (trehalose-phosphate phosphatase), and other genes (hexokinase). According to the major two sugars and related DEGs, we constructed an accumulation pathway of D-galactose and β-D-glucose (Figure 6A). In this way, there were three DEGs encoding INV, namely CWINVs (CWINV3, CWINV4) and VINV(BRFUCT3), all of which encode AI. Of these genes, only the expression of CWINV4 was up-regulated. Raffinose and stachyose located in the galactose metabolic pathway were decomposed into D-galactose under AI (CWINV4). In the meantime, raffinose and stachyose were hydrolyzed into D-glucose under the action by the same gene. CWINV4 was also present in the starch and sucrose metabolic pathway, converting sucrose to D-glucose by hydrolysis. Moreover, cellulose in the starch and sucrose metabolic pathway was hydrolyzed to generate D-glucose. There were six DEGs associated with cellulose hydrolysis, EG (BraA03g023380.3C, CEL1) was up-regulated, while only one (BGLU16) of the BGL DEGs (BGLU16, BGLU9, BGLU15, and BGLU47) was up-regulated. Under the synergistic effect of BraA03g023380.3C, CEL1, and BGLU16, cellulose was gradually hydrolyzed into D-glucose. Aldose 1-epimerase (AEP) was able to catalyze the conversion of D-glucose to β-D-glucose. The generated D-glucose was converted to β-D-glucose by up-regulated expression of ARB_05372 (AEP). HK could phosphorylate β-D-glucose to β-D-Glucose 6-phosphate (β-D-glucose 6P), which later entered the glycolysis pathway. The four HK DEGs identified in this paper (BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C) were all down-regulated, reducing the phosphorylation of β-D-glucose and promoting the accumulation of the sugar. The genes (galactokinase) catalyzing D-galactose were not differentially expressed, which showed that the accumulation of D-galactose mainly depended on AI under the action of CWINV4 during the maturation process of wucai. In the transcriptome analysis, the FPKM value of CWINV4 at 34 DAP was zero. Hence, the relative expression of CWINV4 in the roots, stems, leaves, and petioles at 34 DAP and 46 DAP was detected. The relative expression of CWINV4 at 46 DAP was generally higher than that at 34 DAP in the four tissues, especially in the leaves and petioles (Supplementary Figure S7). To explore other genes that contribute to the accumulation of D-galactose and β-D-glucose, we selected TOP100 DEGs in the transcriptome and calculated the correlation between the expression of DEGs and response intensity data of biomarkers using the Pearson correlation method. DEGs with correlation values ≥0.98 or ≤−0.98 and p < 0.05 were selected and an interaction network was produced (Figure 6B). These were 26 and 8 DEGs that were significantly associated with D-galactose and β-D-glucose, respectively. BraA09g036850.3C and BraA01g000700.3C had a significant positive correlation with both D-galactose and β-D-glucose (Figure 6B). The DEGs with a significant negative correlation with β-D-glucose were SAHH2 (adenosylhomocysteinase 2), CHI (chalcone-flavonone isomerase), CHS1 (chalcone synthase 1), CHS3 (chalcone synthase 3-like), FLS1 (flavonol synthase/flavanone 3-hydroxylase), and OMT1 (flavone 3’-O-methyltransferase 1-like), which also had a significant negative correlation with D-galactose (Figure 6B). Twenty DEGs in the KEGG pathways and eight DEGs significantly associated with both D-galactose and β-D-glucose were selected and we measured their relative expression levels at 34 DAP, 37 DAP, 40 DAP, 43 DAP, and 46 DAP (Figure 7). The changes in the relative expression level of these genes at 46 DAP vs. 34 DAP were consistent with the transcriptome data (Figure 6 and Figure 7). The relative expression levels of CWINV4, BraA03g023380.3C, BGLU16, and ARB_05372 showed an increasing trend from 40 DAP and peaked at 46 DAP (Figure 7). CWINV3, BGLU9, BGLU15, BGLU47, BraA06g003260.3C, BraA05g027230.3C, BraA05g019040.3C, BAM1, BAM3-like, SAHH2, CHI, and FLS1 were genes that were down-regulated in the transcriptome, generally peaking at 37 DAP or 40 DAP and continuing to be downregulated until 46 DAP (Figure 7). CEL1, SUS3, and BraA01g000700.3C had irregularly varying relative expression levels, but the highest expression was observed at 46 DAP (Figure 7). Although BraA09g036850.3C was upregulated around maturation, its expression level peaked at 37 DAP (Figure 7). These results suggested that these DEGs may function at different stages. To understand whether the enzymes encoded by these genes play a role in sugar accumulation, we determined eight enzyme activities at 34 DAP and 46 DAP due to problems with the assay of some enzymes. The activities of CL, AI, and SUS were significantly increased, consistent with the up-regulated expression of CWINV4, BraA03g023380.3C, CEL1, BGLU16, and SUS3 (Figure 7 and Figure 8B,D,E). Similarly, the down-regulation of BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, BraA05g027230.3C, BAM1, BAM3, BAM3-like, BAM5, CHS1, and CHS3 resulted in a significant decrease in the activities of HK, β-amylase (BMY), and chalcone synthase (CHS) (Figure 7). The activity of α-amylase (AMY) and SPS at 46 DAP was close to that at 34 DAP, and DEGs encoding these two enzymes also did not appear in our transcriptome data (Figure 5B and Figure 8C,G). In general, the significant increase in AI and CL activities promoted sugar biosynthesis, while the significant decrease in BMY, HK, and CHS activities suppressed sugar loss. Sugar regulatory pathways are vital for metabolism during vegetable and fruit development and maturation [33]. The sweetness of vegetables and fruit depends mainly on the type and composition of sugars, which play key roles in flavor [10,48]. Sweetness, as an important indicator of wucai quality, increased significantly during the sugar maturation process. As research on sugar accumulation in wucai is limited, the sugar composition, sugar changes, and expression of genes related to sugar accumulation were analyzed during sugar transformation in wucai ”W16-19-5” herein. As previously reported in Chinese cabbage, tomato, pumpkin, watermelon, and melon, a significant increase in soluble sugars occurred during ripening [28,34,42,49,50,51]. In our study, the change in soluble sugar in wucai was similar to those in the above fruit and vegetables during the maturation process. In addition, we found that the soluble sugar content at 28 DAP was relatively low compared to at 22 DAP (Figure 1A). Wucai is grown in autumn and winter, and the air temperature gradually decreases after sowing. The growth environment of wucai was simulated in a growth chamber herein, and lowering of the temperature was first initiated at 28 DAP. Thus, we inferred that the soluble sugar decreased at 28 DAP due to the change in temperature. The growth environment of wheat is similar to that of wucai, and D-galactose accumulated greatly at the late stage of development in wheat [52]. D-galactose, in addition to sucrose, glucose, and fructose, in wucai was measured at 34 DAP and 46 DAP. We found that sucrose did not increase significantly, whereas glucose and D-galactose did more than fructose. Compared to 34 DAP, the ratio of glucose/soluble sugar increased significantly at 46 DAP (Figure 1F). Though there were no differences between the ratio of D-galactose/soluble sugar at the two periods, a great increase in their content occurred (Figure 1B,G). Carbohydrates also mainly constitute the differential metabolites during the ripening of kiwifruit and watermelon, which is consistent with our results [53,54]. In grape berry, sorghum stem, saffron corm, and melon, metabolites related to sugar accumulation were mainly enriched in fructose and mannose metabolism, starch and sucrose metabolism, glycolysis/gluconeogenesis, and pentose phosphate pathways [51,55,56,57]. We found that in addition to the pathways described above, galactose metabolism was also a significantly enriched pathway (Figure 3). The results showed that D-galactose and β-D-glucose were indeed the major accumulated sugars during the sugar transformation process and played a critical role in sugar accumulation. Sweetness, one of the major traits of wucai, is a significant factor influencing wucai quality and is also an indicator of consumer preference [3]. In this study, we found that D-galactose and β-D-glucose, which have a sweet taste, were the major sugars in the sugar accumulation process in wucai (Table 1 and Figure 4). Therefore, the mechanism of accumulation of the two major sugar was analyzed using transcriptomics. AI promoted the hydrolysis of not only sucrose, but also raffinose and stachyose [26]. CWINV and VINV activities were positively regulated by their encoding genes and they all were the AI [26,27,28]. The downregulation of BFRUCT3 showed that sugar accumulation did not depend on the hydrolysis of sucrose in the vacuoles during wucai ripening. Thus, the up-regulation of CWINV4 during the ripening of wucai resulted in a significant increase in AI activity, allowing for more D-galactose and β-D-glucose production. Wucai leaf is both the source tissue and the sink tissue. We found that the expression of CWINV4 was significantly increased in wucai leaf compared to the other tissues at 46 DAP (Supplementary Figure S7). This result was contrary to that of Chinese cabbage [5,42]. The IM is the main tissue of sugar accumulation in Chinese cabbage. CWIN1 (CWINV), NIN-like (CINV), and VIN4b (VINV) had relatively lower expressions in the inner leading leaves than the external leading leaves during Chinese cabbage ripening, especially in IM [5]. Three INV genes (encoding β-fructofuranosidase 1, β-fructofuranosidase 6, and β-fructofuranosidase 3) were also significantly downregulated in the inner leaves of yellow-head Chinese cabbage [42]. In addition, the basic leucine zipper (bZIP) transcription factor (TF) GmbZIP123 promoted the expression of three CWINV genes (CWINV1, CWINV3, and CWINV6) by directly binding to their promoters, resulting in higher levels of glucose, fructose, and sucrose in soybean [58]. A pitaya WRKY TF HpWRKY3 was associated with fruit sugar accumulation via the activation of the sucrose metabolic gene HpINV2 [59]. While there was no bZIP TF detected herein, WRKY TFs were detected in this study. Identifying which WRKY TFs can work with CWINV4 needs further analysis and verification. The SPS activity did not change during the maturation of wucai, but SUS activity increased remarkably. In addition, one DEG (SUS3) encoding SUS was up-regulated in the transcriptome data, and no SPS DEGs were found, consistent with the enzyme activities (Figure 8B,C and Figure 5B). Therefore, it was inferred that SUS3 promoted the synthesis of sucrose to offset the hydrolysis of sucrose under CWINV4. Starch degradation during ripening is a key additional process for D-glucose accumulation in fruit and is catalyzed by the action of amylases [60]. The activity of AMY and DPE increased during mango ripening with a concomitant decrease in the starch content of the fruit [13]. BMY activity and BAMs (BAM1, BAM3, BAM3-like, and BAM5) were significantly down-regulated (Figure 5B). DPE catalyzing starch conversion into D-glucose was also found to be downregulated (Figure 5B). However, there was no differential accumulation of starch during wucai ripening, due to the downregulation of SS1 and SBE3 for starch synthesis. It follows that the accumulation of β-D-glucose did not originate from starch degradation during wucai ripening. The cellulose hydrolytic enzyme beta-1, 4-endoglucanase (E1) gene, from the thermophilic bacterium Acidothermus cellulolyticus, was overexpressed in rice through Agrobacterium-mediated transformation [61]. Hydrolysis of transgenic rice straw yielded 43% more reducing sugars than wild-type rice straw did [61]. It was found that overexpression of EG promoted the hydrolysis of cellulose, which is consistent with our study. Additionally, the up-regulated expression of BGL genes in a ripe rich-sugar mango variety showed that the genes could promote the accumulation of sugar [13]. There were no CBH DEGs detected in our transcriptome data (Figure 5B). However, we observed a significant increase in CL activity. It was inferred that CEL1 and BraA03g023380.3C combined with BGLU16 catalyzed cellulose into β-D-glucose. A β-glucosidase from Clostridium cellulovorans (CcBG) was fused with cellulosomal endoglucanase CelD (CtCD) from Clostridium thermocellum [62]. CtCD CcBG showed favorable specific activities on phosphoric-acid-swollen cellulose (PASC), with greater glucose production (2-fold) when compared with a mixture of the single enzymes, further supporting our conclusions [62]. The transcription levels in mature Chinese cabbage and rich-sugar mango were significantly higher than those of unmatured Chinese cabbage and low-sugar mango, which proved that the downregulated expression of HK led to the accumulation of more glucose [13,41]. Significantly reduced HK activity during maturation of wucai was accompanied by the down-regulated expression of HK DEGs (BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C), which reduced the loss of D-glucose and led to more conversion of D-glucose to β-D -glucose. Similarly, the downregulation of HK activity reduced the phosphorylation of β-D-glucose, thereby promoting sugar accumulation. We screened 26 DEGs possibly related to D-glucose and β-D-glucose accumulation by calculating the correlation between TOP100 DEGs in transcriptome and target metabolites. Interferon-related developmental regulator (IFRD) was mainly involved in plant salt tolerance, cold tolerance, and the ABA signal transduction pathway in previous reports [63,64,65]. As wucai gradually matured, the relative expression levels of BraA09g036850.3C were higher than those at 34 DAP, suggesting that the high expression of the gene during this process may promote sugar accumulation (Figure 7). Some scholars have pointed out the beneficial role of inositol in promoting sugar accumulation [66]. In the biosynthesis of inositol, the rate-limiting step is catalyzed by inositol-3-phosphate synthase (ISYNA) [67]. Thus, BraA01g000700.3C was speculated to be highly expressed after maturation to enhance sugar accumulation (Figure 7). S-adenosylhomocysteine hydrolase (SAHH) is a widespread enzyme in cells. Over-expression of SlSAHH2 could enhance SAHH enzymatic activity in tomato development and ripening stages and resulted in a major phenotypic change of reduced ripening time from anthesis to breaker [68]. Interestingly, SAHH enzyme activity levels and SlSAHH2 transcript levels appeared to be inconsistent in some tissues. For example, SlSAHH2 was not significantly elevated in transgenic fruit, but its enzymatic activity remained at a high level [68]. From the above, it was assumed that SAHH2 decreased during the ripening process, but it still maintained a high level of enzyme activity to promote ripening and sugar accumulation in wucai. Sugars can be used as precursors and information-regulating molecules for synthesis of anthocyanins [69]. CHI, CHS, FLS, F3H (flavanone-3-hydroxylase), PAL (phenylalaninammo-nialyase), and OMT1 that affect the synthesis and accumulation of anthocyanin were regulated by sugar [69,70]. For example, the expression of the petunia CHS gene in transgenic Arabidopsis leaves was induced by sugars [71]. CHI, CHS, FLS, and OMT1 in wucai were down-regulated during ripening, where the measured CHS activity was also significantly decreased (Figure 7 and Figure 8). Different sugar sensing mechanisms exist in plants and respond to different sugars [72]. We speculate that in wucai, D-galactose and β-D-Glucose could have a negative effect on the synthesis of anthocyanin, and the down-regulation of CHI, CHS, FLS, and OMT1 reduced the loss of anthocyanin synthetic precursors. There were 18 other DEGs that had a significant correlation with D-galactose, and they were all negatively correlated (Figure 6B). However, how these genes regulate sugar accumulation remains unknown, which needs the support of further studies. This study is the first to report on sugar accumulation during the maturation process of wucai. We found that D-galactose and β-D-glucose were mainly accumulated during wucai ripening and are essential for improving the taste quality of the fruit. The upregulated expression of CWINV4, CEL1, BGLU16, and BraA03g023380.3C and downregulated expression of BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C in the pathway might contribute to the accumulation of D-galactose and β-D-glucose. Twenty-six DEGs significantly related to D-galactose and β-D-glucose may regulate their accumulation in wucai. This research could support the quality grading of wucai and the breeding of excellent wucai lines. W16-19-5, a typical wucai cultivar line, was used in this study. This experiment was carried out at the breeding base of Anhui Agricultural University (Hefei, China). The seeds of the experimental variety were obtained from the Vegetable Genetics and Breeding Laboratory of Anhui Agricultural University. Seeds were sown in plugs in a greenhouse, and seedlings with 6–7 leaves were transplanted into pots containing a substrate and vermiculite at a volume ratio of 2:1. Subsequently, the seedings were grown in a growth chamber (0 DAP) at 25 ± 1 °C (day) and 15 ± 1 °C (night) with a 300 μmol·m−2·s−1 photon flux density and 70% relative humidity under a 16/8 h (day/night) photoperiod. At 28 DAP, the growth chamber was modified to 10 °C (day) and 4 °C (night), and the other conditions remained the same. The fourth and fifth fully expanded young leaves from the center of the plants, petiole, root, and stem were sampled. Fresh leaves were placed at 105 °C for 20 min and then dried at 75 °C for 24 h to obtain a dry sample. The first sampling was performed at 4 DAP and then at 5-day intervals, with sampling ending at 52 DAP (Supplementary Figure S1). Fresh samples were immediately frozen in liquid nitrogen and maintained at −80 °C for analyses. Measurements of soluble sugar were carried out at nine sampling periods, namely 4 DAP, 10 DAP, 16 DAP, 22 DAP, 28 DAP, 34 DAP, 40 DAP, 46 DAP, and 52 DAP. The soluble sugar was measured according to the anthrone colorimetric method with slight modifications [73]. Fresh leaves (0.2 g) were boiled in ddH2O (10 mL) for 30 min and then filtered and homogenized (25 mL). The extract (0.5 mL) was added to 1.5 mL of ddH2O, 0.5 mL of anthrone ethyl acetate, and 5 mL of pure sulfuric acid. The absorbance was measured at 630 nm by a UV-vis spectrophotometer (TU1950, PERSEE). Soluble sugar, sucrose, and fructose in the dry sample were measured at 34 DAP and 46 DAP by the anthrone colorimetric method with slight modifications [73]. Dried leaves (50 mg) were mixed with 4 mL of alcohol (80%, v/v) and shaken at 80 °C for 30 min. The residue was extracted with 80% alcohol. The two mixtures were configured to determine the described sugar content. The first mixture contained 0.25 mL of extract, 0.25 mL of ddH2O, and 50 µL of NaOH (2 mol/L) and was boiled at 90 °C for 5 min. The second mixture of 0.5 mL of extract and 2.5 mL of anthrone was boiled at 40 °C for 10 min. The corresponding absorbance values were measured at 620 nm. Glucose was extracted using a Solarbio reagent kit (Cat #BC1580; Beijing Solarbio Science & Technology Co., Ltd., Beijing, China). D-galactose was quantified using a kit (ADS-W-TDX046; Shanghai Kexing Trading Co., Ltd., Shanghai, China). AI, CL, AMY, BMY, HK, SPS, and CHS activities were measured at 34 DAP and 46 DAP according to kits (Cat #BC0560, Cat #BC2540, Cat #BC2040, Cat #BC0740, Cat #BC0600, and Cat #BC0580; Beijing Solarbio Science & Technology Co., Ltd., Beijing, China. Cat # ml092866; Shanghai Enzyme-linked Biotechnology Co., Ltd., Shanghai, China), respectively. The extraction, detection, and quantitative analysis of metabolites in the samples were performed by Shanghai Lu-Ming Biotech Co., Ltd. (Shanghai, China) (https://www.lumingbio.com/, accessed on 3 January 2021). In brief, freeze-dried wucai leaf samples (80 mg) were weighed and extracted overnight at −20 °C with 20 μL of 2-chloro-l-phenylalanine (0.3 mg/mL) dissolved in methanol as an internal standard and 1 mL of mixture of methanol and water (7/3, v/v). The samples were centrifuged at 13,000 rpm and 4 °C for 15 min. The supernatants (150 μL) were collected and then filtered through 0.22 μm microfilters and transferred to LC vials. Sample extracts were filtered and analyzed by LC-MS/MS. All metabolites were identified by Progenesis QI (Waters Corporation, Milford, CT, USA) Data Processing Software, based on public databases (http://www.hmdb.ca/; http://www.lipidmaps.org/, accessed on 3 January 2021) and self-built databases. The GC-MS/MS analysis was similar to that of the LC-MS/MS analysis. Sixty milligrams of freeze-dried wucai leaves samples was weighed and combined with 40 μL of 2-chloro-l-phenylalanine (0.3 mg/mL) dissolved in methanol as an internal standard and 360 μL of cold methanol. Two milliliters of chloroform and 4 mL of water were added to the sample, which was ground and then extracted. The supernatant (200 μL) was transferred to a glass sampling vial for vacuum-drying at room temperature. Eighty microliters of 15 mg/mL of methoxyamine hydrochloride in pyridine was subsequently added, following which 80 μL of BSTFA (with 1% TMCS) and 20 μL of n-hexane were added into the mixture after rotating for 2 min and incubating at 37 °C for 90 min, which was then followed by vigorous vortexing for 2 min and then derivatization at 70 °C for 60 min. After 30 min at room temperature, the sample extracts were filtered and analyzed by GC-MS/MS. Metabolites were annotated through the LUG database (Untarget database of GC-MS/MS from Lumingbio). Metabolic alterations among experimental groups were visualized by principal component analysis (PCA) and (orthogonal) partial least-squares-discriminant analysis (O)PLS-DA. Group discrimination was ascertained based on VIP scores >1 obtained from the OPLS-DA model. Metabolites with VIP > 1 and p-value < 0.05 were considered differential metabolites. The OPLS-DA S-plot was obtained from the OPLS-DA, with minor modification. All points representing DAMs in the figure are distributed in the first and third quadrants, similar to an S-shape, which is called an OPLS-DA S-plot. Metabolites that are significantly different are distributed in the upper left corner and lower right corner. Biomarker analysis was performed by MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/,accessed on 27 August 2021). The total RNA of the wucai leaf samples at the two sampling periods (34 DAP and 46 DAP) was extracted using a mirVana miRNA Isolation Kit (Ambion) according to the manufacturer’s instructions. The RNA integrity was evaluated using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The samples with RNA Integrity Number (RIN) ≥ 7 were subjected to subsequent analysis. The libraries were constructed using a TruSeq Stranded mRNA LTSample Prep Kit (Illumina, San Diego, CA, USA) following the manufacturer’s instructions. Then, six cDNA libraries were sequenced on the Illumina sequencing platform (HiSeqTM 2500 or Illumina HiSeq X-Ten). Raw data (raw reads) were first processed using Trimmomatic [74], and then the low-quality reads were removed to obtain the clean reads for subsequent analyses. The clean reads were mapped to the B. rapa reference genome using HISAT2 [75]. Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values and the read counts of each gene were obtained, respectively, by Cufflinks and HTSeqcount [76]. Differentially expressed unigenes (DEGs) were identified using the DESeq (2012) function estimateSizeFactors and nbinomTest, and q < 0.05 and |log2(fold change)| > 1 were set as the threshold for significant differential expression. KEGG pathway enrichment analysis of DEGs was performed in R software based on the hypergeometric distribution. Twenty-eight genes were selected for qRT-PCR analysis, and a gene encoding actin was used as the internal reference gene. The total RNA of the wucai leaves was extracted using an RNA kit (Takara Biomedical Technology Co., Beijing, China). The primers designed by Primer software v6.0 (Premier Biosoft International, Palo Alto, CA, USA) are listed in Supplementary Table S6. The qRT-PCR was performed using the Hieff® qPCR SYBR® Green Master Mix (No Rox) (Yeasen, Shanghai, China). The relative mRNA expression level of genes was calculated using the 2-ΔΔCT method [77]. All data were analyzed using Origin 2020 64 Bit, Adobe Illustrator 2019, Excel 2019, Adobe Photoshop 2021, Cytoscape_v3.8.2, and SPSS 26.0 and were expressed as mean ± SD. Tukey’s post hoc test was used for mean comparisons using p < 0.05. All data were from three biological replications. In the present study, LC-MS/MS, GC-MS/MS, and RNA-Seq profiling were performed to explore the molecular regulatory mechanisms of sugar accumulation during the maturity process of wucai. In the comparison of 46 DAP vs. 34 DAP, the number of DAMs associated with carbohydrates was prominent in LC-MS/MS and GC-MS/MS. The main ways of sugar accumulation were the pentose phosphate pathway, galactose metabolism, glycolysis/gluconeogenesis, starch and sucrose metabolism, and fructose and mannose metabolism in metabolome profiling. D-galactose and β-D-glucose, the two significantly accumulated metabolites, were identified as the main sugar to improving the taste quality of wucai during sugar transformation. Combined with the transcriptome data, the pathway of sugar accumulation and the interaction network of DEGs and the two sugars were generated. CWINV4, CEL1, BGLU16, and BraA03g023380.3C, which directly regulate sugar production, were significantly upregulated, and the enzymes activities (AI and CL) they encode showed the same results. Likewise, the expressions of HK (BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C) and HK activity were both significantly decreased, reducing the metabolic loss of sugar. The 26 DEGs in the interaction network may regulate sugar accumulation through some unknown pathways. Among them, BraA09g036850.3C, BraA01g000700.3C, SAHH2, CHI, CHS1, CHS3, FLS1, and OMT1 all have effects on D-galactose and β-D-glucose metabolism. These findings could help us understand the main substances and molecular regulation mechanism during the process of sugar accumulation.

PMC10003348

Maria Spada,Claudio Pugliesi,Marco Fambrini,Diego Palpacelli,Susanna Pecchia

Knockdown of Bmp1 and Pls1 Virulence Genes by Exogenous Application of RNAi-Inducing dsRNA in Botrytis cinerea

02-03-2023

gray mold,lettuce,plant protection,topical application of dsRNA,post-transcriptional gene silencing,RNAi-based fungicides

Botrytis cinerea is a pathogen of wide agronomic and scientific importance partly due to its tendency to develop fungicide resistance. Recently, there has been great interest in the use of RNA interference as a control strategy against B. cinerea. In order to reduce the possible effects on non-target species, the sequence-dependent nature of RNAi can be used as an advantage to customize the design of dsRNA molecules. We selected two genes related to virulence: BcBmp1 (a MAP kinase essential for fungal pathogenesis) and BcPls1 (a tetraspanin related to appressorium penetration). After performing a prediction analysis of small interfering RNAs, dsRNAs of 344 (BcBmp1) and 413 (BcPls1) nucleotides were synthesized in vitro. We tested the effect of topical applications of dsRNAs, both in vitro by a fungal growth assay in microtiter plates and in vivo on artificially inoculated detached lettuce leaves. In both cases, topical applications of dsRNA led to gene knockdown with a delay in conidial germination for BcBmp1, an evident growth retardation for BcPls1, and a strong reduction in necrotic lesions on lettuce leaves for both genes. Furthermore, a strongly reduced expression of the BcBmp1 and BcPls1 genes was observed in both in vitro and in vivo experiments, suggesting that these genes could be promising targets for the development of RNAi-based fungicides against B. cinerea.

Knockdown of Bmp1 and Pls1 Virulence Genes by Exogenous Application of RNAi-Inducing dsRNA in Botrytis cinerea Botrytis cinerea is a pathogen of wide agronomic and scientific importance partly due to its tendency to develop fungicide resistance. Recently, there has been great interest in the use of RNA interference as a control strategy against B. cinerea. In order to reduce the possible effects on non-target species, the sequence-dependent nature of RNAi can be used as an advantage to customize the design of dsRNA molecules. We selected two genes related to virulence: BcBmp1 (a MAP kinase essential for fungal pathogenesis) and BcPls1 (a tetraspanin related to appressorium penetration). After performing a prediction analysis of small interfering RNAs, dsRNAs of 344 (BcBmp1) and 413 (BcPls1) nucleotides were synthesized in vitro. We tested the effect of topical applications of dsRNAs, both in vitro by a fungal growth assay in microtiter plates and in vivo on artificially inoculated detached lettuce leaves. In both cases, topical applications of dsRNA led to gene knockdown with a delay in conidial germination for BcBmp1, an evident growth retardation for BcPls1, and a strong reduction in necrotic lesions on lettuce leaves for both genes. Furthermore, a strongly reduced expression of the BcBmp1 and BcPls1 genes was observed in both in vitro and in vivo experiments, suggesting that these genes could be promising targets for the development of RNAi-based fungicides against B. cinerea. Botrytis cinerea Persoon: Fries (teleomorph Botryotinia fuckeliana (de Bary) Whetzel) is a polyphagous necrotrophic pathogenic fungus that causes significant economic losses to agricultural production. The fungus infects mainly dicotyledonous crop species worldwide and can attack most plant parts such as leaves, flowers, stems, petioles, and fruits [1,2]. Unlike other plant pathogenic fungi, B. cinerea has a prominent role year-round and may cause infections in a wide range of climatic conditions. B. cinerea is recognized as a “high-risk” pathogen in terms of its resistance development to fungicides (Fungicide Resistance Action Committee, FRAC: https://www.frac.info, accessed on 9 November 2022) [3,4,5,6,7]. The resilience of the pathogen to the natural defense mechanisms of plants and toward many fungicides has pushed research toward new control strategies. Recently, novel approaches based on the use of RNA interference (RNAi) are rising up in the crop protection scenario. RNAi is a process of post-transcriptional gene silencing (PTGS) triggered by double-stranded RNA (dsRNA), small interfering RNA (siRNA), or hairpin RNA (hpRNA), resulting in the specific degradation of target mRNA. In particular, RNAi based on the exogenous application of dsRNA has been reported as a non-genetically modified organism (non-GMO) strategy in plant disease control against some pathogenic fungi that involves targeting specific genes. A nucleotide-sequence-specific dsRNA is applied to plants, and it could represent a potential alternative to conventional fungicides [8,9,10,11]. There is great interest in the use of RNAi as a control strategy against B. cinerea. Until now, some genes have been targeted for RNAi studies (e.g., effector genes, cell wall elongation genes, ergosterol and chitinase biosynthesis genes, vesicle trafficking pathway genes, and virulence genes involved in signal transduction or in the secretory pathway) [12,13,14,15,16,17,18]. Due to the sequence-dependent nature of RNAi, dsRNA sequences can be customized to reduce the possible effects on non-target species. One of the possible strategies is to use highly specific genes of the pathogen such as virulence genes, which are much less likely to have adverse effects on non-target organisms. Therefore, in view of the future perspectives on the use of RNAi for the control of B. cinerea (SIGS, the in vivo production of dsRNA, and dsRNA-based formulations), the use of this type of gene is much more useful and less risky than the use of essential genes. The infection process of B. cinerea involves stages of conidial attachment, germination, host penetration, primary lesion formation, lesion expansion, and tissue maceration, followed by sporulation [19]. Many studies based on gene inactivation approaches have highlighted virulence genes that are closely linked to the various phases of the B. cinerea infection [20]. According to a recent classification [21], the sensu lato virulence genes in B. cinerea include: (i) a gene associated with the appressorium formation [22], (ii) sensu stricto virulence genes according to the definition of Choquer et al. [20], and (iii) plant cell wall disassembly genes (CAZyme genes) [23]. In previous studies, to minimize off-target problems, we selected the B. cinerea sensu stricto virulence gene BcBmp3, which is known to have a key role in the infection process of the pathogen. We demonstrated that our dsRNA that targeted this gene was effective at controlling B. cinerea and was highly specific [15]. Moving on, in our RNAi knockdown studies, we selected two other sensu stricto virulence genes: BcBmp1 (a Fus3/Kss1-type MAP kinase essential for fungal pathogenesis) and BcPls1 (a tetraspanin related to appressorium penetration), which are known in the literature for their use in knockout experiments [20,24]. In eukaryotic organisms, mitogen-activated protein kinases (MAPKs) play critical roles in sensing extracellular signals and regulating various development and differentiation processes. Among MAPKs, the Fus3/Kss1-type MAPKs play important roles in pathogenicity in many fungi. Data from earlier studies have shown that the Fus3/Kss1-type MAPKs are essential for virulence in fungal pathogens because the knockout mutants for these genes failed to penetrate the host cuticles and/or to grow invasively in host tissues [25]. The BcBmp1 gene is the ortholog of the yeast Fus3/Kss1 and of the Magnaporthe grisea virulence factor PMK1 [26]. Gene knockout approaches for the BcBmp1 gene show that bmp1 mutants have a reduced growth rate and are non-pathogenic on carnation flowers and tomato leaves due to their inability to penetrate and macerate plant tissues. The BcBmp1 gene is required for host surface recognition and the penetration ability of germinated conidia in the early infection process. Moreover, the germination of bmp1 mutant conidia is somewhat retarded when compared to that of the wild type [27,28,29]. Tetraspanins are small eukaryotic integral membrane proteins that are known to have varying functions. In filamentous fungi, three families of tetraspanins (Pls1, Tsp2, and Tsp3) with different distributions among the phyla were identified [30,31]. The most important tetraspanin of ascomycetes seems to be Pls1, which was first tetraspanin to be identified as a virulence factor in Magnaporthe oryzae. The Pls1 tetraspanin in B. cinerea is necessary for its appressoria-mediated penetration into host plants leaves. Moreover, knockout experiments evidenced that BcPls1 has an impact on pathogenicity, but is not involved in the germination of asexual conidia or vegetative hyphal fusion events [24,32]. The aim of this study was to assess the effectiveness of an exogenous application of BcBmp1- and BcPls1-targeting dsRNA molecules in the silencing of BcBmp1 and BcPls1 genes in vitro and in vivo on lettuce (Lactuca sativa L.) leaves. We first used dsRNAs in experiments on the pathogenic fungus that investigated mycelial growth, relative gene expression, and conidia germination. Subsequently, artificial inoculation tests with B. cinerea were carried out on the detached lettuce leaves where topical dsRNA applications were performed. The knockdown efficacy was evaluated by gene expression and a measurement of necrotic areas. We then verified the effects of dsRNAs on non-target organisms in silico and in vivo. To the best of our knowledge, this is the first report on the use of the sensu stricto virulence genes BcBmp1 and BcPls1 in RNAi experiments for the control of gray mold caused by B. cinerea. As a first step, we investigated whether a knockdown of the BcBmp1 and BcPls1 genes could affect the growth of B. cinerea in an axenic culture. Therefore, we generated a 344 bp dsRNA (BcBmp1-dsRNA), which was complementary to a portion of the fourth exon of the BcBmp1 gene (Figure S1A and S2), and a 413 bp dsRNA (BcPls1-dsRNA), which was complementary to a portion of the second exon of the BcPls1 gene (Figure S1B and S3). To quantify the effects of the BcBmp1-dsRNA and BcPls1-dsRNA on fungal growth, we measured the optical density of the fungal mycelium at different times. For the treatment with BcBmp1-dsRNA, the fungal growth was not significantly delayed in the in vitro assay (Figure 1A and Figure S4A). In the case of BcPls1-dsRNA, the fungal growth was delayed at 24 (69.8 ± 0.24%), 48 (59.8 ± 0.34%), and 72 h (75.8 ± 0.52%), respectively, compared to the controls (Ctrl = SMB + TE buffer and GFP-dsRNA) (Figure 2A and Figure S4B), and was subsequently restored at 96 h (100 ± 0.30%). According to these results, two times 48 and 96 h were chosen to sample the mycelium in order to verify a correlation between reduced fungal growth and the silencing of the target genes. Quantitative real-time PCR (qRT-PCR) was used to assess the expression of the BcBmp1 and BcPls1 genes. After 48 h of incubation in the presence of BcBmp1-dsRNA, the expression of the BcBmp1 gene in the mycelium was significantly suppressed (to about 10%) compared to both control media. Analogously, a reduction in the BcBmp1 mRNA levels was detected 96 h after treatment (Figure 1B). These data suggest that BcBmp1-dsRNA, delivered in vitro, silenced the expression of the BcBmp1 gene during the vegetative axenic growth of the pathogen. In contrast, a more complex and diversified BcPls1 expression was detected. After 48 h of incubation in the presence of BcPls1-dsRNA, the expression of the BcPls1 gene was significantly suppressed (to 60.5%) compared to the Ctrl (Figure 2B). However, the reduction in the BcPls1 mRNA level was not significant in comparison to the GFP-dsRNA-treated mycelium. In addition, at 96 h after treatment, the BcPls1 expression was not significant different for both Ctrl and GFP-dsRNA. These data suggest that the in vitro BcPls1-dsRNA was able to silence the expression of the BcPls1 gene during the early stages of the vegetative axenic growth of the pathogen. The effects of BcBmp1-dsRNA and BcPls1-dsRNA on the germination kinetics of B. cinerea conidia were determined at 3, 6, and 9 h on liquid SMB in 96-well polystyrene microtiter plates. When BcBmp1-dsRNA was used, the conidial germination was significantly delayed at 6 and 9 h compared to controls (Ctrl = SMB + TE buffer and GFP-dsRNA). On average, the reduction in germination was 37.4% (6 h) and 5.7% (9 h) compared to the germination of both Ctrl and GFP-dsRNA. At 3 h, there were no significant differences between the treatments (Figure 3A). For the treatment with BcPls1-dsRNA, the conidial germination was not significantly delayed in the in vitro assay at any of the times tested (Figure 3B). We focused on the effects of treatments with BcBmp1-dsRNA and BcPls1-dsRNA by applying them topically to Lactuca sativa cv. Romana. We evaluated the efficacy of dsRNA treatments on the symptoms caused by B. cinerea using a detached leaf assay. After a drop application of BcBmp1-dsRNA or BcPls1-dsRNA (20 ng µL−1), the leaves were inoculated with a drop of conidial suspension (5 × 102). Necrotic areas (mm2) were recorded and analyzed after 120 h (5 dpi). At 5 dpi, the leaves treated with both controls (water + TE buffer and GFP-dsRNA at the concentration of 20 ng µL−1) showed necrotic lesions, representing a successful B. cinerea infection on the lettuce leaves (Figure 4A,B), whereas the BcBmp1-dsRNA- or BcPls1-dsRNA-treated leaves showed strongly reduced necrotic lesions at the inoculation site (Figure 4C,D). The lettuce leaves treated with BcBmp1-dsRNA (3.3 ± 0.7 mm2) or BcPls1-dsRNA (3.1 ± 0.9 mm2) developed lesions about eight times smaller than those of the control leaves treated with either water + TE buffer (24.7 ± 1.9 mm2) or GFP-dsRNA (25.6 ± 2.1 mm2) (Figure 5A and Figure 6A). To verify if the reduction at 5 dpi of the B. cinerea necrotic areas on both the BcBmp1-dsRNA and BcPls1-dsRNA-treated leaves was correlated with a knockdown of the genes, qRT-PCR analyses were performed on the inoculated leaves. The BcBmp1 transcript levels were drastically reduced: 12.8% and 10.6% compared to the Ctrl and GFP-dsRNA levels, respectively (Figure 5B). Similarly, the BcPls1 transcript levels were drastically reduced: 17.6% and 12.5% compared to the Ctrl and GFP-dsRNA levels, respectively (Figure 6B). To explore co-silencing effects, we calculated the possible off-target effects for the tested BcBmp1-dsRNA and BcPls1-dsRNA molecules. Precursor sequences of the constructs were targeted against the complementary DNAs (cDNAs) of different phytopathogenic and beneficial fungi, humans, and lettuce using the si-Fi v21 software (default parameters). The results are summarized in Tables S1 and S2 as the number of siRNA hits found (total and efficient) for each corresponding target. The prediction of BcBmp1 off-target transcripts using the si-Fi v21 software evidenced that in one isolate of Sclerotinia sclerotiorum alone, 78 siRNAs were found, of which only 37 were efficient (Table S1). The target sequence found (GenBank accession number APA14320) corresponds to the catalytic domain of extracellular signal-regulated kinase 1- and 2-like serine/threonine kinases. This subfamily is composed of the mitogen-activated protein kinases (MAPKs) ERK1, ERK2, baker’s yeast Fus3, and similar proteins. The BcBmp1 gene is the ortholog of the yeast Fus3/Kss1 and was characterized by gene replacement approaches, but a similar sequence was also found in the genome of S. sclerotiorum [22]. In the case of BcPls1, the prediction of off-target transcripts using the si-Fi v21 software showed that in S. sclerotiorum alone, seven siRNAs were found, of which only four were efficient (Table S2). The target sequences found (GenBank accession numbers EDO03107 and APA12012) corresponded to a hypothetical protein and to a tetraspanin, respectively. In the in silico analysis of both genes, only a few efficient siRNAs were found in the off-target fungal pathogen S. sclerotiorum, which is a close relative of B. cinerea. The results obtained by these bioinformatic analyses proved to be a useful guide in the choice of multiple targets for RNAi. Therefore, the results indicate that BcBmp1-dsRNA and BcPls1-dsRNA are highly specific for the target Bmp1 and Pls1 genes of B. cinerea, with no off-target sequences in the host plant (Lactuca sativa), distantly related phytopathogenic fungi (Alternaria alternata, Fusarium oxysporum, Rhizoctonia solani, or Pythium ultimum), beneficial fungi (Trichoderma asperellum, T. harzianum, or Rhizophagous irregularis), or the human genome. Using the databases of three B. cinerea isolates, including B05.10, we found a high number of efficient off-target siRNAs that exactly matched only with the Bmp1 and the Pls1 genes, as expected (Tables S1 and S2; Figures S5 and S6). To further explore the co-silencing effects of the BcBmp1-dsRNA and BcPls1-dsRNA against off-targets organisms, we tested them against the promising biocontrol agent T. harzianum T6776 and against F. oxysporum DAFE SP21-23. For these fungi, the off-target prediction analysis with the si-Fi v21 software did not find any efficient siRNAs (Tables S1 and S2). To quantify the effects of BcBmp1-dsRNA and BcPls1-dsRNA on fungal growth, the optical density (OD595) of the fungal mycelium at different times (24, 48, 72, and 96 h) was measured. The growth of T. harzianum T6776 (Figure 7A) and F. oxysporum DAFE SP21-23 (Figure 7B) was not significantly reduced at any time compared to the growth of the controls (Ctrl (SMB + TE buffer) and GFP-dsRNA), thus confirming both the high specificity of the molecules and the prediction analysis. In this work, we demonstrated that the Fus3/Kss1-type mitogen-activated protein kinase (MAPK) BcBmp1 and the tetraspanin BcPls1 genes are efficient and novel targets for RNAi with the purpose of reducing disease symptoms in lettuce after a B. cinerea infection. The topical application of BcBmp1-dsRNA and BcPls1-dsRNA mediated both the in vitro and in vivo knockdown of the B. cinerea transcripts. To the best of our knowledge, this is the first report on the reduction of B. cinerea virulence through a topical application of dsRNA that targets these sensu stricto virulence genes. In eukaryotic organisms, mitogen-activated protein kinase (MAPKs) pathways are involved in the transduction of a variety of extracellular signals and in the regulation of many developmental processes [25,26]. Among MAPKs, the yeast and fungal extracellular signal-regulated kinase (YERK1) subfamily is represented by Fus3/Kss1 in Saccharomyces cerevisiae. Different gene knockout studies have shown that Fus3/Kss1-type MAPKs are essential for virulence in fungal pathogens because of the failure of phytopathogenic and entomopathogenic fungi knockout mutants to penetrate the host cuticles and/or to grow invasively in host tissues [25,33]. BcBmp1 is a single-copy gene, and is the ortholog of the yeast Fus3/Kss1 and of the Magnaporthe grisea virulence factor PMK1. bmp1 mutants showed an altered vegetative growth phenotype; the conidia germinated on plant surfaces, but were unable to penetrate and macerate the plant tissues. This clearly indicates that the gene is essential for plant infection; in fact, the MAP kinase pathway seems to be widely conserved in pathogenic fungi and involved in regulating infection (appressorium formation and virulence) processes [27]. Fungal tetraspanins have a key role in the infection process in several pathogenic fungi [34]. The first fungal tetraspanin, Pls1, was found in the plant pathogenic fungus Magnaporthe grisea (MgPls1) [35]. Three fungal tetraspanins homologous to Pls1 were further identified in the ascomycetes B. cinerea (BcPls1), Colletotrichum lindemuthianum (ClPls1), and Neurospora crassa (NcPls1), defining a novel class of tetraspanins in fungi [36]. Thanks to the increasing availability of fungal genomes in databases, orthologous genes to Pls1 have been identified in other species of Ascomycetes and Basidiomycetes, but only a single Pls1 tetraspanin-encoding gene was found in Ascomycetes, facilitating their functional study. The roles of the tetraspanins MgPls1, BcPls1, and ClPls1 were analyzed by inactivating genes through insertional mutagenesis or targeted gene replacement. The corresponding null mutants were unable to infect their host plants, indicating that Pls1 is essential for appressorium-mediated penetration into the host plant [32,35,37]. For the reasons described above, we considered the sensu stricto virulence genes Bmp1 and Pls1 of B. cinerea as good potential targets for RNAi mediated by the exogenous application of complementary dsRNAs. Moreover, the target sequences were chosen so that, in silico, they share no homology with the genes of the host or other off-target organisms. Using the si-Fi v21 software [38], the BcBmp1-dsRNA and BcPls1-dsRNA were determined to be highly specific for B. cinerea, with no off-target hits in the host plant, in distantly related phytopathogenic fungi, in beneficial fungi, or in the human genome. The siRNAs were found to be efficient only in the close relative Sclerotinia sclerotiorum (37 for BcBmp1 and 4 for BcPls1). The choice of highly specific target sequences should avoid homology with off-target transcripts and reduce off-target impacts. Specific software and databases were used to test different regions of a gene in order to minimize off-target hits [39]. Nevertheless, the best approach to reduce risks is to combine bioinformatics analyses with biological data [40]. In light of these considerations, we tested the effects of BcBmp1-dsRNA and BcPls1-dsRNA molecules against the promising biocontrol agent T. harzianum T6776 and the F. oxysporum isolate DAFE SP-21-23. Neither of the dsRNAs gave negative results, neither in silico nor in vivo, but their high specificity was confirmed in accordance with the prediction analysis. In this work, to validate the virulence genes chosen, a first approach was to challenge the fungal pathogen in vitro with the dsRNA molecules. The BcBmp1-dsRNA and BcPls1-dsRNA molecules were applied to liquid cultures of B. cinerea, which was grown in 96-well microtiter plates. This assay is considered very simple, cost-effective, and rapid for quantifying the inhibitory effects of molecules on fungal growth [41]. Furthermore, the assay can be very useful for a preliminary evaluation of the effects of dsRNAs on the vegetative growth and conidial germination of fungi using small amounts of dsRNA [39,42]. The validity of in vitro studies using dsRNA molecules against fungal pathogens has been demonstrated by different studies. The molecules were designed to target essential genes in Fusarium oxysporum f.sp. cubense and Mycosphaerella fjiensis [43], Sclerotinia sclerotiorum [13], F. graminearum [42], F. asiaticum [44], and B. cinerea [15,18]. The applications of BcBmp1-dsRNA did not affect mycelial growth, but resulted in a delay in conidial germination. Conversely, the applications of BcPls1-dsRNA led to a gene knockdown with an evident growth retardation, without significant effects on conidial germination. No alteration in the morphology of the germ tubes was observed in either treatment. It has been reported that the conidial germination of a B. cinerea knockout mutant in the Bmp1 gene is somewhat retarded when compared to the wild type. In addition, the germ tubes continue to elongate on hydrophobic surfaces and never differentiate into appressoria, indicating that they are defective in the signaling related to appressorium formation [27,28,29]. By comparing the expression data with the vegetative growth data, we highlighted that the strength of the BcBmp1 gene knockdown is not directly related to the growth retardation, according to other studies [42]. The transcript levels at 48 h were significantly lower than the controls when using a topical application of BcBmp1-dsRNA. Gene expression silencing was also observed at 96 h when the vegetative growth was restored. In S. sclerotiorum, 48 h were required for optimal RNAi silencing using a topical application of dsRNA, and the level of suppression persisted at 96 h without changing significantly after 48 h [13]. In the case of BcPls1-dsRNA, the fungal growth was delayed at 24, 48, and 72 h, respectively, compared to the controls and was subsequently restored at 96 h. Regardless, the expression data at 48 and 96 h suggested that the in vitro BcPls1-dsRNA was able to silence the expression of the BcPls1 gene during the early stages of the vegetative axenic growth of the pathogen. The inactivation of BcPls1 in B. cinerea by insertional mutagenesis was observed to have no effect on the mycelial growth, conidiation, and conidial germination rate in the Bcpls1::bar null mutant. BcPls1 expression (monitored with GFP) is limited to the penetration process in the early stages of infection and is independent of plant signals, since it has also been observed in germinating conidia, germ tubes, and appressoria developed on artificial surfaces [32]. Under our experimental conditions, it was not possible to perform expression studies in the early stages of fungal growth (less than 48 h), as the obtained biomass was too small to yield a sufficient amount of RNA. Furthermore, the observations reported by Gourgues et al. [36] were conducted using a methodological approach that was different from the one used in this work (null mutant vs. RNA silencing mediated by dsRNA). Gray mold caused by B. cinerea is considered one of the main diseases in greenhouse-grown lettuce. The romaine lettuce variety and some iceberg lettuces are susceptible to B. cinerea, both in greenhouses and in the field [45]. A second approach used in this work was to evaluate the efficacy of the BcBmp1-dsRNA and BcPls1-dsRNA molecules at reducing disease symptoms using Lactuca sativa cv. Romana-B. cinerea as a pathosystem. We performed a detached leaf assay by applying a conidial suspension of the pathogen as the inoculum after locally treating the lettuce leaves with dsRNAs. A topical application of the BcBmp1-dsRNA and BcPls1-dsRNA molecules reduced the lesion areas at 5 dpi by approximately eight-fold compared to the controls. This strong decrease in the necrotic areas was associated with a drastically reduced level of Bmp1 and Pls1 transcripts on the infected leaves. Similarly, an external application of dsRNAs targeting different B. cinerea genes on the surfaces of fruits, vegetables, and flower petals significantly inhibited gray mold disease [12,13,14,15,16]. Recently, it was demonstrated that a SIGS application of dsRNAs can confer protection for grapevines against B. cinerea under both pre- and post-harvest conditions [14,17,18]. Data from many previous studies have shown that Fus3/Kss1-type MAPKs are essential for virulence in fungal pathogens due to the failure of pathogen knockout mutants to penetrate the host cuticles and/or to grow invasively in host tissues. Indeed, in B. cinerea, Bmp1 gene-replacement mutants are non-pathogenic on carnation flowers and tomato leaves due to their inability to penetrate and macerate the plant tissues [27,28,46]. Fus3/Kss1-type MAPK homologs have been studied using knockout mutants, highlighting the crucial role of these genes in the infection process of the following phytopathogenic, entomopathogenic, and mycoparasitic fungi: Magnaporthe oryzae (Pmk1), Pyrenophora teres (Ptk1), Cochliobolus heterostrophus (Chk1), Colletotrichum lagenarium (Cmk1), Fusarium oxysporum (Fmk1), Beauveria bassiana (BbMpk1), Metarhizium acridum (MaMk1), and Trichoderma virens (TmkA) [33,47,48,49,50,51,52,53]. Pls1 tetraspanins in B. cinerea, Magnaporthe grisea, and Colletotrichum lindemuthianum play a key role in the appressorium-mediated penetration into the host plant, since Pls1 null mutations result in appressoria that are unable to form functional penetration pegs [30,31,32]. The expression of this phenomenon was clearly observed in B. cinerea using a transcriptional fusion between the PLS1 promoter and an EGFP reporter gene [32]. The overall results obtained are in agreement with what has been observed by other authors, even when using different fungi and investigation techniques. Both Fus3/Kss1-type MAPKs and Pls1 tetraspanins have conserved virulence-related functions among taxonomically different fungal species, including B. cinerea [20,34,54,55]. A topical application of dsRNA molecules that trigger a gene knockdown is a flexible approach that does not require transgenic plants for RNAi-based protection against plant diseases. We identified three dsRNA molecules in B. cinerea: BcBmp3-dsRNA [15], BcBmp1-dsRNA, and BcPls1-dsRNA (this work), which all showed a high efficacy in RNAi against the corresponding genes by the application of the exogenous dsRNA molecules produced in vitro. These dsRNAs are specific for B. cinerea and are related to functions involved in the pathogenicity/virulence of the fungus; they have been used for SIGS experiments on whole lettuce plants with very promising results [56]. However, this interesting biotechnological approach needs to overcome some aspects before being translated into practical applications. The dsRNA molecules are susceptible to degradation when exposed to the environment, such as on the surface of plants or fruits. One of the best approaches to increase the stability and longevity of naked dsRNAs for topical applications is to complex them with biocompatible nanoparticles [40,57,58]. In tomatoes and chickpeas, Niño-Sánchez et al. [59] reported that dsRNAs carried by layered double hydroxide particles increased the effectiveness of the protection over time against B. cinerea. SIGS-based disease management strategies require systems that can rapidly produce large quantities of dsRNA molecules and are cost-effective. Classical strategies for dsRNA production based on chemical synthesis or in vitro transcription are not feasible on a large scale due to high costs and low yields. The most suitable alternative is the production of dsRNAs using bacteria and yeasts as biofactories. In recent years, this option has allowed production costs to be significantly lowered, making the RNAi technique competitive on the market. Moreover, the products obtained from this technology are currently the subject of in-depth studies to verify their safety for the environment and for the consumer. Technical advances in the production and formulation of dsRNAs to improve their efficacy, stability, and persistence could therefore make it realistic to consider their use as “RNAi-based biofungicides” of a high commercial interest [8,9,60]. Looking ahead, RNAi can be considered a promising strategy due to its potential for the environmentally friendly control of B. cinerea as well as other economically important plant pathogenic fungi. Botrytis cinerea B05.10 was the fungal pathogen used in this study. It was a haploid strain obtained after a benomyl treatment of the wild-type isolate SAS56 [61,62]. In this study, Trichoderma harzianum T6776 and Fusarium oxysporum DAFE SP-21-23 were used as off-target organisms. The T. harzianum isolate T6776 is known as a promising biocontrol agent against different plant pathogens [63], and the F. oxysporum isolate DAFE SP-21-23 was recovered from asymptomatic Salicornia europea plants. All fungi were incubated on PDA (Biolife Italiana S.r.l., Milano, Italy) plates at 25 °C with a 12/12 NUV/light cycle unless indicated otherwise. The conidial suspensions were prepared from 7-to-10-day-old PDA cultures by gently scraping conidia from the surface of the culture with a sterile spatula in Sabouraud maltose broth (SMB: myco_logical peptone (Sigma-Aldrich, Saint Louis, MO, USA), 10 g L−1; maltose (Sigma-Aldrich, Saint Louis, MO, USA), 40 g L−1; pH, 5.6 ± 0.2) prepared with MilliQ water (EASYpure® II LF, Thermo Scientific, Waltham, MA, USA; resistivity, 18.2 MΩ cm−1). The resulting conidial suspension was filtered through a layer of sterile Miracloth (Calbiochem, San Diego, CA, USA), and the conidia concentration was checked with a hemacytometer (Bürker, LO—Laboroptik Ltd., Lancing, UK) and adjusted to the desired concentration with SMB. Fungal growth was studied in 96-well polystyrene microtiter plates (Cellstar®, Greiner Bio-One, Frickenhausen, Germany) to evaluate the effects of BcBmp1- and BcPls1-derived dsRNA (BcBmp1-dsRNA and BcPls1-dsRNA). Aliquots of a B. cinerea conidial suspension in SMB (5 × 102 spores) and 2 µg (final concentration 20 ng µL−1) of BcBmp1- or BcPls1-dsRNA were added to the wells (n = 8 for each treatment in a total assay volume of 100 µL). The controls included in each plate were prepared in SMB and consisted of: (i) 2 µg of Green Fluorescent Protein (GFP)-derived dsRNA (GFP-dsRNA) + B. cinerea conidia, (ii) no dsRNA + B. cinerea conidia + TE buffer (10 µM Tris/1.0 µM EDTA, pH of 7.0), and (iii) no dsRNA and no conidia + TE buffer (blank background control). The volume of TE corresponded exactly to the volume of the dsRNA added for the treatment. The plates were incubated at 25 °C with a 12/12 NUV/light cycle and fungal growth was assessed by measuring the optical density (OD) at 595 nm with a microplate reader spectrophotometer (Bio-Rad, Model 680, Bio-Rad Laboratories, Cressier, Switzerland) at different times between 0 and 96 h. The experiments were repeated three times. Absorbance values were converted to the percentage of fungal growth relative to that of the untreated control (100%) using the following formula: After 48 and 96 h of incubation, B. cinerea mycelium was collected and washed with sterile MilliQ water by centrifugation for a fungal transcript analysis to assess the silencing of the BcBmp1 and BcPls1 genes. To determine the effect of BcBmp1- and BcPls1-derived dsRNA (BcBmp1-dsRNA and BcPls1-dsRNA) on the conidial germination of B. cinerea, the experiments were performed as previously described except, in this case, the conidial suspension was adjusted to 1 × 106 conidia for each well. After 3, 6, and 9 h of incubation, germination rates were determined microscopically (Dialux 22, Leitz, Oberkochen, Germany) by taking small aliquots from each well. Conidia (n ≥ 200 for each biological replicate) were considered germinated when the germ tube length exceeded the conidial diameter. The percentage of germination was estimated by counting the number of germinated conidia relative to the total number of conidia. The experiment was performed in triplicate and repeated twice. Lactuca sativa cv. “Romana” (Romana Verde degli Ortolani, Sementi Dom Dotto S.p.A., Udine, Italy) plants were grown in a climate chamber with a 12 h photoperiod at 22 ± 1 °C with 65% relative humidity. Then, 20 µL of BcBmp1- or BcPls1-dsRNA (20 ng µL−1), GFP-dsRNA (20 ng µL−1), or sterile MilliQ water + TE buffer (10 µM Tris/1.0 µM EDTA, pH 7.0) were dropped on the adaxial surface of detached lettuce leaves (third or fourth pair) taken from 3-to-4-week-old plants (n = 16). The volume of TE corresponded exactly to the volume of the dsRNA added for the treatment. The dsRNAs were allowed to dry, and then 5 µL droplets of the B. cinerea conidial suspension (5 × 102 spores) were placed on the same spot. The inoculated lettuce leaves were placed on sterile filter paper moistened with sterile MilliQ water in transparent plastic boxes (16 cm × 11.5 cm × 5 cm) and were incubated at 25 °C with a 12/12 NUV/light cycle. Infection symptoms were observed and photographed at 5 days post-inoculation (dpi). The necrotic areas (mm2) were measured using the ImageJ software, version 1.53a (http://imagej.nih.gov/ij, accessed on 21 October 2022) from digital images of the detached leaves [64]. The experiment was repeated twice. For DNA extraction, the fungal mycelium of B. cinerea B05.10 was grown in sterile 50 mL Falcon tubes filled with 25 mL of SMB at 150 rpm (Rosi1000™, Thermolyne, Dubuque, IA, USA) for 2–4 d at 25 ± 1 °C. The mycelium was harvested by filtration through a layer of sterile Miracloth, washed with sterile MilliQ water, and dried on sterile filter paper. The total genomic DNA was extracted by the Genesig Easy DNA/RNA extraction kit (Primer Design Ltd., Chandler’s Ford, UK). The mycelium (200 mg) was placed into a 2 mL sterile extraction tube, which was prefilled with 0.5 mm of silica acid-washed glass beads (Sigma-Aldrich, Saint Louis, MO, USA) and 500 µL of sample prep solution supplied by the kit. The mycelium was then homogenized by a bead-beating method using the BeadBug™ Microtube homogenizer (Benchmark Scientific Inc., Sayreville, NJ, USA). Tubes were subjected to three beating cycles of 30 s at 4000 rpm, followed by 30 s on ice. The lysed suspension (200 µL) was collected and DNA extraction was performed by following the kit manufacturer’s instructions. We used the si-Fi software for the in silico analysis (siRNA Finder ver. siFi21_1.2.3-0008, https://sourceforge.net/projects/sifi21/, accessed on 7 February 2022), which is designed for RNAi silencing efficiency predictions and off-target analyses. This analysis was performed on the sequences of both the BcBmp1 and BcPls1 CDS of B. cinerea B05.10 (GenBank accession numbers NC_037311.1 and NC_037318.1, respectively; Figure S1A) in order to choose the optimal sequence for the design of dsRNAs to be employed in RNAi experiments (Figure S1B). The default parameters were used and the cDNA of B. cinerea B05.10 obtained from EnsemblFungi (http://ensemblgenomes.org/pub/fungi/release-50/fasta/botrytis_cinerea/cdna/ accessed on 7 February 2022) was selected as the database. The genomic DNA of B. cinerea B05.10 was used as the template for the synthesis of a partial sequence of the Mitogen-Activated Protein Kinase (MAPK) BcBmp1 gene (GenBank accession number NC_037311.1) that was 344 bp long (Table S3), and of a partial sequence of the tetraspanin BcPls1 gene (GenBank accession number NC_037318.1) that was 413 bp long (Table S3). The PCR conditions were the following: 95 °C for 5 min; 5 cycles of 30 s at 95 °C, 30 s at 63 °C, and 30 s at 72 °C; 30 cycles of 30 s at 95 °C, 30 s at 77 °C, and 30 s at 72 °C; and 72 °C for 5 min. The pCT74-sGFP plasmid [65] was used as the template for the synthesis of the Green Fluorescent Protein (GFP)-dsRNA (Table S3) of 712 bp. The PCR conditions were the following: 95 °C for 5 min; 5 cycles of 30 s at 95 °C, 30 s at 55 °C, and 30 s at 72 °C; 30 cycles of 30 s at 95 °C, 30 s at 76 °C, and 30 s at 72 °C; and 72 °C for 5 min. The DreamTaq DNA polymerase was used (Thermo Fischer Scientific, Vilnius, Lithuania). The amplified products were purified and sequenced on both strands. The following software programs were used to analyze the amplified sequence: GENESCAN, FASTA, BLAST, and CLUSTALW, which are available at the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/ accessed on 15 March 2022) [66]. Moreover, the PROSITE and PFAM databases were used to identify conserved domains [67,68]. The conserved motifs were also recognized by searching the conserved domain database (CDD) at NCBI and by the program InterPro at EMBL-EBI (http://www.ebi.ac.uk/ accessed on 20 March 2022). The analyses were performed using the representative genome of B. cinerea B05.10 [22,69] and the GFP sequence of the pCT74-sGFP plasmid [65]. The dsRNAs were generated using the MEGAscript RNAi Kit (Invitrogen by Thermo Fisher Scientific, Vilnius, Lithuania) as previously described [15]. Primer pairs for BcBmp1-dsRNA, BcPls1-dsRNA (Figure S1A,B), and GFP-dsRNA with a T7 promoter sequence at the 5′end of both the forward and reverse primers were designed for the amplification of dsRNA (Table S3). The total RNA was extracted from 100 mg of mycelium; lettuce leaves treated with GFP-dsRNA, BcBmp1-dsRNA, or BcPls1-dsRNA; or untreated leaves (Ctrl). The extraction was performed using the RNeasy Plant Mini Kit (Qiagen, Milan, Italy) by following the manufacturer’s instructions. The concentration of each RNA sample was measured using the QubitTM RNA BR Assay Kit in a Qubit™ 4 Fluorometer (Invitrogen by Thermo Fisher Scientific Inc., Eugene, OR, USA), and the integrity was evaluated by agarose gel electrophoresis. The RNA samples were treated with amplification-grade DNase I (Sigma-Aldrich, St. Louis, MO, USA) and reverse-transcribed into cDNA (400 ng per sample) using the iScript cDNA synthesis kit (BioRad, Hercules, CA, USA). The synthesized cDNAs were used for quantitative Real-Time polymerase chain reaction (qRT-PCR) using gene-specific primer pairs (Table S3). qRT-PCRs were performed using Real-Time Step One apparatus (Applied Biosystem, Foster City, CA, USA) by using the recommended thermal-cycling conditions. For the in vitro growth of B. cinerea mycelium, BcSac7 (GenBank accession number XM_024693149.1) and β-tubulin A (BctubA, GenBank accession number XM_024690731.1) were selected as housekeeping genes. Although both the endogenous control genes tested exhibited stable expression among the different samples, BctubA was chosen to normalize the gene expression data for its high transcriptional stability. For the inoculated lettuce leaves, genes encoding the TIP41-like protein (LsTIP41, GenBank accession number NC_056630.1), ubiquitin-NEDD8-like protein RUB2 (LsUBQ-RUB2, GenBank accession number NC_056624.1), and glyceraldehyde-3-phosphate dehydrogenase GAPC1, cytosolic (LsGAPDH, GenBank accession number NC_056630.1) were selected as housekeeping genes [70]. Although all the tested endogenous control genes exhibited a stable expression among the different samples, LsGAPDH was chosen to normalize the gene expression data for its high transcriptional stability. The amplifications of the target genes and the endogenous controls were run using three biological replicates, each with three technical replicates, and were analyzed on the same plate in separate tubes. The relative abundance of transcripts was calculated by using the 2−∆∆CT method [71]. Relative transcript values were calculated using the Ctrl and GFP controls as reference samples. Before the quantification, a validation experiment was performed to ensure that the amplification efficiency of the target and reference genes was closely the same. The precursor sequences used for the BcBmp1-dsRNA and BcPls1-dsRNA molecules were targeted against the complementary DNA (cDNA) databases of some phytopathogenic and beneficial fungi (Sclerotinia sclerotiorum, Alternaria alternata, Fusarium oxysporum, Rhizoctonia solani, Pythium ultimum, Trichoderma asperellum, T. harzianum, and Rhizophagous irregularis), humans, and lettuce using the si-Fi v21 software (default parameters) for the off-target prediction. The databases of three isolates of B. cinerea, including B05.10, were used as controls (Tables S1 and S2). The effects of Bmp1- and BcPls1-derived dsRNAs (BcBmp1-dsRNA and BcPls1-dsRNA) on the fungal growth of Trichoderma harzianum T6776 and Fusarium oxysporum DAFE SP21-23 were investigated in 96-well polystyrene microtiter plates as described above for B. cinerea (Section 4.2). The optical density (OD of the fungal mycelium at different times (24, 48, 72, and 96 h) was measured at 595 nm. The data obtained from the in vitro assay in the 96-microtiter plates were converted as growth percentages of the untreated control. All data were subjected to an analysis of variance (ANOVA) using the statistical program CoStat 6.4 (Cohort Software, Monterey, CA, USA). The percentage data were transformed into arcsine √ % before the ANOVA. In the expression analysis, the values were the means (±SE) from three different biological replicates for each treatment. All the means were separated by Tukey’s honestly significant difference post-hoc (HSD) test (p ≤ 0.05). The normality of the data was tested using a Shapiro–Wilk test, whilst the homoscedasticity was tested using Bartlett’s test.

PMC10003351

Joan Sala-Gaston,Laura Costa-Sastre,Leonardo Pedrazza,Arturo Martinez-Martinez,Francesc Ventura,Jose Luis Rosa

Regulation of MAPK Signaling Pathways by the Large HERC Ubiquitin Ligases

03-03-2023

ubiquitin,Large HERC,neurodevelopmental disease,cancer,MAPK,RAF,ERK,p38,PROTACs

Protein ubiquitylation acts as a complex cell signaling mechanism since the formation of different mono- and polyubiquitin chains determines the substrate’s fate in the cell. E3 ligases define the specificity of this reaction by catalyzing the attachment of ubiquitin to the substrate protein. Thus, they represent an important regulatory component of this process. Large HERC ubiquitin ligases belong to the HECT E3 protein family and comprise HERC1 and HERC2 proteins. The physiological relevance of the Large HERCs is illustrated by their involvement in different pathologies, with a notable implication in cancer and neurological diseases. Understanding how cell signaling is altered in these different pathologies is important for uncovering novel therapeutic targets. To this end, this review summarizes the recent advances in how the Large HERCs regulate the MAPK signaling pathways. In addition, we emphasize the potential therapeutic strategies that could be followed to ameliorate the alterations in MAPK signaling caused by Large HERC deficiencies, focusing on the use of specific inhibitors and proteolysis-targeting chimeras.

Regulation of MAPK Signaling Pathways by the Large HERC Ubiquitin Ligases Protein ubiquitylation acts as a complex cell signaling mechanism since the formation of different mono- and polyubiquitin chains determines the substrate’s fate in the cell. E3 ligases define the specificity of this reaction by catalyzing the attachment of ubiquitin to the substrate protein. Thus, they represent an important regulatory component of this process. Large HERC ubiquitin ligases belong to the HECT E3 protein family and comprise HERC1 and HERC2 proteins. The physiological relevance of the Large HERCs is illustrated by their involvement in different pathologies, with a notable implication in cancer and neurological diseases. Understanding how cell signaling is altered in these different pathologies is important for uncovering novel therapeutic targets. To this end, this review summarizes the recent advances in how the Large HERCs regulate the MAPK signaling pathways. In addition, we emphasize the potential therapeutic strategies that could be followed to ameliorate the alterations in MAPK signaling caused by Large HERC deficiencies, focusing on the use of specific inhibitors and proteolysis-targeting chimeras. Ubiquitylation is a post-translational modification that consists of the attachment of ubiquitin to a substrate protein. Ubiquitin can be linked as a single moiety or in the form of polymeric chains of different topology. Over the years, it has been discovered that proteins can also be modified by ubiquitin-like molecules such as SUMO or NEDD8. In addition, further modifications of ubiquitin with acetylation and phosphorylation have also been identified. Similar to a code, different ubiquitin modifications lead to different outcomes in the cells [1]. Typically, ubiquitin attaches to a substrate through the formation of a covalent bond between the C-terminal glycine residue of ubiquitin and an internal lysine residue of the substrate. However, in the last decade non-lysine ubiquitylation through ester linkages on serine, threonine and cysteine residues have also been established [2,3]. This expands the ubiquitin code with new layers of ubiquitin modifications and shows the complexity and potential versatility of the ubiquitin code in cell signaling. Ubiquitin E3 ligases are the enzymes that catalyze the transfer of ubiquitin to a protein substrate. Therefore, they determine the precise substrate specificity of ubiquitylation, and play essential roles in the cell signaling networks mediated by ubiquitin [4,5]. According to their structure and mechanism of ubiquitin transfer, they can be classified into three main kinds: Really Interesting New Gene (RING) E3s, Homologous to the E6AP Carboxyl Terminus (HECT) E3s and RING-in-Between-RING (RBR) E3s [6]. RING E3s are the most abundant class. Up to 600 different types have been described in humans. They are characterized by the presence of a RING or U-box domain. Although U-box-containing E3 ligases have sometimes been classified as an independent class of E3s, sequence-profile analysis has shown that the U-box is actually a derived version of the RING finger, their mechanism of action being very similar [6,7]. These domains bind the ubiquitin-charged E2 enzyme and catalyze the transfer of ubiquitin directly to the substrate. Therefore, they act as a scaffold positioning the E2 enzyme in relation to the substrate protein [8]. Conversely, the HECT E3s catalyze ubiquitin transfer to the substrate protein by a two-step reaction. In brief, they present a HECT domain in their C-terminal region. This domain holds a bilobed structure that enables the transmission of the ubiquitin molecule to the target protein. Specifically, the first lobe (the one closest to the amino terminus) binds the E2 enzyme from which the ubiquitin is transferred to a catalytic cysteine located in the second lobe, forming a thioester bond. Next, the conjugation of ubiquitin to the target protein is catalyzed. In humans, 28 different types of HECT E3s have been identified [9]. RBR E3s represent the third class of E3 ligases. They are characterized by a mixed mechanism of ubiquitin transfer. They bind the E2 enzyme to a RING1 domain and transfer the ubiquitin to a second domain called RING2, which contains a catalytic cysteine. Then, the ubiquitin is transferred to the substrate protein. Despite being a small family, RBR E3s regulate different cellular process in human cells [10]. Centering now on HECT ubiquitin ligases, sequence and structural comparison analysis has shown a complex division of the HECT family into 16 different subfamilies: NEDD4-like proteins, Small HERCs, Large HERCs and 13 different subfamilies formerly called “other HECTs” [11]. In this review, we will focus on the HECT family of E3s and more specifically on the Large HERC subfamily, which is structurally characterized by the presence of the HECT domain in the C-terminal region and more than one RCC1-Like domain. This family is composed of two members: HERC1 and HERC2 [12]. Ubiquitin modifications regulate different cellular processes through proteolytic mechanisms, including targeting the substrate for proteasomal and autophagic degradation, but also through non-proteolytic mechanisms, for instance regulating protein interactions, subcellular localization and enzymatic activities. It is therefore not surprising that ubiquitylation is implicated in the regulation of several intracellular signaling pathways [13]. Some of these are the mitogen-activated protein kinases (MAPKs) signaling pathways. MAPKs constitute intracellular signal transduction cascades that in response to various extracellular signals elicit an appropriate intracellular response [14]. Each MAPK cascade consists of three core protein kinases: MAPKKK (MAP3K), MAPKK (MAP2K) and MAPK. MAP3Ks are the most upstream kinases and they activate the MAP2Ks by phosphorylation. In turn, MAP2Ks phosphorylate the downstream MAPKs, thus forming a three-tiered phosphorylation cascade [15]. Several HECT ubiquitin ligases have been implicated in the regulation of these pathways through different mechanisms [16]. In this review, we will give some insight into how HECT ubiquitin ligases can regulate MAPKs and more specifically, we will focus on the Large HERCs, since knowledge about their involvement in MAPK signaling is fairly recent and has grown in the last years. The physiological relevance of the Large HERCs is illustrated by their involvement in different diseases as shown in Figure 1. Although expressed in different tissues, Large HERCs are notably expressed throughout different areas of the nervous system [17]. Therefore, it is not surprising that most of the diseases with which these ubiquitin ligases are related are of a neurological nature. Germ-line mutations in the HERC1 gene are mostly associated with an autosomal recessive neurodevelopmental disorder called MDFPMR syndrome. This acronym comes from the phenotypic description of this disease, characterized by Macrocephaly, Dysmorphic Facies and PsychoMotor Retardation (OMIM #617011) [19,20,21,22,23]. In addition, genetic analysis has identified HERC1 as a risk factor in the autism spectrum disorder, Parkinson’s disease, schizophrenia and febrile seizures [24,25,26,27,28]. Moreover, a missense mutation in mice that causes loss of cerebellar Purkinje cells, tremor and unstable gait also provokes myelin abnormalities in the peripheral nervous system, which are histological hallmarks of neuropathic periphery diseases [29]. Recently, HERC1 was identified as a differentially expressed gene in the major depressive disorder associated with COVID-19 [30]. Other non-neurological diseases related to HERC1 include human immunodeficiency virus (HIV) acquisition and acquired immunodeficiency syndrome (AIDS) [31], diabetes [32], cardiovascular disease [33] and osteopenia [34] (Figure 1, HERC1 section). On the other hand, germ-line mutations in HERC2 are also associated with an autosomal recessive neurodevelopmental disorder (OMIM #615516). It was first identified in an Old Amish community holding a loss-of-function mutation in the HERC2 gene (c.1781C>T, p.Pro594Leu). Later, other loss-of-function mutations have also been described. All cases show global developmental delay with Angelman syndrome-like features such as intellectual disability, autism spectrum disorders and movement disorders [35,36,37,38,39,40,41,42,43,44]. For further details, its phenotypic characteristics have been recently reviewed in [62]. In addition, due to the association between HERC2 and LRRK2 proteins, it has been suggested that HERC2 might be involved in Parkinson’s disease pathogenesis [45]. Other brain-related disorders in which HERC2 has been associated are agenesis of the corpus callosum (ACC), brain arteriovenous malformation (BAVM), diabetic cerebral ischemia–reperfusion (I/R) injury and central precocious puberty [46,47,48,49]. HERC2 has also been linked with other types of pathology such as refractive astigmatism [50], asthma [56], hypertension [57,58], several skin conditions such as vitiligo and rosacea [59,60,61] and some inflammatory diseases. Among these inflammatory diseases there are some related to the digestive system and, recently, HERC2 has also been described to promote inflammation-driven cancer stemness and immune evasion in hepatocellular carcinoma [51,52,53,54,55] (Figure 1, HERC2 section). The involvement of both Large HERC family members in cancer has been extensively studied and it was previously reviewed in [18] (Figure 1). Putting efforts into basic research to better understand how cell signaling is altered in these different pathologies is important to uncover novel therapeutic targets. To this end, in this review we will summarize the recent advances in how the HECT E3s and, more specifically, Large HERCs, can regulate the MAPK signaling pathways, emphasizing the potential implications in disease. MAPK signaling pathways are intracellular signal transduction cascades that in response to various extracellular signals elicit an appropriate intracellular response affecting different cellular processes such as cell growth, cell proliferation, differentiation, migration, stress responses, survival and apoptosis. MAPK cascades can be activated by several factors such as hormones, growth factors, inflammatory cytokines and different types of stress [14]. Each MAPK cascade consists of three core protein kinases: MAPKKK (MAP3K), MAPKK (MAP2K) and MAPK, that in the classical three-tiered cascade are activated sequentially. In brief, in response to different stimuli, MAP3Ks are activated through phosphorylation, often as a result of their interaction with a small GTP-binding protein of the Ras/Rho family. MAP3K activation leads to the phosphorylation and activation of MAP2K, which then stimulates MAPK activity through phosphorylation. In turn, activated MAPKs eventually lead to the phosphorylation of target regulatory proteins in order to elicit an appropriate cellular response [15]. Currently, seven different MAPK cascades have been identified in mammals and named according to their central MAPK component. These are the so-called “conventional MAP kinases”, which include ERK1/2, p38, JNK and ERK5; and those termed “atypical MAPK kinases”, consisting of ERK3/4, ERK7/8 and NLK [16,63,64]. In recent years, it has become clear that the MAPK catalytic modules consisting of kinases that mediate the activation of downstream effectors are exposed to several layers of regulation. These regulatory mechanisms are not restricted to protein phosphorylation; instead, they involve other post-translational modifications such as ubiquitylation. Ubiquitylation catalyzed by E3 ligases influences MAPK pathways in terms of the duration and type of the signaling cascade through its role in affecting the assembly of protein kinase complexes, subcellular localization and the degradation of MAPK components or their downstream substrates [65]. For this reason, it is not surprising that several HECT ubiquitin ligases have been linked to these signaling pathways in different studies. Below, we will give a brief overview of the role of HECT E3s in MAPK regulation and, in the next section, we will focus on the Large HERC subfamily, as knowledge about their involvement in these pathways is fairly new. In Table 1, we summarize the current scientific knowledge of HECT E3 enzymes that regulate the conventional MAPK signaling pathways, indicating the related molecular mechanism that has been described. Some of them regulate a single MAPK pathway. For instance, NEDD4, UBE3A and HUWE1 regulate the ERK signaling pathway. NEDD4 regulates ubiquitylation of the G-protein coupled receptor (GPCR) mGlu7. Going into detail, after agonist stimulation mGlu7 is ubiquitylated by NEDD4, which induces its endocytosis and eventually leads to its degradation by both the lysosomal and proteasomal pathways. This mechanism is required for the mGlu7-induced ERK1/2 activation [69]. Moving now to UBE3A, in mice holding Ube3a deficiency, activation of ERK1/2 induced by membrane depolarization by KCl treatment is impaired. This suggests the presence of a regulatory mechanism between this HECT E3 and the ERK1/2 pathway, where UBE3A would act as an activator of this signaling pathway [84]. Finally, regarding HUWE1, it has been shown to regulate the ubiquitylation and protein levels of Shoc2, a C-RAF signaling partner. In turn, both Shoc2 and HUWE1 are required to control ubiquitylation and protein levels of C-RAF. In agreement with this, HUWE1 silencing increases C-RAF protein levels, which triggers ERK1/2 phosphorylation [85]. Other HECT E3 ubiquitin ligases have been implicated in the p38 signaling pathway. This is the case of HERC2 and UBR5. In both cases, their deficiency is related to increased levels of p38 activity, suggesting that they have an inhibitory role in this pathway. While the mechanism behind p38 regulation by UBR5 is not well established yet, HERC2 regulates p38 activity through controlling C-RAF ubiquitylation and its subsequent proteasomal degradation [68,86]. Lastly, in terms of the JNK signaling pathway, it has been described that the HECT E3 SMURF2 promotes ubiquitylation of tumor necrosis factor receptor 2 (TNF-R2). The formation of this ubiquitin chain appears to be required for TNF-R2-induced JNK activation [83]. There are also some HECT E3s whose involvement in more than one MAPK signaling pathway is currently described. For example, HERC1 regulates both ERK1/2 and p38 signaling pathways by modulating C-RAF protein levels through ubiquitylation [34,66,67]. Another HECT E3 that regulates both ERK1/2 and p38 signaling pathways is NEDD4L. NEDD4L overexpression is reported to inhibit ERK1/2 activation. In addition, NEDD4L regulates K63-linked ubiquitylation of protease-activated receptor 1 (PAR1), which leads to its activation and promotes recruitment of TAB2, which in turn associates with TAB1 and induces p38 activation independent of MKK3 and MKK6. Thus, while acting as a repressor of the ERK1/2 pathway, it would act as an activator of the p38 pathway [70,71,72]. Other HECT E3s have been shown to regulate three distinct MAPK pathways, including the ERK1/2, p38 and JNK cascades. In this regard, the ubiquitin ligase ITCH has been extensively studied for its multiple roles in the regulation of MAPKs, acting at different levels and affecting them in different ways in terms of activation or inhibition depending on the target and the context. Specifically, ITCH is recruited by GRAMD4 to promote ubiquitylation and protein degradation of the MAP3K TAK1, thus controlling activation of the conventional MAPKs ERK1/2, p38 and JNK [73]. In addition, K-27 linked ubiquitylation of the MAP3K B-RAF by ITCH leads to sustained B-RAF activation and subsequent elevation of the MEK/ERK1/2 signaling pathway [74]. Regarding the p38 pathway, ITCH acts inhibiting it, from one hand by targeting TXNIP for ubiquitin-dependent proteasome degradation, and from the other hand by catalyzing the K48-linked ubiquitylation and degradation of TAB1, a known activator of p38 [75,76]. In relation to the JNK pathway, ITCH has been described to regulate MKK4 ubiquitylation and subsequent degradation, thus decreasing JNK activation [77]. The HECT E3 ligases WWP1 and SMURF1 have also been related with the regulation of the three conventional MAPK signaling pathways ERK1/2, p38 and JNK. In cardiomyocytes, it has been reported that WWP1 regulates ubiquitylation and subsequent degradation of KLF15, which acts as an inhibitor of MAPK signaling. In particular, it was demonstrated that WWP1 overexpression down-regulates KLF15 and subsequently enhances ERK1/2 and p38 activation under hypoxic conditions [78]. Moreover, another study identified that under LPS stimulation, WWP1 binds TRAF6 promoting its K48-linked polyubiquitylation and subsequent proteasomal degradation. TRAF6 eventually leads to MAPK activation, hence, by means of increased protein levels of TRAF6, WWP1 knockdown activates ERK1/2, p38 and JNK pathways [79]. Regarding SMURF1, it seems to act, generally, as a repressor of the three conventional MAPK pathways ERK1/2, p38 and JNK. From one hand by interacting and modulating the ubiquitylation-mediated proteasomal degradation of MyD88, which is a major adaptor upstream protein of the Toll-Like Receptor (TLR) pathway [80]. From the other hand by promoting ubiquitylation and subsequent proteasomal degradation of the MAP3K MEKK2, a known activator of ERK1/2, p38 and JNK [81,82]. As shown in the table (Table 1) and indicated in the previous paragraph, the same HECT E3 can regulate different MAPK pathways by targeting a common upstream factor. For example, ITCH regulates ERK1/2, p38 and JNK signaling pathways by controlling ubiquitylation and protein degradation of the upstream kinase TAK1 [73]. Thus, there is some evidence that some HECT E3s regulate crosstalks between different MAPK cascades. Another example is HERC1, which regulates both ERK1/2 and p38 pathways via regulation of C-RAF protein stability. Thus, C-RAF, which has classically been defined as a MAP3K of the ERK1/2 pathway, appears that it may also act as a crosstalk factor for the p38 pathway, at least in a context of regulation by HERC1 [67]. Interestingly, the other Large HERC member, HERC2, also regulates p38 signaling through C-RAF [68]. This raises the question of whether this crosstalk of C-RAF to the p38 pathway is specifically regulated by Large HERCs. The precise molecular mechanisms of how the Large HERCs regulate MAPK signaling pathways through C-RAF are discussed in the following section. Small and Large HERC subfamilies of the HECT ubiquitin ligases were initially classified together and defined by the presence of an HECT domain and RCC1-like domains [12]. However, it was demonstrated that the RCC1-like domains from Small and Large HERCs had significant phylogenetic differences [87], and that these domains were acquired by each subfamily in two independent events. Thus, the homology between Large and Small HERCs is due to a convergent evolution phenomenon rather to a common phylogenetic ancestor and, consequently, they should be classified in different protein subfamilies [11]. In addition, while Small HERCs only have one single RCC1-like domain, Large HERCs contain more than one in their structure. The Large HERC subfamily is composed by two members: HERC1 and HERC2. Due to their huge size they are designated as “Large” HERCs. HERC1 has 4861 amino acids with a molecular weight of 532 kDa, while HERC2 has 4834 amino acids and 528 kDa of molecular weight [12]. Structurally, HERC1 possesses the HECT domain, two RCC1-like domains (RLD1 and RLD2), an SPla and ryanodine receptor (SPRY) motif, a Bcl-2 homology domain 3 (BH3) and a Trp-Asp rich (W-D) 40-amino acid repeat region (WD40). HERC2, in turn, presents the HECT domain, three RCC1-like domains (RLD1, RLD2 and RLD3), a cytochrome b5-like region (Cyt b5), a mind-bomb/HERC2 (M-H) domain, a conserved domain within Cul7, PARC and HERC2 (CPH), a ZZ-type zinc finger region and a domain homologous to subunit 10 of APC (DOC) [9,12] (Figure 2a). Knowledge about the involvement of the Large HERCs in the regulation of MAPK signaling is fairly recent and has evolved in the past years. In 2018 the involvement of HERC1 in the regulation of these signaling pathways was identified for the first time. More recently, a role for HERC2 was also described. Interestingly, both HERC1 and HERC2 appear to regulate MAPKs through the same protein target, the serine and threonine kinase C-RAF [66,68]. C-RAF, also known as RAF1, belongs to a family of protein kinases that has three members: A-, B-, and C-RAF. All three share some structural characteristics containing three conserved regions (CR1, CR2 and CR3). CR1 contains a RAS-binding domain (RBD) and a cysteine-rich domain (CRD). Importantly, CR3 contains the kinase domain [88] (Figure 2b). Through its kinase domain, C-RAF, which acts as a MAP3K, initiates the RAF-MEK-ERK1/2 phosphorylation cascade. The main function of this signaling pathway is to regulate cell growth, proliferation, survival and differentiation. For this reason, it is not surprising that mutations in C-RAF have been linked to cancer [89,90]. Both members of the Large HERC family interact with the C-terminal region of C-RAF, with residues 301 to 648 reported to be the most relevant. This region contains the kinase domain. HERC1 interacts through its N-terminal region, and the residues described as the most relevant are those from position 1 to 412. This region contains a small first portion of the RLD1 domain [66]. In contrast, HERC2′s affinity for C-RAF appears to reside in its C-terminal region. The region comprising the residues 4252 to 4834 seems to be the most relevant. This region holds the HECT domain [68,91] (Figure 2a,b). Going into detail on the molecular mechanisms, HERC1 interacts with the MAP3K C-RAF and controls its protein stability by regulating its polyubiquitylation and subsequent proteasome-dependent degradation. Thus, HERC1 modulates the activation of the RAF-MEK-ERK1/2 pathway and controls cell proliferation [66]. Accordingly, HERC1 knockdown induces the stabilization of C-RAF, increasing its protein levels. In consequence, an overactivation of the RAF-MEK-ERK1/2 signaling cascade occurs. Remarkably, in these conditions of HERC1 deficiency, the p38 signaling pathway is also overactivated. The underlying molecular mechanism is that by controlling C-RAF protein levels, HERC1 also regulates the expression of MKK3, the MAP2K of the p38 signaling pathway. This crosstalk between ERK and p38 pathways occurs because the induced overexpression of C-RAF after HERC1 knockdown positively regulates the mRNA levels of MKK3 [66,67]. The physiological relevance of this crosstalk is that its activation affects cellular migration (Figure 3a). Therefore, the overactivation of ERK along with p38 that is triggered upon HERC1 deficiency could presumably lead to tumorigenesis and malignancy due to upregulation of the processes of cell proliferation and cell migration, pointing to HERC1 as a probable tumor suppressor protein [18,67,92]. The first evidence of the involvement of the other Large HERC family member, HERC2, in the regulation of MAPK signaling came from proteomic analysis where HERC2 was reported to be associated with E6AP, NEURL4 and the atypical MAPK ERK3 [93,94]. More recently, the participation of HERC2 in regulation of the p38 signaling pathway has also been described, expanding our understanding of the Large HERCs and their involvement in MAPK signaling. Similarly to HERC1, HERC2 interacts with C-RAF and controls its protein levels by regulating its polyubiquitylation-dependent proteasome degradation. However, although HERC2 knockdown increases C-RAF protein levels, this is not signaled through the RAF-MEK-ERK1/2 signaling pathway. Instead, it triggers MKK3-p38 cascade overactivation. This C-RAF-MKK3-p38 module induces the stabilization of the master regulator of the antioxidant response NRF2, which in turn enhances transcription of antioxidant genes such as SOD1, SOD2, GPX1 and its own transcription through the NFE2L2 gene (Figure 3b). This confers HERC2-deficient cells an overactivated antioxidant system, which causes an imbalance in the cellular redox homeostasis [68]. This mechanism could probably be exploited by tumor cells harboring HERC2 mutations, which would make cancer cells more resistant to the oxidative stress to which they are exposed [18,68]. A recent study also stablishes a regulatory link between HERC2 and NRF2. In this study, the authors described that HERC2 gene holds putative antioxidant response elements (AREs) in which NRF2 is coupled to promote its transcription [95]. This suggests the presence of a feedback loop regulation in which HERC2 controls NRF2 stability through the p38 pathway and subsequently, NRF2 promotes HERC2 expression through enhancing its transcription. However, how this feedback is regulated and in which contexts it occurs still requires additional investigations. It is interesting to note that although both HERC1 and HERC2 regulate MAPK signaling through modulating C-RAF protein levels, they diverge in the pathways that are finally modulated. I.e., while HERC1 regulates both ERK and p38 cascades, HERC2 regulation of C-RAF affects specifically the p38 pathway. Although the specific molecular mechanism by which these differences occur has not yet been described, there are some considerations important take into account. In first place, HERC1 and HERC2 proteins do not interact, suggesting that each of them forms a different protein complex with C-RAF. Secondly, while HERC1 interacts with the kinase domain of C-RAF through its N-terminal region, HERC2 does it through its C-terminal region, mainly involving its HECT domain (Figure 2a). Hence, the differences in cell signaling could be explained, at least in part, by the different complexes formed between C-RAF and each Large HERC protein [67,68]. Whether the alterations in these MAPK signaling pathways are associated with clinical outcomes in the neurodevelopmental disorders caused by mutations in HERC1 or HERC2 still requires further research. Even so, dysfunctions of the MAPK signaling pathways have already been implicated in several neurodevelopmental disorders, for instance autism spectrum disorder [96,97], which is also manifested in the syndromes caused by Large HERC mutations [17]. In addition, MAPK pathways are also associated with neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease and amyotrophic lateral sclerosis [98,99]. All things considered, a deeper understanding of how Large HERC-dependent MAPK signaling affects the clinical manifestations of these neurodevelopmental disorders could reveal novel therapeutic approaches for these rare diseases. Given that both HERC1 and HERC2 deficiency causes alterations in MAPK signaling due to increased levels of C-RAF, the most evident therapeutic strategy would be to inhibit C-RAF in order to block the triggered downstream overactivation. Indeed, the RAF inhibitors LY3009120 and sorafenib have shown success in counteracting ERK and p38 overactivation after HERC1 deficiency [66,67]. In the case of HERC2 deficiency, both inhibitors efficiently abrogate the increase in p38 phosphorylation caused by HERC2 downregulation and, importantly, they also reverse the overactivated antioxidant phenotype [68]. It is worth noting that sorafenib was approved for use in renal, hepatic and thyroid cancer in the USA in 2005 and in the EU in 2006 by the Food and Drug Administration (FDA) and European Medicines Agency (EMA), respectively [100,101]. Therefore, its use would represent a very feasible therapeutic option. However, experience with the use of RAF inhibitors in cancer has shown that there are some resistance mechanisms that eventually render cells insensitive to treatment (the RAF inhibitor paradox). The mechanistic basis by which this might occur is that RAF proteins form dimers. This implies that when RAF dimers are exposed to the inhibitors, binding of the drug to one monomer induces a conformational change that may result in the transactivation of the other non-drug bound monomer of RAF, and by this way bypass the inhibitory action [102,103]. With selective C-RAF inhibitors it seems that this phenomenon could also occur [104]. However, genetic ablation of C-RAF resulted in a complete regression of a subset of pancreatic carcinoma, inducing only some tolerable toxicities in adult mice [105]. These results suggest that other therapeutic approaches, aimed at the removal of the protein rather than in its inhibition, may provide greater therapeutic benefit. In the last few years, an innovative technology called proteolysis-targeting chimera (PROTAC) has gained interest in the field of drug discovery [106]. PROTACs are heterobifunctional small molecules comprised of a moiety that links a protein of interest (POI), a linker and another moiety capable of recruiting an E3 ubiquitin ligase. By approaching the POI to an E3, the PROTAC enables polyubiquitylation of the target and its subsequent degradation by the proteasome [107]. The main advantages of PROTACs compared to the traditional inhibitory drugs are their increased selectivity, their ability to target previously “undruggable” proteins due to the fact that they do not necessarily target catalytic pockets, and their catalysis of the elimination of the target from the cell, which is pharmacologically more effective than a mere target inhibition [108]. In addition, PROTACs may also avoid the phenomena of resistance and transactivation that occur with the use of some inhibitors. Taking this into account, could we use PROTACs to target MAPK alterations due to Large HERC deficiencies? So far, this approach has not been described nor studied in depth, but it might be a promising line of research. Since C-RAF is a common ubiquitylation target of the Large HERCs, and its accumulation is responsible for altered MAPK signaling in the case of HERC1 or HERC2 deficiency, one possibility could be to target C-RAF. In this aspect, several PROTACs against B-RAF, the most commonly mutated RAF isoform in cancer, have been successfully developed and provided promising results [108,109,110]. Hopefully, PROTAC technology will continue improving in the coming years, also expanding the number of target proteins to which they are directed, which may provide novel therapeutic opportunities. Large HERCs are involved in several diseases, with a notable implication in neurological diseases and cancer. HERC1 regulates ERK and p38 signaling pathways through controlling C-RAF protein levels. HERC2 regulates C-RAF protein levels, affecting the p38 signaling pathway. Downregulation of HERC1 or HERC2 causes accumulation of C-RAF protein levels which alters MAPK signaling. The use of RAF inhibitors such as sorafenib, or the development of specific PROTACs against C-RAF, may represent a promising therapeutic option to counteract alterations in MAPK signaling caused by HERC1 or HERC2 deficiency.

PMC10003355

Paloma Bermejo-Bescós,Karim L. Jiménez-Aliaga,Juana Benedí,Sagrario Martín-Aragón

A Diet Containing Rutin Ameliorates Brain Intracellular Redox Homeostasis in a Mouse Model of Alzheimer’s Disease

02-03-2023

quercetin,rutin,glutathione,APPswe,BACE1,Alzheimer’s disease

Quercetin has been studied extensively for its anti-Alzheimer’s disease (AD) and anti-aging effects. Our previous studies have found that quercetin and in its glycoside form, rutin, can modulate the proteasome function in neuroblastoma cells. We aimed to explore the effects of quercetin and rutin on intracellular redox homeostasis of the brain (reduced glutathione/oxidized glutathione, GSH/GSSG), its correlation with β-site APP cleaving enzyme 1 (BACE1) activity, and amyloid precursor protein (APP) expression in transgenic TgAPP mice (bearing human Swedish mutation APP transgene, APPswe). On the basis that BACE1 protein and APP processing are regulated by the ubiquitin–proteasome pathway and that supplementation with GSH protects neurons from proteasome inhibition, we investigated whether a diet containing quercetin or rutin (30 mg/kg/day, 4 weeks) diminishes several early signs of AD. Genotyping analyses of animals were carried out by PCR. In order to determine intracellular redox homeostasis, spectrofluorometric methods were adopted to quantify GSH and GSSG levels using o-phthalaldehyde and the GSH/GSSG ratio was ascertained. Levels of TBARS were determined as a marker of lipid peroxidation. Enzyme activities of SOD, CAT, GR, and GPx were determined in the cortex and hippocampus. ΒACE1 activity was measured by a secretase-specific substrate conjugated to two reporter molecules (EDANS and DABCYL). Gene expression of the main antioxidant enzymes: APP, BACE1, a Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), caspase-3, caspase-6, and inflammatory cytokines were determined by RT-PCR. First, overexpression of APPswe in TgAPP mice decreased GSH/GSSG ratio, increased malonaldehyde (MDA) levels, and, overall, decreased the main antioxidant enzyme activities in comparison to wild-type (WT) mice. Treatment of TgAPP mice with quercetin or rutin increased GSH/GSSG, diminished MDA levels, and favored the enzyme antioxidant capacity, particularly with rutin. Secondly, both APP expression and BACE1 activity were diminished with quercetin or rutin in TgAPP mice. Regarding ADAM10, it tended to increase in TgAPP mice with rutin treatment. As for caspase-3 expression, TgAPP displayed an increase which was the opposite with rutin. Finally, the increase in expression of the inflammatory markers IL-1β and IFN-γ in TgAPP mice was lowered by both quercetin and rutin. Collectively, these findings suggest that, of the two flavonoids, rutin may be included in a day-to-day diet as a form of adjuvant therapy in AD.

A Diet Containing Rutin Ameliorates Brain Intracellular Redox Homeostasis in a Mouse Model of Alzheimer’s Disease Quercetin has been studied extensively for its anti-Alzheimer’s disease (AD) and anti-aging effects. Our previous studies have found that quercetin and in its glycoside form, rutin, can modulate the proteasome function in neuroblastoma cells. We aimed to explore the effects of quercetin and rutin on intracellular redox homeostasis of the brain (reduced glutathione/oxidized glutathione, GSH/GSSG), its correlation with β-site APP cleaving enzyme 1 (BACE1) activity, and amyloid precursor protein (APP) expression in transgenic TgAPP mice (bearing human Swedish mutation APP transgene, APPswe). On the basis that BACE1 protein and APP processing are regulated by the ubiquitin–proteasome pathway and that supplementation with GSH protects neurons from proteasome inhibition, we investigated whether a diet containing quercetin or rutin (30 mg/kg/day, 4 weeks) diminishes several early signs of AD. Genotyping analyses of animals were carried out by PCR. In order to determine intracellular redox homeostasis, spectrofluorometric methods were adopted to quantify GSH and GSSG levels using o-phthalaldehyde and the GSH/GSSG ratio was ascertained. Levels of TBARS were determined as a marker of lipid peroxidation. Enzyme activities of SOD, CAT, GR, and GPx were determined in the cortex and hippocampus. ΒACE1 activity was measured by a secretase-specific substrate conjugated to two reporter molecules (EDANS and DABCYL). Gene expression of the main antioxidant enzymes: APP, BACE1, a Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), caspase-3, caspase-6, and inflammatory cytokines were determined by RT-PCR. First, overexpression of APPswe in TgAPP mice decreased GSH/GSSG ratio, increased malonaldehyde (MDA) levels, and, overall, decreased the main antioxidant enzyme activities in comparison to wild-type (WT) mice. Treatment of TgAPP mice with quercetin or rutin increased GSH/GSSG, diminished MDA levels, and favored the enzyme antioxidant capacity, particularly with rutin. Secondly, both APP expression and BACE1 activity were diminished with quercetin or rutin in TgAPP mice. Regarding ADAM10, it tended to increase in TgAPP mice with rutin treatment. As for caspase-3 expression, TgAPP displayed an increase which was the opposite with rutin. Finally, the increase in expression of the inflammatory markers IL-1β and IFN-γ in TgAPP mice was lowered by both quercetin and rutin. Collectively, these findings suggest that, of the two flavonoids, rutin may be included in a day-to-day diet as a form of adjuvant therapy in AD. Decline in cognitive function is a fundamental clinical neurodegeneration symptom strictly related to age [1]. The impact of nutrition on age-associated cognitive decline is an increasingly growing topic, as it is a vital factor that can easily be modified. Pathological changes in the brain observed during cognitive decline take place well before any clinical manifestation, which mostly occur in old age. This provides a lengthy period of time to establish prevention strategies concerning age-related cognitive decline and dementia, which is a major public health concern [2]. For many years, intensive research on compounds of natural origin, found in day-to-day diets, has been carried out on cognitive-enhancing therapy [3]. One of the most common age-related neurodegenerative diseases is Alzheimer’s disease (AD), which is characterized by two neuropathological hallmarks: amyloid-β (Aβ) plaques and neurofibrillary tangles. In terms of research on animals, animal models can simulate the asymptomatic phase of AD by modifying the Aβ precursor protein (APP), for example [4,5]. It is remarkable that several bioactive phytochemicals derived from plants associated with various health benefits and decreased risk of many diseases have been screened for forming noncovalent complexes with the amyloid-β (Aβ) peptide [3]. Although numerous traditional medicines and natural dietary products have shown great progress toward AD pathology mitigation, we are fully aware of the limitations of AD animal models, since promising effects of those substances are not always replicable in human studies [6]. However, due to the difficulty of analyzing brain tissue in humans, especially at very early stages of progression, studies in rodent models are necessary. As a result, these experimental models may support the development of useful agents from traditional medicines and safe natural compounds to delay the progression of neurodegenerative diseases. Thus, testing natural compounds, found in day-to-day diets, for disease prevention and protection against the risk of AD, should be a priority. Among these important dietary natural agents is quercetin, which is the main polyphenolic flavonoid in several fruits and vegetables [7]. Quercetin is mainly present in its glycoside form, i.e., rutin. For its part, rutin (quercetin-3-O-rutinoside) has shown profound effects on the various cellular functions that underpin several pathological conditions, namely antimicrobial, anticarcinogenic, antithrombotic, cardioprotective, and neuroprotective. These pharmacological effects are mainly associated with rutin’s anti-inflammatory and antioxidant activities. Due to its ability to cross the blood–brain barrier, and/or its metabolites, it has been demonstrated that rutin is able to alter both cognitive and behavioral symptoms of neurodegenerative diseases [8]. Our previous studies have found that both flavonoids, quercetin and rutin, affect various signaling pathways and molecular networks associated with the modulation of proteasome functions in neuroblastoma cells [9]. In addition, it has been demonstrated that BACE1 expression and APP processing are regulated by the ubiquitin–proteasome pathway [10] and that supplementation with reduced glutathione (GSH) protected neurons from proteasome inhibition [11]. GSH depletion in the brain is a common finding in patients with neurodegenerative diseases, such as AD, and can cause neurodegeneration prior to disease onset [12]. Ubiquitination of BACE1 and blocking the ubiquitin–proteasome pathway inhibits BACE1 degradation and, consequently, leads to increased production of BACE1 enzymatic activity [10]. Based on these findings, and that dietary habits and supplementation can affect the cellular redox status, we aimed to explore the effects of a diet containing quercetin or rutin on intracellular redox homeostasis of the brain (GSH/GSSG), its correlation with BACE1 activity, and APP expression in mice models of AD (bearing human Swedish mutation Amyloid Precursor Protein APP transgene, APPswe). Finally, as there is convincing evidence of an effect of flavonoid supplementations in improving specific cognitive domains and/or MRI findings [13], we attempted to mimic, in animals, an intervention by delivering a healthy diet containing moderate amounts of a particular potential active ingredient (quercetin or rutin) as an effective strategy for preventing the expression of AD markers. The TgAPP mouse colony was developed in our laboratory from Tg2576 heterozygous males and wild-type females. Genotyping of mice was performed to detect transgenic individuals. Of all the mice tested, approximately 40% were found to be transgenic (TgAPP). The PCR products obtained were separated by electrophoresis in 1.5% agarose gels in 0.5X TBE (Tris-Borate-EDTA) buffer at 70 V (constant voltage) and then imaged by staining with GelRed (Millipore). The amplification profile for both transgenic and WT mice is shown in Figure 1. In order to evaluate intracellular redox homeostasis in neurons in TgAPP mice, GSH and GSSG levels were quantified, and the GSH/GSSG ratio was determined as a marker of cellular-reducing power in both males and females (Figure 2). In the assessment of the effect of the transgene on the glutathione system, a decline in the cellular-reducing power (GSH/GSSG) was observed in the TgAPP mice with respect to WT animals, in both males and females, and in both areas of the brain (Figure 2C3,H3), especially in hippocampus. In both WT and TgAPP mice, the GSH/GSSG ratio was significantly lower in males than in females (Figure 2C3,H3; p < 0.05). While in TgAPP females this decline is the result of lower GSH levels (Figure 2C1,H1), in TgAPP males it is mostly attributed to an increase in GSSG levels (Figure 2C2,H2). Changes in GSH and GSSG levels of TgAPP mice, respectively, upon quercetin or rutin treatment, are more prominent in males than in females. It seems that quercetin tends to augment GSH levels (Figure 2C1,H1; p < 0.05) and rutin to lower GSSG levels (Figure 2C2,H2; p < 0.05). Quercetin and rutin treatments, in both males and females, were able to reverse the fall in the ratio GSH/GSSG in hippocampus (Figure 2H3) where the recovery of redox power was significant versus the untreated TgAPP mice. In males, this index achieved similar values to those of WT mice in hippocampus (H3). In females, although this ratio is not raised up to that of the WT mice, treatment with quercetin and rutin enhanced it significantly in comparison to that of the TgAPP mice in their hippocampi (H3: quercetin, p < 0.001; rutin, p < 0.05). Levels of TBARs were determined as a marker of lipid peroxidation. Using calibration curves, the results were expressed as malondialdehyde (MDA) concentration (Figure 3). Following APP overexpression, a significant increase in MDA levels when compared to WT mice was observed in both the cortex (Figure 3C) and the hippocampus (Figure 3H), and in both males and females (p < 0.001). In TgAPP females, both quercetin and rutin treatments almost restored MDA levels to the same as those of WT mice (Figure 3C,H). In TgAPP males, likewise, both quercetin and rutin treatments reinstate MDA levels to the same as those of WT mice in the cortex (Figure 3C), and are decreased even further in the hippocampus (Figure 3H). In both WT and TgAPP mice, untreated and flavonoid diet-treated, MDA levels were sex-dependent (Figure 3C,H; p < 0.05), except for the quercetin-treated TgAPP mice in hippocampus. To address whether regulation of the enzymatic activity or the gene expression of the main antioxidant enzymes, or both, occurs upon a quercetin or rutin diet, determination of the enzymatic activity and mRNA levels was performed. Figure 4 shows the enzyme activities of SOD, CAT, GR, and GPx, determined in female and male mice, in the cerebral cortex (Figure 4a) and the hippocampus (Figure 4b). As a consequence of APP overexpression, only a significant decrease in CAT activity was observed in TgAPP mice compared to WT mice in both the cortex (Figure 4a(C2); p < 0.05) and the hippocampus (Figure 4b(H2); p < 0.05). Quercetin treatment did not produce any significant variation in enzyme activities in comparison to TgAPP mice, in males or females, in the brain areas studied. In contrast, animals treated with rutin experienced an increase in CAT activity in the cortex (Figure 4a(C2)) and in GR activity in the hippocampus (Figure 4b(H3)) in both males and females (p < 0.05). Moreover, rutin increased hippocampal CAT activity in TgAPP males (Figure 4b(H2)) and GPx activity in females (Figure 4b(H4)). Figure 5 shows the gene expression of the main antioxidant enzymes, SOD, CAT, GR, and GPx, determined in female and male mice, in the cerebral cortex (Figure 5a) and the hippocampus (Figure 5b). No differences in gene expression between TgAPP and WT mice are observed for the main antioxidant enzymes (Figure 5a,b). TgAPP males treated with rutin showed a significant increase in the expression of CAT in the hippocampus (Figure 5b(H2)). As for the hippocampal GPx, a similar pattern to CAT was observed, although the increase was not significant (Figure 5b(H4)). The results of BACE1 enzyme activity in both the cerebral cortex and the hippocampus in males and females are shown in Figure 6, expressed as percentages of activity with respect to untreated TgAPP mice. In Figure 6, BACE1 enzyme activity in TgAPP mice was found to increase by around 10% when compared to WT mice, in both the brain areas under investigation and in both sexes, and was found to be statistically significant (p < 0.05). The increase in activity observed in the transgenic mice was lowered by both quercetin and rutin treatments, both in the cortex and in the hippocampus. Nevertheless, it could still be noted that the rutin effect was slightly greater than that of quercetin in males. Once the activity of BACE1 was known, we decided to carry out the gene expression study of APP, the main characteristic of the transgenic animal model, and its main processing enzymes: BACE1 and ADAM10. Figure 7 shows the results obtained in female and male mice, both in the cortex and the hippocampus. In both sexes, a significant increase in APP expression greater than 85% was observed with respect to WT mice, demonstrating the overexpression of the gene both in the cerebral cortex (Figure 7C1; p < 0.05) and in the hippocampus (Figure 7H1; p < 0.05). Treatments with quercetin and rutin were able to reduce this expression by more than 45% (p < 0.05) for both male and female mice in both brain areas under investigation (Figure 7C1,H1), with the effects being more prominent in the hippocampus (Figure 7H1). As for the BACE1 protein expression, though BACE1 activity was altered, there were no significant differences between transgenic and non-transgenic mice regardless of sex and flavonoid treatment examined. Thus, we evaluated the ADAM10 expression involved in the non-amyloidogenic processing of APP. Although the changes in ADAM10 expression in TgAPP mice in comparison to WT mice were not statistically significant, a slight decrease was observed. Regarding the flavonoid treatments, rutin displayed an increasing trend in ADAM10 expression, both in males and females and in both areas of the brain (Figure 7C3,H3). TgAPP mice showed an increase in caspase-3 gene expression (Figure 8C1,H1), which was significant and greater than 30% compared to the hippocampi of WT mice (Figure 8H1; p < 0.05). As for caspase-6 expression, no differences were observed between transgenic and non-transgenic mice (Figure 8C2,H2). Quercetin and rutin treatments were able to lower caspase-3 mRNA levels in the hippocampus in a statistically significant manner (Figure 8H1; p < 0.05), with inhibition percentages of around 17% and 27% for female and male mice, respectively. In the cerebral cortex, significant differences were only observed in the treatment with rutin in males (Figure 8C1; p < 0.05). With regard to caspase-6, quercetin and rutin treatments did not exert any statistically significant effect in the cortex or in the hippocampus (Figure 8C2,H2), though in the latter the Caspase-6 in TgAPP males showed a tendency to decrease (Figure 8H2). The results obtained for gene expression of the inflammatory mediators IL-1β, TNF-α, and IFN-γ are shown in Figure 9. In the TgAPP, there was a significant increase in IL-1β gene expression of around 20% in the cortex and hippocampus in both sexes compared to WT mice (Figure 9C1,H1; p < 0.05). As regards TNF-α, although higher mRNA levels are shown in TgAPP, they are not statistically significant in relation to WT mice (Figure 9C2,H2). Regarding IFN-γ, there was an increase of around 30% in its expression in males, which was only statistically significant in the cortex (Figure 9C3; p < 0.05). Treatments with quercetin and rutin, both in females and males, were able to diminish IL-1β expression in the cerebral cortex and hippocampus in comparison to control TgAPP mice (Figure 9C1,H1; p < 0.05), obtaining similar values to those of WT mice, and particularly lower in the hippocampi of male mice (Figure 9H1; p < 0.05). The overall effect of both flavonoid treatments on IL-1β expression was not observed with TNF-α nor with INF-γ. Thus, TgAPP males, upon quercetin treatment, underwent a significant decrease in hippocampal TNF-α (Figure 9H2; p < 0.05) and in cortical IFN-γ expression (Figure 9C3; p < 0.05). No characteristic signs of neurodegeneration were observed at the age at which the transgenic TgAPP mice were tested, compared to WT mice, nor did treatments with quercetin and rutin show any change for 4 weeks in comparison to TgAPP (Figure S1, Supplementary data). No significant differences were found in receptor expression, comparing the values obtained for the control TgAPP mice with those obtained for the WT mice. There were also no notable effects on the expression of these ionotropic receptors in the presence of quercetin or rutin treatment (Table S5, Supplementary data). The purpose in our present study was to assess the impact of two flavonoids, quercetin and rutin, at the first stages of AD pathogenesis, regardless of their effect on neurodegeneration and/or cognitive function. The cortex and hippocampus were the areas of the brain under analysis, as they are the most affected brain structures in AD. It should be taken into account that quercetin and rutin were administered through a formulated diet containing either one of the two flavonoids, with the aim to mimic, in an AD animal model, the intake of a healthy human diet, containing an active ingredient. In particular, the transgene APPswe in the C57B6 mouse exerted a significant impact on GSH/GSSG ratio, MDA levels, antioxidant enzyme capacity, APP expression, BACE1 activity, and caspase-3 and IL-1β expression. Whilst APP mutations in humans generally result in typical AD, they are predominantly linked to solely amyloid pathology in APP transgenic mice and there is no noticeable neurodegeneration [14,15], as there were no characteristic signs observed in our transgenic mice TgAPP, contrary to the WT mice (Supplementary data, Figure S1). Counterstaining with 4′-6-diamidino-2-phenylindole (DAPI) of hippocampal neurons allowed us to observe the nuclear morphology, as this compound is a fluorescent dye for nucleic acids. We did not observe fragmented or lobular nuclei, typically apoptotic; nor did we observe any remarkable differences comparing the hippocampal histological sections of the control transgenic line TgAPP with respect to the WT sections; nor did we observe any differences between the quercetin and rutin treatments with respect to the control TgAPP mice. In the panel of AD biochemical features to be analyzed, we focused primarily on determining the GSH/GSSG ratio upon either one of the two flavonoid diets, since depletion of GSH levels represents one of the most important early biochemical markers in AD [16,17] and has been observed during its pathogenesis and disease progression. Measurement of brain GSH levels [18] and, more recently, blood GSH levels [19] have been promising as diagnostic markers for early stages of AD. Moreover, efforts have also been made to supplement endogenous GSH stores by themselves or their precursors [20,21,22]. In our study, a decline in the cellular reducing power (GSH/GSSG) was observed in the TgAPP mice with respect to WT animals, in both males and females, and in both areas of the brain. In cortex and hippocampus of both WT and TgAPP mice, the GSH/GSSG ratio was lower in male than in female. Quercetin and rutin diets significantly increased the GSH/GSSG ratio in comparison to untreated TgAPP mice, and this increase was more pronounced in the hippocampus. The changes in GSH and GSSG levels and GSH/GSSG ratio upon quercetin or rutin treatment of males, regarding increasing redox power, were more prominent than in females. The results from our determinations may reveal an important basis underlying sex-associated differences in Tg2576 mice in the susceptibility to the oxidative damage of macromolecules on one hand, since the glutathione system is a versatile reductant in multiple biological functions, and in the impact of preventive flavonoid diets in restoring its physiological status on the other hand. As we will see throughout this discussion, we have set the increase in the GSH/GSSG ratio as the main axis that might explain the set of effects observed in the TgAPP mice. It has recently been proposed that the GSH/GSSG ratio, rather than simply functioning as a redox buffer, would instead operate as a main regulatory mechanism, allowing proteins to attain their native conformation and functionality by tightly controlling the thiol-disulphide balance of the cellular proteome. In short, the glutathione system arises as essential to preserve a healthy proteome, showing that disruption of glutathione redox homeostasis (i.e., genetically or pharmacologically) increases protein aggregation due to disturbances in the efficacy of autophagy [23]. Therefore, strategies aimed at maintaining glutathione redox homeostasis may have a therapeutic potential in diseases associated with protein aggregation, such as AD. Closely related to the preservation of the proteome is the ubiquitin–proteasome degradation machinery, which is involved in the pathogenesis of AD. The proteasome selectively degrades multiple substrates that are crucial in maintaining neuronal homeostasis, including the catabolism of oxidized and aggregated proteins. BACE1 undergoes ubiquitination, and it has been demonstrated that blocking the ubiquitin–proteasome pathway will inhibit BACE1 degradation and consequently lead to increased production of BACE1 enzymatic activity, more β-cleavage product C99, and increases in both Aβ1-40 and Aβ1-42 in neuronal and non-neuronal cells [10]. Our previous studies have found that both flavonoids, quercetin and rutin, affect various signaling pathways and molecular networks associated with modulation of proteasome function in neuroblastoma cells [9]. In addition, it has been demonstrated that neurons supplemented with reduced glutathione (GSH) recovered the proteasome activity and reduced aggregate formation [11], since the proteasome function is redox status-regulated [24]. Therefore, the increase in the GSH/GSSG ratio experienced by the animals upon having a quercetin or rutin diet is consistent with the modulation of proteasome by quercetin and rutin, demonstrated ex vivo previously. As previously mentioned, redox imbalance leads to highly oxidatively-modified proteins that tend to accumulate and create aggregates resulting in proteasome impairment [25]. Thus, given the crucial role of oxidative stress in the pathogenesis of AD, biomarkers of oxidative stress, including lipid peroxidation (MDA levels) and antioxidant enzymes, were assessed in the cortex and hippocampus in the TgAPP and WT mice. SOD, CAT, GR, and GPx are the most important antioxidant enzymes that act against oxygen free radicals and regulate the metabolism of free radicals in the body and play a role in the free radical scavenging system, protecting the cells in the body from lipid peroxidation. In our study, as a consequence of APP overexpression, a generalized decrease in antioxidant enzyme activities was observed in TgAPP mice compared to WT mice, being statistically significant for CAT. Consistent with reduced GSH levels, lipid peroxidation was significantly increased in the TgAPP mice. While the source of oxidative stress in human AD is highly complex and multifactorial, the amyloid pathology developed in mice seems to be sufficient to initiate the pathological process leading to increased oxidative stress in the brain [26]. Animals treated with rutin experienced an increase in CAT activity in the cortex and in GR activity in the hippocampus, in both males and females. Only animals treated with rutin experienced changes in gene expression of CAT and GR in the cortex and the hippocampus in both males and females, and GPx in the hippocampi of female mice. In this context, several natural compounds have been shown to affect the crosstalk between the proteasome and redox regulation. More precisely, quercetin is a known Nrf2 activator [27] which exhibits antioxidant properties through the stimulation of proteasome function, promoting increased oxidative stress resistance and conferring enhanced cell longevity [28]. Tissue-specific expression of BACE1 is critical for normal APP processing, and its dysregulation expression may play a role in AD pathogenesis. BACE1 is predominantly expressed in hippocampal neurons, the cortex, and the cerebellar granular layer [10]. It should be noted that earlier studies have shown that Swedish mutant APP transgenic mice had significantly increased brain levels of Aβ at a steady state [29], suggesting that BACE1 plays an essential role in the amyloidogenic pathway in AD pathogenesis and is a good therapeutic target for AD treatment. In our study, we observed a significant reduction of BACE1 activity upon quercetin and rutin treatments, which might contribute to the decrease of Aβ deposition in mice. We argue that more than solely operating as BACE1 inhibitors of the enzyme, quercetin and rutin might exert a reduction in BACE1 activity related to an increase in the ratio GSH/GSSG, based on the hypothesis of an enhancing recovery of proteasome activity. In this sense, it is known that targeting of BACE1 inhibitors to the β-cleavage site of APPswe (Swedish mutation) occurs before it reaches the plasma membrane, whereas APPwt (Wild-type) is processed in an early endosome originating at the cell surface. Therefore, BACE1 that cleaves APPwt is sometimes bound to the BACE1 inhibitor on the cell surface prior to APP processing, however, the enzyme that processes APPswe is not [30]. It is for this reason that the aberrant localization of APPswe processing might significantly lower the potency of quercetin and rutin as BACE1 inhibitors. Thus, we are more inclined to support that the BACE activity’s decreasing in this in vivo model is not so much due to the inhibition of the enzyme but to the increase in the GSH/GSSG ratio. In any case, reduced BACE1 activity could be interpreted as a putative attempt to reduce β-amyloid production in the TgAPP mice. As for the most remarkable effect of quercetin and rutin in the hippocampus on BACE1 activity attenuation, it is worth noting that the cortex has a significantly higher neuron density than the hippocampus [31], and a selective impairment of the proteasome in AD pathological phenotype makes the cortex more vulnerable and affected than the hippocampus [32]. After determining the effect of the treatments on BACE1 enzyme activity, we were interested in evaluating its expression. Curiously, no significant differences in BACE1 expression were found between TgAPP mice compared to WT mice and no noticeable changes were observed with quercetin or rutin treatment. Therefore, it seems that the increase in BACE1 enzyme activity is not associated with an increase in expression. In this context, it is remarkable that Apelt et al. [14] found an increase in cortical BACE1 activity in Tg2576 mice between ages of 9 and 13 months while the expression level of BACE1 protein and mRNA did not change with age. Furthermore, evidence has been found supporting that fibrillar amyloid Aβ1–42., rather than soluble amyloid Aβ1–42, is able to upregulate BACE1 protein expression, and thus small modifications in the ratio of amyloid isoforms may modulate amyloid aggregate conformations and cell damage [33]. Thus, the absence of change in BACE1 expression upon an increase of its activity that we found may account for the prevalence of soluble amyloid Aβ1–42 over the fibrillar amyloid Aβ1–42 isoform in our mouse model TgAPP. Following the determination of gene expression of the enzymes involved in APP processing, we evaluated the effect of quercetin and rutin on the enzyme α-secretase involved in the non-amyloidogenic processing of APP. We focused on ADAM10 because it is the physiologically most important constitutive isoform of α-secretase. ADAM10 counteracts the generation of neurotoxic oligomeric Aβ plaques via cleaving APP within the Aβ domain to produce sAPPα and C-terminal fragment (α-CTF) [34,35]. Although the changes in ADAM10 expression found in our study were not statistically significant, a slight decrease in ADAM10 expression was observed in TgAPP mice relative to WT mice. Predominantly, rutin treatment showed a tendency to increase ADAM10 gene expression in both brain areas under study. Postina et al. [36] showed that the up-regulation of wild-type ADAM10 in the hippocampus of an AD mouse model mediated sAPPα secretion, leading to inhibition of Aβ plaques generation. The effect of quercetin has been studied in an aluminum chloride-induced AD rat model showing a significant enhancement of the α-secretase (ADAM10 and ADAM17) in the hippocampus compared to untreated ones. This indicates that quercetin possesses the potential to increase the non-amyloidogenic pathway through the activation of α-secretase genes [37]. Preclinical data reinforce the hypothesis that enhancing brain sAPPα levels is a potential strategy to improve AD-related symptoms and attenuate synaptic deficits. ADAM10 and BACE1 compete for the APPβ cleavage, therefore potentiating ADAM10 activity might inhibit the neurotoxic amyloid generation. Moreover, sAPPα can prevent the activation of the stress JNK-signaling pathway, leading to activation of NF-κB-induced phosphorylation activity, which leads to proteasome degradation [38]. Therefore, the formation and the accumulation of disease-related protein aggregates are significantly reduced, and the cellular proteasome activity is enhanced, thereby providing evidence for a function of sAPPα in the regulation of proteostasis [39]. Furthermore, it has been demonstrated that sAPPα specifically upregulates glutamate AMPA receptor synthesis and its trafficking [40]. In our study, we explored whether the slight increase of ADAM10 expression upon rutin treatment exerts some influence in glutamatergic synaptic transmission. As shown in the Supplementary data section, no significant effects on the expression of these ionotropic receptor were observed upon quercetin and rutin diets, perhaps due to a weak increase in ADAM10 expression, which is not sufficient for the upregulation of the AMPA receptor (Supplementary data, Figure S2 and Table S5). It should be taken into consideration that in vitro studies have shown a wide variety of ADAM10 substrates [41], and therefore, undesirable effects obtained by non-specific ADAM10-targeting might be found in cancer proliferation, cell adhesion, promotion of T cell/NK-cell precursor and inflammation, etc. [42]. To circumvent this constraint, our study suggests a strategy aimed at promoting the release of sAPPα in a more physiological manner. This approach might be based on a long-term intake of an active ingredient (quercetin or rutin), which is consumed through a healthy human diet. However, further studies are needed to find out whether the increase in ADAM10 is flavonoid dose-dependent and whether the potential beneficial effects outweigh putative side effects. As for the expression of APPswe, although the insertion of the human APP transgene in the mouse genome guarantees that APPswe is overexpressed from birth, it has been reported that APP mRNA and protein hippocampal levels show significant fluctuations during the animal development, being maximal when mice are asymptomatic (1-month-old) and decreasing when full symptomatology occurs [43]. Notwithstanding this issue, APP expression both in the cortex and the hippocampus was significantly higher compared to that of WT mice in our study. Further treatment with quercetin or rutin was able to significantly reduce such expression for both male and female mice, in both areas of the brain. These findings are in line with those reported by Augustin et al. [44] who studied a standardised extract of Ginkgo biloba (Egb761), rich in flavonols such as quercetin, in 4-month-old female TgAPP mice, finding decreased APP mRNA and protein levels. Taking into consideration that upregulation of APP translational in Tg2576 mice occurs in the prodromal and early symptomatic stages [45], it is likely that a restoration of APP translation by quercetin or rutin might have taken place in our TgAPP mice and, likely, in an early symptomatic stage, resulting in reduction of cortical and hippocampal levels of APP, BACE1 activity, and caspase-3 activation. Furthermore, it has been reported elsewhere that in Tg2576 mice (in the absence of neuronal loss) there is an increase in caspase-3 activation in the hippocampus [46], as found in our study, at the onset of memory impairment, together with a reduction in dendritic spines prior to the deposition of extracellular amyloid [46]. There is evidence in support of non-apoptotic roles for caspases in the nervous system without neuronal death [47], and caspase-3 activity has been localized to dendritic spines where it may elevate calcineurin levels. In turn, the dephosphorylation of GluR1 subunit of AMPA-like receptors, triggered by calcineurin is thought to result in postsynaptic dysfunction. Our values of caspase-3 expression, as a consequence of transgenesis, are in agreement with those obtained by other researchers who reported an increase in caspase-3 expression at the level of dendritic spines in the hippocampus of TgAPP mice [48]. Since APP contains three distinct cleavage sites for caspase-3 in its amino acid sequence, two of which are located at the level of the extracellular domain and one in the intracellular C-terminal portion of the APP tail [49], hydrolysis of APP by caspase-3 may alter the proteolytic processing of APP in favor of the amyloidogenic pathway [50], leading to the release of a cytotoxic C-terminal-derived peptide of 31 amino acids in length (C31), for example [51]. This suggests that, since caspase-3 can mediate the amplification of toxic fragment release from APP, lowering caspase-3 expression by quercetin or rutin may allow for the clearance of aggregated protein. In addition, as mentioned earlier, we have explored the influence of both the increase and decrease of caspase-3 expression in glutamatergic synaptic transmission, based on the ability of calcineurin-activated caspase-3 to dephosphorylate the GluR1 subunit of AMPA receptors at the postsynaptic level. These molecular modifications alter glutamatergic synaptic transmission and neuronal plasticity at the level of dendritic spines in the hippocampus [48]. Theoretically, pharmacological inhibition of caspase-3 activity in TgAPP mice might save the AD-like phenotypes from a mechanism that drives synaptic failure. However, despite the augmentation in caspase-3 expression in our TgAPP mouse, we found no significant differences in AMPA receptor expression compared to that in WT mice, as mentioned earlier. It might be that the changes in caspase-3 expression are not prominent enough to produce significant modifications in AMPA receptor expression (Supplementary data, Figure S2 and Table S5). As for the values of caspase-6 expression, no significant differences were found between TgAPP and WT mice. Activation of caspase-6 has been identified as an important mediator of neuronal stress that cleaves important cytoskeletal proteins (Tau and α-tubulin), thus disrupting the ubiquitin–proteasome degradation of misfolded proteins, and a number of actin-regulating post-synaptic density proteins [52]. The unchanged expression of caspase-6 in our study agrees with the absence of characteristic signs of neurodegeneration at the age at which these transgenic mice were evaluated, compared with the WT mice (Supplementary data, Figure S1). A marked increase in neuroinflammatory mediators has been observed in AD patients, mainly around senile plaques [53,54,55]. Astrocytes are the main supplier of GSH to microglia and neurons. During chronic inflammation and oxidative stress, astrocytes release toxic inflammatory mediators and free radicals, accelerating activation of microglia and neurodegeneration [56]. It is worth noting that decreased intracellular glutathione is related to the activation of the inflammatory pathways, p38 MAP-kinase, Jun-N-terminal kinase (JNK), NF-κB, in human microglia and astrocytes [57]. In this regard, we decided to quantify the levels of IL-1β, IFN-γ, and TNF-α in our animal model and determine the effect of quercetin and rutin on them. As is known, inflammation promotes defective processing of Aβ peptide and APP, promoting Aβ peptide aggregation and in turn modifying Aβ reactivity [58]. Thus, in our study, we observed that TgAPP mice had increased mRNA levels of the pro-inflammatory mediators IL-1β, TNF-α and IFN-γ, compared to WT mice, showing that overexpression of APPswe might induce neuro-inflammatory cascades triggering a series of molecular pathways in glia and neurons, which would activate the inflammatory response. Quercetin and rutin were able to attenuate IL-1β gene expression in both males and females and in the brain areas studied. Several pieces of evidence support the anti-inflammatory effect exerted by quercetin at the CNS level, as it may inhibit the activation of transcription factors such as the nuclear factor-kappa B (NF-κB) [59], involved in the induction of iNOS, and therefore, decrease the release of mediators such as IL-1β, TNF-α and IFN-γ [60]. Regarding the impact of GSH on the inflammatory response, it should be noted that GSH is involved in the maintenance of optimal cytokine levels in such a way that the expression of pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) are increased due to GSH depletion, whereas the expression of anti-inflammatory cytokines (i.e., IL-10) remained unaltered. This GSH homeostasis alteration happens due to upregulation in NF-κB and JNK signaling pathway which could be the feasible apoptotic pathway towards neuronal cell death [61]. In our study, down-regulation of NF-κB by quercetin and rutin might be a plausible mechanism to recover the GSH/GSSG homeostasis and therefore the cause of the balance between pro-inflammatory and anti-inflammatory cytokines. Lastly, since BACE1 promotor has an NF-κB binding site, inflammation-induced activation of NF-κB facilitates the upregulation of BACE1 expression, and subsequently increases Aβ production [62]. Thus, if down-regulation of NF-κB occurs upon quercetin and rutin diets, BACE1 activity would decrease as a result of the release regulation of pro-inflammatory and not anti-inflammatory cytokines. A transgenic mouse (Tg2576, B6;SJL-Tg(APPswe)2576 Kha) that expresses the Swedish double mutation of human amyloid precursor protein (hAPP) was used as the animal model of experimental AD [14]. The mouse is a knock-in heterozygote line which expresses the human AβPP695 isoform with the double Swedish mutation (K670N/M671L; Lys670→Asn and Met671→Leu) under the control of the hamster prion protein promoter [63]. As a result, this mouse exhibits levels of human amyloid-β precursor protein (Aβ PP), six times greater than that of a mouse’s Aβ PP levels. In addition, this mouse shows higher levels of Aβ40 and Aβ42. Aβ deposits begin at 9 months of age [63]. Within the Tg2576 hippocampus and cortex, APPswe transgene expression is primarily neuronal [64]. As a negative control, wild-type (WT) mice from the same colony [65,66] were used. The Tg2576 (B6;SJL-Tg(APPswe)2576 Kha) mouse colony was developed in our laboratory from Tg2576 heterozygous males and wild-type females. The transgenic parents were donated by Dr. Diana Frechilla from the Neuroscience Division at the Centre for Applied Medical Research at the University of Navarra (Pamplona, Spain) [67]. Animals were housed in individual ventilated cages and kept at 22–24 °C on a 12-h light/dark cycle in 50–60% humidity. Animal protocols were approved by the Institutional Animal Care and Use Committee (IACUC) at the Complutense University of Madrid and were in full accordance with the European Directive 2010/63/on the protection of animals used for scientific purposes and Spanish legislation on Animal Welfare (Royal Decree 53/2013, 1 February 2013). Transgenicity was determined within 30 days of birth by tail biopsy. Genotyping analyses of animals were carried out by PCR. Considering that Tg2576 (TgAPP) is a heterozygous line, the insertion gene (PrP, from prion protein) was used as a positive reaction control. Genomic DNA was extracted from mouse tails digested with proteinase K (0.1 μg/μL) in NID buffer (50 mM KCl, 50 mM Tris-HCl pH 8.3, 50 mM MgCl2, 0.05% gelatin, 0.45% NP-40 and 0.4% Tween 20) at 56 °C for 3 h and shaken. DNA fragments were precipitated with isopropanol and washed with 70% ethanol. DNA precipitates were dissolved in 30 μL of TE buffer (10 mM Tris-1 mM EDTA). The purity and concentration of DNA was determined at 260 and 280 nm. The PrP and APP genes were amplified by PCR. Sequences of primers used to screen the transgenic mice were as follows: PrP forward: CCTCTTTGTGACTATGTGGACTGATGTCGG; PrP reverse: GTGGATACCCCCTCCCCCAGCCTAGACC; APP reverse: CCAGATCTCTGAAGTGAAGATGGATG. The steps of the PCR reaction were as follows: denaturation at 94 °C for 90 s, 39 cycles at 60 °C for 60 s and 72 °C for 90 s, then final extension at 72 °C for 7 min. In all cases, negative controls (without DNA mold) and positive controls of the APP gene were considered. The PCR products obtained were separated by electrophoresis in 1.5% agarose gels in 0.5X TBE (Tris-Borate-EDTA, Merck KGaA, Darmstadt, Germany) buffer at 70 V (constant voltage) and then imaged by staining with GelRed (Millipore). TgAPP mice and wild-type littermates, both aged 6–7 weeks with an initial body weight of 16.2 ± 0.8 g, were randomized into the following four groups (n = 8/group): (a) Untreated TgAPP; (b) Quercetin-treated TgAPP; (c) Rutin-treated TgAPP; and (d) Untreated wild-type. Since both male and female mice were studied, two sets of groups were established. At the age of 45 weeks, the mice started to be treated with quercetin or rutin for 4 weeks. Quercetin (3,3′,4′,5,7-pentahydroxyflavone) and rutin hydrate (quercetin-3-O-rutinoside hydrate) were ≥95% pure and purchased from Sigma–Aldrich. Each one of the flavonoids was incorporated into a standard diet (Harlan Ibérica, Barcelona, Spain) at a concentration of 200 ppm, corresponding to an intake of 30 mg flavonoid/kg body weight/day. The untreated mice received exclusively the un-supplemented standard diet. Diets and water were provided for ad libitum intake. At the end of treatment, mice were fasted overnight, they were euthanized by means of cervical dislocation, and the entire brain was quickly removed. The brain was rinsed in saline at 4 °C and the arachnoid membrane was carefully removed. Then, the hippocampus and cortex were isolated. Samples were immediately stored at −80 °C until further use. The entire brains of some animals were used for obtaining histological sections, for which, once euthanized by means of cervical dislocation, brains were frozen by immersion in isopentane at −80 °C. Immediately afterwards, coronal sections of the brain (30 μm of thickness) were made from the olfactory bulb to the cerebellum, 120 μm apart in a cryostat (Leica CM1850, Nussloch, Germany). The whole procedure was performed at −20 °C. Histological sections were collected on slides and kept at −80 °C until analysis (See Supplementary Methods). For glutathione tests, cerebral cortex and hippocampus samples were homogenized in a redox-quenching buffer-5% Trichloride acetic acid (RQB-5% TCA) (previously bubbled with N2 for 15 min on ice) at a concentration of 25 mg/mL (w/v). Samples were resuspended by sonication for 10 s, then centrifuged at 12,000× g for 10 min at 4 °C, and supernatants were collected. Then, in the supernatant obtained, spectrofluorometric methods were adopted to determine GSH and GSSG levels using the o-phthalaldehyde method, described by Senft et al. [68]. GSH and GSSG values were corrected for spontaneous reaction in the absence of biological sample. In both cases, supernatants were incubated for 30 min at room temperature and afterwards fluorescence was measured using a FLUOSTAR microplate reader (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany), with the excitation filter set at 360 nm (bandwidth 5 nm) and the emission filter set at 460 nm (bandwidth 5 nm). The concentration of GSH and GSSG in each sample was interpolated from known GSH standards. Concentrations of both GSH and GSSG were expressed as nmol GSH/mg protein, which allowed for the calculation of the glutathione redox ratio GSH/GSSG. The remaining pellets were vortexed until completely dissolved in 240 μL of 0.1 M NaOH to measure protein concentration by the bicinchoninic acid (BCA) method, using bovine serum albumin as a standard. The content of TBARs was used as an index of lipoperoxidation. In brain tissue, 50 mM phosphate buffer (pH 7.4) was added to a concentration of 25 mg/mL (w/v) and the suspension was homogenized by sonication for 10 s. To 30 μL of the homogenate, 250 μL of 1% phosphoric acid and 75 μL of 0.6% thiobarbituric acid (TBA) were added. The reagent mixture was incubated at 100 °C in a water bath for 45 min, after which it was cooled in an ice bath and then centrifuged at 3000× g for 10 min at 4 °C. A volume of 150 μL of supernatant was taken from each sample. Fluorescence was measured using a FLUOSTAR microplate reader (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany) with the excitation filter set at 485 nm (bandwidth 5 nm) and the emission filter set at 530 nm (bandwidth 5 nm). A calibration curve was prepared using malondialdehyde (MDA) as a standard. The results were expressed in pmol MDA/mg protein. For the determination of enzyme activity in brain tissue, a lysis buffer containing 50 mM phosphate buffer (pH 7.4) and antiproteases (1 mM EDTA, 1 mM PMSF, 1 g/mL pepstatin and 1 g/mL leupeptin) was added to a concentration of 50 mg/mL (w/v). Then, suspension was sonicated for 30 s in an ice bath, and the homogenate was centrifuged at 10,000× g for 15 min at 4 °C. Supernatants were collected for the determination of the enzymatic activity of the antioxidant enzymes. Superoxide dismutase (SOD) activity was measured by following the inhibition of pyrogallol autoxidation at 420 nm [69]. One unit of enzyme was defined as the amount of enzyme required to inhibit the rate of pyrogallol autoxidation by 50%. The SOD enzymatic activity was expressed as international units (IU)/mg protein. Catalase (CAT) activity was measured in Triton-X-100 (1%, v/v)-treated supernatants by following hydrogen peroxide (H2O2) disappearance at 240 nm [70], and enzyme activity was reported as substrate (μmol H2O2) transformed/min ∙ mg protein. Total glutathione peroxidase (GPx) was determined following NADPH oxidation at 340 nm in the presence of excess GR, GSH, and cumene hydroperoxide [71]. GPx activity was expressed as substrate (nmol NADPH) transformed/min mg protein. Glutathione reductase (GR) activity was analyzed following NADPH oxidation at 340 nm in the presence of GSSG [72] and expressed as substrate (nmol NADPH) transformed/min ∙ mg protein. GR and both GPx activities were corrected for spontaneous reaction in the absence of biological samples (in the absence of enzyme). The ΒACE1 test protocol involves the use of a secretase-specific substrate (peptide) which is conjugated to two reporter molecules, namely EDANS and DABCYL, which results in the release of a fluorescent signal [73,74]. The BACE1 activity was measured both in the cortex and hippocampus lysates. The reaction was carried out at 37 °C for 1 h using 10 μM substrate in 50 mM sodium acetate buffer (pH 4.5). Fluorescence intensity measurements were done using a FLUOSTAR microplate reader (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany) with the excitation filter set at 360 nm (bandwidth 5 nm) and the emission filter set at 530 nm (bandwidth 5 nm). The level of secretase enzymatic activity is proportional to the fluorometric reaction, and the data are expressed as x-fold increase in fluorescence over that of background controls (reactions in the absence of substrate or tissue). The BACE1 activity was normalized with protein concentration. The mice’s BACE1 activity, quercetin or rutin-treated, was expressed as the percentage of activity of that of TgAPP control mice. We analyzed the different areas of the brain, namely the cortex and hippocampus, stored at −80 °C. To a known amount of brain tissue, Triomol® lysis buffer was added at a ratio of 1:10 (w/v). Samples were homogenized for 30 s using a Cordless motor (Pellet pestle, Sigma-Aldrich), and incubated for 5 min at 25 °C to allow for complete dissociation of nucleoprotein complexes. Then, 0.2 mL of chloroform was added for each mL of Triomol® lysis buffer used. The tubes were shaken vigorously for 15 s and incubated at 25 °C for 3 min. Then, they were centrifuged at 11,000× g for 15 min at 4 °C. After centrifugation, three phases were obtained, with RNA in the upper phase. To isolate the RNA, the upper phase was transferred to another tube and precipitated by adding 0.5 mL isopropanol. After thorough mixing of isopropanol and aqueous solution by inversion, the mixture was incubated at room temperature for 10 min to promote precipitation, and centrifuged at 12,000× g for 10 min at 4 °C. The supernatants were removed, and the pellets were washed with 75% ethanol and centrifuged at 7500× g for 5 min at 4 °C. The pellets were dried at room temperature and dissolved in 50 μL of DEPC-treated water. To remove traces of DNA, 2.5 μL of DNase (RNase-free) was added and incubated at 37 °C for 30 min. Finally, samples were incubated at 64 °C for 5 min to inactivate the DNase. Subsequently, the concentrations of RNA were measured in a UV-VIS spectrophotometer (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany) at 260 nm and the purity was assessed considering the absorbance ratio at 260 and 280 nm (A260/A280). The determination of RNA integrity and purity was performed by electrophoresis in a 1% agarose gel stained with GelRed and visualized under UV light, where, if the RNA was intact, two upper bands corresponding to ribosomal RNA (28S and 18S) and two lower bands corresponding to transfer RNA (tRNA) and 5S ribosomal RNA had to be observed. cDNA is much more stable than RNA and therefore allows for more convenient and safer sample handling. The cDNA was synthesized from mRNA by retrotranscription using the First Strand cDNA Synthesis Kit for RT-qPCR (Fermentas Life Sciences). In order to carry out the retrotranscription for cDNA synthesis to 2 μg of RNA, 11 μL of DEPC-treated water and 1 μL of 10X Random primers were added. Then, the mixture was incubated at 65 °C for 10 min to denature the RNA. After this time, the tubes were immediately brought to 4 °C for 5 min to avoid renaturation of the RNA. The reagent mix for cDNA synthesis is shown in Table S1 (Supplementary data). Eight μL of the reaction mixture was added to each sample. The entire volume was brought to the bottom of the tubes and incubated at 42 °C for 60 min. Finally, the reaction was stopped by inactivating the reverse transcriptase by heating it at 70 °C for 10 min. The main feature of real-time PCR is that the analysis of the products takes place during the amplification process by determining the fluorescence. In this way, the amplification and detection processes occur simultaneously in the same tube or vial without the need for any further action. For real-time PCR, thermal cyclers are used, which can amplify and detect fluorescence simultaneously. We utilized the LightCycler real-time thermal cycler (Roche Diagnostics, Mannheim, Germany). Table S2 (Supplementary data) lists the reagents required for real-time PCR, using sequence-specific primers and DNA-binding dye (SYBR Green I, Roche Molecular Systems, Inc., Rotkreuz, Switzerland) as a detection system. For the design of the primers for the different quantified markers, the Primer3Plus bioinformatics program (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi, accessed on 21 January 2023) was used, for which we took the cDNA sequences of the genes of interest from the Medline open-access database (http://www.ncbi.nlm.nih.gov/entrez, accessed on 21 January 2023). The primers were supplied by Merck (Sigma-Aldrich). The hybridization temperature and the sequence of the different primers used are shown in Table S3 (Supplementary data). The reaction conditions for the amplification of the genes of interest are shown in Table S4 (Supplementary data). Finally, the samples were subjected to a melting program: 95 °C for 15 s, 65 °C for 30 s, and up to 98 °C at a rate of 0.1 °C/s with continuous fluorescence recording. For the quantification of cDNA levels, the cycle threshold (Ct) comparison method [75] was used, using GADPH as a housekeeper. The amplification of the housekeeper was done in parallel with the analyzed gene. Ct values were calculated using the 4.0 software provided by LightCycler (Roche Diagnostics, Mannheim, Germany). The software allows distinguishing between fluorescence due to sample amplification and due to background. Melting curves were also recorded. Determination of the melting temperature of the amplified fragment allowed for characterization of the amplified product. The size of the bands was checked on a 1.5% agarose gel. The variation of the expression of the gene under study with the quercetin or rutin treatment was expressed as a function of the control TgAPP (mice without treatment) and normalizing this expression with the levels of GADPH. The Change Fold (2−ΔΔCt) represents the number of times that the gene of interest is modified under the particular treatment with respect to the control mice. All tests were performed at least in duplicate and in three different experiments. The results obtained are expressed as the mean ± standard error. One-way analysis of variance (ANOVA) was performed once the data were tested and demonstrated that it fits a normal distribution. The Newman–Keuls multiple comparison post-hoc test was run, examining mean differences between groups. Values of p < 0.05 were considered significant. SigmaPlot 11.0 software was used for statistical analyses. Dietary habits and supplementation can affect the cellular redox status. On this basis, we aimed to ameliorate the cellular redox homeostasis in an AD mouse model by a flavonoid diet containing quercetin or rutin in order to alleviate amyloid pathology, considering the interplay between cellular redox status and proteasome-dependent amyloid features in asymptomatic AD. Our datasets are relevant, since the flavonoid effects displayed in the TgAPP mouse model are consistent with those reported earlier in our in vitro and ex vivo models. In conclusion, our findings show that initiating a diet treatment at the asymptomatic stage or at the onset of AD-like symptoms might reinstate cellular redox status and APP physiological processing via concurrent regularization of APP expression and BACE1 activity. Although it is difficult to extrapolate our findings to the human condition, they may have broad implications for the human response to future therapeutics. Of the two flavonoids, rutin, with an overall more prominent in vivo effects, seems to be most suitable to be included in a day-to-day diet as an adjuvant therapy in AD, based on the augmentation on intracellular redox homeostasis of the brain.

PMC10003356

Martin Rumbo,Mihai Oltean

Intestinal Transplant Immunology and Intestinal Graft Rejection: From Basic Mechanisms to Potential Biomarkers

25-02-2023

intestinal transplantation,allorecognition,acute rejection,biomarkers,calprotectin,metabolomics,enterocytes,proteomics

Intestinal transplantation (ITx) remains a lifesaving option for patients suffering from irreversible intestinal failure and complications from total parenteral nutrition. Since its inception, it became obvious that intestinal grafts are highly immunogenic, due to their high lymphoid load, the abundance in epithelial cells and constant exposure to external antigens and microbiota. This combination of factors and several redundant effector pathways makes ITx immunobiology unique. To this complex immunologic situation, which leads to the highest rate of rejection among solid organs (>40%), there is added the lack of reliable non-invasive biomarkers, which would allow for frequent, convenient and reliable rejection surveillance. Numerous assays, of which several were previously used in inflammatory bowel disease, have been tested after ITx, but none have shown sufficient sensibility and/or specificity to be used alone for diagnosing acute rejection. Herein, we review and integrate the mechanistic aspects of graft rejection with the current knowledge of ITx immunobiology and summarize the quest for a noninvasive biomarker of rejection.

Intestinal Transplant Immunology and Intestinal Graft Rejection: From Basic Mechanisms to Potential Biomarkers Intestinal transplantation (ITx) remains a lifesaving option for patients suffering from irreversible intestinal failure and complications from total parenteral nutrition. Since its inception, it became obvious that intestinal grafts are highly immunogenic, due to their high lymphoid load, the abundance in epithelial cells and constant exposure to external antigens and microbiota. This combination of factors and several redundant effector pathways makes ITx immunobiology unique. To this complex immunologic situation, which leads to the highest rate of rejection among solid organs (>40%), there is added the lack of reliable non-invasive biomarkers, which would allow for frequent, convenient and reliable rejection surveillance. Numerous assays, of which several were previously used in inflammatory bowel disease, have been tested after ITx, but none have shown sufficient sensibility and/or specificity to be used alone for diagnosing acute rejection. Herein, we review and integrate the mechanistic aspects of graft rejection with the current knowledge of ITx immunobiology and summarize the quest for a noninvasive biomarker of rejection. Intestinal transplantation (ITx) remains a lifesaving option for patients suffering from irreversible intestinal failure and complications from total parenteral nutrition. Since the technique was established and became a clinical option in the late 1990s, it has been recognized that one of the outstanding features of this procedure was the strong allogenic response triggered by the graft, which has to be contained using more aggressive immunosuppressive regimes compared to other types of solid organ transplantations [1,2]. Considering the complexity of the tissue-resident immune cell populations along the gastrointestinal tract and the constant exposure to external antigens, including a diverse and wide microbiota, it was accepted that the intestinal graft is at the top of the list of high-immunogenic grafts. Pioneering work from K.A. Newell and coworkers in the end of the 1990s and early 2000s, elegantly performed in murine models, showed that acute cellular rejection is triggered by redundant effector pathways including CD4+ and CD8+ lymphocytes [3,4,5] and that blocking these effectors gives rise to chronic rejection, illustrating the redundancy of different immune-mediated effectors of rejection and the differences in costimulatory signals needed to trigger intestinal rejection by these populations [6,7,8,9]. In recent years, the use of immune activity surrogates such as the monitoring of DSA has been established in clinics and has allowed us to gain insight into the dynamics of alloresponse. Furthermore, we have progressed in our understanding of the immunology of the gastrointestinal tract and in aspects of solid organ alloresponse. The aim of this review is to integrate the present knowledge on ITx immunobiology with mechanistic aspects of graft rejection and review how this knowledge is bringing about new candidate biomarkers that may contribute to better monitoring of the graft status. Traditionally, it has been considered that there are several possibilities to elicit an allogenic immune response that will contribute to graft rejection [10]. The so-called direct pathway involves the presentation of allogenic molecules by antigen-presenting cells from the donor, which implies the presentation in the context of donor MHC molecules to the lymphocytes of the recipient. This pathway is mainly responsible for acute cellular rejection by the activation of CD4+ and CD8+ lymphocytes and, due to the limited lifespan of donor-derived antigen-presenting cells (APC), may not sustain alloresponse for longer than several months after transplantation. Depending on the number of antigen-presenting cells present in the graft, this pathway may constitute a serious threat to the survival of the allograft. In the case of intestinal transplantation, there are different professional APC populations either in the lamina propria or in organized lymphoid structures that may contribute to this mechanism [11,12,13]. Strong induction of immunosuppression, especially using depleting agents, aims to minimize this response. In addition, another important mechanism of alloresponse is the so-called indirect pathway, which involves the presentation of donor-derived allogenic peptides by recipient antigen-presenting cells using the exogenous antigen-presenting pathway [14]. Because of its nature, this pathway may be operative throughout the whole lifespan of a graft, as long as donor allogenic molecules (particularly donor MHC proteins and other alloantigens) are expressed in the graft. This pathway can mainly activate CD4+ lymphocytes by the presentation of allogenic molecules in the context of MHCII using the extrinsic pathway of antigen presentation. CD4+ lymphocytes activated by this pathway can provide cytokine signals to B cells specific to allogenic molecules, which is one important mechanism that contributes to the generation of donor-specific antibodies (DSA) [15]. The use of immunosuppressive agents that limit T cell activation is intended to limit the activation of this pathway. Some years later, the semi-direct pathway was described [16,17,18], which implies the transference, mainly by extracellular vesicles, of functional donor-derived membrane-bound MHC molecules to recipient antigen-presenting cells, which afterward can present donor MHC molecules, potentially eliciting recipient CD8+ and CD4+ lymphocyte allogenic activation. This pathway can be operative indefinitely after transplantation and may be responsible for acute cellular rejection that may take place several years after transplantation, events that have been extensively documented in the ITx field [19,20,21]. Irrespective of the pathway that is eliciting the allogenic response, one feature that has been clearly established in experimental models of organ transplantation is the importance of the secondary lymphoid organs as sites of allorecognition and T cell activation. In the absence of secondary lymphoid organs in mouse models, the kinetics of alloresponse are much slower or absent, depending on the type of solid organ considered [22]. ITx has the particular feature of an important load of lymphoid structures in the graft, either the mesenteric lymph nodes included in the graft as part of the portal draining system or the multiple lymphoid structures present in the mucosa (Figure 1). There is important evidence that graft-organized lymphoid tissue is important for the development of rejection: in experimental models, it has been shown that recipient-derived lymphocytes are present in important amounts as early as 24 h after transplantation in mesenteric lymph nodes and Peyer patches of the graft [22] and that they expand and produce critical cytokines for acute rejection, such as interferon (IFN)-gamma, in the first days after transplantation. Furthermore, the absence of these structures in the graft completely abolishes the acute cellular rejection, indicating the importance of the direct pathway of recognition in this process. Additionally, in human ITx, it has also been shown a fast turnover (more than 50% of the population at days 3 to 5 post-transplant) of the recipient-derived lymphocytes emerging through the mesenteric lymph [23] and also the presence of recipient-derived lymphocytes in the Peyer’s patches and isolated lymphoid follicles of the graft in the first 2 weeks after transplantation [24]. In recent years, due to different technical refinements [24,25], it was possible to appreciate the diversity of lymphoid structures present in the human mucosa, reinforcing the idea of the singularity of ITx from an immunological point of view. Although it is still incomplete, the understanding of the functional differences between structures in all cases of B cell compartments is present [25], and it has been shown that human ILF [24] and Peyer’s patches [26] contain TFH able to deliver T-B cooperation and that these structures are not affected by immunosuppression [24], raising the possibility that these sites are also important for the activation and expansion of donor-specific B cells, giving rise to donor-specific antibodies (DSA). Recent evidence indicates the existence of a new activation pathway, the so-called inverted direct pathway, that is responsible for early de novo DSA formation. This pathway operates by the interaction of donor-derived CD4+ T lymphocytes with recipient B cells that may present in the context of recipient MHCII molecules and consequently act as direct alloactivators of donor T lymphocytes, operating in a way similar to the direct pathway with the particular feature that, in this case, donor vs. recipient cell roles are inverted [27]. From an immunological point of view, this is further evidence of the “two-ways allogenicity model” that we will describe below. In this case, the activation of donor-derived T cells is a feature of a graft vs. host response; however, the cytokines produced by the activated T cells contribute to the class switch and expansion of the host vs. graft B cell response (in this case, recipient B cells act as antigen-presenting cells of the recently described inverted direct pathway). Although this mechanism has been elegantly demonstrated in a mouse model and there are indications that it is acting on human solid organ transplantation, its relative importance still needs to be proven [28]. There is evidence that this could be an important source of DSA in clinical ITx since a correlation between the amount of passenger donor-derived T cells in the graft and the kinetics of the appearance of DSA in different types of transplants [27]. Furthermore, the presence of donor-derived B cells in the intestinal graft and intestinal graft-derived lymph has been described [23,29], indicating that this pathway could also be operating by the migration of recipient B cells into graft lymphoid structures and also by the emigration of donor-derived passenger T cells, as proposed by this recent study [27]. In the past few years, with the possibility of performing sequencing techniques that allow the identification of individual T cell clones and a clever combination of allostimulation experiments [30], pioneering work by Megan Sykes’ lab has shown that, upon solid organ transplantation, there is an expansion of effector T cells of donor origin (so-called graft versus host clones, GvH) concomitant with an expansion of effector T cells of recipient origin (host versus graft clones, HvG), in both cases triggered by the different alloactivation pathways described above. The magnitude of the GvH and HvG responses depends on the relative abundance of donor T cells in the graft [31,32,33]. Interestingly, the opposing activity of GvH and HvG responses may coexist under immunosuppressive regimes to a certain extent without consequences in the clinical aspect of the patient [31]. If one of these responses results in overexpansion, clinical rejection or graft versus host disease takes place. As expected, in the case of intestinal and multivisceral transplantation, the amount of T cells that are transferred with the graft makes the magnitude of the GvH response detectable, whereas it is less evident in other solid organ grafts [32]. In experimental rat models of multivisceral transplantation, this has also been evidenced by changing the lymphoid size of the graft upon inclusion of the spleen as part of the graft or removal of the recipient’s spleen [34]. The presence of lymphoid precursors in the intestinal graft has also been evidenced in a clinical setting by showing the repopulation of the recipient bone marrow with precursors of donor origin in the case of ITx [35,36], which is dependent on the initial expansion of GvH clones that, in part, due to their effector function, facilitate the population of the bone marrow niche by the donor-derived precursors. The recognition of the coexistence of these two opposite effector populations and their functional evolution may allow us to adjust immunosuppressive regimes or generate tolerogenic strategies based on improved knowledge of chimerism dynamics. Resident memory T cells (Trm) are a subset of memory cells phenotypically and transcriptionally different from circulating effector and central memory T cells, which are mainly characterized by their non-circulating behavior, remaining long term, particularly in barrier organs such as skin, gut, lungs and reproductive tract, with the subset numerically the largest T cell memory subset. In recent years, it has been clearly established that in addition to its role in infectious immunity, this subset can be particularly relevant in the process of graft rejection [37]. Interestingly, using a mouse model of chronic kidney rejection based on the recognition of a transgenic OVA peptide ubiquitously expressed in tissues and recognized by transgenic TCR CD8 T cells, it was recently shown that resident memory CD8 T cells are central players in this model of chronic CD8-driven rejection [38]. Although authors transferred naïve OVA-specific CD8 T cells as drivers of rejection, over time it was observed that these allogenic cells activate in the kidney graft and acquire the phenotype of Trm CD8 cells. In spite of persistent antigenic exposure, Trms maintain activation markers without showing an exhaustion phenotype and are responsible for graft loss in this model. It is remarkable that, in spite of being a “non-frontier” organ, the kidney graft developed a strong proliferation of Trms at 4 weeks post-transplant, which do not recirculate, as shown through elegant parabiosis experiments. In another seminal study, a new mouse model of subsequent skin grafts was used to study the role of Trm in graft rejection: initially using an immunocompetent MHC mismatched recipient, allowing the generation of alloreactive CD4+ and CD8+ Trm that established in the skin, with a very low frequency of recirculation [39]. These animals were used as skin donors to be transplanted into SCID or IL2 gR-/- animals that are not able to mount T cell responses. In this second transplanted animal, the only source of alloreactive cells is the alloreactive Trm included in the graft. By using this animal as a recipient for the next skin transplant, authors could show that alloreactive Trm is sufficient to cause skin rejection. In this case, either CD8+ or CD4+ Trm are generated, as both populations are redundant in causing skin rejection. Interestingly, they also showed that, upon activation, there is a proliferation of Trm that, under these circumstances, can be detected in the circulation and spleen, indicating that part of the activity generated in the graft could be reflected in changes in peripheral blood, even in the case of Trm, allowing the possibility of monitoring the process. Intriguingly, the authors also performed heart transplantation in these recipient animals, which showed that skin alloreactive Trm is also able to reject heterotopic heart grafts, showing the capacity of alloreactive Trm to reject solid organs. Authors have also transcriptionally and functionally characterized the profile of the alloreactive CD4+ Trm, which are mainly Th17-like cells in this model. In the field of clinical ITx, Kroemer et al. (2021) recently described Th17 cells as central players in keeping the progress of thymoglobulin-resistant graft rejection [40]. The characterization of these cells showed that they express a memory phenotype. Since the authors did not use antibody panels equivalent to those in previously mentioned studies [38,39], it is not possible to conclude exactly the role of Trm in this scenario, but this warrants future research on this topic. Recent work from Columbia University [31] showed that, in a clinical setting, there is a progressive replacement of intestinal graft donor lymphocytes by recipients, with higher turnover in the cases that develop clinical rejection, with remarkable expansion of specific HvG clones. Interestingly, this study indicated that these cell populations progressively acquire Trm phenotypes, reinforcing the concept that alloreactive Trms are mid- and long-term post-transplant central actors of the rejection process. The confirmation of this concept may have important implications since the capacity of different immunosuppressive drugs used for patient management have lower activity on memory cells compared with naïve cells. Furthermore, considering the above-mentioned two-way alloreactivity pathway, it is important to consider that the intestinal graft harbors an important population of resident memory T cells [41,42] that may also contribute to the different possibilities of immunological activation, such as graft vs. host activity and also the inverted direct allorecognition pathway already mentioned. The different contributions of these different pathways to the clinical condition are yet to be established but may contribute to bringing additional options for patient management. Although the main drivers of alloresponse have been characterized, as described above, there are several mechanisms that have been described on homeostatic/physiopathogenic circuits in the intestinal mucosa that have not been explored in the context of intestinal transplantation. MHC class II expression by intestinal epithelial cells (IECs) was described in the 1980s [43,44], and it has been shown that they may function as non-conventional APCs, interacting with T cells and shaping homeostatic circuits [45]. Their putative role as APCs in the different pathways of alloresponse has not been clearly established. It has been shown that IECs can secrete extracellular vesicles containing MHCII molecules capable of being acquired by mononuclear phagocytes: a circuit that participates in eliciting an adaptive response to microbial antigens [46]. These circuits can clearly participate in a semi-direct pathway of allogenic response in intestinal transplantation; however, their relevance in the rejection process has not been established yet. Furthermore, several unconventional lymphoid populations in the intestinal mucosa may participate in antigen-driven activation circuits [47]. Type 3 innate lymphocytes (ILC3) can also express MHCII and participate in antigen presentation to CD4+ conventional T cells [48], but rather than inducing T cell activation, they act as modulators of adaptive responses, inducing Tregs for commensal microbiota [49]. Deletion of MHCII in ILC3 induces dysregulation in CD+T cell responses that results in spontaneous intestinal inflammation [48]. Although ILC3 have been reported to have a protective role in intestinal rejection, possibly associated with their capacity to generate IL22 [50,51], their role as inducers of alloresponse has not been assessed. Still, in the same way, changes in the intraepithelial lymphoid compartment along intestinal transplantation follow-up have been described [52]; however, the contribution to alloresponse of several unconventional T cell populations, such as MAIT, CD8aa or gdT lymphocytes, is still not clearly established. As of today, there are no noninvasive biomarkers showing adequate sensitivity and specificity to stand alone as diagnostic assays for intestinal acute cellular rejection (ACR). However, a number of biomolecules have been suggested as potential rejection markers, with some of them, such as plasma citrulline or fecal calprotectin, which are in clinical use. These biomolecules show altered expression during ACR, either due to tissue injury, the accompanying immune response activation and/or bystander inflammation or the ensuing metabolic changes in the rejecting intestinal graft (Figure 2). Unfortunately, tissue injury and immune response activation/inflammation also occur during other circumstances following ITx, such as ischemia-reperfusion injury or infectious enteritis, and the few biomolecules that are in clinical use so far can only be regarded as screening tools or exclusionary markers. Below, we summarize the most significant findings and hypotheses explored so far according to three main pathophysiological mechanisms: direct graft injury secondary to the acute rejection process, local and systemic inflammation triggered by the alloimmune response and altered local metabolism following damage to the intestinal graft, explored via high throughput technologies. Many molecular events and subsequent cellular and molecular alterations are intertwined and dependent on the intensity and gravity of the immune response. Intestinal mucosa is the main target of the rejection process, and ultimately enterocyte loss ensues. Circulating levels of citrulline, a nonprotein amino acid produced mostly by enterocytes as the end product of glutamine metabolism, have been suggested as a measure of functional enterocyte mass. Citrulline is stable and relatively easy to analyze in plasma and dried blood spot samples [53]. In ITx recipients, serum citrulline levels have been reported to decrease during ACR and inversely correlate with its severity, prompting several investigators to suggest citrulline as a biomarker of acute rejection [54]. Unfortunately, a series of limitations related to the metabolism of citrulline, such as its variation related to body (and graft) size and renal function, have dampened the initial enthusiasm around it [55,56]. The individual variation generates a considerable overlap between plasma citrulline levels in patients with normal allograft histology and those with ACR. Additionally, the observation that citrulline concentrations in the early post-transplant period (up to three months) are decreased due to ischemia-reperfusion injury at a time when the incidence of ACR is potentially at its highest, further limits its usefulness. In spite of a rather satisfactory sensitivity (>80%), the specificity of low citrulline levels for rejection is modest (58%), and it cannot discern between rejection and other cases of citrulline decrease such as infectious enteritis [57]. Thus, the current belief is that citrulline levels reflect the extent of mucosal injury but do not seem to be a useful diagnostic marker for rejection or viral enteritis, as their values decline only when significant, widespread mucosal damage has occurred. Several other biomolecules involved in enterocyte metabolism have been explored in the setting of intestinal ACR. Rodent studies have indicated that the intestinal fatty-acid binding protein (I-FABP), present primarily in mature, villus enterocytes which are normally undetectable in the serum, increased during ACR (196 ± 24 ng/mL), and rejection treatment with cyclosporine consistently reversed rejection and decreased I-FABP in rats [58]. However, a small clinical study of nine patients did not find meaningful elevations of serum and/or urine I-FABP in patients with histologically proven rejection [59]. Reasons behind the discordant results may have been represented by the low-lipid diets given early after transplantation, which may limit the expression of I-FABP [60], or the fact that only one out of four rejection episodes was severe and involved I-FABP-rich villus enterocytes, whereas the other three rejection episodes were mild/moderate and limited to the crypts. The activity of histamine-degrading enzymes diamine oxidase and histamine N-methyltransferase (HNMT) was found to decrease in the mucosa of rejecting rat allografts and revealed a strong negative correlation with the histological rejection score, whereas isografts showed rather constant tissue enzyme activity up to eight days after ITx [61]. These two enzymes are relatively constant within each individual and bowel segment and reflect the functional integrity of the intestinal mucosa. Although serum and stool assays for the activity of these two mucosal enzymes are well established, no human studies have explored this hypothesis so far. Enterocyte apoptosis is a central mechanism of tissue injury during intestinal ACR as one of the key effector mechanisms of cytotoxic T lymphocytes (CTL). Its increased occurrence is ubiquitous in different species, and its magnitude correlates with the severity of rejection [62,63,64]. Indeed, quantitation of apoptotic activity in the allograft (crypt cells) is one of the features used for the pathologic grading of the severity of rejection of the transplanted small intestine [64,65]. One of the death-inducing mechanisms used by CTLs is the exocytosis of granules containing perforin (a pore-forming protein) and several types of granzymes (serine proteases). Upon contact between CTLs and enterocytes, perforin facilitates the entry of granzymes into the target cell, where the latter can directly cleave the proapoptotic protein BH3 interacting-domain death agonist (BID) to its active form, which will then translocate to the mitochondria and increase its permeability. In the cytoplasm, granzymes cleave several substrates and induce cell death through the activation of caspase-dependent and -independent pathways. Both granzyme B and perforin were identified as co-expressed in the mucosa of rejecting intestinal allografts, correlating significantly with the histological severity of ACR [66]. A larger follow-up study from the same group analyzing granzyme B and perforin using total RNA extracted from peripheral blood mononuclear cells confirmed their increase during acute rejection and identified a sensitivity and specificity for acute rejection of 80% and 87% for granzyme B GB and 70% and 87% for perforin, respectively [67]. However, similar increases were found during post-transplant lymphoproliferative disease and viral enteritis, thus greatly reducing the diagnostic value of these two biomolecules. In addition, the study identified a “physiologic” increase in both molecules during the first four weeks after ITx and a high susceptibility of both these tests to antirejection treatment (steroid pulse or Thymoglobuline), both circumstances making the interpretation of the tests difficult in the case of acute rejection. Increased serum levels of suppressor of tumorigenicity 2 (ST2), a regulatory decoy receptor of IL-33, have been observed during inflammatory bowel diseases [68]. In a small study of 18 pediatric intestinal transplant recipients with and without rejection or non-specific enteritis without rejection, ST2 levels were found to be significantly increased at the time of biopsy-proven rejection compared to rejection-free periods [69]. This increase appeared specific to rejection, as it differentiated rejection from non-specific enteritis. ROC analysis identified a cutoff of 3150 pg/mL and suggested a discriminative capacity for serum ST2 to distinguish rejection with a sensitivity of 62% and specificity of 72.2%. A recent murine study using proteomics revealed significant alterations in the tissue expression of ninety-four proteins in the intestinal grafts that developed moderate rejection, compared to non-rejecting isografts [70]. Interestingly, the analysis of the canonic pathways revealed multiple known alterations corresponding to several metabolic pathways during intestinal rejection, such as citrulline biosynthesis, serotonin, dopamine or arginine degradation. The analysis also evidenced previously unknown changes in the tissue expression of numerous structural proteins, enzymes and components of several cellular signaling pathways, which could be further explored up- or downstream in search of potential biomolecules or metabolites useful as rejection biomarkers. One such biomolecule could be chromogranin A, which was found to decrease in the rejecting intestines in the confirmatory analysis of the study. The initial inflammation in the early stages of allorecognition initiates multiple phenotypic changes in the graft. Earlier experimental studies have indicated numerous alterations, including progressive mucosal pro-inflammatory activation [71,72], heat stress response [73] or graft dysmotility [74], occurring during intestinal acute rejection. Although many of these changes have been indicated, mostly evidenced in rodent transplant models without the use of immunosuppression, their confirmation in a clinical setting is still incomplete, and results based on human biopsies are mandatory for any meaningful advancement in the search for biomarkers. Cytokines and their receptors play key roles in the activation and propagation of the alloimmune response through their chemotactic effects, inducing the expression of adhesion molecules, promoting the proliferation and differentiation of specific alloreactive T and B cell clones or having a direct cytotoxic effect on the allograft cells [75,76]. Several experimental studies [71,72,77,78,79,80] reported a significant and sustained increase in several cytokines and adhesion molecules in rejecting intestinal allografts. However, essentially all these studies focused on the intragraft expression of these molecules, and the information on this topic in body fluids remains surprisingly limited. In spite of the early enthusiasm around the potential of various cytokines to diagnose intestinal ACR, there seems to be a gap between the experimental and clinical data, and only a few clinical reports have been published and are based on a small number of analytes and patients [81,82,83,84]. These limited, early observations showed increased soluble adhesion molecules or cytokines in patients rejecting their intestinal allografts but generally failed to identify clear patterns, thresholds or roles for them. A more recent study performed on formalin-fixed, paraffin-embedded, human mucosal biopsies investigated the expression of 280 genes involved in immune response, inflammation and apoptosis and found 92 genes showing significantly different expression levels between rejecting and non-rejecting intestines [85]. These genes included several cytokines and chemokines, endothelial adhesion molecules (ICAM-1, E-selectin), numerous epitopes involved in allorecognition (likely reflecting the immune cells’ infiltration), as well as multiple receptors for bradykinins, leukotrienes or cytokines. As all the samples selected for this analysis had moderate or severe ACR, it is still unclear which changes are associated with the earlier stages of rejection, which may be used for diagnostic or early detection as part of a surveillance strategy. In addition, no graft samples presenting confounding pathology such as infectious enteritis were analyzed, leaving the specificity of these findings unclear. Another shortcoming of this study is the continuous need for graft biopsies, whereas a non-invasive biomarker would ideally be identified in the stool or in the blood. A reason for the paucity of clinical studies may be the perceived confounding effect of immunosuppression (tolerance induction regimens, maintenance immunosuppression) and its impact on the kinetics of various biomolecules [86,87], adding to all the other causes of heterogeneity encountered in a clinical setting. Indeed, a clinical study found that, whereas the expression of intragraft IFN-gamma, CXCL10, and CXCL11 was clearly increased during rejection, rejecting individuals receiving reduced immunosuppression showed a 13-fold increase in IFN-gamma expression and a 9-fold increase in CXCL10 expression, while patients with more intense immunosuppression revealed a significantly lower increase [88]. A small pilot study found an increase in plasma regenerating islet-derived 3-alpha (REG 3-alpha), a C-type lectin antimicrobial peptide synthesized by enterocytes and Paneth cells, during intestinal acute rejection [89]. As the REG3-alpha increase seems to have also heralded rejection within 1 week, it is possible that this molecule will attract more attention in an effort to determine its value in terms of specificity and sensitivity in the setting of intestinal transplantation. A relatively recent and still evolving paradigm in the follow-up of ITx patients is the monitoring of the development of humoral immunity against the graft. De novo production of antibodies against the graft’s human leukocyte antigens (HLA), the so-called donor-specific HLA antibodies (DSA), has been linked with a higher risk of ACR in several types of organ transplants, including ITx [90,91,92,93,94]. A detailed account of the type, impact and management of DSAs after ITx is beyond the scope of this review. Nonetheless, it is worth mentioning that several independent studies analyzed the relationship between de novo DSAs and outcomes, including ACR, and most could not identify a clear, significant relationship between de novo DSA and ACR. However, most studies suggest that long-term outcomes were poorer in patients developing de novo DSAs, and DSAs can be considered an indicator of ongoing, low-grade immunologic activity against the intestinal allograft. A different and more pragmatic approach has been represented in the analysis of the ostomy effluent. Whereas this approach is less used in rodents, it allows easy, non-invasive access to abundant biological material originating in or having direct contact with the intestinal mucosa, the same site where rejection occurs. Fecal calprotectin levels (FCL) have been routinely used in practice over the last few decades to initially differentiate between inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), as well as to assess mucosal healing or the recurrence of inflammation in the follow-up of IBD patients. Calprotectin is a calcium- and zinc-binding protein of the S-100 protein family, mainly found within neutrophils, and its presence in feces is due to neutrophil infiltration into the gastrointestinal tissue secondary to an infection or an inflammatory process. Fecal calprotectin is homogenously distributed in stools and is very resistant to in vivo degradation (pancreatic secretions and intestinal proteases, bacterial degradation) and in vitro degradation (several days at room temperature). The first article on the analysis of calprotectin in the stomal fluid of intestinal transplant recipients reported increased FCL both during ACR rejection and non-specific enteritis and found an optimal cut-off level for calprotectin in predicting the presence or absence of intestinal allograft rejection at 92 mg/L with 77% specificity and 83% sensitivity [95]. This interesting report was soon followed by several other independent analyses that confirmed FCL is consistently increased during rejection compared with normal patients, but it has a rather low specificity for intestinal rejection [96,97,98]. In spite of the common conclusion that FCL alone cannot satisfactorily discriminate between rejection and inflammation or infection, there is a general perception that FCL could be used as a first-line test for continuous evaluation of intestinal graft status, as it may be useful to exclude inflammatory pathology and thus reduce the need for graft endoscopy by up to 45%. A combined approach using a multiplexed analysis of 17 cytokines and high-throughput proteomics of the ostomal effluent of 16 intestinal transplant recipients found increased levels of five innate immune cytokines early post-transplantation (granulocyte colony-stimulating factor, interleukin (IL)-8, tumor necrosis factor (TNF)-alpha, IL-1beta and IFNγ), but only IFNγ levels were significantly higher in samples with rejection [99]. Proteomic analysis revealed 17 proteins differentially seen in rejection, with three of them identified as human neutrophil peptides 1, 2 and 5. These proteins, which belong to the alpha-defensins (antimicrobial peptides), were also found to elevate early in the post-transplant stage and could reflect the rejection-associated innate immunity. Although the significance of these findings is unclear, this analysis suggests the potential presence of more interesting biomolecules in the stomal effluent, which may deserve further analysis. The presence of a very large, complex and dynamic microbial microenvironment makes the intestinal graft unique. The recent advances in sequencing technology have allowed the high-resolution analysis of the intestinal microbiome, unraveled the profound effects of intestinal microbiota on their hosts and involved the occurrence of multiple, highly diverse diseases, such as asthma [100], diabetes [101] and colon cancer [102], to name only a few. The high incidence of infections following ITx [103,104] mandates prolonged and repeated use of antibiotics, which alter the intestinal microbiome. Several immunosuppressive drugs currently used also have antibiotic activity [105,106], and changes in microbiome profiles during different immunosuppression regimens have been reported, suggesting that immunosuppression has an impact on the human microbial population [107]. In addition, the presence of feeding tubes and ostomies alters the normal microbial ecology of the transplanted intestine [108]. Thus, a shift in the microbiome from an aerobic–anaerobic condition to a predominantly anaerobic condition has been found following ileostomy removal and the restoration of intestinal continuity in intestinal transplant recipients, although the small bowel did not seem to be negatively affected by this. In a clinical study on 19 ITx recipients, comparisons between samples from non-rejecting ITx and ITx with ACR revealed major alterations in the proportions of multiple bacterial taxa associated with active rejection [109]. At the phylum level, it has been reported that there was a reduction in Firmicutes (from 81 to 29%) and an expansion of Proteobacteria (from 16 to 61%) during manifest ACR, whereas at the family level, a decrease in Streptococcaceae, Enterococcaceae and Lactobacillaceae was observed. However, the study did not detect clear, significant differences between non-rejecting ITx and ITx in the period preceding ACR, which could be used as early biomarkers, although the ITx microbiota in the pre-rejection period showed the same trend as that found during ACR. Part of these findings was confirmed by a recent analysis of 43 ITx recipients, where patients without ACR beyond the first 6 months after transplantation and normal ITx function showed a large predominance of Firmicutes and a composition of other phyla, including Proteobacteria and Bacteroidetes, that was closer to the general population. In contrast, the transplanted microbiome showed an Enterococcus-dominant dysbiosis and a relative increase in Enterococcous and Fuminococcus [110]. Although a direct cause–effect relationship between the microbiome alterations (including the enterococcus predominance) and the ACR and its role in graft monitoring remains to be established, these initial findings have important potential clinical implications in terms of patient management, as future targeted strategies to control the degree of intestinal Enterococcus colonization could have a beneficial impact on graft and patient outcome. The last four decades of experimental and clinical research have identified hundreds of molecules that may be altered during the intestinal ACR, with some having the potential to assist with its diagnosis, prognosis and follow-up. Unfortunately, very few, if any, have shown true value in a clinical setting. This may be due both to the differences between experimental and clinical settings, the small size and inherent heterogeneity of clinical studies, as well as the technical and biological limitations of the approaches used. Nowadays, it is believed that either an entirely new, intestine-specific assay or a panel of less specific tests would be necessary to increase the accuracy of non-invasive rejection monitoring. The application of new analytical and bioinformatics techniques would allow a comprehensive analysis of complex biological samples and the simultaneous detection of a large number of chemically diverse analytes. This has already been applied in kidney transplantation, where a composite metabolite–mRNA signature in urine was diagnostic of ACR with high accuracy [111,112]. In ITx, the recent technical developments and progress of high-throughput omics technologies have already identified some additional molecules or biological pathways with potential biomarker value, which are summarized below. In 36 ITx patients receiving different types of visceral allografts, metabolomics of the stomal effluent or feces demonstrated different metabolomic profiles between rejection and nonrejection [113]. A total of 477 (19%) of the 2541 detected metabolites revealed a significant fold change between rejection and nonrejection, and, following the examination of several databases, the metabolites with the most significant fold change between rejection and nonrejection were identified as leukotriene E4 (a metabolite of arachidonic acid), D-pantethine, the dimeric form of pantothenic acid (vitamin B5), pyridoxal-5-phosphate (vitamin B6), taurocholate (a bile salt of taurocholic acid) and riboflavin (vitamin B2). Whether these analytes themselves could be useful as new biomarkers of intestinal rejection or other components of their metabolic pathways are affected by rejection and could be analyzed remains unclear. A second high-throughput analysis using quantitative proteomics with iTRAQ-labeling and mass spectrometry performed in rejecting murine intestines and mentioned earlier [70] identified 86 proteins differentially expressed in rejecting allografts versus non-rejecting isografts (variation > 20%) and an alteration pattern unique to the rejecting allografts: thirty-seven proteins and enzymes (including S100-A8 and IDO-1) were significantly upregulated, whereas forty-nine (among other chromogranins, ornithine aminotransferase and arginase) were downregulated. Following the exclusion of eight proteins that revealed the same alteration pattern as that found in syngeneic grafts and were likely unrelated to AR, 86 proteins continued to reveal an alteration pattern only found in the rejecting allografts. These changes involved multiple metabolic pathways, whose secondary metabolites and downstream metabolic processes may reveal potential biomarkers for intestinal AR. The intestinal graft appears to have a unique immunology due to its contact with external antigens and the exposure to the intestinal microbiota, the gut-associated lymphoid tissue following with the graft, as well as the abundance of epithelial cells. Graft rejection occurs more frequently than in any other type of organ transplant, in spite of potent immunosuppression, and may rapidly result in the loss of the mucosal barrier, life-threatening sepsis and patient death. At the same time, the transplanted intestine lacks reliable, specific, noninvasive biomarkers, allowing non-invasive rejection surveillance. As most of the non-invasive assays tested to date in ITx are the same as those used in the management of inflammatory bowel disease, they all lack specificity by default. Future research should continue the quest to improve our understanding of two-way allogenicity, with an emphasis on the generation of regulatory populations that may reduce the burden of immunosuppression. Additionally, further research efforts should continue to explore the development of assays capable of determining the involvement of memory T cells in the graft rejection process and their potential translational use. Likewise, advances in the monitoring of other types of allografts, such as circulating cell-free donor (i.e., graft) DNA or the alterations in the microbiota that may herald or favor ACR, should be tested in adequately sized, multicenter studies on either prospectively collected material or on existing biobank samples. The continuous quest for the identification of well-defined alterations occurring during rejection in the main targets of the immune response, that is, the intestinal mucosa and its microenvironment, could ultimately reveal the long-sought and badly needed rejection biomarker.

PMC10003357

Hsin-Han Hou,Bor-Shiunn Lee,Yu-Cheng Liu,Yi-Ping Wang,Wei-Ting Kuo,I-Hui Chen,Ai-Chia He,Chern-Hsiung Lai,Kuo-Lun Tung,Yi-Wen Chen

Vapor-Induced Pore-Forming Atmospheric-Plasma-Sprayed Zinc-, Strontium-, and Magnesium-Doped Hydroxyapatite Coatings on Titanium Implants Enhance New Bone Formation—An In Vivo and In Vitro Investigation

03-03-2023

atmospheric plasma,hydroxyapatite coating,osteogenesis,antibacterial,dental implant,zinc,strontium,magnesium

Objectives: Titanium implants are regarded as a promising treatment modality for replacing missing teeth. Osteointegration and antibacterial properties are both desirable characteristics for titanium dental implants. The aim of this study was to create zinc (Zn)-, strontium (Sr)-, and magnesium (Mg)-multidoped hydroxyapatite (HAp) porous coatings, including HAp, Zn-doped HAp, and Zn-Sr-Mg-doped HAp, on titanium discs and implants using the vapor-induced pore-forming atmospheric plasma spraying (VIPF-APS) technique. Methods: The mRNA and protein levels of osteogenesis-associated genes such as collagen type I alpha 1 chain (COL1A1), decorin (DCN), osteoprotegerin (TNFRSF11B), and osteopontin (SPP1) were examined in human embryonic palatal mesenchymal cells. The antibacterial effects against periodontal bacteria, including Porphyromonas gingivalis and Prevotella nigrescens, were investigated. In addition, a rat animal model was used to evaluate new bone formation via histologic examination and micro-computed tomography (CT). Results: The ZnSrMg-HAp group was the most effective at inducing mRNA and protein expression of TNFRSF11B and SPP1 after 7 days of incubation, and TNFRSF11B and DCN after 11 days of incubation. In addition, both the ZnSrMg-HAp and Zn-HAp groups were effective against P. gingivalis and P. nigrescens. Furthermore, according to both in vitro studies and histologic findings, the ZnSrMg-HAp group exhibited the most prominent osteogenesis and concentrated bone growth along implant threads. Significance: A porous ZnSrMg-HAp coating using VIPF-APS could serve as a novel technique for coating titanium implant surfaces and preventing further bacterial infection.

Vapor-Induced Pore-Forming Atmospheric-Plasma-Sprayed Zinc-, Strontium-, and Magnesium-Doped Hydroxyapatite Coatings on Titanium Implants Enhance New Bone Formation—An In Vivo and In Vitro Investigation Objectives: Titanium implants are regarded as a promising treatment modality for replacing missing teeth. Osteointegration and antibacterial properties are both desirable characteristics for titanium dental implants. The aim of this study was to create zinc (Zn)-, strontium (Sr)-, and magnesium (Mg)-multidoped hydroxyapatite (HAp) porous coatings, including HAp, Zn-doped HAp, and Zn-Sr-Mg-doped HAp, on titanium discs and implants using the vapor-induced pore-forming atmospheric plasma spraying (VIPF-APS) technique. Methods: The mRNA and protein levels of osteogenesis-associated genes such as collagen type I alpha 1 chain (COL1A1), decorin (DCN), osteoprotegerin (TNFRSF11B), and osteopontin (SPP1) were examined in human embryonic palatal mesenchymal cells. The antibacterial effects against periodontal bacteria, including Porphyromonas gingivalis and Prevotella nigrescens, were investigated. In addition, a rat animal model was used to evaluate new bone formation via histologic examination and micro-computed tomography (CT). Results: The ZnSrMg-HAp group was the most effective at inducing mRNA and protein expression of TNFRSF11B and SPP1 after 7 days of incubation, and TNFRSF11B and DCN after 11 days of incubation. In addition, both the ZnSrMg-HAp and Zn-HAp groups were effective against P. gingivalis and P. nigrescens. Furthermore, according to both in vitro studies and histologic findings, the ZnSrMg-HAp group exhibited the most prominent osteogenesis and concentrated bone growth along implant threads. Significance: A porous ZnSrMg-HAp coating using VIPF-APS could serve as a novel technique for coating titanium implant surfaces and preventing further bacterial infection. Titanium dental implants have revolutionized dentistry and become one of the most common treatment options for replacing missing teeth in partially or fully edentulous patients [1]. Osseointegration is defined as the direct functional and structural connection between living bone and the load-bearing surface of a titanium implant [2]. Osseointegration includes primary stability (mechanical stability) and secondary stability (biological stability). Mechanical stability is determined by the bone density and implant design, whereas biological stability is associated with physiologic bone healing. The cellular and molecular phenomena that occur during osseointegration form a cascade including blot clot formation, angiogenesis, the migration of osteoprogenitor cells, woven bone formation, and bone remodeling [3]. Therefore, the surface treatment of a dental implant may influence bone deposition and determine the implant success at an early stage. Various studies have proposed increasing surface hydrophilicity and attracting osteoprogenitor cells using the advantages of metal ions [4,5,6,7,8]. Treating titanium implant surfaces with calcium phosphate deposition via immersion in simulated body fluid under physiological conditions of temperature (37 °C) and pH (7.4) has been proven to enhance surface hydrophilicity, attract osteoinductive agents, and promote bone healing [9]. Strontium (Sr) has been reported to regulate osteoblast-related gene expression, enhance alkaline phosphatase (ALP) activity, and reduce osteoclast differentiation [5]. Strontium ranelate has been demonstrated to increase runt-related transcription factor 2 (Runx2) expression and matrix mineralization and attenuate bone resorption in an osteopenic mouse model [6]. Zinc (Zn) and magnesium (Mg) are essential elements for increasing alkaline phosphatase activity [7,8] and bone protein synthesis [10], thus promoting bone formation [11]. Peri-implantitis is defined as soft tissue inflammation and progressive bone loss around dental implants and is considered a polymicrobial anaerobic infection associated with biofilms [12,13]. Various clinical regimes for preventing and treating peri-implantitis have been proposed based on its pathophysiology, including mechanical debridement, laser treatment, locally delivered antiseptics, local or systemic antibiotics, and surgical access and regenerative procedures. However, a gold standard protocol for treating peri-implantitis has yet to be established [14]. Metal coatings, such as Ag+, Zn2+, Sr2+, Mg2+, Ca2+, F−1 and Sc+3, and antimicrobial peptides have been reported to inhibit bacterial adhesion and enhance osseointegration [15,16,17,18,19]. Hydroxyapatite (HAp) coatings doped with 1 wt% AgNO3 (AgHA1.0) exhibit the ability to minimize the initial adhesion of Streptococcus aureus and Staphylcoccus epidermidis [20]. Metal ions can prevent the emergence of drug-resistant bacteria resulting from the overuse of antibiotics. Titanium plates coated with a copper-HAp composite via two-stage electrochemical synthesis have demonstrated excellent antibacterial properties against Escherichia coli (Gram-negative) and S. aureus (Gram-positive) [21]. Moreover, Zn has been added to toothpaste and mouth rinses to inhibit calculus deposition and the growth of cariogenic bacteria [22]. Therefore, the development of an implant surface with antimicrobial properties is essential. Implant coating materials, such as metals (titanium and its alloys, aluminum alloys, cobalt, and zirconium), ceramics (HAp), and polymers (polyurethane and polyethylene), are crucial to maintaining superior mechanical properties, corrosion resistance, and antimicrobial properties [23]. Surface modification treatments, including physical (electron beam evaporation, thermal spraying, pulsed laser deposition, and thermal evaporation) and chemical methods (chemical vapor deposition, electrophoretic deposition, and sol–gel coating), have been widely applied to improve surface properties [23]. HAp is among the most in-demand materials for the modification of surface properties for optimal osseointegration in implantology [24,25,26]. Furthermore, HAp is resistant to X-ray and UV irradiation and does not display visible aging/structural damage [27,28]. Our previous study proved that the vapor-induced pore-forming atmospheric plasma spraying (VIPF-APS) technique could effectively produce a porous HAp coating and contribute to a more bioactive coating for osteoblast proliferation [29]. Sr- and Mg-doped HAp implants were demonstrated to enhance osteoblast proliferation and new bone formation in a beagle dog model [29]. To the best of our knowledge, the effect of Zn-, Sr-, and Mg-multidoped HAp-coated titanium implants on the enhancement of bone formation has yet to be investigated. In addition, Zn-, Sr-, and Mg-multidoped HAp coatings produced using the VIPF-APS technique have never been examined. Therefore, the novelty of this study lies in the use of the VIPF-APS technique to create Zn-, Sr-, and Mg-multidoped HAp porous coatings on titanium discs and implants. The mRNA and protein levels of osteogenesis-associated genes such as collagen type I alpha 1 chain (COL1A1), decorin (DCN), osteoprotegerin (TNFRSF11B), and osteospontin (SPP1) were examined. The antibacterial effects against periodontal bacteria, including Porphyromonas gingivalis and Prevotella nigrescens, were investigated. Moreover, a rat model was used to evaluate osseointegration via histologic examination and micro-computed tomography (micro-CT). The HEPM cells were incubated on titanium discs coated with HAp, Zn-HAp, or ZnSrMg-HAp for 3 (Figure 1A), 7 (Figure 1B), and 11 days (Figure 1C). The purified cellular total RNA was used for a qPCR assay with primer sets of COL1A1, DCN, TNFRSF11B, and SPP1. The mRNA levels of TNFRSF11B and SPP1 significantly increased in the ZnSrMg-HAp group after 7 days of incubation compared with those of the HAp group (Figure 1B). Moreover, the mRNA levels of TNFRSF11B and DCN also significantly increased in the ZnSrMg-HAp group after 11 days of incubation compared with those of the HAp group (Figure 1C). To confirm the protein expression level according to the previous qPCR results, the cellular lysate was used in a Western blot assay. The protein levels of TNFRSF11B and SPP1 significantly increased in the ZnSrMg-HAp group after 7 days of incubation compared with those of the HAp group (Figure 2A,B). Moreover, the protein levels of TNFRSF11B and DCN significantly increased in the ZnSrMg-HAp group after 11 days of incubation compared with those of the HAp group (Figure 2C,D). These results demonstrated that the titanium discs coated with ZnSrMg-HAp prominently increased the expression of osteointegration-associated genes and proteins and suggested that the ZnSrMg-HAp coating promoted osteointegration ability. The ZnSrMg-HAp group demonstrated superior antibacterial activity against P. gingivalis compared with the Zn-HAp and HAp groups (Figure 3A). The ZnSrMg-HAp and Zn-HAp groups demonstrated prominent antibacterial activity against P. nigrescens. However, no difference was observed between the ZnSrMg-HAp and Zn-HAp groups (Figure 3B). In contrast, the HAp group did not demonstrate an apparent antibacterial effect against P. gingivalis or P. nigrescens. Micro-CT reconstruction images are shown in Figure 4A. Within the ROI of 0.85 mm and 1.1 mm, the bone coverage rate was significantly higher in the Zn-HAp and ZnSrMg-HAp groups compared to the HAp group at 2 and 4 weeks (Figure 4B,C). BV/TV was also significantly higher in the Zn-HAp and ZnSrMg-HAp groups at 2 and 4 weeks compared to the HAp group (Figure 4D). In contrast, the Zn-HAp and ZnSrMg-HAp groups exhibited significantly lower BMDs at 2 and 4 weeks compared to the HAp group (Figure 4E). Figure 5 shows that the ZnSrMg-HAp group exhibited better osteointegration than the HAp and Zn-HAp groups. At 2 weeks after implantation, the HAp group only achieved integration within the cortical bone area (the first and second threads). A focal discontinuous deposit of the bone on the implant surface was observed down to the interthread area between the third and fourth threads. Similar effects were also discerned in the Zn-HAp group, with a patchy surface bony deposit present down to the region slightly beyond the tip of the fifth thread (the third thread in the cancellous bone). In contrast, continuous bone formation on the implant surface was evident down to the lower slope of the sixth thread in the ZnSrMg-HAp group. The advantage of ZnSrMg-HAp surface processing in terms of osteointegration was more profound 4 weeks after implantation. Continuous and complete bone coverage was identified on all threads in the cancellous bone in the ZnSrMg-HAp group, whereas this feature could only be found down to the fourth and fifth threads in the HAp and Zn-HAp groups, respectively. At higher magnification (100×, thickened bone deposition was more apparent on the implant surface in the ZnSrMg-HAp group than in the HAp and Zn groups. This was the first study to use VIPF-APS to prepare porous coatings on dental implant surfaces. In addition, three-element doped HAp was successfully produced using ion doping technology. Compared with multi-element doped HAp prepared using the traditional solid-phase method [30], the coprecipitation method adopted in this study controlled the amount of ion doping more precisely and suppressed the generation of other non-targeted substances resulting from HAp phase transformation or an incomplete oxidative process [31]. Various coating techniques, such as plasma spraying, hydrocoating, two-stage processing, physical vapor deposition, thermally applied coating, and nanoscale technology, have been developed for implant surface modification [32]. Plasma spraying is the most commonly used technique for applying ion coatings on implant surfaces. The physical principles of the novel VIPF-APS technique in this study are based on the penetration of expansive vapors through melted HAp. The porous structure serves as a cavity for the recruitment of undifferentiated mesenchymal cells to the implant surface compared with the dense HAp coatings using traditional APS. Achieving a balance between mechanical strength and adequate pore size for bone ingrowth is critical for implant surface modification. In this study, the pore diameter of the coatings on titanium discs prepared via VIPF-APS was approximately 38 μm [33]. Our previous study demonstrated that the VIPF-APS technique could effectively produce porous HAp coatings that are favorable for higher osteoblast proliferation and alkaline phosphatase activity. The size of interconnecting pores is critical in affecting bone ingrowth. A pore size between 100 and 400 μm has been suggested to be favorable for bone ingrowth [34]. Another study showed that a pore size range of approximately 50 to 400 μm is optimal for fixation strength (17 MPa) [35]. The HAp coatings prepared using the VIPF-APS technique had more than 8% porosity compared to the traditional APS technique [31]. Therefore, we used the advantage of the VIPF-APS technique to produce Zn-, Sr-, and Mg-doped HAp coatings on titanium discs and implants. In addition to the successful preparation of porous HAp coatings on dental implants, this study also succeeded in preparing a three-element doped HAp coating powder for VIPF-APS. HEPM cells are preosteoblasts that can differentiate into osteoblasts on titanium plates [36]. The growth and differentiation of osteoblasts can be divided into three periods based on the different genes expressed in each period: proliferation, extracellular matrix maturation, and extracellular matrix mineralization. First, collagen 1 and 2 (COL1, 2) are upregulated in the early stages of osteoblast differentiation. Next, SPP1 is required for extracellular matrix maturation. Finally, in the period of extracellular matrix mineralization, Ca2+ binding proteoglycans such as biglycan and DCN are secreted [37]. In addition, DCN has been proven to modulate collagen matrix assembly and mineralization [38] and regulate the cell cycle [39]. Otherwise, TNFRSF11B, a tumor necrosis factor receptor superfamily member, functions as a negative regulator of bone resorption by regulating osteoclast development [40]. Thus, we quantified the mRNA and protein expression of gene markers, including COL1, SPP1, DCN, and TNFRSF11B at different stages of HEPM (3, 7 and 11 days). The results showed that Zn-HAp had significantly higher COL1 and DCN mRNA than the HAp group on the third day. On the 11th day, Zn-HAp and ZnSrMg-HAp had significantly higher DCN and TNFRSF11B activity than HAp. In a previous study, human dental pulp stem cells cultured on Zn-modified titanium plates were proven to enhance the expression of osteoblast-related genes, such as COL1, bone morphogenetic protein 2, ALP, Runx2, osteopontin, and vascular endothelial growth factor A in vitro [41]. Our results were in agreement with previous studies that demonstrated the upregulating ability of Zn in an osteoblast culture (24–72 h) [42,43]. In addition, ZnSrMg-HAp had significantly higher SPP1 and TNFRSF11B activity than the HAp group on the seventh day. In bone-defect mice, the promoter activity of nuclear factor-kappa beta and vascular endothelial growth factor receptor-2 is upregulated by Sr supplementation [44]. Mg supplementation has been proven to upregulate the mRNA of peroxisome proliferator-activated receptor gamma and glucose transporter 1 in peripheral blood mononuclear cells from women with gestational diabetes [4]. The results of this study were in line with the process of bone differentiation and proved that Zn alone or ZnSrMg were effective in improving bone growth and maturation. In other words, ZnSrMg plays a critical role in the process of osteoblast growth and differentiation in vitro. Antibiotics represent the most effective method for treating peri-implantitis in a clinical setting. However, bacterial resistance could be a concern because of excessive antibiotic usage [45]. To examine the effect of element-doped HAp coatings against periodontal pathogens, we chose P. gingivalis and P. nigrsecens as the target bacteria. Our results showed that the antibacterial activity of the ZnSrMg-HAp group was superior to that of the Zn-HAp group. Previous studies have reported that Zn, Sr, and Mg ions released from HAp coatings enhanced bone mineralization and exhibited antibacterial properties [46,47,48]. The release of mental ions from HAp coatings formed an alkaline environment and was not favorable for bacterial growth. Moreover, the membrane potential difference caused by metal ions may result in electron transfer and generate excessive amounts of reactive oxygen species, which further kills bacteria [49]. An implant surface with antibacterial properties, particularly the inhibition of biofilm formation and bacterial adhesion, is the most promising strategy for preventing or treating peri-implantitis. Unlike the results regarding protein expression shown in Figure 2, the bone coverage rate in the Zn-HAp group was not significantly different from that of the ZnSrMg-HAp group. The reason might be that animals were sacrificed after at least 2 weeks, which was longer than the examination time for protein expression. The bone growth for osteointegration occurs very early after implant placement. The ZnSrMg-HAp group exhibited a higher bone coverage rate at an ROI of 0.85 mm compared with the Zn-HAp group at both 2 and 4 weeks (Figure 4B). In contrast, the bone coverage rate was higher in the Zn-HAp group than in the ZnSrMg-HAp group at an ROI of 1.1 mm (Figure 4C). However, no significant difference was found for both ROIs. The Sr2+ and Mg2+ ions released from ZnSrMg-HAp could stimulate osteogenesis and new bone formation concentrated along the implant threads. Therefore, the bone coverage rate of the ZnSrMg-HAp group was more prominent at the smaller ROI (0.85 mm). These results were in agreement with the histological findings, which demonstrated that the ZnSrMg-HAp group exhibited more prominent continuous bone coverage on implant threads compared with the HAp and Zn-HAp groups (Figure 5). In addition, the concentrated bone growth on implant threads observed during the histological examination was not composed of cancellous bone. The bone volume fraction (BV/TV) did not differ significantly between the Zn-HAP and ZnSrMg-HAp groups (Figure 4D). The reason for this may be that the BV/TV was examined at an ROI of 1.1 mm and the animals were sacrificed at least 2 weeks after implant placement, as discussed previously. Compared with HAp coatings on titanium implants, the Zn-HAp and ZnSrMg-HAp groups showed significantly less bone mineral density (Figure 4E); these two groups exhibited more newly formed and unmineralized woven bone around the titanium implants, which in turn caused the lower bone mineral density. The preparation details of HAp, Zn-doped HAp, and Zn-Sr-Mg-doped HAp powders were described in a previous study [30]. Briefly, HAp coatings doped with different metal ions were prepared and denoted as HAp, Zn-HAp [Zn/(Ca+Zn) = 2.5%], and ZnSrMg-HAp [Zn/(Ca+Zn+Sr+Mg) = 2.5%, Sr/(Ca+Zn+Sr+Mg) = 5%, Mg/(Ca+Zn+Sr+Mg) = 5%]. The molar ratio of Ca(NO3)2/(NH4)2HPO4 was 10:6 for HAp, that of [Ca(NO3)2 + Zn(NO3)2]/(NH4)2HPO4 was 10:6 for Zn-HAp, and that of [Ca(NO3)2 + Sr(NO3)2 + Mg(NO3)2 + Zn(NO3)2]/(NH4)2HPO4 was 10:6 for ZnSrMg-HAp. The synthetic parameters were pH = 10 and a calcination temperature of 800 °C. The VIPF-APS technique was used to deposit HAp, Zn-HAp, and ZnSrMg-HAp on titanium implants (Stryker Leibinger GmbH & Co. KG, Freiberg, Germany) that were made of Ti6Al4V alloy, 5 mm in length and 1.2 mm in diameter (Figure 6). The technique involved water vapor being splashed on the titanium implant. The surfaces of the implant were roughened by sandblasting to Ra = 11.20 μm and then sprayed with a thin layer of HAp coating. After immersion in pure water, a single spray cycle was applied to the implant surface repeatedly until the desired thickness of HAp coating was achieved (30 µm). Finally, a porous surface structure was formed [33]. Human embryonic palatal mesenchymal (HEPM) cells (ATCC®CRL-1486TM) were incubated on titanium discs (diameter: 15 mm, thickness: 2 mm, Biomate Swiss GmbH, Zug, Switzerland) coated with HAp, Zn-HAp, or ZnSrMg-HAp for 3, 7, and 11 days. Subsequently, HEPM cells were used with TRIzol reagent (15596026, Invitrogen, Waltham, MA, USA) to extract mRNA. Purified cellular total RNA (100 ng) was used with the Power SYBR™ Green RNA-to-CT™ 1-Step Kit for reverse-transcription reaction. The corresponding cDNA was used in a quantitative polymerase chain reaction (qPCR) assay with Biorad CFX96 (Bio-Rad, Hercules, CA, USA) with primer sets of COL1A1, F: GATTCCCTGGACCTAAAGGTGC, and R: AGCCTCTCCATCTTTGCCAGCA; DCN, F: AGCTGAAGGAATTGCCAGAA, and R: CTCTGCTGATTTTGTTGCCA; TNFRSF11B, F: GAACCCCAGAGCGAAATAC, and R: CGCTGTTTTCACAGAGGTC; SPP1, F: CGAGGTGATAGTGTGGTTTATGG, and R: GCACCATTCAACTCCTCGCTTTC; and GAPDH, F: GTCTCCTCTGACTTCAACAGCG, and R: ACCACCCTGTTGCTGTAGCCAA [50,51]. HEPM cells were cultured on titanium discs coated with HAp, Zn-HAp, or ZnSrMg-HAp for 7 and 11 days at 37 ℃ in an incubator with 5% CO2 in Dulbecco’s modified Eagle’s medium/F12 (1:1) (1×) (21041-025, Gibco™ - Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum and 1% antibiotic pen-strep-amphotericin. HEPM cells were lysed using radioimmunoprecipitation assay buffer (W-7849-500, Goal Bio, Taipei, Taiwan) and cellular lysates were centrifuged at 12,000× g rpm for 5 min for supernatant collection. The extracted protein was quantified using a protein assay kit (500-0006, Bio-Rad, Hercules, CA, USA). Equal amounts of protein were separated using 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to Amersham Hybond P 0.45 μm polyvinylidene fluoride (10600023, GE Healthcare, Chicago, IL, USA). After blocking with 5% skimmed milk, the membranes were incubated with various primary antibodies and then incubated with the corresponding secondary antibodies. The protein bands were detected using an Amersham ECL Select Western Blotting Detection Reagent (RPN2235, GE Healthcare, Chicago, IL) and quantified using ImageQuant 5.2 software (Healthcare Bio-Sciences, Pittsburgh, PA, USA). All experiments were repeated in triplicate (n = 3). P. gingivalis (ATCC 33277) and P. nigrescens (ATCC 332563) were stored at −80 °C and separately cultured on Brucella blood agar plates (Taiwan Prepared Media, Taipei, Taiwan) at 37 °C for 7 days under standard anaerobic conditions (80% N2, 10% H2, and 10% CO2). A strain of a single colony of these bacteria was then separately cultured in 5 mL of brain heart infusion broth (Neogen, Lansing, MI, USA) with 5 g of yeast extract (Thermo Fisher, Waltham, MA, USA) and an L-cysteine solution (0.5 g/mL) (Sigma-Aldrich, Lyon, France) at 37 °C under anaerobic conditions for 48 h. Subsequently, these bacteria were collected via centrifugation at 3000× g rpm for 10 min. Each resultant bacterial pellet was washed 3 times with sterile phosphate-buffered saline and then adjusted to a concentration of 1.6 × 108 colony-forming units (CFU)/mL before use [52]. The test samples were sterilized using saturated steam at 121 °C for 30 min. The HAp, Zn-HAp and ZnSrMg-HAp titanium discs were placed in P. gingivalis and P. nigrescens broth and incubated at 37 °C under anaerobic conditions for 120 h (n = 4). The bacterial suspension served as the control group. After 120 h, 1 mL was taken from each suspension, pipetted onto anaerobic blood agar, and cultured at 37 °C under standard anaerobic conditions for 120 h to count the CFU. Eight-week-old male Sprague Dawley rats (The Jackson Laboratory, BioLASCO Taiwan Co., Ltd., Taipei, Taiwan, 232.11 ± 20.33 g) were used (n = 18, randomly divided into 6 groups in 6 cages) following the guidelines and protocols of the Institutional Animal Care and Use Committee of National Taiwan University (IACUC-20200127). All animals were given free access to water and standard rat food (fat 50 g/kg, protein 226 g/kg, and metabolizable energy 3030 kcal/kg). The environment was maintained at a temperature between 20 °C and 24 °C and relative humidity between 40% and 70%. Moreover, the rats were kept under a 12 h light/dark cycle. All animal experiments complied with the ARRIVE guidelines and were conducted following the National Research Council’s Guide for the Care and Use of Laboratory Animals. Thirty-six titanium implants were coated with HAp, Zn-HAp, and ZnSrMg-HAp (n = 12). The titanium implants were randomly allocated to 2 experiment durations (2 and 4 weeks, n = 6 each) and placed in the tibia of 18 rats that were anesthetized with 20–40 mg/kg of Zoletil® 50 (Virbac, Carros, France) mixed with 5–10 mg/kg of Rompun® (Bayer, Leverkusen, Germany). Each rat received a 5–6 mm longitudinal skin incision along the tibia. After soft tissue dissection, 2 holes were drilled into the tibia bone using a 1.0 mm electronic drill at low speeds (800–2000 rpm), and 3 types of titanium implants were randomly allocated to be inserted into the holes. The wound was sutured layer by layer, and the stitches were removed after 1 week of healing. In addition, analgesics and antibiotics were provided in the drinking water (0.2 mg/mL of ibuprofen and 0.268 mg/mL of ampicillin in 5% dextrose) to reduce post-surgical pain and infection. All rats were sacrificed after 2 and 4 weeks of implantation. A flowchart of the animal experiment is shown in Figure 7. The tibia was harvested and scanned using the high-resolution SKYSCAN 1076 micro-CT apparatus (Skyscan NV, Kontich, Belgium). The bone coverage rate was defined as the percentage of direct bone-to-implant contact on the titanium implants. Two cylinders (0.85 and 1.1 mm in radius, 2.0 mm in length) starting from the first thread of the titanium implant were defined as the region of interest (ROI) [53,54]. For the evaluation of the bone volume fraction (bone volume/total volume, BV/TV) and bone mineral density (BMD), the ROI was defined as a cylinder (1.1 mm in radius and 2.0 mm in length) starting from the first thread of the titanium implant. The micro-CT technician and histological analyzer were blind to the sample groups. After fixation, serial dehydration, and embedding, resin blocks were trimmed to an appropriate size. The implant was sectioned into symmetrical halves using a low-speed saw (Isomet, Buehler Ltd., Lake Bluff, IL, USA) with a wafering diamond blade (6.6 cm × 0.15 mm) [55]. Cutting was performed at a blade speed of 100 to 500 rpm, using tap water as a lubricant, and with a force of 0.3 to 7 N acting on the specimen. The surface of the exposed specimen was polished using 600- or 800-grit silicon carbide paper followed by 4000-grit paper under water lubrication to remove cutting marks and obtain a highly polished surface. Subsequently, specimens were stained with Stevenel’s blue and then counterstained with alizarin red S for histological examination. An analysis of variance was used to examine the differences among all the groups, and Tukey’s post hoc test was used for qPCR and Western blotting to identify significant differences between 2 specific groups. A p-value less than 0.05 was considered statistically significant. In conclusion, porous ZnSrMg-HAp was successfully coated on titanium implants using the VIPF-APS technique. The ZnSrMg-HAp group was the most effective at inducing mRNA and protein expression of TNFRSF11B and SPP1 after 7 days of incubation, and TNFRSF11B and DCN after 11 days of incubation. The ZnSrMg-HAp group also demonstrated superior antibacterial activity against P. gingivalis. The animal model suggested that BV/TV was significantly higher in the Zn-HAp and ZnSrMg-HAp groups at 2 and 4 weeks compared to the HAp group. In addition, continuous bone coverage and thickened bone deposition was more apparent on the implant surface in the ZnSrMg-HAp group than in the HAp and Zn groups. However, notably, bone adjacent to the implant surface does not equate to a structural or functional connection between bone and the implant. Both osteointegration and antibacterial properties are essential characteristics for preventing peri-implantitis. Therefore, ZnSrMg-HAp has the potential to be used as a bioactive coating material for implant surfaces and consequently improve the survival rate in clinical use.

PMC10003359

Ju Zhao,Ye Zhao,Haifeng Liu,Quanquan Cao,Lin Feng,Zhihao Zhang,Weidan Jiang,Pei Wu,Yang Liu,Wei Luo,Xiaoli Huang,Jun Jiang

Dietary Leucine Improves Fish Intestinal Barrier Function by Increasing Humoral Immunity, Antioxidant Capacity, and Tight Junction

01-03-2023

leucine,intestinal barrier function,humoral immunity,antioxidant capacity,tight junction,autophagy

This study attempted to evaluate the possible impact and mechanism of leucine (Leu) on fish intestinal barrier function. One hundred and five hybrid Pelteobagrus vachelli ♀ × Leiocassis longirostris ♂ catfish were fed with six diets in graded levels of Leu 10.0 (control group), 15.0, 20.0, 25.0, 30.0, 35.0, and 40.0 g/kg diet for 56 days. Results showed that the intestinal activities of LZM, ACP, and AKP and contents of C3, C4, and IgM had positive linear and/or quadratic responses to dietary Leu levels. The mRNA expressions of itnl1, itnl2, c-LZM, g-LZM, and β-defensin increased linearly and/or quadratically (p < 0.05). The ROS, PC, and MDA contents had a negative linear and/or quadratic response, but GSH content and ASA, AHR, T-SOD, and GR activities had positive quadratic responses to dietary Leu levels (p < 0.05). No significant differences on the CAT and GPX activities were detected among treatments (p > 0.05). Increasing dietary Leu level linearly and/or quadratically increased the mRNA expressions of CuZnSOD, CAT, and GPX1α. The GST mRNA expression decreased linearly while the GCLC and Nrf2 mRNA expressions were not significantly affected by different dietary Leu levels. The Nrf2 protein level quadratically increased, whereas the Keap1 mRNA expression and protein level decreased quadratically (p < 0.05). The translational levels of ZO-1 and occludin increased linearly. No significant differences were indicated in Claudin-2 mRNA expression and protein level. The transcriptional levels of Beclin1, ULK1b, ATG5, ATG7, ATG9a, ATG4b, LC3b, and P62 and translational levels of ULK1, LC3Ⅱ/Ⅰ, and P62 linearly and quadratically decreased. The Beclin1 protein level was quadratically decreased with increasing dietary Leu levels. These results suggested that dietary Leu could improve fish intestinal barrier function by increasing humoral immunity, antioxidative capacities, and tight junction protein levels.

Dietary Leucine Improves Fish Intestinal Barrier Function by Increasing Humoral Immunity, Antioxidant Capacity, and Tight Junction This study attempted to evaluate the possible impact and mechanism of leucine (Leu) on fish intestinal barrier function. One hundred and five hybrid Pelteobagrus vachelli ♀ × Leiocassis longirostris ♂ catfish were fed with six diets in graded levels of Leu 10.0 (control group), 15.0, 20.0, 25.0, 30.0, 35.0, and 40.0 g/kg diet for 56 days. Results showed that the intestinal activities of LZM, ACP, and AKP and contents of C3, C4, and IgM had positive linear and/or quadratic responses to dietary Leu levels. The mRNA expressions of itnl1, itnl2, c-LZM, g-LZM, and β-defensin increased linearly and/or quadratically (p < 0.05). The ROS, PC, and MDA contents had a negative linear and/or quadratic response, but GSH content and ASA, AHR, T-SOD, and GR activities had positive quadratic responses to dietary Leu levels (p < 0.05). No significant differences on the CAT and GPX activities were detected among treatments (p > 0.05). Increasing dietary Leu level linearly and/or quadratically increased the mRNA expressions of CuZnSOD, CAT, and GPX1α. The GST mRNA expression decreased linearly while the GCLC and Nrf2 mRNA expressions were not significantly affected by different dietary Leu levels. The Nrf2 protein level quadratically increased, whereas the Keap1 mRNA expression and protein level decreased quadratically (p < 0.05). The translational levels of ZO-1 and occludin increased linearly. No significant differences were indicated in Claudin-2 mRNA expression and protein level. The transcriptional levels of Beclin1, ULK1b, ATG5, ATG7, ATG9a, ATG4b, LC3b, and P62 and translational levels of ULK1, LC3Ⅱ/Ⅰ, and P62 linearly and quadratically decreased. The Beclin1 protein level was quadratically decreased with increasing dietary Leu levels. These results suggested that dietary Leu could improve fish intestinal barrier function by increasing humoral immunity, antioxidative capacities, and tight junction protein levels. The intestine plays an important role in nutrient absorption and it is a key immunological barrier and physical barrier to the entry of harmful substances [1]. Amino acids play an important regulating role in intestinal barrier function [2]. Leucine (Leu) is one of the branched-chain amino acids, which are essential for human, fish, and other animal species [3,4]. Supplementation of dietary Leu or providing a Leu-rich diet will increase the protein accretion in tissues [3,5]. Yellow catfish (Pelteobagrus fulvidraco) is a common and commercially significant freshwater fish species raised in China. Hybrid catfish have been developed in recent years via breeding female Pelteobagrus vachelli and male Leiocassis longirostris. The hybrid catfish showed improved traits compared to their parents such as better growth performance and hypoxia tolerance [6]. Previous reports mainly focused on lipid accumulation, oxidative stress [7], disease resistance [8], and water temperature and stocking density [6]. Our earlier research determined optimal dietary tryptophan [9], threonine [10], and isoleucine [11] levels. In our previous study, the Leu requirement of hybrid catfish (23.19–54.55 g) for percent weight gain was estimated to be 28.10 g/kg of the diet (73.04 g/kg of dietary protein) based on the broken-line model [12]. However, no study has investigated the effect of Leu on intestinal barrier function in this fish. The intestinal immune barrier in fish is an important component of the intestinal barrier [13], which is maintained via humoral immune factors, such as lysozyme (LZM) [14,15,16], acid phosphatase (ACP), alkaline phosphatase (AKP) [11], complements (C3 and C4), immunoglobulin M (IgM) [17,18], and antimicrobial peptides (hepcidin and β-defensin) [11,19]. Previous studies have reported that Leu increased LZM activity and C3 and C4 contents in the intestine of juvenile golden pompano (Trachinotus ovatus) [20], and C3 and IgM contents in the liver of juvenile blunt snout bream (Megalobrama amblycephala) [21]. These data suggested that dietary Leu could enhance the intestinal immune barrier through increased humoral immunity. However, little research has focused on the influence of Leu on the intestinal immune barrier in hybrid catfish, which deserves further investigation. The reactive oxygen species (ROS) frequently found to metabolic production and fodder environments [22,23], increase the chance of oxidative damage and disturbed intestinal physical barrier function [24]. Antioxidant capacity is important for maintaining intestinal physical barrier function [13]. Fish intestinal antioxidant capacity is improved with increasing antioxidant enzymes activities, non-enzymatic antioxidant content, and up-regulating gene expressions of antioxidant enzymes [25]. The Nrf2/Keap1 signaling pathway is a fundamental signaling pathway responsible for regulating gene expressions of antioxidant enzymes [26]. Previous studies have indicated that Leu enhanced antioxidant enzyme activities and non-enzymatic antioxidant content through improving corresponding antioxidant gene expressions via the Nrf2/Keap1 signaling pathway in liver of the juvenile blunt snout bream [21] and intestine of young grass carp (Ctenopharyngodon idella) [27]. However, it is still unclear what impact Leu has on the intestinal antioxidant capacity of hybrid catfish. Tight junctions (TJs) play an important role in paracellular barrier functions. TJs comprise transmembrane proteins, such as occludin and Claudins, and intracellular plaque proteins, such as ZO-1 [28]. The impairment of intestinal TJ protein expression leads to the disruption of paracellular barrier function [29]. A previous study indicated that optimal dietary Leu increases the mRNA levels of occludin and ZO-1 in the intestine of grass carp [30]. Leu significantly enhanced protein levels of occludin in human colon carcinoma cell line LS174T [31] and increased the Claudin-2 protein level in human Caco2 BBe cells [32]. These up-to-date data suggested that Leu may enhance intestinal TJs by promoting protein expression of TJs via increasing their mRNA levels. Previous studies indicated that autophagy inhibition can significantly increase the protein level of occludin in mouse brain endothelial cells [33] and the protein level of ZO-1 rat brain microvascular endothelial cells [34]. A limited study indicated that Leu inhibits autophagy in zebrafish sperm [35]. However, whether Leu is involved in regulating intestinal TJs by inhibiting autophagy merits further investigation. Therefore, the objectives of the present study are to investigate the possible impacts and potential mechanisms of dietary Leu on the intestinal barrier function in hybrid catfish. These results may provide a partial theoretical basis to reveal the potential regulatory approach for intestinal barrier function by Leu in fish. The orthogonal polynomial contrasts showed that there were significant interactions of intestinal LZM, ACP and AKP activities, and C3, C4, and IgM contents, with graded dietary Leu levels (Table 1). The increasing Leu levels led to significant linear and quadratic increases in intestinal LZM, ACP, and AKP activities and C4 content (p < 0.05). With increasing dietary Leu level, the C3 content increased linearly (p < 0.05). The IgM content increased quadratically (p < 0.05). The itnl1, itnl2, c-LZM, and g-LZM mRNA expression increased linearly and quadratically (Figure 1A–D, p < 0.05). The β-defensin mRNA expression increased quadratically with increasing dietary Leu levels (Figure 1E, p < 0.05). The above results suggested that dietary Leu enhanced the intestinal immune barrier by increasing humoral immune-related parameter expression. The orthogonal polynomial contrasts showed that there were significant interactions of intestinal PC, MDA, ROS, and GSH contents, and ASA, AHR, T-SOD, CAT, GPX, GST, and GR activities, with graded dietary Leu levels (Table 2). The ROS, PC, and MDA contents were linearly and/or quadratically decreased with increasing dietary Leu levels (p < 0.05). No significant differences in the CAT and GPX activities were detected among treatments (p > 0.05). Increasing dietary Leu levels quadratically increased the GSH content, and ASA, AHR, T-SOD, and GR activities (p < 0.05). The GST activity was linearly increased with increasing dietary Leu levels (p < 0.05). The CuZnSOD mRNA expression increased quadratically (Figure 2A, p < 0.05). With increasing dietary Leu levels, the CAT and GPX1α mRNA expressions increased linearly (Figure 2B,D, p < 0.05). The GST mRNA expression decreased linearly (Figure 2C, p < 0.05). The GCLC and Nrf2 mRNA expressions were not significantly affected by different dietary Leu levels (Figure 2E,F, p > 0.05). The Nrf2 protein level quadratically increased (Figure 2H, p < 0.05). With increasing dietary Leu level, Keap1 mRNA expression and protein level decreased quadratically (Figure 2G,I, p < 0.05). The results demonstrated that dietary Leu increased antioxidant gene expression via the Nrf2/Keap1 signaling pathway. Immunochemistry analysis of TJ proteins, occludin, and ZO-1 showed that they were highly expressed in the fish fed the 25.0 g Leu/kg diet (Figure 3A). There was a linear and quadratic effect of dietary Leu levels on occludin mRNA expression (Figure 3B, p < 0.05). With increasing dietary Leu level, ZO-1 mRNA expression and protein level and occludin protein level significantly increased quadratically (Figure 3C–E, p < 0.05). Dietary Leu levels had no significant difference on Claudin-2 mRNA expressions and protein level (Figure 3F,G, p > 0.05). The orthogonal polynomial contrasts showed that the increasing Leu levels linearly and quadratically decreased the Beclin1, ULK1b, ATG5, ATG7, ATG9a, ATG4b, and LC3b mRNA expressions and ULK1 and LC3II/I protein levels, and linearly and quadratically significantly increased mRNA expression and protein level of P62 (Figure 4A,B,D–L, p < 0.05). The Beclin1 protein level was quadratically decreased with increasing dietary Leu levels (Figure 4C, p < 0.05). These results suggested that dietary Leu improved intestinal TJ function via up-regulating occludin and ZO-1 expressions and down-regulating autophagy-related parameter expressions. The immune function of the intestine is also an important element of the intestinal barrier [11]. Immune parameters such as immune-related enzymes (LZM and ACP), complement, and immune globulin have been regarded as crucial tools for investigating the intestinal immune barrier in fish [36,37]. LZM, as a first barrier against microbial invasion, participates in the innate immune response in fish [38,39,40,41]. ACP and AKP, important hydrolytic enzymes in lysosomes, have a beneficial effect on defense of the body against foreign pathogens and microorganism invasion [42]. The central components of the complement system mainly include C3 and C4, which play an essential role in alerting about potential pathogens in the host [43]. IgM has been well characterized in fish and seems to be specialized in systemic immunity [44]. The present study therefore further detected the effect of humoral immunity in hybrid catfish intestine and found the activities of LZM, ACP, and AKP and C3, C4, and IgM contents had positive linear and/or quadratic responses to dietary Leu levels. These results were in agreement with previous findings in the intestine of grass carp [30], and head kidney of Labeo rohita fingerlings [45]. Intelectin is a glycan-binding lectin, and it plays a major role in bacterial agglutination and binding capacity, as well as polysaccharide recognition in blunt snout bream [46]. The LZM activity was regulated by c-type and g-type LZM, which catalyzed the hydrolysis of bacterial cell walls [11,47]. β-defensins have been considered as a major class of antibacterial peptides, which have significant effect on congenital immunity of bony fish against bacteria [48,49]. In the present study, the itnl1, itnl2, c-LZM, g-LZM, and β-defensin mRNA expression had a positive linear and/or quadratic response in the intestine of hybrid catfish. These results are parallel to the previous studies showing that Leu dramatically improved mRNA expression of β-defensin in the intestine of weaned piglets and IPEC-J2 [50]. These results implied that dietary Leu exerts a positive effect on intestinal immune barrier function in hybrid catfish. A fish’s intestinal microbiota is essential to the host because it controls metabolic function, pathogen resistance, immunological activity, and feed conversion [51,52]. Previous research indicates that the intestinal microbiota may act as a mediating factor in the positive effect of dietary Leu supplementation on intestinal health of mice [53]. It is also unknown whether dietary Leu regulates the function of the intestinal immune barrier by affecting intestinal microbiota in hybrid catfish, which needs further study. The physical barrier function of the fish intestine is the first line of defense against infection [54], which is concerned with the cellular antioxidative state [11,55]. MDA and PC are considered to be important biochemical indicators, which are usually used to reflect lipid peroxidation and protein oxidation in tissues [56,57]. Due to the inescapable exposure to foreign materials, the intestine is also considered as a critical source of ROS [58]. Insufficient scavenging of ROS contributes to oxidative injury in the intestine [57]. This result demonstrated that dietary Leu linearly and/or quadratically decreased ROS, PC, and MDA contents in the intestine of hybrid catfish. Correlation analysis found that ROS was positively correlated with MDA (r = +0.912, p = 0.004) and PC contents (r = +0.793, p = 0.033) (Table 3), which indicated that dietary optimal Leu could ameliorate oxidative damage by reducing ROS accumulation. Studies on the gills of grass carp and porcine intestinal epithelial cells also demonstrated that Leu reduced the level of cell ROS [57]. The activities of ASA and AHR are two vital indices to assess the ability to scavenge superoxide anions (O2−) and hydroxyl radicals (OH−) in the intestine and hepatopancreas of juvenile Jian carp (Cyprinus carpio var. Jian) [59]. Here, we found that the activities of ASA and AHR had positive quadratic responses to dietary Leu levels. Correlation analysis showed that the ROS content was negatively related to ASA (r = −0.956, p = 0.001) and AHR (r = −0.954, p = 0.001) activities in the intestine of hybrid catfish (Table 3), which suggested that dietary Leu might decrease ROS accumulation by enhancing ASA and AHR activities. Previous researchers also reported that dietary Leu enhanced the activities of ASA and AHR in the gills of grass carp [60]. To alleviate oxidative damage caused by ROS, fish have formed efficient antioxidant networks that can be divided into two categories, non-enzymatic antioxidants (such as GSH) and antioxidant enzymes (such as CuZnSOD, CAT, GPX, and GR) [61,62]. The present experimental results indicated that GSH content and T-SOD, GST, and GR activities were linearly and/or quadratically increased with increasing dietary Leu levels. No significant differences in the CAT and GPX activities were detected among treatments. Correlation analysis showed that ROS was negatively correlated with GSH (r = −0.965, p = 0.000), T-SOD (r = −0.933, p = 0.002), CAT (r = −0.928, p = 0.003), GPX (r = −0.920, p = 0.003), GST (r = −0.943, p = 0.001), and GR (r = −0.942, p = 0.001) (Table 3), showing that Leu might diminish the accumulation of ROS via improving the intestinal GSH content, and T-SOD, CAT, GPX, GST, and GR activities. These results were in accordance with previous reports in the muscle of grass carp and intestine of juvenile golden pompano [20,27,63]. Increases in GSH content may be attributed to Leu metabolism. Leu can be transamined to form glutamate, which can be used as a source for mucous GSH synthesis [64,65]. The enzyme activities of antioxidants show positive relationships with their gene expressions in fish [66,67]. The current study found that the CuZnSOD, CAT, and GPX1α mRNA expressions were linearly and/or quadratically significantly increased with increasing dietary Leu levels. The GST mRNA expression decreased linearly while the GCLC mRNA expression was not significantly affected. Further correlation analyses showed that CuZnSOD, CAT, and GPX1α were, respectively, positively correlated with T-SOD (r = 0.981, p = 0.00), CAT (r = 0.861, p = 0.013), and GPX (r = 0.643, p = 0.119) (Table 3), which is in agreement with the results of previous research on the intestine of Jian carp [68]. Transcription factor Nrf2 was regarded as a pivotal regulator of the cellular antioxidant response. Keap1 is a critical sensor in cellular oxidative stress, which can bind to Nrf2 and constantly promotes its degradation, and is a negative regulator to switch off the Nrf2 response [26,69]. In this study, we observed that the Nrf2 mRNA expression was not significantly affected by different dietary Leu levels. The Nrf2 protein level quadratically increased, whereas the Keap1 mRNA expression and protein level decreased quadratically in the intestine of hybrid catfish. Correlation analysis showed that mRNA expression of Nrf2 was positively correlated with CuZnSOD (r = +0.892, p = 0.007), CAT (r = +0.794, p = 0.033), GPX1α (r = +0.849, p = 0.008), and GCLC (r = +0.818, p = 0.025) mRNA expressions, and Keap1 mRNA expression was negatively correlated with CuZnSOD (r = −0.975, p = 0.000), CAT (r = −0.906, p = 0.005), GPX1α (r = −0.794, p = 0.033), and GCLC (r = −0.919, p = 0.003) mRNA expressions (Table 3). Western blot analysis demonstrated that dietary Leu increased the protein level of Nrf2 and reduced the protein level of Keap1. Similar results were observed in the intestine of juvenile golden pompano [20] and the head kidney of Labeo rohita fingerlings [45]. Taken together, these results clearly indicated that dietary Leu could enhance intestinal antioxidative capacity by modulating the Nrf2/Keap1 signaling pathway in hybrid catfish. The paracellular barrier function of the intestine is related to the level of TJ proteins between epithelial cells [70]. The TJ proteins act as a paracellular barrier and serve as a first line of cellular defense against paracellular permeation of noxious luminal antigens [71,72]. Occludin, ZO-1, and Claudin-2, as the major components of TJ proteins, affect intestinal paracellular barrier functions [73]. Occludin plays a critical role in formation of TJ seals, and its damage facilitates macromolecule flux across the intestinal epithelial barrier [74]. ZO-1 is a cytoplasmic plaque protein that interacts with both transmembrane proteins and cytoskeletal proteins [75]. In the present study, the mRNA expression and protein level of intestinal ZO-1 and protein level of occludin significantly increased quadratically. Similarly, a study on the intestine of grass carp showed that optimal dietary Leu up-regulated occludin and ZO-1 mRNA expressions [30]. An in vitro model of intestinal epithelium lines demonstrated that Leu significantly enhanced occludin protein production [31]. Claudin-2 is expressed in the TJs of leaky epithelia, which is responsible for the flux of cations and small solutes [76]. In the current study, no significant differences were found in Claudin-2 mRNA expression and protein level. Claudin-2 knockout can cause defects in paracellular Na+ flow and nutrient transport in the intestine and result in death from malnutrition [77]. These results were in agreement with our previous report. Optimal dietary Leu improved feed efficiency in hybrid catfish [12] (Table S3). However, the underlying mechanism needs further investigation. The present study is the first to show that dietary Leu up-regulated the TJ function, partly ascribed to increases in TJ protein levels. New evidence revealed that autophagy plays an important role in maintaining occludin and ZO-1 protein levels [78]. The autophagy process involves three major phases: autophagosome initiation, elongation, and completion [79]. Beclin1 and ULK1 are involved in autophagy initiation [80,81]. ATG5 initiates the formation of double membrane vesicles [82]. Autophagy requires ubiquitin-like ATG8 and ATG12 conjugation systems, where ATG7 has a critical role as the sole E1 enzyme [83]. ATG9 is a multispanning membrane protein, which is essential for autophagy [84]. ATG4 is a key cysteine protease, which is crucial for proper biogenesis of the autophagosome [85]. The marker protein of autophagy is microtubule-associated protein light-chain 3 (LC3), which is responsible for the fusion of autophagosomes to lysosomes and formation of autolysosomes [86]. P62 is a multifunctional, cytoplasmic protein, which is degraded by autophagy in autophagy-mediated degradation progresses [87]. The present study observed that the Beclin1, ULK1b, ATG5, ATG7, ATG9a, ATG4b, and LC3b mRNA expressions and ULK1, Beclin1, and LC3II/I protein levels linearly and/or quadratically decreased, and mRNA expressions and protein levels of P62 linearly and quadratically increased, with increasing dietary Leu levels. A similar observation in sperm of zebrafish revealed that Leu suppressed autophagy by inhibiting the fusion of autophagosomes and lysosomes [35]. In addition, related research in HeLa cells showed that Leu alleviated autophagy via the impact of its metabolite AcCoA on mTORC1 [88]. Therefore, Leu might down-regulate autophagy levels in the fish intestine. Autophagy regulates the level of TJ proteins and therefore changes epithelial barrier function [89]. Di-(2-ethylhexyl) phthalate exposure destroyed the blood–testis barrier integrity of the immature testis through excessive ROS-mediated autophagy [90]. Autophagy inhibition increased occludin protein level in mouse brain endothelial cells [33]. In human squamous cell carcinoma cells, inhibition of autophagy can up-regulate ZO-1 protein level [91]. A previous study has demonstrated that Claudin-2 enhances the intestinal permeability [89]. Studies in MDCK I cells have shown that Claudin-2 mediated cation and water transport [92]. Thus, Claudin-2 may be beneficial for nutrient absorption of small molecules, which needs further investigation. These findings might partly explain why dietary Leu increased occludin and ZO-1 protein levels through down-regulating autophagy. Nevertheless, the detailed mechanism still requires a further investigation. This present experiment used a total of 630 fish with an average initial weight of 23.19 ± 0.20 g were randomly distributed into 21 tanks, with 30 fish in each tank, and feed formulation according to our previous study [12] (Table S1). The Leu was added to the experimental diets at levels of 10.0 (control), 15.0, 20.0, 25.0, 30.0, 35.0, and 40.0 g/kg diet [12] (Table S2). After the 8-week feeding trial, twelve fish from each replicate were anesthetized with benzocaine solution (50 mg/L). Then, fish were sacrificed on the basis of the methods of Lisbeth et al. [93]. The intestine samples were obtained and stored at −80 °C until further analysis. The samples of intestine were carefully homogenized with 10 volumes (mg/mL) of chilled physiological saline solution. The homogenates were centrifuged at 6000 g for 20 min at 4 °C. The supernatant was collected for antioxidant and humoral immune indicators. The MDA, PC, and GSH contents and ASA, AHR, T-SOD, CAT, GPX, GST, and GR activities were determined as described by Jiang et al. [55]. The LZM, AKP, and ACP activities, and C3, C4, and IgM contents, were measured as described in the study by Zhao et al. [11]. The ROS content was spectrophotometrically assayed by detecting the oxidation of 2′,7′-dichlorofluorescein [94]. The intestine tissues were embedded in paraffin and sectioned into slices 6 μm thick. Slices were incubated at 37 °C for 24 h before being incubated at 60 °C overnight. Following normal immunohistochemistry procedures, paraffin-embedded tissue slides were deparaffinized with xylene, and dehydrated with gradient ethanol. Heat-induced antigen retrieval was carried out for 15 min at 95 °C in citrate buffer [95]. This was followed by a 15 min incubation with 3% hydrogen peroxide at room temperature for elimination of endogenous peroxidase. Next, the tissue sections were blocked with 2% bovine serum albumin (BSA) for 30 min at room temperature, and then incubated overnight at 4 °C with occludin and ZO-1 polyclonal antibodies (diluted 1:100 with TBST; ABclonal, Chengdu, China). Afterwards, the tissue sections were incubated for 15 min at 37 °C with IgG secondary antibody, and then for another 30 min with peroxidase-labeled streptomycin (MXB Biotechnologies, Fuzhou, China), followed by washing for 5 min with phosphate buffer thrice. The sections were visualized with a DAB chromogenic substrate kit, and the nuclei were stained with hematoxylin. Imaging and analysis were carried out under an Olympus BX43F upright microscope. Total RNA from intestinal tissues was extracted according to the manual of the RNAiso Plus kit (TaKaRa, Dalian, China), and quantified by DU 640 UV spectrophotometer detection (Beckman, USA) at 260 and 280 nm. Using 1.0% agarose gels detecting the integrity of RNA, thereafter, we immediately reverse-transcribed it into cDNA by using the PrimeScript® RT reagent kit with gDNA Eraser (TaKaRa, Dalian, China). Sequences of primers used to perform RT-qPCR are listed in Table S4. The qRT-PCR analysis was performed using a CFX96 Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA). The relative mRNA expression was computed using the 2−ΔΔCT method, and the final results were all normalized to house-keeping genes (including β-actin and 18S rRNA). The protein from intestines was extracted according to a previous study [12]. Protein concentration was determined using a protein quantification kit (Beyotime, Shanghai, China). The protein samples were subjected to SDS-PAGE and then transferred onto a PVDF membrane (Millipore, Inc., Bedford, MA) by wet electroblotting. After blocking with 5% bovine serum albumin (in Tris-buffered saline containing Tween 20) at room temperature for approximately 2 h, samples were subsequently incubated overnight in primary antibodies: Nrf2 and Keap1 (1:2000, Zen Biotechnology, Chengdu, China), Beclin1, ULK1, LC3Ⅱ/Ⅰ, P62, occludin, ZO-1, and Claudin-2, (1:2000, ABclonal, Chengdu, China). The membranes were subjected to washing three times, and then incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies for approximately 2 h. β-actin (1:1000; CST) and Lamin B1 (1:2000, Zen Biotechnology) were considered as the control proteins for total and nuclear protein. The immune response bands were measured by enhanced chemi-luminescence. Quantify protein expression was detected by a Gel-Pro Analyzer (Media Cybernetics Bethesda, MD, USA), and analyzed by the ImageJ gel analysis software [96]. The trends of linear and quadratic analyses were measured by using SAS software version 8.0 (SAS Institute Inc., Cary, NC, USA) [97,98]. All results were subjected to one-way ANOVA analysis followed by Duncan’s multiple range test to evaluate the differences within treatments using SPSS version 25.0 (SPSS Institute Inc., Chicago, IL, USA). The level of significance for all analyses was considered p < 0.05. Data were expressed as the mean ± SEM. Bivariate correlation analysis was performed with Pearson correlation. In summary (Figure 5), dietary Leu enhanced intestinal immune barrier function via increasing humoral immune factors and related genes’ expression, and intestinal physical barrier function by regulating intestinal antioxidant capacity via the Nrf2/Keap1 signaling pathway, in fish. In addition, this study provides evidence that dietary Leu improved the functioning of intestinal TJ by down-regulating autophagy in fish, but the detailed mechanism needs further study. These results of the study will fill the knowledge gaps regarding the impact of Leu on fish intestinal barrier function.

PMC10003365

Fabiana Tortora,Evelina La Civita,Pankaj Trivedi,Ferdinando Febbraio,Daniela Terracciano,Amelia Cimmino

Emerging RNA-Based Therapeutic and Diagnostic Options: Recent Advances and Future Challenges in Genitourinary Cancers

27-02-2023

genitourinary cancer,renal cell carcinoma,bladder cancer,prostate cancer,long non-coding RNA,molecular biomarkers

Renal cell carcinoma, bladder cancer, and prostate cancer are the most widespread genitourinary tumors. Their treatment and diagnosis have significantly evolved over recent years, due to an increasing understanding of oncogenic factors and the molecular mechanisms involved. Using sophisticated genome sequencing technologies, the non-coding RNAs, such as microRNAs, long non-coding RNAs, and circular RNAs, have all been implicated in the occurrence and progression of genitourinary cancers. Interestingly, DNA, protein, and RNA interactions with lncRNAs and other biological macromolecules drive some of these cancer phenotypes. Studies on the molecular mechanisms of lncRNAs have identified new functional markers that could be potentially useful as biomarkers for effective diagnosis and/or as targets for therapeutic intervention. This review focuses on the mechanisms underlying abnormal lncRNA expression in genitourinary tumors and discusses their role in diagnostics, prognosis, and treatment.

Emerging RNA-Based Therapeutic and Diagnostic Options: Recent Advances and Future Challenges in Genitourinary Cancers Renal cell carcinoma, bladder cancer, and prostate cancer are the most widespread genitourinary tumors. Their treatment and diagnosis have significantly evolved over recent years, due to an increasing understanding of oncogenic factors and the molecular mechanisms involved. Using sophisticated genome sequencing technologies, the non-coding RNAs, such as microRNAs, long non-coding RNAs, and circular RNAs, have all been implicated in the occurrence and progression of genitourinary cancers. Interestingly, DNA, protein, and RNA interactions with lncRNAs and other biological macromolecules drive some of these cancer phenotypes. Studies on the molecular mechanisms of lncRNAs have identified new functional markers that could be potentially useful as biomarkers for effective diagnosis and/or as targets for therapeutic intervention. This review focuses on the mechanisms underlying abnormal lncRNA expression in genitourinary tumors and discusses their role in diagnostics, prognosis, and treatment. The treatment of genitourinary cancers has received considerable attention in recent years. These tumors comprise a heterogeneous group that includes renal cell carcinoma (RCC), bladder cancer (BlCa), and prostate cancer (PCa) [1]. Different research strategies have been implemented to identify novel biomarkers for these tumors [2]. In facilitating an early and accurate diagnosis, biomarkers can be quite useful in improving clinical disease management and reducing the use of invasive diagnostic methods [1,2]. Furthermore, clinicians may be able to lessen side effects and cost by choosing the best treatment plan for patients exhibiting certain biomarkers [1]. In particular, the identification of specific targets/biomarkers has led to the most recent significant advancements in the development of immunotherapies, especially of immune checkpoint inhibitors or immunomodulatory agents of the tumor microenvironment [2]. Overall survival has risen with immunotherapy and this therapeutic approach also has reduced the onset of metastases in some patients and revolutionized management of malignant tumors in the genitourinary system [2]. Among the currently available immune checkpoints, the following two have often been targeted with corresponding antibodies: (1) PD-1, a receptor found on the surface of T lymphocytes that have been activated, as well as its ligand, PD-L1, which is expressed on antigen presenting/tumor cells, modulates T-cell activity, and inhibits the antitumor immune response; and (2) CTLA-4, which suppresses the immune response and is expressed by activated T cells [2]. For the treatment of urothelial carcinoma and RCC, which are classified as immunologically “hot” malignancies, a number of checkpoint inhibitors (CPI) have been approved [3]. RCCs have higher neoantigen loads and higher levels of tumor-infiltrating lymphocytes (TILs), which make these neoplasms more readily identifiable by the immune system and prompt an intense immunological response [3]. The intricacy of the tumor microenvironment influences T-cell activation against malignancies. However, it is generally known that only a small percentage of patients, even those with immunologically “hot” malignancies, respond to CPIs [3]. The varying reactions to various medicines can be partially explained by the molecular heterogeneity of malignancies. As part of the immunotherapeutic approach, new drugs are continuously being sought after which are specifically suited to a range of targets, such as tyrosine kinase inhibitors, mTOR inhibitors, and new fusion proteins [4]. In this scenario, we also find the most recent data on non-coding RNAs. In particular, long non-coding RNAs (lncRNAs), transcribed throughout the human genome, have been revealed as novel markers using advanced genome sequencing technologies. LncRNAs, a class of RNA molecules with a length of more than 200 nucleotides, are crucial for the emergence and growth of malignancies. In particular, regulation of cell migration, invasion, the cell cycle, epithelial-mesenchymal transition (EMT), DNA damage, and drug resistance are greatly influenced by lncRNAs [4]. Drug discovery is advancing quickly right now and there are several ongoing preclinical investigations and promising clinical trials. This review focuses on the use of lncRNAs as biomarkers for cancer diagnosis and/or prognosis, as well as development of novel therapeutics, which are predicted to continue to improve outcomes in patients with genitourinary malignancies. RCC is the most widespread kidney malignancy in adults, accounting for 3.7% of all tumors in the world. This tumor is also the main cause of cancer-related morbidity and mortality worldwide [5]. The most prevalent subtype of RCC is clear cell renal cell carcinoma (ccRCC), and comprehending the molecular changes associated with malignant transformation is crucial to achieving longer survival [6]. Currently, RCC treatment and diagnostic methods are few and mostly restricted to advanced disease stages. There is an increasing need to include new prognostic and predictive biomarkers, which can also serve as therapeutic targets, because practically all subtypes of RCC are resistant to chemotherapy and radiotherapy [7]. The connection between lncRNAs and RCC has recently received attention, and certain significant lncRNA molecules have been identified as biological markers and therapeutic targets. In particular, lncRNAs contribute to cancer phenotypes by interacting with proteins, DNA, and RNA [7]. Recent research on the molecular mechanisms of lncRNAs has clarified their function in the development of malignant tumors, making them suitable targets for cancer treatment and detection. Several cancer phenotypes are the result of dysfunctions in intrinsic cellular regulatory networks and intercellular communications that are conducive to the tumor microenvironment [8,9]. An interesting example is the association between increased MALAT1 expression in the early diagnosis of lymph node metastases and poor survival in RCC patients [10,11]. In ccRCC, MALAT1 is overexpressed and plays an important role in regulating epithelial–mesenchymal transition (EMT) via its well-documented interaction with EZH2 [12]. Furthermore, miRNAs, the small, single-stranded, 18–25-nucleotides-long cellular RNAs that do not code for proteins and are evolutionarily highly conserved, play a relevant role in carcinogenesis. They contribute to cancer development by controlling cell growth, proliferation, angiogenesis, invasion, and migration and function as either oncogenic or suppressor miRs [13]. Thus, the differential expression of miRNAs can serve as a key marker for the diagnosis and prognosis of tumors as well as a possible therapeutic target. It has been demonstrated that lncRNAs function as “molecular sponges” for miRNAs to prevent their “silencing impact” on target miRNAs [13]. MALAT1 has also been demonstrated to promote EMT in ccRCC cells by functioning as a competing endogenous RNA (ceRNA) and preventing miRNA-mediated degradation of the transcript-encoding zinc finger E box binding homeobox 2 (ZEB2), a transcriptional regulator of E-cadherin [14]. Regarding the mechanisms that control transcription, it was found that the HIF pathway is required for transcription factor FOS to upregulate MALAT1 in ccRCC [12]. Additional research revealed that shorter survival and bad clinicopathological characteristics were linked to increased lncRNA ZFAS1 expression. Furthermore, ZFAS1 knockdown inhibited migration, invasion, and proliferation of ccRCC cells [15]. Compared to nearby non-tumor tissues, it was discovered that the expression of lncRNA ZFAS1 in ccRCC was considerably elevated. It appeared that ZFAS1 was consistently expressed at higher levels in ccRCC tumor cell lines than in the normal renal tubular epithelial cell line [16]. According to these findings, ZFAS1 acts as an oncogene in ccRCC. In particular, the interactions between ZFAS1 and miR-10a have been validated by luciferase reporter assay and RNA immunoprecipitation (RIP) assay [15]. MiR-10a silencing could attenuate the ability of ZFAS1 to promote ccRCC cell proliferation and metastasis. Subsequently, it was validated that SKA1, as a key downstream target protein for miR-10a, is responsible for the biological role of ZFAS1. ZFAS1 positively regulates SKA1 expression via miR-10a sponging. Through targeting the miR-10a/SKA1 pathway, ZFAS1 knockdown was shown to decrease the growth and metastasis of ccRCC in biological tests, suggesting that it may provide a new therapeutic target or biomarker for the disease [15]. Akin to MALAT1 above, lncRNA CYTOR was found to be upregulated while miR-136-5p was found to be downregulated in RCC cell lines and tissues [16]. CYTOR inhibition attenuated cell proliferation and invasion while promoting apoptosis. The lncRNA CYTOR sponged miR-136-5p, which negatively regulated RCC development. MiR-136-5p targets MAT2B. The corresponding MAT2B protein interacts directly with BAG3 protein to influence RCC cell proliferation, invasion, and apoptosis. In vivo experiments revealed that CYTOR knockdown increased miR-136-5p expression while decreasing MAT2B expression, thus preventing the development of RCC [16]. Several studies have concurred that CYTOR plays a crucial regulatory role in the initiation and growth of malignant tumors [17,18,19]. Compared to the control group, it was discovered that the expression of lncRNA CYTOR was raised in kidney tumor tissues and cells. Based on these findings, it has been suggested that lncRNA CYTOR may enhance RCC cell proliferation [16]. Previous studies have demonstrated that miR-136-5p participates in a number of physiological and pathological processes, including cell proliferation, differentiation, and apoptosis in a variety of malignancies, and it may help to inhibit cell growth [20,21,22]. These investigations demonstrated that RCC tissues and cells had lower miR-136-5p expression than the controls. Additionally, miR-136-5p binding to CYTOR was confirmed, and bioinformatics prediction software indicated target genes of lncRNA CYTOR. A functional experiment was carried out to learn more about the regulation of kidney cancer by the interaction of lncRNA CYTOR and miR-136-5p [16]. In particular, the results showed that lncRNA CYTOR knockdown inhibited renal cancer progression and could be reversed by miR-136-5p. These findings implied that CYTOR controlled miR-136-5p to affect the development of kidney carcinoma. Indeed, as mentioned earlier, by influencing the miR-136-5-p/MAT2B/BAG3 axis, CYTOR may contribute to kidney cancer [16]. According to one study, the CYTOR/miR-3679-5p/MACC1 axis may play a critical role in the development of CRC and carcinogenesis [23]. In addition, several studies have shown that lncRNAs ROR, UCA1, and MALAT1 may influence the growth of RCC cells differently. ROR promoted the progression of RCC cells through the miR-206/VEGF axis [24]; UCA1 influenced RCC cell growth through the miR-182-5p/DLL4 axis [25]; and MALAT1 sped up the development and progression of RCC cells by upregulating BIRC5 and decreasing miR-203 expression [26]. It has been shown that stimulation of the HIF1 pathway causes the production of H19, a lncRNA from a cluster of maternally imprinted genes on chromosome 11, in glioblastoma cell lines [27]. This discovery sparked a lot of curiosity to better understand how H19 functions in ccRCC and how the HIF pathway is upregulated. Compared to healthy kidney tissue, H19 was found to be more highly expressed in ccRCC [28]. H19 may also function in ccRCC cells as a ceRNA to prevent degradation of E2F1, a transcription factor that promotes cell proliferation [29]. Further research into several solid tumors revealed that H19 indeed interacted with a variety of transcriptional regulators and promoted the expression of genes related to EMT [30], thus highlighting H19 as a viable therapeutic target for cancer. In contrast to healthy kidney cells, ccRCC cells have notable overexpression of lncRNA HOTAIR, which is also linked to ccRCC progression [31]. As suggested by a recent study on the human HOX transcriptome [32], the carcinogenic potential of HOTAIR might depend on its interaction with PRC2 subunits, which mediates epigenetic reprogramming. It has also been noted that HOTAIR may also affect other oncogenic pathways in ccRCC. In this context, it is intriguing that levels of insulin-like growth factor-binding protein 2 (IGFBP2), a protein that promotes proliferation, have been related to an increase in HOTAIR overexpression [33]. It is noteworthy that HOTAIR might function as a ceRNA to promote HIF1 expression in ccRCC cell lines [34]. Additionally, it has been shown that estrogen receptor (ER) is a prospective therapeutic target since it positively regulates HOTAIR expression in ccRCC [35]. The lncRNAs TCL6, NBAT-1, SPRY4-IT1, RCCRT1, GAS5, and CADM1-AS1 have all been associated with poor prognosis in patients with RCC [36,37,38,39,40] (Table 1, Figure 1). Approximately 15–20% of all renal malignancies are kidney renal papillary cell carcinomas (KIRP), and patients have a dismal prognosis. Treatment of KIRP is a significant clinical challenge because of its advanced stage at diagnosis and grim outcome [41]. Ferroptosis plays a role in pathological cell death in degenerative illnesses, in overcoming cancer cell resistance to chemotherapy, and in enhancing the clearance of faulty cells [42,43]. As an alternate treatment for cancer, ferroptosis provides a potential function as a tumor suppressor [44]. However, its impact on KIRP production through lncRNA regulation is unclear. As a result, co-expression analysis was used to investigate the connections between ferroptosis-related gene expression and lncRNAs. Numerous lncRNAs have been linked to ferroptosis-related genes in KIRP [45]. Ferroptosis-related lncRNAs were split into high- and low-risk groups based on the risk score in order to examine their potential roles in KIRP. Prognosis-related lncRNA data were used to determine the confidence interval and hazard ratio [45]. Eight ferroptosis-related lncRNAs were discovered, which differed in expression between high- and low-risk patients and were associated with prognosis [45]. It was revealed that some lncRNAs were overexpressed in high-risk patients whereas others were overexpressed in low-risk cases (p < 0.05) [45]. The prognosis of patients with low-risk lncRNAs was better than that of patients with high-risk lncRNAs [45]. The lncRNAs CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were overexpressed in high-risk patients, suggesting that they can be considered cancer-promoting markers implicated in malignancy processes in KIRP patients. Recent years have seen the discovery of new regulators of ferroptosis, including the P53, ATF3/4, SLC7A11, ACSL4, and BECN1 pathways. LncRNAs are connected to controlling the expression of these factors [46]. By altering the P53 signaling pathway, ferroptosis-related lncRNAs have been found to affect the migration and proliferation of KIRP cells. A ferroptosis-related lncRNA prognostic model revealed that the low-risk subtype had a greater survival rate than the high-risk subtype. The idea has been used in a range of clinical contexts. These findings suggested that ferroptosis-related lncRNAs are vital biomarkers in predicting survival outcomes for KIRP patients [46]. As an anticancer therapy, a great opportunity is provided by the expansion of RNA-targeted treatments to modulate lncRNAs. Different lncRNA-targeting therapeutic methods are under investigation and many pharmaceutical companies are intensively working on developing lncRNA-targeted treatments [47,48]. Numerous studies have also demonstrated that the screening of suitable strategies for a notable modulation of lncRNAs depends critically on their cellular location [49]. While antisense oligonucleotides (ASOs) can deplete lncRNAs regardless of their location, small interfering RNAs (SiRNAs) can significantly decrease levels of cytoplasmic lncRNAs. LncRNA-targeting therapeutics can currently use ASOs [48]. Up to 549,393 new cases of bladder cancer were reported worldwide in 2018 [50], making it a major cause of mortality globally. Both non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), which have different molecular patterns, are subtypes of bladder cancer. BlCa has a variable 5-year overall survival rate, ranging from 23% to 48% [51]. Currently, cystoscopy is the top diagnostic tool used for BlCa detection since carcinoma in situ is difficult to detect. In addition, the technique is invasive and occasional false negatives make matters worse [52]. Therefore, a number of screening tools, including computed tomography and radiographic imaging of the upper urinary tract, are necessary for the diagnosis of bladder cancer [53]. Patients with BlCa frequently have surgery, chemotherapy, radiation, and immunotherapy, but their prognosis remains poor and the 5-year overall survival rate is low [54,55]. Moreover, the combination of conventional chemotherapy and surgery is insufficient for the treatment of BlCa once the cancer has reached a locally advanced or metastatic stage. According to statistical data, the response rate to new immunotherapy with the use of immune checkpoint inhibitors (ICI) is 30% or less [56]. Due to the limitations in BlCa treatments, new therapeutic targets are needed to improve the patient survival time. Due to a combination of the above mentioned factors, classifying the risk of BlCa patients and making accurate treatment decisions has been challenging for urologists [57]. Therefore, there is an urgent clinical need to find molecular biomarkers for BlCa via molecular profiling. The high frequency of genetic alterations is one of the crucial factors in the context of BlCa. One of the most frequent mutations observed in over 70% BICa patients is in the gene encoding telomerase reverse transcriptase (TERT) [58,59,60,61]. It is thus imperative to pinpoint the chemical elements contributing to the development of BlCa. Several studies have focused on identifying the causes of BlCa progression and therapeutically addressing them. Many molecular pathways are affected in BICs and their functional restoration could pave the way for an effective eradication of this tumor [62,63,64,65]. Indeed, several countries have initiated BICa genetic profiling. For instance, P53, Bcl-2, Bax, BMI1, and CD44 are among the variables that exhibited aberrant expression in Iranian patients with BlCa [66]. Such investigations are crucial for developing precision medicine-based therapies. Genetic and epigenetic mechanisms also control BlCa cell migration, proliferation, and treatment response. Non-coding RNAs (ncRNAs) have attracted considerable attention as epigenetic regulators of BlCa development [67]. Since it is known that ncRNAs can control a variety of biological processes [68,69], it follows that they have a significant impact on the growth, migration, and therapeutic response of BlCa [70,71]. The first consideration of lncRNA functions in BlCa may be connected to growth and viability. It has been shown that colon cancer-associated transcript 1 lncRNA (CCAT1) is overexpressed in BlCa and has favorable correlations with cancer stage, size, and grade. Targeting the lncRNA CCAT1 may offer a new tool for BlCa therapy [72]. The conversion of BlCa cell metabolism to aerobic glycolysis is a well-known method by which cells multiply more quickly [73]. Thus, the discovery of the mechanisms underlying the metabolic reprogramming of BlCa cells may open the door to therapeutic intervention. According to many reports, the development of BlCa correlated with the induction of aerobic glycolysis and upregulation of hypoxia-inducible factor-1α (HIF-1α) and β-arrestin 1 proteins [74,75]. Clinical investigation also demonstrated a link between enhanced glycolysis and worse outcomes for BlCa patients. LncRNAs are thought to control glycolysis in BlCa. As BlCa progresses, lncRNA SLC16A1-AS1 can promote glycolysis and mitochondrial respiration by increasing ATP generation. Therefore, lncRNA SLC16A1-AS1 promotes BlCa proliferation by increasing β-oxidation of fatty acids [76]. Targeting these lncRNAs could inhibit aerobic glycolysis in BlCa cells and thus impair their proliferation. Apoptosis is another feature of BlCa cells that lncRNAs can control. An example of how lncRNAs negatively regulate apoptosis in BICa is provided by SNHG7. The latter is highly expressed in BICa. Once its expression is suppressed by siRNAs, apoptosis ensues [77]. Another lncRNA, ZEB2-AS1, promotes BlCa cell proliferation and inhibits apoptosis [78]. LncRNAs are also known to control the cell cycle progression of cancer cells through cyclin-dependent kinase 9 (CDK9). Indeed, reduced expression of CDK9 leads to cell cycle arrest and apoptosis [79]. Through the overexpression of CDK9, lncRNA GAS6-AS2 encourages the proliferation and viability of BlCa cells. In contrast, cell cycle arrest at the G1 phase has been linked to the silencing of GAS6-AS2, which downregulates CDK9 expression [80]. CDK1 is another modulator of the cell cycle. The progression of BlCa cells is hampered when CDK1 is downregulated by tristetraprolin [81]. In addition, licochalcone B induces cell cycle arrest in BlCa cells by inhibiting CDK1 [82]. It was discovered that lncRNA PVT1 increased the viability and proliferation of BlCa cells by upregulating CDK1 [83]. Moreover, lncRNAs are associated with the stemness of BlCa cells. In the initial stage, NCK1-AS1 promoted BlCa development and was linked to an increase in the abundance of CD133+ stem cells [84]. Since lncRNAs regulate cell cycle progression, apoptosis, and stemness, targeting them may result in decreased viability and survival rates for BlCa cells. Studies on extracellular vesicles (EVs) [85,86] have shown that these tiny structures, which are enclosed by a lipid bilayer membrane, play crucial roles in biological processes depending on the load they carry, which can include lipids, proteins, or nucleic acids [87,88,89,90,91]. Through exocytosis, exosomes are secreted into the extracellular milieu and are thought to play a role in cell-cell communication [92]. Exosomes have been shown to transport lncRNAs between cells, which can affect tumor cell growth, invasion, and treatment resistance [93]. Studies have concentrated on the function of exosomes in the transport of lncRNAs and the connection to BlCa. It has been demonstrated that exosomal release of the lncRNA PTENP1 causes apoptosis in BlCa cells and inhibits its development. Moreover, PTENP1-containing exosomes are released from normal cells to deliver this antitumor factor to BlCa cells [93]. Numerous studies have demonstrated the important role played by immune-related long noncoding RNAs (IRLs) in the tumor microenvironment (TME) [94]. Many cancers have a higher risk associated with gene polymorphisms in lncRNAs [95,96]. A signature consisting of four lncRNAs (HCP5, IPO5P1, LINC00942, and LINC01356), all of which were discovered for the first time in bladder cancer, was established. Compared to the typical clinical features of BlCa patients, the IRL signature had a strong predictive ability for overall survival (OS) [97]. Surprisingly, the TME immune cell infiltration and ICI therapy response had a strong association with the IRL signature. Therefore, in comparison with earlier data, this novel IRL signature seems to have a superior role in predicting patient prognosis and the effectiveness of ICI immunotherapy [97]. Reducing cell proliferation and invasion may not be sufficient for a recovery from BlCa. It has recently been demonstrated that BlCa cells can become resistant to therapy by activating tumor-promoting factors such Akt, autophagy, and integrin 8 [98,99,100]. This calls for new therapeutic strategies designed to minimize drug resistance. Indeed, the evolution of resistance makes cisplatin (CP) treatment ineffective for treating BlCa patients. It is hypothesized that the lncRNA MEG3 enhances CP cytotoxicity against BlCa cells. MEG3 reduces the expression of matrix metalloproteinase-2 (MMP2) and MMP9 in BlCa cells, which lowers their ability to invade. It appears that upregulating P53 and boosting the production of pro-apoptotic proteins such as Bax and caspase-3 are two ways through which MEG3 could make BlCa cells more susceptible to CP-mediated apoptosis. Additionally, MEG3 inhibits Bcl-2 expression to cause cell death [101]. The lncRNA DLEU1, on the other hand, acts in a reverse manner and promotes BlCa cell migration and proliferation. DLEU1 is highly expressed in BlCa and associated with poor prognosis. By blocking miRNA-99b, DLEU1 mechanically increases HS3ST3B1 expression and causes CP resistance [102]. LncRNAs can control P53, which in turn affects how CP affects BlCa cells. By inhibiting acetylation, sirtuin 3 (SIRT3) can decrease P53 expression [103]. An increase in the expression of lncRNA MST1P2 leads to CP resistance. MST1P2 inhibits miRNA-133b to increase SIRT3 expression, which in turn downregulates P53 and contributes to drug resistance [104]. The lncRNA UCA1 stimulates the production of Wnt6, which is also closely related to CP resistance. UCA1 silencing leads to inactivation of Wnt signaling and consequently to suppression of CP drug resistance [105]. Interestingly, UCA1 can make BlCa cells resistant to both CP and gemcitabine [106]. H19 is another key lncRNA that is overexpressed in BlCa [107,108,109] through the induction of EMT by multiple mechanisms. Interactions with transcriptional regulatory complexes are necessary for one of these mechanisms. For instance, H19 binds to the EZH2 subunit of PRC2, which promotes WNT-β-catenin pathway activation and consequently the EMT [30,110]. Additionally, it has been shown that H19 functions as a ceRNA to prevent miRNAs from degrading the essential transcriptional regulator DNA (cytosine-5)-methyltransferase 3B (DNMT3B), which is connected to the development of EMT in cancer [111]. It is interesting to note that the expression of H19 in BlCa is increased by the EMT protein YAP1 [112]. As mentioned earlier, the expression of MALAT1, an important epigenetic regulator implicated in oncogenic pathways in a range of tumor types, is dysregulated in bladder cancer. The TGF pathway [113], which promotes the activation of transcriptional programs that support EMT, also seems to include MALAT1 as a downstream target. The EZH2-mediated transcriptional regulation found in prostate cancer [114] and ccRCC [11,14] appears to be different from this mechanism. By directly interacting with the PRC2 protein SUZ12, MALAT1 functions as a transcriptional regulator in the context of bladder cancer [115]. By boosting the expression of transcription factors ZEB1, ZEB2, and zinc finger protein SNAI2, which promote EMT, MALAT1 is specifically conducive to EMT [116]. Overall, lncRNAs can influence miRNA expression directly or indirectly. LncRNAs directly lower miRNA expression through sponging. Indirectly, they alter the level of expression of miRNAs by attracting other factors, such as EZH2, to act as their promoters [68,117,118]. To increase the expression of miRNA-196a-5p in BlCa cells, lncRNA UCA1 employs CREB as a transcription factor for the miRNA-196a-5p promoter. Consequently, UCA1 confers resistance to cisplatin/gemcitabine in bladder cancer cells by activating miR-196a-5p via CREB [106]. Additionally, the lncRNA containing uc.8+, which is a member of the class of lncRNAs known as transcribed ultraconserved regions (T-UCRs), is the most upregulated T-UCR in BlCa [119]. Specifically, a previous qPCR-based expression analysis [120] conducted on RNA isolated from BlCa biopsies (n = 40) [121] revealed that uc.8+ levels correlated with both grading (i.e., cell differentiation) and staging (i.e., tumor invasiveness), although its expression was lower than in precancerous bladder tissues [122]. It is intriguing to note that in contrast to other malignancies, a number of lncRNAs may potentially have special functions in bladder cancer. For example, XIST has been characterized as a tumor suppressor in prostate cancer, but it functions as a ceRNA in bladder cancer and increases AR signaling, an important pathway in tumor development and drug resistance [123]. Fluorescence microscopy data for BlCa cell line J82 showed that uc.8+ was a natural decoy for miR-596, thus the upregulation of uc.8+ caused MMP9 to be expressed more frequently, which increased the ability of bladder cancer cells to invade other tissues (Table 2, Figure 2). Since BlCa patients have a poor prognosis, lncRNA targeting can be viewed as a potentially successful treatment option [124]. Furthermore, these patients frequently experience chemotherapeutic failure. Synergistic therapy can be achieved by combining genetic tools and anticancer agents. Notably, erdafitinib was the first targeted treatment for metastatic bladder cancer to receive approval [125]. The FDA recently approved the use of combination therapies using ICI and targeted drugs, such as pembrolizumab or avelumab with axitinib, because they have been proven to be efficient and safe [126]. Interestingly, there is no evidence linking lncRNAs to the response of BlCa cells to radiotherapy. Studies are needed to identify the lncRNAs involved in radiotherapy resistance or sensitivity because it is a key component of BlCa therapy. As previously mentioned, exosomes can contain lncRNAs in BlCa and may affect the development of BlCa by transferring ncRNAs. The role of exosomal lncRNAs in BlCa development needs more research as well. Finally, a better understanding of the interaction between lncRNAs and MMP and the effects on BlCa cell migration and invasion would be beneficial to design novel therapies. Pca is the second most frequent cancer among older men, which also rates as the second leading cause of cancer-related mortality [5]. The incidence and death due to this tumor have significantly increased over the past ten years due to changes in aging, lifestyle, and the environment [127]. Patients who undergo close monitoring and endocrine therapy at a very early stage might retain a generally favorable prognosis within 5 years; however, in many patients, it is detected at middle or late stages due to hidden symptoms [128,129,130]. Currently, in accordance with the conventional mechanism of the androgen receptor (AR) signaling pathway, androgen deprivation therapy (ADT) is the first-line systemic treatment for advanced PCa [131]. However, it has been found that the innate cellular diversity in PCa can eventually adapt to ADT. Castration-resistant prostate cancer (CRPC) is a severe condition that can develop as a result of this activation of AR signals, even at low blood androgen levels [132,133]. Serum testosterone values less than 50 ng/mL or 1.7 nmol/L, along with biochemical or radiographic progression, make up the diagnostic criteria used to prognosticate CRPC [134]. According to the guidelines of the Response Evaluation Criteria in Solid Tumors, the presence of more than two new lesions found during an imaging survey is specifically referred to as radiological progression (RECIST) [135]. After initial PCa treatment, the prevalence of CRPC is estimated to be 10–20% within 5 years of follow-up, with metastatic CRPC (mCRPC) representing 84% of all cases. Furthermore, 33% of non-metastatic CRPC cases will develop metastases within 2 years of follow-up [136]. The median PCa-specific survival in mCRPC only increases by 2.8 to 4.8 months since the mechanism of CRPC is highly complex and changeable [137,138,139,140,141,142,143]. This is true even with novel medications continually being proposed and employed. The main mechanism of CRPC is believed to be the persistent activation of AR signaling in cancer cells, even in the presence of ADT [144]. Nevertheless, the majority of CRPC cases are dependent on AR signaling because it occurs via a number of additional routes. These mechanisms can include AR point mutations, increased AR expression, altered intratumoral androgen biosynthesis, emergence of AR splice variants, as well as cofactor activity modulations [145]. Abiraterone, apalutamide, and enzalutamide are examples of more potent AR signaling inhibitors (ARSI) that are acknowledged as first-line therapeutic alternatives in CRPC [146]. However, not all castration resistance is dependent on AR signaling because of the tumor’s variety, heterogeneity, and flexibility. Further resistance to ARSI may result from tumor cells switching from AR-dependent to AR-independent signaling pathways [147,148]. It has been established that ncRNAs, which participate in a variety of molecular regulatory activities, including signal transduction, post-transcriptional regulation, post-translational regulation, and epigenetic regulation, are an essential molecular component in many of the pathologic mechanisms underlying CRPC [149,150,151]. The two ncRNA categories that are most frequently studied in CRPC research are miRNAs and lncRNAs, both of which have been shown to be involved in a variety of patho-physiologic pathways [150,151]. The first function of miRNAs in CPRC was shown to be regulatory. CPRC has been linked to the formation of at least 20 different types of miRNAs, which take part in a variety of pathogenic pathways, such as AR-related cell proliferation, cancer cell survival, apoptosis, or EMT [149]. On the other hand, because of advancements in detection technology over the past ten years, the connection between CPRC and lncRNAs, as larger and more complex ncRNAs, has been steadily investigated [150]. A single type of lncRNA can also be regulated by many pathways due to the fact that lncRNAs contain more information and have a stronger affinity for biomolecules in the human body. As a result, lncRNAs play important regulatory roles in the development of PCa from an androgen-dependent state to CRPC [152]. For instance, the AR protein may upregulate AR-regulated long noncoding RNA 1 (ARLNC1), which then stabilizes the AR transcript by RNA-RNA interaction [153]. In vitro and in vivo AR-dependent PCa cell growth was inhibited by ARLNC1 knockdown, which also resulted in decreased AR expression [152]. Prostate cancer-associated long-noncoding RNA 1 (PRNCR1) and PCa gene expression marker 1 (PCGEM1) are highly expressed in CRPC and known to be involved in the AR signaling pathway; however, knockdown of either PRNCR1 or PCGEM1 inhibited the growth of CRPC cells in vivo [154,155,156]. Interactions with miRNAs provide another method via which lncRNAs can affect AR. Growing evidence suggests that the interaction patterns between lncRNAs and miRNAs are strongly linked with the development of cancers [157,158]. It has been demonstrated that they interact in a variety of ways, including the most popular “sponge” effect [159,160]. Over the past five years, several studies have outlined regulation mechanisms and interactions between lncRNAs and miRNAs in several CRPC pathogenic pathways [161]. The critical role of tyrosine kinase receptors (RTKs) has also been defined, as well as how activation of the downstream signaling cascade can give rise to the changing phenotypic and molecular landscape of metastatic CRPC [161]. Liu et al. assessed the expression of lncRNA AFAP1-AS1 in castration-resistant C4-2, PC3, and DU145 cell lines, discovering that their expression was considerably higher than in androgen-sensitive LNCaP cells. To suppress IGF1R, AFAP1-AS1 binds to miR-15b and interferes with its tumor suppressor function [162]. According to Huang et al., lncRNA PTTG3P levels were noticeably higher in CRPC tissues and castration-resistant cell lines. By competing for miR-146a-3p, PTTG3P may enhance PTTG1 expression [163]. SChLAP1, another lncRNA, is significantly highly expressed in PCa and is intimately associated with tumor development. SChLAP1 has the potential to suppress the expression of miR-198, which is specifically correlated with the 3′ UTR of MAPK1. The principal target genes of miR-198, including ELK-1, F-actin, and PAK1, are associated with the advancement of cancer [164] and miR-198 suppression greatly enhanced the expression of MAPK1. The lncRNA Linc00963 was shown to be upregulated in C4-2 cells, as opposed to LNCaP cells, highlighting its function in the change from androgen-dependent PCa to androgen-independent CRPC [165]. Linc00963 is directly attached to miR-655 in CRPC cells, and prevents it from interacting with TRIM24 mRNA. This promotes cell proliferation by increasing TRIM24 [166]. In advanced CRPC, TRIM24 is a well-known oncogene [167]. The activation of AR by TRIM24 expression via the PI3K/AKT pathway may aid in the prevention of CRPC. Additionally, it was shown that TRIM24 controls the transcription of the EGFR and PIK3CA genes, and that PIK3CA and EGFR work in synergy to activate the PI3K/AKT pathway in PCa [167]. The lncRNA SNHG7 is overexpressed in PCa tissue and cell lines and strongly associated with poor prognosis. Its knockdown reduced critical cell cycle regulators, such as cyclin D, CDK4, and CDK6. Both in vivo and in vitro studies have shown cell cycle arrest in the G0/G1 phase following SNHG7 silencing [168]. Furthermore, it was discovered that miR-503 had complementary binding sites within the 3′UTRs of both SNHG7 and cyclin D. Thus, miR-503 mimic transfection has been shown to reduce cyclin D and SNHG7 miRNA expression and inhibit tumor growth [168]. The PCa cell’s cytoplasm is home to lncRNA LOXL1-AS1, which acts as a miRNA sponge to interact with miR-541-3p [168]. By interacting with the 3′UTR of cyclin D, this miRNA suppresses its expression and causes G0/G1 phase cell cycle arrest. Genes highly enriched in nuclear division and cell cycle checkpoints were upregulated by LOXL1-AS1 induction. Through modifying the expression of miR-541-3p and subsequently cyclin D, LOXL1-AS1 controlled cell cycle progression [169]. In PCa, lncRNAs can also control apoptosis. An apoptosis-related mechanism involving toll-like receptor (TLR) is induced in the TME [170]. The activation of TLR signaling pathway accelerates PCa progression [171]. The lncRNA PART1 can activate TLR signaling and its downstream targets, such as TLR3, TNFSF10, and CXCL13, to suppress PCa cell death. PCa growth and apoptotic induction are both reduced when PART1 is silenced [172]. Similarly, by decreasing the expression of miRNA-15a-5p, the lncRNA PVT1 encourages KIF23 expression to inhibit apoptosis in PCa cells. Indeed, apoptosis induction and PVT1 knockdown have been shown to be linked [173]. Metastasis, which occurs when cancer cells migrate to distant organs, such the lung, liver, bone, and lymph nodes, is a major cause of PCa-related mortality [174]. Bone metastasis, the most frequent side effect of PCa, is consequently linked to osteoblastic and osteolytic diseases [175]. Therefore, it is essential to pinpoint the causes of PCa metastases in order to effectively treat this dangerous condition. Molecular pathways linked to metastasis can also be thought of as prognostic biomarkers [176,177]. The NDRG1 gene, the downregulation of which increases migration, is one of the molecular processes involved in controlling PCa metastases [178]. As a tumor suppressor factor, the lncRNA LINC00844 is downregulated in metastatic PCa and is linked to poor prognosis. In order to promote NDRG1 expression and prevent PCa cell migration and invasion, LINC00844 mechanically mediates the binding of AR to chromatin [179]. C-X-C chemokine receptor type 4 (CXCR-4) is another component that contributes to PCa bone metastases [180,181]. CXCR4 is overexpressed in many cancers and hence responsible for their aggressive behavior [182,183,184,185]. Its overexpression in PCa causes lymph node and bone metastases and is linked to poor prognosis [186]. The lncRNA UCA1 can control CXCR4 expression in PCa to influence tumor development. The former stimulates the production of the latter to increase metastasis of PCa by sponging miRNA-204 [187]. Overall, lncRNAs have been shown to be important regulators of PCa metastasis, and more work is ongoing to identify other lncRNAs involved in facilitating PCa cell migration and invasion [188,189]. Indeed, the lncRNA ATB is a tumor-promoting factor that promotes PCa cell proliferation and invasion, and its overexpression is associated with poor prognosis [190]. Because lncRNAs can help PCa evade the immune system, their expression levels affect how well PCa responds to immunotherapy [191]. As expected, tumor-suppressor lncRNAs experience considerable downregulation, in contrast to tumor-promoting lncRNAs, which are highly expressed in PCa. The lncRNA TINCR has been linked to clinical T staging, lymph node change, and distant metastases in PCa. Because low TINCR expression indicates poor prognosis, it is crucial to include evaluation of its expression levels in clinical courses [192]. PCa patients with low expression of tumor suppressor lncRNA DGCR5 have a worse chance of survival [193]. As a result, identifying these lncRNAs and determining their degree of expression can be used as an effective and trustworthy predictive tool [194]. Additionally, the serum of PCa patients can be tested for expression levels of exosomal lncRNAs as a diagnostic and predictive tool [195]. However, lncRNAs in PCa can also be targeted with anticancer drugs. Since most antitumor agents in nature that target lncRNAs are phytochemicals and have poor bioavailability, approaches such as using drug delivery vehicles to increase potency should be taken into consideration [196]. A natural substance of plant origin called quercetin is frequently used in PCa therapy. The response of PCa cells to chemotherapy can be greatly enhanced by the ability of quercetin to inhibit cell migration and proliferation. Additionally, nanoparticles have been created for the release of quercetin to enhance its anticancer action against PCa [197]. It targets a number of lncRNAs. In a concentration- and time-dependent manner, quercetin lowers the expression level of MALAT1. In addition to the in vitro study, in vivo experiments with xenograft tumors demonstrated the effect of quercetin in preventing the spread of PCa. Through the regulation of EMT, quercetin prevented metastases by downregulating MALAT1. Quercetin negatively affects cell proliferation by inhibiting the PI3K/Akt pathway [198]. Another well-known naturally occuring anticancer substance is curcumin. It is derived from the rhizome and root of the Curcuma longa plant. Curcumin slows the growth of PCa by triggering apoptosis and cell cycle arrest by controlling NF-B signaling and preventing angiogenesis [199]. PCa stem cells are adversely affected by curcumin administration, which inhibits their migration and proliferation. The lncRNA ROR functions as a ceRNA to decrease miRNA-145, thus advancing PCa [200]. Interestingly, curcumin administration decreases ROR expression while increasing miRNA-145 expression and limits PCa cell proliferation [200] (Table 3, Figure 3). In conclusion, lncRNAs can control the growth and metastasis of PCa cells. Additionally, they can program cell death by modulating autophagy and apoptosis in PCa. LncRNAs have several downstream targets; STAT3, NF-B, PTEN, PI3K/Akt, and miRNAs being some of the most significant ones [201]. Generally, expression of tumor-promoting lncRNAs is increased in PCa and that of tumor-suppressor lncRNAs is decreased. In addition, lncRNAs can control how PCa cells react to chemotherapy and radiotherapy. Some lncRNAs are also responsible for chemoresistance to PTX and DOX. A reduction of such lncRNA may improve the effectiveness of anticancer chemotherapy [201]. Additionally, via modulating radio resistance, lncRNAs can encourage the suppression of autophagy. To assess their pro-survival and pro-death roles in PCa, the link between the two needs to be further studied. Cytotoxic T cells are essential for stopping the spread of PCa by activating antitumor immunity. Therefore, in order to increase the potential of immunotherapy lncRNAs with a positive influence on this T cell subset are urgently needed to be identified. Thus, lncRNAs seem to play a crucial role in PCa suppression, and pharmacological and genetic therapies are in the offing to target them. Furthermore, lncRNAs can also be employed as diagnostic and prognostic tools for PCa patients in clinical settings [201]. In order to pave the road for PCa treatment, future research will need to concentrate on identifying more lncRNAs implicated in the disease’s progression or suppression. Other genitourinary cancers include ovarian cancer (OC), one of the main common gynecological cancers. Globally, there were over 295,000 new OC cases in 2018, among which 184,000 were fatal [51]. Epithelial OC (EOC), which accounts for over 90% of cases, has four main histological subtypes: serous, endometrioid, clear cell, and mucinous. Their primary sites of origin are the fallopian tube and endometrium, with ovary involvement occurring secondarily [202]. However, the asymptomatic character of early-stage disease, different histological subtypes, and resistance to therapy continue to be significant contributors to poor prognosis and low 5-year overall survival rates (40%) [203,204]. Advanced OC (AOC) is defined as stage FIGO IIB to IV, where cancer cells have metastasized to the peritoneal cavity and exhibit resistance to first-line therapy. Stage I-IIA is restricted to the ovaries [205]. Cytoreductive surgery is the first step in treating OC, followed by platinum- and taxane-based chemotherapy. First-line treatments often work well for patients with e I–IIA stage OC. However, unfortunately, the disease returns in more than 85% of AOC patients who receive the standard treatment and achieve complete remission during the first two years, with a median survival of less than 24 months [203,206]. Recurrent OC (ROC) is characterized by a small number of OC cells that have undergone therapeutic stress and repopulate the site of origin or secondary metastatic locations. For OC patients, the poor prognosis of ROC remains a substantial management problem. Cancer stem cell (CSC) activity, invasion, and metastatic features, and treatment resistance are all linked to ROC progression [207]. Therefore, it is crucial to find novel therapeutic approaches and diagnostic/prognostic markers. Dysregulation of lncRNA is a significant factor in the early onset, development, spread, and chemoresistance of ROC [208,209,210]. The differential expression of H19, LSINCT5, XIST, CCAT2, HOTAIR, AB073614, and ANRIL is linked to oncogenic and invasive characteristics of OC cells [211,212,213]. More than 500 differentially expressed lncRNAs between original tumor cells and malignant OC cells from ascites have been reported [214]. Additionally, their variable levels after treating OC with carboplatin-docetaxel suggest a role in predicting medication response [215]. Targeting particular processes in OC progression has been made possible by the functional involvement of lncRNAs with various mechanisms of action, in particular with OC stages [216]. Cancer metastases and the stem-like characteristics of cancer cells are both directly related to EMT [217]. ROR, HOTAIR, H19, and UCA1 encourage EMT and control the proliferation of CSCs [218,219]. Having stem cell markers, including CD24, CD44, CD133, CD44v6, NESTIN, NANOG, and OCT3/4, that reflect self-renewal capabilities and propensity to spread, CSCs are crucial in predicting metastasis, chemoresistance, and relapse [220,221,222]. The biomarker Ca-125, also known as MUC16, is frequently evaluated in serum to assess the progression and response of OC to treatment [223]. However, its applicability in predicting the prognosis of OC patients is constrained by variability in Ca-125 expression levels in later stages of the disease and correlation with other clinical conditions. In precision medicine, liquid biopsy-based disease screening and detection methods have become more common [224]. Several techniques, including quantitative reverse transcription-polymerase chain reaction (qRT-PCR), fluorescent in situ hybridization (FISH), microarray hybridization, and gene profiling, have been used to evaluate the expression of lncRNAs involved in the proliferation, apoptosis, invasion, and migration of tumor cells [225]. The expression of ANRIL, HOTAIR, MALAT1, and UCA1 in OC cells was found to be histotype-specific and thus identifying them as potential detection/diagnostic biomarkers. Due to its higher expression in ROC relative to normal tissue, ANRIL has the potential to be employed as a biomarker to predict poor survival in patients with ROC [226]. The differential expression levels of circulating extracellular lncRNAs connected to bodily fluids, such as plasma/serum, may serve as biomarkers for routine clinical use to predict the prognosis, risk of tumor spread, and recurrence after surgery [227]. The capacity of circulating lncRNAs to withstand RNase makes them excellent biomarkers [227]. Therefore, the use of circulating lncRNAs as tumor biomarkers may be clinically beneficial because of their high sensitivity, specificity, and due to non-invasive mode of collection. It has been suggested that the circulating lncRNAs H19, HOTAIR, and MALAT1 in bodily fluids, such as plasma, may function as indicators of drug response, risk of tumor metastasis, and recurrence in OC patients after first-line therapy [227]. The upregulation of ANRIL, AB073614, CCAT2, HOTAIR, NEAT1, TC0101441, and UCA1 in primary samples was also positively correlated with poor prognosis for OC patients [228]. It has been proposed that C17orf91, also known as MIR22HG, can be employed as a predictive biomarker for OC patients due to its increased expression between primary and metastatic tumors [229]. Furthermore, since lower GAS5 expression indicates poor prognosis, growth-stop-specific 5 (GAS5), a tumor suppressor lncRNA in OC, may be useful for assessing the patient’s response to first-line therapy [230]. Increased lncRNA MEG3 expression inhibits proliferation and induces apoptosis by upregulating miRNA and expression of TP53, GDF15, and RB1. MEG3 has been reported to be suppressed by promoter hypermethylation in the majority of EOC tissues [231]. Increased SNHG15 expression has been shown to play a critical role in EOC migration, invasion, proliferation, and chemoresistance and has been linked to pathophysiology, ascites, and higher FIGO stage [232]. In EOC, a prognostic indicator and potential target are both possible due to the association between the high expression of SNHG15 and resistance to cisplatin [232]. These findings imply the potential utility of lncRNA expression profiles in screening, illness monitoring, and as prognostic indicators in OC [233]. Targeting lncRNAs for therapy may be a promising strategy because of their highly potent and particular functional importance in OC development. The following methods can be used to target them: (1) using siRNA or antisense oligonucleotides (ASO) with chemical modifications to degrade post-transcriptional RNA; (2) inducing loss of function by producing steric inhibition of RNA-protein interactions by ASO; (3) preventing interactions between lncRNAs and miRNAs using oligonucleotides; and (4) modifying lncRNA expression by promoting steric hindrance [233]. Great strides have been made in understanding the roles of lncRNAs in OC, but further studies are needed for their therapeutic applications. It is crucial to find the most therapeutically relevant candidates in ROC that have cancer-enriched or cancer-specific signatures and can predict or identify the early stages of disease. The development of lncRNA-based techniques can be greatly sped up by identifying the expression signatures and predicting target sites in silico utilizing reliable algorithms or bioinformatics tools [233]. The development of nanotechnology-based sensors and nanoscale delivery vehicles can improve the success of clinical translations of lncRNA-based techniques. It is suggested that future research should focus on developing cutting-edge nanoparticle-based methods to block their functions associated with drug resistance and spread in ROC. Although promising, the use of ASOs is currently limited by poor membrane permeability, which prevents nuclear lncRNA targeting [233]. Additionally, the stability and permeability of ASOs or other lncRNA targeting agents can be improved with nanoparticles, allowing them to reach the desired regions. In summary, more efforts are urgently needed to determine whether and how lncRNA-based technologies can be clinically useful in ROC [233]. Another genitourinary cancer is testicular germ cell tumor (TGCT), a common solid tumor in young men aged 20–40 and is the leading cause of death from solid tumors in men of this age. TGCT is classified into two types: seminoma and non-seminoma. The global incidence of TGCT is increasing [234,235], with 15–30% of patients experiencing recurrence and metastases, frequently associated with poor prognosis [236]. Researchers have discovered a range of increased gene expression in TGCT in recent years. BOB1 and prominin 1, two new germ cell markers, are upregulated in seminoma [237]. Cyclin D2 and N-Myc were overexpressed in rat spermatogonial cells by Houldworth et al. [238]. Cyclin D2 is a precursor to carcinoma and is crucial for the development of germ cell malignancies [239]. These findings show that TGCTs are associated with aberrant gene expression patterns and that different testicular tumor subtypes have distinct regulatory mechanisms for genes involved in processes such as proliferation, pluripotency, and epigenetics. More research is required to determine how these gene targets relate to the pathophysiology of TGCT. Identifying biomarkers for early diagnosis and therapy response prediction for TGCT is critical. LncRNAs could be of clinical use in this cancer as well because of their strong tissue and disease specificity [240,241]. RNA sequencing and high-throughput gene chip technology offer dependable ways to discover efficient lncRNA biomarkers. Yang et al. found that the MEG3 modulates TGCT progression through the PTEN/PI3K/AKT pathway [242]. Another study discovered that the expression of LNC00467 was strongly connected to the pathological grade and poor prognosis of TGCT, and that it might facilitate TGCT cell invasion and migration via controlling the expression of AKT3 and influencing AKT phosphorylation [243]. The selection of a suitable treatment technique is currently a significant problem in the study of testicular cancer [244]. Studies have indicated that classifying cancer patients according to their clinical features, such as molecular markers, stage, and grade, and choosing the right therapy can enhance patient prognosis and lessen side effects from surgery, radiation, and chemotherapy [245]. To direct TGCT treatment, it is crucial to extract detailed medical information from large-scale databases such as TCGA, high-throughput GEO, epidemiological, and prognostic databases. Testis-specific lncRNA RFPL3S expression profiling was used for the first time by Guo et al. to discriminate seminoma from non-seminoma and prognostically predict TGCT [243]. Elevated RFPL3S expression predicted longer disease-free and progression-free intervals in TGCT patients. Furthermore, both genetic (copy number variation) and epigenetic (DNA methylation) factors influenced RFPL3S expression, a tumor suppressor that significantly reduced TGCT cell invasion and proliferation in vitro. An essential barrier to stop tumor spread in tissue is the ECM. The primary components, fibronectin and laminin, are coupled to integrin receptors on the cell membrane, which regulate cell shape, differentiation, and migration [246]. Through a number of signaling pathways, focal adhesion kinase is crucial for the control of the cell cycle, growth, adhesion, cytoskeletal assembly, motility, and survival [247]. Focal adhesion kinase is widely expressed in a variety of tumor types and plays a critical role in the development, invasion, and metastasis of malignancies. It may emerge as a new target for tumor treatment [248]. In addition to its link with tumor cell growth and migration, higher RFPL3S expression has been found in patients who benefit and respond to immunotherapy. RFPL3S has been linked to the PI3K/AKT/mTOR, b-catenin/Wnt, and Hippo pathways, all of which are linked to immunotherapy [249,250,251,252,253,254,255]. These findings suggest that RFPL3S may be a reliable biomarker for predicting immunotherapy efficacy in TGCT patients. Furthermore, the vast majority of patients, including those with metastatic disease, have favorable prognosis or recovery after treatment since seminoma cells are typically particularly susceptible to platinum-based pharmacological therapies. However, some cisplatin (CDDP)-resistant cases have also been documented, typically with poor prognosis [256]. Several mechanisms have been proposed to explain the high sensitivity or resistance to CDDP [257,258]. One of these proposed mechanisms was the TDRG1 gene, which regulates the activity of the PI3K/Akt signaling pathway to regulate CDDP sensitivity [259]. The H19/miRNA-106b-5p/TDRG1 axis was confirmed in a CDDP-resistant environment and in homeostatic seminoma [259]. The “sponge” function of lncRNA H19 caused miRNA-106b-5p to be sequestered, which promoted TDRG1 production. Furthermore, the H19/miR-NA-106b-5p/NDRG1 axis was recently identified as a potential target for the treatment of seminoma and CDDP-resistant cancers [260]. LncRNAs have been found to play important roles in a variety of biological processes, including the pathogenesis of many complex human diseases, including cancer. Their detailed regulation mechanisms in cancer initiation and progression largely remain unknown. Currently, functions of only a few lncRNA have been identified. Here, we have attempted to summarize recent advances in understanding the mechanisms and functions of lncRNAs in genitourinary cancers. Specifically, we focused on the roles of newly identified lncRNAs as oncogenes and tumor suppressors, as well as the molecular pathways in which they are involved. We have also discussed their potential utility as biomarkers for the cancer diagnosis and prognosis. In conclusion, lncRNAs, like miRNAs, play crucial roles in cancer progression by regulating gene regulatory networks. In fact, in clinical diagnosis and treatment, they have emerged as important new players. Despite the fact that a lot is known about their functions, substantial challenges still remain to be tackled. To fully elucidate how these ncRNAs regulate gene expression, we will have to further investigate their functional motifs, secondary or tertiary structures, as well as the development of advanced bioinformatics methods to predict the target genes. Moreover, a better understanding of their role in gene regulation will provide new insights into cancer diagnosis and therapy and help to develop novel therapeutic strategies. RNA-based therapies represent a promising field that could provide great advantages in the treatment of aggressive cancers. In genitourinary cancers, particularly in prostate and renal cancers, some progress has been made. However translation of novel therapeutic approaches into routine clinical practice is far from satisfactory. If the outstanding success of mRNA-based vaccines, both in terms of efficacy and remarkable adaptability, in the management of the current SARS-CoV-2 pandemic [261] is anything to go by, we can anticipate new impetus and hope for RNA based therapies in cancer [262].

PMC10003366

Tong Gao,Xu Yang,Masayoshi Fujisawa,Toshiaki Ohara,Tianyi Wang,Nahoko Tomonobu,Masakiyo Sakaguchi,Teizo Yoshimura,Akihiro Matsukawa

SPRED2: A Novel Regulator of Epithelial-Mesenchymal Transition and Stemness in Hepatocellular Carcinoma Cells

05-03-2023

cancer stem cells,epithelial–mesenchymal transition,ERK1/2-MAPK,tumorigenesis

The downregulation of SPRED2, a negative regulator of the ERK1/2 pathway, was previously detected in human cancers; however, the biological consequence remains unknown. Here, we investigated the effects of SPRED2 loss on hepatocellular carcinoma (HCC) cell function. Human HCC cell lines, expressing various levels of SPRED2 and SPRED2 knockdown, increased ERK1/2 activation. SPRED2-knockout (KO)-HepG2 cells displayed an elongated spindle shape with increased cell migration/invasion and cadherin switching, with features of epithelial–mesenchymal transition (EMT). SPRED2-KO cells demonstrated a higher ability to form spheres and colonies, expressed higher levels of stemness markers and were more resistant to cisplatin. Interestingly, SPRED2-KO cells also expressed higher levels of the stem cell surface markers CD44 and CD90. When CD44+CD90+ and CD44−CD90− populations from WT cells were analyzed, a lower level of SPRED2 and higher levels of stem cell markers were detected in CD44+CD90+ cells. Further, endogenous SPRED2 expression decreased when WT cells were cultured in 3D, but was restored in 2D culture. Finally, the levels of SPRED2 in clinical HCC tissues were significantly lower than those in adjacent non-HCC tissues and were negatively associated with progression-free survival. Thus, the downregulation of SPRED2 in HCC promotes EMT and stemness through the activation of the ERK1/2 pathway, and leads to more malignant phenotypes.

SPRED2: A Novel Regulator of Epithelial-Mesenchymal Transition and Stemness in Hepatocellular Carcinoma Cells The downregulation of SPRED2, a negative regulator of the ERK1/2 pathway, was previously detected in human cancers; however, the biological consequence remains unknown. Here, we investigated the effects of SPRED2 loss on hepatocellular carcinoma (HCC) cell function. Human HCC cell lines, expressing various levels of SPRED2 and SPRED2 knockdown, increased ERK1/2 activation. SPRED2-knockout (KO)-HepG2 cells displayed an elongated spindle shape with increased cell migration/invasion and cadherin switching, with features of epithelial–mesenchymal transition (EMT). SPRED2-KO cells demonstrated a higher ability to form spheres and colonies, expressed higher levels of stemness markers and were more resistant to cisplatin. Interestingly, SPRED2-KO cells also expressed higher levels of the stem cell surface markers CD44 and CD90. When CD44+CD90+ and CD44−CD90− populations from WT cells were analyzed, a lower level of SPRED2 and higher levels of stem cell markers were detected in CD44+CD90+ cells. Further, endogenous SPRED2 expression decreased when WT cells were cultured in 3D, but was restored in 2D culture. Finally, the levels of SPRED2 in clinical HCC tissues were significantly lower than those in adjacent non-HCC tissues and were negatively associated with progression-free survival. Thus, the downregulation of SPRED2 in HCC promotes EMT and stemness through the activation of the ERK1/2 pathway, and leads to more malignant phenotypes. Liver cancer ranks 6th in incidence and 4th in mortality worldwide [1]. Although overall cancer death rates have decreased, the 5-year survival rate of liver cancer patients is 18% and liver cancer is the second most lethal cancer after pancreatic cancer [2]; thus, liver cancer remains a global health challenge. Approximately 70–90% of liver cancers are hepatocellular carcinoma (HCC), resulting from multiple etiologic landscapes, including viral infection, alcohol abuse, metabolic syndrome, obesity, and genetic alteration [3,4]. Recently, much attention has been directed to the contribution of the ERK1/2 pathway to HCC carcinogenesis [4]. Aberrant activation of the ERK1/2 pathway is frequently observed in human HCC [5,6]. Sorafenib, a Raf-1 kinase inhibitor, was the first systemic drug approved by the FDA for the treatment of advanced HCC; it improved the overall survival rate and delayed the time to progression [7], indicating that the ERK1/2 pathway is a major driver in HCC. SPRED2 (Sprouty-related, EVH1 domain-containing protein 2) is a member of the SPRED protein family and inhibits Ras-dependent ERK1/2 signaling by suppressing the phosphorylation and activation of Raf [8]. The downregulation of SPRED2 expression was detected in advanced human cancers, including HCC [9]. Since the ERK1/2 pathway is a major driver in HCC [10], increased ERK1/2 activation by downregulated SPRED2 expression could contribute to the HCC development. We previously showed, using Spred2 (the term in mice)-deficient mice, that endogenous Spred2 controls the severity of several inflammatory diseases by downregulating the ERK1/2 pathway [11,12,13,14,15,16,17,18,19,20]. In a mouse model of bleomycin-induced lung injury [21], the strong accumulation of Spred2 mRNA was observed in bronchial basal cells and club cells, which are tissue specific stem/progenitor cells [22]. The proliferation of bronchial basal cells and club cells was increased in bleomycin-treated mice with Spred2 deficiency [21]. These results suggest a role of endogenous SPRED2 in regulating the proliferation of stem cells. It is possible that downregulated endogenous SPRED2 in cancer, including HCC, may play a role in the regulation of cancer stem cells (CSCs). Previous studies demonstrated the role of SPRED2 in the behaviors of cancer cells via the exogenous overexpression of this protein [23,24,25]. In the present study, we aimed to determine the biological significance of endogenous SPRED2 regarding the fate of HCC cells and demonstrate, for the first time, that the loss of endogenous SPRED2 results in increased epithelial–mesenchymal transition (EMT) and stemness, two potentially linked cellular states [26,27], in HCC cells via the upregulation of ERK1/2 and its downstream signaling pathways. We first evaluated the expression of SPRED2 in three human HCC cell lines, HepG2, Hep3B and HLE cells, with parenchymal characteristics [28]. All three cell lines expressed endogenous SPRED2, but the expression level was different among them, highest in HepG2 and lowest in HLE (Figure 1A). SPRED2-knockdown with SPRED2-specific siRNA (Figure S1) enhanced the phosphorylation of ERK1/2 (Figure 1B), and cell proliferation (Figure 1C) in all three cell lines. The effects of SPRED2-knockdown appeared highest in HepG2 cells. To verify the results obtained by SPRED2-knockdown, we attempted to generate SPRED2-knockout (KO) cells by mutating the SPRED2 gene in HepG2 cells by the CRISPR-Cas9 technology and obtained 7 potential clones (Figure S2). Among the 7 candidate clones, the deletion of SPRED2 protein was confirmed in two clones, B5 and E1, by western blotting. ERK1/2 activation, as evidenced by the increased phosphorylation of ERK1/2 and an increased cell proliferation, was detected in both clones (Figure S2B,C). The presence of a deletion in one allele and an insertion in the other allele in the SPRED2 gene was detected in the genome of clone E1 by DNA sequencing (Figure S2D). The E1 clone was used in SPRED2-KO cells in subsequent experiments. We first compared the morphological differences between wild-type (WT) and SPRED2-KO cells. WT cells showed a cobblestone epithelial morphology (Figure 1D, left), while SPRED2-KO cells displayed an elongated spindle shape with front/back polarity (Figure 1D, right), a feature of cells that undergo EMT. Functionally, the proliferation of SPRED2-KO cells was higher than that of WT cells (Figure 1E). In an in vivo transplantation model, tumors developed more frequently after the implantation of SPRED2-KO cells than of WT cells (Figure S3). In a cell scratch assay, SPRED2-KO cells showed an accelerated gap closure compared to WT cells (Figure 1F). The migration of SPRED2-KO cells was also increased in a Matrigel cell invasion assay (Figure 1G). These results strongly suggested that endogenous SPRED2 is involved in the downregulation of cell proliferation, EMT and tumorigenicity in HCC cells. To examine the mechanisms whereby SPRED2 regulates cell proliferation, we evaluated the effects of SPRED2-KO and SPRED2-overexpression (OE) on the activation of ERK1/2, and the expression of molecules regulating cell growth and progression. An increased SPRED2 level and a decreased ERK1/2 phosphorylation level in SPRED2-OE cells were confirmed by western blotting and immunofluorescence (Figure S4). The level of the cell cycle marker cyclin D1 was increased in SPRED2-KO cells but not in SPRED2-OE cells compared to WT cells (Figure 2A). The activation of STAT3, a transcription factor that regulates cell growth and differentiation, was also increased in SPRED2-KO cells and decreased in SPRED2-OE cells (Figure 2B). Cadherin switching, which is defined by decreased E-cadherin and increased N-cadherin levels, is a characteristic of cells with EMT [29]. A significant decrease in the E-cadherin level and an increase in the N-cadherin level were seen in SPRED2-KO cells, whereas an increased E-cadherin level and a decreased N-cadherin level were detected in SPRED2-OE cells via western blotting (Figure 2C,D) and immunofluorescence (Figure 2E). The expression of the EMT-related transcription factor Snail was also increased in SPRED2-KO cells and decreased in SPRED2-OE cells, although the differences were not statistically significant (Figure 2C,D). Cadherin switching and augmented Snail expression were also detected in SPRED2-knockdown HepG2, Hep3B and HLE cells (Figure S5). These results further support the notion that endogenous SPRED2 plays a role in the regulation of HCC cell growth and EMT. CSCs are a small subset of cancer cells that drive tumor initiation and cause relapse. Since the ERK1/2 pathway is important in the maintenance of CSCs [30] and because SPRED2-KO upregulates ERK1/2 activation, we assessed whether the loss or overexpression of SPRED2 affects the stemness of HCC cells by using a sphere formation and a spherical colony formation assay. SPRED2-KO cells formed tight stem-like spheroids faster than WT cells, while SPRED2-OE cells formed smaller spheroids with a loose structure (Figure 3A). The number of spherical colonies formed by SPRED2-KO cells was significantly higher than that by WT cells, while the number of spherical colonies formed by SPRED2-OE cells was lower relative to WT cells, although the difference was not statistically significant (Figure 3B). CSCs are resistant to cell death and anti-cancer agents such as cisplatin [31]. We speculated that SPRED2-KO or OE may influence the sensitivity of HepG2 cells to cisplatin. The % of apoptotic cells in SPRED2-KO cells was lower than that in WT cells with or without cisplatin treatment (Figure 3C). By MTT assay, the proliferation of untreated SPRED2-KO cells was higher and conversely lower in SPRED2-OE cells compared to WT cells (Figure 3D, left). Cisplatin treatment reduced the cell proliferation of all cell types (Figure 3D, right), but chemoresistance, calculated by the mean value from each time point [(1-cisplatin:A570/control:A570) × 100], showed that the inhibitory rate was high in SPRED2-OE cells and low in SPRED2-KO cells, compared to WT cells (Figure 3E). The expression of multidrug resistance protein 1 (MDR1) and the multidrug resistance-related protein 1 (MRP1), the molecules responsible for the chemo-resistance of tumor cells [32], were next examined. The expression of both MRP1 and MDR1 mRNA in WT cells was significantly decreased by the MEK inhibitor PD98059 (Figure 3F), indicating that these molecules were activated through the ERK1/2 pathway. MDR1 mRNA expression levels were increased in SPRED2-KO cells and decreased in SPRED2-OE cells, compared to WT cells (Figure 3G), although no statistical differences were found in MRP1 expression among the cell types. These results suggest that endogenous SPRED2 may downregulate cancer cell stemness and the sensitivity to cisplatin of HCC cells by inhibiting the ERK1/2 pathway. To obtain further evidence supporting the suppressive role of endogenous SPRED2 in HCC cell stemness, we examined the expression of pluripotency factors that drive stemness, such as Nanog, c-Myc and KLF4 [33,34]. The loss of SPRED2 resulted in an increased expression of c-Myc and KLF4, but not of Nanog, while SPRED2 overexpression downregulated the expression of Nanog (Figure 4A). PD98059 decreased the expression of all three factors in WT cells, compared to DMSO control (Figure 4B). Although the effects by SPRED2-OE were not as potent as by PD98059, our results suggested that SPRED2 regulates the expression of pluripotency factors via inhibition of the ERK1/2 pathway. Hepatic CSCs are reported to express several cell surface markers, including CD44 and CD90 [35,36]; therefore, we examined their expression in three cell types. The percentages of CD44+ or CD90+ cells were both higher in SPRED2-KO cells and lower in SPRED2-OE cells (Figure 4C). The percentages of CD44+ or CD90+ cells were markedly decreased by PD98059 in WT cells (Figure 4D), indicating that the expression of CD44 and CD90 in HepG2 cells was dependent on the ERK1/2 pathway. Next, we isolated CD44−, CD44+, CD90− and CD90+ cells from WT cells and compared the expression of SPRED2 and pluripotency factors, and the phosphorylation of ERK1/2 (Figure 4E). Interestingly, the expression of SPRED2 was lower and the phosphorylation of ERK1/2 was conversely higher in CD44+ and CD90+ cells compared to CD44− and CD90− cells. The expression of c-Myc and KLF4 in CD44+ or CD90+ cells was high compared to CD44− or CD90− cells. There was no statistical difference in Nanog expression (Figure 4E). The high expression of both CD44 and CD90 was associated with significantly reduced relapse-free survival in patients with non-small cell lung cancer [37], suggesting that CD44+CD90+ cells may have stronger CSC properties. To further evaluate the association of SPRED2 expression with CSCs, we isolated CD44−CD90− cells (60% of total cells) or CD44+CD90+ cells (2% of total cells) from WT cells. Morphologically, CD44−CD90− cells showed a cobblestone shape (Figure 4F, upper), whereas CD44+CD90+ cells had an elongated spindle shape (Figure 4F, lower). Interestingly, SPRED2 expression was almost undetectable in CD44+CD90+ cells, compared to CD44−CD90− cells (Figure 4G). ERK1/2 activation and the expression of all three factors were significantly higher in CD44+CD90+ cells (Figure 4G). These results indicated a negative association between the expression of SPRED2 and stem cell markers, and suggested that endogenously expressed SPRED2 in HepG2 cells may be preventing the acquisition of stemness by inhibiting the ERK1/2 pathway. To further evaluate the association of SPRED2 expression and the acquisition of stemness, we cultured WT-HepG2 cells on an ultra-low attachment plate in a three-dimensional (3D) culture condition. For this, 3D tissue culture models closely resemble the natural environment of cells compared to 2D culture models, providing more physiologically useful information, which may allow for a better understanding of cancer cell biology [38]. As demonstrated above, HepG2 cells cultured in 2D expressed a significant level of SPRED2 at both the mRNA and protein level. Under a 3D culture condition, the SPRED2 mRNA level significantly decreased with time (Figure 5A), and the level of SPRED2 protein was markedly reduced on day 14 with an increased level of ERK1/2 activation (Figure 5B). Cadherin switching and increased Snail expression were observed on day 14 (Figure 5C). The mRNA expression levels of Nanog, c-Myc and KLF4 (Figure 5D) and the protein levels of c-Myc and KLF4 (Figure 5E) were all up-regulated on day 14, indicating that SPRED2 expression in HepG2 cells is negatively associated with the acquisition of EMT and stemness. To examine whether 3D-cultured HepG2 cells with an increased stemness regain SPRED2 expression after incubation in 2D, spheres were washed and seeded in two standard 6-well culture plates, after which the cells were cultured in either standard medium (sphere condition: SC⇀adherent condition: AC) or serum-free sphere medium (SC⇀SC) for 3 days. The SPRED2 mRNA and protein expression levels that were reduced over 14 days in a 3D sphere culture condition (SC) returned to the original levels after 3 days of incubation in a standard adherent condition (SC⇀AC); however, they remained low in non-adherent conditions (SC⇀nonAC) (Figure 5D,E). The opposite phenomena were seen in the ERK1/2 activation, Nanog, c-Myc and KLF4 expression (Figure 5E). These results indicated that the expression of SPRED2 is negatively associated with the state of cell stemness in HepG2 cells and that this negative feedback system may no longer function in HCC cells that lose endogenous SPRED2 expression. Finally, we examined SPRED2 expression in the tumors of HCC patients. Among 371 HCC cases from the TCGA database, 82 cases that could be followed for 2 years, including of those who died, were selected. The overall survival of HCC patients was higher in patients with a high SPRED2 mRNA level, compared to that of patients with a low SPRED2 mRNA level (Figure 6A). SPRED2 mRNA expression levels were also analyzed in 40 pairs of HCC and adjacent non-cancer tissues collected at the Okayama University Hospital (Table 1) by RT-qPCR. The levels of SPRED2 mRNA expression in cancer tissues were significantly lower than those in adjacent non-cancer tissues (Figure 6B). By IHC, HCC cells were stained weakly for SPRED2, whereas adjacent non-cancer hepatocytes were moderately stained. In poorly differentiated HCC tissues, the levels of SPRED2 appeared to be lower than those in well-differentiated HCC tissues, and many HCC cells were SPRED2-negative (Figure 6C). Thus, there was a negative correlation between SPRED2 levels and cancer grades. The expression levels of Nanog, c-Myc and KLF4 in cancer tissues were significantly higher than those in adjacent non-cancer tissues in our forty pairs of HCC tissues (Figure 6D). Among these, there was a significant negative correlation between SPRED2 and KLF4 mRNA expression (Figure 6E), supporting a possible role of endogenous SPRED2 in the downregulation of stemness in patients with HCC. These results suggest that a loss of or a decrease in endogenous SPRED2 may contribute to the upregulation of the ERK1/2 pathway, and subsequent cancer progression in HCC. The expression of SPRED2 was previously shown to be downregulated in invasive carcinomas, including HCC [9,24]. The overexpression of SPRED2 inhibited SMMC-7721 HCC cell proliferation in vitro and in vivo, and induced apoptosis [24]. These results suggested that exogenously expressed SPRED2 could affect HCC cell function; however, the role of endogenously expressed SPRED2 in pathophysiology remains unknown. Here, we demonstrated that endogenous SPRED2 negatively regulated the ability of HCC cells to proliferate, migrate and invade. Endogenous SPRED2 also suppressed EMT and the acquisition of stemness, two potentially linked cellular states [26,27]. Furthermore, SPRED2 level changes in HCC cells during sphere formation in 3D culture and the SPRED2 expression levels were strongly associated with cell stemness. We previously found using a mouse bleomycin-induced lung injury model that Spred2 mRNA expression was decreased in proliferating bronchial epithelial cells (likely stem cells) after injury, but that this increased later in cells characteristic of mouse club cells, a population of stem cells that play an important role in tissue repair in the mouse airway [21]. There was a significant negative correlation between SPRED2 and KLF4 mRNA expression in clinical HCC tissues. Taken together, our results strongly suggested that endogenous SPRED2 may govern the biological basis of not only HCC, but also normal epithelial cells via the ERK1/2 pathway. This is the first study to suggest a functional role of endogenous SPRED2 in the regulation of cancer cell stemness. EMT is controlled by a coordinated interplay of multiple signaling pathways [39]. There are common properties between EMT cells and CSCs, suggesting a link between EMT programs and stem cell states [26,27]. In SPRED2-KO HepG2 cells, the expression of both EMT markers and stem cell markers was upregulated. One of the pathways important for the induction of EMT is the ERK pathway [40]. STAT3 activation is another mechanism that is known to induce EMT through the induction of Snail [41]. We showed that STAT3 activation was enhanced in SPRED2-KO cells, but the direct relationship between the ERK1/2 and STAT3 signaling is unclear. Epidermal growth factor (EGF) and IL-6 activates STAT3 in different cell types, including HepG2 cells [42,43]. We found that SPRED2-KO cells, compared to WT cells, expressed a higher level of EGF mRNA in an unstimulated state, and showed a much higher capacity to express EGF and IL-6 mRNA when stimulated (Figure S6). Thus, SPRED2 can regulate EMT directly through ERK1/2 activation and indirectly through STAT3 activation, caused by an increased cytokine production. In most types of cells, EMT leads to increased migratory and invasive properties, while reducing cell proliferation [44]. Interestingly, our results showed that the loss of SPRED2 promoted both cell proliferation and EMT, while the overexpression of SPRED2 hampered cell proliferation and EMT. We showed that STAT3 was activated by SPRED2 deficiency and was repressed by SPRED2 overexpression. This may explain our results, since STAT3 promotes cell proliferation [45], in addition to EMT induction [41]. Additional studies are required to clarify the mechanism of STAT3 activation in SPRED2-KO cells. Uncovering the mechanism(s) that regulate cancer cell stemness continues to be a challenge. In the present study, we demonstrated evidence suggesting that endogenous SPRED2 serves as a regulator of stemness in HepG2 cells. By deleting SPRED2, HepG2 cells showed enhanced stemness phenotypes, including increases in sphere formation/spherical colony formation and the expression of stemness markers; meanwhile, the overexpression of SPRED2 demonstrated opposite effects. Interestingly, endogenous SPRED2 expression gradually decreased in HepG2 cells under a sphere culture condition without any treatment. Transforming growth factor (TGF)-β is known to induce not only EMT, but stemness characteristics [46]. We detected a decreased SPRED2 expression in HepG2 cells after treatment with TGF-β (Figure S7), suggesting that endogenous SPRED2 plays a common role in EMT and cell stemness. Recently, it was shown that HepG2 spheroid proteome was divergent from the monolayer proteome after 14 days in culture, and that it continued to change over the successive culture time points. Not only hepatic marker proteins (e.g., albumin, α-fetoprotein), but also cell–cell interaction proteins, including cell junction, extracellular matrix, and cell adhesion proteins, were found to be continually modulated [47]. We demonstrated here a clear difference in the SPRED2 expression level and the expression of stemness markers between 2D and 3D models, suggesting the strong impact of endogenous SPRED2 on stemness regulation in HCC cells. SPRED2 is a membrane-associated substrate of receptor tyrosine kinases [48], and reacts with Raf that is localized in the raft domain of the plasma membrane [49]. The altered expression of cell–cell interaction proteins may affect the expression and function of SPRED2. It will be important to elucidate the precise mechanism that regulates the expression of SPRED2. We have been investigating the role of SPRED2 in inflammatory responses and cancer by analyzing human data and performing experiments using human cell lines and Spred2 KO mice. However, the role of SPRED2 in the process of cell signaling is still unclear. As described above, SPRED2 inhibits the Ras-ERK1/2 signaling pathway by interacting with Raf [8]. In general, Ras is thought to be a signaling molecule that is downstream of receptor tyrosine kinases, but it also plays a role in other signaling pathways [50]. The deletion of SPRED2 likely activate many signaling pathways in which Ras plays a role. It is necessary to continue studies to better understand the role of this molecule in cancer biology. In conclusion, we have demonstrated new evidence that strongly suggests that endogenous SPRED2 plays a critical role in the suppression of cancer cell proliferation, EMT and stemness in HCC cells. Accumulating evidence indicates that CSCs, only a rare subset of cancer cells with stem cell properties, are responsible for the early recurrence of cancer caused by tumor invasion and metastasis, as well as for the failure of chemotherapy and radiotherapy [51,52]. Therefore, targeting signaling pathways that are critical to the proliferation and survival of CSCs could present a powerful therapeutic strategy. The decreased expression of SPRED2 is associated with the grades of malignancy [9,53,54], suggesting that endogenous SPRED2 as a potential biomarker for HCC. Thus, maintaining the endogenous SPRED2 level in malignant cells could be a novel treatment strategy in order to inhibit not only cancer cell growth and progression, but also the acquisition of EMT and stemness. HepG2 and HLE cells (JCRB cell bank, Osaka, Japan) were cultured in Dulbecco’s modified Eagle medium (Nacalai Tesque, Kyoto, Japan), supplemented with 10% fetal bovine serum (FBS) (Gibco, Carlsbad, CA, USA), 100 U/mL penicillin and 100 μg/mL streptomycin (Sigma-Aldrich, St. Louis, MO). Hep3B cells (DS Pharma Biomedical, Osaka, Japan) were cultured in Eagle’s minimal essential medium (MEM) (Sigma-Aldrich, St. Louis, MO, USA), supplemented with MEM non-essential amino acid solution, 10% FBS, and antibiotics. In some experiments, cells were treated with the MEK/ERK1/2 inhibitor PD98059 (20 μM; Thermo Fisher Scientific, Waltham, MA, USA) or vehicle (DMSO) for 24 h. All experiments were performed with mycoplasma-free cells. Transfection was performed using Lipofectamine 3000 (Thermo Fisher) in OPTI-MEM 1X reduced serum medium (Gibco) for 48 h. For loss-of-function experiments, 2 μg of SPRED2-specific or non-targeting control siRNAs (Thermo Fisher) was introduced into HCC cells, and the cells were cultured for 48 h. For gain-of-function analysis, HCC cells were transfected with 8 μg of SPRED2 expression plasmid (Oligene, Rockville, MD, USA). The efficacy of siRNA and its overexpression were validated by real-time quantitative PCR (RT-qPCR) or western blotting. HepG2 cells (2 × 105 cells) were seeded into a 6-well plate. After overnight incubation, cells were transfected with SPRED2 Double Nickase Plasmid (sc-404738-NIC) or Control Double Nickase Plasmid (sc-437281) (Santa Cruz, Dallas, TX, USA) using Lipofectamine 3000 (Thermo Fisher). The sequences for sgRNAs used to disrupt the SPRED2 gene were as follows; 5′-GCTGATGCCCGAGCCTTTGA-2′and 5′-GCAATCGAAGACCTTATAGA-3′. Then, 72 hours after transfection, the medium was changed to the same medium, which contained puromycin (2 μg/mL), and transfected cells were selected for 5 days in the presence of puromycin. Subsequently, single cell clones were selected through serial dilution. Total RNA was isolated from cultured cells using a High Pure RNA Isolation kit (Roche, Mannheim, Germany). First-strand cDNAs were synthesized from 2 μg of total RNA using a High-capacity cDNA reverse transcription kit (Thermo Fisher). RT- qPCR was performed using a StepOnePlus system (Thermo Fisher). The primers used in this study are listed in Table 2. The expression level of each gene was normalized against the expression level of GAPDH. Cells were lysed in a lysis buffer (Cell Signaling Technology). The protein concentration in the lysates was measured by BCA protein assay (TaKaRa, Kusatsu, Shiga, Japan). Equal amounts of samples (15 μg) were fractionated by sodium dodecyl sulphate–polyacrylamide gel electrophoresis (Thermo Fisher) and the proteins were transferred onto PVDF membranes. After blocking, the membranes were incubated overnight with a primary antibody, followed by a horseradish peroxidase-conjugated secondary antibody. Target proteins were visualized by ImmunoStar LD (Wako, Osaka, Japan) and the membranes were scanned using a C-DiGit Blot scanner (LI-COR Biotechnology, Lincoln, NE). The blot images were semi-quantitated with Image Studio software. The antibodies used for Western blotting are listed in Table 3. Cells were seeded in a 96-well plate at 2000 cells/well with 100 µL of cell suspension. The cell growth was determined every 24 h using the MTT assay (Roche, Mannheim, Germany). The optical density (OD) values at 570 nm were determined using a microplate reader. A higher absorbance rate indicates an increase in the cell proliferation. In some experiments, cells were exposed to a sublethal dose of cisplatin (10 µg/mL) [55]. Each assay was performed in triplicate. Cells (2 × 105 cells) were grown in a 6-well plate to obtain the confluence of the monolayer, scratched with a sterile 200 µL tip, and then cultured for 18 h, at a time when there was no difference in cell proliferation between SPRED2-KO and WT cells. The images were captured at different time points with an inverted microscope (Olympus CKX41; Olympus, Tokyo, Japan), and the wound distance at each time point was measured by Image J software. The percent of wound closure was assessed by (Original distance-final distance)/original distance × 100 (%). The experiments were performed in triplicate. Transwell chambers (Corning, Lowell, MA, USA) were used. Cells (5 × 105) were seeded on Matrigel-containing upper chamber and incubated for 18 h, at a time when there was no difference in the cell proliferation between SPRED2-KO and WT cells. Cells that invaded into the lower chamber were fixed in methanol and stained with crystal violet. Three low-power fields (magnification, ×20) were randomly selected from each chamber to count the migrated cells. The experiments were performed in triplicate. Cells at ~80% confluence were dissociated into single-cell suspensions using 0.25% trypsin and 0.05% EDTA (Sigma-Aldrich). The cells were suspended in B-27 (Thermo Fisher); this was supplemented by DMEM/F12 medium containing 20 ng/mL of epidermal growth factor (EGF, Peprotech, Cranbury, NJ, USA) and 20 ng/mL of basic fibroblast growth factor (bFGF, Peprotech), seeded in ultra-low attachment 96-well plates (Corning) at a density of 1000 cells per well, and were incubated at 37 °C. Fresh aliquots of EGF and bFGF were added every 2 days. These were cultured for 14 days. Spheres were then dissociated, and 1 × 104 cells were plated onto a 6-well plate (BioLite 6 Well Multi-dish, Thermo Fisher), cultured for an additional 14 days to investigate the self-renewal ability of the cells through secondary sphere formation. At appropriate time points, the images were captured with an inverted microscope (Olympus). Cells were seeded on a Lab-Tek II Slide (8 Chamber, Electron Microscopy Sciences, Hatfield, PA) for 1 day at 37 °C. The cells were fixed in acetone and immunostained with the indicated primary antibodies (Table 3). The slides were then incubated with Alexa Fluor 568-conjugated anti-rabbit IgG, and visualized using confocal laser scanning microscopy (LSM780, Zeiss Microscopy, Jena, Germany). For the apoptosis assay, cells were washed with PBS, resuspended in 500 µL cold PBS, and stained with fluorescein isothiocyanate (FITC)-Annexin V and Propidium Iodide (PI) using TACS Annexin V Kits (R&D Systems, Minneapolis, MN). To detect CD44+ and CD90+ cells, cells were incubated with an Alexa Fluor 488-conjugated anti-human CD44 antibody and anti-human CD90 antibody (Biolegend, San Diego, CA), respectively. Cells were analyzed using a MACSQuant Analyzer (Miltenyi Biotec, Bergisch Gladbach, Germany), and data were analyzed using MACSQuantify software (Miltenyi Biotec). CD44 and CD90 Microbeads (Miltenyi Biotec) were used for the isolation of CD44+ and CD90+ cells from single-cell suspensions from WT-HepG2 cells, respectively. The purity and % of alive cells were >95%. Immunostaining for Spred2 was carried out using the Polink-2 plus HRP rabbit with DAB kit (GBI, Bothell, WA, USA), according to the manufacturer’s instructions. In brief, sections (4-µ-thick) were deparaffinized, rehydrated, and treated in 0.3% H2O2 in methanol for 10 min at room temperature. After antigen retrieval, using a microwave oven in 0.1 M of citric acid buffer for 25 min, sections were blocked with DAKO Protein Block Serum-Free (Dako, Carpinteria, CA, USA), and incubated with an anti-human Spred2 polyclonal antibody (Table 3) for 90 min at room temperature. After washing, sections were incubated with rabbit antibody-specific enhancer for 15 min at room temperature, followed by the incubation with polymer-HRP for rabbit IgG for 30 min at room temperature, and visualized using diaminobenzidine (Dako, Santa Clara, CA, USA). Nuclear counterstaining was performed using hematoxylin. Expression levels were determined by staining intensity. Forty HCC surgically resected specimens were retrieved from the pathology record at the Department of Pathology, Okayama University Hospital. The patients who underwent chemotherapy or radiotherapy before the resection were not included in this study (Table 1). The protocol in this study was reviewed and approved by the Ethics Committee of Okayama University (1703-007). Although individual written consents were not obtained, we disclosed the study plan on our website, providing the patients or their families with the opportunity to opt out, and only the cases without their refusal were enrolled in the study. A data set of 371 HCC patients was collected from The Cancer Genome Atlas (TCGA) database (https://www.cancer.gov/tcga (accessed on 6 October 2020)). Among 371 HCC cases, 82 cases that could be followed for 2 years, including those who died, were selected. The SPRED2 expression of these 82 cases was dichotomized, and a survival curve was drawn with the high 50% as SPRED2-high and the low 50% as SPRED2-low. All statistical calculations were performed using GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA). Statistical significance was analyzed using a parametric two-tailed unpaired t test and non-parametric Mann–Whitney u test for normal distribution and non-normal distribution, respectively. Data were expressed as the mean ± SEM (normal distribution). Survival rate was compared using the log-rank test. A p value < 0.05 was considered statistically significant.

PMC10003371

Duangnapa Kovanich,Teck Yew Low,Manuela Zaccolo

Using the Proteomics Toolbox to Resolve Topology and Dynamics of Compartmentalized cAMP Signaling

28-02-2023

cAMP signaling,cAMP compartmentalization,G-protein coupled receptor,A-kinase anchoring protein,phosphodiesterases,protein kinase A,proteomics

cAMP is a second messenger that regulates a myriad of cellular functions in response to multiple extracellular stimuli. New developments in the field have provided exciting insights into how cAMP utilizes compartmentalization to ensure specificity when the message conveyed to the cell by an extracellular stimulus is translated into the appropriate functional outcome. cAMP compartmentalization relies on the formation of local signaling domains where the subset of cAMP signaling effectors, regulators and targets involved in a specific cellular response cluster together. These domains are dynamic in nature and underpin the exacting spatiotemporal regulation of cAMP signaling. In this review, we focus on how the proteomics toolbox can be utilized to identify the molecular components of these domains and to define the dynamic cellular cAMP signaling landscape. From a therapeutic perspective, compiling data on compartmentalized cAMP signaling in physiological and pathological conditions will help define the signaling events underlying disease and may reveal domain-specific targets for the development of precision medicine interventions.

Using the Proteomics Toolbox to Resolve Topology and Dynamics of Compartmentalized cAMP Signaling cAMP is a second messenger that regulates a myriad of cellular functions in response to multiple extracellular stimuli. New developments in the field have provided exciting insights into how cAMP utilizes compartmentalization to ensure specificity when the message conveyed to the cell by an extracellular stimulus is translated into the appropriate functional outcome. cAMP compartmentalization relies on the formation of local signaling domains where the subset of cAMP signaling effectors, regulators and targets involved in a specific cellular response cluster together. These domains are dynamic in nature and underpin the exacting spatiotemporal regulation of cAMP signaling. In this review, we focus on how the proteomics toolbox can be utilized to identify the molecular components of these domains and to define the dynamic cellular cAMP signaling landscape. From a therapeutic perspective, compiling data on compartmentalized cAMP signaling in physiological and pathological conditions will help define the signaling events underlying disease and may reveal domain-specific targets for the development of precision medicine interventions. cAMP is a ubiquitous secondary messenger. In eukaryotes, cAMP production is triggered by the activation of G protein-coupled receptors (GPCRs), a large and diverse protein family with around 800 members [1] that transmit signals from a variety of stimuli (e.g., hormones, cytokines, neurotransmitters, mechanical stress). Upon activation, the receptor undergoes a conformational change to achieve its active state, followed by coupling to and activation of heterotrimeric G-proteins (α, β and γ). This initiates a signaling cascade that triggers adenylyl cyclase (AC) to catalyze the conversion of ATP to cAMP. Elevated intracellular cAMP then activates a small number of effector proteins, including the cAMP-dependent protein kinase (PKA), the exchange factors activated by cAMP (EPAC), the hyperpolarization-activated cyclic nucleotide-gated channels (HCN) and the popeye domain-containing proteins (POPDC). Despite relying on a limited number of effectors, cAMP signaling is central to multiple physiological processes, ranging from proliferation, differentiation, metabolism, and control of specialized cellular activities, such as synaptic transmission, cardiac contraction and hormone secretion. Unsurprisingly, disruption of cAMP signaling is associated with several diseases, including heart failure [2] and cancer [3]. The most extensively studied target of cAMP is PKA. The inactive PKA holoenzyme consists of two regulatory (R) and two catalytic (C) subunits. There are four versions of R subunits, further classified as type I (RIα, RIβ) and type II (RIIα, and RIIβ), and three versions of C: Cα, Cβ, and Cγ. cAMP binds to R in the inactive tetrameric holoenzyme R2C2 inducing a conformational change that removes the inhibitory action of R on C subunits, leading to phosphorylation of nearby substrates. PKA is an extremely promiscuous kinase with the ability to phosphorylate many targets within the same cell, thus contributing to the ability of cAMP to mediate a multiplicity of cellular effects. It is now widely accepted that cAMP signaling achieves specificity of response via compartmentalization. Given the large number and variety of activating stimuli, receptors and PKA substrates, cAMP/PKA signaling is organized within the cell as a collection of multiple pathways controlled by a precise spatial and temporal coordination of signal transduction. Such organization enables the correct translation of the message conveyed by a given external stimulus into the appropriate phosphorylation events and cellular responses [4]. The spatial constraint on cAMP signaling became obvious with the observation, almost 40 years ago, that stimulations of cardiac myocytes with isoproterenol or prostaglandin E1 led to different cellular responses despite the fact that a similar increase in cAMP was generated in response to the two stimuli [5]. Evidence supporting the concept of PKA compartmentalization came later, with the identification of several scaffolding proteins, termed A-kinase anchoring proteins (AKAPs), that tether PKA at specific subcellular locations [6,7]. Currently, the AKAP family includes around 60 diverse proteins which share a characteristic R-binding domain [8]. It is now recognized that AKAPs coordinate unique cAMP signaling domains, or signalosomes, by recruiting and anchoring PKA in proximity to its substrates and by agglomerating other signaling components, including additional kinases, phosphatases, ACs, and the cAMP-hydrolyzing phosphodiesterases (PDEs), to form signaling hubs with distinct subcellular localization [8]. Specific anchored pools of PKA can then be selectively activated by a spatially confined pool of cAMP generated in response to receptor activation. The active kinase subsets, in turn, phosphorylate target proteins anchored in proximity, avoiding crosstalk and signal contamination among different cAMP/PKA signaling hubs. One example of cAMP signaling compartmentation is the organization of signaling domains at the plasma membrane, where signaling domains are organized by scaffolding proteins that may bring together GPCRs, cAMP effectors, cAMP producing (ACs) and degrading (PDEs) enzymes, signaling regulators and targets into functional domains that are few tens of nanometers in size [9,10,11] (Figure 1). The protein components (proteome) of each signalosome can be very dynamic, consisting of constitutive as well as contextually recruited or dissociated proteins across activation states and in physiological versus pathological conditions [12,13,14]. The spatiotemporal dynamics of the cAMP/PKA signalosomes make the characterization of such signaling domains daunting. Although GPCRs are one of the most successful therapeutic target families, current drug discovery programs remain associated with very high attrition rates due to the complexity of the signaling associated with these receptors. The realization that cAMP signaling is organized in discrete subcellular domains offers a new opportunity for the development of drugs that selectively target individual domains for therapeutic interventions that can achieve subcellular precision. Establishing the blueprint of individual cAMP signaling compartments across cell types, activation states and disease states would provide invaluable insight for targeted drug design. Quantitative proteomics methodologies that uncover protein phosphorylation, interaction and proximity provide powerful tools for this type of analysis and are increasingly being applied to study cAMP compartmentalization. Basic principles of the methods and specific examples of the applications to address particular questions are described in detail below. cAMP signaling uses different mechanisms, including protein–protein interactions (PPIs) and protein phosphorylation, to relay, process, and translate signals into cellular responses. cAMP signaling compartmentalization heavily relies on the formation of local signaling domains where cAMP signaling components involved in a specific cellular response cluster together. Compartmentalization is critically dependent on the assembly of multiple signaling components that come together via protein–protein interactions to become functional signaling units. Within such domains, cAMP signals are translated into specific cellular responses via the phosphorylation of target proteins. As such, mapping the domain interaction landscape and defining the downstream phosphorylation events are the key aspects of compartmentalized signaling studies. Typically, the proteomics analysis of PPIs and protein phosphorylation is usually performed in a quantitative manner, so the changes in phosphorylation events across experimental conditions can be compared, and true signalosome components can be distinguished from the background. To guide the reader through the applications discussed in this review paper, in Box 1, we describe the general principles of quantitative proteomics. Currently, liquid chromatography-tandem mass spectrometry (LC-MS/MS) is the main workhorse driving proteomics studies. In bottom-up proteomics, proteins are first extracted and proteolyzed with a protease, such as trypsin, to yield smaller peptides [15]. To reduce sample complexity, protein/peptide mixtures can be fractionated with gels or by chromatography [16]. During LC-MS/MS analysis, each peptide fraction is separated with a C18 reversed-phase column connected online to a mass spectrometer. C18-separated peptides are eluted and ionized before measuring the intact mass (MS1) and the fragment mass (MS2) of a peptide and its fragments upon gas phase dissociation in the mass spectrometer. Both the intact and fragment masses are subsequently used for matching a corresponding peptide sequence and a protein(s) from a protein database. To enable protein quantification, (i) label-based and (ii) label-free methods can be additionally coupled to LC-MS/MS. In label-based methods, stable isotopes are usually introduced in a protein/peptide via (i) metabolic (in vivo) labeling or (ii) chemical (in vitro) labeling [17,18,19,20,21,22,23]. In SILAC (stable isotope labeling with amino acids in cell culture), cells are cultured in a special cell culture medium containing stable isotope-labeled versions of amino acids, such as “heavy” arginine or lysine, that can be metabolically incorporated in newly synthesized proteins [17,24]. After cell lysis, proteins from differentially labeled populations are combined, avoiding experimental variations that may be introduced by subsequent sample processing. In MS1 spectra, each SILAC-labeled peptide manifests itself as a doublet or triplet with distinct mass differences and quantification is based on the difference in peak intensities of these multiplets (Figure 2A). Originally, SILAC was designed to compare only two or three cell populations as only three isotopically distinct versions of arginine and lysine are commercially available. Recently, NeuCode SILAC, which enables simultaneous comparison of up to nine treatments and control (18-plex), was developed [25]. It is noteworthy that not all biological samples are amenable to metabolic labeling, notably clinical samples. For these samples, chemical labeling, which involves in vitro reaction between labeling reagents and proteins/peptides, is applicable to any biological samples with the caveat of higher experimental variations since labeled samples are mixed at a later step. Chemical labeling reagents contain different heavy isotopes to produce mass shifts in the MS1 spectrum (e.g., dimethyl labeling [21,26]) or MS2 spectrum (e.g., isobaric labeling [22,23]). Dimethyl labeling was developed as a cost-effective platform that is performed at the peptide level (after proteolysis) and involves reductive dimethylation of all primary amines (N-terminus of peptides and ε-amino group of lysine) with isotopomeric dimethyl labels. Similar to SILAC, co-eluting dimethyl-labeled peptides manifest themselves as doublets or triplets with distinct mass differences in MS1 spectra and quantification is performed by comparing the differences in the ion intensity of the differentially labeled peptides (Figure 2A) [21,26]. For studies that require higher level of multiplexing, isobaric-tag-based methods, such as iTRAQ and TMT, can be used [22,23]. The isobaric tagging strategy is based on the covalent modification of the primary amines of peptides with different isobaric tags. Peptides originating from each experimental condition are labeled with each isobaric tag in parallel and combined for MS analysis. In contrast to dimethyl labeling, differentially tag-labeled peptides tend to comigrate and appear as a single peak in the MS1 spectra (Figure 2A). However, post peptide fragmentation, each isobaric tag generates a reporter ion with a distinct mass in the MS2 spectra, which is used for relative quantification (Figure 2A). Currently, up to 8-plex iTRAQ and 16-plex TMT reagents are available commercially [27,28], albeit the cost of the labeling reagents is high. For label-free strategies there is no limitation with respect to the number and origin of samples. This approach is therefore, cost-effective and convenient, as no labeling is required. Since samples are separately collected, processed, and mass-analyzed, such experiments need very careful execution to minimize experimental or analytical variations. Label-free quantification can be as simple as spectral counting, where the number of peptide-spectrum matches (PSM) of a protein is used as a proxy for protein abundance. However, spectral counting is biased towards larger proteins, which generate more peptides than small proteins [29]. Recently, several computational platforms, including the MaxLFQ algorithm (embedded in MaxQuant), or the Minora tool (embedded in Proteome discoverer), were developed for more accurate label-free quantification (LFQ) [30,31]. In the LFQ workflow, the peak intensity, or the area under the curve of a peptide ion, is used for relative quantification across samples (Figure 2B) [30,31]. Until now, most discovery-based quantitative proteomics studies have been performed with mass spectrometers that operate in a data-dependent acquisition (DDA) mode. In DDA, the top N (usually 10–20) most intense peptide precursors in a survey MS1 scan are sequentially selected for fragmentation and MS2 detection. The downside of this approach is that DDA is biased towards measuring highly abundant proteins. Additionally, due to the stochastic nature of precursor selection, if the number of precursor ions exceeds the number of top N, peptides may not be consistently detected in all LC-MS/MS runs, resulting in many missing values [32,33]. As a solution, data-independent acquisition (DIA) schemes have been implemented. These include SWATH-MS and Boxcar, developed by the Aebersold’s and Mann’s laboratories, respectively [34,35]. In DIA, essentially all peptide precursors in a fixed m/z isolation window are fragmented in parallel and analyzed, resulting in a near complete recording of all MS2 scans and highly reproducible label-free quantification. DIA enables large-scale protein quantification with low variation and high reproducibility, as demonstrated in a multi-laboratory evaluation study [36]. In term of quantification reproducibility, DIA is superior to DDA and can overcome the issue of abundant peptides dominating the MS1 scan [36]. In MS-based interaction proteomics, the constituents of protein signaling complexes are systematically mapped. Several MS-based interactomics strategies, including affinity purification-MS (AP-MS), proximity labeling-MS (PL-MS), crosslinking-MS and coFractionation-MS (coFrac-MS), have been comprehensively reviewed recently [37]. Among these methods, AP-MS and PL-MS are the most commonly adopted for PPI studies. The AP-MS workflows involve multiple steps, including (i) cell lysis, (ii) incubation of lysate with a specific antibody, followed by capturing with protein A/G beads or with resins conjugated with epitope tag-specific antibodies, (iii) several extensive washing steps to remove non-specific binding proteins and elution of the enriched proteins, and (iv) identification of the eluted proteins by LC-MS/MS. Since purification is performed post-lysis, one challenge is that some detected PPIs may be spurious and non-physiological as the bait and prey may be brought together by chance upon lysis, giving rise to biological false positives. Technical false positives often arise from nonspecific protein binding to the affinity matrices. In addition, mapping the interaction landscape of integral membrane proteins remains a technical challenge. Detergents used to solubilize membrane proteins may disrupt antigen-antibody recognition and membrane protein complexes [38]. Additionally, the success of AP-MS often depends on stable protein interactions, while weak and transient interactors can be lost easily during cell lysis and extensive washing steps. In recent years, PL-MS has been developed to overcome these limitations. Since its introduction in 2012 [39], PL-MS has been used for PPI mapping and proximity profiling in several cell models and organisms. The technique is based on the labeling of the “neighboring” proteins to the bait protein. These include proteins that physically interact with the bait and other proteins that are in close proximity to the bait. In this approach, the bait protein is expressed as a fusion protein with an enzyme capable of biotin labeling—either as an exogeneous protein or endogenously, under the control of the target gene promoter, using CRISPR/Cas9-mediated genome editing technology [40,41]. Biotin is then added, followed by its catalysis by the fused enzyme into reactive biotin intermediates. These intermediates subsequently diffuse away to biotinylate proteins in the vicinity, a process named promiscuous biotinylation. The labeling strength of these intermediates is limited by the distance of the prey away from the bait. This gives rise to an important concept coined as the “effective labeling radius”. The same experimental settings, but with the expression of free enzyme, are commonly used as a control to reveal false positives that are randomly labeled or that are labeled due to their non-specific association with the enzyme. If transient interactions have ceased and the binding partners have moved away from the bait protein at the time of extraction, that is not a problem since interacting, and other relevant proteins have already been “marked”. The denaturing condition can then be applied to solubilize the whole proteome without the need to preserve protein interactions. This characteristic of PL approaches is a great advantage for spatiotemporal proteomics. Biotinylated proteins are then purified using avidin/streptavidin-coated beads and are identified by MS. As the biotin-avidin association is the strongest known non-covalent interaction, multiple stringent washing steps can be performed to minimize background contaminants. Similar to AP-MS, to distinguish bona fide proximal proteins from irrelevant labeled proteins, the PL experiment is usually combined with quantitative proteomics approaches, either based on isotopic labeling or label-free quantification. There are two main enzyme systems used in PL-MS, which are promiscuous biotin ligases, or BioID, in the case of proximity-dependent biotin identification and peroxidases, or APEX, in the case of peroxidase-catalyzed proximity labeling (Figure 3). The promiscuous biotin ligase catalyzes the conversion of biotins to the highly reactive biotinoyl-5′-AMP intermediates to react with proximal primary amines (i.e., lysine residues), leading to the promiscuous biotinylation of surrounding proteins within an estimated radius of 10 nm [42]. Depending on the types of promiscuous biotin ligases used, proximity labeling can occur within ten minutes and up to 18–24 h after the addition of exogeneous biotin [42,43,44,45,46,47] (Figure 3). APEX utilizes modified soybean ascorbate peroxidase to catalyze the oxidation of biotin-phenol to produce highly reactive biotin phenoxyl radicals, which can react with neighboring electron-rich amino acids such as tyrosine and possibly tryptophan, cysteine, and histidine [48]. The reaction requires H2O2 treatment in the presence of biotin-phenol to produce the radicals, and labeling can be achieved in as short a time as 1 min [48], meaning that the biotin labeling can be timely controlled through H2O2 availability. This becomes very practical for studies that require cell incubation with ligands for a period of time before initiating the labeling. Additionally, the short half-life of the radicals (<1 ms) and their inability to cross membranes ensures that labeling occurs only within an estimated radius of 20 nm and is contained only within the candidate space [48]. These are, in fact, the key advantages of APEX over BioID. Several current developments in PL-MS have focused on the use of different fusion biotinylating enzymes with a small size to reduce mislocalization and to improve the efficiency and speed of labeling so as to capture PPIs at a higher temporal resolution. These include BioID2 [43], TurboID [44], miniTurbo [44], UltraID [45] and MicroID2 [46] biotin ligases and APEX2 ascorbate peroxidase [49] (Figure 3). The experimental details of PL-MS have been reviewed by several recent publications [37,50,51,52]. cAMP signals are translated into specific cellular responses largely through protein phosphorylation. Accordingly, mapping the cAMP-dependent phosphorylation landscape is key to establishing the topology and functions of cAMP signaling domains. Current state-of-the-art phosphoproteomics technologies allow investigators to identify and quantify at a depth of >10,000 phosphorylation sites in a population of cells in one setting, with high specificity and reproducibility [54,55]. This unprecedented resolution provides a new perspective on the molecular mechanisms underlying diseases and the identification of potential therapeutic targets. It has been well documented that the identification and quantification of phosphorylated peptides are constrained by their low abundance and stoichiometry relative to their non-phosphorylated counterparts. Besides, during MS data analysis, the proper assignment of a phosphate group among several phosphorylatable residues within a peptide sequence has also posed a considerable challenge [56]. Due to the inherently low stoichiometry, the phosphoproteomics workflows heavily rely on enrichment protocols prior to MS analysis [57]. While the detailed may vary in different workflows, the combination of initial fractionation, phosphopeptide enrichment, stable isotope labeling, and LC-MS/MS has become the method of choice. To enhance the coverage of phosphopeptides, orthogonal peptide fractionation strategies, such as low-pH strong cation exchange (SCX) or high-pH reversed-phase chromatography, are often performed prior to the enrichment [55,58,59,60,61,62]. For quantification, both stable isotope labeling approaches and label-free quantification have been employed [54,55,61,62]. Several affinity enrichment strategies have also been developed to isolate phosphopeptides [57]. For global enrichment of phosphopeptides, immobilized metal affinity chromatography (IMAC) and metal oxide affinity chromatography (MOAC) are the two most popular approaches. IMAC is based on the interaction of positively charged metal ions such as Fe3+ or Ti4+ with the negatively charged phosphate groups in the phosphopeptides [59,60]. As the name implies, MOAC uses metal oxides, such as TiO2, to capture phosphopeptides through the formation of the bidentate binding mode of phosphates to the metal oxide surface [63]. In terms of enrichment efficiency, the two methods are generally comparable, with each showing preferences toward distinct phosphopeptide subpopulations [64,65]. This is not surprising as the two enrichment techniques bind differently to the phosphopeptides. Of note, we have found that the SCX-Ti4+-IMAC enrichment method, developed by Heck’s laboratory, shows advantages when it comes to the identification of PKA phosphorylation events [60]. Phosphorylation sites of basophilic kinases, such as PKA or PKC, usually display high basic residue (R/K) content in the neighborhood that can hinder the enrichment of the peptides. The SCX-Ti4+-IMAC method was shown to specifically enrich this subset of phosphopeptides [60], therefore, providing extra benefit in the analysis of PKA substrates. Additionally, a more targeted enrichment platform for PKA phosphorylated substrate identification was developed by the same laboratory [66]. The method utilizes specific antibodies against the PKA phosphorylation consensus to capture peptides bearing the motif from cell lysate digests. The high specificity and selectivity of the platform were illustrated by the fact that 98% of the phosphopeptides identified in the study were found to harbor the PKA consensus motif [66]. Phosphoproteomics data analysis involves the identification and quantification of phosphopeptides and the localization of the phosphorylation sites. Even though peptides may be tentatively identified as phosphorylated, it might not be possible to assign the actual sites of modification. In fact, the correct localization of phosphorylation sites is a critical aspect of phosphoproteomic data analysis. Site localization can be complicated when multiple potential phosphoresidues are present within a single peptide, and peptides harboring adjacent or multiple phosphorylated residues can become problematic. In order to resolve the ambiguity between multiple potential sites, the site-determining fragments ions exclusive to a specific site location must be obtained in MS/MS spectra. If these fragment ions are not generated efficiently during fragmentation, the site localization will be significantly impaired. For this purpose, several peptide fragmentation modes have been developed to produce good-quality fragmentation spectra for the assignment of phosphorylation site(s) and are described elsewhere [67]. For a large-scale proteomics experiment involving thousands of phosphopeptides, probability-based site-localization algorithms have been developed and implemented in the main software tools to determine the most likely phosphorylation site(s) and are extensively reviewed elsewhere [68]. In terms of quantification, confident site localization is important since only the phosphopeptides in which phosphorylation sites are assigned can be used for quantitation. To translate a list of differentially regulated phosphorylation events into biological insight, Gene Ontology (GO) enrichment analysis can be performed to deconvolute the biological processes in which the list of proteins harboring the phosphopeptides are involved [69]. Another important bioinformatic task is the identification of the protein kinases/phosphatases responsible for the observed changes in phosphorylation. Generally, the prediction is based on the kinase phosphorylation motif, and several prediction tools are available and extensively reviewed elsewhere [70]. Interestingly, studies using these prediction tools and investigating the cAMP-associated phosphoproteome have found that phosphorylation mediated by several other kinases, in addition to PKA, is upregulated in response to an increase in cAMP levels [71,72]. These studies have also found that many phosphopeptides are downregulated by cAMP. Overall, these observations indicate that cAMP activates complex signaling networks involving other kinases as well as phosphatases. These networks are bound to be relevant for the regulation of cellular function, although we currently have very little understanding of the role that this more extensive and complex wiring of intracellular signaling plays in cell physiology. It is widely appreciated that not only can different GPCRs trigger different signals in the same cell, but the same GPCR activated by different agonists can transduce distinct cellular responses through receptor compartmentation [73]. An additional level of signaling complexity is provided by receptor internalization. GPCR signaling is terminated via receptor phosphorylation by GPCR kinases (GRKs), which promotes binding of the receptor to the adaptor proteins β-arrestins (βarrs), leading to receptor desensitization. The internalized receptor either undergoes resensitization by dephosphorylation and recycling back to the plasma membrane or is trafficked to lysosomes for degradation. It is now apparent that different ligands can stabilize distinct receptor conformation states that favor coupling to certain effectors, resulting in the selective activation of certain pathways. So, depending on the ligand, the receptor conformational change can lead to the activation of different G proteins [74] or β-arrestin isoforms [75] or can result in exclusive engagement of the G-protein or β-arrestin pathways [76,77], adding significant complexity to GPCR-mediated signaling. GPCR signaling was initially believed to happen exclusively at the plasma membrane. In the case of GPCR signaling to ACs, it was demonstrated that the cAMP pool generated by the receptor at the plasma membrane could reach only a nanoscale distance and is short-lived due to local PDE activity [9] and rapid receptor internalization. However, mounting evidence indicates that receptor activation by some ligands, such as peptide hormones, can lead to sustained cAMP production after receptor internalization when the receptor is embedded in the membrane of endosomes or after the trafficking of the internalized receptor to the trans-Golgi network (TGN) [78,79]. Through this signaling modality, cAMP can reach distal organellar targets such as the nucleus [79,80]. In addition, several GPCRs primarily reside at the organellar membranes and trigger distinct inward signaling from these locations inside the cell [81]. Notably, the downstream cellular responses triggered by GPCRs at internal membrane sites were found to be distinct from those elicited by receptors at the cell surface. In the context of specialized cells, the specificity of the downstream response can be ascribed to differences in receptor compartmentalization at the cell surface as well as at intracellular signaling sites. For example, in cardiomyocytes, β1-adrenergic receptors (β1ARs) and the highly homologous β2-adrenergic receptors (β2ARs) bind to norepinephrine and activate G protein/cAMP/PKA signaling. β2ARs are highly enriched in specialized membrane structures, including T-Tubules and caveolae, whereas the homologous β1ARs are distributed across the entire cell membrane [2,82]. While β1AR stimulation results in more diffuse cAMP signals across the entire cell, β2AR activation generates a cAMP pool more narrowly confined to the site of production [2]. At early time points after receptor internalization, β1ARs and β2ARs appear to traffic to distinct endosomal compartments [83]. β2ARs activate G protein signaling from early endosomes, while the endocytic trafficking route for β1ARs appears to also involve the trans-Golgi network [84,85]. In the heart, β1AR signaling regulates chronotropic, inotropic and lusitropic responses through PKA-mediated phosphorylation of multiple proteins involved in Ca2+ handling and excitation-contraction coupling, while β2AR signaling induces modest chronotropic and no lusitropic responses. β1AR signaling drives the expression of pro-apoptotic genes while β2AR signaling promotes antiapoptotic signaling and cardiomyocyte survival, possibly through Gαi coupling or activation of β-arrestin-mediated pathways (as reviewed in [86]). In the failing heart, β2ARs were shown to redistribute to the non-tubular membrane and produced more diffuse β2AR cAMP signals [2], which could lead to the loss of their cardioprotective properties. From the examples above, it is clear that receptor compartmentalization provides well-defined signaling domains that contribute to the specificity of the downstream response. How exactly this is achieved, however, is far from clear. For example, as the trafficking route of a given receptor appears to depend on the specific ligand bound to it, it is conceivable that the unique conformation the receptor adopts after binding could facilitate the recruitment of distinct compartment-specific sorting proteins that are not presently known. How do cAMP signals generated at internal membrane sites reach the nucleus and selectively drive ligand-specific cAMP-dependent transcription events? The identification of proteins recruited to the internal membrane domains could provide critical cues. Despite the open questions, recent findings indicate that targeting disease-specific signaling at defined subcellular locations may be a valid alternative to the prevalent and rather blunt approach that targets the receptor at the plasma membrane [87,88]. Such a strategy has the potential to provide more specific therapeutic interventions with reduced undesirable side effects. However, efforts to develop subpathway- or location-specific treatments are presently hindered by our limited understanding of the full makeup of a given receptor signaling network. Elucidation of the complexity of receptor dynamics, as well as of the architecture of signaling complexes with the subcellular resolution, is, therefore, paramount. APEX-based proximity labeling has been exploited to capture both location- and time-dependency of ligand-specific GPCR signaling dynamics in simplified cell models [89,90,91,92]. One of the advantages of APEX for mapping the GPCR signaling domain is that this rapid labeling technique provides a snapshot that captures the transient signaling landscape within the timescale of GPCR activation (Figure 4) [89,90,91,92]. When combined with a well-designed control system and quantitative proteomics, GPCR-APEX allows identification, in an unbiased manner, of the molecular components in the local environment, including interacting proteins and proximal bystanders to the receptors, through the quantification of thousands of biotinylated proteins. The bystanders identified are considered to store important information on localization and can be used as spatial markers to map the trafficking route of the receptor [89,90,91,92]. As a proof-of-concept, Lobingier et al. investigated the signaling networks associated with the well-studied β2AR and the less explored delta-opioid receptor (DOR) in the HEK293 model system stably expressing fusions of each receptor with APEX2 [89]. Several spatial references were generated, including APEX2-tagged Lyn11 as a plasma membrane marker (PM-APEX2), 2xFYVE-tagged APEX2 as an early endosome marker (Endo-APEX2) and GFP-APEX2 (Cyto-APEX2) as a cytoplasmic reference. Technically, the proteins captured by the APEX labeling method represent a complex mixture of two sets of proteins, the receptor signaling network components and proximal bystanders. To distinguish bystanders from bona fide signaling network components, the abundance of proteins enriched from receptor APEX can be compared to the proteins enriched in the localization-matched control. Bystander proteins from the same subcellular compartment should be equally biotinylated, while the signaling network components should be enriched in the receptor APEX compared sample compared to the control. For instance, by comparing the proteins identified from β2AR APEX with control APEX using PM-APEX2 after 1-min activation, plasma membrane proteins were identified with similar abundance while β-arrestin 2 and proteins of the endocytic adaptor complex AP2, which are recruited to the active receptor, were more enriched in the β2AR-APEX dataset. Similarly, by comparing proteins identified from β2AR APEX with control APEX using Endo-APEX2 10 min past activation, several proteins engaged in β2AR endosomal sorting, including retromer complex components, were enriched while other early endosomal proteins were equally detected, highlighting the importance of selecting appropriate spatial references for the success of the GPCR APEX study [89]. The same strategy was then utilized to study the underexplored DOR signaling and trafficking network, with a focus on the characterization of DOR-engaged endosomal ubiquitin network components that target the active receptor to lysosomes. Briefly, DOR-APEX2-expressing cells were exposed to the opioid agonist for varying periods of time. Biotinylated proteins identified from each time point were quantified against proteins identified from spatial references using label-free quantification. This experiment led to the identification of 29 specific interacting proteins, which were classified as being biotinylated at an early, middle, or late phase following receptor activation. WWP2 and TOM1, two ubiquitin-linked proteins that showed the strongest labeling in the late phase, were further validated as network components that mediate endosomal sorting of the DOR to the lysosome [89]. APEX has also been utilized to probe biased signaling. One example is the angiotensin II type 1 receptor (AT1R), which responds to the peptide hormone angiotensin II (Ang II) and has a critical role in cardiovascular physiology. AT1Rs are targeted for the treatment of cardiovascular diseases, and G-protein- and β-arrestin-biased AT1R ligands have been developed [76]. HEK293 stably expressing AT1R-APEX2 were treated with the full agonist Ang II, a partial agonist, two G-protein-biased agonists and two β-arrestin-biased agonists [91]. Biotin labeling was activated 1.5 min, 10 min, and 1 h after receptor activation. Controls included ligand-free cells with and without biotin labeling and cells treated with a receptor blocker. In order to compare the signaling landscape for all treatments at each time point, TMT-based quantitative proteomics was performed to enable parallel and quantitative analysis of the AT1R signaling landscape in all treatments through a single MS analysis. This study has provided novel functional insights into AT1R-biased signaling and ligand-dependent receptor trafficking patterns and kinetics. For instance, G-protein-biased ligands were found to be associated with receptor trafficking to endosomes, lysosomes, and clathrin-coated vesicles, while β-arrestin-biased ligands were associated with proteins involved in F-actin cytoskeleton remodeling, membrane ruffling, lamellipodium and, interestingly, the centrosome, suggesting the potential involvement of AT1R in cell cycle regulation [91]. To our knowledge, APEX-MS is currently the only platform that allows the identification and quantification of GPCR signaling components within a native condition in an unbiased, medium- to high-throughput fashion. However, the GPCR APEX is still in its infancy as, in all studies reported so far, the experiments were performed in a cell model system, with exogenous expression of the APEX-tagged receptor and treatment of the cells with high doses of agonists. This may result in protein interactions or signaling events that may not happen in more physiologically relevant settings. The next step is for such an experiment to be performed in primary cells and with tagged proteins expressed at the endogenous level. For instance, β2AR APEX could be performed in iPSC-derived cardiomyocytes expressing APEX-tagged receptors where the receptor function is of importance, and its interactome could be studied in parallel with β1AR APEX in normal and disease conditions. Moreover, the platform can also be utilized to study organelle-resident GPCRs. For instance, more than 40 functional nuclear GPCRs (nGPCRs) have been identified in several cell types, and there is a growing body of evidence supporting a pathological role for these receptors in the cardiovascular and nervous systems [81,93]. However, the exact signaling landscape and downstream targets of nGPCRs require further investigation. The APEX-MS could provide a platform to identify and discriminate, for instance, the nuclear receptor signaling components from cell membrane receptor signaling components, without the need to biochemically isolate the nucleus, paving the way for organelle-specific drug development. One of the key aspects of cAMP signaling compartmentation is the anchoring of PKA holoenzymes in proximity to the source of cAMP production and/or to their substrates, which is achieved via PKA binding to AKAPs [94]. Proteins in the AKAP family can roughly be divided into three categories: RI-specific AKAPs, RII-specific AKAPs and dual-specificity AKAPs, which can anchor both RI and RII, although with rather different affinities. The AKAP-PKA interaction is based on binding between an amphipathic α-helix in the AKAP and a complementary surface formed by a dimer of R subunits and involving the dimerization-docking domain located at the N terminus of R [95]. AKAPs also serve as scaffolds that assemble into the cAMP signaling complexes’ signal terminators, such as protein phosphatases and PDEs, as well as additional kinases and other signaling proteins. Owing to the AKAPs’ diverse subcellular localization and ability to assemble multiple signaling components, customized cAMP signaling units can then be arranged at specific local sites. The functional importance of AKAPs in organizing cAMP local domains is supported by several meta-analysis studies that identify a link between SNPs and mutations in AKAPs with increased risk of diseases [96,97,98,99]. In one example, an SNP that results in one amino acid change from isoleucine to valine in the anchoring domain of AKAP10 was shown to reduce RI-binding affinity by 3-fold. The isoleucine variant was unable to target RI to mitochondria, resulting in RI accumulation in the cytosol [96]. In another example, the cardiac AKAP Yotiao, harboring a single mutation that disrupts its interaction with the PKA-modulated I(Ks) potassium channel, was demonstrated to eliminate the functional response of the channel to cAMP, causing long QT syndrome [100]. Alterations in AKAP expression levels and interactions have also been associated with pathologies, including heart failure [101], disorders of the nervous system [102] and male infertility [103]. Over the past decade, studies have evaluated selective targeting of individual AKAP signaling complexes as a strategy to manipulate cAMP-mediated cellular events in diseases [8], with the view that this approach would cause only ultra-fine changes at the relevant signaling complex without affecting other cellular functions. This line of investigations has driven the development of fundamental knowledge, especially of the architecture of individual PKA-AKAP signaling complexes, in physiologically relevant systems under normal and pathophysiological states. Proteomics offers a powerful set of tools for AKAP research, starting from the cAMP-centric proteome-wide screening of the cAMP interactome in a given cell or tissue to the identification of an AKAP’s anchoring landscape. The chemical proteomics platform based on cAMP affinity chromatography was developed to purify cAMP primary interactors (e.g., PKA isoforms, EPACs and PDEs) from a lysate of any origin. At the same time, secondary interactors (e.g., AKAPs, and PKA substrates) could be co-purified [104,105,106,107]. The enrichment of the co-purified proteins represents solely their association with R isoforms and not the expression levels, as in the case of primary interactors. The method makes use of different synthetic cAMP-analog resins that show different affinities toward PKA isoforms, PDEs and other primary interactors [108,109]. When combined with quantitative mass spectrometry, the method provides cues for profiling dynamic rearrangements of signaling scaffolds in response to stimulation or diseases [101,110,111]. For instance, cardiovascular conditions are often associated with inappropriate activation of blood platelets. An increase in intracellular cAMP was shown to interfere with platelet activation via PKA-mediated phosphorylation events impacting the organization of the platelet cytoskeleton [112]. Evaluation of the differential cAMP interaction landscape of resting and stimulated platelets revealed the cAMP signaling domain(s) involved in the inhibition of platelet activation. The cAMP interactome was enriched using cAMP resins from resting-state, and collagen-stimulated platelet lysates and quantitative LC-MS/MS analysis were conducted on differentially dimethyl-labeled peptides. The platform first identified the landscape of the cAMP interactome in platelets, consisting of three PKA isoforms (PKA-RIα, RIIα and RIIβ) and seven AKAPs. Stimulation led to increased anchoring of PKA-RII to AKAP2 and AKAP9 [110], suggesting the involvement of these PKA-AKAP pools in the inhibition of platelet activation. In another example, the same platform was used to investigate altered PKA signaling complexes in heart failure (HF) [101]. The study design involved a comparison of enriched cAMP interactors from normal and end-stage failing human heart tissues in a label-free fashion. Since R subunits were found to be down-regulated in failing hearts, enriched AKAPs were then normalized against their preferred R isoform before comparison to the healthy control. The study revealed extensive reorganization of PKA associations to AKAPs and their substrates. In failing hearts, a much larger population of R was found to associate with AKAP18 γ/δ, PALM2-AKAP2 and SPHKAP. Additionally, an increase in MAP2-RII and a decrease in Yotiao-RII interactions were observed. This type of information may offer a starting point for the development of specific therapeutics to locally rescue dysfunctional signaling at specific scaffolds. The analysis also revealed a decrease in the enrichment of several myofibrillar PKA targets (e.g., troponin I, titin and cardiac myosin binding protein C) from the patient materials, suggesting an uncoupling of the myofibril pool of PKA from their substrates [113]. The cAMP-centric chemical proteomics screening approach can provide insight into which PKA-AKAP scaffolds might underlie the physiological process or pathological condition of interest. To further characterize the molecular composition of a relevant cAMP signaling domain, interaction proteomics can be applied by using the scaffold protein as bait. For example, SPHKAP was among the AKAPs that showed a dramatic increase in association with PKA in HF [101], suggesting an important role for this AKAP in cardiac pathophysiology. SPHKAP was discovered by cAMP affinity chromatography as a novel and highly abundant AKAP in the heart [104]. Later, its affinity to RI was established, making it the first RI-specific AKAP ever identified in mammalian species [114]. To gain more insight into its function, AP-MS was employed to reveal the SPHAKP anchoring landscape. Anti-flag affinity resins were used to capture flag-SPHAKP interacting proteins in HEK293 cells expressing flag-SPHKAP. Enriched proteins were identified by LC-MS/MS and compared, by a spectral counting method, to the proteins identified from the control experiment performed using empty vector-transfected cells. Strongly enriched with SPHKAP were RI and several members of the MICOS, a mitochondrial inner membrane complex involved in the formation and maintenance of mitochondrial cristae, and several mitochondrial outer membrane proteins that together form the mitochondrial intermembrane space bridging (MIB) complex [115]. The detection of SPHKAP in the mitochondrial intermembrane space in cardiac myocytes and the identification of MICOS proteins as PKA substrates [115,116] indicate that SPHKAP scaffolds RI at the MICOS/ cristae domain. AKAPs contain targeting domains to anchor PKA to distinct subcellular compartments and in proximity to specific substrates. In different cell types, the same AKAP can be found at different cellular locations, engaging with different sets of proteins to serve different functions. For instance, in cardiomyocytes, AKAP18γ/δ localizes to the sarcoplasmic reticulum, where it scaffolds PKA with the Ca2+ pump SERCA-PLN complex to regulate adrenergic effects on Ca2+ re-uptake [117], while in renal collecting duct cells it targets PKA to aquaporin 2 (AQP2)-bearing vesicles, to regulate shuttling of the water channel from the cytosol to the plasma membrane [118]. Endogenous AKAP18γ was found in both the nucleus and cytoplasm of oocytes [119]. However, the exact function of the cytosolic and nuclear pools of the AKAP is unclear. Mapping the anchoring landscape of specific AKAPs is a valid approach to defining the specific function of a specific cAMP signaling domain. As a proof of concept, AKAP18γ was modified to localize either to the nucleus or the cytoplasm. The nuclear and cytosolic AKAP18γ were tagged with miniTurbo biotin ligase, overexpressed in HEK293T cells, and BioID-MS was performed in a label-free fashion to identify and compare the proximal proteomes of the two AKAP18γ pools. The cytosolic pool of AKAP18γ was shown to associate with proteins involved in the cell cycle and regulation of translation, while the nuclear pool was specifically associated with the RNA splicing machinery [98]. Even though the identification of components of AKAP signaling scaffolds in cell models can yield insights into the potential cellular function regulated by that complex, one should bear in mind that this role may be cell-type and/or cellular-state specific. Thus, experiments performed using physiologically relevant cells, and tissues are recommended. For AKAPs where a specific antibody is available, the signaling complex can then be studied directly in an endogenous context. For instance, AKAP12 is required to promote endothelial cell migration through unknown mechanisms. In order to identify components of the AKAP12-associated cAMP signaling domain involved in the regulation of cell migration, immunoprecipitation was performed by incubating an AKAP12-specific antibody or control IgG with the lysate from human endothelial cells where migration had been triggered by treatment with vascular endothelial growth factor (VEGF). Enriched proteins were analyzed by LC-MS/MS, and comparison was performed using the LFQ approach. The study revealed that, in migrating endothelial cells, endogenous AKAP12 was strongly associated with multiple key regulators of actin dynamics and actin filament-based movement and the VEGF stimulation was translated, via PKA-mediated phosphorylation events, into actin cytoskeleton remodeling and cell movement [120]. As mentioned earlier, AKAPs scaffold PKA holoenzymes with their substrates. This has led to the concept of AKAP-centric phosphoproteomics profiling to identify compartmentalized PKA phosphorylation events orchestrated by a specific AKAP. The RII-specific AKAP Cypher/ Zasp was shown to be strongly associated with dilated cardiomyopathy (DCM), and the cardiac L-type CaV1.2 calcium channel was the only known PKA effector regulated by this AKAP upon β-adrenergic activation [121]. To screen for additional cardiac PKA substrates regulated by Cypher, neonatal cardiac myocytes from wild-type and Cypher-KO mice were treated with isoproterenol to trigger β-adrenergic/PKA phosphorylation events before cell harvesting. Phosphopeptides were enriched from cardiac tissue digests by the TiO2 enrichment method and identified by LC/MS-MS in a label-free fashion. Compared to WT mice, the study identified 216 phosphopeptides differentially expressed in the Cypher-KO tissue, about half of which were down-regulated. In this case, the hypophosphorylated peptides that harbor a PKA consensus motif are likely to represent PKA-dependent phosphorylation events regulated by Cypher. These include β-catenin (Ser675), vimentin (Ser72), and the known PKA substrate Troponin I (Ser23/24) [122]. The study led to several discoveries, including a novel role for Cypher in the modulation of β-catenin transcriptional activity and cardiomyocyte proliferation via β-catenin phosphorylation [122]. This discovery highlighted a signaling crosstalk between the Wnt/β-catenin and the cAMP signaling pathways, possibly mediated by the colocalization of Cypher, vimentin and integrin β1 at the costamere [122]. The principal intracellular target for cAMP is PKA. PKA activation requires cooperative binding of cAMP to two sites on each R subunit. Upon binding of four molecules of cAMP, the catalytic subunits are freed from the inhibitory action of R subunits and phosphorylate nearby substrates at serine/threonine residues located within the consensus amino acid sequence (R/K)-(R/K)-x-(pS/pT), where x is any amino acid [123,124]. Besides serving as a cAMP binding site, the R subunit can be considered as an adaptor that tethers bound C subunits to distinct subcellular sites near their protein targets. cAMP binding to R subunits is thought to release active C subunits, raising the question of how specificity is maintained when the active C subunit is no longer attached to the AKAP scaffold. A study in living neurons may provide cues to this conundrum [125]. Upon activation, only a fraction of Cα was dissociated from anchored holoenzymes. The freed Cα was preferentially translocated to the membrane via the myristoylation of its N-terminus, enabling phosphorylation of membrane-bound substrates [125]. However, how the C subunit is uncoupled from the membrane for signal termination remains unknown. Contrary to current dogma, recent studies in Scott’s laboratory indicate that local PKA action can proceed through intact holoenzymes [126]. In the case of the PKA type II-AKAP79 complex, a substantial proportion of anchored PKA was shown to remain intact and proximal, within a distance of 15–25 nm, to anchoring sites and substrates [126], indicating that C phosphorylation activity may be more locally confined than previously appreciated. Interestingly, the dimension of anchored PKA action measured in this study is consistent with the estimated dimension of cAMP gradients shaped by PDEs (10–30 nm) [9,10]. As a major target of cAMP, it is safe to assume that PKA resides in a large proportion of functional cAMP signaling units. In a subcellular or suborganellar compartment where the cAMP interactome is not completely known, PKA can thus be used as a “proximity bait” to discover the landscape of cAMP signaling domains in that compartment. For instance, it is apparent that there are two separate cAMP signaling systems that operate on the surface of and inside mitochondria. The signaling cascades hosted at the outer mitochondria membrane are well established and are involved in the regulation of apoptosis and mitochondrial dynamics [127,128]. In contrast, the secluded intramitochondrial cAMP signaling system is still debated [129,130], even though all the components necessary to form cAMP functional domains have been identified within the organelle, potentially enabling intramitochondrial cAMP production in response to CO2/HCO3 [129]. Although components of the electron transport chain and TCA cycle have been hypothesized to be phosphorylated by a mitochondrial pool of PKA [129], studies aiming at the characterization of the intramitochondrial cAMP signaling landscape remain scarce, partly due to the difficulty of generating pure mitochondrial sub-compartment fractions. New insight was recently provided by the application of BioID-MS to characterize the PKA proximal proteome in the mitochondrial matrix [131]. First, the authors confirmed that a pool of Cα subunits is present inside the mitochondria in HeLa cells. Cα proximal proteins were enriched from cells overexpressing fusion proteins of the matrix-localized Cα and BioID2 (mt-PKA-BioID2). Cells transfected with empty vectors were used as a control. After quantification by spectral counting, 33 of the enriched proteins (~15%) were found to be mitochondrial, of which around 60% were predicted to harbor a PKA phosphorylation motif. These proteins are involved in various mitochondrial processes such as stress response, TCA cycle, protein synthesis and degradation. Interestingly, around two-thirds of the mt-PKA potential targets identified overlap with interactors of the prohibitin complex, an inner mitochondrial membrane ring-like structure important for cristae morphogenesis and functional integrity of the organelle [131]. These proteins could represent the intramitochondrial cAMP signaling domains. However, the question remains whether these predicted PKA targets are phosphorylated by the mitochondrial pool of PKA. Quantitative PKA phosphorylation profiling in the conditions that specifically lead to intramitochondrial cAMP production could help resolve this point. In addition, no expression of free biotin ligase was used in this experiment as a control, making it difficult to draw firm conclusions on the specificity of the interactions detected. Despite these caveats, this study provides an example of how compartmentalized cAMP signaling can be explored at subcellular locations where the cAMP interactome is uncharacterized. This type of study could be further developed to include quantitative PL-MS experiments using R or C isoforms targeted to specific locations. The use of appropriate controls would allow mapping of the PKA proximal proteome, including AKAPs, PKA substrates, as well as other components residing in the local signaling domains. A recent study from Scott’s laboratory demonstrated the use of this strategy to identify the local landscape of cAMP signaling events relevant to Cushing’s syndrome [132]. Somatic mutations L205R and W196R, found in the PRKACA gene encoding for PKA-Cα, were found to drive the overproduction of the stress hormone cortisol in this condition [132]. Mechanistically, the mutations were found to disrupt the binding of Cα to R subunits, resulting in the uncoupling of the C variants from AKAP scaffolds [132]. In order to gain insight into the new landscape associated with the disanchored C variants, the proximal proteomes enriched from adrenal cell lines stably expressing low level of a miniTurbo-tagged version of the two Cα mutants were compared with the proteome of wild-type C using an LFQ approach. Besides the expected reduced association with R and AKAPs, both variants revealed enrichment in different nuclear domains, including nuclear pore, inner nuclear membrane, spliceosomal complex, and histone modification, in agreement with imaging data showing a more pronounced nuclear localization of the C variants. In a general sense, a mislocalized active kinase can lead to non-physiological phosphorylation events, driving pathological consequences. In order to gain further insight into aberrant phosphorylation induced by the two mutations in Cα, phosphopeptides were enriched from each variant proximal proteome using an Fe-IMAC approach and compared with those of the WT enzyme. Apart from the expected decrease in phosphorylation in AKAPs, the two variants appeared to engage with different substrates and potentiate distinct downstream mitogenic signaling pathways [132]. Whether the abnormal phosphorylation pattern observed drives the pathological processes in Cushing’s syndrome remains to be established. Overall, this study highlights the importance of signaling compartmentalization and the power of proteomics approaches to help unravel aberrant signaling events. In a different paradigm, a comprehensive analysis of phosphorylation changes upon inhibition of PKA activity can uncover specific cellular processes selectively regulated by PKA. System-level phosphoproteomic profiling of a kinase-specific phosphorylation activity can be considered a large-scale proximity analysis where the kinase comes into physical contact with its substrates [133]. As a proof of concept, Knepper’s laboratory established a double Cα and Cβ knockout vasopressin-responsive mpkCCD cell lines, which they used as a collecting duct (CD) principal cell model to study vasopressin signaling [134]. Vasopressin binds to the vasopressin receptor (V2R), leading to an increase in cAMP production and PKA activation. The actions of vasopressin are associated with several physiological responses, including the regulation of the water channel aquaporin-2 (AQP2) to modulate osmotic water permeability in CD epithelia [133]. To identify vasopressin-mediated cellular processes that are regulated by PKA phosphorylation, the authors first identified PKA-dependent phosphorylation events in PKA-C KO cells. Phosphopeptides were enriched from light SILAC-labeled PKA-C KO and heavy SILAC-labeled PKA-intact mpkCCD cell lysates. Differentially regulated phosphorylation sites were classified according to the sequences surrounding the phosphorylated amino acids. As expected, down-regulated phosphorylation sites in double KO cells were predominantly PKA sites, although other basophilic kinase sites were also identified. Interestingly, most of the up-regulated sites were proline-directed kinase sites, suggesting that in CD cells, proline-directed kinases, such as MAP kinases, are negatively regulated by PKA, either directly or indirectly. The authors further mapped the differentially regulated phosphorylation events to known vasopressin-regulated physiological responses to build a PKA-dependent signaling landscape in response to vasopressin. Several key cellular processes were identified as PKA-regulated. These include transcriptional regulation of the AQP2 gene, AQP2 phosphorylation and translocation to the apical plasma membrane, AQP2 exocytosis, MAP kinase signaling, and actin dynamics [134]. The authors further investigated the PKA-dependent signaling landscape specific to Cα and Cβ. In native CD and mpkCCD cells, the two catalytic subunits are expressed at a comparable level, in keeping with the notion that they are functionally non-redundant [135]. To dissect the phosphorylation landscape associated with each catalytic subunit, Cα or Cβ knockout mpkCCD cell lines were generated [136]. Phosphopeptides were enriched from TMT-labeled knockout and PKA-intact cell lysates using a TiO2 and Fe-IMAC sequential enrichment method. As expected, the two kinases were shown to have a substantially different set of phosphorylation targets, with most of the PKA sites being found to be decreased in Cα-null cells. Interestingly, several differentially-regulated sites of PKA-RI and RII, AKAPs, and PDEs were identified in Cα-null cells, while only one site in AKAP12 was identified in Cβ null cells, suggesting that Cβ is less associated with PKA-AKAP complexes than Cα is. Cα targets were mainly associated with cell membranes and vesicles, whereas Cβ targets were related to the actin cytoskeleton and cell junctions [136]. If these findings are taken together, they indicate that the two catalytic subunits operate at discrete locations, engaging with distinct sets of local targets. Cα might be associated with a cAMP signaling domain in the AQP2 storage vesicles or at the apical membrane, while Cβ may operate at actin barrier domains. One can then utilize these two catalytic subunits as bait to dissect a specific signaling pathway in response to vasopressin. For example, a major element of vasopressin action in CD cells is the dramatic rearrangement of the actin barrier for proper trafficking of AQP2-bearing vesicles to the apical membrane [137]. The local signaling events that regulate actin barrier dynamics are a critical yet incompletely understood aspect of water homeostasis. To dissect the landscape of local cAMP/ PKA signaling involved in actin barrier remodeling, one could utilize Cβ as a bait protein for PL-MS analysis to identify the local signaling complexes/PKA effectors in the presence and absence of vasopressin stimulation. To further dissect the local cAMP domains specific to a specific stimulus, the list of PKA-dependent phosphorylation targets identified from such studies could be further examined in combination with the list of phosphorylation events that are differentially regulated in response to a ligand of interest (e.g., vasopressin, in the case of CD cell lines [138,139]). The level of cAMP is determined by the rate of synthesis by ACs and the rate of degradation by the cyclic nucleotide-hydrolyzing enzyme PDEs. There are eight different families of cAMP-degrading PDEs (PDE1, 2, 3, 4, 7, 8, 10, 11). PDE families include multiple genes and several splice variants, giving rise to multiple isoforms. PDE isoforms differ greatly in their tissue distribution, and multiple PDE isoforms can be expressed in an individual cell type [140]. Different PDE isoforms can be targeted to different subcellular compartments by targeting sequences or via interactions with local macromolecular complexes. Hydrolysis of cAMP is the only major mechanism to reduce the second messenger concentration, and by degrading cAMP to a different extent at different sites, PDEs play key roles in shaping and maintaining cAMP signaling compartmentalization. In fact, a large body of work demonstrates the role of PDEs in organizing cAMP signaling domains [141,142,143]. PDE enzymatic activity and PDE clustering, together with cAMP buffering, have been identified as key factors that contribute to the formation of local cAMP domains [10,144,145]. Using fluorescence resonance energy transfer (FRET)-imaging, different PDEs were demonstrated to organize differently scaled domains of nanometer size [10]. In such domains at basal state, a cluster of PDEs was shown to function as a local sink by actively degrading cAMP in their immediate vicinity. When cAMP production increases upon GPCR stimulation, the local PDE capacity is saturated, leading to local PKA activation and downstream signaling [10]. In another FRET-based study, it was observed that the cAMP synthesizes on stimulation of GPCR with low doses of agonist remains confined in the vicinity of the receptor thanks to the activity of local PDEs, generating a receptor-associated independent cAMP nanodomain, or RAIN, where anchored PKAs is strongly activated by a high concentration of local cAMP [9]. PDE inhibitors are currently in use to treat conditions that associate with the dysregulation of cAMP signaling, owing to the role of PDEs as signal terminators. For example, PDE3 inhibitors are used clinically for the treatment of acute, refractory heart failure. However, these drugs are associated with significant side effects [146,147], possibly due to their non-selective disruption of PDE3 activity in all domains where isoforms of this family operate, some of which could be vital for normal physiological function. In such a scenario, therapeutic strategies that specifically target only the unique pool of PDE isoforms that control the desired function would be ideal. For instance, displacement of a resident PDE from a local cAMP signaling compartment would result in a local increase in cAMP with restricted activation of PKAs only in that compartment and exclusive phosphorylation of neighboring targets. However, to be able to exploit compartment-selective displacement of individual PDEs for therapeutic purposes, a blueprint of which cAMP signaling compartments are regulated by which PDE isoform and a detailed understanding of how the PDE is retained in that compartment are required. PDE-selective inhibitors have been exploited to study the roles of different PDEs in the regulation of cyclic nucleotide signaling. A collection of inhibitors highly selective for each PDE family is commercially available [87]. These inhibitors can be used in combination with quantitative phosphoproteomics to interrogate phosphorylation events regulated by each PDE family. For example, work by Ong’s and Beavo’s laboratories used PDE-centric profiling of cAMP-mediated phosphorylation after treatment with family-selective PDE inhibitors, with or without a receptor agonist co-stimulation, to increase local cAMP signals and generate changes in phosphorylation events on the target proteins in the vicinity of the PDE [71,72,148]. This platform was used to profile cAMP-mediated phosphorylation events involved in steroidogenesis in the mouse cell line MA-10 [71]. An increase in cAMP levels upon lutropin-choriogonadotropin hormone receptor (LHCGR) activation is known to induce steroidogenesis, although the cAMP signaling events involved in this regulation are not fully understood. It was found that in MA-10 cells, only the co-inhibition of PDE4 and PDE8 was able to increase the intracellular cAMP level as observed after LHCGR activation, even though to a lesser extent [71]. In order to investigate cAMP signaling events in a condition that mimics LHCGR receptor activation, two overlapping sets of experiments were carried out in triple SILAC-labeled MA-10 cells. The first set included individual SILAC (light, medium, heavy) labeled cells treated with DMSO control, PDE4 inhibitor and a combination of PDE4 and PDE8 inhibitors. The second set was designed to compare DMSO control, PDE8 inhibition, and co-inhibition. For each experiment, individual SILAC-labeled lysates were combined, digested, and phosphopeptides were enriched using an Fe-IMAC approach. The study reported a rich dataset, including the identification of ~28,000 phosphorylation sites in ~14,000 different phosphopeptides derived from ~5000 proteins. Among the regulated sites, ~23% were identified as PKA sites, suggesting that multiple kinase-dependent pathways acted downstream of PKA. This study demonstrates how the identification of cAMP-mediated phosphorylation events can be used to construct an atlas of (PDE-regulated) local PKA activity, which, in the case of MA-10 cells, includes a great number of functional compartments involved in the regulation of cell cycle, insulin receptor signaling, transcription, endocytosis, vesicle trafficking and others. In addition, the identification of unique PDE8-regulated phosphorylation sites suggested the distinct role of this PDE in apoptosis signaling. In another study, this quantitative phosphoproteomics platform was used to characterize, in label-free experiments, the PDE-regulated phosphoproteomes in the T lymphocyte cell line Jurkat treated with various combinations of PDE inhibitors and a low concentration of prostaglandin 2 [72]. Treatment with individual PDE inhibitors was not sufficient to induce changes in total cAMP or phosphorylation events, and simultaneous inhibition of multiple PDEs was required to obtain such a change. Different combinations of PDE inhibitors were found to impinge on distinct pools of cAMP, in turn regulating different cellular functions. For example, several functional compartments involved in the regulation of RNA metabolism were controlled by PDE1, 7, and 8, while the nuclear domains involved in histone trimethylation and DNA repair were modulated by PDE3 and 4 [72]. One of the key advantages of using this platform lies in the unbiased identification of regulated phosphorylation events and the sheer number of phosphorylation sites identified. Potentially, this platform can be utilized in preclinical screening to determine the possible collateral adverse effects that might be originated from the inhibition of PDE(s). One limitation of the PDE family-centric phosphoproteomics profiling described above is that it does not provide insight into the specific role of individual PDE isoforms, as there are no available isoform-selective PDE inhibitors. The analysis of PDE isoform-selective interactomes, however, can overcome this shortcoming, and by cross-referencing the PDE family–dependent phosphoproteome with the PDE isoform-specific interactome, a more detailed view of the full cellular landscape of cAMP signaling events in response to specific receptor activation should be attainable. This information could then be used as a starting point to design single-domain targeting interventions, e.g., based on individual PDE isoforms displacement, to raise cAMP only at specific locations, resulting in highly targeted functional effects. Surprisingly, data on a PDE isoform-selective interactome are very scarce. The analysis of the interactions in which a PDE isoform is involved is critical to link a specific enzyme with specific cellular responses. For example, treatment with an AC agonist, ectopic expression of PKA Cα, or pharmacological inhibition of endogenous PDE2A activity were shown to impair translocation of the ubiquitin ligase Parkin, a key effector of mitophagy to depolarized mitochondria, hence inhibiting mitophagy [149,150]. Of the three PDE2A isoforms, only isoform 2 (PDE2A2) is localized to mitochondria. In an attempt to define the mitochondrial target(s) involved in the PDE2A2/cAMP/PKA-dependent regulation of mitophagy, we performed a strep-tag-based AP-MS analysis to identify the interactome of PDE2A2 (Figure 5) [149]. Enriched proteins from strep-tagged PDE2A2 expressing cells were quantified against those from control cells expressing an irrelevant protein containing strep tag by the LFQ method. As expected, we found multiple mitochondria-resident proteins enriched in the PDE2A2 pull-down. The PDE2A2 interactome included the MIB complex (Figure 5), a core component of which is mitofilin (IMMT), which had been previously identified as a PKA target [116]. PKA phosphorylation of mitofilin was shown to be involved in Parkin recruitment to damaged mitochondria [116]. The study further demonstrated that PDE2A2 regulates a pool of mitochondrial cAMP that enables PKA-dependent phosphorylation of mitofilin, thus promoting Parkin recruitment and mitophagy. The study also demonstrates, as a proof of concept, that the analysis of PDE isoform-specific interactomes can effectively identify the isoform-associated cAMP signaling compartments. Interestingly, the analysis also revealed the enrichment of several members of the endosomal sorting complex required for transport (ESCRT) and autophagosome formation (Figure 5). The future challenge will be to establish whether distinct pools of PDE2A2 participate in the different complexes and to resolve the PDE2A2-regulated phosphorylation events and cellular targets involved in the ESCRT-dependent and autophagy processes. However, this study clearly demonstrates that individual PDE isoforms can be involved in the organization and regulation of multiple cAMP signaling domains at different locales within the same cell. As more information becomes available on how cAMP/PKA signaling exploits compartmentalization to translate individual signal inputs into the appropriate functional outputs and how such organization is disrupted in disease, it also becomes apparent that the highly structured architecture of this signaling pathway provides extraordinary potential for the development of targeted interventions to normalize signaling only where required, without perturbing the entire network. The ability of PL-MS techniques to capture both stable, weak and/or transient PPIs in combination with state-of-the-art phosphoproteomics profiling technologies offers a powerful toolbox for resolving in detail the map of the cellular cAMP signaling landscape, both in physiological and pathological conditions. For example, PKA-R and/or PKA-C PL-MS can be performed to uncover the full repertoire of PKA signaling domains in the cell overall (Figure 6A). For a more targeted study, AKAP-centric and PDE isoform-centric PL-MS can be performed to gain more detailed insights into the subcellular distribution and regulation of individual domains (Figure 6B,C). Downstream signaling events regulated by specific AKAP or PDE can be identified by quantitative phosphoproteomics profiling in combination with specific AKAP gene knockout, use of AKAP-PKA disrupting peptides or PDE-family inhibitors (Figure 6D). Changes in phosphorylation events determined in these studies pinpoint the protein targets that can be mapped to specific domains and provide insight into the cellular function under the control of that specific domain. The information obtained from the analysis of the interactome and of the phosphoproteome can be combined to draw robust conclusions on the composition and function of individual cAMP signaling domains. The map of the cAMP signaling landscape generated in this way can then be used to reveal potential protein targets or protein interactions that can be targeted to manipulate local signaling via domain-specific intervention. Several strategies have been proposed to intervene in discrete cAMP domains. Synthetic peptides mimicking the A-kinase binding domain of AKAPs have been developed to displace PKA from the AKAP scaffold [150,151,152]. These disrupting peptides are usually PKA-R isoform selective since they are all designed to interact with the same surface on the D/D domain of either RI or RII. These peptides represent useful tools to selectively probe anchored PKA signaling events in the laboratory [153] but have limited use as therapeutics since they interfere with multiple PKA-AKAP complexes. Knockdown of specific AKAPs to disrupt a specific signalosome may lead to more extensive effects than those desired as not only the PKA but also other signaling molecules brought together to the domain are also displaced (Figure 6D, blue box). A more selective strategy would be to locally modulate cAMP signals at specific domains by targeting the local PDE. Generally, PDE isoforms localize to different subcellular locations by protein interaction with AKAPs or other domain components. With the cAMP signaling map at hand, one can design a targeted intervention to increase cAMP signals/ phosphorylation of target proteins by displacement of local PDEs from specific signaling domains using disrupting peptides (Figure 6E, yellow box). This strategy has been validated in experiments where a synthetic peptide encompassing a stretch of amino acids in PDE4D5 involved in its binding to HSP20 was used to disrupt the PDE4D5/HSP20 interaction, leading to an increase in PKA phosphorylation of HSP20 and attenuated β-agonist-induced hypertrophy in neonatal cardiac myocytes [154]. Future studies will no doubt provide further details on the molecular composition, functional role and regulation of the multiple cAMP signaling domains in specific cell types and on how the cAMP signaling landscape is remodeled in disease. The already rich proteomics toolbox will see new developments and will significantly contribute to progress in this field, ultimately offering rational ground for the design of therapeutics that target molecular mechanisms with subcellular precision.

PMC10003372

Elisa Parciante,Cosimo Cumbo,Luisa Anelli,Antonella Zagaria,Immacolata Redavid,Angela Minervini,Maria Rosa Conserva,Giuseppina Tota,Nicoletta Coccaro,Francesco Tarantini,Crescenzio Francesco Minervini,Maria Giovanna Macchia,Giorgina Specchia,Pellegrino Musto,Francesco Albano

The Role of NLRP3, a Star of Excellence in Myeloproliferative Neoplasms

02-03-2023

myeloproliferative neoplasms,nucleotide-binding domain (NOD)-like receptor protein 3,inflammasome

Nucleotide-binding domain (NOD)-like receptor protein 3 (NLRP3) is the most widely investigated inflammasome member whose overactivation can be a driver of several carcinomas. It is activated in response to different signals and plays an important role in metabolic disorders and inflammatory and autoimmune diseases. NLRP3 belongs to the pattern recognition receptors (PRRs) family, expressed in numerous immune cells, and it plays its primary function in myeloid cells. NLRP3 has a crucial role in myeloproliferative neoplasms (MPNs), considered to be the diseases best studied in the inflammasome context. The investigation of the NLRP3 inflammasome complex is a new horizon to explore, and inhibiting IL-1β or NLRP3 could be a helpful cancer-related therapeutic strategy to improve the existing protocols.

The Role of NLRP3, a Star of Excellence in Myeloproliferative Neoplasms Nucleotide-binding domain (NOD)-like receptor protein 3 (NLRP3) is the most widely investigated inflammasome member whose overactivation can be a driver of several carcinomas. It is activated in response to different signals and plays an important role in metabolic disorders and inflammatory and autoimmune diseases. NLRP3 belongs to the pattern recognition receptors (PRRs) family, expressed in numerous immune cells, and it plays its primary function in myeloid cells. NLRP3 has a crucial role in myeloproliferative neoplasms (MPNs), considered to be the diseases best studied in the inflammasome context. The investigation of the NLRP3 inflammasome complex is a new horizon to explore, and inhibiting IL-1β or NLRP3 could be a helpful cancer-related therapeutic strategy to improve the existing protocols. Myeloproliferative neoplasms (MPNs) are a set of uncommon, neoplastic blood disorders that affect the bone marrow. They are characterized by a set of mutations in the hematopoietic stem cells and progenitor cells (HSPCs), from which erythrocytes, leucocytes and platelets are derived. They are genetically extremely varied and exhibit an aberrant HSPC unregulated proliferation and/or an inhibition of the differentiation in the bone marrow (BM) [1,2,3]. Inflammatory conditions in the BM can lead to DNA mutations and genomic instability, which contribute to or cause the initial impact on the hematopoietic stem cells and trigger the clonal evolution-related mutations in the MPN [4]. The cancerous cell can change the niche to its advantage and at the expense of healthy HSPCs [5]. As a result, the blood cells proliferate out of control [6]. Polycythemia vera (PV), essential thrombocytemia (ET), primary myelofibrosis (PMF) and chronic myeloid leukemia (CML) are examples of MPNs. They are identified by a rise in erythrocytes, platelets, and bone marrow fibrosis, respectively [7]. CML, associated with the Philadelphia chromosome and sometimes even genomic deletions [8,9], is characterized by a clonal myeloproliferation, leading to a marked overproduction of both mature and immature granulocytes [10]. Some individuals develop PMF during the progression of PV and ET, which is frequently accompanied by complications such as thrombosis or hemorrhages. The worst possible outcome is the development of acute myeloid leukemia (AML) [6]. Somatic mutations in the JAK2 gene (exon 12 or 14), the CALR gene (exon 9) or the MPL gene (exon 10) are found in MPNs. The point mutation in exon 14 of the JAK2 gene is the most frequent genetic change that can be discovered in these entities (JAK2V617F) [11,12]. The MPL/JAK/STAT signaling pathway is constitutively activated by JAK2V617F, MPL mutations at position W515 (in the juxtamembrane domain), and pathologic CALR mutations that are out-of-frame insertions and/or deletions yielding a new C-terminal peptide [13,14]. In addition to these driver mutations, 10–15% of MPNs are classified as triple negative and typically have a worse prognosis since they lack any of these prevalent mutations [15]. Additional mutations contribute to the development of the disease by increasing the cell self-renewal and preventing differentiation, including those in the linker proteins (IDH2, SH2B3, and CBL), spliceosomal components (SRSF2, U2AF1, and SF3B1), epigenetic modifiers (specifically ASXL1, TET2, and EZH2), and metabolic modifiers [16]. In addition to the JAK2/MPL/CALR “driver” alterations, the latter are present in most MPNs [17]. Surprisingly, they seldom develop during the progression and frequently exist during the diagnosis [18]. This wide variety of genetic abnormalities in MPNs appears to contribute to the inflammasome activation. Depending on the mutational setting, the influence of the inflammasome on leukemogenesis can either promote or prevent leukemia. The context-dependent and tissue-specific character of such cytokines is probably the cause for their seemingly incongruous roles in tumor progression and antitumor immunity [19,20]. The presented work aims to investigate the role of NLRP3 in MPNs as a new horizon to ensure a more significant and accurate assessment of these disorders, paving the way for several novel therapeutic options. In 2015, Hasselbalch and Bjørn combined the epidemiological, biochemical, pathogenetic, and clinical evidence, considering MPN as an inflammatory disorder—a paradigm of the relationship between chronic inflammation and oncogenesis [21]. Chronic inflammation is widely recognized as one of the main initiators of vascular damage, specifically endothelial injury [22]. The inflammatory state of the vascular system appears to be brought on by driver mutations, particularly those in the JAK2 gene [23]. Chronic non-neoplastic inflammation caused by autoimmune diseases or recurrent infections leads to a steady release of pro-inflammatory cytokines such as TNFα, IL-6, and IL-8, as well as an accumulation of reactive oxygen species (ROS), which in turn promote the growth and spread of cancer by causing genetic instability and oxidative stress and blocking the apoptosis program and cell migration [24]. MPNs frequently result in a rise of these three inflammatory cytokines [23]. Among the pro-inflammatory ones, the most significant is IL-1β, which has been linked to the MPNs pathogenesis and its role in niche remodeling [25,26]. IL-1β modulates the gene expression related to the fever, vasodilation, and hypotension [27]. A recent study found that the ablation of IL-1β in MPN mice reduced the severity of the disease, concluding that IL-1β encouraged the clonal proliferation of HSPCs with the JAK2 mutation [28]. Additionally, the JAK2V617F mutation, together with an inflammatory milieu, enhances MPN development. By secreting cytokines and activating the bystander immune cells, the malignant JAK2V617F mutant cells also contribute to the inflammatory microenvironment. the higher expression of the JAK2V617F mutation on the endothelial cells of MPN patients causes increased inflammation and permeabilization of the vascular bed, a reduction in the cell development and a more rapid cell senescence. This suggests that MPN cells change the immediate local environment to promote their growth and limit that of their normal counterparts [22,29,30,31]. Therefore, the inflammatory milieu induces death and cell cycle arrest in wild-type cells while favoring the proliferation of JAK2V617F mutant neoplastic hematopoietic stem cells. Hence, the relationship between chronic inflammation and MPN development becomes evident. Recent studies have revealed that inflammation, based on the pathophysiology and development of myeloid malignancies, is mediated by the innate immune system. The innate immune system’s multiprotein cytosolic oligomers are inflammasomes and are responsible for triggering inflammatory reactions [27]. Myeloid cells, especially macrophages, are the primary cell types involved in the inflammasome assembly [32]. The prevalence of MPNs in patients was higher in those with autoimmune or inflammatory conditions [33,34]. The innate immune system interacts with various pattern recognition receptors (PRRs) to find the microbial contamination or tissue injury. PRRs can identify features that are common to multiple microbial species or endocrine substances produced by cell and tissue injury, both of which are referred to as pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs) [35]. The PAMPs or DAMPs are recognized by monocytes, macrophages, neutrophils, and dendritic cells [36]. There are four distinct classes of PRR families, which include cytoplasmic proteins such as retinoic acid-inducible gene (RIG)-I-like receptors (RLRs), nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs), transmembrane proteins such as the toll-like receptors (TLRs) and C-type lectin receptors (CLRs) [35]. The TLRs and their signaling pathways molecules TNFR1, TNFR2, and CD95, as well as the other important innate immune regulators, are upregulated or constitutively activated in HSPCs [37,38]. This suggests that these molecules play a significant role in developing myeloid malignancies. The dysregulation of these molecules causes aberrant hematopoiesis, imbalanced cell death, and a proliferation in patients’ bone marrow [39]. Among them, the NLRs appear to have a more prominent role in persistent non-infectious sterile inflammation than any other innate immune receptor molecule [40]. Most of these can assemble into the inflammasome complexes, including NLRP3, NLRP1, NLRP6, NLRC4, NAIP, AIM2, and pyrin [41], but NLRP3 is the undisputed protagonist of the inflammasome, involved in numerous cancers. Cell death and inflammation are controlled by the NLRP3 inflammasome regulation [42]. NLRP3 inflammasomes are also essential for tumor-specific adaptive immunity. As evidence of this, the lack of a functioning NLRP3 inflammasome in the mouse model failed the CD8+ T cell priming [43]. The analyzed data showed a close relationship between NLRP3 inflammasomes and carcinoma susceptibility, progression, and prognosis [44]. Inflammation, vascular damage, and dysimmunity were all strongly correlated. It has long been understood how the innate immune system and the equilibrium of pro- and anti-inflammatory cytokines affect endothelial functions [45,46]. The ability of immune dysregulation in cancer to produce a favorable milieu that allows for immunosurveillance escape and tumor growth has been identified as a hot topic of research. MPNs are an excellent example of inflammatory disease and a helpful model for analyzing the links between clonal proliferation, immunological tolerance loss, and chronic inflammation. NLRP3 is an inflammasome molecule that can detect multiple hosts and external ligands [47]. It is a cytosolic receptor, now known as the most researched member of the inflammasome family. It is expressed in HSPCs and peripheral blood cells [48]. The NLRP3 gene, found on chromosome 1, codes for the NLRP3 inflammasome, also known as cryopyrin, and is expressed in several cells involved in the innate immune response, including monocytes, neutrophils, lymphocytes, epithelial, and endothelial cells. The NLRP3 protein is composed of a leucine-rich repeat (LRR) domain at the C-terminus, a nucleotide-binding oligomerization (NOD or NACHT) domain in the middle, and a pyrin (PYD) domain at the N-terminus [49]. The protein structure is described in detail in Figure 1. According to a recent publication, the PYD domain is a desirable target for developing NLRP3 inhibitors due to its significance in activating the NLRP3 inflammasome [50]. After identifying the pathogens and other damage-related signals, the NLRP3 protein interacts with the ASC via its pyrin domain which binds pro-caspase-1, and converts pro-IL-1β and pro-IL-18 into their active forms. These cytokines have a pleiotropic effect on hematopoiesis, aging, and metabolic complications [51,52]. The proteolytic cleavage, maturation, and secretion of IL-1β and IL-18, as well as the cleavage of gasdermin-D (GSDMD), a specific substrate of the inflammatory caspases, are all encouraged by the inflammasome activation and assembly. This cleavage produces an N-terminal fragment that triggers pyroptosis and the generation of the cell membrane holes, causing severe membrane damage and the release of cytokines and proteins from the cytoplasm. Pyroptosis, a pro-inflammatory form of programmed cell death, affects tumor growth and aggressiveness [53,54]. NLRP3 drives this phenomenon through cell lysis and burst cell membranes. Inflammasome-mediated pyroptosis aids in the host’s defense against bacterial infections, but an unchecked process increases the risk of multiple organ failure, disseminated intravascular coagulation, and death [55]. The dying cells secrete the DAMPs, and this positive feedback loop process causes an even worse inflammatory response [56]. The NLRP3 inflammasome can be activated through a canonical, a non-canonical, and an alternative pathway. A two-step mechanism is involved in the canonical signal, in the macrophages, and the dendritic cells [57,58]. The first one, also known as the “priming step” or “signal 1”, is produced by the endogenous cytokines, PAMPs, and inflammatory stimuli such as TLR4 agonists, which cause an NF-κB-mediated NLRP3 and pro-IL-1β and pro-IL-18 expression [54]. The NF-κB-induced transcriptional priming of inflammasome proteins sets the stage for the cation channel activation, cell volume expansion, and the inflammasome component assembly [59,60]. The post-translational modifications occur during this phase. The second step, known as the “activation step” or “signal 2”, is brought on by the PAMPs, DAMPs, or glucose and amino acid efflux, which facilitates the assembly of the NLRP3 inflammasome and caspase-1-mediated IL-16 and IL-18 secretion [54]. Many NLRP3 activators induce a K+ efflux, the common trigger of the inflammasome [61]. A non-canonical and alternative pathway can turn on NLRP3 with LPS as the main trigger. The non-canonical response depends on casp-4/5 or casp-11. It has been noted that intracellular LPS directly binds to the CARD domain of casp-11 [62] and casp-4 [63], activating both, and hence these can be triggered by exogenous substances and other parts of gram-negative bacteria [64]. Both can enhance a K+ efflux, leading to the activation of the NLRP3 inflammasome, rupturing the membrane through either GSDMD cleavage and subsequent pyroptosis or currently unknown mechanisms [63,65]. In the alternative NLRP3 pathway, LPS/TLR4 alone is sufficient to cause the NLRP3 inflammasome activation through the caspase-8 signaling cascade upon TLR4/TRIF/FADD. This drives caspase-1 to become active and IL-1β to be processed and secreted. A K+ efflux is not essential for this pathway; IL-1β is secreted gradually and pyroptosis does not occur [66]. NLRP3 can be enhanced by a variety of physically and chemically unrelated stimuli. The PAMPs are microbial, fungal, viral, and parasitic products released during infection. The DAMPs are released during non-pathogen-related “sterile inflammation”, resulting from tissue/organ damage under stress [67]. The DAMPs, such as extracellular alarmins like extracellular adenosine triphosphate (eATP), nuclear protein high mobility group protein B1 (HMGB1), uric acid crystals, extracellular DNA and RNA fragments, and S100 proteins (S1009a and S1008a), trigger this activation in a paracrine/autocrine manner [68]. The release of IL-1β and IL-18 stimulates the innate immunity cells, releasing the other DAMPs and starting the complement cascade (ComC) that maintains a sterile inflammation state in the BM microenvironment [68,69,70]. NLRP3 has been suggested as a sensor for cellular homeostasis [71], and it is regulated by the GAPDH and α-enolase, mTORC1, and HK1-dependent glycolysis [72]. The DAMPs-mediated calcium influx or potassium efflux, as well as the alterations in the uptake of glucose and amino acids, all cause the activation of the NLRP3 inflammasome [73]. Among the NLRP3 modulators, NIMA-related protein kinase 7 (NEK7), along with the inhibitor of nuclear factor kappa-B kinase (IKKβ), were recently discovered to be crucial parts of the NLRP3 inflammasome and an essential modulator of the NLRP3 activity [74,75,76]. As we have seen, the NLRP3 startup takes place under different fronts. Since it is considered the undisputed protagonist, based on numerous pathologies, one of the promising goals could be to consider the NLRP3 inflammasome complex as a potential therapeutic target, especially in the hematopoietic context. The role of the NLRP3 protein is now evident on several fronts. While some studies proposed a preventive role for the NLRP3 inflammasome [84], most contended that it contributes to cancer pathophysiology [85]. The role of NLRP3 is evident in several neoplasms. For instance, breast cancer growth and metastasis were boosted by the NLRP3 inflammasome produced by cancer-associated fibroblasts [86]. Several hematological diseases, such as myelodysplastic syndrome (MDS), myeloproliferative neoplasms, leukemias, lymphomas and graft-versus-host diseases (GvHD), are also impacted by the NLRP3 inflammasome [48,87]. In MDS, the hematopoietic stem/progenitor cells exhibit the NLRP3 complex activation, which produces IL-1β and IL-18, causing pyroptotic cell death [88]. IL-18, triggered by the NLRP3 inflammasome, is involved in hematopoiesis and is currently thought to be primarily a proinflammatory cytokine that regulates both the innate and adaptive immunity (essential for the synthesis of IFNγ) and has a role in the etiology of autoimmune and inflammatory illnesses [27,89,90]. Through the IFNγ expression, IL-18 suppresses the development of the erythroid colonies. On the other hand, IL-1R signaling decreases erythropoietin production in the kidney [91]. Zhou et al. provided the first evidence of a higher NLRP3 inflammasome-related gene expression in MPN patients. They carried out a study on bone marrow cells for some genetic polymorphisms affecting the inflammasome genes, such as NLRP3 (rs35829419), NF-κB1 (rs28362491), CARD8 (rs2043211), IL-1β (rs16944), and IL-18 (rs1946518). The analysis revealed an association between MPN and a higher expression of NLRP3, NF-κB1, CARD8, IL-1β, and IL-18. The NF-κB-94 ins/del ATGG (rs28362491) polymorphism contributed to the susceptibility of MPN and to the enhancement of NF-κB1 and the NLRP3 expression. Given that NF-κB signaling hyperactivation promotes chronic inflammation in MPN, there has been substantial discussion about the therapeutic benefits of targeting NF-κB in MPN. The elevated expression of these genes was connected to the JAK2V617F mutation, increased white blood cell counts, and splenomegaly [92]. Unlike the other genetic variations, the JAK2 kinase activity may have a significant role in triggering the NLRP3 inflammasome [93]. The JAK2V617F mutation has been shown to promote the onset and development of MPN by increasing the cytokine sensitivity, constitutive activation of JAK2 kinase and the JAK/STAT signaling, and the maintenance of the cytokine-dependent survival in the cell lines [94]. However, further research is required to confirm and describe the molecular function of the NLRP3 inflammasome in JAK2V617F-mutant MPN [92,93,94]. The NLRP3 inflammasome’s genetic polymorphisms in CML may be used as possible outcome predictors. More specifically, the association between the polymorphisms mentioned above and their influence on the first-generation tyrosine kinase inhibitor’s (TKIs) therapeutic effects has been evaluated [95]. Many TKIs stimulate the NLRP3 inflammasome system. Among these, both imatinib and masitinib induce lysosomal expansion and cause damage that results in the cathepsin-mediated membrane instability of myeloid cells and, subsequently, cell lysis that is followed by a potassium (K+) efflux. This activates NLRP3 through the cleavage of IL-1β, caspase-1, and GSDMD, as well as the formation of the ASC specks. This effect is restricted to the primary myeloid cells (such as the peripheral blood mononuclear cells and the mouse bone marrow-derived dendritic cells) [96]. How the TKIs cause lysosomal instability is still unclear, but it is known that certain TKIs, including imatinib, have been found to accumulate in the lysosome [97,98] causing an increased osmolarity, enlargement, and possible rupture [99]. Neuwirt et al., using the membrane stabilizer polyethylene glycol (PEG), discovered that lysosomal loss is insufficient for activating NLRP3, but that the TKIs play an important role in triggering lytic cell death and the inflammasome signals [96,100]. Studies on the cells lacking caspase-1, or GSDMD, have shown that imatinib and masitinib induce an inflammasome-independent form of lytic cell death and a K+ efflux–dependent NLRP3 activation [96]. According to several studies on myeloid lineage, the mature and progenitor cells exhibit different cytokine profiles, indicating that they play separate roles in MPN pathogenesis [30]. However, Zhou et al. showed that both cancerous MPN cells and their healthy counterparts triggered inflammatory responses. It can, therefore, be presumed that the NLRP3 inflammasome plays a role in both healthy and malignant hemopoietic cells [92]. As mentioned above, the development of MPN is accelerated by excessive inflammatory signaling pathways, such as NF-κB and STAT, which lead to aberrant inflammatory cytokine production and ongoing immune cell overreaction [101]. The NLRP3 inflammasomes’ importance in MPN is poorly understood, even if it is known that inflammatory cytokines that encourage clonal expansion to extramedullary locations are directly linked to splenomegaly development [102]. This finding showed that patients with a greater symptom burden had increased NLRP3 inflammasome activity. An increased release of IL-1β and IL-1R signaling from the NLRP3 inflammasome enhanced the production of pro-myelopoietic cytokines in BM accessory cells, explaining the rise in myelopoiesis, at least in part [103]. Another key player in the MPNs inflammatory scenario is hepcidin, a negative regulator of iron homeostasis, whose synthesis is stimulated by the ROS, which also promotes the release of IL-1β in human monocytes by activating NLRP3. A functional iron deficiency is common in MF where immunological dysregulation and abnormal inflammatory cytokine production lead to an increase in hepcidin. Hepcidin reduces the bioavailable iron by inhibiting intestinal absorption, downregulating the iron exporter channel ferroportin, and increasing iron deposits in the monocyte–macrophage system. As a result of this mechanism, hyperinflammation will unavoidably become worse. Birgegard et al. discovered that the inflammatory state of myelofibrosis affects the iron turnover and plays a role in the development of anemia [104]. Researchers have also found a connection between the MPN-related NLRP3 inflammatory process and the micro-RNA miR-146a. miR-146a-5p has been identified as a negative regulator of the innate immunological and inflammatory responses mediated by Toll-like receptor 4. In mice, the miR-146a wild type significantly suppressed autoimmune disease, myeloproliferation, and cancer [105], and, in the context of the TLR4 pathway, it negatively regulated the innate immunological and inflammatory responses [106]. Compared to the controls, the rs2431697 TT genotype was frequently found in MPN patients with MF subtypes. The polymorphism is considered a marker for MF early progression. The study revealed that the TT genotypes were linked to an elevated expression of inflammation-related genes, specifically NLRP3, NF-κB1, and IL-1β. The elevated expression of these genes in the BM cells from the MPN patients was related to the JAK2V617F mutation, white blood cell counts, and splenomegaly [105,106,107]. The patients with KRAS mutations presented a higher caspase-1 activation and IL-1β production than those with the KRAS wild type in CMML, JMML, and AML. The microarray-based studies revealed that the NLRP3 expression was elevated in murine hematopoietic bone marrow cells carrying the active inducible KrasG12D allele. Compared to the wild-type the KrasG12D BM-derived dendritic cells produced more IL-1β and triggered caspase-1, supporting NLRP3’s functional relevance in the myeloid compartment. KrasG12D mice lacking NLRP3 in the hematopoietic system did not exhibit cytopenia or myeloproliferation, unlike those that have expressed it. This demonstrates that oncogenic KrasG12D initiates the RAC1/ROS/NLRP3/IL-1β axis, a potential target for the treatment strategies that regulate myeloproliferation. Through the expression analysis, Shaima et al. demonstrated that the KRAS/RAC1 pathway triggered NLRP3 and produced the ROS. This suggests that oncogenic KRAS affects the NLRP3/IL-1β axis via its oncogenic driver function but also increases its activation [108]. The inflammasome scenery in the MPN cells is illustrated in Figure 2. Studies on the relationship between NLRP3 and MPNs are still lacking but given the significant evidence of this protein in hematological diseases and cancer in general, there are excellent reasons to investigate the role of NLRP3 in the MPNs on several fronts. It might be interesting to get more substantial data on the NLRP3 multi-protein complex from a biochemical and structural point of view and its interactions with the inflammasome molecules in the MPNs context. Given the biochemical heterogeneity of MPNs, it would also be interesting to study the real effect of the therapeutic combination of the JAK2 and NLRP3 inhibitors on a large cohort of patients who are refractory to treatment. There are limits to the JAK inhibitors’ activity despite the radical changes they have brought to the MPN landscape and their crucial part in the treatment of MF [109]. Several intriguing new drugs such as BET inhibitors (pelabresib), BcL-xl inhibitors (navitoclax), and PI3K inhibitors (parsaclisib), with different mechanisms of action beyond the JAK-STAT pathway, are in advanced clinical development. These can be used alone or with ruxolitinib, a targeted JAK2 inhibitor [110,111]. In the preclinical investigations, novel immunotherapies have been investigated, including neoepitope-directed vaccinations and monoclonal antibodies against mutant-driven MPNs [112,113]. The JAK2-NLRP3 axis has been studied in vitro in autoimmune inflammatory diseases in which JAK modulates the myelination/demyelination balance in the neurons, at least through the NLRP3-mediated pathways. The ruxolitinib-inhibited NLRP3 expression, phosphorylation of JAK2, and IL-1β are released, induced by the thymic stromal lymphopoietin receptor [114]. Zhu et al. demonstrated that the JAK2 inhibition through ruxolitinib administration reduces the NLRP3 inflammasome activation through the JAK2/STAT3 pathway, to improve the ischemic stroke damage and neuroinflammation. Ruxolitinib suppresses the production of the NLRP3 inflammasome components and reduces several proinflammatory cytokines [115]. The novel therapeutic agents target various biomolecules from the inflammasome pathway in MDS and AML [116]. Inflammasome targeting therapies can be explored as combinatorial strategies with JAK2 inhibitors as possible synergistic mechanisms, but we have no data about this in the MPN context. The world of the inflammasome is fascinating because it is the basis of the most common neoplasms. Studies of healthy and unhealthy hematopoiesis have transformed the NLRP3 inflammasome into an intriguing topic [48]. The relationship between NLRP3 and MPNs has now become evident. Since inflammasomes play a role in myeloid malignancies, they are potentially appealing therapeutic targets. Several NLRP3 inhibitors have been created, and some are currently undergoing clinical trials to treat cancer and inflammatory diseases [84]. The study of genetic variations, such as the copy number variants (CNVs), indels (deletions or insertions), structural variants, and single nucleotide polymorphisms (SNPs), further increased since the development of high-throughput techniques and has greatly aided the diagnosis and treatment of diseases [92]. Although the biochemical heterogeneity of MPNs has not yet been fully understood, current knowledge about the function of inflammasomes is encouraging the creation of novel therapeutic approaches. Combination therapies that eliminate uncontrolled proliferation, systemic inflammation, and loss of immunoregulation will soon dominate. To ensure a more significant and accurate assessment of these disorders and their care, hematologists and oncologists should develop interdisciplinary expertise. For targeted therapy, translational research should also examine the relationships between the clinical manifestations, risk scores, molecular profiles (and its evolution), and the participation of the inflammasomes [117]. Although inflammasome-targeting immunotherapies in hematology have not yet entered clinical use, the wide range of interactions opens up new possibilities for disease management [87]. It is known that the administration of the NLRP3 inhibitors reduced the severity of the disease in AML [118], DLBCL [119], GvHD [120], multiple myeloma [121], and sickle cell anemia [122] in both vitro and in vivo studies. Starting from the protein, the PYD domain is an attractive target for developing the NLRP3 inhibitors due to its importance in the NLRP3 activation [50]. MCC950, a selective NLRP3 inhibitor, could be a promising drug candidate to stop the advancement of myeloid malignancies caused by NLRP3-mediated illness [123]. Myeloproliferation was decreased through therapy with either the IL-1β receptor blockade or MCC950. Other potent novel medications are being researched, and the first human clinical trials will soon begin [48]. Today, MCC950 has demonstrated its universality by preventing inflammasome-induced platelet aggregation in sickle cell anaemia [124]. In the hematological context, ibrutinib is the BTK inhibitor that binds specifically to the ASC and NLRP3, preventing the inflammasome activation [125]. Ibrutinib-like substances can also decrease the IL-1β synthesis by suppressing caspase-1 [126]. This substance is being tested in high-risk MDS phase I clinical studies [127]. Through regulation of the miRNA rs2431697 genotype and NLRP3, NF-κB1, and IL-1β genes, new therapeutic strategies could be considered to prevent myelofibrosis progression in MPN patients [107]. For KRAS-driven hematological malignancies, a therapeutic approach might include the use of NLRP3 and IL-1R suppressors [108]. Inflammasomes can contribute to the pathophysiology, development, and progression of cancer. They may build and maintain the tumor microenvironment in some kinds of neoplasms. Given the good evidence of NLRP3 inhibitors in blood malignancies, although there is still much to learn about the variability of MPNs, studying the NLRP3 multi-protein complex from a biochemical and structural point of view and its interactions with the inflammasome molecules could pave the way for several novel therapeutic options in the world of MPNs.

PMC10003376

Belén Toledo,Aitor González-Titos,Pablo Hernández-Camarero,Macarena Perán

A Brief Review on Chemoresistance; Targeting Cancer Stem Cells as an Alternative Approach

24-02-2023

chemoresistance,DNA-damaging drugs,cancer stem cells,drug metabolism,p53,reactive oxygen species,drugs pumps,DNA repair,differentiation therapy

The acquisition of resistance to traditional chemotherapy and the chemoresistant metastatic relapse of minimal residual disease both play a key role in the treatment failure and poor prognosis of cancer. Understanding how cancer cells overcome chemotherapy-induced cell death is critical to improve patient survival rate. Here, we briefly describe the technical approach directed at obtaining chemoresistant cell lines and we will focus on the main defense mechanisms against common chemotherapy triggers by tumor cells. Such as, the alteration of drug influx/efflux, the enhancement of drug metabolic neutralization, the improvement of DNA-repair mechanisms, the inhibition of apoptosis-related cell death, and the role of p53 and reactive oxygen species (ROS) levels in chemoresistance. Furthermore, we will focus on cancer stem cells (CSCs), the cell population that subsists after chemotherapy, increasing drug resistance by different processes such as epithelial-mesenchymal transition (EMT), an enhanced DNA repair machinery, and the capacity to avoid apoptosis mediated by BCL2 family proteins, such as BCL-XL, and the flexibility of their metabolism. Finally, we will review the latest approaches aimed at decreasing CSCs. Nevertheless, the development of long-term therapies to manage and control CSCs populations within the tumors is still necessary.

A Brief Review on Chemoresistance; Targeting Cancer Stem Cells as an Alternative Approach The acquisition of resistance to traditional chemotherapy and the chemoresistant metastatic relapse of minimal residual disease both play a key role in the treatment failure and poor prognosis of cancer. Understanding how cancer cells overcome chemotherapy-induced cell death is critical to improve patient survival rate. Here, we briefly describe the technical approach directed at obtaining chemoresistant cell lines and we will focus on the main defense mechanisms against common chemotherapy triggers by tumor cells. Such as, the alteration of drug influx/efflux, the enhancement of drug metabolic neutralization, the improvement of DNA-repair mechanisms, the inhibition of apoptosis-related cell death, and the role of p53 and reactive oxygen species (ROS) levels in chemoresistance. Furthermore, we will focus on cancer stem cells (CSCs), the cell population that subsists after chemotherapy, increasing drug resistance by different processes such as epithelial-mesenchymal transition (EMT), an enhanced DNA repair machinery, and the capacity to avoid apoptosis mediated by BCL2 family proteins, such as BCL-XL, and the flexibility of their metabolism. Finally, we will review the latest approaches aimed at decreasing CSCs. Nevertheless, the development of long-term therapies to manage and control CSCs populations within the tumors is still necessary. Currently, chemotherapy is still considered an irreplaceable front-line therapeutic strategy to combat almost all types of cancers, but multidrug resistance represents a common hurdle that deeply compromises clinical outcomes. Therefore, it is key to identify new resistance biomarkers and to analyze their predictive potential in order to guide treatment regimens [1]. Furthermore, a better understanding of the underlying drug tolerance mechanisms may be critical in achieving alternative therapies to improve oncological patients’ prognosis. However, it is challenging since a high heterogeneity of chemoresistance markers expression profiles has been observed between different tumors and even between different cell lines of the same tumor type [2]. In this regard, the development of drug-resistant cell lines is essential to study chemoresistance mechanisms. Figure 1 summarizes the procedure to obtain in vitro chemoresistant cell lines by mimicking the conditions experienced by cancer patients during chemotherapy. The use of increasing concentrations of chemotoxic agents represents a common experimental procedure with the aim of establishing stable, drug-tolerant tumor cell lines in vitro [3]. Although this method is very reliable and reproducible, some potential limitations should be kept in mind: first, since only a small fraction of the bulk population of cells will show chemoresistance, it is recommended to start with a large population of cells (a minimum of 106 cells); second, it is very important to use the same freshly prepared drug stock for long-term use; third, it is crucial to start the protocol by determining the IC50 in each individual cell line, as variations may occur when using a new batch of cells (Figure 1). In general, it is crucial to choose a cell line that is resistant to chemotherapy with a relatively low referenced IC50 value for the drug of interest; finally, it is mandatory to avoid any contamination, including Mycoplasma, since it has been proved that microbiota can increase chemoresistance [4]. Amongst the huge variety of anti-cancer agents, we have focused on DNA-damaging drugs (DDDs), gemcitabine (Gem) (dFdC), 5-fluorouracil (5-FU), cisplatin, and doxorubicin as the main treatments for high-incidence tumors. Gemcitabine and 5-FU are “anti-metabolites”, analogous to pyrimidine-based nucleotides, namely, cytosine and thymine/uracil, respectively, while cisplatin is an alkylating agent that generates DNA adducts and doxorubicin is a topoisomerase II inhibitor [5]. Tumor cells protect themselves from the aggression of cytotoxic agents through a series of mechanisms that range from preventing the entry of the drug to repairing the damage caused (Figure 2). Accordingly, in the face of aggression, tumor cells raise their first line of defense, preventing the entry of the drug and favoring its efflux through membrane pumps to compromise intracellular drug accumulation [6]. Further, DDDs are kept out of the nucleus where they perform their cytotoxic action by interfering mechanisms, for instance, lysosomal sequestration, as described for platinum-based treatment resistance [7]. In addition, the inactivation of chemotherapeutic agents, such as gemcitabine or 5-FU, has also been shown to contribute to the clinical failure of chemotherapy [8] (Figure 2). Moreover, the basal DNA repair mechanism of eukaryotic cells is enhanced in tumor cells after prolonged exposition to cytotoxic agents, implying the resistance to treatment in many cancer types including diffuse large B-cell lymphoma [9]. Finally, apoptosis evasion, mainly through p53 mutations, has been described in a wide spectrum of cancers as a mechanism of cytotoxic drug tolerance [10]. While highly proliferative cancerous cells are more sensitive to DDDs, low-proliferative cancer cells tend to be more resistant. In this sense, cancer stem-like cells (CSCs) have been defined as low-proliferative/quiescent cells, with high invasive, metastatic, and chemoresistant potentials, which undergo the epithelial-to-mesenchymal transition (EMT) process [11]. Thus, the acquisition of a CSC-like phenotype upon exposure to chemotherapy can be considered as a pro-survival tumor cells’ mechanism [12]. CSCs chemo and radio resistance are both supported by the intrinsic characteristics of their quiescent nature: (i) increased DNA repair mechanism, (ii) the ability to escape cell death [13], and (iii) the flexibility of their metabolism [14]. In addition, CSCs chemoresistance is also due to an increased drug efflux through ABC transporters [15]. In fact, a wide variety of studies have shown the strong relationship between stemness developed through upregulation of stemness markers, such as Nanog, OCT4, SOX2, and CD44, and drug resistance via increased drug efflux [16]. Similarly, it has been demonstrated that the dedifferentiation of melanoma cells toward a CSC-like status was accompanied by an increased xenobiotic efflux capacity and thus, an alteration of the therapeutic agent uptake [17]. Other studies have correlated EPCAMhigh/CD44+ colorectal CSCs with oxaliplatin tolerance through increased DNA repair capacity, altering the cell cycle checkpoints or ROS scavenging [18]. Notably, the authors also mentioned some molecular pathways, i.e., Notch, WNT/β-Catenin, and the Janus kinase/signal transducer and activator transcription (JAK/STAT), which are significantly involved in the CSCs maintenance and thus, in the acquisition of a chemoresistant phenotype. In the same context, Matou-Nasri and colleagues identified the key role of the p38/MAPK and NFKβ signaling pathways in the survival of acute myeloid leukemia CSCs and their chemoresistance to 5-fluorouridine through the inhibition of the therapy-related induction of apoptosis [19]. Specifically, the Janus kinase/Signal Transducers and Activators of Transcription (JAK/STAT3) pathway has been shown to play an important role in CSCs. This pathway is activated by interleukine-6 (IL-6) and the epithelial growth factor (EGF), among others factors [20]. Activated JAK/STAT3 triggers JAK activation, which phosphorylates STAT3. P-STAT3 dimerizes and enters the nucleus inducing the expression of genes related to cancer progression and epithelial to mesenchymal transition (EMT) and stemness, resulting in an increase in chemoresistance [20,21]. In addition, the JAK/STAT3 pathway in breast cancer has been shown to increase chemoresistance via the regulation of the lipid metabolism-activating fatty acid oxidation [22]. Other studies have shown that an overexpression of STAT3 in colorectal CSCs increased chemoresistance while STAT3 degradation enhanced cell chemosensitivity and decreased stem cell markers expression [23]. Here, we will compare tumor cells chemoresistance mechanisms against common treatments in high-incidence tumors. Furthermore, we will focus on cancer stem cells (CSCs) as key players in cancer drug-resistance, introducing novel approaches to reduce this cell population and therefore, chemoresistance. To exert their anti-cancer effects, DDDs have to reach their molecular targets inside the nucleus, mainly DNA and/or DNA synthesis-related enzymes. Undoubtedly, the trafficking across the plasma membrane and the drug influx/efflux ratio determine the cytotoxic agent intracellular concentration. Thus, dysfunctions in drug uptake pumps lead to an increase in chemoresistance. For instance, Zeng and co-workers (2021) described the volume-regulated anion channel (VRAC) as a mediator of cisplatin uptake. Moreover, it has been documented that the cisplatin influx promoted by the organic cation transport 1 (OCT1) in esophageal squamous cell carcinoma shows a significant positive correlation between a low expression of OCT1 and a reduced sensitivity to cisplatin, along with a poor prognosis [24]. In addition, the ion transporters OCT1, OCT2, OCT3, and OATP1A2 (organic anionic transporter 1A2) have been shown to promote the cellular uptake of doxorubicin under physiological conditions [25]. Furthermore, Wang and colleagues reported the participation of the OAT2 transporter in 5-FU uptake in hepatocellular carcinoma cells, which explained the correlation between OAT2 downregulation and acquired chemoresistance [26]. On the other hand, the increased efflux of therapeutic agents has been widely described as a central mechanism leading to multidrug resistance, with special emphasis on the upregulation of the ATP-binding cassette (ABC) superfamily with up to 48 different subtypes [27]. The huge heterogeneity among efflux pumps has clinical relevance since it dictates the substrate-binding affinity. In fact, Mora Lagares and colleagues (2021) [28] have shown the implication of ABC transporters transmembrane domains, with a large proportion of non-conserved residues, in the establishment of the substrate-binding pocket, suggesting different substrate specificities that are characteristic of each ABC member. According to this idea, a specific cytotoxic drug may be recognized and expelled out of the tumor cell by only certain ABC pumps. For instance, gemcitabine is ejected from the cells by overexpressed ABCC4 [29] or ABCC5 [30] transporters, leading to chemoresistance in pancreatic cancer treatments. It has also been demonstrated that the downregulation of hENT1, a nucleotide transporter associated with gemcitabine uptake, may also contribute to the acquisition of chemoresistance by pancreatic cancer cells [31] (Figure 2). In regard to cisplatin, some studies identified ABCB1 (MDR1), ABCG2 (BCRp), ABCC1, and ABCC4 as mediators of drug extrusion, thereby contributing to cisplatin tolerance [32]. Similarly, ABCA5, ABCC2, and ABCB5 [33] have also been reported to exert the same effect. Additionally, 5-FU has been documented in colorectal cancer cells to be expelled from the intracellular space by ABCC11, but surprisingly, not by the widely recognized ABCB1 drug efflux pump [34]. In a recent study using non-small lung carcinoma cells, it was reported that 5-FU can also be a substrate of ABCA5 and ABCC1 transporters [33]. Moreover, in a hepatocellular carcinoma study, the overexpression of ABCB1, ABCB5, ABCC1, or ABCG2 had the potential to induce resistance to doxorubicin, and this fact was prevalent in hepatic CSCs rather than in non-stem cancerous cells [26]. Furthermore, the subcellular distribution of chemotherapeutic agents is key to supporting their cytotoxic effect. In this regard, it has been shown that the major vault protein (MVP) can promote doxorubicin transference from the nucleus to the cytoplasm and then to the extracellular space, inducing drug tolerance [35,36]. Reinforcing the importance of subcellular drug location, the copper transporter ATP7B has been shown to induce platinum-derived compounds lysosomal sequestration and their subsequent exocytosis, thereby promoting cisplatin chemoresistance in ovarian cancer cells [7]. Collectively, these data reflect the importance of the bidirectional trafficking across the plasma membrane, which is mediated by multiple transporters. Nevertheless, it is relevant to note that different tissues, tumor types, and even distinct cell lines of the same tumor may exhibit specific expression patterns of such transporters [25]. Antimetabolites cytotoxic drugs exert their effect by incorporation into RNA and DNA molecules producing fatal errors, which lead to cell death. Gemcitabine and 5-FU are representative examples of antimetabolites that are analogous to pyrimidine-based nucleotides, namely cytosine and uracil/thymine, respectively [37] (Figure 2). Thus, the pyrimidine metabolic activity of target tumor cells may significantly influence drug availability and cytotoxic efficacy (Figure 2). Of note, dihydropyrimidine dehydrogenase (DPD) has been shown to be an important enzyme in the pyrimidine catabolic route which catalyzes a two-electron reduction in pyrimidine bases [38]. In fact, DPD deficiency in bladder cancer cells has been associated with gemcitabine sensitivity, whereas the overexpression of DPYD (DPD-coding gene) was linked to gemcitabine resistance via its catalytic inactivation [8] (Figure 2). Similarly, DPD upregulation in colorectal cancer has also been shown to promote 5-FU tolerance through intracellular 5-FU transformation into inactive metabolites [39]. Moreover, cytidine-metabolizing enzymes, such as cytidine deaminases (CDA), have been shown to interfere with gemcitabine-based therapies. A representative example is CDA, whose upregulation has been related to gemcitabine resistance in pancreatic cancer via metabolic neutralization [1]. Interestingly, other cytidine deaminases, such as the AID and APOBEC family, have also been related to key roles in cancer biology [40]. Hence, it seems reasonable to propose a relevant crosslink between gemcitabine efficiency and these enzymes. In the case of CDA, its gemcitabine-neutralizing capacity has also been detected outside tumor cells, for instance in systemic blood circulation [12]. Parallelly, the secretion of pyrimidine nucleosides, such as deoxypyrimidine dehydrogenase (DPD), by tumor-associated macrophages (TAMs) in pancreatic ductal adenocarcinoma has been observed. Deoxypyrimidine dehydrogenase promotes gemcitabine resistance through the competitive attenuation of its uptake by tumor cells and by increasing its metabolic neutralization [41]. Furthermore, hypoxic TAMs have been proven to be the main contributors to DPD expression in colorectal cancer, implying the relevance of surrounding stromal cells in promoting resistance to chemotherapeutic antimetabolites [42]. Importantly, Malier and colleagues also noted that mice-derived macrophages did not express significant levels of DPD, contrary to human TAMs. Once inside the cells, gemcitabine activated metabolites: difluorodeoxycytidine monophosphate (DFDCMP), the diphosphate form (DFDCDP), and subsequently, the triphosphate compound (DFDCTP) are phosphorylated by the enzyme deoxycytidine kinase (dCK) before achieving therapeutic effectiveness [43,44] (Figure 2). Concordantly, it has been revealed that an increased expression of dCK in high-grade meningioma cells determined the intracellular activation of gemcitabine leading to a significant increase in drug sensitivity [45]. Along with its misincorporation into synthesizing DNA strands (DFDCTP metabolite), gemcitabine (DFDCDP form) can also hamper the synthesis and repair of DNA via the inhibition of ribonucleotide reductase (RR). Indeed, the high expression of RR and the activation of the RR large subunit (RRM1) were associated with poorer patient outcomes and gemcitabine resistance in pancreatic cancer [43] (Figure 2). On the other hand, 5-FU has to be converted to the active metabolite: fluorodeoxyuridine monophosphate (FDUMP) by mediation of enzymes such as thymidine kinase 1 (TK1) in order to exert its cytotoxic effect [46]. 5-FU causes DNA damage by being mistakenly incorporated into DNA- and RNA-based molecules, and by the induction of thymidine synthase (TS) inhibition, thus, hampering de novo thymidine synthesis. Moreover, the upregulation of TS has been shown to attenuate 5-FU cytotoxicity and to lead to drug resistance in a cholangiocarcinoma study [47]. Regarding CSCs, many studies have reported that the acquisition of a stem-like phenotype by cancerous cells may be accompanied by a deep metabolic reprogramming. To note, glycolysis is commonly enhanced in CSCs, as has been described in the case of glioblastoma CSCs [48]. The authors specified that this phenomenon along with the acquisition of a stem-like phenotype were induced by the long non-coding RNA HULC. In a similar way, another study has exposed that biomechanical forces derived from the extracellular matrix contributed to the dedifferentiation of colorectal cancer cells toward CSCs through the enhancement of glycolysis and HIF1 expression [49]. However, it has been highlighted that the metabolic reprogramming of CSCs may be much more flexible/reversible according to their phenotypic plasticity. Indeed, CSCs are able to transit between a quiescent, low-metabolic phenotype with little energy needs and a proliferative behavior with high energy costs [50]. Interestingly, it has been revealed that the acquisition of cisplatin tolerance by non-small cell lung carcinoma cells was associated with their glycolysis/oxidative phosphorylation metabolic flexibility and with an increased mitochondrial function [51]. Moreover, the dedifferentiation of cancerous cells toward CSCs can also be accompanied by other metabolic alterations. In regard to this, the overexpression of OCT4 has been related to the CSC-like phenotype along with the enhancement of both glycolysis and the oxidative pentose phosphate pathway [52]. These events may be of special relevance considering the well-known role of the pentose phosphate pathway in the defense against reactive oxygen species (ROS), which can also be correlated with the acquisition of chemoresistance (see the following section). According to the many metabolic changes surrounding the CSC-like phenotype, it seems reasonable to hypothesize that nucleotide metabolism could also be altered in CSCs. In agreement, it has been confirmed that the TS enzyme may be essential for the maintenance of the CSC-like status of triple-negative breast cancer cells, which has also remarkably been associated with an increased activity of DPD enzyme [53]. In addition, others observed that the overexpression of RRM2 (related to nucleotide synthesis) was closely correlated with the stemness of squamous cells of oral carcinoma [54]. These facts may be relevant considering the participation of DPD, RRM2, and TS enzymes in the drug tolerance of cancerous cells, as mentioned above. Upon reaching the nucleus, DDDs cause a variety of DNA lesions. Depending on the level of DNA damage, several types of DNA-damage responses (DDRs) are triggered and these can be classified into two main groups: (i) pro-survival responses (i.e., DNA repair and/or cell cycle arrest/premature cell senescence) and (ii) cell death (i.e., pro-apoptotic signaling). Specifically, DDRs are characterized by complex and multifactorial phosphorylation cascades comprising a wide variety of molecules such as DNA sensors (i.e., MRN complex, ATM, or ATR), DDR transducers such as checkpoint kinases (for example CHK1 or CHK2), and mediators/effectors such as p53 and executioners (i.e., DNA repair-, cell cycle arrest-, or apoptosis-related factors) [55]. Considering that the final goal of cancerous cells relies on surviving at all costs, the reported association between the optimization of DDR through ATM/ATR/p53 axis upregulation and the tolerance to chemotherapeutic drugs such as gemcitabine in pancreatic cancer is not surprising at all [56]. Relevantly, some degree of specificity in the induction of certain DDR pathways according to the type of DNA damage has been shown. For instance, the activation of ATM/CHK2 signaling has been mainly correlated to double-stranded DNA breaks while the enhancement of the ATR/CHK1 axis has been mainly linked to single-stranded DNA breaks [57,58]. Similarly, different DNA repair mechanisms have been described according to the type of DNA damage. For instance, in the repair of double-strand DNA breaks, the high-fidelity homologous recombination (HR) or the error-prone non-homologous end-joining (NHEJ) are involved [59] (Figure 2). On the other hand, nucleotide excision repair (NER) is induced by DNA adducts [60] and single-stranded DNA breaks are repaired by base-excision repair (BER) [61]. Generally, DDDs can trigger several DNA repair responses, as has been revealed in the case of gemcitabine-based treatment, which can induce either NHEJ [62] or HR [63]. Nonetheless, some trends with certain chemotherapeutic treatments have been identified, such as NER activation to overcome DNA adducts caused by alkylating platinum compounds [64]. However, HR repair machinery has also been shown to be involved in the resolution of DNA damage induced by a wide spectrum of cytotoxic agents, including gemcitabine, 5-FU, cisplatin, and doxorubicin [5]. The development of suitable experimental protocols to simultaneously test a broad range of DNA repair responses may be of great interest. In regard to this, Ge and co-workers pointed out that the transcriptional profiling of DNA repair-associated genes does not always correlate with the real DNA repair capacity. Therefore, they developed a “cometchip platform” based on the previously established comet assay that is suitable for the parallel assessment of multiple repair pathways such as BER, NER, and NHEJ [61]. Furthermore, it may be relevant to note that DNA damage and, thus, the DNA repair capacity can also be enhanced in some cellular contexts that are different from the exposure to therapeutic compounds. For instance, a high-proliferative phenotype may elicit excessive proliferative stress, which has been associated with the overactivation of DNA repair signaling [65]. On the other hand, a close correlation between chronic inflammation and the induction of oxidative stress and DNA damage has been established [66]. Considering the uncontrolled proliferation of tumor cells and the documented pro-inflammatory microenvironment surrounding solid tumors since the earliest stages of their growth [67], a remarkable DNA repair capacity even in the absence of antitumor drugs seems like a reasonable suggestion. Importantly, the reinforcement of DDRs by a pro-inflammatory microenvironment may be a significant difference between in vitro and in vivo chemoresistance-based studies. Parallelly, cell cycle arrest promoted by DNA damage is a well-known cellular response in physiological conditions [68]. In fact, DNA-induced cell cycle arrest after chemotherapy might be a pro-survival cellular response, which may lead to chemoresistance by providing sufficient time to complete DNA repair. However, some studies have interpreted the inhibition of DNA damage-mediated cell cycle arrest by a cancerous cell as a drug-resistant mechanism [69]. With regard to this controversy, the authors also noted the importance of carefully considering the balance between the DNA repair potential and the cell cycle arrest/growth inhibition in chemoresistance-based research. Moreover, distinguishing between punctual/short-term cell cycle arrest and permanent/long-term cell cycle blockade (also known as “cellular senescence”), both promoted by DNA damage, may be relevant to clarify such a dichotomy. In this sense, the induction of cellular senescence in several types of cancers upon treatment with doxorubicin and etoposide has been shown [70]. On one hand, the induction of tumor senescence as an anti-cancer strategy to inhibit tumor proliferation and growth has been considered [71]. Nevertheless, the plasticity and reversibility of the senescent-like phenotype leading to a more aggressive and invasive behavior and even the promotion of disease relapse and metastasis have also been pointed out [70]. Interestingly, these are well-documented negative events that are closely related to the CSC population, the EMT process, and chemoresistance [72]. In agreement, the promotion of cellular senescence and a stem-like phenotype after sustained and long-term DNA-damaging conditions, i.e., radiotherapy, has been identified [73]. Additionally, it has been indicated that DDDs can also be associated with the EMT process and tumorogenesis [74]. Therefore, cellular senescence and the acquisition of a CSC-like phenotype seem to support chemotherapy through pro-survival tumor cell behavior [12]. Nuclear DNA damage triggers cell death mainly by the activation of p53, also known as “the guardian of the genome” [75]. In fact, p53 phosphorylation leads to the phosphorylation cascade toward apoptosis-based cell death [55]. In healthy cells, the expression of p53 is usually low, with a half-life of about 20 min [76]. However, after cellular stress, the p53 half-life extends to several hours, promoting different responses such as cell-cycle arrest, senescence, apoptosis, regulation of cellular energy metabolism, antioxidant defense, DNA repair, and immune system regulation [77]. Accordingly, the mutant p53 protein has been shown to interfere with a variety of processes such as the regulation of cell survival, DNA damage repair, and drug resistance [78]. p53 versatility has been shown to be driven by different levels of phosphorylation and it has been shown that p53 can act as a “cell cycle arrestor” permitting DNA repair and cell survival when it is phosphorylated on Serine15 (Ser15) and/or Serine20 (Ser20). Nevertheless, additional phosphorylation on Ser46 under severe DNA damage conditions may change its role to “killer”, leading to apoptosis [55]. In summary, as a cellular “gatekeeper”, p53 recognizes whether DNA damage is irrevocable and acts accordingly by inducing apoptosis [77,79]. Therefore, p53 plays a dual role by activating either a mechanism that leads to apoptosis or one that enhances DNA repair and cell survival. The mutated p53 gene (TP53) has been detected in approximately 50% of all human tumors, such as breast, brain, lung, or colorectal carcinomas, among others [80], which may deeply condition the prognosis and clinical outcomes of oncological patients. Particularly, germline p53 mutants are mainly associated with Li–Fraumeni Syndrome, which is characterized by a high risk of oncogenesis [80,81]. Some mutations can make the p53 protein unable to recognize and interact with p53-binding sites located in its target genes. In accordance with this, Donzelli and co-workers (2012) showed that mutant p53 conferred tolerance to doxorubicin, cisplatin and 5-FU by procaspase-3 downregulation, and apoptosis inhibition [82]. Furthermore, p53 mutations promote the acquisition of new and distinct oncogenic properties by interacting with different genes, which is generally referred to as “gain of function” alterations (GOF) [83]. Specifically, mutant p53 can reach the promoter of target genes through the interaction with several sequence-specific transcription factors including NF-Y, E2F1, NF-kB, and the Vitamin D receptor (VDR) [84]. GOF mutations may promote tumor progression and possibly lead to resistance to a variety of anticancer drugs. For instance, studies have shown that mutant p53 may be associated with chemoresistance in an independent way of its pro-apoptotic role, increasing the expression of the MDR1 efflux pump (ABCB1) [85]. Additionally, a relationship between mutant p53 and EFNB2 (ephrin-B2), a receptor tyrosine kinase involved in cell invasion, migration, angiogenesis, and tumor resistance, has been established [86]. Moreover, it was reported that mutant p53 increases EFNB2 expression in colorectal carcinoma cell lines upon treatment with 5-FU [87]. The authors also showed that EFNB2 induced 5-FU resistance through the upregulation of the ABCG2 drug efflux transporter, mediated by the activation of the c-Jun/JNK signaling pathway. Further, it has been observed that p53 knockdown reduced cell proliferation and resistance to cisplatin, adriamycin, and etoposide in several cancer cell lines [88]. On the contrary, an overexpression of p53 has been associated with gemcitabine tolerance in pancreatic cancer [89]. Thus, p53 phosphorylation status and not only its expression patterns should be taken into account to explain observed controversies regarding p53 expression and chemoresistance. Apart from the high rate of TP53 mutations, the remaining 50% of cancers may exhibit p53 dysregulation or alterations in p53-related pathways [90]. To note, it has recently been discovered that the overexpression of CD147 may promote the acquisition of gemcitabine resistance by pancreatic tumor cells by interfering with the activation of p53 upon ATM/ATR/p53 complex formation, thus preventing cell apoptosis (REF: CD147). Similarly, the overexpression of MSIM2 may cause resistance to gemcitabine and cisplatin in pancreatic cancer by negatively regulating p53 (REF: MSIM2). Notably, p53 has been documented to control its protein levels through a negative feedback loop involving MDM2 [91]. P53 can act as a transcription factor activating MDM2, which can then enhance p53 protein ubiquitination and degradation [92]. Upon cellular stress, mediated for example by DNA damage, MDM2 activity decreases, leading to an increase in p53 levels through its protein stabilization (non-degradation) [93]. As a consequence, a re-increase in MDM2 is observed, which in turn, may promote p53 protein degradation. In physiological conditions, nuclear concentrations of both p53 and MDM2 may be mutually maintained at low levels [91]. Nonetheless, the dysregulation of MDM2/p53 balance could be associated with severe disorders such as tumorigenesis and poor clinical prognosis [93], hence, interfering with such a feedback control may represent a promising therapeutic strategy in oncology. In addition, p53 dysregulation could also lead to deficient immune system responses [94], which may play a key role in cancer immune evasion. For instance, Major Histocompatibility Complex Class I (MHC-I) was described to be positively regulated by p53, promoting damaged cell recognition by T cells. Parallelly, reactive oxygen species (ROS) levels have been reported to be increased in cancerous cells due to both environmental (smoking or UV) and internal mechanisms (ROS are considered as an inevitable by-product of cellular metabolism). Therefore, the increased metabolism of high-proliferative cancerous cells may result in elevated ROS production [95]. Furthermore, ROS generation can be related to well-known cancer features, for instance, the overactivation of oncogenes such as C-myc, Kras, or BRCA1, or the alteration of integrins during metastasis. In cancer cells, ROS could play a dual role: under basal conditions, ROS play a critical role in maintaining cellular proliferation and homeostasis [96], whereas high ROS concentrations may inhibit cell cycle progression and induce apoptosis [97] (Figure 2). Relevantly, many anticancer compounds, namely doxorubicin, cisplatin, or 5-FU, can induce DNA damage by further promoting the accumulation of ROS and thereby enhancing apoptosis [58]. Importantly, this study also indicated that ROS, like H2O2, can trigger the activation/phosphorylation of p53 through a DDR-independent manner. Strikingly, mutant p53 can also induce ROS accumulation due to the loss of its antioxidant potential, i.e., by causing antioxidant enzyme imbalance [98]. Hence, p53 mutations can contribute, at least in part, to the intracellular ROS accumulation and thus, to the genomic instability characteristics of malignant cells [99]. As it has been revealed that cancer cells could enhance their antioxidant mechanisms to counterbalance excessive oxidative stress, this could be considered as chemoresistant behavior. For instance, the overexpression of antioxidant enzyme Isocitrate Dehydrogenase 1 (IDH1) reduced ROS levels and promoted gemcitabine resistance in pancreatic ductal adenocarcinoma [100]. Similarly, cisplatin can interact with endogenous nucleophiles such as reduced glutathione (GSH), which makes the redox balance prone to oxidative stress [101]. Thus, the observed susceptibility of cisplatin-based treatments to cytoprotective antioxidant molecules [102,103] may be determined in a double way: ROS direct neutralization and cisplatin activity mitigation by the overexpression of GSH. Several resistant routes can be triggered in response to elevated ROS levels, involving endoplasmic reticulum (ER) stress, autophagy, cell cycle perturbations, and the acquisition of a CSC-like phenotype through the EMT process [104]. Supporting the malignant cells’ adaptation to high ROS accumulation, recent evidence suggests that prolonged chemotherapy can reduce the overall ROS concentration, thus leading to drug tolerance [105]. As an additional example, gemcitabine-induced oxidative stress accompanied by an increase in antioxidant genes, i.e., NRF2, SOD1, SOD2, CAT, or GPX1, has been demonstrated [106]. Additionally, oxygen availability may significantly determine anticancer drug efficiency. While hypoxic conditions may limit ROS production, the recovery of normal oxygen levels can elevate the cytotoxicity of DDDs, such as doxorubicin, by increasing the generation of ROS and ultimately, alleviating the chemoresistance [107]. Therefore, the development of hypoxic environments in almost all solid malignancies may represent an important difference between in vitro and in vivo and/or clinical studies. However, the therapeutic feasibility of pro-oxidant drugs in cancer with mutant p53 status remains to be well-defined [108]. As revised in previous sections, the acquisition of a quiescent, CSC-like phenotype by well-differentiated cancerous cells provides them with sufficient time for successful DNA repair after the cytotoxic assault. Nevertheless, CSCs chemoresistance can rely on multiple additional mechanisms. Indeed, the correlation between breast, colorectal, and lung CSCs, the upregulation of ABC family members, such as ABCC1, and the cisplatin and doxorubicin tolerance have been demonstrated [109] (Figure 3). Moreover, it has been revealed in a colorectal cancer study using 5-FU as a chemotherapeutic agent that a high drug metabolic detoxification capacity is a typical property of dormant CSCs [110]. In addition, CSCs usually exhibit enhanced DNA repair mechanisms in a similar way to healthy stem cells, which may lead to increased DDDs tolerance (Figure 3). What is more, the key importance of DNA repair-related pathways/proteins in the maintenance of a CSC-like phenotype, for instance, by regulating the EMT process, has been reported [111]. The chemoresistance capacity of CSCs also relies on avoiding apoptosis mediated by the enhancement of BCL2 family proteins, such as BCL-XL, as has been determined by the Medema group in a colorectal cancer study [112]. Interestingly, they documented the reliance of different antiapoptotic proteins according to the tumor progression stage, which may suggest the existence of distinct antiapoptotic mechanisms between healthy cells, well-differentiated cancerous cells, and CSCs. Altogether, these data reinforce the crucial importance of developing therapeutic strategies with the aim of eliminating such a cancer cell subpopulation (Figure 3). In a tumor mass and surroundings, the CSCs population is maintained by the dedifferentiation of tumors cells located in the borders (revised in Hernández-Camarero et al., 2018) [113]. Thus, CSCs are a population that subsists after chemotherapy, enhance drug resistance, and reappear constantly upon tumor cell dedifferentiation. All these facts make the development of long-term therapies to manage and control the revival of CSCs populations necessary, while avoiding chemotherapy that is associated severe side effects (Figure 3). In this regard, strategies that control and deregulate the CSCs population are interesting approaches. For instance, targeting pathways that regulate CSCs has been proposed. One of the main candidates has been the Notch pathway and to this end, different strategies have been tested: (i) gamma-secretase inhibitors (GSIs) [114]; (ii) monoclonal antibodies targeting Notch signaling [115], and (iii) pan-Notch inhibition [116]. Another strong candidate has been the Wnt pathway, whose inhibition has been achieved by an IgG4 mAb (DKN-01) that targets Dkk1 and suppresses canonical Wnt signaling via negative feedback [117]. In addition, efforts have been undertaken to control the hedgehog signaling pathway, with the use of SMO inhibitors and GLI inhibitors [118]. Furthermore, CSC-directed immunotherapy has also received attention. CSC lysates are used to generate CSC-specific T cells that directly target the subpopulation of CSCs within tumors [119]. The relevance of these approaches is supported by their translation to the clinical arena. In fact, several clinical trials on therapies targeting CSCs are actually ongoing or have already been completed [120]. Nevertheless, the depletion of CSCs by itself has not been shown to be effective in reducing chemoresistance because other factors, such as the tumor microenvironment (TME) [121], play a key role in CSC regulation and stem maintenance via the transition of non-stem cells to stem cell states [122]. Thus, strategies should focus on directing CSCs differentiation (Figure 3) instead of CSCs eradication. In conclusion, the development of novel therapeutic approaches directed against CSCs and the TME could reduce chemoresistance and the associated adverse effects.

PMC10003380

Yu Wang,Meiping Wu,Haidong Guo

Modified mRNA as a Treatment for Myocardial Infarction

01-03-2023

myocardial infarction,modified mRNA,myocardial regeneration,gene therapy,paracrine effect

Myocardial infarction (MI) is a severe disease with high mortality worldwide. However, regenerative approaches remain limited and with poor efficacy. The major difficulty during MI is the substantial loss of cardiomyocytes (CMs) with limited capacity to regenerate. As a result, for decades, researchers have been engaged in developing useful therapies for myocardial regeneration. Gene therapy is an emerging approach for promoting myocardial regeneration. Modified mRNA (modRNA) is a highly potential delivery vector for gene transfer with its properties of efficiency, non-immunogenicity, transiency, and relative safety. Here, we discuss the optimization of modRNA-based therapy, including gene modification and delivery vectors of modRNA. Moreover, the effective of modRNA in animal MI treatment is also discussed. We conclude that modRNA-based therapy with appropriate therapeutical genes can potentially treat MI by directly promoting proliferation and differentiation, inhibiting apoptosis of CMs, as well as enhancing paracrine effects in terms of promoting angiogenesis and inhibiting fibrosis in heart milieu. Finally, we summarize the current challenges of modRNA-based cardiac treatment and look forward to the future direction of such treatment for MI. Further advanced clinical trials incorporating more MI patients should be conducted in order for modRNA therapy to become practical and feasible in real-world treatment.

Modified mRNA as a Treatment for Myocardial Infarction Myocardial infarction (MI) is a severe disease with high mortality worldwide. However, regenerative approaches remain limited and with poor efficacy. The major difficulty during MI is the substantial loss of cardiomyocytes (CMs) with limited capacity to regenerate. As a result, for decades, researchers have been engaged in developing useful therapies for myocardial regeneration. Gene therapy is an emerging approach for promoting myocardial regeneration. Modified mRNA (modRNA) is a highly potential delivery vector for gene transfer with its properties of efficiency, non-immunogenicity, transiency, and relative safety. Here, we discuss the optimization of modRNA-based therapy, including gene modification and delivery vectors of modRNA. Moreover, the effective of modRNA in animal MI treatment is also discussed. We conclude that modRNA-based therapy with appropriate therapeutical genes can potentially treat MI by directly promoting proliferation and differentiation, inhibiting apoptosis of CMs, as well as enhancing paracrine effects in terms of promoting angiogenesis and inhibiting fibrosis in heart milieu. Finally, we summarize the current challenges of modRNA-based cardiac treatment and look forward to the future direction of such treatment for MI. Further advanced clinical trials incorporating more MI patients should be conducted in order for modRNA therapy to become practical and feasible in real-world treatment. According to global death statistics, cardiovascular diseases (CVDs) are the first cause of mortality [1], therein, myocardial infarction (MI) accounts for 46% of deaths in CVDs [2]. MI induces multiple complications from myocardial necrosis and fibrosis of the heart milieu to whole heart damage with limited ability to regenerate [3]. Difficulties in MI treatment still exist, despite updated medical methods that have been developed over the decades. With the development of gene editing technology, significant progress has been made in clinical translations and applications of gene therapies, including mRNA-based therapy, DNA-based therapy, and recombinant proteins [4]. In terms of the aims of MI treatment, mRNA should be a better substitute for DNA or recombinant proteins, due to its transient expression for transcription to DNA and encoding proteins [4]. However, mRNA-based therapy still has limitations that should be further addressed. Firstly, mRNA is quickly degraded by ribonucleases (RNase) because of host defense activities [5]. Therefore, exogenous mRNA is extremely unstable when transferred to a specific organ, and there is insufficient protein translation of exogenous mRNA [6]. Secondly, exogenous mRNA has high immunogenicity, which induces a potent immune response via the activation of Toll-like receptors (i.e., TLRs, TLR7, and TLR8) [7,8,9]. Thirdly, uridine in mRNA renders translation difficult for the involvement of RNA-dependent protein kinase (PKR) with the ribosome inhibiting mRNA [10,11]. The low efficiency of translatability, instability, and high immunogenicity of exogenous mRNA are crucial limitations to be optimized for effective therapeutic application. Due to these potential limitations, there has been significant interest in how to successfully transduce exogenous mRNA into cardiac cells. The aim of modRNA-based gene therapy is to achieve powerful protein translation with low immunogenicity, stability, as well as a low risk of insertional mutagenesis of exogenous mRNA [12]. In this review, we discuss the optimal conditions for modRNA-based therapy by using gene modification methods and selecting suitable delivery materials. Moreover, the effects and mechanisms of modRNA in MI treatment are discussed. Finally, we discuss the current challenges of modRNA-based cardiac treatment and look forward to the future direction of such treatment for MI. Production of mRNA in eukaryotic cells involves several processes that include adding 5′ cap, splicing to delete non-coding introns, and forming the 3′ terminus [13]. The 5′ cap and untranslated regions (UTR, 5′ UTR, and 3′ UTR) have the ability to increase transcript stability and initiate translation in whole processes [14]; 5’ UTR seems to be the crucial driver of protein expression, in which distinct 5′ UTR characteristics have different effects on the mRNA translation [15,16]. For example, one study built a library of 300,000 randomized 5′ UTRs and created a potential model regarding 5′ UTR sequences and translation efficiency which allowed the design of 5′ UTRs with enhanced protein production [17]. The 5′ UTR modRNA (adding 5′ UTR with GATA2) has been shown to promote differentiation of the pluripotent stem cells (PSCs) into endothelial cells (ECs) [18]. In addition to designing 5′ UTRs, the efficiency of translation can be increased by adding 3′ UTR twice in tandem [19]. The last step of mRNA transcription is the insertion of a poly-A tail, which is located at the 3′ terminus; the long poly-A sequences facilitate nuclear transport, commence translation, and enhance mRNA stability [20]. Internal modifications on mRNA are also crucial in translational efficiency. The modified nucleosides change the secondary structure of RNA by altering hydrogen bonding patterns, influencing base stacking potential, or favoring a specific nucleotide conformation [21]. By editing nucleotides of mRNA, including insertion of methyl or hydroxylate groups and replacement of uridine with pseudouridine (ψ), the TLR signaling pathway is inactive, and thus inhibits immunogenicity [22]. Furthermore, the translation capacity of mRNA can be significantly enhanced through the replacement of uridine with ψ by inhibiting the PKR pathway [23] and RNase activity [24]. Nevertheless, mRNA modification seems to be a double-edged sword, with a context-dependent translating ability in different cells and different coding sequences [25]. To solve these limitations, several studies have been undertaken to optimize the technology for increasing the translational capacity of modRNA. Modified mRNA is a nucleotide-modified vector, which instantly translates sufficient proteins with gradual degradation (5–7 days in vitro, 10 days in vivo) and low immunogenicity [26]. Commonly, chemically modified nucleotides, such as 5-methylcytidine (5meC), N6-methyladenosine (m6A), and N1-methylpseudouridine (m1ψ) have effective functions in mRNA translation (Figure 1) [27]. Studies have validated that both the types of fluorescent vectors [28] and the pH values [29] affect the translated capability of modRNA. Accordingly, enhanced green fluorescent protein (eGFP) mRNAs with m1ψ have been shown to have the most potent expression of encoded protein as compared with 5moU, ψ, and encoding firefly luciferase (FLuc) modifications [28]. This could be because of a reduction in immune response with antigen-specific cell-induced m1ψ modRNA [30], increased ribosome loading [31], augmented microRNA, and protein sensitivity [32]. However, eGFP coupled with 5moU has been shown to be less sensitive to RNase than other modRNA [28]. David et al. compared eGFP expression between nucleotide-modified RNA and unmodified RNA, and the results showed that mean protein expression increased 1.5-fold for m1Ψ modRNA in HeLa cells [33]. Interestingly, the temperature at neither 30 °C nor 37 °C affected the translated results, which means the temperature was independent of the translation [28]. Moreover, 5meC-modified mRNA had optimized protein expression at pH 5, and ψ did best at pH 7 [29]. Codon modification also influences the translation efficiency of mRNA. The “GC3” codon combined with m1ψ has produced an mRNA more than 1000-fold than other mRNA variants and outperformed all other unmodified mRNA [34]. Moreover, the optimal dosage of N1-methylpseudouridine-5′-triphosphate nucleotide (1-mΨU) modRNA in MI treatment was 0.013 μg modRNA/mm2 with RNAiMAX of cardiomyocytes (CMs) in vitro and 1.6 μg/μL with sucrose-citrate buffer in vivo [35,36]. In addition, Andries et al. coupled m1ψ with 5meC and found that the combination of both increased translation efficiency and reduced immunogenicity, which was superior to modifying alone [37]. Post-translational modifications have been shown to affect protein expression in various ways [38]. The glycosylation of human follistatin-like 1 (hFSTL1) significantly influenced cardiac function and transported the mutation of a single site (N180Q) hFSTL1 modRNA into the myocardium, increasing the proliferation of CMs and myocardial regeneration in MI mice [39]. Moreover, Yiangou et al. encoded Ca2+ indicators (GEVIs and GECIs) in modRNA and delivered them into human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) for long-term observation (lasting for 7 days), and demonstrated the value of modRNA as a gene delivery method [40]. In conclusion, the translation efficiency of modRNA can be further elevated by editing nucleotides, combining the actions of modified nucleosides, optimizing the 5′ UTR and 3′ UTR vector sequences, an optimal pH value, as well as optimal dosages in vitro and in vivo. Traditional virus vectors, including adenovirus, adenovirus-associated virus (AAV), and lentivirus have limited insert capacity for mRNA transduction [41], whereas non-viral vectors such as naked DNA plasmid and modified mRNA (modRNA) do not have size limitations, and can support therapeutical genes regardless of size. Moreover, the modRNA method has an overwhelming characteristic that most viral vectors lack, i.e., it is not affected by the conditions of the nuclear membrane, thus, it can transfect either dividing or non-dividing cells. Furthermore, MI has its own unique temporal expression window within 3 d of the inflammation phase and significant changes can even happen in cardiac cells as early as 24 h; therefore, the modRNA is an ideal vector for optimal delivery with a specific time window for protein expression. Virus vectors, especially AAV, can prolong gene expression for up to 4 weeks, and even 11 months in MI [42]. This uncontrolled and long-term gene delivery method can miss the optimal time of treatment, and can also induce some unnecessary risks. Accordingly, the specific pulse-like, transient gene expression of modRNA is highly favorable for protecting the heart from further damage [43]. In addition to the risk from constant gene expression, adopting viruses for gene therapy poses a series of safety concerns. Lentivirus vectors are rarely used in MI with their high immunogenicity, as well as their random insertion into a host with a preference of targeting coding regions can cause risks of insertional mutagenesis and tumorigenesis [44]. Although AAV vectors without immunogenicity are highly preferred in MI treatment, a critical limitation in AAV therapy is the translation efficiency, because from 30 to 50% of the protein is neutralized by the presence of pre-existing anti-AAV antibodies [45]. By contrast, non-viral vectors are favorable to use as delivery vectors. Achieving the ideal biodistribution of the target gene in the myocardium is still a challenge in MI treatment. There are multiple vectors for delivering modRNA both in vivo and in vitro. Gene knockout induced via RNA interference (RNAi), a biological activity regulated through double-stranded RNA and referred to as small non-coding RNAs (20–30 nucleotides), is widely applied in MI therapy. By encapsulating modRNA with RNAiMAX (a new transfection reagent) based on the cationic lipid formulation that possesses polar heads and non-polar tails, transfection efficiency has reached the maximum in vitro [46], whereas it was not an ideal choice to inject into the myocardium [35]. The administered RNAiMAX faces several obstacles in accomplishing its targets, i.e., it needs to pass through cellular membranes as well as evade enzyme processes and immune-induced degradation. To overcome these problems and to enhance the stability of mRNA in vivo, the application of nanoparticles is recognized as the best biomaterial to encapsulate modRNAs. Based on the biomaterial used, nanoparticles (10–1000 nm) are subgrouped into inorganic, organic (e.g., micelles, liposome, protein-based carriers, polymers, and cyclodextrins), viral, and mixed nanoparticles [47]. Delivering nanoparticles needs to avoid agglomeration and to retain them in colloidal suspension. These functions require assistance from several materials, including polyethylene glycol, dextran, chitosan, pullulan, and sodium oleate [48]. In acute MI, M3-FLuc modRNA delivered via intramyocardial injection increased protein expression in primary CMs and lasted for up to 7 days without morphological and functional changes in CMs [49]. Zaitseva et al. designed hepatocyte growth factor (HGF) modRNA in incorporated nanofibrillar scaffolds, which allowed modRNA release from nanoscaffolds in a transient controlled way [50]. Lipid nanoparticles (LNPs), a lipid cargo that possesses a homogeneous lipid core against mRNA from extracellular ribonucleases, have been shown to help with intracellular mRNA transport [51]. In MI treatment, LNPs can effectively deliver modRNA to an injured heart, which stands as an excellent prospect for modRNA-based MI therapy. Through detecting the biodistribution of fluorescent-label LNPs, researchers have found that the majority of LNPs are distributed in heart fibroblasts in the infarct zone, but there are still a few LNPs in CMs and macrophages [52]. Moreover, the translated efficiency of formulated lipidoid nanoparticles (FLNPs) has been shown to be superior to other vehicles [53,54]. Paradoxically, researchers have also found that nanoparticle-encapsulated modRNA has lower translation efficiency than sucrose-citrate buffer-encapsulated modRNA, in which encoded protein can be detected within 10 min [35,55]. Interestingly, polymeric nanoparticles are novel and potential vectors for modRNA transportation with highly efficient transfection and low toxicity [56]. In addition to various materials, there are also different delivery methods for modRNA-based treatment. The two major methods for modRNA administration are intramyocardial and intravenous injections [57]. Multiple previous studies have indicated that intramyocardial injection of stem cells is more helpful in the recovery of heart function [58] since injected cells did not distribute throughout the whole body [59]. However, intramyocardial injection is still an invasive method, which can produce damage in the epicardial area and ventricular wall [60]. Intravenous injections can inhibit prolonged inflammatory processes compared to intramyocardial injections and have the ability of repeated injections several times [61]. Appropriate vehicles and injection methods are crucial to delivering disease-specific genes to the myocardium in cases of damage. A combination of gene modification, delivery materials, and methods to maximize the potential utility of modRNA for gene therapy could be considered in the future. The limited ability of heart regeneration results in undesired morbidity and mortality after an MI. Factors such as inflammation, cardiac tissue remodeling, and the fibrotic environment contribute to limited CM proliferative activity after MI [62]. Stem cells are a group of unspecialized cells that have a special capacity to renew themselves and differentiate into other cell types [63]. Stem cells are associated with the repair of cardiac tissues mostly via direct differentiation into CMs, differentiation into endothelial cells, and secreting various trophic and paracrine factors, as well as inhibiting immune responses [64]. However, the ability of stem cells to differentiate into CMs is still disputable. Despite promising efficacy in preclinical and clinical studies, there are still some limitations that need to be addressed before broad clinical application of stem cell therapy, especially the extremely low survival rate, limited differentiation ability, safety concerns, as well as ethical issues [65]. Furthermore, an inflammatory microenvironment is also the main element to hinder the efficacy of stem cell therapy in cases of MI [66]. Thus, multiple technologies have been used to solve these challenges, therein, genetic manipulations regarding modRNA are also utilized in MI treatment. The favorable characteristics of modRNA as a transport vehicle, including highly efficient protein expression and flexible time dynamics, render it a potent choice for augmenting the regenerative ability of the myocardium. The protein can be detected within 3 h after injection of modRNA into the left ventricle, reaches a peak at 18 h post injection, and then gradually decreases in 6 days [67]. These time points correspond to the timeline of the MI process, i.e., CM death within 1 h after obstruction, secretion of proinflammatory factors at 4 h, fibrosis and angiogenesis after 2 days, and eventually, scar formation 2–3 weeks post MI [68]. Modified mRNA-based therapy with appropriate therapeutical genes can potentially treat MI by directly promoting proliferation and differentiation and inhibiting apoptosis of CMs, as well as enhancing paracrine effects in terms of promoting angiogenesis and inhibiting fibrosis of the cardiac microenvironment (Figure 2). Furthermore, apart from pathological processes, there are still multiple cell signaling pathways involved in mediating various cells after an MI, including CMs, endothelial cells, fibroblasts, monocytes, as well as stem cells [69]. These signaling pathways, for example, the PI3K/Akt, Notch, TGF-β/SMADs, Wnt/β-catenin, NLRP3/caspase-1, TLR4/MyD88/NF-κB, Nrf2/HO-1, RhoA/ROCK, MAPK, JAK/STAT, Hippo/YAP, and Sonic hedgehog pathways, mainly focus on several processes, including inflammation, oxidative stress, fibrosis, hypertrophy, apoptosis, survival, angiogenesis, and regeneration after an MI [69]. Next, we summarize some related genes for modRNA therapy in MI treatment published so far. In terms of promoting the proliferation of CMs, modRNA delivery follistatin-like 1 (FSTL1) [39,70] or pyruvate kinase muscle isoenzyme 2 (PKM2) [43] both have this function. The transfer of N180Q mutant coupled with h-FSTL1 modRNA to the heart have been shown to trigger CM proliferation, reduce the infarct area, promote angiogenesis, and recover the heart function of MI mice [39]. Ajit et al. studied the role of PKM2 in an MI mouse model by using bidirectionally regulated methods, losing PKM2 via CM-specific PKM2 knockout or gaining it via CM-specific PKM2 modRNA. The results indicated that PKM2 promoted proliferation and division during CM development but disappeared in adult mice [43]. The insulin-like growth factor-1 (IGF1) modRNA, encapsulated by the polyethyleneimine nanoparticle, protected CM survival and abrogated CM apoptosis in the scar border area. The cytoprotective effect of IGF1 was induced by activation of the Akt/the Erk pathway and the production of miR-1 and miR-133 [71]. Additionally, IGF-1 modRNA also promoted differentiation of the epicardial progenitor cells (EPCs) into adipose cells [72]. Hadas et al. performed a transcriptome, sphingolipid, and protein analysis to study the roles of sphingolipid metabolism in MI. Acid ceramidase (AC)-induced modRNA altered components of immune cells (decreased neutrophils), alleviated cardiac function, and minimized the infarct area in MI mice [73]. Meanwhile, the transcriptional co-stimulator yes-associated protein (YAP) also decreased necrosis of CMs and neutrophil infiltration by inhibiting the TLR pathway, thus improving heart function in MI mice [74]. Several works have validated that direct injection of vascular endothelial growth factor (VEGF) and vascular endothelial growth factor-A (VEGF-A) modRNA to MI mice resulted in expanded capillary density and maturity and decreased scar size, promoted heart function, and improved survival. Pulse-like transfer of VEGF-A modRNA led to the mobilization of EPCs and governed EPC differentiation toward vascular cell populations [75]. Additionally, VEGF-A modRNA has been recognized as a cell fate switch for embryonic stem cell (ESC)-derived Isl1+- ECs [76]. In larger animal-mini pigs, VEGF-A modRNA has also contributed to improving heart function and promoting angiogenesis [55]. Transfected VEGF modRNA in iPSC-CMs eventually promoted survival rates of iPSC-CMs, which constructed a tight vascular network in the injection zone [77]. Combination multi-gene therapy represents a potent technology for MI treatment. The 7G-modRNA method combines four cardiac reprogramming genes, i.e., Gata4, Mef2c, Tbx5, and Hand2, together with three helper genes, i.e., TGFb, Wnt8a, and AC, to induce CM-like cells. The results have shown that 7G-modRNA induced 57% CM-like cells in vitro and 25% CM-like cells in vivo. Interestingly, 7G-modRNA was unable to produce CMs, it only markedly promoted pro-angiogenic mesenchymal stromal cell markers and transcription factors [78]. Moreover, the 7G-modRNA method has been attributed to angiogenesis in ischemic limb injury [78], as well as VEGF modRNA [79]. Type 2 phosphatidylinositol-5-phosphate-4-kinase-gamma (Pip4k2c), an mTORC1 regulator delivered by modRNA, significantly inhibited TGFβ1 by its N-terminal motif, thus inhibiting cardiac fibrosis [80]. Another method to increase the number of CMs is to reprogram cardiac fibroblasts directly into CMs by viral introduction of lineage core transcription factors such as Gata4, Hand2, Mef2c, and Tbx5 [60]. Nevertheless, despite utilizing distinct approaches to enhance the redifferentiation rate, the efficiency of this method remains low, because of the limited number of fibroblast cells and eventual totally reprogrammed CMs [81]. Moreover, fibroblasts can be differentiated into endothelial cells, which can assistant the beating of CMs. Until now, there has been no relevant modRNA therapy of fibroblast differentiation for MI treatment [82]. As an emerging field of MI treatment, there should be a focus on more gene modification therapies. The above-described studies reveal the efficiency of using direct or indirect methods for the treatment of MI. Modified mRNA-based therapy mainly focuses on the proliferation and differentiation of CMs; modRNA-based therapy can promote angiogenesis, promote stem cells to differentiate to ECs, or inhibit hostile microenvironment formation, such as fibrosis and hypoxia (Table 1). Modified mRNA is a potent technique for MI treatment because it circumvents the limitations proposed by traditional DNA and protein-based therapies. Transfection by modRNA is attributed to transient protein expression, which no longer needs long-term protein expression. Nevertheless, there are still some problems that need to be addressed. For modRNA to be functional in the body, it must be delivered to the specific scar area first, and then transported into the specific cells, evading the endosomal entrapment, and going to the cytosol, eventually translating to an encoded protein [86]. Any obstruction across the complicated procedure will significantly affect the final translation. However, modRNA dissolved in a solution is non-specifically absorbed or has premature clearance, which fails in the specific area at the first step [85]. Importantly, current modRNA-based therapy has no tissue and cell type-specific target ability in vivo, whereas adeno-associated virus vehicles can include tissue-specific promoters [87]. Moreover, the merit of modRNA, a short and transient expression of mRNA, also seems like a shortcoming. Whether the short-term expression is enough to induce authentic efficiency of myocardial regeneration or not, is still under debate [84]. Additionally, there are still some issues that have not been addressed, such as the optimal delivery route with an atraumatic operation (intramyocardial or transvascular), and the minimal effective dosage for cost-saving modRNA. To address these limitations, developing modRNA with long-term duration (2–3 weeks) or developing a method to repeat transfection of modRNA with non-invasion to sustain an effective protein level for a longer, under-controlled period, may accomplish a longer lasting efficacy. Moreover, modRNA target-specific genes or tissues are required because activating intracellular genes in incorrect cells are harmful. Combinations of genes or materials or other vectors are also needed to guarantee specific and non-invasive transport of RNA. More recently, application of the CRISPR-Cas13 system, which adopts bacteria to degrade viral RNA with high efficiency and to reduce the off-target effect, makes it possible to modify mRNA in a more efficient and safe way [88]. The clinical evaluation of modRNA-based therapy for MI is still in the initial state. In 2019, a phase I trial was conducted to evaluate the therapeutic effect and safety of AZD8601, an experimental VEGF-A-mRNA, which was formulated in biocompatible citrate-buffered saline and optimized for high-efficiency VEGF-A expression with minimal innate immune response [89]. Directly injecting a novel medicine into a human heart is extremely dangerous; therefore, this phase I safety study injected VEGF-A mRNA into the skin of 33 men, and showed temporary and plentiful production of a therapeutic protein without severe side effects. In 2021, positive results were reported from a phase 2 study that evaluated the clinical effect of AZD8601 using epicardial injection in patients who underwent coronary artery bypass grafting with moderately decreased left ventricular function (ejection fraction 30–50%) [90]. The results showed that exploratory efficacy endpoints were met, including increased left ventricular ejection fraction and decreased NT-proBNP level. Although there are still limited results regarding modRNA-MI therapy, the early clinical trials presented today are a result of pushing new boundaries in the treatment of cardiovascular and other ischemic vascular diseases to address serious unmet needs, with the goal of improving patients’ lives. Future advanced clinical trials incorporating more MI patients should be conducted within 10 years. Only in these ways can patients indeed get the benefits from the modRNA delivery system. Despite numerous studies that have been undertaken in terms of MI treatment, there are still many obstacles to curing MI. Especially, CMs have a limited capacity to regenerate even by strongly extrinsic or intrinsic stimuli. Modified mRNA-based therapy is an excellent therapeutic method to solve preclinical and clinical questions for cardiac regeneration with its properties of efficiency, non-immunogenicity, transiency, and relative safety. However, so far, a comprehensive summary of modRNA-based therapy has not been proposed, and further exploration of modRNA-based therapy needs to be discussed. Firstly, we summarized the optimization of modRNA-based therapy, including gene modification and delivery materials of modRNA. In the articles discussed above, the translation efficiency of modRNA-based therapy can be further improved via editing nucleotides or a combination of modified nucleosides, optimization of the 5′ UTR and 3′ UTR vector sequences, optimal pH value, as well as optimal dosage values in vitro and in vivo. Additionally, appropriate vehicles, such as RNAiMAX in vitro, nanoparticles, LNPs, and FLNPs in vivo, are crucial to delivering disease-specific genes to the myocardium. A combination of gene modification and delivery materials, can maximize the potential utility of modRNA for gene therapy. Secondly, we focused on the efficacy and mechanisms of modRNA-based therapy in MI treatment; modRNA-based therapy can promote the proliferation of CMs and differentiation of stem cells and can also alleviate the harsh microenvironment of the myocardium, for example, inhibiting fibrosis and promoting angiogenesis. Therein, VEGF and VEGF-A both have important effects on angiogenesis and pro-angiogenic differentiation in modRNA-based therapy. Other genes, such as FSTL1 and Pkm2, can promote CM proliferation, meanwhile, IGF-1, a growth factor activity, and integrin binding related gene, can promote differentiation of EPCs. Multiple genes-combined modRNA termed cocktail therapy, markedly upregulate pro-angiogenic MSC markers and transcription factor. Finally, we summarized the principal obstacles and future direction of modRNA-based therapy. There is a need to develop modRNA with more safety, cost-effectiveness, stable transfer vectors, and relatively long-term controlled protein expression. Finally, the scale-up from animal experiments and clinical translation requires non-invasive methods. The clinical translation should be evaluated as soon as there is adequate evidence from animal studies.

PMC10003381

Isaac Narbona-Sánchez,Alba Pérez-Linaza,Isabel Serrano-García,Inmaculada Vico-Barranco,Luis M. Fernández-Aguilar,José L. Poveda-Díaz,María J. Sánchez del Pino,Fermín Medina-Varo,Mikel M. Arbulo-Echevarria,Enrique Aguado

Expression of Non-T Cell Activation Linker (NTAL) in Jurkat Cells Negatively Regulates TCR Signaling: Potential Role in Rheumatoid Arthritis

26-02-2023

NTAL,LAT2,LAB,rheumatoid arthritis,TCR,signaling

T lymphocytes are key players in adaptive immune responses through the recognition of peptide antigens through the T Cell Receptor (TCR). After TCR engagement, a signaling cascade is activated, leading to T cell activation, proliferation, and differentiation into effector cells. Delicate control of activation signals coupled to the TCR is needed to avoid uncontrolled immune responses involving T cells. It has been previously shown that mice deficient in the expression of the adaptor NTAL (Non-T cell activation linker), a molecule structurally and evolutionarily related to the transmembrane adaptor LAT (Linker for the Activation of T cells), develop an autoimmune syndrome characterized by the presence of autoantibodies and enlarged spleens. In the present work we intended to deepen investigation into the negative regulatory functions of the NTAL adaptor in T cells and its potential relationship with autoimmune disorders. For this purpose, in this work we used Jurkat cells as a T cell model, and we lentivirally transfected them to express the NTAL adaptor in order to analyze the effect on intracellular signals associated with the TCR. In addition, we analyzed the expression of NTAL in primary CD4+ T cells from healthy donors and Rheumatoid Arthritis (RA) patients. Our results showed that NTAL expression in Jurkat cells decreased calcium fluxes and PLC-γ1 activation upon stimulation through the TCR complex. Moreover, we showed that NTAL was also expressed in activated human CD4+ T cells, and that the increase of its expression was reduced in CD4+ T cells from RA patients. Our results, together with previous reports, suggest a relevant role for the NTAL adaptor as a negative regulator of early intracellular TCR signaling, with a potential implication in RA.

Expression of Non-T Cell Activation Linker (NTAL) in Jurkat Cells Negatively Regulates TCR Signaling: Potential Role in Rheumatoid Arthritis T lymphocytes are key players in adaptive immune responses through the recognition of peptide antigens through the T Cell Receptor (TCR). After TCR engagement, a signaling cascade is activated, leading to T cell activation, proliferation, and differentiation into effector cells. Delicate control of activation signals coupled to the TCR is needed to avoid uncontrolled immune responses involving T cells. It has been previously shown that mice deficient in the expression of the adaptor NTAL (Non-T cell activation linker), a molecule structurally and evolutionarily related to the transmembrane adaptor LAT (Linker for the Activation of T cells), develop an autoimmune syndrome characterized by the presence of autoantibodies and enlarged spleens. In the present work we intended to deepen investigation into the negative regulatory functions of the NTAL adaptor in T cells and its potential relationship with autoimmune disorders. For this purpose, in this work we used Jurkat cells as a T cell model, and we lentivirally transfected them to express the NTAL adaptor in order to analyze the effect on intracellular signals associated with the TCR. In addition, we analyzed the expression of NTAL in primary CD4+ T cells from healthy donors and Rheumatoid Arthritis (RA) patients. Our results showed that NTAL expression in Jurkat cells decreased calcium fluxes and PLC-γ1 activation upon stimulation through the TCR complex. Moreover, we showed that NTAL was also expressed in activated human CD4+ T cells, and that the increase of its expression was reduced in CD4+ T cells from RA patients. Our results, together with previous reports, suggest a relevant role for the NTAL adaptor as a negative regulator of early intracellular TCR signaling, with a potential implication in RA. T cells recognize antigens in the form of small peptides coupled with Major Histocompatibility Complex (MHC) molecules via a clonally distributed antigen receptor called the T-cell receptor (TCR). Upon TCR binding by a peptide–MHC complex (pMHC), an intracellular signaling cascade is triggered in T cells, leading to their activation and proliferation. Intracellular signals include tyrosine phosphorylation of several proteins, which allows their enzymatic activation or recruitment to different subcellular compartments. One of the first signaling events triggered after TCR engagement is the Lck-mediated phosphorylation of tyrosine residues found on ITAMs present in the cytosolic domains of CD3 [1,2]. Phosphorylated ITAMs recruit the tyrosine kinase ZAP70, leading to its phosphorylation and activation by Lck, and activated ZAP70 phosphorylates the LAT (Linker for Activation of T cells) transmembrane adaptor [3,4]. Tyrosine phosphorylation of LAT generates docking sites for cytosolic adaptors such as Grb2, Gads, and SLP-76, or effectors such as PLC-γ1 or Vav. However, despite the central role of LAT in the transduction of activator signals coming from the TCR complex, analysis of several knock-in mouse strains showed that the LAT adaptor is also capable of negatively regulating T-cell homeostasis [5,6,7,8]. LAT expression is restricted to thymocytes, peripheral T lymphocytes, Natural Killer (NK) cells, mast cells, and platelets, but is not expressed in B cells [9]. NTAL (non-T cell activation linker) is a LAT-like adaptor protein that is expressed in B, NK, and mast cells, which is rapidly phosphorylated after BCR or FcR engagement [10,11]. While NTAL lacks a binding site for PLC-γ1, both adapters are capable of generating binding sites for Gads and Grb2 [10,11], and the three NTAL C-terminal tyrosines are essential for signal transduction [12]. Although LAT knockout results in a block of thymic development and the absence of mature peripheral T cells [13], NTAL knockout mice show no difference in the development or phenotype of the B compartment as compared to normal mice [14]. Interestingly, NTAL knockout eventually developed an autoimmune syndrome characterized by splenomegaly and the presence of antinuclear antibodies [15]. The B cells present in these mice were normal, but T cells showed a hyperactivated phenotype producing high levels of cytokines such as IL-2, IL-10, and INF-γ, demonstrating for the first time that NTAL can negatively regulate T cell activation. This paradoxical phenotype could be explained by the fact that, although NTAL is not expressed in resting T lymphocytes, it is indeed expressed in activated T cells [15]. This regulatory role of NTAL in T cells is consistent with the fact that although an NTAL transgene expressed in a LAT-deficient strain is able to restore T cell development, these mice develop severe organomegaly with hyperactivated T cells, producing large amounts of TH2 cytokines [16]. In addition, NTAL seems to play a negative regulatory function in B cells, since NTAL deficient B cells exhibit slightly increased Ca2+ mobilization and proliferation after BCR crosslinking [11,14]. Thus, despite its similarity to LAT, the NTAL adaptor does not exert a function in B cells that is similar to the role played by LAT in T cells [14,16]. Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by persistent synovitis, inflammation, and autoantibodies against rheumatoid factor and citrullinated peptide, affecting up to 1% of the world’s population [17]. Although the etiology of RA remains unresolved, a genetic component of susceptibility to RA has been firmly established [18]. There are more than 100 confirmed polymorphisms showing a strong association with RA, mainly with MHC class-II alleles, thus reinforcing the central role of adaptive immunity, particularly effector T cells. Among the more than 100 genes implicated in RA predisposition, many of them are involved in T-cell selection, maturation, and function [19,20]. Tumor necrosis factor (TNF) plays a central role in the pathogenesis of RA, and TNF inhibitors effectively suppress inflammatory activity in RA in a percentage of patients [21]. However, the considerable inter-patient variability in response to the current treatments is a challenge, and more biomarkers are needed for patient classification. It has been recently reported that p-p38, IkBa, p-cJun, p-NFkB, and CD86 may constitute markers for differentiation between RA patients and healthy donors [22]. Although the intracellular signals responsible for the activation of T lymphocytes following antigen recognition are well understood, we still lack a thorough understanding of the molecular mechanisms by which tolerance mechanisms are broken down in genetically susceptible individuals. In this context, it can be proposed that autoimmune diseases would be triggered either by an increase in the percentage of autoreactive T lymphocytes, or by defects in any of the peripheral tolerance mechanisms, or by a combination of both. Any of these scenarios would be the result of alterations in the intracellular signaling cascade associated with the TCR, so a detailed analysis of these events could be useful to elucidate the molecular mechanisms underlying RA, and consequently facilitate the discovery of prognostic and/or diagnostic markers. In this report we confirmed that NTAL expression in Jurkat cells negatively affects TCR-mediated signals and that the NTAL adaptor is expressed in human CD4 T cells after CD3/CD28 stimulation. Moreover, comparative analysis showed that the NTAL expression increase in CD4 T cells from RA patients was reduced as compared with healthy controls, and that CD3 stimulation of CD4 T cell blasts from RA patients generated a greater phosphorylation of Erk when compared with CD4 T cells from healthy controls, suggesting that decreased NTAL expression could affect the disease progression. Altogether, our data support a role for NTAL as a negative regulator of early intracellular TCR signaling, which could have relevance in immune-based pathologies. To analyze the potential role of NTAL expression in T cell function, we generated Jurkat cells expressing this adaptor protein by means of a lentiviral system [23]. This system allows the generation of polyclonal cell populations, avoiding the undesired effects of analyzing individual clones. In all cases, since our vector had a GFP reporter behind an IRES sequence [23], the vector expression levels were higher than 80%. As can be seen in Figure 1A, Jurkat cells do not express the NTAL adaptor, and after a lentiviral transfection NTAL adaptor was detected by Western blot. Following TCR engagement, the protein tyrosine kinase ZAP70 is rapidly phosphorylated on several tyrosine residues. Phosphorylation of tyrosine 319, located in the interdomain B of ZAP70, is needed for the transduction of intracellular signals coming from the TCR/CD3 complex [24]. Thus, Jurkat cells expressing NTAL were stimulated at 37 °C with anti-CD3 monoclonal antibody, and whole-cell lysates were obtained after 0, 3, 10, and 30 min of stimulation. As can be seen in Figure 1B, anti-CD3 stimulation induced a rapid increase in the phosphorylation level of Tyr319 of ZAP70 in both Jurkat cells and Jurkat cells expressing NTAL (Jurkat-NTAL). No clear differences in the phosphorylation level of Tyr319 in ZAP70 were observed between Jurkat and Jurkat-NTAL cells. Densitometric quantification of four independent experiments failed to show differences in the activation of ZAP70 (Figure 1C). It has been described that T cells from NTAL knockout mice show increased calcium responses after TCR/CD3-mediated stimulation [15]. Therefore, it was of interest to verify whether the expression of NTAL in Jurkat cells decreases calcium influx generation. To do so, Jurkat and Jurkat-NTAL cells were labeled with the intracellular calcium indicator Indo-1 and then stimulated with anti-CD3 mAb. Before the stimulation, cells were kept at 37 °C for one minute, and then stimulated with anti-CD3 mAb (OKT3, 1 μg/mL). The increase in the ratio of fluorescence emitted at 405 and 485 nm (F405/F485) was collected alternately and was indicative of the rise in intracellular calcium concentration. As can be seen in Figure 2A, the calcium concentration increased after CD3-mediated stimulation in both Jurkat and Jurkat-NTAL cells. The intensity of such increase was similar for both types of cells, but after reaching a peak about two minutes after anti-CD3 stimulation (about 200 s from the start of the experiment), the calcium concentration began to decline slowly, and this decline was more pronounced in Jurkat-NTAL compared with Jurkat cells (Figure 2A). The difference in calcium concentration between Jurkat and Jurkat-NTAL cells reached statistical significance after approximately 5 min (300 s) from the start of the experiment. We next sought to verify whether the observed calcium reduction was caused by a deficient PLC-γ1 activation. Thus, Jurkat and Jurkat-NTAL cells were stimulated with the OKT3 anti-CD3 mAb and phosphorylation of tyrosine 783 in PLC-γ1 was analyzed by Western blot in the corresponding cell lysates. As can be seen in Figure 2B, CD3 stimulation induced phosphorylation of PLC-γ1-Tyr783, which is indicative of its enzymatic activation [25]. Both Jurkat and Jurkat-NTAL cells showed upregulation of PLC-γ1 phosphorylation at all stimulation time points analyzed (Figure 2B). Interestingly, PLC-γ1 phosphorylation in Jurkat-NTAL cells was reduced compared with Jurkat cells. Densitometric quantification of four independent experiments show that the relative phosphorylation of Tyr783 in PLC-γ1 was statistically higher in Jurkat cells compared with Jurkat-NTAL cells after 10 min of CD3 stimulation. Therefore, these results support the view of NTAL as a negative regulator of intracellular calcium-dependent signaling pathways associated with the TCR/CD3 complex. It has been shown that TCR stimulation leads to Erk activation through two different mechanisms, and both of them need phosphorylation of the LAT membrane adaptor [26]. One of these mechanisms requires the activation of the PLC-γ1-RasGRP1 pathway, while the other depends on the binding of Grb2-SOS to phosphorylated LAT. Given the negative effect of NTAL expression on PLC-γ1 activation, it was of interest to test what happened in the activation of the MAP kinase pathway after activation through the TCR/CD3 complex in Jurkat cells expressing NTAL. Accordingly, Erk phosphorylation at residues Thr202/Tyr204, which is indicative of its enzymatic activation, was analyzed in lysates of Jurkat cells stimulated for different times. As observed in Figure 3A, anti-CD3 stimulation induced rapid Erk phosphorylation, which was clear at 3 min of stimulation, and was still appreciable at 30 min. However, after densitometric quantification of four independent experiments, we were not able to appreciate quantitative differences in the relative Erk phosphorylation levels in Jurkat and Jurkat-NTAL cells (Figure 3A, right graphics). This result was rather unexpected, given the negative effect that NTAL expression had on PLC-γ1 activation. In order to further test the effect of NTAL expression on the MAP-kinase pathway, we analyzed the activation of MEK, i.e., the kinase responsible for the phosphorylation and activation of Erk [27]. Therefore, we used a specific antibody to phospho-MEK-1/2 to investigate MEK activation. CD3 stimulation of Jurkat cells rapidly induced phosphorylation of MEK, and the same was observed for Jurkat-NTAL cells (Figure 3B). Again, densitometric quantification of four independent experiments did not show any difference between both types of cells (Figure 3B, right panel). Therefore, from these results we can conclude that NTAL expression in Jurkat cells does not modify the activation of the MAP-kinase pathway. It has been previously shown that mouse peripheral T lymphocytes can express NTAL adaptor after activation [15]. Given that NTAL knockout mice develop an autoimmune syndrome with hyperactivated T cells, producing higher levels of cytokines than T cells from wild type mice, it was of interest for us to study if T cells from healthy donors and Rheumatoid Arthritis (RA) patients express this transmembrane adaptor. Thus, we obtained peripheral blood from healthy donors and rheumatoid arthritis patients, and CD4+ T lymphocytes were purified and cultured for 5 days in the presence of anti-CD3/CD28 beads and recombinant interleukin-2 (IL-2). The percentage of CD3+CD4+ T cells from both RA patients and healthy donors was analyzed by flow cytometry, and the average was higher than 85%. Cell lysates were obtained from resting and activated cells, and NTAL expression was determined by Western blot with a specific mAb. Membranes were stripped and subsequently blotted with anti-β-actin mAb in order to determine total protein load and allow comparative analysis. As shown in Figure 4A, samples corresponding to resting cells from both healthy controls (C) and RA patients (P) showed very low, barely detectable levels of NTAL expression, with one exception. The activation of T cells with anti-CD3/CD28 beads plus IL-2 led to an increase in the number of cellular proteins, as demonstrated by β-actin Western blots (Figure 4A, bottom panels). Interestingly, the activation of T cells induced the expression of the NTAL protein (Figure 4A, top panels), demonstrating that the NTAL adaptor is also expressed in activated CD4+ T cells. We performed densitometric quantification of bands and calculated the relative expression of NTAL with regard to β-actin expression for resting and activated CD4+ T cells for 7 healthy controls and 16 RA patients. Every experiment with CD4+ T cells was always performed at the same time with one healthy control, and for quantifications a value of 1.0 was assigned to resting cells from healthy controls. As it can be seen in Figure 4B, resting CD4+ T cells from RA patients showed slightly enhanced relative expression of NTAL compared with CD4+ T cells from healthy controls, although there was not statistical significance. However, the relative expression of NTAL in activated CD4+ T cells was higher in healthy controls compared with RA patients (Figure 4B), although, again, the difference did not reach statistical significance (p = 0.1030). Given that the NTAL expression levels were slightly higher in resting cells from RA patients, we decided to calculate the relative increase in the expression of this membrane adaptor in CD4+ T cells from patients and healthy controls. As can be seen in Figure 4C, the increase was greater in healthy controls than in patients, and in this case there was a statistically significant difference (p < 0.05). Therefore, the induction of NTAL expression, which appears to act as a brake on T-cell activation, was decreased in rheumatoid arthritis patients relative to healthy controls, which could explain part of the pathology of these patients. Data obtained in mice demonstrated that TCR-mediated signaling was enhanced in T cells from NTAL knockout mice [15]. Interestingly, the same group showed that an NTAL transgene under the control of the human CD2 promoter in mouse T cells produced a significant reduction of TCR-signaling. Our data show that the induction of NTAL expression in CD4+ T cells from RA patients was reduced compared with healthy controls, and this could mean that they would be activated more intensely. Therefore, we purified CD4+ T cells from RA patients and healthy controls and cultured them in the presence of anti-CD3/CD28 and IL-2 for 5 days in order to induce NTAL expression, and then analyzed Erk activation after anti-CD3 stimulation. Figure 5A shows three independent experiments in which CD4+ T blasts were stimulated for 0, 5, and 10 min with anti-CD3 mAb, which induced phosphorylation of Erk. Membranes were stripped and reblotted with anti-Erk mAb to show total protein load for every sample and allow densitometric quantification. The images show that, although variations in Erk phosphorylation were observed, a trend was evident wherein CD4+ T cells from RA patients exhibited a higher induction of Erk phosphorylation (Figure 5A). Five independent experiments were performed, always including a healthy control with samples from RA patients. Quantification of Erk phosphorylation for five healthy controls and nine RA patients did show increased Erk activation in RA patients compared with healthy controls, at both 5 and 10 min, with a statistically significant difference at 5 min of anti-CD3 stimulation. Consequently, this result is concordant with the lower induction of NTAL expression in CD4+ T cells in RA patients, which could be one of the causes of T cell hyperactivation in this pathology. RA is a chronic inflammatory disease affecting the synovium, leading to joint damage and bone destruction, and causes severe disability and increases mortality [17]. Prevalence studies of RA show a substantial variation of the disease occurrence among different populations, with a prevalence of 0.5–1.1% in Northern European and North American areas, and a relatively lower prevalence of in 0.1–0.5% in developing countries [17]. There is a consensus that RA is a multifactorial disease, resulting from the interaction of genetic and environmental factors. Although the etiology of RA remains unresolved, a genetic component of susceptibility to RA has been firmly established [18]. More than 100 polymorphisms associated with RA have been confirmed, mainly with MHC class-II alleles, pointing to the involvement of adaptive immunity mechanisms in the origin and development of this disorder [19,20]. In this context, it has been suggested that infectious agents could activate adaptive immune responses triggering the development of the disease in genetically susceptible individuals [19]. Therefore, balanced and carefully controlled immune responses are essential to avoid adverse reactions that could lead to autoimmune pathological processes. T cells are central players in adaptive immune responses, and these cells are specifically activated upon antigen recognition through the TCR. After TCR engagement, an intracellular signaling cascade is triggered, leading to the activation and proliferation of naive T cells, as well as their differentiation into effector/memory cells. Regulation of such signals is crucial to prevent exaggerated responses, which might be harmful for the organism. TCR-activating intracellular signals are well understood, but many spatiotemporal and regulatory aspects remain to be discovered [1,2]. In contrast to LAT with respect to T cells, NTAL knockout does not impair the development of B cells, NK cells, or mast cells [14,28]. Remarkably, mast cells from NTAL-deficient mice showed increased degranulation, calcium flux, and cytokine production [29], indicating that, like LAT, NTAL also possesses intrinsic functions to control cell activation. Additionally, aged NTAL knockout mice develop an autoimmune syndrome, with enlarged spleens and production of autoantibodies, which is due to the absence of NTAL expression on activated T cells [15]. This was the first time that expression of this transmembrane adaptor was demonstrated in activated mouse T cells, raising the possibility that NTAL expression could control excessive T cell activation. We demonstrated that human CD4+ T lymphocytes from healthy donors express the NTAL adaptor after stimulation with anti-CD3/CD28 microbeads plus IL-2. Therefore, this seems to be a general mechanism for the control of immune responses mediated by T lymphocytes. Concordantly, NTAL expression in Jurkat cells negatively modulates calcium influxes and PLC-γ1 activation after CD3 stimulation. In contrast, NTAL expression in Jurkat cells does not modify ZAP70 activation. This is an expected result, since LAT and NTAL adaptors are known substrates of ZAP70 and Syk tyrosine kinases, respectively [1,30]. Moreover, ZAP70 is the only kinase phosphorylating NTAL in T cells, since Syk is not expressed in this population. Therefore, it was not foreseeable that an effector such as ZAP70 upstream of NTAL would be affected in its enzymatic activity. Consequently, the negative role exerted by NTAL expression in PLC-γ1 activation and calcium influx generation may be due to competition with LAT for localization in lipid rafts, as previously suggested by others [15]. It is possible that ZAP70 substrates (LAT and NTAL) compete for space in membrane areas, but one of them (NTAL) lacks a PLC-γ1-binding site, causing its activation to be reduced. However, as opposed to calcium fluxes and PLC-γ1 activation, Erk and MEK phosphorylation are not affected by the expression of NTAL in Jurkat cells. The latter is a conflicting result with that observed by Zhu et al. in NTAL-deficient mice and transgenic mice expressing NTAL in T cells [15], in which the negative effect of NTAL expression on Erk phosphorylation was demonstrated. One possible explanation for this discrepancy may lie in the difference between the Jurkat cell line and primary T cells. In fact, even the involvement of the LAT adaptor with Erk activation is controversial. We previously showed that Erk phosphorylation is similar in the absence of LAT in J.CaM2 cells (a Jurkat derivative deficient in LAT expression) cells, and the reintroduction of LAT had no substantial effect on Erk phosphorylation [31]. On the other hand, using a conditional knockout mouse strain with normal thymic development but able to generate CD4+ T lymphocytes deprived of LAT [8], Malissen and coworkers showed that CD3-mediated stimulation of CD4+ T lymphocytes did not induce Erk phosphorylation. Besides, Samelson and coworkers demonstrated a LAT-independent pathway by which Erk can be activated after CD3 stimulation [32]. Therefore, given the functional complexity of LAT and NTAL adaptors, the different effects observed in Jurkat and primary T cells are not surprising. More work is needed to shed definitive light on this point. Given the potential role of NTAL as a negative regulator of T cell activation, we sought to verify whether activated CD4+ T cells from RA patients expressed this transmembrane adaptor or not. We demonstrated for the first time that human T cells are able to express NTAL after CD3/CD28-mediated activation. Our data obtained in Jurkat cells, together with the phenotype of NTAL knockout and NTAL-Tg mice, suggest that in RA patients, in whom T-cell hyperactivation is one of its typical hallmarks [19,20], there would be a deficit of NTAL expression. We found that activated CD4+ T cells from RA patients showed a reduced increase in the expression of NTAL as compared with healthy controls. We are aware that of our work involves a small number of patients. Another limitation is the lack of study on CD8+ T cells. Future work should address, with a larger number of patients, the combined analysis of both populations. However, our data suggest that NTAL expression may act as a brake on excessive T-cell activation. Very little is known about the regulation of NTAL expression at the transcriptional level. It has been shown that the leukaemia-specific fusion oncoprotein RUNX1/RUNX1T1 represses the expression of NTAL [33]. Indeed, knockdown of RUNX1/RUNX1T1 with small interfering RNA (siRNA) decreased NTAL expression in Kasumi-1 cells, a myeloblast cell line widely used as a model for the study of myeloid leukemias [34]. Interestingly, these authors showed that repression of NTAL expression is readily reversed by the use of entinostat and mocetinostat, two histone deacetylase (HDAC) class I-specific inhibitors. If the reduced expression of NTAL in activated T cells from RA patients is confirmed as a key factor in the development and/or progression of this disease, the use of these drugs as a potential therapy for its control would not be ruled out. Consistent with a reduced increase in NTAL expression in activated CD4+ T cells from RA patients, they show increased activation of Erk phosphorylation. Although we did not observe any modification in Erk or MEK phosphorylation in Jurkat cells expressing NTAL, the Jurkat model is perhaps not suitable for the analysis of the MAP-kinase signaling pathway. Our data obtained in activated CD4+ T cells are consistent with previous reports showing increased excessive activation of the Ras/MEK/ERK pathway in T lymphocytes from RA patients as compared with T cells from healthy donors [35]. In line with that, pharmacological inhibition of Ras GTPases significantly reduced the disease in the rat adjuvant-induced arthritis model (AIA) [36]. The association of RA with a non-synonymous SNP (R620W) missense mutation in the PTPN22 phosphatase has been shown [37]. PTPN22 is a tyrosine phosphatase involved in the regulation of TCR signaling, and this mutation increases its phosphatase activity, lowering the TCR threshold. Here, we presented data pointing to the decreased induction of NTAL expression on CD4 T cells in RA patients. This could be an additive factor for the development and progression of the disease. If confirmed, new therapeutic strategies aimed at increasing the expression of this membrane adaptor on T cells could be explored. Jurkat cells were grown in complete RPMI 1640 medium supplemented with 10% FCS (both from Lonza, Basel, Switzerland), and 2 mM L-glutamine at 37 °C in a humidified atmosphere containing 10% CO2. NTAL cDNA cloning was performed as previously described [23]. The coding sequence in the plasmid was verified by sequencing, and then subcloned in the SIN lentiviral transfer plasmid pHR’SINcPPT-Blast through site-specific recombination (Gateway LR Clonase, Invitrogen, Waltham, MA, USA). Lentiviral supernatants were generated and used to induce NTAL expression in polyclonal cell populations. Blasticidin selection (20 μg/mL) was applied to transduced cells after 72 h of culture, and the expression of GFP was analyzed as a reporter of transfection using FACS analysis (CytoFLEX, Beckman Coulter, Brea, CA, USA). In all cases, the percentage of GFP-positive cells was higher than 80%. Anti-LAT, anti-PLC-γ1, and anti-Erk antibodies were from Santa Cruz Biotechnology (Heidelberg, Germany). The anti-NTAL NAP-07 monoclonal antibody was from EXBIO (Prague, Czech Republic). Antibodies binding phospho-Erk, phospho-PLC-γ1-Tyr783, ZAP70, phospho-ZAP70-Tyr319, phospho-MEK-Ser221, and anti-MEK were from Cell Signaling Technology. Anti-β-actin, anti-CD3 (OKT3), and anti-CD4 monoclonal antibodies were provided by Biolegend (San Diego, CA, USA). Ethical approval for this study was obtained from the Comité Coordinador de Ética de la Investigación Biomédica de Andalucía (Spain) (reference numbers 01/2018 and 120.21), and informed consent was obtained from all subjects enrolled. Patients’ and healthy controls’ blood samples were collected in the Rheumatology area of the Hospital Puerta del Mar (Cádiz, Spain). Patients had confirmed written diagnosis of Rheumatoid Arthritis according to ACR/EULAR 2010 criteria. All patients and healthy controls, males and females, were between 41 and 72 years old. RA patients had a mild-to-moderate inflammatory burden, and their treatment consisted of conventional disease-modifying antirheumatic drugs (DMARD). CD4+ T cells were purified from peripheral blood using the RosetteSep Human CD4+ T Cell Enrichment Cocktail kit (Stemcell Technologies, Vancouver, BC, Canada), following the manufacturer’s instructions, and the purification was efficiency was tested by flow cytometry. Purified CD4+ T cells were subsequently cultured in 24-well plates, at a density of 1 × 106 cells/mL in RPMI 1640 medium supplemented with 10% FCS (both from Lonza, Basel, Switzerland), and 2 mM L-glutamine at 37 °C in a humidified atmosphere containing 10% CO2. Dynabeads® Human T-activator CD3/CD28 (Gibco Laboratories, Paisley, Great Britain) were used to activate cells, at a cell:bead ratio of 1:1, together with recombinant interleukin-2 (IL-2) at 40 U/mL. Cells were cultured under these conditions for 5 days before analysis. Lentivirally transduced Jurkat cells were starved in RPMI 1640 without FCS for 3 h prior to stimulation with anti-CD3 monoclonal antibody (mAb) at 37 °C. Cells were then lysed at 2.0 × 107 cells/mL in 2× Laemmli buffer, followed by incubation at 99 °C for 5 min and sonication. For Western blotting, whole-cell lysates were separated by SDS-PAGE and transferred to PVDF membranes, which were incubated with the indicated primary antibodies, followed by the appropriate secondary antibody conjugated to IRDye 800 CW (Li-Cor, Lincoln, NE, USA) or horseradish peroxidase (HRP). Reactive proteins were visualized using the Odyssey CLx Infrared Imaging System (Li-Cor, Lincoln, Nebraska USA), or by enhanced chemiluminescence (ECL) acquired in a ChemiDoc Touch Imaging System (Bio-Rad Laboratories, Hercules, CA, USA). For reprobing, PVDF membranes were incubated for 10 min at room temperature with WB Stripping Solution (Nacalai Tesque, Kyoto, Japan), followed by a TTBS wash. Measurement of intracellular free Ca2+ was carried out using Indo-1 AM (acetoxyme-thyl) (2 μM; Molecular Probes, Invitrogen) as previously described [31]. Calcium measurements were performed using a Synergy MX Multi-Mode Reader (Biotek, Winooski, VT, USA) at 37 °C. Cells were excited by light at a wavelength of 340 nm, and the fluorescence emitted at 405 and 485 nm was collected alternately per second. Calcium mobilization was evaluated by the ratio of 405/485 nm fluorescence signal. Statistics were processed with Microsoft Excel using a two-tailed t-test. Levels of significance p < 0.05 are presented as *, and p < 0.01 as **.

PMC10003384

Chunyuan Yin,Amy C. Harms,Thomas Hankemeier,Alida Kindt,Elizabeth C. M. de Lange

Status of Metabolomic Measurement for Insights in Alzheimer’s Disease Progression—What Is Missing?

04-03-2023

Alzheimer’s disease,metabolomics,lipidomics,biomarkers,pathways,animal,human

Alzheimer’s disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Status of Metabolomic Measurement for Insights in Alzheimer’s Disease Progression—What Is Missing? Alzheimer’s disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis. Alzheimer’s disease (AD), the most common form of dementia in aging population, leads to the progressive loss of memory and other cognitive functions [1]. In 1907, Dr. Alois Alzheimer discovered the first patient with senile plaques and NFTs, which represent the major hallmarks of AD which has become a major public health problem due to the increase in the elder population worldwide [2]. AD can be divided into two types: familial AD (5%) and sporadic AD (95%). Familial AD (FAD) has an early onset (<65 years of age) and it is caused by mutations in the genes encoding amyloid precursor protein (APP) and presenilin 1 and 2 (PS1 and PS2) [3]. Age is a major risk factor for AD, but inactivity (lack of exercise), obesity, diabetes, high blood pressure, high cholesterol, and too high alcohol consumption also increase the incidence of AD. Furthermore, it seems that low educational level, social isolation, and cognitive inactivity also contributes to AD [4]. Today, diagnosis of AD is based on several neuropsychological tests, imaging, and biological analyses, which all indicate AD in a later stage. Currently, there is no efficient treatment available, although treatment by the recently approved drug lecanemab seems to delay AD progression [5], and provides some hope. Currently, we know that brain extracellular amyloid deposits, called neuritic senile or amyloid-β plaques, and fibrillary protein deposits inside neurons, known as neurofibrillary bundles or tau tangles, appear mainly in the frontal and temporal lobes and contribute to AD progression [6]. However, there are still many questions about how AD initiates and how it progresses. Information on factors in and mechanism of initiation and progression, therefore, is crucial for earlier diagnosis, as well as to find targets to treat AD in a stage-dependent manner. AD is very complex, and a systems biological approach is warranted. Metabolomics allows such an approach as it can be used to measure biochemical alterations underlying pathological processes thus offering great potential for the diagnosis and prognosis of neurodegenerative diseases. This is because a subject’s metabolome reflects alterations in genetic, transcript, and protein profiles as well as influences from the environment [7]. Moreover, since metabolic pathways are largely conserved between species, metabolomics could improve the translation of preclinical research conducted in animal models of AD into humans. Furthermore, the brain has a high lipid content, which indicates that lipidomics may be a highly valuable omics technique as well, to provide novel insights into AD pathogenesis. In this review, we provide an overview of the current state of application of metabolomics (including lipidomics) research on AD in human and animal models, together with the metabolite information that has been obtained from plasma, brain, and cerebrospinal fluid (CSF) samples in human studies and animal studies. We then analyze this information using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models of different disease stages. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis. Metabolites are substrates, intermediates, and products of metabolic body processes, which typically are small molecules with a molecular weight of less than ~1.5 kDa [8]. Since low molecular weight metabolites are intermediates or end products of cellular metabolism, metabolomics, or the study of metabolism can be considered one of the core disciplines of systems biology. It can help in improving our understanding of changes in biochemical pathways, revealing crucial information that is closely related to human disease or therapeutic status [9,10,11,12,13]. Metabolomics allows the systematic study of unique metabolomic fingerprints that result from the body functioning in different conditions, such as healthy and diseased. These fingerprints can be viewed as biomarkers of normal biological processes, pathological processes, or pharmacological responses to a therapeutic intervention [14,15,16]. Metabolism refers to the biochemical reactions that occur throughout the body within each cell and that provide the body with energy. This energy is needed for vital body processes and the synthesis of new body components [17]. Some of these are mediated by enzymes, with specialized functions in anabolism and catabolism. To that end, the body needs nutrients and energy that come from the diet. Metabolism is affected by many factors such as sex, race, exercise, diet, age, and diseases such as Parkinson’s or Alzheimer’s. The biggest impacts on metabolites are genetics and environment. Lipidomics, a subfield of metabolomics, is the study of the lipidome, i.e., all the lipids within cells, organs, or biological systems. Lipids are vital in the biological processes of living organisms. They not only serve as structural components of cell membranes, but also play an important role in the source of chemical energy and cell signaling molecules [18]. Apart from adipose tissue, which is the most lipid-rich organ, the brain is the body’s second lipid-rich organ; 10% to 12% of the fresh weight and more than 50% of the dry weight is composed of lipids [19]. With significant structural diversity, major lipid species in the brain can be categorized as sphingolipids, glycerolipids, glycerophospholipids, fatty acids, cholesterol, and cholesterol ester. Among them, phospholipids account for 50% of total lipid content [20]. Plasma abnormal lipid profiles have been known to be associated with AD for several decades [21,22,23]. Lipidomics profiling of plasma and tissues has the potential to discover biomarkers of aging or AD, which can contribute to understanding the pathological mechanism of AD. There are a number of metabolomics platforms available, each with its specific advantages and disadvantages, most notably differences in sensitivity, reproducibility, and equipment costs [24]. Due to the diversity of the metabolome and the complexity of biological systems, it is impossible to give a fully comprehensive metabolite profile of a biological sample by using a single analytical platform [25]. Therefore, the choice of analytical platforms will be determined by the nature of the biological specimen to be analyzed, the goal of the analysis, the nature of the compounds under investigation (i.e., polar or apolar, volatile or non-volatile), and the resources of the laboratory [24,26,27]. Numerous metabolomics platforms are commonly used in both targeted and untargeted studies, and include gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), direct-infusion mass spectrometry (DI-MS), and nuclear magnetic resonance (NMR). GC-MS is generally considered a versatile platform given its excellent separation power, sensitivity, and reproducibility [28]. This platform often requires a chemical derivatization procedure to create volatile compounds, which means the compounds profiled are limited to those that are volatile or can be made volatile using this complex and time-consuming procedure [29]. In addition, derivatization can improve volatility, thermal stability, sensitivity, chromatographic selectivity, and peak shapes [30]. GC-MS uses electron ionization (EI) or chemical ionization (CI) to analyze volatile metabolites. EI-MS is a hard ionization technique that does not suffer from ion suppression, which means it can generate quantitative data and extensive and predictable fragmentation for the structural characterization of metabolites [31]. As EI mass spectra are consistent across instruments and laboratories, sample identification in GC-MS is based on the use of EI mass spectral libraries by matching mass spectral fragment ion patterns, which can be seen as a compound-specific “fingerprint” [32,33]. LC-MS, which is also known as high-performance LC-MS (HPLC-MS) or ultra-HPLC (UHPLC or UPLC), is predominantly used in metabolomics and can provide analysis of thermally non-volatile, unstable, high- or low-molecular weight compounds with wide polarity range. LC-MS does not need a derivatization step, which makes sample preparation simpler and more amenable to high throughput analysis [25]. The columns used in liquid chromatography separate metabolites based on the physical properties of the molecules. Two classes of stationary phases commonly used in metabolomics analysis are hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP). HILIC is good at analyzing highly hydrophilic and ionic compounds and therefore suitable for profiling polar metabolites, whereas RP with C8 or C18 columns is widely used in providing good separation of non-polar or weakly polar compounds [34]. CE-MS has been recognized recently as an attractive complementary technique for metabolomic studies and is particularly suitable for the separation of polar and ionic compounds based on a charge-to-mass ratio. The separation of CE is fast and highly efficient and does not need extensive sample pretreatment [35]. In addition, CE-MS only needs very low or even no organic solvents. A drawback of CE is the poor concentration sensitivity due to the limited sample volume. The currently available CE-MS techniques only allow sample loading of up to 1µL, and usually only utilize 10–100 nL [36]. In addition, migration times of metabolites can fluctuate with changing environmental temperatures, which can lead to reduced reproducibility [37]. DI-MS is a high throughput method with a short analysis time where the sample is directly introduced into the ESI source without chromatographic separation by using a syringe pump or nanospray chip [38]. However, its quantitative performance is inferior to LC-MS because of the strong matrix effect. A stable isotope labeling strategy has been applied to overcome the matrix effect [39]. NMR spectroscopy is an analytical technique based on the exploitation of the magnetic properties of atomic nuclei such as 1H, 13C, and 31P, allowing the identification of different atomic nuclei based on their resonant frequencies, which are dependent on their location in the molecule [14,24,40]. The NMR technique can uniquely and simultaneously quantify a wide range of organic compounds as well as provide unbiased information about metabolic profiles [29]. The applications of NMR spectroscopy are not only limited to liquid samples [41,42,43,44] but can also be used on solid [45,46] and tissue samples [47,48,49,50]. This platform is straightforward, largely automated, and non-destructive, so samples can be reused for further studies [15,29]. The major limitation of NMR for comprehensive metabolite profiling is its relatively low sensitivity, which makes it inappropriate for analyzing low-abundance metabolites [29]. Metabolomics techniques can be divided into untargeted and targeted. Untargeted metabolomics is a global, unbiased analysis of all small-molecule metabolites within a biological system, under a given set of conditions [51]. It measures hundreds of metabolites to identify metabolic changes, in a relative or non-quantitative way, and may serve to identify changed pathways for hypothesis building and further targeted studies [52]. Compared to targeted metabolomics, it is impossible to quantify all metabolites in untargeted metabolomics due to the large number of variables as well as the identity of metabolites is often unknown [53,54,55]. An important advantage of the untargeted approach is that it may also identify new metabolism areas [56,57]. The principal challenges of untargeted metabolomics lie in several aspects: (i) the protocols and time required to process the generated a large amount of raw data, (ii) the bias towards detection of molecules in high-abundance, (iii) the reliance on the intrinsic analytical coverage of the platform used, (iv) identifying and characterizing unknown small molecules [58]. In contrast, targeted metabolomics is the (semi-)quantitative measurement of a predefined set of metabolites [7]. It is commonly driven by a hypothesis or a specific biochemical question [59]. Targeted metabolomics can be effectively used for a pharmacokinetic study of drug metabolism as well as for measuring the influence of therapeutics or genetic modifications on specific enzymes [60]. There are many public databases available for metabolomics studies, such as the Human Metabolome Database (HMDB), METLIN, PubChem, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) [61]. MetaboAnalyst (https://www.metaboanalyst.ca/) (accessed on 1 October 2022) is a powerful tool designed for processing and analyzing LC-MS-based global metabolomics data including spectral processing, functional interpretation, statistical analysis with complex metadata, and multi-omics integration [62]. To investigate the current status of knowledge on metabolomics and insights into AD, for this review, an advanced literature search was performed using the following words: “Alzheimer’s disease [Title] AND (metabolomics OR lipidomics)”, until October 2022. It gave 498 results. We included experimental articles which compared the results of metabolomics analysis performed in biological samples taken from controls and from pathological conditions, both in AD animal models and in AD subjects. Case reports, reviews, editorials, conference summaries, and communications articles were excluded. We found 44 articles that reported the outcomes of metabolomics analyses on CSF, plasma, saliva, and brain tissue samples from human subjects (Table 1) [63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106]. Among them, 5 articles used CSF sample alone, 25 articles used plasma samples alone, 8 articles used brain samples alone, 4 articles used plasma along with CSF samples, 1 article used postmortem CSF samples, and 1 article used saliva samples alone. These human studies have used metabolomics to establish disease-related plasma, brain, and CSF metabolite differences between cognitively normal (CN) individuals, mild cognitive impairment (MCI), and AD patients as predictors of AD progression. In humans, CSF is the only fluid that can be sampled from the CNS, and therefore CSF is often used to obtain some information about what is happening in the brain. The composition of CSF reflects, to some extent, the composition of the brain’s extracellular space environment, which is in close connection with the metabolic processes occurring in this fluid and in the brain cells [107]. Several studies have shown that high CSF-total tau (tTau) and CSF-hyperphosphorylated tau (pTau) levels were found in early AD [108,109]. It is hypothesized that the metabolome in CSF may be altered in MCI or AD [64]. For that reason, the number of metabolomics-based studies investigating CSF composition is rapidly increasing. However, the collection of CSF through a lumbar puncture procedure is invasive and can be painful. It requires a patient’s cooperation which may be challenging especially for elderly people [15]. Blood samples are collected more easily compared to CSF, and would reduce the need for expensive, invasive, and time-consuming tests [110]. However, the difficulty in developing blood-based biomarkers for AD is underscored by the often-unknown ability of the molecule to pass through blood–brain barrier (BBB) and the difficulty in directly linking peripheral markers with brain processes [15]. Nevertheless, it is generally stated that the BBB is disrupted, which will increase permeability, with aging and in AD. Moreover, BBB disruption worsens as cognitive impairment increases, which means the relationships between metabolite concentrations in blood and the brain are strengthened [111]. However, there needs to be a somewhat better specification on what is meant by BBB permeability and conclusions on altered BBB transport [112]. Below we describe the results that have been reported in the metabolomics studies and summarize them in Table 1. Maffioli et al. [103] explored the metabolome of healthy (n = 20) and AD-affected (n = 23) individuals by performing an untargeted metabolomics analysis on hippocampal samples. They detected 126 metabolites in total; 13 and 11 were up- and down-regulated, respectively, when comparing HC with AD samples. Enrichment analysis revealed that the most significantly upregulated pathways in AD samples were Arg/Pro metabolism and the pentose phosphate pathway. In contrast, the most significantly downregulated ones in AD samples were Ala/Asp/Glu metabolism, pyruvate metabolism, glycolysis/gluconeogenesis, pyrimidine metabolism, and aminoacyl-tRNA biosynthesis. In addition, gender-specific hallmarks of AD were explored. They found women with AD display a decrease in the D-serine/total serine ratio compared with men with AD. To investigate the association between fatty acid metabolism and AD, Snowden et al. [82] conducted an untargeted metabolomics study. The samples were brain tissue from 43 individuals (14 AD, 14 healthy controls (HC), and 15 asymptomatic AD), ranging from 57 to 95 years old. They found that lower tissue levels of linoleic acid, linolenic acid, eicosapentaenoic acid, oleic acid, and arachidonic acid were related to worse cognitive performance, whereas higher brain DHA levels were associated with poorer cognitive performance. Three potential biomarkers (ornithine, uracil, lysine) were identified by CE-TOF-MS on plasma samples from 40 HC, 26 MCI, and 40 AD patients [104]. For ornithine, there were significant differences between the HC and AD groups and between the MCI and AD groups. For uracil and lysine, there were significant differences between the HC and AD groups. They also measured mRNA expression levels of the metabolic enzymes in ornithine pathways, spermine synthase (SMS), nitric oxide synthase2 (NOS2), and ornithine transcarbamylase (OTC) mRNA levels were significantly different among the three groups. Gonzalez-Dominguez et al. [68] utilized CE-TOF-MS to discover the early diagnostic biomarkers of Alzheimer’s disease. The serum samples were obtained from different stages of the disease (42 AD, 14 MCI, 37 HC). They found that with the progression of the disease, the levels of choline, creatinine, asymmetric dimethyl-arginine, homocysteine-cysteine disulfide, phenylalanyl-phenylalanine, and different medium-chain acylcarnitines were observed to increase significantly, while asparagine, methionine, histidine, carnitine, acetyl-spermidine, and C5-carnitine levels were reduced. Those metabolites are related to oxidative stress and defects in energy metabolism. Shao et al. [96] used RP-UPLC-MS based untargeted metabolomics to measure the concentration of plasma metabolites among AD (n = 44) and cognitively normal control (n = 94) groups. Then, another cohort (43 HC, 31 neurological disease controls, 30 AD) was used to validate the result. They identified five metabolites that were able to distinguish AD patients from the HC group, which are allocholic acid, cholic acid, chenodeoxycholic acid, indolelactic acid, and tryptophan. This finding suggested that altered bile acid profiles in AD and MCI might indicate an early risk for AD development. Wang et al. [71] applied UPLC-MS and GC-MS to analyze plasma samples from HC, MCI, and AD patients. They found a biomarker panel consisting of six metabolites (glutamine, glutamic acid, arachidonic acid, N,N-dimethylglycine, thymine, and cytidine) that can discriminate AD patients from control. Another panel of five metabolites (arachidonic acid, N,N-dimethylglycine, 2-aminoadipic acid, thymine, and 5,8-tetradecadienoic acid) was able to differentiate MCI patients from control subjects. Peña-Bautista et al. [105] performed an untargeted lipidomics analysis on plasma samples from 20 healthy participants, 31 MCI-AD, and 11 preclinical AD. Statistically significant differences in the levels of Cer, lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), and monoglyceride (MG) were observed between the preclinical AD and healthy groups. Statistically significant differences were also observed in the levels of diglycerol (DG), MG, and phosphatidylethanolamines (PE) between healthy groups and MCI-AD. In addition, LPE (18:1) showed significant differences between healthy participants and early AD (MCI and preclinical). To determine whether the lipidome in AD has racial and ethnic disparities, Khan et al. [102] conducted a targeted lipidomics analysis of plasma samples from 54 HC and 59 AD from African American/Black (n = 56) and non-Hispanic White (n = 57) backgrounds. Five lipids (PS (18:0/18:0), PS (18:0/20:0), PC (16:0/22:6), PC (18:0/22:6), and PS (18:1/22:6)) were altered between the AD and HC sample groups. As for racial analysis, PS (20:0/20:1) was found reduced in AD in samples from non-Hispanic White but not altered in African American/Black samples. Chouraki et al. [79] conducted a longitudinal assessment for 2067 participants with an average period of 15.6 ± 5.2 years to identify the novel biomarkers association with AD. Among 2067 participants, 93 developed dementia, including 68 with AD. Plasma samples were collected every 4 to 8 years. Four candidate plasma biomarkers were found for dementia through the metabolomics technique. Anthranilic acid, glutamic acid, taurine, and hypoxanthine levels were found to be associated with the risk of dementia. Van der Lee [87] studied 299 metabolites in two discovery cohorts (n = 55,658) to find the associations with cognition. A total of 15 metabolites were discovered and replicated associated with cognition including subfractions of high-density lipoprotein (HDL), docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. Moreover, fish (oil) intake was found to be strongly associated with DHA blood concentrations (p = 9.9 × 10−53). Physical activity was found to be associated with increased (p < 0.05) levels of metabolites that were associated with higher cognitive function (medium and large HDL subfractions) and decreased levels of metabolites that were associated with lower cognitive function (glycoprotein acetyls, ornithine, and glutamine). Smokers were found to have decreased concentrations of all HDL subfractions associated with higher cognitive function and increased concentrations of metabolites associated with decreased cognitive function. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) began in 2004, and unites researchers who are investigating longitudinal data in AD. Here, clinical, neuroimaging, cognitive, biofluid biomarkers, and genetic data were collected to define the progression of AD [113]. Horgusluoglu et al. [101] systematically interrogated metabolomic, genetic, transcriptomic, proteomic, and clinical data from ADNI and found that short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical severity. Arnold et al. [114] used metabolomics data from 1571 participants of ADNI to investigate AD group-specific metabolic alterations. Fifteen metabolites were found to be associated with the female sex and APOE ε4 genotype: For CSF Aβ1–42, threonine showed a sex-specific effect with a greater effect size in males, while valine showed a larger effect in females. For CSF p-tau, acylcarnitines C5-DC (C6-OH), C8, C10, C2, and histidine showed stronger associations in females, whereas the related ether-containing PCs, PC ae C36:1, PC ae C36:2, asparagine, glycine, and one hydroxy-SM (SM (OH) C16:1) yielded stronger associations in males. MahmoudianDehkordi et al. [90] measured 15 primary and secondary bile acids in serum levels of 1464 subjects (37 CN older adults, 284 early mild cognitive impaired patients, 505 late mild cognitive impaired patients, and 305 AD). Primary bile acid cholic acid was found to be significantly lower serum levels in AD patients compared to CN subjects, whereas higher levels of secondary bile acids deoxycholic acid (DCA) and its conjugated forms (glycodeoxycholic acid (GDCA), glycolithocholic acid (GLCA), and taurolithocholic acid (TLCA)) were significantly associated with worse cognitive function. Taken together, metabolomics allows the detection of metabolic alterations by monitoring multiple metabolites simultaneously. Multiple human studies have used metabolomics to distinguish age and sex-specific changes in plasma, brain, or CSF samples between CN subjects, MCI, and AD patients as predictors of AD progression which were then tested in animal models of AD to identify possible underlying causal mechanisms. More insights have been obtained on changes in metabolic pathways in AD, however, the lack of substantial time course data in humans is hindering understanding the sequence of disease stage-dependent changes in metabolic pathways. In other words, if we do not follow the change of metabolites and lipids over time, we cannot understand what changes along with disease progression and what may be important for developing adequate (stage-dependent) treatment of AD. This knowledge gap in biomarkers indicates that the onset and early stage of AD cannot be bridged by human studies since extensively obtaining human samples is by far more costly and time-consuming than obtaining samples from animals, it is also impossible to obtain human brain samples in longitudinal studies from the human aging population. Therefore, there is a need for alternative approaches to obtain the relation between the changes in biomarkers and AD stages, which can be achieved through animal model studies [115]. The most commonly used experimental animal models are transgenic mice that express human genes associated with familial AD (FAD) that result in the formation of amyloid plaques (by expression of human APP alone or in combination with human PSEN1), whereas human familial AD accounts for only 5% of cases [115,116,117,118,119]. Though not ideal, animal models provide an opportunity to study the early pathological disease mechanisms that can help to unravel processes associated with the development of AD. Additionally, animal models allow the investigation of (brain) tissues and fluids, and longitudinal studies can be performed to track disease progression, which cannot be accomplished in humans. Currently, along with the popular animal models of FAD including APP (Tg2576), APP/PS1, or 3xTg AD mice, the development of humanized mouse models expressing genetic risk factors, such as APOE ε4 allele, allows researchers to study mechanisms of late-onset sporadic AD [120,121,122]. In the present review, we specifically summarized AD mouse model research as only mouse research included age information in young mice. As summarized in Table 2, we found 42 articles [123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164] that carried out metabolomics analyses on samples of the brain, plasma, feces, spleen, and pancreas in mouse models of AD. Among them, nine articles studied plasma samples. A total of 21 articles only studied brain samples, and 9 articles conducted metabolomics experiments on plasma and brain samples. One study profiled spleen and brain samples, one study used serum and pancreas samples, one study used pancreas and serum samples, and one article used serum, brain, and feces samples on AD research. The results are described below. Speers et al. [157] conducted metabolomics analysis of cortical tissue in 8-month-old male and female 5xFAD mice and their aged-match wild-type littermates. Sex differences were observed: 12 metabolites (betaine, lysine, pyridoxamine, urate, NAD, erythritol, spermine, N-acetylmannosamine, glycerol 2-phosphate, lauroyl-L-carnitine, sodium taurocholate, nicotinamide hypoxanthine dinucleotide) were significantly altered by the transgene in the female 5xFAD mice, whereas only five (homocysteine, betaine, N-Acetyl-mannosamine, S-Adenosyl-homocysteine, Adenosine 3′,5′-cyclic monophosphate) significantly altered metabolites in male 5xFAD. Zhao et al. [159] applied targeted metabolomics on the hippocampi of 2- and 6-month-old triple transgenic AD male mice and age-sex-matched wild-type mice (WT). A total of 70 differential metabolites were identified, among them 24 metabolites were found changed in 2-month-old AD mice compared to WT, 60 metabolites were found changed in 6-month-old AD mice compared to WT. Fourteen metabolites were found in common, which are 7-methylguanosine, adenosine, adenosine 3′,5′-cyclic monophosphate (cAMP), cis-4-Hydroxy-d-proline, deoxycytidine, cytidine, deoxyadenosine monophosphate (dAMP), ethanolamine, glycerophosphocholine (GPC), L-2-aminoadipic acid, L-methionine, N-acetyl-D-glucosamine (GlcNAc), N-acetyl-L-tyrosine, and riboflavin (VB2). These results highlight the involvement of abnormal purine, pyrimidine, arginine, and proline metabolism, along with glycerophospholipid metabolism in the early pathology of AD. Dejakaisaya et al. [156] identified alterations in cerebral metabolites and metabolic pathways in cortex, hippocampus, and serum samples from the Tg2576 AD mice model. Eleven metabolites showed significant differences in the cortex, including hydroxyphenyllactate (linked to oxidative stress) and phosphatidylserine (linked to lipid metabolism). For the network analysis, the authors used weighted correlation network analysis (WGCNA) to investigate the metabolite-group corrections. They identified five pathways, including alanine, aspartate, and glutamate metabolism, and mitochondria electron transport chain, that were significantly correlated with AD genotype. Kim et al. [150] used untargeted metabolomics to investigate alterations in metabolite profiles of hippocampal tissues in 6-, 8- and 12-month-old wild-type and 5xfamiliar AD (5xFAD) mice. They found nicotinamide and adenosine monophosphate levels significantly decreased while lysophosphatidylcholine (LysoPC) (16:0), LysoPC (18:0), and lysophosphatidylethanolamine (LysoPE) (16:0) levels significantly increased in the hippocampi from 5xFAD mice at 8 months or 12 months of age when compared to age-matched wild type mice. In addition, the authors assumed that the primary neurons from 5xFAD reflect the hippocampal pathophysiological characteristics of 5xFAD. They treated the primary neurons with nicotinamide and found that treatment with nicotinamide rescued synaptic deficits in hippocampal primary neurons derived from 5xFAD mice. This finding indicated that decreased hippocampal nicotinamide levels could be linked with AD pathogenesis. In 2020, Hunsberger et al. [149] collected prefrontal cortex, hippocampus, and spleen samples in 6-, 12- and 24-month-old APP/PS1 mice and age-matched wild-type mice. They conducted untargeted metabolomics analysis to investigate metabolomic alterations in naturally aged and APP/PS1 (AD) mice. Pathway analysis of changed metabolites revealed that across age, histidine metabolism was affected in all tissue samples, whereas amino acid metabolism and energy metabolism were altered in the prefrontal cortex, and AD significantly altered protein synthesis and oxidative stress in the hippocampus. Moreover, they found age-related metabolic changes occur earlier in the spleen compared to the CNS. Zheng et al. [141] explored metabolic changes in six different brain regions between transgenic APP/PS1 mice and wild-type mice at 1, 5, and 10 months of age by using an NMR-based metabolomics approach to explore the metabolic mechanism that underlies the progression of amyloid pathology. They found the concentrations of glycerolphosphorylcholine, phosphocholine, and myo-inositol increased significantly in the hypothalamus of APP/PS1 mice when compared to WT mice, which indicated that the hypothalamus may be the main hypermetabolic region in the brain. In conclusion, considering that biochemical pathways are largely conserved between humans and rodents [165], animal research is considered a valuable addition to human studies as human samples are costly and—especially in the case of brain samples—not available for longitudinal study. Different animal models of AD closely mimic the changes in metabolic networks associated with disease progression in humans. MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/) (accessed on 1 October 2022) is a website that provides software to analyze metabolomics data. It processes raw MS spectra, normalizes comprehensive data, and provides statistical analysis, functional analysis, meta-analysis, and metabolic pathway analysis. Metabolic pathway analysis identifies which metabolic pathways have compounds (from the user’s input list) that are over-represented and returns pathway impact. Pathway impact is calculated as the sum of the importance measures of matched metabolites normalized by the sum of the importance measures of all metabolites in each pathway [166]. Using this software, we analyzed the metabolic pathways to identify altered metabolites in the brain, plasma, and CSF in the literature studies described above. The metabolic pathways were represented as circles according to their scores from enrichment (y-axis) and topology analyses (pathway impact, x-axis). Darker circle colors indicated more significant changes in metabolites in the corresponding pathway. The size of the circle corresponds to the pathway impact score and was correlated with the centrality of the involved metabolites. After inputting all the altered metabolites from 43 human studies among different AD stages (MCI and AD) in brain, plasma, and CSF samples, 13 main metabolic pathways had a p-value less than 0.05 and impact value greater than 0.5 (Figure 1), including phenylalanine, tyrosine and tryptophan biosynthesis, taurine and hypotaurine metabolism, alanine, aspartate and glutamate metabolism, cysteine and methionine metabolism, arginine and proline metabolism, phenylalanine metabolism, tryptophan metabolism, arginine biosynthesis, beta-alanine metabolism, histidine metabolism, tyrosine metabolism, glycine, serine and threonine metabolism, and D-glutamine and D-glutamate metabolism. Details of pathway information are presented in Supplementary Table S1. Furthermore, we investigated the altered metabolic pathways in common among different sample types in MCI and AD patients. After inputting all the altered metabolites from human MCI plasma samples, 12 metabolic pathways had a p-value less than 0.05 and impact values greater than 0. Using all the altered metabolites from the human AD plasma sample, 16 metabolic pathways had a p-value less than 0.05 and an impact value greater than 0. As shown in Figure 2A, a total of eight pathways were shared in the comparison between MCI VS. CN and AD VS. CN in plasma samples, which indicated that the metabolic mechanisms of AD and MCI share similar pathological alterations. Similarly, all the altered metabolites from CSF samples were analyzed among MCI and AD groups. As shown in Figure 2B, a total of five pathways were shared in the comparison between MCI VS. CN and AD VS. CN. It is noted that all the MCI pathways overlapped with AD pathways in CSF samples. We next used the combined (MCI + AD) altered metabolites found in plasma and CSF samples to understand important pathways in common between these two sample matrices. As shown in Figure 2C, a total of 13 pathways were shared between the plasma and CSF samples. Details of pathway information are presented in Supplementary Table S2. For all the altered metabolites from the 35 mouse studies among different ages (2 months–24 months) in brain and plasma samples, when comparing to the control group, 13 main metabolic pathways were found with a p-value less than 0.05 and an impact value greater than 0.5 (Figure 3), including phenylalanine, tyrosine and tryptophan biosynthesis, linoleic acid metabolism, synthesis and degradation of ketone bodies, alanine, aspartate and glutamate metabolism, glycine, serine and threonine metabolism, arachidonic acid metabolism, phenylalanine metabolism, beta-alanine metabolism, arginine biosynthesis, glycerophospholipid metabolism, histidine metabolism, arginine and proline metabolism, and glyoxylate and dicarboxylate metabolism. Details of pathway information are presented in Supplementary Table S3. Literature studies were combined to find disturbed pathways at different ages of AD mouse models, using all the altered metabolites at different ages in plasma and brain samples to perform pathway analysis. We included the pathways that meet a p-value less than 0.05 and an impact value greater than 0. The results showed that 31 pathways were significantly altered in mouse brain and plasma samples, the pathway impact values are shown as a heatmap (Figure 4A). Furthermore, we investigated the altered metabolic pathways in common including all ages in plasma and brain samples. After including all the altered metabolites from mouse plasma samples, 18 metabolic pathways were found with a p-value less than 0.05 and an impact value greater than 0. Using all the altered metabolites from mouse brain samples, 18 metabolic pathways had a p-value less than 0.05 and an impact value greater than 0. As shown in Figure 4B, a total of 10 pathways were overlapping between the brain and plasma, indicating that the metabolic mechanisms seen in mouse plasma and brain share similar pathological alterations. Details of pathway information are presented in Supplementary Table S4. The previous Section 3.1 and Section 3.3 highlighted that there was a total of 13 significant (p-value < 0.05 and impact value > 0.5) metabolic pathways altered in all matrices measured across all studies, including human and mouse research. Of these, eight altered metabolic pathways were found to be in common between AD mouse models and human AD subjects over all matrices: (i) alanine, aspartate, and glutamate metabolism, (ii) arginine and proline metabolism, (iii) arginine biosynthesis, (iv) β-alanine metabolism, (v) glycine, serine, and threonine metabolism, (vi) phenylalanine metabolism, vii) histidine metabolism, and (viii) phenylalanine, tyrosine, and tryptophan biosynthesis. Section 3.2 highlighted metabolic pathways in human plasma and CSF samples. Section 3.4 highlighted metabolic pathways in mouse brain and plasma samples. The matrix commonly investigated in both human and mouse research is plasma. There were 17 significant (p-value < 0.05 and impact value > 0.5) metabolic pathways in human plasma samples, whereas there were 18 significant (p-value < 0.05 and impact value > 0.5) metabolic pathways in mouse plasma samples. Of all of these, there were 12 metabolic pathways that were altered in both AD mouse models and human AD subjects in plasma: (i) alanine, aspartate, and glutamate metabolism, (ii) arginine and proline metabolism, (iii) arginine biosynthesis, (iv) butanoate metabolism, (v) citrate cycle (TCA cycle), (vi) glutathione metabolism, (vii) glycerophospholipid metabolism, (viii) glycine, serine, and threonine metabolism, (ix) glyoxylate and dicarboxylate metabolism, (x) linoleic acid metabolism, (xi) phenylalanine metabolism, and (xii) phenylalanine, tyrosine, and tryptophan biosynthesis. The following section is a detailed description of these important metabolic pathways that emerged as significantly altered after consolidating the analysis results. L-arginine is a semi-essential amino acid that can be metabolized to form a number of bioactive molecules [167] (Figure 5). It is synthesized from proline or glutamate, with the ultimate synthetic step catalyzed by argininosuccinate lyase [168]. L-arginine can be metabolized by arginases, nitric oxide synthases (NOS), and possibly also by arginine decarboxylase (ADC), resulting ultimately in the production of agmatine, ornithine, nitric oxide (NO), or urea [168]. The expression of several of these enzymes can be regulated at transcriptional and translational levels by changes in the concentration of L-arginine itself [169]. L-ornithine is the arginase-mediated metabolite of L-arginine, with urea as the by-product. L-ornithine can be further metabolized to form putrescine, spermidine, and spermine polyamine, which are essential for normal cell growth and functioning, or via a separate pathway to form glutamine and cell-signaling molecule, GABA [167]. Previous research has reported decreased glutamate and GABA levels in AD brains and increased glutamine synthase (GS) levels in the lumbar cerebrospinal fluid of AD patients [170,171]. In peripheral organs and also CNS, arginine can also be metabolized by ADC to produce agmatine, a neurotransmitter that plays an important role in the learning and memory process [172]. NO is a gaseous signaling molecule produced by NOS. NO, derived from neuronal NOS (nNOS), plays an important role in synaptic plasticity and learning, and memory [173,174,175]. Moreover, L-arginine and NO affect the cardiovascular system as endogenous antiatherogenic molecules that protect the endothelium, modulate vasodilatation, and interact with the vascular wall and circulating blood cells [176,177,178,179,180]. Glutamate is the principal excitatory neurotransmitter of the brain [181]. Most neurons and glia are likely to be influenced by glutamate since they have receptors for glutamate. Glutamate is considered the main neurotransmitter of neocortical and hippocampal pyramidal neurons and is involved in higher mental functions such as cognition and memory [182]. Disturbance of excitatory glutamatergic neurotransmission is believed to be associated with many neurological disorders, including Alzheimer’s disease (AD) [182], ischemic brain damage [183], and motor neuron disease [184]. Glutamate receptors can be divided into two classes: ionotropic (N-methyl-D-aspartate, NMDA) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)/kainite subtypes and metabotropic [185]. The role of glutamate and glutamate receptors in learning and memory is widely recognized. For instance, NMDA antagonists impair learning and memory while NMDA agonists and facilitators improve memory [182]; likewise, AMPAKines (positive modulators of receptor function) facilitate learning and memory [186]. Circumstantial evidence of the involvement of glutamatergic pathways derives from the well-known role of structures such as the hippocampus in learning and memory [187]. More specifically, lesions of certain glutamatergic pathways impair learning and memory [188]. Moreover, glutamate and glutamate receptors are involved in mechanisms of synaptic plasticity, which are considered to underlie learning and memory [189,190,191]. Purines and pyrimidines are components of many key molecules in living organisms. The primary purines adenine and guanosine and the pyrimidines cytosine, thymidine, and uracyl are the core of DNA, RNA, nucleosides, and nucleotides involved in energy transfer (ATP, GTP) [192,193]. Several studies indirectly suggested that purine metabolism has altered in AD. Energy metabolism, which depends on mitochondrial function and ATP production, is markedly altered in AD [194,195]. In addition, oxidative damage to DNA and RNA, as revealed by the increase in 8-hydroxyguanosine, is found in the brain samples of AD [196,197,198,199]. Direct alterations of purine metabolism in AD have been detected by metabolomics in postmortem ventricular CSF [200] and in the spinal cord CSF of living individuals [201,202,203]. Only a limited number of metabolomics studies have been carried out in AD brains [203]. Taurine is the second most abundant endogenous amino acid in the central nervous system (CNS) and has multiple roles in our body: thermoregulation [204], stabilization in regulating protein folding [205], anti-inflammatory effects [206], antioxidation [207], osmoregulation [208], and calcium homeostasis [209]. Recently, taurine has shown therapeutic effects as a cognitive enhancer in animal models of non-AD neurological disorders [210,211,212,213]. Taurine protected mice from the memory disruption induced by alcohol, pentobarbital, sodium nitrite, and cycloheximide but had no obvious effect on other behaviors including motor coordination, exploratory activity, and locomotor activity [210]. Intravenously injected taurine significantly improves post-injury functional impairments of traumatic brain injury in rats [211]. The intracerebroventricular (ICV) administration of taurine protects mice from learning impairment induced by hypoxia. Neither beta-alanine nor saccharose was able to mimic the effects of taurine [212]. In streptozotocin-induced sporadic dementia rat models, cognitive impairment and deterioration of neurobehavioral activities are ameliorated by taurine [213]. Taurine also has multiple disease-modifying roles to cease or prevent AD neuropathology. During the development of AD, amyloid-β (Aβ) progressively misfolded into toxic aggregates, which are strongly associated with neuronal loss, synaptic damage, and brain atrophy. An electron microscopy study indicates that taurine slightly decreases β-amyloid peptide aggregation in the brain at a millimolar concentration [214]. Taurine also has anti-inflammatory and antioxidant properties; it can provide protection for neuronal cells and mitochondria from the neurotoxicity of Aβ. By activating GABA and glycine receptors, taurine inhibits excitotoxicity caused by Aβ-induced glutamatergic transmission activation [215]. As acetylcholine (ACh) plays a vital role in cognitive processes, the cholinergic system is considered an important factor in AD [216]. The brain regions most affected by a loss of elements of the acetylcholine system include the hippocampus, cortex, and entorhinal [217]. Cholinesterase inhibitors are one of the few drug therapies available in the clinic for the treatment of AD, and it was inspired by the fact that cholinesterase inhibitors increase the availability of acetylcholine at brain synapses [218]. The validation of the cholinergic system was seen as an important therapeutic target in the disease. Fatty acids are the basic building blocks of more complex lipids and can be classified by the number of double bonds as saturated fatty acids (SFAs) and unsaturated fatty acids. SFAs do not include any double bonds, whereas unsaturated fatty acids contain at least one (monounsaturated fatty acids, MUFAs) or two or more (polyunsaturated fatty acids, PUFAs) double bonds [219,220]. Altered unsaturated fatty acids have been associated with AD in multiple studies. The brain is especially enriched with two PUFAs: docosahexaenoic acid (DHA) and arachidonic acid (AA). DHA, as one of omega-3 PUFAs, is the predominant structural fatty acid in the mammalian brain and plays an essential role in brain functioning, especially in cognitive function; DHA levels were lower in AD brains [221,222] or plasma [69], and increased intake of DHA from fish or marine oils may lower AD risk [223,224,225]. AA of the ω-6 fatty acid family appears to play critical mediator roles in amyloid (Aβ)-induced pathogenesis, leading to learning, memory, and behavioral impairments in AD [226]. The levels of free AA have been found to increase in AD patient brain samples [82], whereas the levels of AA in phospholipids are reduced in the hippocampus of AD subjects [227]. Glycerolipids can be categorized into triacylglycerols (TAG, also known as triglycerides, TG), monoacylglycerol (MAG), and diacylglycerol (DAG) based on the number of acyl groups in the structure. TAG, the most predominant glycerolipids, are esters composed of a glycerol backbone and three fatty acids. TAG levels are found not to be changed in the serum of AD patients when compared to control subjects. [228]. However, MAG and DAG are elevated in both the prefrontal cortex and plasma of AD and MCI subjects in comparison to controls [229,230]. Moreover, MAG and DAG are elevated in the grey matter of MCI and AD patients, suggesting that these biochemical changes may play a role in the development of MCI and in the transition from MCI to AD [231]. Glycerophospholipids (GPs), also referred to as phospholipids (PLs), are typically amphipathic and make up the characteristic lipid bilayer structure of biological membranes. Moreover, GPs are the major type of lipids that make up cell membranes and account for 50–60% of the total membrane mass along with cholesterol and glycolipids [232]. GPs include phosphatidylethanolamine (PE), phosphatidic acid (PA), phosphatidylserine (PS), phosphatidylglycerol (PG), phosphatiylcholine (PC), phosphatidylinositol (PI), sphingomyelin (SM), and cardiolipin (CL) [233]. Studies on GP composition indicate that levels of PC, PE, and PI are significantly decreased in neural membranes from different regions of AD patients compared to age-matched control brains [234,235,236,237,238,239]. Phosphatidylethanolamine (PE) is converted to lysophosphatidylethanolamine (lyso-PE) by phospholipase A2 (PLA2), an important inflammatory mediator that is dysregulated in AD. PLA2 level has been found to be elevated in the human cerebral cortex [240] or decreased in the human parietal and frontal cortex [241]. Moreover, PLA2 influences the processing and secretion of amyloid precursor protein, which gives rise to the β-amyloid peptide, the major component of the amyloid plaque in AD [241]. Moreover, PLA2 has been found to play an important role in memory retrieval [242]. Phosphatidylserine (PS) is the major acidic phospholipid class that accounts for 13–15% of the phospholipids in the human cerebral cortex [243]. PS is known as a “brain nutrient”, as it can not only nourish the brain, but also enhance brain functions such as improving cognition, memory, and reaction force [244]. In six double-blind trials, PS has been found effective for AD. At daily doses of 200–300 mg for up to six months, PS consistently improved clinical global impression and activities of daily living [245]. In milder cases, PS improved orientation, concentration, learning, and memory for names, locations, and recent events. In the largest trial, involving 425 elderly patients (aged between 65 and 93 years) with moderate to severe cognitive decline, PS significantly improved memory, learning motivation, and socialization, suggesting that it has a vital impact on the quality of life of such elderly patients. Phosphatidylcholine (PC) is an essential component of cell membranes and makes up approximately 95% of the total choline compound pool in most tissues [246,247]. Its function is defined primarily by chain length since chain length differences can affect cell membrane fluidity [248]. Three PCs (PC 16:0/20:5, PC 16:0/22:6, and PC 18:0/22:6) have been found significantly diminished in AD patients [249]. Lysophosphatidic acids (LPAs) are phospholipids derivatives that can act as signaling molecules [250]. Ahmad et al. [95] investigated the association between LPAs and CSF biomarkers of AD, Aβ-42, p-tau, and total tau levels overall and with MCI to AD progression. Five LPAs (LPA C16:0, LPA C16:1, LPA C22:4, LPA C22:6, and isomer-LPA C 22:5) correlated significantly and positively with CSF biomarkers of AD, Aβ-42, p-tau, and total tau. Additionally, LPA C16:0 and LPA C16:1 showed associations with MCI to AD dementia progression. Sphingolipids, a class of membrane biomolecules, include sphingosine 1-phosphates (S1P), Cers, SMs, and glycosphingolipids, which are vital for maintaining cell integrity and signal transduction processes [251]. Cers, the basic structural units of the sphingolipid class, have been seen as key contributors to the pathology of AD as they are able to affect both Aβ generation and tau phosphorylation [252]. Filippov et al. found elevated levels of ceramides Cer16, Cer18, Cer20, and Cer24 in the brains of AD patients. Two saturated ceramides, Cer (d18:1/18:0) and Cer (d18:1/20:0) were significantly increased in the senile plaques [253]. High ceramide levels were also found in AD serum [254] and CSF samples [255]. The greatest genetic risk factor for late-onset AD is the ε4 allele of apolipoprotein E (ApoE). ApoE regulates the secretion of the potent neuroprotective signaling lipid S1P [256]. S1P is derived by phosphorylation of sphingosine, catalyzed by sphingosine kinases 1 and 2 (SphK1 and 2). SphK1 positively regulates glutamate secretion and synaptic strength in hippocampal neurons. Reduced levels of S1P have been found in AD brains compared to controls [256,257]. All these studies mentioned above suggested that sphingolipid metabolism plays a critical role in AD pathology. Despite the brain occupying only 2% of total body weight, it contains 25% of the body’s cholesterol. Due to the BBB, cholesterol metabolism in the CNS is largely separated from that in the periphery and cholesterol is de novo synthesized in the CNS [258]. Studies have found that brain cholesterol was significantly increased in AD patients than in controls [259,260]. Moreover, cholesterol showed abnormal accumulation in the senile plaques of the human brain, a hallmark neuropathological feature of AD [261]. Considering the dramatic aging of populations worldwide, it is of great importance to explore AD pathogenesis. Metabolic changes associated with AD progression occur prior to the development of clinical symptoms; metabolomics by itself or in conjunction with the additional currently available biomarkers for AD diagnosis could serve as an additional tool to increase the accuracy of diagnosis, to predict the disease progression, and to monitor the efficacy of therapeutic intervention. Metabolomic studies have demonstrated the dramatic impact of AD pathogenesis and progression on metabolites and related metabolic pathways, including energy-related metabolism, fatty acid metabolism, abnormal lipid metabolism, altered amino acids metabolism (e.g., arginine, glutamate), and some others. In the present review, we summarized the metabolomics studies that were performed in biological samples of AD subjects and AD mouse models. The results of rats were too sparse and not suitable for further analysis. The mouse research shows that 12- and 24-months, middle and old age in AD mouse models, can be equivalated to the MCI and AD late stage in humans, respectively. As obtaining human body samples is costly, limited in possible samples sites by ethics (i.e., brain), and time-consuming for the long life span of humans, the above indicates that animal research may be considered a valuable addition, as it can be designed in a longitudinal fashion and with samples from multiple sites of the body to obtain time-course information and interrelationships, to gain insights that support research on AD in humans. The disturbed pathways by AD were analyzed based on metabolite data collected from the literature. Eight disturbed metabolic pathways were found in common between AD mouse research and AD human research. These pathways are alanine, aspartate, and glutamate metabolism, arginine and proline metabolism, arginine biosynthesis, β-Alanine metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism, histidine metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis. Our analysis of the literature studies has several limitations. The coverage of metabolites varied among different studies due to the detection sensitivity differences, as analytical platforms (e.g., NMR, GC-MS, LC-MS) and analytical methods are diverse in different laboratories. In addition, it is hard to reproduce various metabolomics results because of different sample sources (brain tissue or plasma) from either deceased or living patients and diverse distribution about sex, age, and suffering from other diseases. Moreover, the methods used for obtaining samples, such as CSF and brain, varied among different studies. For example, delays between removing and freezing animal or human brain tissue can affect metabolomics analysis. Altogether, in this review, we summarized and analyzed existing metabolomics data and the relation between plasma, CSF, and brain for animals and plasma and CSF for human data. We identified missing longitudinal information, which would be difficult to be obtained from humans (high costs, long direction) while also in the human brain cannot be sampled. Longitudinal and multi-body site information, however, is important to understand the processes in AD. This is where animal research may support AD research in humans to provide new insights on disease biomarkers patterns and biological pathways, that will support AD stage diagnosis in humans but also the discovery of AD future therapeutic targets.

PMC10003385

Yuchen Zou,Qing Guo,Yidan Chang,Yongyong Zhong,Lin Cheng,Wei Wei

Effects of Maternal High-Fructose Diet on Long Non-Coding RNAs and Anxiety-like Behaviors in Offspring

24-02-2023

gestation,lactation,brain development,full-length RNA sequencing,Oxford Nanopore Technologies

Increased fructose intake is an international issue. A maternal high-fructose diet during gestation and lactation could affect nervous system development in offspring. Long non-coding RNA (lncRNA) plays an important role in brain biology. However, the mechanism whereby maternal high-fructose diets influence offspring brain development by affecting lncRNAs is still unclear. Here, we administered 13% and 40% fructose water to establish a maternal high-fructose diet model during gestation and lactation. To determine lncRNAs and their target genes, full-length RNA sequencing was performed using the Oxford Nanopore Technologies platform, and 882 lncRNAs were identified. Moreover, the 13% fructose group and the 40% fructose group had differentially expressed lncRNA genes compared with the control group. Enrichment analyses and co-expression analyses were performed to investigate the changes in biological function. Furthermore, enrichment analyses, behavioral science experiments, and molecular biology experiments all indicated that the fructose group offspring showed anxiety-like behaviors. In summary, this study provides insight into the molecular mechanisms underlying maternal high-fructose diet-induced lncRNA expression and co-expression of lncRNA and mRNA.

Effects of Maternal High-Fructose Diet on Long Non-Coding RNAs and Anxiety-like Behaviors in Offspring Increased fructose intake is an international issue. A maternal high-fructose diet during gestation and lactation could affect nervous system development in offspring. Long non-coding RNA (lncRNA) plays an important role in brain biology. However, the mechanism whereby maternal high-fructose diets influence offspring brain development by affecting lncRNAs is still unclear. Here, we administered 13% and 40% fructose water to establish a maternal high-fructose diet model during gestation and lactation. To determine lncRNAs and their target genes, full-length RNA sequencing was performed using the Oxford Nanopore Technologies platform, and 882 lncRNAs were identified. Moreover, the 13% fructose group and the 40% fructose group had differentially expressed lncRNA genes compared with the control group. Enrichment analyses and co-expression analyses were performed to investigate the changes in biological function. Furthermore, enrichment analyses, behavioral science experiments, and molecular biology experiments all indicated that the fructose group offspring showed anxiety-like behaviors. In summary, this study provides insight into the molecular mechanisms underlying maternal high-fructose diet-induced lncRNA expression and co-expression of lncRNA and mRNA. In recent years, people have shown increasing preference for sweet foods in their diet, and sugar-sweetened beverage (SSB) demand is increasing [1]. A sweet monosaccharide, fructose, is the major form of high-fructose corn syrup (HFCS) [2], which is widely added to foods and SSBs [3,4]. A common phenomenon suggests that mothers exposed to such a diet environment are also at risk of excessive fructose intake. In America, pregnant women consume more than the recommended intake of SSBs, and fructose intake is out of balance [5,6]. A high-fructose diet can affect many biological processes and functions, including the nervous system [7,8]. Studies have shown that maternal high-fructose diet during gestation or lactation can cause insulin resistance and inflammation in the child’s brain [9,10], although the mechanisms have not been explored in depth. In our previous studies, maternal high-fructose diet could influence many biological processes related to brain development by changing transcription expression [11]. Anxiety-like behaviors have become a research hotspot in recent years. A strong link was identified between metabolic syndrome and mood disorders caused by high-fructose diet [12]. The repeated intake of high levels of fructose during adolescence has been proven to lead to stress response disorders and increase anxiety-like behaviors [13,14]. However, the effect of maternal high-fructose diet during gestation and lactation on offspring anxiety-like behaviors is still unclear. Long non-coding RNA (lncRNA) has a length of 200 nt to 100,000 nt and does not encode proteins [15]. lncRNA can regulate gene expression by recruiting regulatory factors, which essentially change the spatial structure of adjacent mRNA genes [16]. lncRNAs can also affect the expression of distal genes by affecting trans-acting factors [17,18]. Consequently, lncRNA expression is correlated with the expression of their potential target genes [19,20], as shown by the lncRNA–target gene co-expression network. lncRNA expression is tissue specific and is especially high in brain tissues [21]. Some studies have shown that lncRNAs participate in nervous system development and function [22,23]. By affecting neurotransmitter transmission efficiency, brain derived neurotrophic factor (BDNF) content, and synaptic conduction [24,25], lncRNAs may regulate emotions [26]. However, lncRNAs are more difficult to detect and annotate, because the sequence conservation of lncRNA is lower than that of mRNA [27]. In nanopore sequencing, single-molecule electrical signals are sequenced in real time, making the accurate detection of lncRNA structural changes and expression changes possible [28,29]. In summary, we hypothesized that maternal high-fructose diet during gestation and lactation may change the expression of lncRNAs and lncRNA target gene co-expression and that this different expression may affect anxiety-like behaviors in offspring. To explore this, dams were exposed to 13% and 40% fructose water during gestation and lactation, and the hippocampus of their offspring was analyzed using Oxford Nanopore Technologies (ONT) full-length RNA sequencing. The co-expression networks of lncRNAs and mRNAs with large gene numbers were enriched to explore the relationship between lncRNAs and anxiety-like behaviors. Our findings reveal the key roles of lncRNAs and the interactions between protein-coding genes and lncRNAs in the effect of maternal high-fructose diet during gestation and lactation on offspring. The gestation weight of dams in the fructose groups was significantly greater than that of dams in the control (Con) group (p < 0.01, p < 0.05) [11]. The weight of offspring in the 13% fructose (F13%) group was significantly greater than that of offspring in the Con group on postnatal day (PND) 30 and PND40 (p < 0.05); the weight of animals in the F13% and 40% fructose (F40%) groups were significantly greater than that of animals in the Con group on PND50 and PND60 (p < 0.01, p < 0.05) [11]. The 12 h FBG, 12 h FinS, and homeostasis model assessment results of PND21 and PND60 offspring in the fructose groups were all higher than those of age-matched offspring in the Con group (p < 0.01) [11]. Frequency in central areas, duration of anxious state, duration of active state, number of standing, and trajectory in the open-field test were used to evaluate offspring anxiety-like behaviors. The frequency in central areas of animals in the fructose groups was significantly lower than that of offspring in the Con group (p < 0.05) (Figure 1A). The active state duration and anxious state duration of animals in the fructose groups were significantly longer than those of offspring in the F13% group (p < 0.01) (Figure 1B,C). Regarding the number of standing instances, the fructose groups displayed significantly higher values than the Con group (p < 0.01), and the F40% group also displayed significantly higher values than the F13% group (p < 0.01) (Figure 1D). Rats were more likely to move along the walls the higher the fructose concentration was (Figure 1E). Using the inverse method, the coding potential calculator (CPC), the coding–non-coding index (CNCI), the coding potential assessment tool (CPAT), and Pfam were employed to predict the following lncRNAs: 1010 lncRNAs, 1232 lncRNAs, 882 lncRNAs, and 1100 lncRNAs, respectively. A total of 882 lncRNAs overlapped and were used for further analysis (Figure 2A). Of these lncRNAs, 57.9% were lincRNA; a total of 21.1% were sense lncRNAs; a total of 16.3% were antisense lncRNAs; and a total of 4.6% were intronic lncRNAs (Figure 2B). Regarding gene differential expression analysis, there were 181 (up-regulated, 105; down-regulated, 76) differently expressed mRNA genes in the control group versus the 13% fructose group (Con/F13%) group, 297 (up-regulated, 215; down-regulated, 64) in the control group versus the 40% fructose group (Con/F40%) group, and 374 (up-regulated, 204; down-regulated, 170) in the 13% fructose group versus the 40% fructose group (F13%/F40%) group. A total of 11 (up-regulated, 3; down-regulated, 8) differentially expressed lncRNA (DElncRNA) genes in the Con/F13% group, 19 (up-regulated, 9; down-regulated, 10) in the Con/F40% group, and 9 (up-regulated, 7; down-regulated, 2) in the F13/F40% group were found. These expression levels are shown below in a volcano map (Figure 2C). We also compared the genomic features of lncRNAs and mRNAs in the three groups. There were 3460.5 bp of lncRNAs and 12,599 bp of mRNA in the Con group; a total of 3467 bp of lncRNAs and 12,599 bp of mRNAs in the F13% group; and a total of 3475.5 bp of lncRNAs and 14,362 bp of mRNAs in the F40% group. Further, lncRNAs were shorter than mRNAs in every group (Figure 3A). It was also apparent that lncRNAs had smaller open reading frames (ORFs) than mRNAs, with an ORF length of 201 bp versus 981 bp for mRNAs in the Con group, 981 bp for F13%, and 1053 bp for F40% (Figure 3C). The exons of lncRNAs were shorter than those of mRNAs. Further, the average exon length of lncRNAs was 639.5 bp, and that of mRNAs was 1633 bp in the Con group; the average exon lengths were 639 bp for lncRNAs and 1633 bp for mRNAs in the F13% group; and they were 639 bp for lncRNAs and 1741 bp for mRNAs in the F40% group (Figure 3B). The introns of lncRNAs were shorter than those of mRNAs. Further, the average intron length of lncRNAs was 2690 bp, and it was 10,494 bp for mRNAs in the Con group; the average intron lengths were 2697 bp for lncRNAs and 10,494 bp for mRNAs in the F13% group; and they were 2698.5 bp for lncRNAs and 12,224 bp for mRNAs in the F40% group (Figure 3D). In summary, lncRNAs were longer and possessed shorter exons and introns. Moreover, lncRNAs were also longer in the fructose groups. The target genes were identified using cis and trans methods and are provided in Tables S2 and S3. These results were used to perform lncRNA–target gene co-expression analysis, and the complete networks are shown in Figures S1–S4. We also combined the cis and trans results of DElncRNAs in the Con/F13% group and the Con/F40% group (Table S4). Clusters with more than ten genes were labeled in different colors in GO enrichment analysis. The cis lncRNA–target gene co-expression cluster with the highest number of genes in the F13% group was labeled in red, and the top terms were “positive regulation of transcription from RNA polymerase II promoter” in Biological Process (BP), “nucleus” in Cellular Component (CC), and “structural constituent of ribosome” in Molecular Function (MF). The next cluster was marked in blue, and the top terms were “positive regulation of transcription from RNA polymerase II promoter” (BP), “nucleus” (CC), and “ATP binding” (MF). The last one was marked in yellow, and the top terms were the same as the blue cluster (Figure 4A). The clusters obtained with the trans method were labeled in red and blue, and the top terms of the two clusters were the same as those obtained with the cis method (Figure 4C). The representative clusters of the F40% group contained fewer genes than the F13% group and were identified as red, blue, and yellow. To our surprise, the top terms of red and yellow clusters were the same as the blue cis cluster of the F13% group as follows: “response to drug” (BP), “nucleus” (CC), and “ATP binding” (MF). The results of the three clusters are provided in Figure 4E. Unfortunately, there was only one representative cluster in the trans results, and it was not sufficient for enrichment analysis. We also performed enrichment analysis on DElncRNA target genes, and the results are provided in Figure 5A. In the Con/F13% group, the top5 CC terms were “nucleus”, “nucleoplasm”, “neuronal cell body”, “extracellular vesicular exosome”, and “axon”. Among these CC results, some terms were related to brain development, such as “postsynaptic density”, “dendrite”, and “postsynaptic membrane”. The top terms for BP and MF were “positive regulation of transcription from RNA polymerase II promoter” and “ATP binding”, respectively. In the Con/F40% group, we paid greater attention to terms of BP, and the top five were “response to drug”, “intracellular signal transduction”, “neuron migration”, “positive regulation of GTPase activity”, and “protein ubiquitination”. “Neuron migration”, “brain development”, “hippocampus development”, and “memory” were the BP results related to the nervous system. The top terms of CC and MF were “nucleus” and “ATP binding”, respectively. The KEGG pathway enrichment analysis also highlighted some pathways. Regarding the cis results of the F13% group, the top three terms of the red cluster were “Parkinson disease”, “Oxidative phosphorylation”, and “Amyotrophic lateral sclerosis”; the terms of the blue cluster were “Leukocyte transendothelial migration”, “Tight junction”, and “Renin-angiotensin system”; and the terms of the yellow cluster were “Ribosome”, “Wnt signaling pathway”, and “Ubiquitin mediated proteolysis” (Figure 4B, Table S5). In the F40% group, there were also three colored clusters. The top three terms in the red cluster were “Melanoma”, “Breast cancer”, and “Gastric cancer”; the terms in the blue cluster were “Ribosome”, “Oxidative phosphorylation”, and “Parkinson disease”; and the terms in the yellow cluster were “Tight junction”, “Leukocyte transendothelial migration”, and “Cell adhesion molecules” (Figure 4D, Table S6). Regarding the trans results, two clusters in the F13% group had enough genes for KEGG enrichment analysis, and the top three terms for the red cluster were “Thermogenesis”, “Huntington disease”, and “prion disease”, while the top three for the blue cluster were “Ribosome”, “Wnt signaling pathway”, and “Ubinquitin mediated proteolysis” (Figure 4F, Table S7). For the DElncRNA target gene enrichment results, the top five pathways were “Oxytocin signaling pathway”, “MAPK signaling pathway”, “Hypertrophic cardiomyopathy”, “Dilated cardiomyopathy”, and “Cardiac muscle contraction” in the Con/F13% group; and “MAPK signaling pathway”, “Adrenergic signaling in cardiomyocytes”, “prion disease”, and “Osteoclast differentiation” in the Con/F40% group (Figure 5B, Table S8). In these KEGG enrichment results, we noted a term referring to “Dopaminergic synapses”. It was found in the cis blue and yellow clusters of the F13% group (p-values and enrichment factors: 0.1550, 1.9229; 0.5555, 1.2463, respectively), the trans blue clusters of the F13% group (0.5134, 1.4021), the cis red and yellow clusters of the F40% group (0.0771, 4.3419; 0.0545, 2.8042, respectively), and the DElncRNA target genes of F40% (0.0417, 6.1182). We performed a gene set enrichment analysis (GSEA) on this term to reveal the expression of all genes annotated to “Dopaminergic synapse”. The enrichment score (ES) peak values were all greater than zero in the Con/F13% and Con/F40% groups, which indicates that in the fructose groups, the up-regulated genes were dominant in “Dopaminergic Synapse” (Figure 6A). According to the enrichment results of “Dopaminergic synapses”, we further tested the DA level in the serum of PND21 and PND60 offspring. On PND60, fructose group offspring had a significantly higher DA level than the Con group (p < 0.05) (Figure 6B). Moreover, we explored the expression level of dopamine receptor D1 (DRD1) and dopamine receptor D2 (DRD2), and these receptor proteins offructose groups were significantly up-regulated (p < 0.05) (Figure 6C). These results, along with results from the open-field test, confirm that maternal high-fructose diet may influence anxiety-like behavior in offspring. To ensure the validity of sequencing and enrichment analysis, some validation tests were carried out. We validated two enriched pathways, the “PI3K/Akt pathway” and the “AMPK pathway”, by testing the changes in core protein expression. The Western blot (WB) results showed no significant differences in PI3K, Akt, nor AMPK, while p-PI3K, p-Akt, and p-AMPK in the fructose groups were all significantly up-regulated compared with the Con group (p < 0.05) (Figure 7A). Regarding the validation of gene expression, we selected eight DElncRNA genes: ONT.13539 (p-value = 0.0003; log2 (fold change) = 1.1685), ONT.119 (0.0057; −0.9770), ONT.13715 (0.0067; −0.6060), and ONT.11765 (0.0077; −0.9760) in the Con/F13% group; ONT.11295 (0.0002; −0.6188), ONT.1222 (0.0014; 1.0059), ONT.5939 (0.0030; −1.3201), and ONT.252 (0.0045; 0.84278) in the Con/F40% group. The reverse transcription quantitative polymerase chain reaction (RT-qPCR) results are provided in Figure 7B. The expression of all genes was significantly different (p < 0.05) according to the comparison, and this expression difference was consistent with the sequencing results. We also predicted the Transcription factor binding site (TFBS) of these DElncRNA genes, as shown in Figure 7C. In addition, immunofluorescence (IF) was used to test the expression of BDNF, which is related to brain development. Clear distinctions were evident, and BDNF was reduced in the fructose groups (Figure 7D). Processing technology has made it easier for consumers to consume convenient and delicious processed foods [1], and these foods are enriched with HFCS [2]. Several studies have shown that eating high-fructose foods for a long time may affect stress response and anxiety-like behaviors [12,13,14]; however, the mechanism is still unclear. lncRNA plays a certain role in nervous system development and is also closely related to emotion regulation [24]. This study examined the effect of maternal high-fructose diets during gestation and lactation on offspring lncRNAs and anxiety-like behavior. lncRNAs were predicted using ONT full-length RNA sequencing. Research has shown that the functional annotation of lncRNAs and the co-expression analysis of lncRNA target genes are powerful methods for the functional analysis of lncRNAs [19]. Our previous study suggested that maternal high-fructose diet during gestation and lactation can affect offspring neurodevelopment by affecting transcript and gene expression [11]. In this study, we also noted that “in utero embryonic development” was enriched in the blue cluster of the F40% group as found using the cis method. Embryo development is a complicated process. It involves the differentiation and growth of a variety of cells, including neuronal cells. Special lncRNAs are able to regulate genes that play key roles in embryonic development [30,31] and in the growth of neuronal cells via both the cis and trans regulation of coding genes [32,33], which is very similar to the role of transcription factors. lncRNAs are specifically expressed in neural stem cell differentiation and regulate the genes of transcription factors that are critical to neural stem cell self-renewal [34]. They can also influence neural stem cell differentiation through chromatin remodeling [35]. In our enrichment analysis of several co-expression clusters and DElncRNA target genes, we observed overlapping results regarding “neuronal cell body” and “negative regulation of neuron differentiation”. Further, “neuron migration” was enriched, and this term was also highlighted in our previous enrichment analysis results of differentially expressed transcripts (DETs) [11]. Neuron migration coordinates the formation of various brain structures during brain development [36]. Most neurons migrate from their birthplace to specific brain locations and then extend out of axons; neurodevelopmental dysregulation may occur when neuronal or axonal migration is disrupted [37]. This indicates that maternal high-fructose diet during gestation may seriously affect the development of the fetal brain. Moreover, lncRNA might influence cognitive function in the central nervous system [38]. Our study found that “hippocampus development” and “memory” of DElncRNA target genes were enhanced. Memory and learning occur in the hippocampal region, and synapses are integral to these processes. Consistently, there were two terms that were enriched in the top ten list: “postsynaptic density” and “postsynaptic membrane”. Studies have shown that synaptic ncRNA-mRNA clusters were more abundant than those in total tissue homogenates [39,40]. Specific long non-coding RNAs can influence synaptic gene expression in cultured hippocampal neurons by interacting with splicing proteins [41,42]. Furthermore, antisense lncRNAs have been demonstrated to regulate neurite formation by regulating several key proteins involved in the process [43,44]. We also noted that “dendrite” was highlighted in DElncRNA target gene results. By influencing the translation and expression of some dendrite-related mRNA, ncRNAs control dendrite cell bodies [45,46]. In Smalheiser [40], the relationship between ncRNAs and learning and memory is further elaborated, in addition to these significantly enriched neuronal structures. In summary, maternal high-fructose diet during gestation and lactation can affect synapse function by changing lncRNA–target gene co-expression; as a result, the cognition of offspring is affected. lncRNAs can also affect brain development. Further, “brain development” was found not only in lncRNA–target gene co-expression but also in DET enrichment results [11]. Allen Brain Atlas (ABA) [47] is a large-scale investigation based on gene expression in adult mice. A large number of non-coding RNAs detected in ABA were linked to specific neuroanatomical areas and neurons [48]. It provided convincing evidence that lncRNAs are strongly associated with brain development. Furthermore, lncRNAs have also been linked to neurodegenerative diseases [49,50], such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD), and these were also highlighted in our enrichment analysis. AD is the most common neurodegenerative disorder, and amyloid β (Aβ) is the key part that causes AD [51]. Some lncRNAs and their target genes were specifically expressed in the brain tissues, cerebrospinal fluid, and even blood of AD patients [52,53]. Moreover, some lncRNAs, such as Neuroblastoma differentiation marker 29, could influence the Aβ42: Aβ40 peptide ratio [54,55]. PTEN-induced kinase 1 (PINK1) is a protein that plays a crucial role in PD, which is a chronic neurological disease. It has been shown that silencing lncRNAs may affect PINK1 expression by regulating PINK1 encoding genes [56]. Other scholars have found that lncRNA expression was changed in the brain tissues of HD patients and HD mouse models [57]. To our surprise, “Cardiac muscle contraction”, “Arrhythmogenic right ventricular cardiomyopathy”, and “VEGF signaling pathway” were enriched. lncRNA can regulate chromatin and affect epigenetic inheritance by forming RNA-RNA, RNA-DNA, or RNA-protein complexes [58,59,60]. Heart disease has been linked to cognitive impairment, and the effects of the hippocampus on cognitive function extend to the circulatory system [61]. The hippocampus is also a potential sentinel site for ischemic lesions after resuscitation cardiac arrest [62,63]. Our research revealed that hippocampal function is affected in terms of signaling pathways, which can have cardiovascular effects. Simultaneously, research has pointed out that cardiac diseases were closely related to chromatin regulation, as chromatin-regulating factors could program cardiac gene expression to regulate cardiomyocyte development in embryos; control cell proliferation and differentiation in the neonatal period; and trigger gene recoding when the mature heart was stimulated [64]. lncRNAs have also became a key target in the treatment of cardiovascular diseases [60]. We also noted that the “AMPK signaling pathway” was highlighted in many of the top enrichment pathway results. AMPK used to be considered as an important regulator of heart energy metabolism; however, some scholars have pointed out that whether AMPK is a friend or foe is still unclear [65]. Many studies have shown that either abnormal activation or deactivation could cause cardiomegaly [66,67,68], and in our verification results, p-AMPK was significantly up-regulated. Both high and low expression of AMPK may affect neuroplasticity [69]; however, the mechanism is not clear at present. We also performed some verification experiments to ensure the accuracy of ONT full-length RNA sequencing. The “PI3K/Akt signaling pathway” was verified, and studies have shown that this pathway is up-regulated in anxiety-like behaviors [70,71,72]. A number of studies have shown that the PI3K/Akt signaling pathway is closely related to the learning and memory functions of the hippocampus and that it is a key pathway for the hippocampus to affect cognitive function [69,73]. Additionally, lncRNAs could regulate target genes to affect brain development, and BDNF has been widely recognized as a key neurotrophic factor involved in brain development [74,75,76]. Consistently, the expression of BDNF was decreased in fructose groups. Anxiety-like behaviors and their molecular mechanisms were investigated in experiments. On PND60, the open-field test was performed on offspring. Compared with the Con group, fructose group offspring were more active and restless in unfamiliar surroundings. The DA level in PND21 and PND60 offspring serum was also tested, and the results confirmed the open-field test results, i.e., the fructose groups had significantly higher DA levels than the Con group. The relationship between emotion and DA remains a hot topic, and one recognized view is that too much or too little of either could have adverse effects [77,78]. Studies have revealed that the decrease in dopamine transporter (DAT) may improve anxiety-related behaviors [79]; the inhibition of DA neurons is also necessary for antianxiety effects [80]; in the social isolation animal model, DA release and DA transporter activity were sustained and increased, and anxiety-like behaviors appeared [81,82]. In many of these enrichment analysis results, “Dopaminergic synapse” is stressed. The dopaminergic synapses regulate the release, diffusion, and uptake of DA [83,84]. The expression of all genes annotated to “Dopaminergic synapse” showed that the up-regulated genes contributed more. The fructose groups showed high levels of expression of DRD1 and DRD2 receptors, which play a key role in anxiety regulation [78]. These results further confirm that maternal high-fructose diet could influence offspring anxiety-like behaviors by influencing offspring dopaminergic synapses and DA content, and this effect may be caused by transcription differential expression, as well as lncRNAs that regulate gene encoding and expression. Our study included 18 healthy two-month-old female and male SD rats raised at Centre for Experimental Animals at China Medical University (Shenyang, China). The rats were raised in a constant environment (20–25 °C, 50–65%), with 12 h light and 12 h dark cycles. After one week of adaptive feeding, the rats were mated (♀:♂ = 2:1). Gestation day (GD) 0 is the day when the vaginal plug was found. On GD0, the dams were randomly divided into Con (n = 6), F13% (n = 6) [85,86], and F40% (n = 6) [87,88]. PND0 is the day when a dam gave birth to offspring. From GD0 to PND21, the three groups drank different-concentration drinks with 0 g/mL, 13 g/mL, and 40 g/mL D-fructose (Solibao, Beijing, China) and were fed uniform fodder used in feeding centers. Offspring were separated and reared according to sex on PND21. Then, all the offspring started the same normal diet until they were PND60. We weighted dams and offspring, tested the offspring 12 h FBG and 12 h FinS on PND21 and PND60. Rats were sacrificed with diethyl on PND60, and materials were stored at −80 °C. Every effort was made to minimize the suffering of animals. Figure 8 illustrates an intuitive experimental route. In a novel environment, an open-field test can evaluate the autonomous behavior, inquiry behavior, and tension of animals. The experimental device consisted of an open-field chamber and a data recorder (Noldus EthoVison XT; Wageningen, The Netherlands). The dark chamber, of 100 cm in length × 100 cm in width × 60 cm in height, was divided into 16 virtual squares of 25 cm × 25 cm, and the 4 squares surrounding the center were the central regions. The test was performed using six rats (♀:♂ = 1:1) from each group at 20:00–22:00 on PND60. We placed each rat in the same corner, and it could freely explore the strange surroundings for 5 min. Simultaneously, the system traced the movement of rats and calculated the speed and frequency of young rats; a rat with a speed of over 50 cm/s was considered anxious, and one with a speed between 30 and 50 cm/s was considered active. To avoid residual information, the chamber was cleaned with 95% alcohol between trials. The speed level, frequency in the central area, number of standing instances, and trajectory were used to measure the offspring anxiety-like behavior. From each group, six rats (♀:♂ = 1:1) were randomly selected, and their blood was kept at room temperature for 2 h and centrifuged at 12,000 rpm for 20 min at 4 °C. The upper serum was used for ELISA. We assayed the DA level using Rat DA ELISA Kit (Enzyme-linked Biotechnology, Shanghai, China). Prepared as above, aliquots of 50 μL of DA standards (0, 0.05, 0.1, 0.2, 0.4, 0.8, and 1.6 ng/mL) were added to standard wells, while 50 μL of the sample was added to test sample wells. Each well was then incubated for 30 min at 37 °C with 50 μL of HRP-conjugated reagent after gently mixing. Chromogen solution A and solution B were added to each well after incubating and washing, and the plate was kept at 37 °C for 15 min in the absence of light. In the last step, 50 μL of stop solution was added to each well. We read the absorbance at 450 nm using a microplate reader (H1MD; Cube Biotech, Monheim, Germany). A curve was generated, and the DA levels of the samples were calculated. Full-length nanopore RNA sequencing was conducted according to the protocol provided by Oxford Nanopore Technologies (Oxford, UK), including sample quality detection, cDNA library construction, library data polishing, and sequencing. Eight hippocampi from PND60 offspring were randomly selected in each group (♀:♂ = 1:1). Total RNA from the tissues was isolated, quality-tested, reverse-transcribed, and subjected to magnetic bead purification, and the final cDNA libraries were run on the PromethION platform (Oxford Nanopore Technologies plc, Oxford, UK) at Biomarker Technology Company (Beijing, China). Raw reads were filtered with a minimum quality score of 6 and a minimum length of 500 bp to avoid affecting the subsequent analysis. From the clean data, full-length non-chimeric (FLNC) transcripts were identified by detecting primers at both ends of the reads (Table S9). The full-length sequence was compared with the reference genome using minimap2 software (version 2.16). The genome was ENSEMBLE (Rnor_6.0_release95). After clustering using the comparison information, the consistency sequence was obtained using pinfish software (version 0.1.0). Finally, consensus sequences were mapped to the reference genome using minimap2. Mapped reads were further collapsed using the cDNA Cupcake package with min-coverage = 85% and min-identity = 90%. The 5′ difference was not considered when collapsing redundant transcripts. As lncRNA does not encode proteins, it is necessary to determine whether lncRNA has coding potential by screening transcripts for coding potential and find transcripts that do not have coding ability, so that the transcripts can be identified as lncRNA. CPC [89], CNCI [90], CPAT [91], and Pfam [92] were used to predict the transcripts with coding potential; then, the transcripts without coding potential were obtained using the inverse extrapolation method. The indexes we used were as follows: for CPC and CNCI, non-protein-coding RNA with score < 0; for CPAT, non-protein-coding RNA with score > 0.38; for Pfam, domain screening condition e-value < 0.001. lncRNA analysis was conducted using the intersection of non-protein-coding transcripts identified using the above four methods. Moreover, the counts per million of all transcripts in each sample were calculated using the EdgeR package (version 3.8.6). lncRNAs with a p < 0.05 and fold change ≥ 1.5 were DElncRNAs. We used the cis and trans prediction methods to predict lncRNA sequences. By using the cis method, lncRNAs control the expression of adjacent genes. The target genes were defined based on the location of lncRNAs and mRNAs on chromosomes. Genes within the 100 kb range of lncRNA were cis target genes. Trans regulation relies on base complementary pairing between lncRNA and mRNA, and the LncTar target gene prediction tool is exclusively used to predict trans target genes. Then, these correlations were shown as co-expression networks using Cytoscape software (version 3.9.1). We selected co-expression clusters with many genes from the network and performed GO enrichment analysis, KEGG pathways enrichment analysis, and GSEA on these clusters. The GO database was established by the Gene Ontology Consortium and is applied to all species. It also describes the functions of proteins and genes with a standard vocabulary system. This database consists of BP, CC, and MF main branches. The GO-seq R packages, based on Wallenius noncentral hypergeometric distribution, were used to perform GO enrichment analysis. KEGG includes the current molecular network interactions, such as icon channels and complexes. KEGG enrichment analysis was performed using KOBAS, and statistical indicators used the proportion of annotated transcripts and enrichment factors. GSEA can understand the expression trend of genes in specific functional gene sets and whether the expression trend has any statistical significance [93]. In the resulting graph, the green line represents the running gene ES, and the ES peak is used to reveal the core genes under this gene cluster; hits represent each gene under this gene set; rank distribution is shown at the bottom. This analysis was implemented in the R-GSEA program, and the gene sets with NES > 1 or < −1 (p-value < 0.05) were the leading-edge subsets. Brain tissues from six rats (♀:♂ = 1:1) were randomly selected in each group. After 36 h of fixation, the tissues were embedded in paraffin blocks and cut into 6 μm thick sections. Complete hippocampus sections were baked at 60 °C for 2 h. Antigen repair was carried out for 15 min, followed by 30 min of preincubation in 10% normal goat serum. Then, the sections were incubated with rabbit anti-BDNF (diluted to 1:100; ABclonal, Wuhan, China) at 4 °C overnight. The sections were then incubated with the second antibody (Cy3 goat anti-rabbit; diluted to 1:800; ABclonal, Wuhan, China) at room temperature for 2 h. The sections were sealed with an antifade mounting medium in a dark environment and observed at ×200 magnification under a forward fluorescence microscope (80i; Nikon Corporation, Tokyo, Japan). In each group, six protein homogenates (♀:♂ = 1:1) were randomly selected. After centrifuging at 12,000 rpm for 10 min at 4 °C, the supernatant was separated from the homogenate and assessed using BCA Protein Assay Kit (Beyotime Biotechnology, Shanghai, China). We adjusted the concentration of protein to 3 μg/μL with phosphate-buffered saline (PBS) and 5× SDS loading buffer (Beyotime Biotechnology, Shanghai, China), and sample degeneration was performed at 100 °C for 5 min. Vertical electrophoresis was performed under the constant voltage of 120 V for 75 min; then, the proteins were transferred onto polyvinylidene difluoride membranes (Thermo Fisher Scientific, Waltham, MA, USA) under the constant voltage of 100 V for 75 min. The membranes were cut at the location of the target proteins following blocking in 5% skimmed milk for 90 min. Then, these cuttings were incubated with the following primary antibodies: rabbit anti-DRD2, rabbit anti-PI3K catalytic subunit alpha, rabbit anti-Akt 1, and rabbit anti-AMPK (diluted to 1:1000; ABclonal, Wuhan, China); rabbit anti-p-Akt (Ser473), rabbit anti-p-AMPKα (Thr172), and rabbit anti-β-actin (diluted to 1:1000; Cell Signaling Technology, Boston, MA, USA); rabbit anti-p-PI3K (Tyr607) (diluted to 1:500; Affinity Biosciences, Changzhou, China); rabbit anti-DRD1 (diluted to 1:1000; Proteintech, Wuhan, China). After incubation with the primary antibody at 4 °C overnight, the second antibody was incubated with HRP secondary antibody (goat anti-rabbit; diluted to 1:5000; ABclonal, Wuhan, China) at room temperature for 2 h. Chemiluminescence Western Blot Kits (Beyotime Biotechnology, Shanghai, China) were used to reveal the proteins using Tanon-5200 (Tanon, Shanghai, China). For each protein, β-actin was analyzed as quality control. Total RNA was extracted from six rats (♀:♂ = 1:1, randomly selected in each group) using TRIzol (Vazyme, Nanjing, China), and RNA purity and concentration were evaluated using Nanodrop ND-2000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The purity of all samples ranged from 1.9 to 2.2. RNA was dissolved in 0.1% diethyl pyro-carbonate (Vazyme, Nanjing, China) and transcribed into cDNA with Reverse Transcription Kit (HiScript III RT SuperMix for qPCR with gDNA wiper; Vazyme, Nanjing, China). The sequence of lncRNAs was provided by Biomarker Technology Company, and the primers were synthesized and produced by Sangon Biotech (Shanghai, China) (Table S1). lncRNA expression was quantified with PCR using qPCR Kit (ChamQ Universal SYBR qPCR Master Mix; Vazyme, Nanjing, China). PCR was performed with QuantStudio 6 Flex Real-time System (Thermo Fisher Scientific, Waltham, MA, USA) according to the following curve: denaturation at 95 °C for 30 s; extension at 95 °C for 10 s; annealing at 60 °C for 30 s; finally, dissociation at 95 °C for 15 s, at 60 °C for 1 min, and at 95 °C for 15 s. We used β-actin (Sangon Biotech, Shanghai, China) as the control and calculated gene relative expression with the 2−ΔΔCt method. TFBStools was used to predict TFBS in the promoter region of specific target genes, and the potential promoter was defined as a region of about 1 kb upstream of the gene. The reference TF motif database was JASPAR. All statistical analyses were performed using SPSS 21.0 software (IBM SPSS, Inc., Chicago, IL, USA). Unpaired Student’s t-test or one-way analysis of variance (ANOVA) was performed between groups. After ANOVA analysis, equal variance with least significant difference (LSD) and Student–Newman–Keuls (S-N-K), and unequal variance with Dunnett’s T3 were performed. p < 0.05 indicated that the difference was statistically significant. Some data were expressed as means ± SEMs. All graphs were created using GraphPad Prism 8.0 software (GraphPad Software, San Diego, CA, USA). Maternal high-fructose diet during gestation and lactation changed the expression of lncRNAs and their target genes in the hippocampus of offspring, and this differential expression further affected multiple physiological functions, especially items related to brain development. In the enrichment analysis results, “dopaminergic receptors” was enriched, and our animal behavior and molecular experiments also confirmed that offspring showed anxious-like behaviors. Our study also suggests a relationship between lncRNAs and emotion regulation.

PMC10003395

Hideji Yoshida,Tomohiro Shimada,Akira Ishihama

Metal-Responsive Transcription Factors Co-Regulate Anti-Sigma Factor (Rsd) and Ribosome Dimerization Factor Expression

01-03-2023

metal-responsive transcription factor,transcriptional regulation,translational regulation,Rsd,RMF,100S ribosome

Bacteria exposed to stress survive by regulating the expression of several genes at the transcriptional and translational levels. For instance, in Escherichia coli, when growth is arrested in response to stress, such as nutrient starvation, the anti-sigma factor Rsd is expressed to inactivate the global regulator RpoD and activate the sigma factor RpoS. However, ribosome modulation factor (RMF) expressed in response to growth arrest binds to 70S ribosomes to form inactive 100S ribosomes and inhibit translational activity. Moreover, stress due to fluctuations in the concentration of metal ions essential for various intracellular pathways is regulated by a homeostatic mechanism involving metal-responsive transcription factors (TFs). Therefore, in this study, we examined the binding of a few metal-responsive TFs to the promoter regions of rsd and rmf through promoter-specific TF screening and studied the effects of these TFs on the expression of rsd and rmf in each TF gene-deficient E. coli strain through quantitative PCR, Western blot imaging, and 100S ribosome formation analysis. Our results suggest that several metal-responsive TFs (CueR, Fur, KdpE, MntR, NhaR, PhoP, ZntR, and ZraR) and metal ions (Cu2+, Fe2+, K+, Mn2+, Na+, Mg2+, and Zn2+) influence rsd and rmf gene expression while regulating transcriptional and translational activities.

Metal-Responsive Transcription Factors Co-Regulate Anti-Sigma Factor (Rsd) and Ribosome Dimerization Factor Expression Bacteria exposed to stress survive by regulating the expression of several genes at the transcriptional and translational levels. For instance, in Escherichia coli, when growth is arrested in response to stress, such as nutrient starvation, the anti-sigma factor Rsd is expressed to inactivate the global regulator RpoD and activate the sigma factor RpoS. However, ribosome modulation factor (RMF) expressed in response to growth arrest binds to 70S ribosomes to form inactive 100S ribosomes and inhibit translational activity. Moreover, stress due to fluctuations in the concentration of metal ions essential for various intracellular pathways is regulated by a homeostatic mechanism involving metal-responsive transcription factors (TFs). Therefore, in this study, we examined the binding of a few metal-responsive TFs to the promoter regions of rsd and rmf through promoter-specific TF screening and studied the effects of these TFs on the expression of rsd and rmf in each TF gene-deficient E. coli strain through quantitative PCR, Western blot imaging, and 100S ribosome formation analysis. Our results suggest that several metal-responsive TFs (CueR, Fur, KdpE, MntR, NhaR, PhoP, ZntR, and ZraR) and metal ions (Cu2+, Fe2+, K+, Mn2+, Na+, Mg2+, and Zn2+) influence rsd and rmf gene expression while regulating transcriptional and translational activities. When an organism is exposed to stress, the expression of many genes is regulated at transcriptional and translational levels. For instance, in Gram-negative bacteria, such as Escherichia coli, the sigma factor RpoD binds to RNA polymerase under favorable growth conditions and serves as a basic transcription mechanism [1]. However, when growth is arrested in response to stress, such as nutrient starvation, the anti-sigma factor Rsd is expressed and binds to the global regulator RpoD, which becomes inactivated [2]. In addition, the sigma factor RpoS binds to RNA polymerase and expresses stationary phase-specific genes [3,4], allowing E. coli to regulate the transcription of stress-responsive genes. However, at the translational level, ribosome modulation factor (RMF), which is expressed in response to growth arrest, binds to 70S ribosomes to form inactive 100S ribosomes (dimers of 70S ribosomes), which regulate translational activity [5,6]. It is worth noting that these transcriptional and translational regulations occur simultaneously under stress, suggesting that several stress-responsive transcription factors (TFs) are involved in the expression of rsd and rmf genes. Therefore, elucidating the mechanisms of rsd and rmf gene expression will be critical to understanding bacterial survival strategies. In a previous study, we used a promoter-specific TF (PS-TF) screening system to identify TFs that regulate rsd and rmf gene expressions by comprehensively examining the binding of approximately 200 E. coli TFs to the promoter regions of rsd and rmf genes [7]. The results revealed that multiple TFs bind to the promoter regions of rsd, which regulates transcription, and rmf, which regulates translation. Thus, we reported in the study that transcription and translation are simultaneously regulated in response to various types of stress. In addition, several studies have shown that the TFs involved in amino acid starvation and biofilm formation are involved in the expressions of both rsd and rmf genes [8,9]. Metal ions are essential for diverse cellular processes, such as photosynthesis, gluconeogenesis, glycolysis, signal transduction, stringent response, sporulation, and pathogenesis [10,11,12,13]. However, metal ions are toxic at high intracellular concentrations [14,15,16] and their levels are regulated by homeostatic mechanisms involving metal-responsive TFs [17,18,19,20,21]. Therefore, in this study, we investigated the involvement of metal-responsive TFs in regulating rsd and rmf gene expressions. In stress caused by either a deficiency in or an excess of metal ions, we hypothesized that metal-responsive TFs might be involved in regulating the expression of rsd and rmf genes, which regulate the transcriptional and translational activities in the cell. Therefore, we examined the involvement of several metal-responsive TFs, namely BasR, CueR, CusR, Fur, KdpE, MntR, NhaR, PhoP, ZntR, ZraR, and Zur (Table 1). BasR and BasS form a typical two-component system, which functions as an iron–zinc-induced transcription regulator for a group of genes related to metal-responsive membrane structure modification and function regulation [22,23]. CueR and CusR regulate intracellular copper levels [16,24]. CueR is activated mainly under aerobic conditions, while CusR is activated under anaerobic conditions [25]. Fur regulates intracellular iron concentration and is essential for many processes, such as DNA synthesis and respiration [21,26]. The two-component KdpD/KdpE system regulates the transport of K+, the most abundant ion in the cell, with KdpD acting as the sensor kinase and KdpE acting as the response regulator [27,28]. MntR is associated with the regulation of intracellular Mn2+ concentration, glycogenesis, and oxidative stress [15,29]. NhaR participates in the maintenance of sodium concentration by regulating the expression of the membrane protein NhaA [30,31]. PhoP, in conjunction with PhoQ, functions as a two-component system facilitating Mg2+ transport [32,33], and ZntR, ZraR, and Zur aid in the regulation of intracellular Zn2+ concentration, an important component of many proteins [14,34,35,36,37,38]. Herein, we first examined whether metal-responsive TFs (listed in Table 1) bind to the promoter regions of the rsd and rmf genes. After that, we then investigated the effect of each TF gene-deficient strain on the expression of rsd and rmf. We believe that this study will be useful for understanding bacterial survival strategies because transcriptional and translational regulations in stress conditions, such as a deficiency in or an excess of metal ions, are essential survival mechanisms for bacteria, and our findings will provide new insights into infectious disease control, where long-term survival is an obstacle to countermeasures. Two assays were used to examine whether metal-responsive TFs bind to the promoter regions of the rsd and rmf genes. First, the TFs used for in vitro assays were purified (Figure S1), and proteins other than His-MntR (Figure S1H) and His-ZraR (Figure S1L) were obtained without difficulty; however, only a small amount of His-MntR was obtained. In particular, several bands obtained during sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) were slightly smaller than those representing the molecular weight of intact His-MntR, suggesting that the purified MntR may have been degraded. Moreover, two His-ZraR bands were obtained using SDS-PAGE, and since the His-tag was attached to the N-terminus of the protein, several amino acids in the C-terminal region may have been trimmed. Figure 1 shows the electrophoresis patterns for examining TFs with rsd and rmf promoter-binding activity using the PS-TF screening system (see Section 4.4). The rtcA DNA probe is a reference DNA fragment corresponding to the open reading frame sequence of the rtcA gene, to which TFs are expected not to bind. Without the addition of a TF, each of the three DNA probes formed a single band against the estimated size, as shown in Figure 1A. However, if the added TF binds to the DNA probe, the band of the probe migrates upward from the position shown in Figure 1A. Dan (previous name: YgiP, a DNA-binding protein under anaerobic conditions) was employed as the negative control since it was found from a previous PS-TF screening [7] not to bind to either the rsd or rmf probes. In contrast, SdiA (a quorum-sensing system regulator) was found to bind to both rsd and rmf probes and was employed as the positive control. Similar to a previous study [7], Dan did not bind to either the rsd or rmf probes (Figure 1B), while SdiA was bound to both probes (Figure 1C). Table 1 shows the characteristics of transcription factors (TFs) targeted in this study. Figure 1D–N shows the electrophoresis patterns demonstrating the binding of various TFs and probes. Remarkably, CueR was clearly bound to both rsd and rmf probes, as shown in Figure 1E, whereas the others showed no binding. Most TFs examined did not bind to the probes, probably because of the lack of additional effectors for each of them. Considering this possibility, electrophoresis was performed by adding effectors (metal ions) to the TF and probe mixture. However, the effectors inhibited electrophoresis (Figure S2). Therefore, we designed an experimental method to verify the binding of TFs and DNA probes using a magnetic bead assay (see Figure 2, Section 4.5). In this assay, fluorescence can be detected if the fluorescein-4-isothiocyanate (FITC)-labeled DNA probe binds to the His-tagged TF in the solution eluted with imidazole (Figure 2E). Figure 3 shows the analyzed fluorescence results using a laser scanner, and the data without effectors can be compared with the PS-TF data in Figure 2. Figure 3A shows the results obtained after the addition of Dan and SdiA. The upper panel is a scanned image of the fluorescence emission state of the solution, and the lower panel is a graph normalized by the fluorescence intensity in the case of Dan, which is known not to emit fluorescence. SdiA binds to both probes and shows fluorescence. Figure 3B–L showed the results when metal-responsive TFs were added. BasR, Fur, KdpE, NhaR, PhoP, ZntR, ZraR, and Zur were bound to the rsd and rmf probes after adding the effector, as shown in Figure 3B,E,F,H–L, respectively, whereas in Figure 3C, although CueR binds to the rsd and rmf probes without the effector (CuSO4), its addition increases the extent of binding (Figure 1E). It is also worth noting that CusR and MntR (Figure 3D,G, respectively) did not show clear binding to the probes, even when the effector was added. The PS-TF screening and beads assay, which examine binding to the rsd and rmf promoters for target TFs [7], have been performed multiple times, and their results were reproduced in this study (Figure 1 and Figure 3). However, these data were obtained in vitro using His-tagged protein, which may bind non-specifically to DNA in the presence of metal ions [42]. Therefore, these results do not guarantee the binding or non-binding of each TF to the rsd and rmf promoters in vivo but only indicate the possibility of occurrence. For example, we looked for non-specific binding of His-tagged protein (Dan) to the rsd promoter by the addition of each effector and could not observe any such binding, as shown in Figure S3. The effect of gene deletions in each TF on rsd and rmf transcription levels was examined through quantitative PCR (qPCR) after reverse transcription. Each bacterial cell used in qPCR analysis was harvested 24 h after incubating the culture. Analysis of the qPCR results confirmed that the mRNA of each TF in the parental strain was transcribed under culture conditions (Figure S4). Gene deletion of each TF was confirmed by the lack of each transcription level in each TF gene-deficient strain harvested 24 h after incubating the culture in a similar experiment as Figure S4. Figure 4 shows the relative transcript levels of rsd (A) and rmf (B) measured using qPCR and normalized to those of the parental strain. When basR, cusR, zraR, and zur were deleted, the transcription level of rsd was comparable to that of the parental strain (Figure 4A). Since CusR does not bind to the rsd promoter, as shown in Figure 3, it was assumed that the transcription level of rsd did not change. Similarly, despite the binding of BasR, ZraR, and Zur to the rsd promoter, the transcription levels of rsd did not change in these gene-deficient strains (Figure 3). However, the transcription levels of rsd increased when the genes encoding other TFs were deleted. In addition, despite the lack of binding of MntR to the rsd promoter (Figure 3), the transcription levels of rsd appeared to increase in the mutant strain with an mntR deletion. Figure 4B shows the relative transcription level of rmf. When basR, cusR, and zur were deleted, the transcription levels of rmf were comparable to those of the parental strain, and this behavior is similar to that observed for rsd transcription. However, the transcription levels of rsd decreased when the fur gene was deleted, and the deletion of genes encoding other TFs increased the transcription levels of rmf. Next, we examined the effect of TF gene deletion on the expression of Rsd and RMF proteins. Figure 5 shows the results of Western blotting with antibodies against Rsd and RMF (as well as RpoA, YqjD, and RplB), performed using the cell extracts from each E. coli strain harvested 24 h after incubating the culture. YqjD is a membrane-binding protein expressed in the stationary phase that binds to ribosomes (Figure 5A) [43]. YqjD expression is regulated by the sigma factor RpoS (σs), which is involved in stress response [43]. Rsd binds to the global regulator RpoD (σD), allowing RpoS to bind to the RNA polymerase [2]. Thus, increased Rsd expression is expected to promote RpoS binding to RNA polymerase and enhance YqjD expression. RNA polymerase subunit alpha (RpoA), one of the proteins that make up RNA polymerase, normalizes the protein levels of Rsd and YqjD. Figure 5B,C shows the ratio of the band density of Rsd and YqjD to that of RpoA normalized by the parental strain (parent) data, respectively. As shown in Figure 5B, the deletion of cueR, kdpE, mntR, nhaR, phoP, or zntR genes increased Rsd expression, while the deletion of other TF genes did not significantly change the expression levels of Rsd. These results are similar to those of mRNA abundance analysis obtained through qPCR (Figure 4A). Moreover, the changes in YqjD expression in each TF-deficient strain (Figure 5C) were similar to the changes in Rsd expression (Figure 5B), thus supporting the speculation that cueR, kdpE, mntR, nhaR, phoP, or zntR gene expression is involved in Rsd expression. However, the deletion of the fur gene did not significantly change the expression levels of Rsd (Figure 5A) but increased that of YqjD (Figure 5B). Furthermore, rsd mRNA expression appeared to increase after fur gene deletion (Figure 4A), suggesting that fur is involved in rsd transcription. Ribosomal protein L2 (RplB) is one of the core proteins that make up the 50S ribosomal subunit and normalizes the level of RMF. Figure 5D shows the results of Western blotting using the RMF antibody. Figure 5E shows the ratio of the RMF band density to the RplB band density normalized by the bar data. The expression of RMF was clearly increased by deletion of the kdpE, mntR, nhaR, phoP, zntR, or zraR genes and decreased by the loss of the fur gene, which is similar to the results of mRNA abundance analysis obtained using qPCR (Figure 4B). RMF is a key factor in 100S ribosomal formation, and its behavior is directly related to the number of 100S ribosomes. Therefore, we examined their formation in each TF-deficient strain (Figure 6). Figure 6A–L shows the ribosome profiles obtained by analyzing the cell extracts obtained from sucrose density gradient centrifugation of each mutant strain cultured for 24 h. The 70S and 100S ribosomes were observed in all strains. Figure 6M shows the 70S to 100S ribosome abundance ratio (100S/70S ratio) for each strain, as calculated by the Systat software (Systat Software, Chicago, IL, USA) from the waveform of the ribosome profile. Genetic deletions of cueR, kdpE, mntR, nhaR, phoP, zntR, and zraR increased the number of 100S ribosomes formed as opposed to their parental strains. However, the number of 100S ribosomes formed by genetic deletions of basR, cusR, and zur was similar to that of the parental strains. Furthermore, the genetic deletion of fur actually reduced the number of 100S ribosomes formed. These results are similar to the data on RMF levels in each mutant strain (Figure 5D,E). In this study, we investigated the involvement of metal-responsive TFs in the expression of Rsd and RMF proteins, which regulate transcriptional and translational activities under stress. In vitro assays showed that most TFs bind the promoter regions of rsd and rmf genes following the addition of effectors (Figure 1 and Figure 3). However, CusR and MntR did not bind to the promoter regions of the rsd and rmf genes, even when an effector, acetyl phosphate (AcP) or MnCl2, was added (Figure 3D,G), which is likely due to the absence of these TF-binding sites in the range of the promoters examined. In addition, we measured the changes in rsd and rmf mRNA levels (Figure 4), Rsd and RMF protein levels (Figure 5), YqjD protein levels affected by Rsd (Figure 5A,C), and 100S ribosome formation affected by RMF (Figure 6) when the gene encoding each TF was deleted. We found that the deletion of cueR, kdpE, mntR, nhaR, phoP, and zntR clearly increased rsd mRNA levels (Figure 4A) as well as Rsd (Figure 5B) and YqjD protein levels (Figure 5C). However, as shown in Figure 1I and Figure 3G, the binding of MntR to the rsd promoter was not observed. The His-tagged MntR used in this assay was difficult to express or purify, as shown in Figure S1H; therefore, we considered that it may have been non-degradable or insoluble. Nevertheless, although in vitro assays have not confirmed the binding of MntR to the rsd promoter region, we presumed that this TF is involved in the expression of Rsd and the above TFs. Furthermore, the deletion of kdpE, mntR, nhaR, phoP, zntR, and zraR clearly increased rmf mRNA levels (Figure 4B), RMF protein levels (Figure 5E), and 100S ribosome formation (Figure 6M). Although cueR gene deletion does not increase RMF levels (Figure 5E), rmf mRNA and 100S ribosomal levels were increased (Figure 4B and Figure 6M, respectively). Since the increase in the 100S ribosome level indicates an increase in the RMF protein level, it is assumed that CueR is also involved in the expression of RMF as well as the above TFs. A series of experiments (Figure 1, Figure 4 and Figure 6) has shown that CusR does not participate in the expression of Rsd or RMF. Furthermore, CusR is activated under anaerobic conditions, while CueR is activated under aerobic conditions [25]. Since this experiment was performed under aerobic conditions, we considered that the involvement of CusR in the expression of the rsd and rmf genes may not be apparent. However, the deletion of the fur gene clearly reduced rmf mRNA (Figure 4B), RMF protein (Figure 5E), and 100S ribosome levels (Figure 6M), unlike other TFs. Based on these results, we discuss the effect of changes in the concentration of several metal ions on the transcriptional and translational activities of E. coli cells. Deletion of cueR, kdpE, mntR, nhaR, phoP, zntR, and zraR increases Rsd, RMF, and YqjD expression along with 100S ribosome formation. This indicates that these TFs repress the expression of rsd and rmf genes by binding their promoter regions. Although some of these TFs are known to have consensus sequences for DNA binding [39], the determination of exact binding sites in the promoter regions of rsd and rmf genes is difficult and remains a future challenge. Furthermore, several studies have shown that most E. coli promoters carry binding sites for multiple TFs, with each factor monitoring different environmental conditions or metabolic states [44,45]. Of these TFs, CueR, MntR, NhaR, and ZntR bind when metal ions such as Cu2+, Mn2+, Na+, and Zn2+ are present at high concentrations in the cell. In contrast, KdpE, PhoP, and ZraR are phosphorylated by response regulators and bind to promoter regions when K+, Mg2+, and Zn2+ are present at low concentrations in the cell. Thus, high and low concentrations of specific metal ions may be implicated in the repression of Rsd and RMF proteins. These facts indicate that inadequate concentrations of these metal ions reduce transcriptional and translational activity and suppress cellular activity. Additionally, the deletion of the fur gene did not alter the expression levels of Rsd and YqjD but reduced RMF expression and 100S ribosome formation. Therefore, this finding indicates that the formation of 100S ribosomes is inhibited in the absence of Fe2+. Since iron ions are essential for many processes, such as DNA synthesis and respiration [21,26], bacteria in the iron-ion-deficient condition may not have the margin of forming 100S ribosomes for long-term survival. A similar trend was observed in previous studies with ArcA [7], a transcription factor involved in redox regulation under anoxic conditions. ArcA has been reported to be involved in iron transport by Fur under anaerobic conditions [46], suggesting that the regulation of iron homeostasis is closely linked to the regulation of translational activity. Previous studies have shown that TFs involved in biofilm formation bind to the promoter regions of rsd and rmf in response to nutrient depletion and other factors, promoting the expression of these genes [7]. In this study, we demonstrated that the expression of rsd and rmf is suppressed by metal-responsive TFs when the intracellular metal ion concentration is not appropriately balanced. Thus, the expression of rsd and rmf is regulated positively or negatively in response to various environmental changes for the long-term survival of bacteria such as E. coli. E. coli strains from the ASKA clone library [47] of the E. coli Stock Center (National Bio-Resource Center, Shizuoka, Japan) were used for TF production. For TF overexpression, E. coli cells were grown in Luria–Bertani (LB) broth at 37 °C with shaking. Mutant strains with one of the TF genes deleted were obtained from the Keio collection [48] of the E. coli Stock Center (National Bio-Resource Center, Shizuoka, Japan.) Mutant cells were grown at 37 °C with shaking at 160 rpm in medium E containing 2% polypeptone and 0.5% glucose [49] under aerobic conditions. Medium E contains MgSO4, citric acid, K2HPO4, and NaNH4HPO4, in which E. coli cells can efficiently form 100S ribosomes under stress conditions. Cell growth was monitored by measuring turbidity at 600 nm using an OD-Monitor (TAITEC, Saitama, Japan). Thirteen TFs were prepared for in vitro assays. E. coli cells carrying each of the TF expression plasmids were grown in LB broth medium up to an OD600 of 0.6; after that, 1 mM isopropyl-beta-D-thiogalactopyranoside was added to induce TF expression. The cells were then harvested, suspended in a lysis buffer, and disrupted by sonication. After DNase I treatment, the cell lysates were incubated on ice for 3 h to digest genomic DNA and centrifuged to remove cell debris at 12,000 rpm (13,000× g) for 10 min at 4 °C. The cell lysates were passed through a HisTrap FF column (Cytiva, Tokyo, Japan) on an AKTA Prime system (Cytiva, Tokyo, Japan) pre-equilibrated with 20 mM PBS (pH 7.2), and the column was washed with the same buffer to remove unabsorbed proteins. The absorbed proteins were eluted with a linear gradient of 500 mM imidazole, from 0% to 100%, in 20 mM PBS (pH 7.2). The purity of each peak was determined using SDS-PAGE. The concentration of individual proteins was determined using the Protein Assay Rapid Kit (Wako Pure Chemical Industries, Osaka, Japan). FITC-labeled DNA probes were prepared by PCR amplification of the rsd (300 bp) and rmf (256 bp) promoter regions [7]. A 193 bp-long FITC-labeled probe, which is part of the open reading frame sequence of the rtcA gene, was prepared as a reference probe that is not expected to bind TFs. FITC emits fluorescence at approximately 520 nm upon excitation with light at approximately 495 nm. The fluorescence intensity was measured using a Typhoon FLA 9000 laser scanner (Cytiva, Tokyo, Japan). A PS-TF screening system was employed to detect TFs with rsd and rmf promoter-binding activity [50]. The DNA probes (0.5 pmol) were mixed with each purified TF (20 pmol). After incubation at 37 °C for 20 min, the mixture was subjected to PAGE to detect DNA–protein complexes. The gels were analyzed using a Typhoon FLA 9000 laser scanner. Binding of the DNA probe to the TF was detected using magnetic beads (MagneHis Ni particle; Promega, Madison, WI, USA) for purification of His-tagged proteins (Figure 2). First, 30 µL of magnetic beads, 5 pmol of DNA probe, and 200 pmol of His-tagged TF were added to a total volume of 40 µL MagneHis Binding buffer, mixed well in a 1.5 mL tube (Figure 2A), and incubated at room temperature (20–24 °C) for 2 min (Figure 2B). The final concentrations of added effectors were as follows: 10 mM of AcP (for Dan, CusR, KdpE, PhoP, and ZraR), 0.5 mM of CuSO4 (for CueR), 0.025 mM of FeSO4 (for Fur), 0.2 mM of MnCl2 (for MntR), 100 mM of NaCl (for NhaR), and 0.5 mM of ZnSO4 (for ZntR and Zur). Notably, a DNA probe with an affinity for a TF could bind to the His-tagged TF-bound magnetic beads. Then, a magnet was used to attract and collect the magnetic beads (Figure 2C). The supernatant was carefully removed using a pipette, and the tube was removed from the magnetic stand. After that, 150 µL of MagneHis Wash Buffer was added to the tube and mixed well through pipetting. The tube was set on a magnetic stand for approximately 30 s to capture the magnetic beads, and the supernatant was removed using a pipette. This washing process was repeated twice for a total of three washes (Figure 2D). After the final wash, the tube was removed from the magnetic stand, and 100 µL of MagneHis Elution Buffer containing 500 mM of imidazole was added and mixed in well through pipetting. After incubation at room temperature (20–24 °C) for 1–2 min, the tube was again placed on a magnetic stand to capture the magnetic beads, and the supernatant containing the free DNA probe was removed using a pipette (Figure 2D). Finally, 100 µL of the eluate was transferred to a well on a plate, and fluorescence was analyzed using a Typhoon FLA 9000 laser scanner (Figure 2E). Total RNA was extracted from E. coli cells using NucleoSpin RNA Plus (Macherey-Nagel, Düren, Germany). cDNA was synthesized using the PrimeScript RT Reagent Kit (TaKaRa Bio Inc., Kusatsu, Japan). PCR assays were conducted in a Mic Real-Time PCR Cycler (Bio Molecular Systems, Upper Coomera, Australia) using SYBR Premix Ex Taq 2 (TaKaRa Bio Inc., Kusatsu, Japan). The number of PCR cycles required to obtain DNA within the linear amplification range from the amplification curve was determined. The copy numbers of the samples were obtained after quantitative amplification of the target gene. The threshold cycle (CT) values of the sample DNAs were normalized to the reference CT values obtained using the values of 16S rRNA. The relative quantity of each target mRNA was obtained using the 2−ΔΔCT method. Harvested E. coli cells were treated with lysozyme, and whole-cell extracts were prepared by sonication. Total cell proteins were fractionated using Tricine-SDS-PAGE on 15% gels [51] and transferred onto polyvinylidene difluoride (PVDF) membranes (Immobilon-FL transfer membrane; Merck, Darmstadt, Germany). The proteins Rsd, RMF, YqjD, RpoA, and RplB were detected on the membranes using rabbit polyclonal antibodies against Rsd, RMF, YqjD, RpoA, and RplB, respectively. Immunostained membranes with ECL substrate (Cytiva, Tokyo, Japan) were scanned using ImageQuant LAS 500 (Cytiva, Tokyo, Japan). The density of each band on the membranes was quantified using ImageJ software (https://imagej.nih.gov/ij/index.html (accessed on 24 August 2022)). The linearity of the quantification was confirmed through several experiments with different amounts of sample solution loaded on an electrophoresis gel. E. coli was grown in medium E, containing 2% polypeptone and 0.5% glucose. The pellets of E. coli cells harvested 24 h after inoculation were suspended in an association buffer (100 mM NH4 acetate, 15 mM magnesium acetate, 20 mM Tris-HCl [pH 7.6], and 6 mM 2-mercaptoethanol) and mixed with an equal volume of glass beads (212–300 µm; Merck, Darmstadt, Germany). The homogenate was centrifuged at 15,000 rpm for 10 min at 4 °C. The supernatant was layered on top of a 5–20% linear sucrose density gradient prepared in the association buffer and centrifuged in an SW41 Ti rotor (Beckman Coulter, Brea, CA, USA) at 41,000 rpm (288,000× g) for 2 h at 4 °C. After centrifugation, the absorbance of the sucrose gradient was measured at 260 nm using a UV-1800 spectrophotometer (Shimadzu, Kyoto, Japan), and the ribosome profile was drawn using UV-Prove software (Shimadzu, Kyoto, Japan). The ratio between 70S and 100S ribosomes was calculated for each peak using PeakFit software (Systat Software, Chicago, IL, USA) for peak separation analysis. We have demonstrated that the metal-responsive TFs CueR, Fur, KdpE, MntR, NhaR, PhoP, ZntR, and ZraR are involved in the expression of rsd and rmf genes. These genes regulate transcription and translation under stressful environments caused by imbalanced metal ion concentrations. Expression of Rsd and RMF is suppressed at high concentrations of Cu2+, Mn2+, Na+, and Zn2+ and low concentrations of K+, Mg2+, and Zn2+. Furthermore, since rmf gene expression is reduced by the deletion of fur gene, we believe that the formation of 100S ribosome is inhibited in the absence of Fe2+. These results are important for understanding bacterial survival strategies under stress conditions and provide new insights into countermeasures for diseases in which stress tolerance is an issue. However, other TFs besides those addressed in this study may also be involved in the expression of rsd and rmf genes [7]. Thus, further elucidation of these additional TFs is needed to obtain a complete picture of bacterial survival strategies.

PMC10003397

Áron Bartha,Zsuzsanna Darula,Gyöngyi Munkácsy,Éva Klement,Péter Nyirády,Balázs Győrffy

Proteotranscriptomic Discrimination of Tumor and Normal Tissues in Renal Cell Carcinoma

24-02-2023

kidney cancer,proteomics,biomarker,diagnostics,mass spectrometry

Clear cell renal carcinoma is the most frequent type of kidney cancer, with an increasing incidence rate worldwide. In this research, we used a proteotranscriptomic approach to differentiate normal and tumor tissues in clear cell renal cell carcinoma (ccRCC). Using transcriptomic data of patients with malignant and paired normal tissue samples from gene array cohorts, we identified the top genes over-expressed in ccRCC. We collected surgically resected ccRCC specimens to further investigate the transcriptomic results on the proteome level. The differential protein abundance was evaluated using targeted mass spectrometry (MS). We assembled a database of 558 renal tissue samples from NCBI GEO and used these to uncover the top genes with higher expression in ccRCC. For protein level analysis 162 malignant and normal kidney tissue samples were acquired. The most consistently upregulated genes were IGFBP3, PLIN2, PLOD2, PFKP, VEGFA, and CCND1 (p < 10−5 for each gene). Mass spectrometry further validated the differential protein abundance of these genes (IGFBP3, p = 7.53 × 10−18; PLIN2, p = 3.9 × 10−39; PLOD2, p = 6.51 × 10−36; PFKP, p = 1.01 × 10−47; VEGFA, p = 1.40 × 10−22; CCND1, p = 1.04 × 10−24). We also identified those proteins which correlate with overall survival. Finally, a support vector machine-based classification algorithm using the protein-level data was set up. We used transcriptomic and proteomic data to identify a minimal panel of proteins highly specific for clear cell renal carcinoma tissues. The introduced gene panel could be used as a promising tool in the clinical setting.

Proteotranscriptomic Discrimination of Tumor and Normal Tissues in Renal Cell Carcinoma Clear cell renal carcinoma is the most frequent type of kidney cancer, with an increasing incidence rate worldwide. In this research, we used a proteotranscriptomic approach to differentiate normal and tumor tissues in clear cell renal cell carcinoma (ccRCC). Using transcriptomic data of patients with malignant and paired normal tissue samples from gene array cohorts, we identified the top genes over-expressed in ccRCC. We collected surgically resected ccRCC specimens to further investigate the transcriptomic results on the proteome level. The differential protein abundance was evaluated using targeted mass spectrometry (MS). We assembled a database of 558 renal tissue samples from NCBI GEO and used these to uncover the top genes with higher expression in ccRCC. For protein level analysis 162 malignant and normal kidney tissue samples were acquired. The most consistently upregulated genes were IGFBP3, PLIN2, PLOD2, PFKP, VEGFA, and CCND1 (p < 10−5 for each gene). Mass spectrometry further validated the differential protein abundance of these genes (IGFBP3, p = 7.53 × 10−18; PLIN2, p = 3.9 × 10−39; PLOD2, p = 6.51 × 10−36; PFKP, p = 1.01 × 10−47; VEGFA, p = 1.40 × 10−22; CCND1, p = 1.04 × 10−24). We also identified those proteins which correlate with overall survival. Finally, a support vector machine-based classification algorithm using the protein-level data was set up. We used transcriptomic and proteomic data to identify a minimal panel of proteins highly specific for clear cell renal carcinoma tissues. The introduced gene panel could be used as a promising tool in the clinical setting. Clear cell renal carcinoma (ccRCC) is the malignant transformation of epithelial cells of the kidney and is the most frequent form of kidney tumors with approx. 70% of all kidney cancer cases [1]. In 2020, there were 431,288 new cases and 179,368 deaths from kidney and renal pelvis cancer worldwide [2]. Although the rate of new cases seems to rise, in the past decades, the mortality rates are stagnating in the US [3]. Risk factors of ccRCC include obesity, smoking, hypertension, older age, and male gender. Patients with a family history of ccRCC also have a higher risk of developing this disease [4]. Diagnosis of ccRCC is usually based on radiological imaging and tissue slide-based histopathological examination. Histopathological confirmation is essential before systematic therapy initiation. [4] Treatment of ccRCC can include surgery, percutaneous ablation [5], and targeted drugs including VEGF inhibitors [6] and mTOR inhibitors [7]. In the case of localized disease, surgical intervention is the first-line therapy, and depending on the size and stage, the intervention can range from partial to radical nephrectomy. If the tumor mass is relatively small, ablative techniques (such as cryo-, thermo-, or radio-ablation) are also available [5]. Patients with early-stage and lack of distant metastasis have more favorable survival rates than those with advanced disease [8]. Patients with advanced disease (stage IV) also require systemic therapy using mTOR inhibitors, VEGF inhibitors, or checkpoint inhibitors such as nivolumab, avelumab, pembrolizumab, ipilimumab, and interleukin 2 therapy [9]. MS was introduced almost half a century ago in endocrinology and toxicology for drug, steroid, and organic acid quantitation and got its main medical application in the widespread newborn screening [10,11]. Although the setup of MS-based diagnostic applications can be costly and complicated at the beginning, their versatility and reliability lead to new applications in clinical settings. In recent years, MS has been proven to be a comparatively cost-effective, precise, and quick analysis tool in microbial identification [12]. With the advent of proteomics and proteogenomics, MS-based techniques have an increasing role in cancer diagnostics, as well [13]. Uncovering a protein abundance-based panel specific to ccRCC could provide valuable support for the everyday clinical diagnostic and therapeutic decision-making process. Our study aimed to utilize large-scale transcriptomic studies to find genes showing higher expression in ccRCC. Then, by using our patient cohort with available proteomic and clinical data, we investigated the abundance of expressed proteins and the effect of these proteins on survival. By specifically focusing on markers with higher expression in tumor tissues, we aim to increase the specificity of our analysis to solidify future clinical application of the results. Altogether, we included 23 GEO series which contained 715 samples. Out of these 715 samples, 277 were from normal kidney tissues, and 438 were from ccRCC. Out of the entire gene array database, 414 samples were paired samples (207 pairs), and we used the paired specimens for the identification of differentially expressed genes. The entire analysis pipeline is summarized in Figure 1. Patient characteristics are listed in Table 1. We uncovered significantly differentially expressed genes between paired ccRCC and adjacent normal tissues. IGFBP3 was found to be the most upregulated gene in tumor tissues (FC gene chip = 8.15, p = 5.88 × 10−32). The most significant genes include previously established molecular targets like VEGFA (FC gene chip = 3.02 p = 5.1 × 10−31) and CCND1 (FC gene chip = 4.12, p = 4.1 × 10−31). PLIN2 and PLOD2 also showed notable gene expression differences with FC values of 3.85 and 4.2 and adjusted p values of 3.09 × 10−31 and 5.24 × 10−32, respectively. The top differentially expressed genes are shown in Figure 2 and listed in detail in Supplementary Table S2. Proteomic analysis was performed using 162 normal and malignant tissue samples. Of the complete list of the 31 selected genes from gene chip results, we were able to successfully measure 22 in the targeted LC-MS/MS. Top differentially expressed genes include PLIN2 (FC = 26.01, p = 3.9 × 10−39), PLOD2 (FC = 15.83, p = 6.51 × 10−36), PFKP (FC = 12.78, p = 1.01 × 10−47), IGFBP3 (FC = 3.04, p = 7.53 × 10−18), CCND1(FC = 7.9, p = 1.04 × 10−24) and VEGFA (FC = 3.5, p = 1.4 × 10−22) shown in Figure 3. Differential analysis between male and female patients resulted in no significant differences. Regression analysis of age and protein expression showed a significant result only in the case of IGFBP2, however, the adjusted R-squared value was 0.064. Thus, we can conclude that neither age nor gender can be considered as a covariate factor. Further results are provided in the Supplementary Table S4. Using the clusterProfiler R package, we performed an enrichment analysis; mostly enriched GO terms are connected to migration and adhesion. Results of the enrichment analysis are presented in Figure 4 and Supplemental Figure S1. Detailed results of the protein expression changes are also presented in Table 2. Intensities of the 22 best protein-specific peptides are presented in Supplemental Figure S2. To estimate the potential effects of protein expression on patient survival, we performed a survival analysis using all available proteins. Five out of the investigated proteins showed a correlation with survival. Patients with elevated expression of PLOD2 protein showed significantly worse overall survival compared to subjects with lower expression (p = 2.42 × 10−7, HR = 5.03). Overexpression of further proteins such as TIMP1 (p < 3 × 10−2, HR = 4.71), VIM (p < 3 × 10−2, HR = 2.49), LGALS1 (p < 3 × 10−2, HR = 2.47), and P4HA1 p < 3 × 10−2, HR = 2.6) also showed significant correlation with impaired overall survival. Kaplan–Meier curves of the best-performing proteins are shown in Figure 5; further results of survival analysis are presented in Supplemental Table S3 and as supplementary figures To further support our analysis, we validated our results using CPTAC data from the study of Clark et al. [14]. Out of the 22 proteins identified by our current study, 21 were also available in the CPTAC dataset. The FC values between the two MS analyses had comparable results. Correlation analysis of the log2FC values of the CPTAC and SE cohorts resulted in a significant correlation (R = 0.91, p = 3.7 × 10−9, Figure 6). Top proteins identified, such as PLIN2 (FC = 6.92, p = 1.7 × 10−33), PLOD2 (FC = 4.89, p = 7.4 × 10−33), PFKP (FC = 4.2, p = 4.3 × 10−56), IGFBP3 (FC = 2.28, p = 2.1 × 10−31), and VEGFA (FC = 3.12, p = 3 × 10−32), had significant differences between normal kidney and ccRCC in the CPTAC study. Further results are displayed in Table 3. MS-based protein abundance data of the investigated proteins in the 162 patient samples were used for establishing the most robust classification algorithm. We investigated multiple machine learning methods (including k-nearest neighbors, random forest, logistic regression, and support vector machines) to build a model which can differentiate between normal and malignant kidney tissues. For the proper estimation of the optimal gene panel, we performed recursive feature elimination. Of the four methods, SVM delivered the best performance in both test and training cohorts using nine proteins as input. SVM was able to identify tumor tissues from MS quantification data with a classification accuracy of 0.98 in the test set (Kappa = 0.95, sensitivity = 0.95, specificity = 1). Results of all four methods (SVM, k-nearest neighbors, random forest, and logistic regression) in both training and test sets are displayed in Table 4; the list of optimal genes is provided in Table 5, and the accuracy of each method with different gene panels is presented in Supplemental Figure S3. Current clinical diagnostics of cancer rely mainly on pathological examination using tissue slide staining or immune histochemistry. The importance of tissue inspection is undoubted. However, with the increasing burden of workload in pathological diagnostics, the need for further potent diagnostic possibilities and tools capable to provide sufficient pathological decision support is necessary. While transcriptome-based methods are useful for this purpose, several studies with promising results were published recently in the proteome field as well. Establishing proteins with differential abundance in malignant samples compared to healthy tissues can provide valuable information in diagnostics and therapeutic target identification. For example, a breast cancer study comparing malignant breast cancer samples to adjacent normal samples using MS identified a novel luminal subtype [15]. A comparison of normal prostate and prostate adenocarcinoma samples was performed to identify a new prognostic biomarker [16]. Like other cancer types, early surgical intervention is the best solution for total recovery in ccRCC as well. Especially in the early stages, when the disease is localized, partial or radical nephrectomy is the most frequently performed treatment option [5]. In the present study, by using transcriptomic data, we uncovered genes with higher expression in ccRCC, and we then developed an algorithm capable of identifying ccRCC tissues with accuracy high enough for future clinical application. We focused on genes having higher expression in the tumor tissues. By using targeted MS data of the selected proteins, our algorithm can differentiate between normal and malignant tissues and could provide valuable decision support during the pathological diagnostic process. The final discriminative algorithm is based on the differential expression of nine proteins. Of these, VEGFA and CCND1 are well-known cancer biomarkers. VEGFA (vascular endothelial growth factor A) is used as a target molecule in ccRCC treatment [6]. CCND1 (cyclin D1), a member of the cyclin family, acts as a regulator of cyclin-dependent kinases (CDKs). CDK inhibitors are widely used in the treatment of breast cancer [17]. PLOD2 (procollagen-lysin 2-oxoglutarate 5-dioxygenase) has a role in the maintenance of intermolecular collagen cross-links [18]. The aberrant function of PLOD2 might have a role in ovarian cancer [18] and gastric cancer progression [19]. PFKP (phosphofructokinase platelet isoform) is responsible for one of the early steps of glycolysis [20]. It might also have a crucial part in metabolic reprogramming in multiple cancer types like breast cancer [21] and non-small cell lung cancer [22]. IGFBP3 (insulin-like growth factor binding protein 3) acts as a carrier protein of several types of IGF molecules, and it is related to cell growth and differentiation [23]. IGFBP3 has been shown to be important in the development of colorectal and breast cancer [23,24]. PLIN2 (perilipin 2) is a member of the perilipin family and takes part in the formation of intracellular lipid storage droplets in multiple tissue types [25]. It has been connected to the development of atherosclerosis [26] but it has relevance in cancer initiation and progression as well [25]. Using Western blot technique, an earlier study has proposed PLIN2 as a potential plasma biomarker in ccRCC [27]. As both IGFP3 and PLIN2 can be detected in the plasma, we hypothesize that they could also serve as potential diagnostic biomarkers of ccRCC. Using our current knowledge, however, we lack any robust evidence for our hypothesis. By survival analysis, we identified five proteins with a high expression which correlates with poor survival outcomes. Out of these five, PLOD2, VIM, and P4HA1 are also highlighted by our model. Both PLOD2 and P4HA1 are enzymes involved in collagen-related pathways and proved to be a biomarker of epithelial-to-mesenchymal transition (EMT) in multiple types of cancers [28,29]. While vimentin acts as an important structural protein and a known marker of EMT, overexpression of these proteins in patients with poor survival outcomes implies their involvement in EMT and metastasis formation in renal cell clear carcinoma. We must note an important limitation of our approach. Although transcriptome-based examinations can provide valuable input of new potential biomarkers, due to mechanisms like alternative splicing, mutations, and post-translational modifications, RNA expression only moderately correlates with protein expression [30]. A further limitation of our model is the incapability of tumor stage estimation, as staging is usually based on imaging, pathological examination, and further clinical characteristics. In conclusion, we used a database of renal samples of paired normal and tumor tissues to identify biomarkers differentiating renal clear cell cancer (ccRCC) and normal kidney tissues. With a support vector machine-based machine learning algorithm using nine genes, we set up a model which can differentiate between normal and malignant ccRCC tissues using proteomic data. Finally, a set of proteins showed a significant correlation with poor survival outcomes and might serve as potential biomarkers of progression. To set up the gene chip cohort, we searched the NCBI GEO repository (https://www.ncbi.nlm.nih.gov/geo/, accessed on 21 January 2021) for potential ccRCC and normal specimens using keywords “ccRCC” AND “normal” OR “GPL570” OR “GPL571” OR “GPL96”. Only those datasets involved contained normal tissues adjacent to tumors from HGU133, HGU133A_2, and HGU133A platforms. We filtered the datasets to exclude xenograft experiments, pooled samples, and cell line studies. Samples with insufficient description, nonexistent raw data, and repeatedly published data with distinct identifiers have been removed. To achieve this, the expression of the first twenty genes was determined, and samples with identical values were identified. In each case, the first published version was retained in the dataset. After the manual selection, the remaining samples were normalized using the MAS5 algorithm by utilizing the Affy Bioconductor library [31]. Finally, a second scaling normalization was executed to set the mean expression on each array to 1000. JetSet correction and annotation package was used to pick the proper probe set for each gene [32]. Data processing and analysis were performed in R version 4.1.0 (https://www.r-project.org, accessed on 6 June 2021). Wilcoxon test was used to compare the tumorous and adjacent normal samples. Genes showing significant differences according to the Wilcoxon test (p < 0.01) have been selected and ranked based on their fold-change values (FC). The Benjamini–Hochberg method was used for p-value adjustment. Finally, the top 31 genes with an FC over two were selected for further investigation. ccRCC samples were collected at the Department of Urology of the Semmelweis University. An institutional ethical review board approved the study under the number ID 7852-5/2014/EKU by Semmelweis University Regional and Institutional Committee of Science and Research Ethics. All subjects were treated under the tenets of the Declaration of Helsinki and written informed consents were obtained before sample collection. Clear cell renal carcinoma and adjacent normal samples were collected during surgical resection, and the tissue samples were stored immediately at −80 °C. Protein isolation was performed using the AllPrep DNA/RNA/Protein Mini Kit by the manufacturer’s protocol using 30 mg of tissue samples. The expression of selected target proteins was verified by targeted LC/MS-MS. After isolation, protein samples were stored in guanidine isothiocyanate and stored at −80 °C. For targeted quantification, we used stable isotope labeled (SIL) peptides (1–5 respectively for each protein, labeled at Arg:13C6;15N4, Lys:13C6;15N2); the peptide sequences of the 75 SIL peptides are listed in Supplementary Table S1. Protein concentration was determined by the bicinchoninic acid (BCA) test. Samples were reduced by dithiothreitol (DTT) and alkylated using iodoacetamide followed by protein precipitation; then, samples were re-dissolved in 5% SDS/50 mM ammonium-bicarbonate for the BCA test. Sample volumes representing 50 μg protein content were digested by trypsin according to the S-trap protocol (https://files.protifi.com/protocols/s-trap-mini-long-4-1.pdf, accessed on 9 January 2023). LC-MS/MS analysis was performed using an ACQUITY UPLC M-Class system (Waters, Milford, MA, USA) with HPLC coupled to an Orbitrap Fusion Lumos Tribrid (Thermo Fisher Scientific, Waltham, MA, USA) mass spectrometer on the mixture of the protein digests spiked with the mixture of the SIL peptides. Samples were loaded onto a trap column, ACQUITY UPLC M-Class Symmetry C18 Trap (100 Å, 5 µm, 180 µm × 20 mm, 2G, V/M); the sample loading time was 5 min; the flow rate was 5 µL/min, and separation was performed on an ACQUITY UPLC M-Class Peptide BEH C18 (130 Å, 1.7 µm, 75 µm × 250 mm) column with a flow rate of 400 nL/min. MS data acquisition was performed in an internal standard triggered parallel reaction monitoring fashion [33], where the presence of the corresponding SIL peptides, verified by their expected retention time and MS2 fragmentation pattern, triggers data acquisition of the targeted peptides with high sensitivity and resolution. MS signal intensities of the SIL peptides were between 1–5 × 107. Raw MS data were analyzed using the Skyline software and the MSstats statistical analysis tool. During the data processing steps, we performed the inbuilt normalization steps of the MSstats software package, which includes median polishing and log2 transformation. T-test was used to compare the log2 transformed protein intensity values between the tumorous and adjacent normal samples. In order to examine if any of the gene candidates are affected by covariates, we performed a t-test to see if any of the proteins show differential expression between male and female patients. To examine age as a covariate factor, we performed regression analysis to see if any of the examined proteins are influenced by age. Functional analysis was performed using the clusterProfiler R package [34]. For each protein, we performed Cox proportional hazard regression analysis. To estimate the best cutoff value for each protein, we examined each possible cutoff values between the lower and the upper quartiles; these cutoff values have been used for Kaplan–Meier plot visualization. The Benjamini–Hochberg method was used for p-value adjustment. For survival analysis, we used the survminer and survival R packages. Further visualization has been done using the R packages ggplot2 [35], ComplexHeatmap [36], and ggrepel (https://cran.r-project.org/web/packages/ggrepel/index.html, accessed on 13 December 2022). Using the results of the targeted LC/MS-MS log2 intensity values, we tried four supervised AI methods, k-nearest neighbors (KNN), random forest (RF), logistic regression (LOGIT), and support vector machines (SVM), to set up the most accurate model for cancer detection. The data matrix from MS data was the input for the classification model, and we used the “caret” R package for data preparation and model establishment [37,38]. From all available patients with MS data, we had to remove one patient due to a missing value. The entire cohort was split into training and test cohorts with a ratio of 0.7:0.3. Repeated K-fold cross-validation was used for training cohort resampling with 10 folds and 5 repeats. Within the resampling mechanism, we performed recursive feature elimination to specify the ideal number of used genes for each of the SVM, KNN, LOGIT, and RF algorithms. Model prediction capability was validated using the test set. The caret package’s built-in methods were used to determine accuracy, specificity, sensitivity, and kappa value, as well as for visualization.

PMC10003398

Cristina-Ilinca Cira,Mara Carsote,Claudiu Nistor,Aida Petca,Razvan-Cosmin Petca,Florica Sandru

Conundrum for Psoriasis and Thyroid Involvement

03-03-2023

psoriasis,thyroid,thyroiditis,autoimmune,antibodies,Hashimoto’s thyroiditis,Basedow disease,thyroid cancer,pathogenic

Strategies concerning thyroid anomalies in patients confirmed with psoriasis, either on clinical level or molecular levels, and their genetic findings remain an open issue. Identification of the exact subgroup of individuals that are candidates to endocrine assessments is also controversial. Our purpose in this work was to overview clinical and pathogenic data concerning psoriasis and thyroid comorbidities from a dual perspective (dermatologic and endocrine). This was a narrative review of English literature between January 2016 and January 2023. We included clinically relevant, original articles with different levels of statistical evidence published on PubMed. We followed four clusters of conditions: thyroid dysfunction, autoimmunity, thyroid cancer, and subacute thyroiditis. A new piece of information in this field was the fact that psoriasis and autoimmune thyroid diseases (ATD) have been shown to be related to the immune-based side effects of modern anticancer drugs—namely, immune checkpoint inhibitors (ICP). Overall, we identified 16 confirmatory studies, but with heterogeneous data. Psoriatic arthritis had a higher risk of positive antithyroperoxidase antibodies (TPOAb) (25%) compared to cutaneous psoriasis or control. There was an increased risk of thyroid dysfunction versus control, and hypothyroidism was the most frequent type of dysfunction (subclinical rather than clinical), among thyroid anomalies correlated with >2-year disease duration, peripheral > axial and polyarticular involvement. With a few exceptions, there was a female predominance. Hormonal imbalance included, most frequently, low thyroxine (T4) and/or triiodothyronine (T3) with normal thyroid stimulating hormone (TSH), followed by high TSH (only one study had higher total T3). The highest ratio of thyroid involvement concerning dermatologic subtypes was 59% for erythrodermic psoriasis. Most studies found no correlation between thyroid anomalies and psoriasis severity. Statistically significant odds ratios were as follows: hypothyroidism: 1.34–1.38; hyperthyroidism: 1.17–1.32 (fewer studies than hypo); ATD: 1.42–2.05; Hashimoto’s thyroiditis (HT): 1.47–2.09; Graves’ disease: 1.26–1.38 (fewer studies than HT). A total of 8 studies had inconsistent or no correlations, while the lowest rate of thyroid involvement was 8% (uncontrolled studies). Other data included 3 studies on patients with ATD looking for psoriasis, as well as 1 study on psoriasis and thyroid cancer. ICP was shown to potentially exacerbate prior ATD and psoriasis or to induce them both de novo (5 studies). At the case report level, data showed subacute thyroiditis due to biological medication (ustekinumab, adalimumab, infliximab). Thyroid involvement in patients with psoriasis thus remained puzzling. We observed significant data that confirmed a higher risk of identifying positive antibodies and/or thyroid dysfunction, especially hypothyroidism, in these subjects. Awareness will be necessary to improve overall outcomes. The exact profile of individuals diagnosed with psoriasis who should be screened by the endocrinology team is still a matter of debate, in terms of dermatological subtype, disease duration, activity, and other synchronous (especially autoimmune) conditions.

Conundrum for Psoriasis and Thyroid Involvement Strategies concerning thyroid anomalies in patients confirmed with psoriasis, either on clinical level or molecular levels, and their genetic findings remain an open issue. Identification of the exact subgroup of individuals that are candidates to endocrine assessments is also controversial. Our purpose in this work was to overview clinical and pathogenic data concerning psoriasis and thyroid comorbidities from a dual perspective (dermatologic and endocrine). This was a narrative review of English literature between January 2016 and January 2023. We included clinically relevant, original articles with different levels of statistical evidence published on PubMed. We followed four clusters of conditions: thyroid dysfunction, autoimmunity, thyroid cancer, and subacute thyroiditis. A new piece of information in this field was the fact that psoriasis and autoimmune thyroid diseases (ATD) have been shown to be related to the immune-based side effects of modern anticancer drugs—namely, immune checkpoint inhibitors (ICP). Overall, we identified 16 confirmatory studies, but with heterogeneous data. Psoriatic arthritis had a higher risk of positive antithyroperoxidase antibodies (TPOAb) (25%) compared to cutaneous psoriasis or control. There was an increased risk of thyroid dysfunction versus control, and hypothyroidism was the most frequent type of dysfunction (subclinical rather than clinical), among thyroid anomalies correlated with >2-year disease duration, peripheral > axial and polyarticular involvement. With a few exceptions, there was a female predominance. Hormonal imbalance included, most frequently, low thyroxine (T4) and/or triiodothyronine (T3) with normal thyroid stimulating hormone (TSH), followed by high TSH (only one study had higher total T3). The highest ratio of thyroid involvement concerning dermatologic subtypes was 59% for erythrodermic psoriasis. Most studies found no correlation between thyroid anomalies and psoriasis severity. Statistically significant odds ratios were as follows: hypothyroidism: 1.34–1.38; hyperthyroidism: 1.17–1.32 (fewer studies than hypo); ATD: 1.42–2.05; Hashimoto’s thyroiditis (HT): 1.47–2.09; Graves’ disease: 1.26–1.38 (fewer studies than HT). A total of 8 studies had inconsistent or no correlations, while the lowest rate of thyroid involvement was 8% (uncontrolled studies). Other data included 3 studies on patients with ATD looking for psoriasis, as well as 1 study on psoriasis and thyroid cancer. ICP was shown to potentially exacerbate prior ATD and psoriasis or to induce them both de novo (5 studies). At the case report level, data showed subacute thyroiditis due to biological medication (ustekinumab, adalimumab, infliximab). Thyroid involvement in patients with psoriasis thus remained puzzling. We observed significant data that confirmed a higher risk of identifying positive antibodies and/or thyroid dysfunction, especially hypothyroidism, in these subjects. Awareness will be necessary to improve overall outcomes. The exact profile of individuals diagnosed with psoriasis who should be screened by the endocrinology team is still a matter of debate, in terms of dermatological subtype, disease duration, activity, and other synchronous (especially autoimmune) conditions. Psoriasis, a complex chronic autoimmune multisystem disease with skin as its dominant manifestation, affects between 1% and 8% of adults worldwide [1,2]. While genetic predisposition is important, environmental factors, comorbidities and behavioral elements also matter [3]. The disorder has five major subtypes—plaque, inverse, guttate, pustular (PP) and erythrodermic (EP)—with the most frequent being chronic plaque psoriasis. This latter is characterized by erythematous, well-demarcated, indurated plaques with white-silvery thick scales. These can be either asymptomatic or pruritic, and typically involve the extensor surfaces, gluteal, and sacral areas. Additionally, specific sites may impose a higher burden on the quality of life of patients, such as palmo-plantar surfaces, the scalp, facial area, and the nail apparatus [4,5,6]. Psoriatic arthritis (PsA), an inflammatory polymorphic arthritis, occurs in up to 20–30% of individuals diagnosed with psoriasis. The majority of cases are identified after (or concurrently with) psoriasis vulgaris (PV). In about half of patients, PsA progresses to a destructive erosive disease with associated functional impairment [3,5,6,7]. Modern approaches to the treatment of psoriasis vary from molecular studies (to better understand pathogenic insights) to complex management in association with comorbidities’ assessment to seek better outcomes [6,8]. Pathogenic mechanisms involve a dysregulation of the innate and adaptive immune systems, primarily a T helper 1 cell and T helper 17 cell/interleukin-23 (IL)-mediated immune response, which may also involve IFN-γ (interferon), TNF-α (tumor necrosis factor), IL-17A, IL-12, and IL-23 [6,9]. Triggers, such as infections or local trauma, lead stressed keratinocytes to release molecules. These may include fragments of self DNA, self RNA, and antimicrobial peptides such as cathelidicin LL37, which stimulates plasmacytoid dendritic cells [6,10]. These cells, through their secretion of IFN-α, activate myeloid dendritic cells which migrate to lymph nodes and present this still unknown antigen to naïve T lymphocytes [6]. The myeloid dendritic cells promote differentiation to T helper 1, T helper 17 and T helper 22 subsets via IL-12 and IL-23 secretion [6,11,12]. Subsequent inflammatory cascades lead to keratinocyte hyper-proliferation with abnormal keratinization, excessive angiogenesis, induction of endothelial adhesion molecules, and a cellular infiltrate comprised of macrophages, dendritic cells and IL-17 secreting cells. This creates a feedback loop between keratinocytes and the immune cells that sustain and promote psoriasis plaque formation [13,14]. Psoriasis is associated with various comorbidities, including insulin resistance, metabolic syndrome, cardiovascular diseases, gastrointestinal diseases, and mental health disorders, imposing a great impact on overall quality of life [15,16,17,18,19]. Furthermore, individuals seem to be at greater risk of developing different autoimmune disorders like Crohn’s disease, vitiligo, celiac disease, ulcerative colitis, rheumatoid arthritis, type 1 diabetes mellitus, respiratory diseases, and autoimmune thyroid diseases (ATD), in addition to any of these or a single comorbidity [15,16,17,18,19]. ATD, with an estimated prevalence of 5% in general population, leads to two autoimmune disorders, situated at the end of the same spectrum: (1) chronic autoimmune (lymphocytic) Hashimoto’s thyroiditis (HT), with a higher risk for hypothyroidism due (albeit not exclusively) to thyroid blocking antibodies, namely antithyroperoxidase antibodies (TPOAb) and antithyroglobulin antibodies (TgAb), respectively; (2) Graves’ disease (GD), or Basedow–Graves’ disease, caused by thyroid-stimulating immunoglobulin or thyroid-stimulating hormone (TSH) receptor antibodies (TRAb), the sole human antibody with stimulating effects [20,21,22,23]. ATD is related to a dysregulation of the immune system, with lymphocytic infiltration of the thyroid gland and associated increased production of autoantibodies. The exact pathogenesis remains an open issue, but both environmental factors (infections, withdrawal of glucocorticoid therapy, stress, etc.) and genetic factors (genes associated with human leukocyte antigen (HLA) system, AIRE gene, or encoding genes for selenoproteins, etc.) are potentially involved [24,25,26]. Our purpose was to overview clinical and pathogenic insights concerning psoriasis and thyroid comorbidities from a dual perspective (dermatologic and endocrine). This was a narrative review of literature published in English between January 2016 and January 2023. We included clinically relevant, original studies in humans, with different levels of statistical evidence, starting from two keywords used in PubMed research: “psoriasis” and “thyroid”. We identified 177 full-length papers and manually searched each of them in order to serve our purpose (Figure 1). Positive correlations between psoriasis (including the subgroup with PsA) and ATD and/or thyroid hormonal anomalies were identified in different studies, aiming to address the hormonal imbalance, the autoimmune background, or both. Of note, HT diagnostic is typically sustained based on positive serum antibodies, while associated thyroid functions may be hypothyroidic, thyrotoxic, or normal, depending on disease evolution and applied therapy. GD is usually associated with hyperthyroidism at first diagnosis, but the copresence of HT may induce hypo- or euthyroidism. Additionally, any thyroid dysfunction may be at the clinical or subclinical levels. Moreover, abnormal thyroid hormone levels might not necessarily be related to an autoimmune background [27]. Knowing these dynamic aspects, a cross-sectional analysis may not capture the evolutionary aspects and complex inter-relationships between these skin and endocrine disorders. The most important studies, having confirmatory profiles with regard to thyroid involvement, in patients known with psoriasis, according to our methodology, were as follows. First, a prospective study conducted by Vastarella et al. [28] analyzed the prevalence of HT in subjects confirmed with two types of psoriasis: PsA (N1 = 108) and cutaneous psoriasis (PsC) (N2 = 100). They showed that HT-associated subclinical hypothyroidism was more frequent in the PsA group and the ratio of positive TPOAb was increased in PsA versus PsC (13.9% versus 2%, p = 0.0018, respectively; 25.9 versus 9%, p = 0.018). Additionally, thyroid anomalies were more often found in subjects with PsA with established disease (≥2 years) than early disease (p < 0.05), and in those with peripheral involvement, when compared to axial PsA (85.7% versus 14.3%, p < 0.05). However, in PsC category, psoriasis severity was similar regardless of the copresence of ATD. A greater inflammatory state in patients with PsA, compared to patients without joint involvement, could possibly represent a factor with which to aid in identifying thyroid anomalies [29]. Another factor that could explain the different degrees of prevalence of HT was the female predominance in the PsA group, in contrast to the PsC group (52.7% versus 37%) [28]. Generally, women are prone to any type of ATD, with a 4 to 10 times higher risk than males [30]. In a prospective longitudinal study, Fallahi et al. [31] followed patients with PsA, without evidence of thyroid dysfunction (N = 97) versus control (N = 97), for 92 months. The PsA group developed TPOAb positivity (p < 0.014) and hypothyroidism (p < 0.05) (N = 97) more quickly than controls (N = 97), but this was not true of hyperthyroidism. PsA patients with subclinical hypothyroidism, compared to PsA individuals without any thyroid disorder, had a longer course of disease (18 ± 17 versus 9 ± 9 years; p = 0.005) and exhibited polyarticular involvement (p < 0.05). Logistic regression identified statistically significant risk factors for developing hypothyroidism in the PsA group, as follows: female gender, positive TPOAb, and a small thyroid volume at cervical ultrasound. No association was found between thyroid hormones and/or antibodies levels and PsA-associated disease activity/severity [31]. As previously shown by a Rotterdam study [32], a systematic review of 7 case-control studies and a meta-analysis of 4 studies confirmed a higher risk of ATDs in subjects with psoriasis [33]. The analysis revealed a link between psoriasis and thyroid hormones anomalies, as well (hypothyroidism (OR = 1.34; 95% CI 1.16–1.54)), and hyperthyroidism (OR = 1.17; 95% CI 1.03–1.32) [33]. A retrospective study by Du et al. [34] evaluated the relationship between different types of psoriasis and thyroid anomalies in 469 patients with PP, EP, PsA, and PV, versus 200 psoriasis-free controls (sex- and age-matched subjects). Individuals with EP had decreased levels of free triiodothyronine (T3) or free thyroxine (T4), with normal TSH (χ2 = 29.816, p < 0.001); patients with PP had decreased fT3 versus non-PP subtypes (p = 0.04); PsA patients had increased levels of TSH (p < 0.05). However, the levels of positive antibodies (TPOAb and TgAb) were similar between the studied subgroups and controls [34]. Another prospective study concerning different types of psoriasis included 63 patients with palmoplantar pustulosis and found a higher prevalence of thyroid disease in these individuals, compared to 34 subjects with PV (31.75% versus 13.51%; p = 0.0421) [35]. Another cross-sectional study on 102 persons suffering from palmoplantar pustulosis showed that comorbidities impacted the quality of life among them, with 16% suffering from ATD [36]. Another retrospective study by Namiki et al. [37] showed a higher rate of thyroid dysfunction in patients with generalized PP (GPP), when compared to PV and PsA (GPP versus PV, p = 0.0037; GPP versus PsA, p = 0.0348), with half of the thyroid anomalies being low T3 or T4 serum levels. The presence of thyroid dysfunction correlated with higher Psoriasis Area and Severity Index (PASI) scores of 21.0 ± 3.2 versus 13.5 ± 1.2 (Shapiro–Wilk test, p < 0.0001; respective Wilcoxon rank sum test, p = 0.0151) and increased C reactive protein (CRP) levels (5.56 ± 2.98 versus 0.73 ± 0.25 mg/dL; Shapiro–Wilk test p < 0.0001; Wilcoxon rank sum test p = 0.0069) [37]. However, the study indicated a higher prevalence of abnormal thyroid hormone profiles in men, as compared to women, which was opposed to most published data [28,30]. While no relationship was established between CRP levels and TSH, a negative correlation was observed between CRP and fT3, respectively, and fT4 (CRP versus TSH, r = -0.0504, p = 0.1777; CRP versus fT3, r = −0.4635, p = 0.0032; CRP versus fT4, r = 0.1242, p = 0.0181) [37]. Zheng et al. [38] published a retrospective study in 2020 on 201 patients with PV, PsA, GPP, and EP, along with 80 controls (individuals with noninflammatory skin conditions). The highest prevalence of thyroid dysfunction was found in the EP group (59.57%), followed by non-EP categories: 42.11% (GPP), 19.05% (PsA), and 18.99% (PV). The EP group was statistically significantly more affected than the PsA group (p < 0.001), but not the GPP group (p = 0.13). It was higher than the control group (p < 0.001) (GPP versus control (p = 0.005)). Two-thirds of the patients with psoriasis exhibited low levels of fT4, with normal TSH as the main abnormal hormonal finding. CRP levels were similar between psoriasis-positive subjects displaying thyroid hormone anomalies and those with normal thyroid profiles [38]. It bears mentioning that the general endocrine populations’ associations with various thyroid conditions do not typically associate anomalies with serum CRP levels except in subacute (viral) or acute (microbial) thyroiditis. That is why, from a strictly endocrine perspective, assessments of CRP add little value to our understanding of common mechanisms with psoriasis [39]. Wang et al. [40] conducted a large retrospective cohort study (National Health Insurance Research Database of Taiwan) including 162,842 individuals with psoriasis (PsA subgroup of 13,266 participants) with 1:1 sex- and age-matched controls (psoriasis-free). The studied population had an increased risk of developing thyroid hormonal imbalances, such as hyperthyroidism (aHR = 1.22, 95% CI 1.11–1.33), hypothyroidism (aHR = 1.38, 95% CI 1.23–1.56), ATD (aHR = 1.42, 95% CI 1.22–1.64), GD (aHR = 1.26, 95% CI 1.13–1.41), and HT (aHR = 1.47, 95% CI 1.18–1.82). The PsA group also showed a 1.44-fold increase in their risk for nontoxic goiter (95% CI 1.24–1.66), a 1.32-fold increased risk for hyperthyroidism (95% CI 1.07–1.65), a 2.05-fold increased risk for thyroiditis (95% CI 1.51–2.77), a 1.38-fold increased risk for GD (95% CI 1.07–1.79), and a 2.09-fold increased risk for HT (95% CI 1.34–3.24) [40]. Similarly, Liu et al. [41] analyzed patients with psoriasis and incident thyroid morbidity (US population-based study), enrolling 15,091 adults (National Health and Nutrition Examination Survey between 2009 and 2014). They confirmated increased risks for thyroid dysfunction (aOR = 1.607; 95% CI 1.011–2.554), mostly affecting those between 40 and 59 years (aOR = 2.667; 95% CI 1.376–5.168) [41]. Kiguradze et al. [42] published a large, cross-sectional cohort study (Northwestern Medicine Enterprise Data Warehouse) on 9654 individuals with psoriasis and 1745 patients with HT; the association between these two disorders was confirmed after adjusting for confounding variables such as gender, age, PsA, and use of systemic antipsoriatic agents (OR = 2.49; 95% CI 1.79–3.48; p < 0.0001) [42]. Valdulga et al. showed that HT prevalence was higher than controls (N = 60 patients with psoriasis versus 60 gender- and age-matched controls: 21.6% versus 6.6% (p = 0.03)). Among subjects with psoriasis, women were more frequently affected by HT (p = 0.002), and logistic regression confirmed that plaque psoriasis was the single independent variable associated with HT [43]. A meta-analysis from 2022, performed by Zhang et al. [44] and involving 253,313 subjects with psoriasis and 1,376,533 controls, showed an increased prevalence of ATDs in psoriasis group versus control (OR = 1.76, 95% CI 1.35–2.28, p < 0.01). When analyzing the prevalence of a specific ATD, HT was significantly more prevalent in patients with psoriasis than controls (OR = 1.88, 95% CI 1.50–2.35, p < 0.01), but not GD [44]. We identified one study on individuals with psoriasis comparing late onset (after the age of 40) with early onset (before the age of 40) cases (278, respectively, 62 individuals). A higher risk of autoimmune thyroiditis was revealed in first group (adjusted OR = 5.05; 95% CI, 1.62–15.7) [45]. Overall, associations between psoriasis, as a general condition as well as its different subtypes, and thyroid disorders, in terms of abnormal thyroid hormone levels and/or thyroid antibodies, were confirmed by these mentioned studies. The results were heterogenous [40,41,42,43]. The extent of statistical relevance varied with study design, enrolled population, specific endocrine assessments, and dermatologic evaluation (types of psoriasis, disease duration, score of activity/severity, PsA association, etc.). The duration of psoriasis disease increased the risk of detecting thyroid abnormalities. The most frequent associations were observed with HT, not GD, while the most frequent hormonal imbalance seemed to be hypothyrodism (sublinically, rather than clinically, manifested). The severity of psoriasis did not seem to correlate with the presence of thyroid dysfunction and/or autoimmunity in most studies [29,31], though some exceptions were reported [37,46] (Table 1). A small case-control study evaluated associations between psoriasis and HT (N = 56 versus 54 controls); similar TSH and fT4 levels were found between the two studied groups. However, higher levels of prevalence of TPOAb and TgAb were observed in the psoriasis group than in the control group. There was also an increased rate of ultrasound findings suggesting ATDs, such as hypo-echogenicity (30.4% versus 9.3%, p = 0.02), high vascularity (35.7% versus 5.6%, p = 0.001), and pseudo-nodularity (16.1% versus 0%, p = 0.002). Severity of disease (PASI score) was not correlated with TPOAb or TgAb positivity [47], as in prior mentioned studies [30,31]. Hansen et al. [48] enrolled a previously-studied population from the Danish General Suburban Population Study [49]. Individuals with psoriasis (N = 1127) were matched (1:5) with healthy controls with regards to gender, age, body mass index, and smoking status. ATD and TPOAb were similar between the groups. Individuals with psoriasis had a higher total T3 (1.69 ± 0.32 versus 1.72 ± 0.33 nmol/L; p = 0.01), but similar levels of TSH and free T4. The exact mechanism behind high total T3 levels, along with normal TSH and total T4, in the studied population was not clearly understood [48]. No correlation was confirmed between psoriasis and thyroid involvement by Lai et al. [50], who analyzed a random population sample of 5560 responders from the U.S. National Health and Nutrition Examination Survey database between 2011 and 2012. Adjusting for confounding factors, such as body mass index, age, gender, smoking habits, and alcohol consumption, yielded results similar to several previous studies [50,51]. Vassilatou et al. [52] examined the prevalence of ATD in subjects with psoriasis (N = 114) in a prospective study (N = 286 age- and body mass index-matched controls, without a history of psoriasis, from areas with sufficient iodine intake). After defining HT as TPOAb and TgAb serum titers over 34 IU/mL and 115 IU/mL, respectively, and evaluating PASI scores, TSH, T3, T4, fT4, and antibody levels were similar between the groups. However, the authors confirmed female predominance by identifying an increased prevalence of HT in females in the control group (14.7% versus 4.9%), but not in the psoriasis groups (10.5% versus 9.6%) [52]. A study focusing on quality of life in patients with psoriasis (N = 74) showed a weak correlation with the presence of thyroid diseases (affecting 6.75% of them) [53]. Another retrospective, observational study showed that patients with plaque psoriasis with thyroid involvement were similar in age, gender, disease severity, and duration to those with normal thyroid profiles. In total, 10% of the entire cohort (N = 290) experienced a thyroid dysfunction (defined as a ≥10% variation in normal thyroid hormone values), while 13.5% of individuals with psoriasis had positive serum TPOAb [54]. Another small study (without a control group) showed that, among 48 patients with palmoplantar pustulosis, 12% had antibody-based thyroiditis [55]. The Mayo Clinic published a retrospective, uncontrolled study on 215 persons with palmoplantar pustulosis, and identified 18 subjects (8%) with thyroid diseases. This was less than expected, according to Olazagasti et al. [56] (Table 2). Thyroid hormones are critical regulators of development. They function at various levels, including the digestive system, cardiac and skeletal muscle, and brain; they also affect energy metabolism and overall homeostasis [57,58]. Skin is involved in thyroid hormone activity, signaling which hormones exert their roles through genomic mechanisms (i.e., by binding nuclear thyroid hormone receptors) as well as non-genomic pathways, involving cellular proteins such as membrane integrin, αvβ3, etc. [57,58,59]. Thyroid hormones are implicated in fetal epidermal differentiation, barrier formation, hair growth, keratinocyte proliferation, and modulation of keratin gene expression [57,58,59]. They induce keratinocyte hyper-proliferation through epidermal growth factor (EGF). Data have shown that antithyroid medications for hyperthyroidism (for example, propylthiouracil) exhibit antiproliferative effects, with beneficial effects on psoriasis plaques [60,61]. Among the targets of T4 and T3, K6, K16, and K17 are connected with psoriasis pathogenic loops, while K1 and K10 are displaced in spinous and cornified layer [58,59,62]. Murine studies on thyroid hormone receptors in mutant mice (lacking TRα1 and TRβ isoforms) showed markedly reduced keratinocyte proliferations, increased activations of p65/NF-κB pathways, and STAT3 phosphorylation—which caused a high expression of pro-inflammatory cytokines and chemokines [58,63]. T-helper 1 lymphocyte dominant response, observed in psoriasis, determines a pro-inflammatory milieu, typically comprised of IFN-γ, TNF-α, and chemokines such as CXCL10 (a chemoattractant for neutrophils found in active psoriasis plaques) [64]. ATDs share a Th1 immune-mediated response with IFN-γ and IFN-γ dependent chemokines like chemokine (C-X-C motif) ligand (CXCL)10, involved in the pathogenesis of both GD and HT [5,64,65]. IL-17 of the IL-23/Th17 axis, as seen in psoriasis, plays an important role in ATD, indicating another potential level of connection between the two conditions [42,43,66]. A shift from a Th-1 to a Th-2 immune response through monocyte chemoattractant protein-1 (CCL2) and macrophage-derived chemokine CCL22 has been described in both PsA and GD [58,67,68]. The latest data concern new pathogenic pathways to potentially connect psoriasis to different anomalies at the thyroid level, either through direct links or indirect associations with other conditions, especially those with a higher risk for developing both skin and thyroid diseases of the autoimmune type [69,70,71,72,73,74]. Jiang Y. et al. published a study in 2022 regarding the Psoriasis susceptibility 1 candidate 1 (PSORS1C1) gene, which has been associated with various autoimmune conditions, including rheumatoid arthritis, ankylosing spondylitis, and systemic lupus erythematosus. This case-control study involved 1065 patients (Chinese Han participants) with ATD and 943 healthy controls, and analyzed 4 single nucleotide polymorphisms (SNPs): rs3130983, rs3778638, rs3815087, and rs4959053. They determined that rs3778638 genotypes were statically significant different from ATD and control (p = 0.046), but the rs3778638 genotype was only correlated with GD (p = 0.039), not with HT (p = 0.141) [75]. Tumor necrosis factor α-induced protein 3 (TNFAIP3) gene was recently incriminated in a large spectrum of autoimmune disorders, including ATD and psoriasis [76]. Another common pathogenic mechanism concerns thyroid hormone signaling, potentially involved in the microRNA-ome underlying psoriatic skin [77]. Anomalies of apoptosis affecting keratinocyte proliferation in psoriasis have been described in ATD, as well [78]. Defects of apoptotic pathways might represent a link to metabolic syndrome in PV and hypothyroidism [79]. A recent hypothesis suggested that viral infections in pregnant females could trigger autoimmune conditions early in life, including type 1 diabetes mellitus, HT, and psoriasis [80]. Another clinical circumstance for developing both ATD and psoriasis was found in HIV-positive and hepatitis C-positive patients to whom prolonged survival was recently registered due to advance of antiviral drugs. A higher risk of developing different autoimmune disorders was identified [81,82]. Globally, one-third of adults presenting common variable immunodeficiencies are admitted for autoimmune comorbidities, including psoriasis and thyroiditis of different kinds [83]. Another clinical entity that may be associated with a higher risk of psoriasis and HT is idiopathic retroperitoneal fibrosis, an immune-mediated condition involving a large frame of chemokines (e.g., CXCL12 and CCL11) and cytokines (e.g., IL-6, IL-12, and IL-13) [84]. Another clinical example is primary biliary cholangitis; a study from 2021 (N = 1554 patients with this condition) showed that ATD coexisted in 10.6% of cases, while 1.5% had psoriasis [85]. Moreover, both HT and psoriasis have been listed as autoimmune complications triggered by infection with Helicobacter pylori, in association with positive gastric autoimmunity [86]. Additionally, the prescription of proton pump inhibitors could exacerbate autoimmunity (including HT and psoriasis) under certain circumstances [87]. Another potential iatrogenic component relates to dipeptidyl peptidase-4 inhibitors (DPP4is), prescribed for inflammatory diseases due to their inhibitory effects on cytokine production and T cell proliferation. A population-based study on 283 individuals treated with these agents, versus 5660 controls, showed a higher prevalence of psoriasis (2.5% versus 1.2%; OR= 2.12; 95% CI 0.99–4.66; p = 0.05), respective to HT (16.6% versus 12.6%; OR = 1.38; 95% CI 1.00–1.91; p = 0.049) [88]. A multimodal approach was proposed, involving thyroid hormones and vitamin D as players in psoriasis lesions progression [89]. One small study on 30 patients with psoriasis and 30 healthy controls showed a higher serum TSH value in the psoriasis group (p < 0.05), but with intra-normal TSH variations and a negative correlation between serum 25-hydroxyvitamin D and PASI [90]. Another endocrine component of psoriasis and disorders associated with an abnormal thyroid profile, like thyroid eye disease (in GD), potentially involves insulin-like growth factor (IGF) axis [91]. One of the most recent pathogenic factors is represented by COVID-19 infection, which seems to trigger various panel of single or poly-autoimmunity, potentially as part of long COVID-19 syndrome [92,93,94]. We identified a single case to highlight this combination: a previously healthy teenager with negative family history for autoimmunity who developed GD and PV after infection with COVID-19 [95]. Further data are expected to highlight autoimmunity following COVID-19 (Figure 2). Of note, major histocompatibility complex (MHC) loci have been reported in relation with a myriad of autoimmune disorders, including many at the skin and thyroid levels. Antigen presentation by MHC-II is related to the immune response, including self-tolerance. Anomalies of MHC are connected to triggering autoimmune responses, involving T cells at many levels, as well as immune recognition, comprising both MHC-I and MHC-II. For instance, genetic susceptibility to PsA includes, among others, MHC-I-associated gene polymorphisms like IL12B, TYK2, etc., while haplotypes such as DR3-DQ2 and DR4-DQ8 are prone to autoimmune thyroiditis [96,97,98,99]. On the other hand, another modern field of common pathogenic interest for many autoimmune diseases, including psoriasis and ATD, bears mentioning: gut microbiota. Anomalies of intestinal metabolites or abnormal interactions between intestinal microorganisms and human host systems might be a cornerstone factor contributing to autoimmune responses [100]. In many skin diseases with autoimmune backgrounds, dual interplays between the immune system, which modulates normal dermatological processes, and intestinal microorganisms (underlying dysbiosis) have been reported [101,102]. Both microbiomes and macrobiomes have been described in terms of their relationships to developing psoriasis [103]. Moreover, Chao1 (which is the index of microflora richness) has been found at increased levels in HT and decreased levels in GD [100,104]. Additionally, T3, by activating its receptor α1 at the intestinal level, represents a contribution to epithelial homeostasis, while metabolite-derived short-chain fatty acids modulate thyroid function [105,106]. Skin and hair conditions have been reported in patients suffering from hypo- or hyperthyroidism of different etiologies, but most reports have been in subjects with ATD, as a single endocrine complication or as part of autoimmune polyglandular syndromes (APS) [107,108,109]. Vitiligo and alopecia have been identified in antibody-related circumstances similar to psoriasis, including those with pediatric onset [107,108,109]. The panel of endocrine conditions in ATD-positive subjects also includes primary ovarian failure, autoimmune hypoparathyroidism, hypophysitis, premature ovarian failure, Addison’s disease, and type 1 diabetes mellitus, among others. [110,111,112]. Non-endocrine autoimmune features include, among others, lupus, dermatomyositis, gastritis, hepatitis, and colitis. [100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115]. For instance, one recent study, from 2022, on 116 patients with Addison’s disease, showed that 74% of them had at least one relative confirmed with an autoimmune entity (N = 221 relatives with 257 diseases); among these, 100 individuals were identified with HT, and 15 were determined to have psoriasis [116]. With regard to assessing psoriasis in endocrine patients, we identified 3 studies, according to our methodology. Fallahi et al. [117] conducted a prospective study on 3069 individuals with autoimmune thyroiditis and found a higher prevalence of PsA in these patients (p < 0.0180) when compared to controls. However, no statistically significant evidence was attained for the PsC subgroup (p = 0.6237) [117]. Kelada et al. retrospectively studied a population diagnosed with thyroid eye disease (GD-associated autoimmune orbitopathy) between 2011 and 2019 (N = 267). Of these, 13.9% displayed non-thyroid autoimmune comorbidities, associated with a more severe/active eye presentation, and 3% of subjects had psoriasis [118]. Takir et al. [119] examined, in a cross-sectional study, 300 persons with thyroid diseases (N1 = 173 with autoimmune disorders, N2 = 127 with non-autoimmune conditions) versus 100 healthy controls. Psoriasis was identified as statistically significantly more frequent in N1 than N2 (p = 0.001), suggesting that patients under endocrine surveillance were more likely to have psoriasis if their thyroid condition were autoimmune [119] (Table 3). Patients with psoriasis are at higher risk of some cancers, and some safety concerns arise in relation to thyroid cancer, as well. However, the fact that patients with psoriasis display an increased risk of thyroid malignancy remains controversial [120,121]. As mentioned, one single study identified a higher risk of nontoxic goiter in PsA [40]. Of note, 5% of the general population (depending on age) has a thyroid nodule, while thyroid cancer represents the most frequent endocrine neoplasia, with an age-dependent prevalence of almost 5% of thyroid nodules [122,123]. We identified only one study which examined thyroid cancer in individuals with psoriasis. This was a nested case-control study (Korean National Health Insurance Service-Health Screening Cohort) that included individuals 40 years and older (N = 6822 subjects with thyroid cancer versus 27,288 controls). A previous history of psoriasis was similar between studied groups (OR = 1.02; 95% CI, 0.85–1.22). The subgroup without hypothyroidism had a higher rate of thyroid malignancy associated with psoriasis (overlap-weighted OR = 1.29; 95% CI 1.06–1.57, p = 0.012) while those with hypothyroidism showed a low rate (overlap-weighted OR = 0.59; 95% CI 0.37–0.96, p = 0.034); no other correlations were identified [121] (Table 4). Based on these findings, we concluded that we did not have sufficient data to support an association between thyroid cancer and psoriasis. Medication used in psoriasis treatment could contribute to the development of immune and autoimmune events with concomitant anticancer drugs. On the other hand, both ATD and psoriasis have been incidentally reported in oncologic patients who developed immune/autoimmune side effects to modern categories of immune checkpoint inhibitors [124,125]. Pre-existent autoimmune conditions increase the risk of developing immune side effects while being treated with anticancer medication [126]. Several studies have observed exacerbation of psoriasis and ATD in oncologic patients [127,128,129,130,131] (Table 5). The largest study, as of 2016, on ipilimumab treatment for melanoma in patients with preexistent autoimmune conditions, showed that one-third of the subjects suffered an exacerbation of prior comorbidities; one-third of these exacerbations were reversible upon glucocorticoid exposure [131]. Studies published within the last few years confirmed that previous psoriasis or ATD may worsen in response to immune checkpoint blockade. In cases with thyroiditis, glucocorticoid therapy and antithyroid medication for hyperthyroidism or, alternatively, substitution with levothyroxine for hypothyroidism, is required, sometimes for the remainder of a patient’s life [129]. A meta-analysis from 2021 on randomized, placebo-controlled studies, including oncologic patients under immune checkpoint inhibitors (N = 5560), showed an incidental rate of thyroiditis (0.86%), and identified one new case with psoriasis [128]. Anti-psoriasis medications, as contributors to thyroid anomalies, include anti-TNF-α drugs; their contributions remain a matter of debate [132]. Subacute thyroiditis, despite being a classically viral condition, has been reported in circumstances involving an abnormal cytokine profile [133]. Biological medications for skin conditions might play a role in triggering flare-ups of colloidal pools filled with thyroid hormones T3 and T4, as seen in thyroiditis-associated thyrotoxicosis [134,135]. For instance, there was a case of a 32-year-old male with confirmed thyrotoxicosis being treated with ustekinumab (monoclonal antibody against IL-12/23). He relapsed twice after reinitiation of the drug [136] Another case (published in 2021) introduced a 71-year-old male patient with PsA who was treated with secukinumab (IL-17A inhibitor), which was later switched to adalimumab (TNF-α inhibitor), while developing subacute thyroiditis. Therapy with prednisolone was necessary. Consecutive treatment with ixekizumab (IL-17A inhibitor) controlled PsA and did not induce a relapse of thyroiditis [137]. Another case of adalimumab-associated subacute thyroiditis was reported in 2017 [138]. Cytomegalovirus-induced subacute thyroiditis was reported in 2016 in a patient with PsA treated with infliximab [139]. As mentioned, most of the data included adult patients. However, APS can be associated with HT, especially type 3, and psoriasis has been reported, extremely rarely, in adults and in children [140,141]. Moreover, results from the International Pharma-Child Registry confirmed that both psoriasis and ATD were among the most frequent autoimmune disorders in populations diagnosed with juvenile idiopathic arthritis. Positive familial autoimmune diseases have been determined to be a risk factor for developing this type of arthritis [142]. Concerning the burden of autoimmune comorbidities in 79 individuals diagnosed with juvenile idiopathic arthritis (aged between 0 and 21 years), a rate of 10% (N = 8) was identified with ATD, while approximatively 4% had psoriasis [143]. Cumulative incidence of ATD was 36%, with mean age at diagnosis of 13.2 years. First-degree relatives were more affected by autoimmune comorbidities than second-degree relatives (16.7% versus 11%) [143]. Interventional studies addressing psoriasis and ATD remain an open issue. Some nutraceutical supplements could improve both psoriasis and HT [144]. Among these, vitamin D supplementation and omega 3 fatty acid supplementation could potentially reduce the burden of autoimmune diseases, but only upon exposure to certain doses and only for a limited period of time [145]. It has not been determined whether or not hypo- or hyperthyroidism in subjects with psoriasis improves skin condition. As has been pointed out, individuals with the most severe psoriasis cases may not necessarily be those displaying a pathological profile, with respect to the thyroid gland. Gluten-free diets have yet to be proven useful in ameliorating psoriasis and ATD, as suggested by some authors. Based on current data, unless celiac disease is co-present, this routine recommendation is not supported [146]. Additionally, vegan and vegetarian habits might trigger phytophotodermatitis; thus, diet could play an important role in modulating thyroid profiles and in psoriasis therapies [147]. The association with celiac disease is not rare; one retrospective study on 749 patients with this digestive condition showed a prevalence of 19.9% for ATD, 14.7% for hypothyroidism, and 2.7% for psoriasis [148]. Additionally, a case-controlled study on 341 individuals with celiac disease showed that 26.6% of them had at least one autoimmune disease (autoimmune thyroiditis, 48%; psoriasis, 17%) [149]. Another case-controlled study on 255 persons with celiac disease (versus 250 controls) showed that 35.2% of them had autoimmune disorders. HT was the most frequent comorbidity (24.3% versus 10%), while the second most prevalent was psoriasis (4.3% versus 1.6%) [150]. Another endocrine condition that can predispose someone to all three mentioned autoimmune diseases is Turner syndrome. In patients suffering from Turner syndrome, lifelong surveillance—including monitoring for autoimmune complications—is necessary [151,152]. Future studies will likely continue the search for an ideal drug to concomitantly target disorders like psoriasis and ATD. Strategically searching for thyroid anomalies in patients confirmed with psoriasis, either on clinical or molecular levels or using genetic findings, also remains an open issue. The exact subgroup of individuals that should be candidates for strategic endocrine assessments has not been determined. The minimum panel of thyroid assays includes: TSH, freeT4 (perhaps also freeT3), and TPOAb (perhaps also TgAb). We followed 4 clusters of conditions: thyroid dysfunction, autoimmunity, thyroid cancer, and subacute thyroiditis. The fact that psoriasis and ATD are related to the immune-based side effects of modern anticancer drugs, namely immune checkpoint inhibitors, is a new piece of information in this field (Figure 3). To our knowledge, this was one the most complex analyses of published studies concerning a dermatological and endocrine dual perspective. Overall, we identified 16 confirmatory studies, but with heterogeneous data. PsA had a higher risk of positive TPOAb (25%) versus PsC or control, as well as an increased risk of thyroid dysfunction versus control. Hypothyroidism was the most frequent type of dysfunction (subclinical rather than clinical). Thyroid anomalies were correlated with >2-year disease duration, peripheral > axial and polyarticular involvement. With a few exceptions, female predominance was observed. Hormonal imbalances included, most frequently, low T4 and/or T3 with normal TSH, followed by high TSH; only one study observed higher total T3. The highest ratio of thyroid involvement in dermatologic subtypes was 59% for EP. An analysis of specific psoriasis subtypes and associated thyroid anomalies, according to prior mentioned studies, can be found in Figure 4. Most studies found no correlation between thyroid anomalies and psoriasis severity. Statistically significant ORs for hypothyroidism: 1.34–1.38; hyperthyroidism: 1.17–1.32 (fewer studies than hypothyroidism); ATD: 1.42–2.05; HT: 1.47–2.09; GD: 1.26–1.38 (fewer studies than HT). Additionally, 8 studies had inconsistent or no correlations or weak statistical power concerning associations between thyroid autoimmunity or dysfunction and psoriasis. The lowest rate of thyroid involvement was 8% (uncontrolled studies). Other data included: 3 studies on patients with thyroid autoimmune conditions looking for psoriasis and one study on psoriasis and thyroid cancer. ICP was shown to possibly exacerbate prior ATD and psoriasis or to induce them both de novo (5 studies). At the case report level, studies examined subacute thyroiditis due to biological medication (ustekinumab, adalimumab, infliximab). Further well-designed, longitudinal controlled studies are necessary. Thyroid involvement in patients with psoriasis remains an open question. However, observed significant data that confirmed a higher risk positive antibodies and/or thyroid dysfunction, especially hypothyroidism, in subjects with psoriasis. Further study, and greater awareness, is necessary to improve overall outcomes for patients. Debate continues concerning the exact profile of individuals, diagnosed with psoriasis, who should undergo endocrinological screening. Uncertainty exists regarding dermatological subtypes, disease duration and activity, and other synchronous (especially autoimmune) conditions.

PMC10003399

Fei Ge,Keyan Sun,Zhenlin Hu,Xin Dong

Role of Omega-Hydroxy Ceramides in Epidermis: Biosynthesis, Barrier Integrity and Analyzing Method

06-03-2023

omega-hydroxy ceramides (ω-OH-Cer),corneocyte lipid envelope (CLE),mass spectrometry (MS) analysis,integrity of skin barrier,skin care

Attached to the outer surface of the corneocyte lipid envelope (CLE), omega-hydroxy ceramides (ω-OH-Cer) link to involucrin and function as lipid components of the stratum corneum (SC). The integrity of the skin barrier is highly dependent on the lipid components of SC, especially on ω-OH-Cer. Synthetic ω-OH-Cer supplementation has been utilized in clinical practice for epidermal barrier injury and related surgeries. However, the mechanism discussion and analyzing methods are not keeping pace with its clinical application. Though mass spectrometry (MS) is the primary choice for biomolecular analysis, method modifications for ω-OH-Cer identification are lacking in progress. Therefore, finding conclusions on ω-OH-Cer biological function, as well as on its identification, means it is vital to remind further researchers of how the following work should be done. This review summarizes the important role of ω-OH-Cer in epidermal barrier functions and the forming mechanism of ω-OH-Cer. Recent identification methods for ω-OH-Cer are also discussed, which could provide new inspirations for study on both ω-OH-Cer and skin care development.

Role of Omega-Hydroxy Ceramides in Epidermis: Biosynthesis, Barrier Integrity and Analyzing Method Attached to the outer surface of the corneocyte lipid envelope (CLE), omega-hydroxy ceramides (ω-OH-Cer) link to involucrin and function as lipid components of the stratum corneum (SC). The integrity of the skin barrier is highly dependent on the lipid components of SC, especially on ω-OH-Cer. Synthetic ω-OH-Cer supplementation has been utilized in clinical practice for epidermal barrier injury and related surgeries. However, the mechanism discussion and analyzing methods are not keeping pace with its clinical application. Though mass spectrometry (MS) is the primary choice for biomolecular analysis, method modifications for ω-OH-Cer identification are lacking in progress. Therefore, finding conclusions on ω-OH-Cer biological function, as well as on its identification, means it is vital to remind further researchers of how the following work should be done. This review summarizes the important role of ω-OH-Cer in epidermal barrier functions and the forming mechanism of ω-OH-Cer. Recent identification methods for ω-OH-Cer are also discussed, which could provide new inspirations for study on both ω-OH-Cer and skin care development. In the history of organic evolution, creatures have covered themselves with skin to isolate their inner organs from the outer environment [1]. As one of the biggest organs in the human body, the skin has several essential functions. Most mechanical injury would be fatal if there is no skin coverage. Furthermore, survival on dry land requires a sustainable moisture containment system in the stratum corneum (SC), which can protect against the loss of body fluid and electrolytes [1,2]. The mammalian epidermis is a kind of multi-layered epithelium, which maintains its self-renewal ability under dynamic equilibrium and injury conditions by maintaining the mitotic active cell groups in hair follicles and the innermost basal layer. The SC functions as a barrier for the human body, and is formed naturally with a linear differentiation process. In this process, basal cells differentiate from a basal layer into spinous cells in the spinous layer, which in turn develop into enucleated granular cells in the granular layer, and subsequently function into squames in the SC [3]. The dysfunction of the SC will cause a disrupted skin barrier, exposing patients to water loss and skin inflammation, all of which would cause severe dermatological conditions such as atopic dermatitis, psoriasis vulgaris, and xeroderma pigmentosum [4]. During the skin-cornification process, lipids are transported to the extracellular space by lamellar bodies containing phospholipids, glycosylceramides, sphingomyelin, cholesterol, and enzymes [5,6]. Enzymes are known as metabolizers of lamellar lipids, and form the final lipid components of SC. Generally, human SC is composed of 50% ceramides (Cer), 25% cholesterol, and 15% free fatty acids (FA) [7]. As the most abundant component of SC, Cer has attracted the attention of researchers. In SC, the lipids derived from sebocytes, keratinocytes and microorganisms function as “mortar” for squames. The strong protective barrier of skin is built via lipids binding squames together [8]. Certain lipid components of SC will maintain a balance of inner homeostasis. To date, the cause of skin barrier disruption is poorly understood. In the meanwhile, the disruption of skin barrier integrity was confirmed as a mechanism for skin dermatoses [9]. Supplementation of Cer assists in the formation of the permeability barrier, which in turn can heal damage to the skin barrier [10]. Severe epidermal barrier perturbation occurs with selective ablation of ceramides in the epidermis [11]. Moreover, as a secondary lipid messenger, Cer and/or its metabolites mediate several cell signaling processes, including growth, differentiation, senescence, necrosis, proliferation, and apoptosis [12]. In current clinical treatment for skin barrier integrity, Cer has become a preferred alternative to corticosteroids, of which the latter might cause side-effects such as high blood pressure, headache, and in terms of skin, barrier weakening [13]. A recent review by Kono et al. [14] reveals 21 positive reports, indicating that external ceramide-containing preparations have effects on improving dry skin and barrier function. In these reports, formulations containing Cer have been shown to reduce transdermal water loss, improve stratum corneum structure, and/or increase stratum corneum fat content. These reports therefore detail the efficacy of ceramide-containing formulations. The Cer molecule is composed of a long-chain base (LCB) and an FA attached by an amide bond [6]. Various combinations of LCB and FA make the molecular structure of Cer to differ from other molecules. For mammals, there are five types of LCB, including sphingosine (Sph), dihydrosphingosine (DS), phytosphingosine (PS), 6-hydroxy sphingosine (H), and 4,14-sphingadiene (SD), as well as four types of FA, including nonhydroxy FA (N), α-hydroxy FA (A), β-hydroxy FA (B), and ω-hydroxy FA (O) [15]. The structures and nomenclature for Cer classes in mammals are illustrated in Figure 1. Sph-based Cer will be the focus of the following discussion. In this review, the nomenclature of ceramides follows the report of Motta et al. [16] and Robson et al. [17]. The name of each Cer is a combination of a letter representing the type of FA, and another one representing the type of LCB. For example, Sph ceramides with α/β/ω-hydroxylated FA are designated as AS/BS/OS. Hydroxylation of LCB in ceramides introduces multiple variations in biomolecule functions. For instance, the absence of AS on the myelin sheath membrane leads to a loss of long-term stability of the myelin sheath, and eventually leads to demyelination [18,19]. The quantitative analysis of B in biological cycles evaluates the energy fatty acid oxidation and interrelated pathways. In other words, a regular and proper BS level indicates the body’s ability to deal with fasting states, as well as normal cell metabolism and maintenance of cell energy supply [20]. When it comes to OS, the most noticed function is its critical role in maintaining the integrity of SC. O-type FA is hydroxylated at the ω position of carbon chain, which is located at the end of carbon chain. Acylated with LCBs, O-type FA forms ω-hydroxyceramides (ω-OH-Cer), namely, OS/ODS/OPS/OH/OSD. This unique hydroxyl position gives ω-OH-Cer surfactant properties, and chances to combine with proteins or other FAs with the hydroxyl at the ω position of ω-OH-Cer. In SC, keratinocytes are surrounded by a highly crosslinked protein network, also known as the cornified lipid envelope (CLE) [21]. ω-OH-Cer is the primary lipid component of CLE, which is covalently attached to the outer surface of the cornified envelope and connected with involucrin, forming lipids in SC [22]. ω-OH-Cers are synthesized in the SC (the outermost layer of the epidermis) from precursor molecules called glucosylceramides. The synthesis of omega-hydroxy ceramides is mediated by a family of enzymes called cytochrome P450 oxidases, which add hydroxyl groups to the ceramide molecules. These hydroxyl groups are typically added to the omega (ω) position of the fatty acid chain of the ceramide molecule, hence the name “ω-OH-Cers” [23]. The hydroxyl group at the ω position can be esterified with other molecules to form esterified FA, or be attached to a protein for the modification of protein-bound FA. Early in 1986, Philip et al. [24] reported that FA, ω-hydroxyacids, and ω-hydroxyacylSphs in mammals are covalently attached to macromolecules, where 60% of the hydrolysis products of these lipids comprises ω-hydroxyacylSph or OS. Acylceramide, formed by acylation of ω-OH-Cer, functions as a molecular rivet. It holds the extracellular bilayers, where the ω-hydroxyacyl chain spans one of the lipid bilayers and the linoleate tail is inserted into another bilayer [25]. The cutaneous permeability barrier is therefore constructed by matured corneocytes to form a moisture-containment system. The significant role of ω-OH-Cer in maintaining the epidermal barrier function was only discovered after years of clinical cases. Numerous abnormal barrier conditions, including malformation of the cornified lipid envelope [26], atopic dermatitis [22], and ultraviolet burns [22], are all due to disturbed ω-OH-Cer biosynthesis, which is huge threaten to skin barrier integrity. ω-OH-Cer contributes to this barrier function by forming lamellar structures that help to seal the spaces between corneocytes (the flattened, dead cells that make up the SC). These lamellar structures are formed by the interdigitation of long-chain ceramides, cholesterol, and free fatty acids, and they provide a water-repellent surface that helps to prevent water loss from the skin [27]. Therefore, quantitation and identification of omega-hydroxyceramides in the skin can provide important insights into the mechanisms underlying skin barrier function. In particular, the development of analytical methods to quantitate ω-OH-Cer has enabled researchers to assess the levels of ω-OH-Cer in healthy and diseased skin, providing valuable insights into the role of ω-OH-Cer in skin function and disease [28]. The analysis of omega-hydroxyceramides in the skin involves different steps, including separation and compound identification. Separation of ω-OH-Cer provides the potential of studying this Cer with an independent view. Compound identification with separated ω-OH-Cer provides a more specific identification, which can possibility be used for further quantitation [2,6,18]. These two steps, along with the analyzing methods, are valuable tools for understanding the biological functions of the ω-OH-Cer molecule, as well as for the study of the pathology and biology of ω-OH-Cer molecules [6]. In this review, the detailed molecule mechanism of SC recovery from acute barrier disruption is discussed, in order to evaluate the efficiency of ω-OH-Cer in CLE development. This review is organized as follows: (1) mechanism of epidermal barrier recovery; (2) the biosynthesis of ω-OH-Cer; (3) ω-OH-Cer functions as a molecular rivet in CLE development; (4) current identification studies of ω-OH-Cer and challenges; (5) conclusions. The mammalian epidermis maintains renewable ability under conditions of injury or homeostatic status, via population of mitotically active cells in hair follicles and the innermost basal layer [28,29]. The epidermal barrier is the outermost layer of the skin, and it plays a critical role in protecting the body from external insults and preventing water loss. When the epidermal barrier is damaged, the skin becomes more permeable and loses its ability to retain moisture. This can lead to skin dryness, inflammation, and other skin disorders [27].The forming process, as well as the recovering process, of the epidermal barrier are dynamic and similar. The detailed structure of the epidermal barrier is pictured in Figure 2. As the beginning sign of terminal differentiation, basal cells withdraw from cell cycles concomitantly and leave the basement membrane. Differentiation of basal cells to spinous cell leads to the next stage of epidermal keratinocytes, where the durable cytoskeleton frame of keratin filaments is reinforced, in order to gain sufficient mechanical strength for the potential physical impact. Following that, the spinous cells develop into granular cells. In granular layer, lamellar bodies produce lipids and herein assemble CLE, the highly crosslinked protein network, via sequential incorporation of precursor proteins underneath the plasma membrane [6]. In this process, epidermal keratinocytes go through most of their cell cycle and are close to the disintegration of their cell membranes [30]. The subsequent calcium influx activates the transglutaminase (TGM) enzyme to crosslink Cers with CLE proteins, forming a sac surrounding the keratin fibers, as shown in Figure 2. One of the protective elements of the epidermal barrier is derived from this tough, insoluble structure. As the dynamic process occurs from the inner layers to the surface, the final stage of the epidermal keratinocyte life cycle occurs in the SC, where lipids derived from sebocytes, keratinocytes, and microorganisms will function as the “mortar” for squames. For physical skin damage recovery, all those mentioned cells are included, and this dynamic process is similar to the process of epidermal barrier-forming, as mentioned before, but with certain differences, including inflammation. The process of wound healing occurs in five overlapping stages, namely hemostasis, inflammation, proliferation, re-epithelization, and fibrosis [31,32]. In inflammation stage, which follows initial hemostasis, the innate immune system helps to remove dead tissue and defend the body from invading pathogens [33]. The reconstruction of damaged tissue involves the proliferation and re-epithelization processes, which include collagen synthesis, extracellular matrix formation, and restoration of the vascular network [33,34]. Basal keratinocytes migrate continuously to the SC layer to rebuild physical barrier [31]. The final stage of wound healing is the formation of functionally and visually intact skin. These overlapping wound individual healing stages are complex and their processes are dependent on one another; disruption in any of the processes can induce a hypertrophic scar with long-lasting pruritis [32]. Hypertrophic scar formation brings a risk of keloids, which is benign hyperproliferation of fibroblasts [35]. Sung et al. demonstrated that growth of fibroblasts can be inhibited by Cer via apoptosis and supposedly Sph; the metabolic product of OS might have cytotoxic effects on growth of keloid fibroblasts [36]. Therefore, ω-OH-Cer not only plays an irreplaceable role in SC formation, but also is beneficial for epidermal barrier construction. Beside open skin injuries, recovery of the skin barrier from atopic dermatitis is another issue of great interest, which is shown in Figure 3. Atopic dermatitis is characterized by inflammation and chronic itching in skin. Barrier dysfunction induces an inflammatory environment and skin dryness, lowering the itch threshold [37]. Pruritus in atopic dermatitis generally causes scratching on the affected area. Scratching breaks down fragile skin barrier and triggers Type 2 inflammatory responses that could exacerbate itch sensitization. Due to continuous damage accrued in the itch–scratch cycle and pre-existing barrier dysfunction, the five overlapping stages discussed in the preceding paragraph will be interrupted, breaking the healing plan [38]. Fortunately, certain treatments can relieve these symptoms. Of numerous studies based on topical therapy, systemic agents, or biologics, the main goal for atopic dermatitis management is to maintain the integrity of the skin barrier [39,40,41]. Intact CLE not only prevents the loss of natural moisturizing, but also helps in forming a proper orientation of the intercellular lipid lamellar structure, by interdigitating with the intercellular lipids [42]. Attached to the outer surface of the cornified envelope, ω-OH-Cer, symbolized by OS in CLE, is linked to involucrin to function as lipid components of SC. ω-OH-Cer forms lipids in the SC in unique ways that other ceramides cannot replace. Patients suffering from a lack of ω-OH-Cer or its related enzymes are at an extremely high risk of atopic dermatitis, harlequin ichthyosis [43], psoriasis [44], and other diseases caused by skin barrier dysfunction [45,46]. Mutations in ω-OH-Cer synthesis or condensing-related gene have been shown to be causes of congenital ichthyoses and ichthyosis syndromes. These ichthyosis conditions can only be modified via ω-OH-Cer supplementation [47]. There has been no successful trial on non-ω-hydroxylated ceramides on modifying congenital ichthyoses or ichthyosis syndromes. Moreover, the specific mechanism for epidermal injury caused by UVB is the breakage of the lipid bond between ω-OH-Cer and other lipids in SC [23]. To assist in epidermal barrier recovery, synthetic ω-OH-Cer has been applied widely in order help regain the moisture containment system in animal experiments [48,49]. All in all, ω-OH-Cer supplementation is not an official treatment for any specific disease, but the existence of ω-OH-Cer builds a strong barrier for the SC. ω-OH-Cer molecules were synthesized via de novo synthesis and salvage pathways. To detail the whole process of ω-OH-Cer synthesis, the FA and Cer synthesis processes are described individually below. Figure 4 is a vivid emerge of this whole process. The synthesis of FA is an iterative process, where FA chain length is strictly under control. Unlike proteins and nucleic acids, the monomeric unit of FA has less freedom and the chain length is more complex to predict, since this process is defined via FA synthase (FAS) instead of mRNA or DNA templates. During FA synthesis, there is no specific boundary for FA chain elongation, hydroxylation, and desaturation. Therefore, the variation of the FA chain is diverse. Despite the numerous FA products garnered using FA biosynthesis, the natural ω-hydroxylation on FA only occurs on FA chains with more than 16 carbon atoms [24]. Upon the onset of long-chain FA (LCFA) synthesis, FASs commonly release palmitic acid (C16:0) and stearic acid (C18:0), or the coenzyme A (CoA) derivatives thereof [50]. Most elongations of FA are achieved based on those products. FA elongations circulate via four processes: condensation, reduction, dehydration, and reduction [51]. In the first step, enzymes embedded in the endoplasmic reticulum elongate FAs, in order to convert FAs into acyl-CoAs. FA elongase catalyzes the production of 3-ketoacyl-CoA by condensing acyl-CoA with malonyl-CoA. Mammals have seven FA elongases with characteristic substrate specificity, named after the elongase of very-long chain fatty acid 1–7 (ELOVL1–7) with specific substrates [50]. In the second step, 3-ketoacyl-CoA is reduced to 3-hydroxy acyl-CoA by 3-ketoacyl-CoA reductase, named KAR in mammals [52]. Later, 3-hydroxyacyl-CoA dehydratase (HACD1-4) dehydrates 3-hydroxy acyl-CoA into 2,3-trans-enoyl-CoA, in order to take the LCFA synthesis to the last step. Then, 2,3-trans-enoyl-CoA reductase (TER) takes over in order to catalyze the formation of elongated acyl-CoA. Besides saturated fatty acid, the synthesis of unsaturated FA is also interesting. Firstly, the unsaturation process of elongated acyl-CoA or FAs should be clarified. CoA desaturases introduce a double bound to a specific location on the acyl-CoA chain, where the biological properties are complexed for further biofunctions. CoA desaturase is classified in accordance with the location on which the double bound is introduced (Δ number to indicate the location on carbon chains). In mammals, activities of Δ9, Δ6, and Δ5 CoA desaturases are observed [52]. All the desaturases found in mammals are only stearoyl-coA desaturases (SCDs). The other desaturase family, the so-called fatty acid desaturase (FADS) family, is not present in mammals. SCDs are endoplasmic reticulum enzymes, which catalyze the saturated FAs, synthesized de novo or from diary intake, into monounsaturated FAs. The desaturating process is essentially the transmission of hydrogen ions (H+). The combination of nicotinamide adenine dinucleotide (NADH), flavoprotein cytochrome b5 reductase, and the electron acceptor cytochrome b5 provides one molecular oxygen of adequate hydrogen ions to form two molecules of H2O, half from the transmission of hydrogen ions and half from substrates [53]. The preferred substrates of SCD are palmitoyl (C16:0)- and stearoyl (C18:0)-CoA, which are desaturated into palmitoleoyl (C16:1)- and oleoyl (C18:1)-CoA [54]. Noticeably, elongase activities and the process of FA occur in parallel until the chain length hits C26, when ELOVL4 takes over the elongase process and the desaturase process barely appears. The longer the carbon chain grows, the weaker the control SCD has on them. Therefore, though FAs can be catalyzed five or six times, the supplementation of essential FAs, such as docosahexaenoic acid (DHA, C22:6), in the diet is important [55]. The ω-hydroxylation of FA is not limited to a certain chain length. Although it is not thoroughly clarified, one of the credible theories based on the activity of microsomal cytochrome P450 enzymes is put into practice in multiple studies [50,56]. Cytochrome P450 family, a heme-containing monooxygenase, has a special ability to catalyze the hydroxylation of the terminal carbon atoms in the inactivated alkyl chain [57]. About 300,000 sequences of cytochrome P450 have been identified since it was first discovered in the early 1960s [58]. ω-hydroxylation of FA includes two main P450-dependent mechanisms. FAs with carbon chain longer than C30 are produced from a chain extension of palmitic acid (C16:0) and then hydroxylated by the P450 enzyme. In contrast, FAs with shorter carbon chains are directly ω-hydroxylated by the P450 family [24]. In 2000, Behne et al. [48] adapted amino benzotriazole, a chemical relative with notable P450 inhibitory activity, into cultured human keratinocytes, and found that it demonstrated significant decline in ω-hydroxylated FA and led to increased water loss in the epidermal barrier. This work proved the vital role P450 plays in ω-hydroxylated FA formation, as well as in epidermal health. Six years later [59], mutations on a new gene FLJ39501, which encodes CYP4F22 (cytochrome P450, family 4, subfamily F, polypeptide 22), were found in 21 patients with autosomal recessive congenital ichthyosis, in four countries. Ohno et al. [60] further delved into the investigation of FLJ39501, the FA ω-hydroxylation gene, to prove that CYP4F22 is a bona fide ULCFA ω-hydroxylase required for acyl Cer production to enhance skin permeability barrier function. In 2019, a more detailed theory of lamellar ichthyosis based on a missense mutation in exon 8, CYP4F22 Arg243Leu, was predicted to be a functionally defective variant via in silico analysis [61]. An abnormality of cytochrome P450-related genes in human mutations can further induce obvious epidermal damage, which will expose hosts to hyperkeratosis, mild acanthosis, or parakeratosis symptoms [24,48,56,57,58]. Not only meaningful for ω-hydroxy FA biosynthesis, fungal P450 and its outstanding ω-hydroxylation performance shed light on the artificial synthesis of ω-hydroxy FA in commercialized synthesis [50]. Despite the related knowledge being still limited, further studies on FA ω-hydroxylase are still carrying on. The onset of LCB biosynthesis in ω-OH-Cer is the condensation of palmitoyl (C16:0)-CoA and L-serine by serine palmitoyltransferase (SPTLC), the product of which is 3-ketodihydro-Sph. In the following, 3-ketodihydro-Sph reductase (KDSR) reduces 3-ketodihydro-Sph to dihydro-Sph. Dihydro-CER D4-desaturase (DES1) desaturates the dihydro-Sph between C4 and C5 to form a double bound, from which a Sph base is completed [62]. Dihydro-Sph can also be hydroxylated at the C3 position by dihydro-CER hydroxylase (DES2) to complete a PS base, which is another LCB, to synthesize ω-OH-Cer [62]. The synthesis of ω-OH-Cer follows the regular synthesis process of Cer synthesis, where Cer synthase (CerS) participates in the main esterifying process. Specifically, CerSs have preference for certain fatty acyl-CoAs. For example, CerS5 and CerS6 are active with C14:0-C18:0 fatty acyl-CoAs [63,64,65]; CerS1 is active with C16:0-C18:0 fatty acyl-CoAs [64]; CerS4, CerS2, and CerS3 are active with C18-C24 fatty acyl-CoAs [64,65,66]. To produce ceramides with longer chain lengths, CerS2 and CerS3 can keep active for fatty acyl-CoAs up to C26 [66,67]. The lack of CerS3 in mice directly induces the complete loss of ultra-long-chain ceramides (>C26) and ω-OH-Cer [67]. In this aspect, the ω-OH-Cer de novo synthesis process in mammals is highly dependent on CerS3. Other than being a de novo pathway, Cers can also be re-acylated by the salvage pathway via CerSs [56]. As mentioned before, SC mainly consists of terminally differentiated keratinocytes, which are embedded into the extracellular lipid matrix. During terminal differentiation, the cornified envelope (CE), a crosslinked protein structure, replaces the plasma membrane [30]. CLE is a monolayer of lipids bound covalently to CE. Being the interface of hydrophilic corneocytes and the lipophilic extracellular lipids, CLE is vital for skin barrier stability [26]. The surfactant properties of CLE are mainly based on its complex lipid components, of which ceramide accounts for the majority. ω-OH-Cer stands out for its hydroxylated group at the end of its carbon tail, with which CE proteins are connected by ester linkage [48]. The CLE is the product of keratinocytes during the differentiation process from specific lipid vesicles, which comprises lamellar bodies in the upper part of viable epidermis keratinocytes [2,6,68]. Within the latter differentiation process, Cer precursors (glycosylated or phosphocholinated ceramides), together with their converting enzymes, are released to extracellular space. Concurrently, the CLE forms via enzymes involved in binding Cer with CE, co-located at SC [68,69]. The binding of Cer with CE is based on the covalent binding of ultra-long-chain (ULC) Cer (ULC-Cer) to proteins on the surface of CE, as shown in Figure 2. ULC-Cer is derived from ultra-long-chain acylceramide, a Cer species in which the N-acyl chain is composed of ω-hydroxylated ULC-fatty acids esterified with linoleic acid (C18:2) to form esterified ω-hydroxy sphingosine (EOS), esterified ω-hydroxy phytosphingosine (EOP), and esterified ω-hydroxy 6-hydroxy sphingosine (EOH) [70]. The formation of CerEOS and CLE, as well as the genes/molecules involved, have been researched by studies on water-loss-related diseases, such as ichthyosis [69]. However, the mechanism of CerEOS binding to proteins on the outer surface of CE is still not well understood. In 2020, Takerchi hypothesized that the loss of SDR9C7, which is generally responsible for ichthyosis, is the key for CerEOS binding to proteins [71]. It was conjected that after 12R-LOX catalyzes CerEOS to form 9R-hydroperoxy-CerEOS, eLOX3 takes over to further catalyze 9R-hydroperoxy-CerEOS into epoxy-alcohol-CerEOS. After these processes, SDR9C7 oxidization happens, resulti into epoxy-enone-CerEOS. The non-enzymatic binding to proteins on the extracellular surface of CE relies on this epoxy-enone [72]. Finally, the covalently bound epoxy-enone-CerEOS forms CerEOS-bound protein by an unknown mechanism (probably via the Michael addition reaction or Schiff base and pyrrole formation) [71]. In 2021, Youssefian et al. [73] conducted a clinical and molecular characterization work of 19 patients with autosomal recessive congenital ichthyosis, in five families with SDR9C7 gene mutation. The apparent knockdown of SDR9C7 coupled with ichthyosis symptoms indicates a strong link between SDR9C7 mutations and ichthyosis. Downregulation of SDR9C7 by small interfering RNA techniques in three-dimensional organotypic skin construction in in vitro keratinocytes also led to similar morphological and histological abnormalities in ichthyosis patients [73]. Takeichi et al. [72] carried out liquid chromatography–mass spectrometry (LC-MS) quantitative assays on epoxy-enone-CerEOS in SDR9C7-mutated patients and SDR9C7-KO mice. The disappearance of epoxy-enone-CerEOS, compared with a higher abundance of other acylceramides related to the lipoxygenase pathway in these cases, verified ADR9C7 as being a critical requirement for production of epoxy-enone-CerEOS, which is known for its nonenzymatic coupling to proteins [72]. Mutations of the SDR9C7 family are strongly associated with Mendelian disorders of cornification, a highly heterogeneous group of diseases [74]. Collectively, constructions of CerEOS with proteins, which ensure epidermal barrier integrity, are severely dependent on SDR9C7. In 1986, Philip et al. [24] reported the irreplaceable position of hydroxylated ceramides in CLE lipids. In the same year, Philip et al. continued to verify that the bound lipids are mostly composed of ω-OH-Cer (53.3%) and ω-hydroxyacid-containing (24.8%) Cer in human SC, via traditional quantitative thin-layer chromatography coupled with gas–liquid chromatography [75]. This innovative discovery, at the time, attracted much interest regarding ω-OH-Cer in the SC, and, therefore, gave a primitive guide for identification studies of ω-OH-Cer. The identification and quantification of small biomolecules such as ceramides can be analyzed via a wide array of analytical methods, such as gas chromatography–mass spectrometry (GC-MS), LC-MS, and high-performance thin layer chromatography (TLC) coupled with MS detection. Herein, the following part will discuss these methods for ω-OH-Cer identification. Hopefully this will be an inspiration for further study. Conventional techniques, for instance, ultraviolet spectroscopy (UV) analysis, have been used as the standard method for ω-OH-Cer identification. However, the accuracy and stability of MS has gradually led to it becoming the technique of choice for structural analysis. Especially when it comes to isomer discrimination, the regular fragmentation makes the identification easier and more specific for detail picturing [76]. There is a small body of work reporting GC-MS for the qualitative study of ω-OH-Cer. Without derivation, lipids are fragile, since they are non-volatile and instable [77]. Commonly, the GC-MS analysis method for ω-OH-Cer identification is developed together with other ceramides. Since ceramides do not show sufficient volatility, derivation is essential for GC analysis. Over the years, methods have been used in order to realize perfect derivations, such as yielding trimethylsilyl derivatives [78] and permethylated ceramides [77]. Due to its complexity and instability, GC-MS commonly displays lower efficiency and adaptability for Cer analysis than LC-MS. In the early stage of Cer analysis, GC was chosen for analysis, due to its cheap cost [79,80]. Modifications of LC systems have drawn more researchers to lean towards LC-MS as the more preferred method for ω-OH-Cer analysis. With the rapid development of lipidomics in recent decades, the number of LC-MS studies on ω-OH-Cer has gone through an exponential growth [81]. The LC separation system is based on different affinities of each component in two phases. The LC systems used can be divided into liquid–solid chromatography, liquid–liquid chromatography, and bonded-phase chromatography, according to the difference in stationary phases. The mostly adapted LC system comprises liquid–solid chromatography, where silica gel is applied as a filler in the columns, and bonded-phase chromatography, where micro silica gel is applied as a matrix for the columns [81]. One of the most important aspects of LC method optimization is to choose a suitable LC column. The choices of mobile phase and its matching ratio, column temperature, and flow rate are all variances for LC method optimization. Commonly, normal-phase (NP) LC and reverse-phase (RP) LC are all used to analyze ceramide. NP-LC distinguishes ceramides according to their hydrophilic functionalities [79], but it is more suitable for separating ceramides into their representative classes than coupling electrospray ionization (ESI), and achieves high sensitivity in mass spectrometry analysis. Furthermore, to separate ω-OH-Cers, a Cer class, NP-LC narrows the elution time to a narrow range, making it difficult to identify each molecule [82]. Conversely, RP-LC realizes the separation of ceramides based on their hydrophobic properties. Depending on mainly the carbon chain length and number of unsaturated bonds, RP-LC significantly raises the separation efficiency for weakly intrinsic hydrophilic biomolecules such as ω-OH-Cers. Likewise, RP-LC improves the higher peak capacity for lipid species [83]. TLC, a traditional and practical means for separation and quantification, has also been applied in ω-OH-Cer analysis for years [81,83]. By comparing the migration front (Rf) with known and available standards, the identification of the Cer class can be achieved [76]. However, TLC suffers as a technique due to the lack of maturity, and thorough and commercialized standards. Luckily, TLC coupled with further identification or validation, namely, MS, technology can overcome this problem. MS is a method to analyze and identify samples by measuring and analyzing the mass-to-charge ratio (m/z) of sample ions. There are three main parts of MS: the ion source, mass analyzer and detector. The mass analyzer is the core component of the mass spectrometer, which determines the sensitivity, resolution, and accuracy. Prior to analysis, the sample must be ionized so that the sample molecules will be charged [80]. Then, the charged ions are first driven by an accelerated electric field and fly into the analysis electric field or magnetic field. Due to the difference in the quality of the sample itself and the ionization charge, the motion trajectories of the sample ions in the analytical electric field are also different, so different ions can be distinguished by analyzing the motion trajectories of the ions, and the information, purity and other characteristics of the sample can be qualitatively and quantitatively determined. The two ion modes in MS, which are the positive mode and negative mode, are separately adapted for their own utilities [84]. Commonly, ω-OH-Cers are analyzed under positive mode, due to its high sensitivity and ability to help characterize the protonated (i.e., [M+H]+) and lithiated (i.e., [M+Li]+) states of the molecular species at low collision energy range [81]. Negative mode stands out for its high efficiency characterizing molecular structures [85]. With the participance of acetic acid (or formic acid), ions in negative mode are detected as adduct [M+CH3CO2]− ions, which are dissociated into [M−H]− for further structure analysis. Unfortunately, the diversification of analytical methods still has not garnered the best method for ω-OH-Cer detection. With more reports on ω-OH-Cer, this research gap will hopefully be fulfilled by further refined methods for the identification and separation of ω-OH-Cer. ω-OH-Cer has gained increasing attention. The unique function of ω-OH-Cer makes this class of Cer molecules vital for epidermal barrier formation and reconstruction. With more experimental and clinical practices on the effect ω-OH-Cer has for skin integrity, the lipid research has now progress into a new stage, where detailed and specific sphingolipid classes should be further studied. In this review, the detailed mechanism of ω-OH-Cer biosynthesis and its role are discussed. Hydroxylation gives ω-OH-Cer more biological potential. Correspondingly, the identification of ω-OH-Cer in studies in recent years has gained more attention. MS technology for qualification in biological samples is impressive, but still faces many challenges. This review aimed to garner inspiration for more specific research on ω-OH-Cer in epidermal integrity.

PMC10003400

Lukasz Dobrek,Krystyna Głowacka

Depression and Its Phytopharmacotherapy—A Narrative Review

01-03-2023

depression,treatment,medicinal plants,herbal,antidepressant

Depression is a mental health disorder that develops as a result of complex psycho-neuro-immuno-endocrinological disturbances. This disease presents with mood disturbances, persistent sadness, loss of interest and impaired cognition, which causes distress to the patient and significantly affects the ability to function and have a satisfying family, social and professional life. Depression requires comprehensive management, including pharmacological treatment. Because pharmacotherapy of depression is a long-term process associated with the risk of numerous adverse drug effects, much attention is paid to alternative therapy methods, including phytopharmacotherapy, especially in treating mild or moderate depression. Preclinical studies and previous clinical studies confirm the antidepressant activity of active compounds in plants, such as St. John’s wort, saffron crocus, lemon balm and lavender, or less known in European ethnopharmacology, roseroot, ginkgo, Korean ginseng, borage, brahmi, mimosa tree and magnolia bark. The active compounds in these plants exert antidepressive effects in similar mechanisms to those found in synthetic antidepressants. The description of phytopharmacodynamics includes inhibiting monoamine reuptake and monoamine oxidase activity and complex, agonistic or antagonistic effects on multiple central nervous system (CNS) receptors. Moreover, it is noteworthy that the anti-inflammatory effect is also important to the antidepressant activity of the plants mentioned above in light of the hypothesis that immunological disorders of the CNS are a significant pathogenetic factor of depression. This narrative review results from a traditional, non-systematic literature review. It briefly discusses the pathophysiology, symptomatology and treatment of depression, with a particular focus on the role of phytopharmacology in its treatment. It provides the mechanisms of action revealed in experimental studies of active ingredients isolated from herbal antidepressants and presents the results of selected clinical studies confirming their antidepressant effectiveness.

Depression and Its Phytopharmacotherapy—A Narrative Review Depression is a mental health disorder that develops as a result of complex psycho-neuro-immuno-endocrinological disturbances. This disease presents with mood disturbances, persistent sadness, loss of interest and impaired cognition, which causes distress to the patient and significantly affects the ability to function and have a satisfying family, social and professional life. Depression requires comprehensive management, including pharmacological treatment. Because pharmacotherapy of depression is a long-term process associated with the risk of numerous adverse drug effects, much attention is paid to alternative therapy methods, including phytopharmacotherapy, especially in treating mild or moderate depression. Preclinical studies and previous clinical studies confirm the antidepressant activity of active compounds in plants, such as St. John’s wort, saffron crocus, lemon balm and lavender, or less known in European ethnopharmacology, roseroot, ginkgo, Korean ginseng, borage, brahmi, mimosa tree and magnolia bark. The active compounds in these plants exert antidepressive effects in similar mechanisms to those found in synthetic antidepressants. The description of phytopharmacodynamics includes inhibiting monoamine reuptake and monoamine oxidase activity and complex, agonistic or antagonistic effects on multiple central nervous system (CNS) receptors. Moreover, it is noteworthy that the anti-inflammatory effect is also important to the antidepressant activity of the plants mentioned above in light of the hypothesis that immunological disorders of the CNS are a significant pathogenetic factor of depression. This narrative review results from a traditional, non-systematic literature review. It briefly discusses the pathophysiology, symptomatology and treatment of depression, with a particular focus on the role of phytopharmacology in its treatment. It provides the mechanisms of action revealed in experimental studies of active ingredients isolated from herbal antidepressants and presents the results of selected clinical studies confirming their antidepressant effectiveness. Depression is a major mood disorder presenting with a persistent feeling of sadness, debilitating low mood, impaired cognition and loss of interest. Depression has a profound effect on the functioning of the affected person, individually, biologically and socially. Depression involves deep sadness, hopelessness, sorrow, emptiness and despair. Over time, it may also involve an inability to experience pleasure, psychomotor dysfunction, changes in sleep and eating behaviours, difficulty concentrating and suicidal thoughts [1]. In fact, depression belongs to a heterogeneous group of diseases, broadly included in the International Classification of Diseases (ICD) published by the World Health Organization (WHO). The current ICD-11 version distinguishes a few depressive disorders: single episode depressive disorder (moderate, without psychotic symptoms, or severe, with or without such symptoms) and recurrent depressive disorder (current episode moderate, without psychotic symptoms, or severe, with or without such symptoms, or recurrent depressive disorder currently in full remission, or unspecified recurrent depressive disorder). Moreover, there are other different forms of depression, such as dysthymic disorder (persistent depressive disorder), mixed depressive and anxiety disorder, other specified depressive disorders and unspecified depression [2]. As presented in this review, depression is currently one of the most important diseases of civilization and a significant public health problem. Therefore, it seems important to perform a periodic, comprehensive analysis focusing on the description of this disease and its therapeutic management options, taking into account phytopharmacotherapy, which is less popular in everyday clinical practice. This paper aims to briefly summarize the most important issues concerning the epidemiology, pathophysiology, symptomatology and treatment of depression. It also discusses the importance of phytopharmacotherapy in treating this disease and provides an outline of the phytopharmacodynamics of medicinal plants with antidepressant activity, with particular emphasis on the importance of their anti-inflammatory effect. This narrative review employs the traditional, non-systematic literature review method (PubMed, Google Scholar databases) with the use of the following search terms and their combinations: “depression”, “epidemiology”, “pathophysiology”, “symptomatology”, “management”, “treatment”, “medicinal plants”, “phytopharmacotherapy”, “phytopharmacodynamics”. The selection of relevant articles for review based on their titles and abstracts by one author (LD) was supervised critically by the second author (KG). Both review articles and original full-text articles were taken into account, preferring search results from the last ten years, but also including older papers, which, according to the authors, introduced important information to the discussion. At the same time, the performed literature screening revealed some papers analogous to our forthcoming review, e.g., Pardhe et al. [3] or Martins and Brijensh [4] and others. These papers describe the phytopharmacodynamics of many different plants with antidepressant activity, mostly focusing on their effect on disturbances of neurotransmission in the CNS found in depression. However, we made efforts to prepare a comprehensive review, discussing phytopharmacotherapy of depression against the background of a broader introduction to the epidemiology, symptomatology and pathophysiology of this disease, focusing the description of phytopharmacodynamics also on other aspects less frequently addressed in other papers, such as the contribution of the anti-inflammatory properties to the antidepressant effect. According to the WHO (data as of 13 September 2021), depression affects 3.8% of the world’s population, including 5.0% of adults and 5.7% of adults over 60 years. Approximately 280 million people worldwide suffer from depression. The disease is a leading cause of disability worldwide and is a major contributor to the overall global burden of disease. More women are affected by depression than men [5]. A population-based study in Europe using data from 27 countries collected between 2013 and 2015 showed that the overall prevalence of the current depressive disorder is high (6.38%), with important variation across European countries, ranging from 2.58% in the Czech Republic to 10.33% in Iceland. Similarly to the WHO data, the study demonstrated higher depression prevalence in women (7.74%) compared to men (4.89%), with clear gender differences for all countries, except Finland and Croatia [6]. Estimates for Poland indicate that around 1.5 million people suffer from depression, and this disease affects approximately 3% of people of productive age (i.e., 766,000 adult Poles had at least one depressive episode in their lives) [7]. Outside Europe, the prevalence of depression is equally high. According to the National Center for Health Statistics of the Centers for Disease Control and Prevention (CDC), 8.1% of adults aged 18 and over had symptoms of anxiety disorder, 6.5% of depressive disorder and 10.8% of anxiety disorder or depressive disorder in the USA in 2019 [8]. In the Asia-Pacific region, the prevalence of 1-month major depression ranged from 1.3% to 5.5%, and rates of major depression ranged from 1.7% to 6.7% [9]. Ogbo et al. estimated the prevalence of depressive disorders in South Asia as high as 3.9%, 4.4% in Bangladesh, 3.9% in India, 3.0% in Pakistan, 4.0% in Nepal and 3.7% in Bhutan [10]. In Latin America and the Caribbean, depression affects 5% of the adult population. Moreover, six out of every ten people do not receive treatment [11]. In South Africa, an estimated 9.8% of the adult population experience major (clinical) depression at some point in their life [12]. The pooled prevalence of depression among older adults in Africa was estimated to be even higher, reported at 26.3% [13]. In Australia, 9.4% of males aged 16–85 and 12.8% of females of the same age experienced a depressive episode in their lives [14]. Thus, it should be concluded that depression is a serious disease of civilization. As early as 2006, the WHO estimated that depression would cause the second largest increase in morbidity after cardiovascular diseases and pose a significant public health challenge [15]. There are some biological (including genetic abnormalities, microbiome disturbances, inflammatory factors, stress and dysfunction of the hypothalamic–pituitary–adrenal (HPA) axis and the kynurenine pathway), psychological and social determinants of depression. Depression may also secondarily develop in the course of many somatic or mental diseases. In fact, depression, or collectively named depressive disorders, cannot be explained by a single theory since many variables are involved in the entity’s initiation and sustainment. This paper does not provide a detailed description of the pathophysiology of depression, which can be found in numerous reviews on this issue. Only selected aspects of the pathophysiology of depression are briefly mentioned below. There are some biological theoretical frameworks for the explanation of the onset of depression. The most common biochemical, neurophysiological explanation for depression is the deficit of monoamines (serotonin, noradrenaline, dopamine), which play a key role in important life-regulating functions (appetite, sleep, memory, learning, temperature regulation, social behaviour). The insufficiency of these monoamine neuromodulators in definite structures of the central nervous system is considered to be responsible for the development of depression [16]. This monoamine hypothesis of depression was historically the first theory proposed by Joseph Schildkraut in the 1960s and was based on the successful use of iproniazid (a monoamine oxidase inhibitor) and imipramine (a monoamine neuromodulator reuptake inhibitor) in the treatment of depression [17,18,19]. This theory is consistent with clinical observations—designed tricyclic antidepressants and monoamine neuromodulator reuptake inhibitors have confirmed the important role of imbalance and neuromodulator deficiency. For many years, the monoamine theory was the basic paradigm setting the ground rules in the treatment of depression. Moreover, the stress-induced overactivity of the HPA axis was also revealed to be involved in the pathophysiology of depression. Significant correlations between measures of stress and depressive behaviour and between cortisol levels and depressive behaviour were found in experimental studies [20]. Influencing the HPA axis and reducing its activity may become another therapeutic option in treating depression [21]. This direction seems to be particularly interesting and promising, especially considering the secondary relationship between the activity of the HPA axis and the gut microbiota. It is believed that the gut microbiota can influence the HPA axis function through the activity of cytokines, prostaglandins or bacterial antigens of various microbial species [22]. Also, both experimental and clinical studies indicate that inflammatory processes may play a causal role in the development of depressive illness. There is growing evidence that immune system disturbances are involved in the development of depression. Various immune cytokines released during systemic, “low grade” and self-sustaining inflammation have been found to be implicated in the pathophysiology of depression, including interleukins (IL)-1, IL-2, IL-4, IL-6, IL-8 and IL-10; interferon-gamma (IFN-γ); C-reactive protein (CRP); tumour necrosis factor-alpha (TNF-α); and monocyte chemoattractant protein-1 (MCP-1) [23,24]. The peripherally released cytokines may pass the blood–brain barrier, activating glial cells and leading to a neuroinflammatory process contributing to brain damage [24,25]. There is also evidence that central neurotransmission disturbances are associated with secondary disturbances concerning relevant cytokines, e.g., serotonin deficiency, contributing to the feeling of sadness, guilt and worthlessness and disturbed appetite related to Il-6, Il-18, TNF-α and CRP abnormalities. Sociability dysfunction, due to lower dopamine levels, was demonstrated to correlate with the disturbances within INF-γ, Il-17, Il-33 and CCR6 and impaired functioning of Th1 and Th17 cells. Some symptoms depend on multiple neurotransmitters, such as psychomotor retardation (manifested by INF-γ, TNF-α, Il-1β and Il-6 disturbances) regulated by serotonin, dopamine, norepinephrine and glutamate [26]. It is noteworthy that antidepressant treatment affects the level of cytokines. A meta-analysis of 32 clinical studies by Więdłocha et al. [27] demonstrated significant decreases in IL-4, IL-6 and IL-10 in major depressive disorder (MDD) subjects after antidepressant treatment. In the case of IL-1ß, the decrease was significant exclusively for SSRI drugs. Moreover, the activation of the kynurenine pathway and reduced tryptophan levels correlate with inflammation-induced depression, as the kynurenine pathway is believed to precipitate depressive symptoms by depleting brain serotonin [28]. Multiple endogenous and environmental factors appear to increase the risk of developing depression and seem to be associated with systemic inflammation; these include psychosocial stressors, poor diet, physical inactivity, obesity, smoking, altered gut permeability, atopy, dental caries, sleep and vitamin D deficiency [29]. Oxidative stress (OS) is a supplementary mechanism involved in the pathophysiology of depression because OS is closely related to the inflammatory process. In the course of an inflammatory process, positive reciprocal action is established—inflammatory mediators intensify the synthesis of free radicals (mainly reactive oxygen/nitrogen species), which in turn sustains inflammation and the release of pro-inflammatory mediators. The limbic brain regions (prefrontal cortex, hippocampus and amygdala) involved in mood and behaviour control are highly susceptible to oxidative damage. Previous studies mention the implication of OS in neurodegenerative and psychiatric disorders, including depression [30,31]. Moreover, excessive and prolonged stress negatively impacts the immune system, which in turn affects the HPA axis. Both factors lead to neurological impairments in the brain, causing changes in mood and behaviour [32]. There is also a relationship between systemic inflammatory alterations and gut microbiota. The gut and brain are two structures connected at multiple levels. The microorganisms inhabiting the gut and their products are essential in this bidirectional communication, conforming to the microbiota–gut–brain (MGB) axis [33,34]. Depressed patients show significant changes to the gut microbiota (dysbiosis) in comparison to healthy patients, leading to a pro-inflammatory status and neuroinflammation, enhancing the HPA axis dysfunction and stress sensitivity in the brain and disrupting the gut–brain communication through the vagus nerve, hence contributing to the pathogenesis of MDD [35]. In addition, an altered immune status described in MDD is responsible for an enhanced bacterial translocation in the bloodstream, aggravating the systemic damage in depressed patients [36]. Moreover, there is growing evidence of an important role of gut microbiota in the production or degradation of multiple neurotransmitters, including serotonin, norepinephrine, dopamine or gamma-aminobutyric acid (GABA) [37], defining the gut microbiota as a critical modulator of brain activity. The contribution of reproductive hormones to mood has also been a focus of efforts to explain the detailed pathophysiology of depression. Recent longitudinal studies have found that women are more susceptible to higher levels of depressed mood during the menopausal transition than just before it starts, suggesting differences in the prevalence of depression in relation to the sex of the patients [38]. In addition, significant decreases in oestrogen production, an overall state of hypogonadism, stability in the hypothalamic–pituitary–gonadal axis and elevated FSH are marks of menopause. The decreased circulating androgen levels associated with menopause have also been linked to the loss of libido, fatigue and an increase in depressive symptoms [39]. Family and twin studies have provided strong evidence for the involvement of genetic factors in the risk of depression. Twin studies have demonstrated that the heritability rate of depression is about 37%, and data from family studies indicate a two- to three-fold increase in the risk of depression in the first-degree offspring of depressed patients [40]. Heredity has also been shown to particularly affect severe forms of depression [41]. In most cases of depression, estimates indicate that about 50% of the causes are genetic, and about 50% are unrelated to genes (psychological or physical factors). Genetic background is especially suspected in patients whose parent or sibling has suffered from depression more than once (“recurrent depression”) and if the depression started relatively early in life (in childhood, teenage years or twenties). However, there is no one “depressive gene”. Some of the possible genetic causes include the role of polymorphisms in genes related to the neurotransmission of serotonin, norepinephrine and dopamine, such as serotonin transporter gene variants that inhibit serotonin reuptake, leading to a deficiency of monoamines in the brain and thus predisposing to depression. Another possibility is a polymorphism in genes regulating nervous system development, leading to a deficiency in the number of neurons in the adult brain or in genes regulating anti-inflammatory cytokines secreted in a compensatory manner to counteract inflammation. Further, genes that regulate circadian rhythms are another potential cause of genetic predisposition to depression by interfering with normal sleep and other bodily functions that depend on the circadian pacemaker. Furthermore, in terms of genetic abnormalities, there are also links between genetic factors and depression; for example, abnormalities in brain-derived neurotrophic factor (BDNF) appear to play an important role in depression. The “BDNF theory” of depression results from preclinical studies demonstrating that several forms of stress reduce BDNF-mediated signalling in the hippocampus, whereas chronic treatment with antidepressants increases BDNF-mediated signalling. Treatment with antidepressants increases several growth factors in the hippocampus that influence neurogenesis. These include BDNF (which promotes neuronal survival) and vascular endothelial growth factor (VEGF) [42]. However, there are also studies revealing that male mice with conditional forebrain deletions of BDNF or its receptor do not show depression-like behaviour [43]. Moreover, the action of BDNF may be brain region dependent—in the ventral tegmental area (VTA) and nucleus accumbens (NAc), BDNF exerts a potent pro-depressant effect, and the direct infusion of BDNF into the VTA–NAc increases depression-related behaviours [44]. These results suggest that the current formulation of the BDNF hypothesis of depression development is too simplistic. BDNF-mediated signalling is involved in neuroplastic responses to stress and antidepressants, but these effects are both region- and antidepressant-specific [42]. In the neurobiology of depression, at the cellular and molecular levels, a number of signalling pathways and targets have been suggested as implicated in the pathogenesis of depression, including the above-mentioned neurotrophic factor and glycogen synthase kinase 3 (GSK3) pathways. The functional consequences of these systems in the context of the damaging effects of chronic stress, including atrophy and loss of neurons and glia, were also observed in brain imaging and postmortem studies of depressed patients [45]. In addition, there are links between genes of the core region of the tissue compatibility system, as well as various gene polymorphisms and depression. Single nucleotide polymorphisms (SNPs) of genes involved in the tryptophan catabolism pathway are also being investigated [46,47,48]. An important role in the current description of depression is also played by epigenetics, i.e., the science dealing with inherited changes in gene expression unrelated to changes in the DNA sequence, examining the mechanisms of interaction between genes and their products in phenotype formation. Thus, epigenetics is the study explaining the cellular control of gene activity without changing the DNA sequence [49]. Epigenetic mechanisms include histone acetylation, which changes the structure of chromatin; cytosine methylation in DNA (in areas rich in the sequence of dinucleotides (cytosine-phosphate group-guanine)), which prevents gene transcription; and the influence of the non-coding microRNA binding complementary to mRNA, thus regulating translation [50]. Experimental studies indicate that genetic and environmental risk factors and their interactions induce aberrant epigenetic mechanisms targeting stress response pathways, neuronal plasticity and other behaviourally relevant pathways involved in major depression. The role of epigenetics in depression pathogenesis would explain the differences in the incidence of this disease in monozygotic twins. The involvement of epigenetic mechanisms in depression pathogenesis also offers an explanation of largely inconsistent genetic association studies of depression, for example, by undermining the transcriptional impact of DNA sequence polymorphisms due to epigenetic modifications on those gene promoters [42,51]. In addition, growing clinical data indicate that the analysis of epigenetic changes in patients with depressive disorders can be not only a marker of clinical improvement, but also a predictor of response to pharmacological treatment. It is suggested that the use of histone deacetylase inhibitors (natural or synthetic small molecules that can inhibit the activity of deacetylases and affect the availability of chromatin for transcription factors) may become a novel method of treating depression and other affective disorders [52]. Finally, the description of the pathophysiology of depression also takes into account social and psychological issues. According to attachment theory, depression is determined by a person’s inability to establish strong and long-lasting affective bonds with other people. The attachment model postulates that vulnerability to depression stems from early experiences that did not meet the child’s need for security, care and comfort, as well as the current state of their intimate relationships. The links between secure attachment and depression also appear to be mediated by the development of maladaptive beliefs or schemas [16]. Complex and incompletely understood psychological and social maladjustment can result in anaclitic depression, which arises from feelings of loneliness and abandonment, and introjective depression, which stems from a sense of failure and worthlessness [53]. There are also studies focusing on the importance of circadian rhythms and its main mediator, melatonin, in the onset and development of the disease [54]. Based on this hypothesis, some melatonin receptor agonists (ramelteon, tasimelteon) have been introduced into clinical practice in the treatment of sleep disturbances, and those acting additionally as serotonergic antagonists (agomelatine), which display antidepressant properties [55]. To sum up, the pathophysiology of depression is multifactorial, and the treatment of this mental illness remains a challenge. Many causative, interrelated factors are implicated in depression pathogenesis, as shown in Figure 1. To underline its complexity, a “psycho-neuro-immuno-endocrinological” term has been introduced to describe depression [56]. The main pathomechanisms of depression have focused on impaired monoamine function, decreased monoamine production, malfunction of the secondary messenger system or changes in other neurotransmissions. A significant role in the pathogenesis of depression is also attributed to inflammation and oxidative stress, which exert a major influence, affecting the proper functioning of the brain. Additional attention has also been given to endocrine abnormalities (excessive cortisol levels) or impaired neurogenesis through reduced levels of the brain-derived neurotrophic factor. The role of abnormal circadian rhythm is also highlighted [15]. Depression manifests itself in a variety of both somatic and psychological symptoms. The disease also has a huge impact on the social and professional functioning of the patient. The typical psychological symptoms of depression include continuous low mood or sadness, with a dominant feeling of hopelessness, helplessness and guilt, feeling worried and/or anxious, poor concentration, lack of motivation to undertake everyday activities and loss of previous interests. In addition, patients with depression may feel overwhelmed, restless or angry and lack confidence. The somatic symptoms include sleep abnormalities, such as insomnia or hypersomnia (many patients experience early morning awakenings; there are also patients who tend to feel sleepy during the day), changes in appetite or body weight (usually reduced, but sometimes increased), feelings of low energy or adynamia, low sex drive (loss of libido), changes in the menstrual cycle and constipation. Social symptoms of depression include avoiding contact with friends and participating in fewer social activities; neglecting hobbies and interests; and difficulties at home, work or family life as a result of chronic emotional disorders affecting the ability to maintain family contacts and professional activity. Usually, depressive patients may also present altered behaviour, such as staying in rather than going out and being less productive at school or work. Depression may also take on an atypical form, manifesting itself by increased mood reactivity (i.e., mood brightens in response to positive events) and increased appetite; sleeping longer; leaden paralysis (i.e., heavy, leaden feelings in arms or legs); and interpersonal rejection sensitivity (not limited to episodes of mood disturbance), resulting in significant social or occupational impairment [57]. Depending on the number and severity of the above-mentioned symptoms, depression can be mild, moderate or severe, with possible suicide attempts. As an aside, it should also be mentioned that depression in some patients may be “masked”, especially in the form of purely somatic disorders in the elderly [58,59,60]. Noteworthy, increased alcohol dependence was demonstrated in the course of depression—the prevalence of depression among alcohol-dependent persons is high (estimated at 63.8%) [61]. The treatment of depression involves both pharmacological and non-pharmacological methods, including, in particular, techniques of therapeutic psychotherapeutic influence. The concept of “collaborative care” is the basis for the comprehensive treatment of depression. Psychological therapy should be the main treatment for mild depression or complementary to pharmacological treatment in other cases. There is strong evidence for the effectiveness of combined pharmacological antidepressants and cognitive behaviour therapy over the sole use of antidepressants in moderate to severe depression and chronic depression [62]. There are several classes of antidepressants used in the pharmacotherapy of this disorder, including selective serotonin reuptake inhibitors (SSRIs), tricyclic antidepressants (TCAs), serotonin and noradrenaline reuptake inhibitors (SNRIs), noradrenaline reuptake inhibitors (NRIs) and noradrenaline and dopamine reuptake inhibitors (NDRIs). These drugs inhibit the transporters responsible for the reuptake of monoamines [63]. There are also other drugs with antidepressant effects (e.g., agomelatine, an MT1 I MT2 melatonin receptor agonist and serotonin 5HT2 receptor antagonist, or mirtazapine, an antagonist of adrenergic alpha2-autoreceptors, alpha2-heteroreceptors, 5-HT2 and 5-HT3 receptors) [63]. Recent antidepressants include desvenlafaxine, levomilnacipran, vortioxetine or vilazodone [64]. Selective serotonin reuptake inhibitors (SSRIs) are considered by general practitioners to be first-line drugs in the treatment of outpatients with depression. All antidepressants are regarded to be more effective than a placebo in adults treated for depression. In a systematic review and meta-analysis by Cipriani et al. [65], agomelatine, amitriptyline, escitalopram, mirtazapine, paroxetine, venlafaxine and vortioxetine were found to be more effective than other antidepressants, while fluoxetine, fluvoxamine, reboxetine and trazodone were found to be the least effective. However, larger differences in the efficacy and acceptability of individual antidepressants were revealed in head-to-head trials. For acceptability, agomelatine, citalopram, escitalopram, fluoxetine, sertraline and vortioxetine were better tolerated than other antidepressants, while amitriptyline, clomipramine, duloxetine, fluvoxamine, reboxetine, trazodone and venlafaxine had the highest dropout rates [65]. Taking into account the clinical picture of depression, the response to initial treatment and the patient’s comorbidities, a precise choice of medication is made, and the effect of treatment is assessed after an appropriate period of follow-up. It should be stressed that antidepressants, like other pharmacological agents, exert some adverse drug reactions (ADRs). The most common ADRs observed in patients treated with SSRIs (e.g., paroxetine, sertraline, fluoxetine, escitalopram) at the primary care outpatient clinics were: gastrointestinal problems (in 17% of subjects), indigestion (22%), nausea (18%), diarrhoea (9%) and constipation (11%). Moreover, tiredness (in 45% of subjects), dizziness (24%), hypotension (15%), headache (34%) and blurred vision (22%) were also reported [66]. SSRIs are generally better tolerated than other antidepressants. The less common ADRs reported in the literature include extrapyramidal symptoms (EPS), serotonin syndrome, QT prolongation, rash, birth defects, hyponatraemia and cataracts [67]. Tricyclic antidepressants show more pronounced side effects due to their complex mechanism of action and receptor non-selectivity. The most common adverse effects include constipation, dizziness and xerostomia. Due to their cholinolytic potential, TCAs may also produce blurred vision, constipation, xerostomia, confusion, urinary retention and tachycardia. Moreover, due to the blockade of alpha-1 adrenergic receptors, orthostatic hypotension and dizziness may develop. TCA-induced histamine blockade (H1) contributes to sedation, increased appetite, weight gain and confusion. TCAs may also cause cardiovascular complications, including arrhythmias, such as QT prolongation, ventricular fibrillation and sudden cardiac death in patients with pre-existing ischaemic heart disease. In addition, treatment with TCAs may be associated with mild liver enzyme elevation [68]. Detailed recommendations for pharmacotherapy of depression are beyond the scope of this paper and can be found in numerous guidelines, including those published by psychiatric scientific societies [69,70,71,72], such as the Polish Society of Psychiatry [73]. Non-pharmacological interventions also play an important complementary role in the comprehensive treatment of depression. They include primarily psychotherapeutic techniques (e.g., cognitive behavioural therapy, naturopathic therapy, physical activity interventions or acupuncture) [74,75]. Some studies demonstrate the benefits of some dietary supplements on depressed mood. They are based on the polyunsaturated fatty acids (PUFAs), combining eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), and probiotics, which is in line with the assumption that inflammation and dysfunction of the gut–brain axis are pathogenetic elements of depression [76]. Other highly promising dietary interventions studied for potential use in depressive patients involve a specific group of nutrients (vitamins, polyphenols and caffeine), foods (fish, nuts, fruit seeds and vegetables, coffee/tea and fermented products) or dietary supplements (such as S-adenosylmethionine, acetylcarnitine, creatine, amino acids, etc.) [77]. In severe cases of depression refractory to classical pharmacological treatment, advanced non-pharmacological techniques, such as repetitive transcranial magnetic stimulation (rTMS) or electroconvulsive therapy (ECT), are also used [78,79]. Systematic reviews and meta-analyses demonstrated that both techniques are effective in depression treatment, with ECT superior compared to rTMS. Although ECT was the most efficacious, it was the least tolerated treatment, while rTMS was the best-tolerated treatment for MDD [80,81]. There is now an upward trend in the number of prescriptions for antidepressants globally. The number of prescriptions for antidepressants in England has almost doubled over the past decade. As many as 70.9 million prescriptions for antidepressants were registered in 2018, up from 36 million in 2008 [82]. From 2009–2010 through 2017–2018, the proportion of adults treated with antidepressants also increased in the USA. According to an analysis by the National Center for Health Statistics, in 2017, the percentage of the US population over the age of 12 years who had taken antidepressants in the past month was estimated at 12.7% [83]. According to “The state of mental health in America 2022” [84], 15.08% of youth experienced a major depressive episode in the past year, and 24.7% of adults with a mental illness reported an unmet need for treatment. European data also indicate high use of antidepressants. In a large general population study from 27 European countries that measured antidepressant use and regularity of use, 7.2% of participants reported taking antidepressants in the past year. There were large differences in the prevalence of antidepressant use between countries, ranging from 15.7% in Portugal to 2.7% in Greece. The top five European countries in terms of the use of antidepressants in the last 12 months were Portugal, Lithuania, Malta, the UK and France. In contrast, the five countries with the lowest use of antidepressants in the last 12 months were Greece, Germany, Bulgaria, Cyprus and the Czech Republic. In this respect, Poland was ranked 19th among the 27 countries assessed. In contrast, the countries with the highest proportion of patients regularly taking antidepressants were Sweden, the United Kingdom, Denmark, Finland and the Netherlands. The countries with the lowest percentage of patients regularly using antidepressants were Bulgaria, Romania, the Czech Republic, Lithuania and Slovakia. In this respect, Poland also took 19th place in the ranking (out of all 27 countries assessed) [85]. It should be strongly emphasized that antidepressants are drugs that produce significant, numerous adverse drug reactions, especially in patients using polypharmacy. The most common adverse effect reported by patients was weight gain after TCAs, followed by sexual dysfunction for SSRIs, nausea or vomiting for monoamine oxidase inhibitors (MAOIs) and headache for SNRIs [86]. Notably, TCAs were associated with a wide range of ADRs, such as toxic delirium, grand mal seizures, increased liver enzymes, urinary retention, flushing or cardiovascular disorders (i.e., mainly orthostatic collapse). Psychological and neurological ADRs were the most common in SSRI-treated patients, followed by gastrointestinal, dermatological and endocrine/electrolyte reactions, with agitation, hyponatraemia, increased liver enzymes, nausea and serotonin syndrome as leading adverse effects [87]. In the study by Uher et al. [88], ADRs induced by nortriptyline or escitalopram were assessed on the basis of the Antidepressant Side-Effect Checklist and the psychiatrist-rated UKU Side Effect Rating Scale. Dry mouth (74%), constipation (33%) and weight gain (15%) were associated with nortriptyline treatment. Diarrhoea (9%), insomnia (36%) and yawning (16%) were more common during treatment with escitalopram. Problems with urination and drowsiness predicted discontinuation of nortriptyline, while diarrhoea and decreased appetite were the main causes of discontinuation of escitalopram. Given the high use of antidepressants and their possible side effects, other treatment options for depression are being explored, including the use of herbal medicines. Therefore, phytopharmacotherapy is a promising therapeutic option that appears to be a safer alternative, particularly for patients with mild depressive disorders or for seasonal dysthymia (“winter depression”). For centuries, people have tried to treat depression with available remedies of natural origin used as part of traditional medicine. In different cultures and geographic regions, certain medicinal plants have been known and used to treat many different conditions. Estimates indicate that of the more than 300,000 seed plants, approximately 60% have been used for their medicinal properties [89]. In some regions (especially Africa, South America and Asia), the use of traditional medicine systems (including medicinal plants) based on social and ethnic continuity and empirical findings is the main therapeutic approach. Ethnomedicine (ethnopharmacology) has also distinguished medicinal plants as effective in the treatment of neurological and psychiatric disorders [90]. In summary, medicinal plants (“herbs”) contain various pharmacologically active compounds in their tissues: alkaloids, glucosides, essential oils, fatty oils, mucilages, tannins, gums, flavonoids, iridoids and bitters, saponins and others that cannot be separated into individual compounds. This fact distinguishes the mode of action of phytopharmaceuticals from classical, synthetic drugs—the pharmacological action mediated by phytopharmaceuticals is not mediated by just one compound, but is the result of the synergistic and polyvalent, complementary action of many active substances. On the contrary, the “mainstream” pharmacodynamic effect in classical pharmacology is based on an isolated, single active compound. A synergistic effect is defined as an effect produced by a combination of substances that is greater than would be expected if the combined action of the individual components were considered [15,91,92]. A complementary concept is the theory of the polyvalent action of phytopharmacological ingredients, which assumes that herbal extracts can exert a wide range of biological activity due to the variety of chemical compounds present in herbs, each of which produces different effects [15,93]. The synergistic and polyvalent effects of herbal compounds in the treatment of depression and other mental disturbances are becoming increasingly important. In a study by Kessler et al. [94], 54% of patients suffering from depression reported using herbal medicines in the past 12 months to treat their disorder. Similar to this finding, it was revealed that 44% of psychiatric inpatients hospitalized for acute care for various psychiatric disturbances had used herbal medicines in the previous 12 months [95]. Despite the popularity of herbal medicines in the treatment of depression, as well as other psychiatric disorders (such as anxiety or insomnia), research on phytopharmaceuticals in neuropsychology is not as advanced as for synthetic drugs. For the most part, the results of beneficial effects of phytopharmaceuticals in the treatment of nervous system disorders have been obtained in vitro or in preclinical studies in laboratory animals, with an abundance of clinical studies validating the efficacy and safety of phytopharmaceuticals in patients [15,96]. There is also well-established use of herbal medicines containing active substances dating back more than ten years, and their efficacy and safety have been well-established, so the use of such preparations is legally possible based on the results obtained from a review of the scientific literature. In addition, there is also traditional use of herbal medicines containing plants or parts or extracts of plants that have been traditionally used for centuries, and their administration for various clinical conditions is based on empirical evidence, which means that they are acceptably safe, although they do not have a precisely defined level of efficacy [97,98]. Most herbal medicines used in the phytopharmacology of depression are over-the-counter (OTC) preparations or dietary supplements and are considered safe and induce fewer ADRs compared to conventional medicines, especially TCAs (cholinolytic symptoms, sexual dysfunction, insomnia, withdrawal problems) [15,99,100,101]. Examples of OTC drugs or dietary supplements used for depression in Poland (the country of residence of the authors of this review) are summarized in Table 1. The examples of preparations listed there indicate that the most popular antidepressant preparations in Poland are based on St. John’s wort and saffron crocus, with the possible addition of lemon balm, B vitamins or amino acids that are sources of monoamines (tryptophan, phenylalanine). Preparations with similar compositions are used in other countries. In general, commercially available OTC drugs or dietary supplements usually contain various nutraceuticals, such as vitamins (including vitamin D and vitamin B group); S-adenosyl methionine (considered the universal methyl donor in living organisms); amino acids (phenylalanine, tyrosine and tryptophan); amino acids that are precursors of neurotransmitters (noradrenaline, serotonin); microelements (zinc, magnesium); and phytoceuticals (St. John’s wort, saffron crocus, turmeric, roseroot, lavender), often with the addition of adaptogenic ashwagandha and anxiolytic kava [102]. Unlike preparations in the Polish pharmaceutical market, foreign products are often enriched with omega-3 acids (e.g., EPA and DHA) because these nutrients can reduce inflammation in the brain, which may positively impact mood. Moreover, turmeric is rarely found in commercially available preparations popular in the Polish pharmaceutical market. Moreover, there is no preparation containing Piper methysticum (kava) in Poland due to the warnings issued by the European Safety Food Authority (ESFA) about the potential hepatotoxicity of kavalactones. Thus, kava cannot be a component of dietary supplements or OTC drugs in Poland, and its use in pharmaceuticals has been prohibited. However, later studies showed the hepatotoxicity of kava preparations obtained by extracting whole plants with organic solvents, while daily intake of kavalactones in the form of tablets obtained from a traditional aqueous plant extract was not harmful [103]. This resulted in the lifting of restrictive regulations on the import and trade of kava-based pharmaceutical products. Nowadays, kava trade is regulated by each country individually. In the further part of our review, we discuss the phytopharmacodynamics of the following plants with antidepressant activity: St. John’s wort (SJW), saffron crocus, lemon balm, lavender, gingko, Korean ginseng, roseroot, magnolia bark, borage, brahmi and mimosa tree. The use of herbal antidepressant preparations is characterized by greater safety compared to classic antidepressants, and this issue is one of the main advantages of phytopharmacotherapy. These preparations, which mostly have the legal status of dietary supplements, are available without a prescription and are perceived to be safe. However, all medicinal agents, including herbal preparations, have potential side effects. As with other drugs, the risk of adverse drug reactions may be influenced by a user’s age, gender, genetics, nutrition status and concurrent disease states and treatments. In clinical practice, recognizing adverse effects of herbal medicine is not routine, and their reporting is less frequent compared to synthetic drugs [104]. Among herbal antidepressants, the most recognized side effects are described for St. John’s wort, perhaps due to the fact that St. John’s wort (SJW) preparations, next to saffron-containing medicines, are the most popular plant antidepressants. The most commonly reported adverse reactions for SJW are gastrointestinal symptoms, allergic reactions, dizziness/confusion, tiredness/sedation and dry mouth. Hyperesthesia and a syndrome of dyspnoea and hyperventilation with flushing headache, mydriasis, nausea, palpitations and tremor have been also reported. The majority of these reactions were generally considered to be mild, moderate or transient. [105,106,107]. Data from observational studies have indicated that adverse events may occur in 1%–3% of patients treated with SJW preparations [108]. In the case of SJW, there is also the possibility of triggering a manic phase in the course of bipolar disorder [109]. In addition, the phytopharmacologically active components of SJW (hypericin and hyperforin) are known inducers of cytochrome enzymes (CYP1A2, 2C9, 2C19, 2D6 and 3A4, 3A2, 3E1), as well as p-glycoprotein. Therefore, chronic use of St. John’s wort is associated with a risk of pharmacokinetic interactions at the biotransformation stage with drugs whose metabolism also occurs in the cytochrome isoenzymes mentioned [110,111,112,113]. Moreover, the most widely known, possibly serious adverse effect associated with SJW administration is a fatal increase in serotonin, which can possibly cause serotonin syndrome when coupled with certain antidepressants (SSRI) and monoamine oxidase (MAO) inhibitors. It is an example of a possible pharmacodynamic SJW interaction. Serotonin syndrome is known to manifest with hyperthermia, tachycardia hypertension, mydriasis and diaphoresis [105,106]. A detailed list of possible clinically significant drug interactions with SJW is presented in Table 2. The photosensitizing effect of St. John’s wort is also well known, which reasonably contraindicates the use of this type of preparation in summer, during high sunlight. On the other hand, the photosensitizing effect of hypericin provides a background for the use of this compound in photodynamic therapy [114,115]. As a side note, all these indications regarding the safety of SJW preparations have been the reason why dietary supplements and OTC monopreparations containing relatively high doses of dry St. John’s wort extract (tablets/capsules containing 160–425 mg) have been withheld from the Polish pharmaceutical market. Saffron is used in foods and is generally regarded as safe when consumed in usual quantities. Ingestion of less than 1.5 g of saffron is nontoxic for human, and it is considered toxic when ingested with doses more than 5 g. The estimated lethal dose is about 20 g/day [116]. The data indicate that the frequency and types of adverse events reported for saffron used as antidepressant are similar to those reported for placebo and standard antidepressants (fluoxetine, citalopram) used as comparators. Spontaneous reports of adverse reactions associated with saffron include rash, flushing, hyperhidrosis, vomiting, malaise and insomnia. However, it must be emphasized that causality has not necessarily been established in all these cases [117]. Other plant antidepressants are also characterized by high safety of use. Lemon balm is generally well tolerated, having no relevant side effects, and only occasionally headache, vomiting, abdominal pain and nausea have been reported [118]. Further, no significant adverse effects associated with the use of lavender preparations in usually appropriate doses have been described [119]. In general, ginkgo administered in antidepressant preparations is also safe and well tolerated. The maximum recommended dose for ginkgo extract is 240 mg/day [120]. The reported gingko-induced adverse effects were mild and included headache, heart palpitations, gastrointestinal upset, constipation and allergic skin reactions [121]. However, it should be emphasized that the biologically active ingredients of gingko are inhibitors of the cytochrome CYP2C9 (important for the metabolism of selected oral anticoagulants and antiplatelet drugs) and inducers of CYP2C19 (important for the metabolism of selected anticonvulsants). Therefore, patients treated with warfarin, diazepam or phenytoin should avoid gingko preparations due to the increased risk of bleeding or seizures, despite anticoagulant/anticonvulsant compliance [122]. Panax ginseng generally is well tolerated, and its adverse effects are mild and reversible and include nausea, diarrhoea, euphoria, insomnia, headaches, hypertension, hypotension, mastalgia and vaginal bleeding. However, it should be noted that biological compounds from Panax ginseng may interact with caffeine to cause hypertension, and it may decrease the effectiveness of warfarin. Concomitant use of Panax ginseng and the monoamine oxidase inhibitor phenelzine may result in manic-like symptoms. Ginseng also exerts hypoglycaemic activity; therefore, caution should be exercised in using ginseng products in patients with diabetes because of possible pharmacodynamic interactions with oral hypoglycaemic agents and insulin [123]. Roseroot is well tolerated, and characteristic adverse effects have not been described. Only a few reports have indicated that repeated doses of roseroot caused mild dizziness and gastrointestinal discomfort. However, it can be mildly stimulating for some people; therefore, taking roseroot late in the day should be avoided to prevent potential interference with sleep. Some sources suggest avoiding using roseroot in people with bipolar, hypomania or paranoia, and as a preventive measure, roseroot preparations should not be combined with coffee [124]. Moreover, the use of the main biologically active ingredients of magnolia bark (magnolol and honokiol) seems to be safe. No specific adverse effects have been described for these substances at a concentration of > 240 mg/kg b.w./day of magnolia bark extract. Intervention trials employing concentrated magnolia bark extract for up to 1 year did not report adverse effects. In conclusion, over the recent years, different food safety authorities evaluated magnolol and honokiol and considered them safe [125]. Data on the side effects of other plants discussed in this review are scarce, and the literature search does not indicate reporting significant disorders during their use. A Sayyah et al. study [126] did not demonstrate any significant differences between groups of patients treated with either 500 mg aqueous extract of borage or fluoxetine (20 mg/day). In a randomized, double-blind, placebo-controlled clinical study aiming to determine the effect of brahmi on attention, cognitive processing and working memory in healthy elderly, no significant adverse effects were demonstrated during the trial in subjects treated with brahmi extract tablets containing either 300 or 600 mg compared to the placebo group [127]. Mimosa tree is considered safe for long-term use. Aqueous extract of mimosa tree was not found to produce any delirious symptoms, and the plant is regarded to be safe even at the dose 2000 mg/kg p.o. [128]. There are several plants usually administered in depression phytopharmacotherapy. In the opinion of the authors of this review and based on literature data [15,90,93,96], several medicinal plants with great potential and a history of use in depression phytopharmacotherapy can be identified. They are listed in Table 3. The authors use their common names in this paper. Classical pharmacotherapy of depression is still based on the monoamine theory and aims to correct the disturbed CNS neurotransmitter levels. In general, the detailed mechanisms by which medicinal plants exert antidepressant effects do not differ from those demonstrated for classic, pharmacological antidepressants. The evidence for their phytopharmacodynamics comes mainly from experimental studies and literature data reported within traditional medical systems, and pharmacopoeias support the use of some herbs in the treatment of depression. The description of the antidepressant activity of selected plant-derived compounds involves several mechanisms, including inhibition of monoamine reuptake; enhanced serotonin receptor binding and sensitization; monoamine oxidase inhibition; GABAergic effects (especially for plants exhibiting sedative and anxiolytic effects accompanying the antidepressant effect); complex, excitatory or inhibitory effects on various receptors (N-methyl-D-aspartic acid (NMDA), GABA, cholinergic, adrenergic, serotonergic, dopaminergic and opioid ones); and cannabinoid system effects [15,129,130,131,132]. In line with the complex, psycho-neuro-immuno-endocrinological pathogenesis of depression, herbal compounds have also been found to affect the activity of the HPA axis and stimulate immunomodulatory activity, which seems to contribute significantly to their antidepressant effect. Considering the mechanism of action of medicinal plants with antidepressant activity, it should be noted once again that their antidepressant effect results from the comprehensive action of numerous active compounds (in line with the theory of polyvalence and synergistic action of plant-derived compounds mentioned above). Due to the complexity of the chemical composition of medicinal plants with antidepressant activity (the most important ingredients are listed in Table 4), the final effect depends on their synergistic action. Thus, unlike traditional synthetic antidepressants, the molecular mechanism of action of herbal preparations cannot be explained based on a separate analysis for individual compounds; instead, it is considered a result of the collective and simultaneous action of many active compounds co-occurring in the studied plant extract. In addition, possible differences in the composition of medicinal plants resulting from the plant sources (harvest from cultivation vs. from a natural stand) and seasonal fluctuations in the chemical composition of plants contribute to the difficulties in an unambiguous description of the phytopharmacodynamics of plant preparations. Moreover, although research on plant-based drugs provides an important source of new antidepressants, it faces numerous problems, including the procurement and authentication of plant material, implementation of high-throughput screening bioassays and scale-up of bioactive compounds with suspected antidepressant activity subjected to clinical assessment. The issues mentioned above pose a challenge to translational pharmacology and the detailed description of plant-derived preparations entering clinical trials [133,134]. Figure 2 presents the essential elements of the phytopharmacodynamics of antidepressant medicinal plants. In addition to the direct effect of active, plant-derived compounds on correcting the disturbances of CNS neurotransmission, an immunomodulatory effect is also considered important to their antidepressant activity. There is evidence that antidepressant plants discussed in this review exert anti-inflammatory effects, also involving CNS. The pathophysiology of depression, as mentioned in the brief description above, is also associated with immune disturbances, releasing pro-inflammatory mediators and increased oxidative stress in the CNS. Hence, the alleviation of immunological disturbances may contribute to an antidepressant effect. The anti-inflammatory effects of plants with antidepressant activity examined in this review are briefly discussed below. Brahmi has been used for nearly 3000 years by Ayurvedic medical professionals for Alzheimer’s disease, improving memory, anxiety, allergic conditions and irritable bowel syndrome. It is a medicinal herb exerting an anti-inflammatory effect due to the selective inhibition of the cyclooxygenase-2 (COX-2) enzyme. Therefore, it is used in relieving acute pain and inflammation due to a reduction in COX-2-mediated prostanoid mediators. In addition, brahmi helps manage diseases involving chronic systemic and brain inflammation driven by the innate immune system. The administration of brahmi is associated with cognitive enhancing (nootropic) activity, including improving free recall, observed after prolonged intake (>3 months) due to the alleviation of chronic inflammation and oxidative stress associated with ageing. Furthermore, brahmi use is associated with the down-regulation of NO and pro-inflammatory cytokines: TNF-a and Il-6, and elevation of Il-10 in stimulated human blood cells [135,136]. Moreover, an additional element of the anti-inflammatory action of brahmi in the brain is the inhibition of signalling enzymes associated with CNS inflammatory pathways: caspase-1 and matrix metalloproteinase-3, as well as caspase-3, which has been shown to cleave protein tau, an early event in the development of Alzheimer’s disease [136]. The brahmi extract solution demonstrated antioxidant activity in the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging method [137]. It was also shown in an experimental study that brain antioxidant status improved in cigarette smoke-exposed rats treated with an extract from brahmi [138,139]. Current pharmacological studies show that borage has analgesic, anxiolytic, antibacterial and antiviral properties. A decoction and hydroalcoholic extracts of borage showed promising antioxidant activity evaluated by DPPH and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS) assays, which are commonly applied to determine total antioxidative potential [140]. Borage also shows anti-inflammatory properties. An in vitro study revealed that macrophages treated with a borage hexane extract modulated their inflammatory mode by reducing NO secretion and COX-2 activity and decreasing IL-1β, IL-6 and TNF-α cytokine levels [141]. Ginkgo is another medicinal plant with antidepressant potential. However, it also has anticancer, antidementia, antidiabetic, antiobesity, antilipidemic, antimicrobial, antiplatelet, hepatoprotective, anti-ageing and neuroprotective effects. It is frequently employed to treat neurological, cardiovascular and respiratory diseases, including tardive dyskinesia [142]. This plant also offers immunomodulatory and anti-inflammatory properties. An experimental study evaluated the protective potential of ginkgo extract against hippocampal neuronal injury induced by trimethyltin (TMT). A significant decrease in oxidative stress, as evidenced by reductions in malondialdehyde (MDA) and total reactive oxygen species (ROS) and marked suppression of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and pro-inflammatory cytokines (TNF-α, IL-1α, 1L-6), was demonstrated in rats treated with the ginkgo extract [143]. In another experimental in vitro study using lipopolysaccharide (LPS) treated cultured primary rat microglia, the ginkgo extract significantly inhibited the release of prostaglandin E2 (PGE2) and differentially regulated pro-inflammatory cytokines (TNF-α, IL-6 and IL-1β). Thus, it can be concluded that ginkgo showed anti-neuroinflammatory activity [144]. In macrophage culture, the ethanol extract of ginkgo flowers and the chloroform and ethyl acetate fractions significantly decreased nitric oxide (NO), interleukin-6 (IL-6) and PGE2 production [145]. Ethanol and acetone extracts from ginkgo added into the culture of human endothelial cells also inhibited ROS production and decreased soluble intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1) and E-selectin adhesion molecule levels [146]. Another medicinal plant used in the additional treatment of neurodegenerative diseases, cardiovascular disease, hypertension, insulin resistance, cancer and other degenerative processes commonly developing with age is Korean ginseng. The administration of preparations from this plant offers several health benefits related to anti-inflammatory and decreasing oxidative stress effects associated with ageing. Korean ginseng bioactive compounds reduce the effects of these conditions, mainly due to the suppression of the COX-2 and 5-lipoxygenase (5-LOX) enzymes. They can also decrease the production of malonaldehyde and increase the expression of antioxidants (glutathione and superoxide dismutase). Furthermore, the chronic administration of preparations from Korean ginseng resulted in the down-regulation of TNF-α, IL-1b and IL-6. Active compounds from Korean ginseng also caused an increase in cellular proliferation; an increase in the activity of free radical scavengers; and the activation of extracellular signal-regulated kinases, mitogen-activated protein kinase (MAPK) pathways and hypoxia-inducible factor 1-alpha (HIF-1a) [147,148]. In vitro studies also reported ginseng saponins as NO synthesis inhibitors in LPS- and IFN-γ-induced murine microglial cells [149]. Lavender is used for restlessness, insomnia, nervousness and depression. It is also administered for various digestive complaints, including dyspepsia, loss of appetite, vomiting and nausea. Lavender essential oils were also studied in macrophage cell lines as an in vitro cell culture model for evaluation of its potential efficacy in LPS-stimulated inflammation. It was demonstrated that compounds constituting the lavender essential oil modulate the activity and action of the NF-κB signalling pathway and are potent inhibitors of the synthesis of four pro-inflammatory cytokines: IL-6, IL-8, IL-β and TNFα [150]. The anti-inflammatory activity of lavender oil was also revealed in an animal study of inflammation induced by carrageenan and croton oil. This inflammation model shows increased cytokine, prostaglandin and leukotriene production. These effects are thought to be mediated by protein kinase C, which mediates a number of intracellular signal transduction pathways implicated in the pathogenesis of inflammation, including phospholipase A2-dependent arachidonic acid release and eicosanoid production. Animals pretreated with lavender oil demonstrated decreased inflammatory response [151]. In an acute model of inflammation (carrageenan-induced paw oedema model) in mice, myeloperoxidase (MPO) activity and NO production were decreased in animals treated with lavender essential oil [152]. Lemon balm is another popular herb with multiple therapeutic properties, including antidepressive, antispasmodic and antimicrobial effects. This medicinal plant reduces stress and anxiety and promotes sleep. Moreover, lemon balm has marked anti-inflammatory and antioxidant properties. This plant is also used to treat neurodegenerative diseases and obesity. Additionally, it finds application in ophthalmology, gynaecology, oncology, gastroenterology and cardiology [153,154]. In an animal study, in the carrageenan paw oedema model in rats, an antioxidant capacity of lemon balm extract was demonstrated, including the ability to scavenge a wide range of free radicals, including nitric oxide. The mechanisms of antioxidant action of lemon balm extract involve improving plasma levels of catalase, superoxide dismutase and glutathione peroxidase, as well as a marked reduction in plasma DNA damage, myeloperoxidase and lipid peroxidation [155]. Noteworthy, essential oils from lemon balm are also a rich source of phenolic antioxidants (mainly citronellal and neral), and its activity is comparable with synthetic antioxidants: butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT) [155]. The anti-inflammatory action of lemon balm, similar to other medicinal plants discussed in this review, was revealed to be attributed to the alleviation of reactions induced by prostaglandins and some pro-inflammatory (TNF-α, IL-1 and IL-6) cytokines [154]. Magnolia bark also shows a strong anti-inflammatory effect. This medicinal plant has been used for thousands of years in Chinese and Japanese medicines to treat anxiety, asthma, depression, gastrointestinal disorders and headache. The main compounds with anti-inflammatory effects are honokiol and magnolol. Honokiol inhibits the TNF-α-stimulated NF-κB pathway, with subsequent inhibition of NO generation. Moreover, honokiol reduces NF-κB target genes, such as VEGF, ICAM-1 and COX-2. This compound is regarded as a potent inhibitor of ROS, with estimated antioxidant activity 1000 times that of α-tocopherol (vitamin E) [156]. In an experimental in vitro study, magnolia bark extract reduced matrix metalloproteinase 2 (MMP-2) and matrix metalloproteinase 9 (MMP-9) secretion from LPS-stimulated monocytes [157]. Both honokiol and magnolol have antioxidant properties [158]. Honokiol significantly inhibited the LPS-induced TNF-α synthesis and NF-κB activity in mouse monocytes [159]. Mimosa tree is a medicinal plant with antidepressant, anticancer, antibacterial, antiallergic, antinociceptive, hepatoprotective, antidiabetic, anti-inflammatory and antioxidant effects [160,161]. Similar to other medicinal plants mentioned above, the mimosa tree also exerted an anti-inflammatory effect in experimental carrageenan, dextran and cotton pellet-induced rat models of inflammation and paw oedema [162]. Furthermore, in the chronic rat model of inflammation, the aqueous extract of mimosa tree alleviated both the first phase of the inflammatory response produced by histamine, serotonin, prostaglandins and bradykinin and inhibited the second transudative and proliferative phase associated with cyclooxygenase products of the entity [163,164]. Again, as with the other medicinal plants discussed above, the anti-inflammatory effect of mimosa tree is accompanied by an antioxidant effect due to potent free radical scavenging effects comparable to those of ascorbic acid and activation of superoxide dismutases and glutathione peroxidase catalase [161,165]. An anti-inflammatory effect is also reported for roseroot, and this action is conditioned by specific compounds: salidroside and rosavin. Roseroot is considered an adaptogen—it means that the plant stimulates the body’s resistance to physical, environmental and emotional stressors. Thus, it is used to fight fatigue, anxiety, stress and depression. The anti-inflammatory property of extracts from this medicinal plant finds use in various pathological conditions, including cardiovascular disease, neurodegenerative diseases, metabolic disease, arthritis or cancer [166]. Both in vitro and in vivo experiments confirmed the immune-regulation effects of roseroot extract via various inflammatory mediators (e.g., TNFα, IL-6, IL-1β, NO, COX-2) and signalling pathways (NF-κB, activator protein 1 (AP-1) and signal transducer and activator of transcription 3 (STAT3)) [166,167]. Furthermore, an experimental study confirmed the anti-inflammatory and neuroprotective effects of roseroot constituents in microglial and neuronal cells. Activated microglia produce large amounts of reactive oxygen species, nitric oxide and pro-inflammatory cytokines, such as TNF-α, interleukin-1β (IL-1β) and interleukin-6 (IL-6), which, in turn, cause neuronal damage. Moreover, the active compound of roseroot protects against glutamate-induced nephrotoxicity. Thus, roseroot preparations may offer some health benefits in neurodegenerative disorders [168]. A pronounced immunoregulatory effect is also documented for dried stigmas of the saffron crocus. This plant may have the potential to treat cancer and age-related macular degeneration. However, it has a well-documented efficacy as an alternative treatment for mild to moderate depression. The putative anti-inflammatory action of saffron crocus is likely caused by crocin, crocetin and safranal. The molecular mechanisms of these derivatives involve a decrease of serum levels of NF-κB p65 subunit, TNF-α, IFN-γ and some interleukins, such as IL-1β, IL-6, IL-12 and IL-17A. Moreover, saffron crocus has been known as the antagonist of NF-κB and the agonist of peroxisome proliferator-activated receptor gamma (PPAR-γ). In addition, this flower was shown to down-regulate pro-inflammatory enzymes, such as MPO, COX-2, inducible nitric oxide synthase (iNOS) and phospholipase A2, inhibiting prostanoids synthesis [169]. In a clinical study of patients with type 2 diabetes, 12 weeks of supplementation with saffron tablets (100 mg/day) yielded no significant differences between groups treated with saffron crocus and placebo regarding TNF-α, but the supplementation resulted in a marked decrease in blood MDA level, which is a marker of oxidative stress [170]. Similarly, patients with chronic obstructive pulmonary disease supplemented with saffron crocus (30 mg/day of crocin during 12 weeks) demonstrated decreased serum levels of total oxidative status and NF-κB, which indicated that saffron supplementation appears to effectively establish oxidant/antioxidant balance and improve inflammatory conditions in patients with COPD [171]. The anti-inflammatory property of saffron crocus was also proved in asthma patients. The 8-week administration of 100 mg/day of saffron crocus preparation resulted in a significant increase of IL-10, IL-35 and transforming growth factor beta (TGF-β) [172]. Some experimental studies showed that saffron crocus contributes to neuroprotection. The saffron crocus compounds decrease CNS inflammation by inhibiting the production of free radicals and enhancing antioxidant activities in the extracellular signal-related kinases 1 and 2 (ERK1/2) pathway-dependent manner. Moreover, saffron crocus preparations enhance gamma-glutamylcysteine synthase activity, the main enzyme for glutathione synthesis [173]. St. John’s wort is one of the most popular medicinal plants. It has been used in digestive disorders, e.g., dyspepsia and spastic ailments of the digestive tract (for the relaxation of the smooth muscles of the digestive tract and bile ducts). It also has cholagogic and cholepoietic effects. Among the numerous biological properties of SJW, the anti-inflammatory effect should be stressed. The medicinal plant has a long history of traditional use in inflammatory conditions, e.g., neuralgia, fibrositis, rheumatism and sciatica. It is also applied externally to treat wounds and bruises [174]. A key anti-inflammatory mechanism of SJW is the inhibition of the expression of pro-inflammatory genes, including COX-2, IL-6 and iNOS [175]. PGE2 is formed from arachidonic acid (AA) by cyclooxygenase-catalysed synthesis of prostaglandin H2 (PGH2) and further transformation by PGE2 synthases. Experimental studies demonstrated that one of the main compounds of SJW, hyperforin, potently inhibited the enzymatic conversion of PGH2 to PGE2, catalysed by PGE2 synthases. Moreover, hyperforin was also found to inhibit 5-LOX. It also contributes to the anti-inflammatory and anti-cancerogenic properties of SJW [176]. In the context of the anti-inflammatory effect of St. John’s wort within the CNS and the associated antidepressant effect, experimental studies have shown that mouse hippocampal neurons were protected against glutamate- or NMDA-induced cytotoxicity by SJW extract. Moreover, a morphological remodelling by increasing neurite outgrowth and activation of the anti-inflammatory defence by inhibiting cytokine production was reported in human macrophages in the presence of SJW extract. These neuroprotective properties may be the beneficial antidepressive effect of SJW supplementation [177]. In conclusion, the evidence discussed briefly above confirms the anti-inflammatory properties of medicinal plants showing antidepressant activity. In the context of the complex pathogenesis of depression, which also includes immunological disturbances within the brain, it should be emphasized that the anti-inflammatory potential of the medicinal plants discussed in this review is an important element of their antidepressant activity. Details on the mechanisms of antidepressant action of individual plants discussed here are presented in Table 4. In addition, the complex antidepressant effect caused by phytopharmacologically active ingredients is often accompanied by an anxiolytic effect, which alleviates sleep disorders, improves cognitive function and counteracts adynamia and fatigue. This is due to the complex action of phytopharmacological compounds. Further, the secondary anxiolytic effect induced by herbal antidepressants may be due to a “halo effect”, which means that anxiety may also be reduced if depression is successfully treated [15,178]. It should be stressed once again that the mechanisms of action of active ingredients present in medicinal plants with antidepressant properties, in accordance with the principles of synergy and polyvalence, are not as clearly defined as for synthetic, single antidepressants. Table 4 lists plants considered to show antidepressant activity, with details regarding their mechanisms of antidepressant action. The literature review also revealed the results of some clinical trials evaluating the efficacy of the antidepressant medicinal plants discussed in this paper. Although the number of these studies is much smaller than studies evaluating synthetic antidepressants, and they are subject to some caveats, as discussed below, the available data support the efficacy of phytopharmacotherapy in mild to moderate depression, with an emphasis on the lower potential for adverse effects. In line with the principles of evidence-based medicine (EBM), Table 5 presents data obtained from the highest level of scientific evidence (systematic reviews, meta-analyses and isolated, methodologically correct (randomized, blinded) clinical trials) [232,233,234]. For some plants (bacopa, mimosa tree, magnolia), the literature review revealed a clear advantage of experimental animal studies and no results from more extensive clinical trials. In these cases, we also enrolled prospective, observational studies. This further justifies the need to undertake large clinical trials evaluating the potential antidepressant efficacy and safety of these plants in patients with depression. Researchers also emphasize that the vast majority of clinical trials conducted to date evaluating herbal antidepressants have numerous limitations. We should interpret the results of these studies with caution due to the high level of heterogeneity between them. The small sample sizes, relatively small follow-up period and differences between the detailed methodology were the most listed limitations of the present clinical trials. Some of these were not randomized, double-blind, placebo-controlled trials, which may lead to potential selection bias and may not exclude natural improvement. Therefore, further high-quality clinical trials are needed to firmly establish the clinical efficacy of medicinal plants with antidepressant effects Many medicinal plants exert a range of psychotherapeutic effects through their influence on central nervous system activity, including antidepressant, anxiolytic, sedative, hypnotic or cognitive effects. Moreover, medicinal plants with adaptogenic and toning effects are important in phytopharmacotherapy because they are believed to enhance adaptation to exogenous stressors through complex and pleiotropic neuroendocrine mechanisms [261,262]. The discussion in this review indicates the pharmacological effectiveness of phytotherapy in correcting pathophysiological disturbances and alleviating the symptoms of depression. The mechanisms of action of herbal-derived active compounds with antidepressant activity presented in this narrative review confirm similar pharmacodynamics to synthetic antidepressants. In addition, a literature review yielded some scientific evidence (systematic reviews, meta-analyses and randomized controlled clinical trials) that indicates the clinical effectiveness of the medicinal plants discussed in this paper in treating mild and moderate depression. It makes phytopharmacotherapy a valuable alternative to classical antidepressant treatment (SSRIs). Antidepressant phytotherapy involves a lower risk of side effects. However, one should not forget that it is not entirely devoid of them, which has been particularly demonstrated for St. John’s wort preparations. According to the authors, taking into account the number of studies carried out so far, the greatest clinical experience regarding the use of phytopharmacotherapy in depression should be attributed to St. John’s wort and Saffron preparations. However, we should emphasize that there are some limitations concerning the methodological quality of clinical studies evaluating the phytotherapy of depression. These concerns necessitate further verification of the antidepressant effect of medicinal plants in large, appropriately designed clinical trials to yield conclusive and incontrovertible results confirming the efficacy and safety of herbal antidepressants. In addition to the medicinal plants described in this review, other plants are currently being studied for their antidepressant activity. Examples of such plants include Asparagus racemosus, Rosmarinus officinalis, Curcuma longa, Camellia sinensis, Emblica officinalis, Cucurbita pepo, Centella asiatica, Glycyrrhiza glabra, Piper methysticum and others [3,4,263,264]. Antidepressant activity is also sought in plants with documented sedative, hypnotic and anxiolytic properties, such as Humulus lupulus (hops), Valeriana officinalis (valerian) and Passiflora incarnata (maypop) [192]. A promising direction in the search for new antidepressant plants may also be turning to traditional Chinese and Indian medicine systems. Evidence is being reported that plants exotic to Europeans, found in Africa or South America, or those widely used for centuries in the traditional folk medicine of East Asia (China, Japan) also have antidepressant potential. The prophylaxis and adjuvant treatment of depression were demonstrated for the genera Aloysia, Gladiolus, Hemerocallis or Convolvulus, commonly used in Ayurvedic and folk medicine. Aloysia virgata grows in Brazil, Bolivia, Argentina and Paraguay. The plant is used as an anti-catarrhal, antirheumatic, diaphoretic, stimulant, stomachic and emollient. Plants from the Aloysia genus are also traditionally used for affective disorders, and some have proven anxiolytic and antidepressant activity. Animal studies using the tail suspension test (TST) and forced swimming test (FST) demonstrated promising antidepressive activity of the ethanolic extract of Aloysia [265]. Hemerocallis citrina is a plant indigenous to Asia. It is used in the folk medicine of East Asia (China, Japan) and North America to improve emotional health and treat various diseases, including insomnia, hepatosis and cancer [266]. Recent clinical studies confirm the sedative effects and high efficiency of ethanol extracts from the plant in mitigating sleep and memory disorders, with the antidepressant effect currently being studied in animal models [267]. Gladiolus dalenii is used by local communities in Africa to treat various infections, such as meningitis, malaria, diarrhoea, ulcers and HIV-related fungal infections [268]. In African ethnomedicine, especially in Cameroon, Gladiolus is regarded to be a cure for various CNS disorders, such as epilepsy, convulsions, schizophrenia and mood disorders. There are reasons to believe preparations from this plant show antidepressant efficacy in animal models of epilepsy. Animal experiments based on the TST and FST also showed the potential effectiveness of this plant in an animal model of depression [267]. Convolvulus pluricaulis (shankhpushpi) is one of the perennial medicinal herbs described in Ayurvedic literature. This plant is reported to improve memory skills as a psychostimulant with a calming effect, reducing mental tension [269]. Pharmacological studies indicate that compounds found in Convolvulus pluricaulis interact with various proteins, neurosynapses, signalling pathways and serotonergic synapses, which play a crucial role in the pathophysiology of Alzheimer’s disease and neurotransmission abnormalities related to long-term depression [270]. In general, according to Moragrega and Rios, there were about 650 reports of antidepressant-like medicinal plants in the PubMed database (considering the timespan from January 2000 to March 2020). There were 155 species studied and reported as antidepressants or as sources of active principles for treating this condition in preclinical studies [271,272]. A paradigm shift in current research should also be noted—the main research directions are shifting from the classic correction of neurotransmission to the immunological and inflammatory aspects, in accordance with the broad “psycho-neuro-immuno-endocrinological” pathophysiological concept of depression. Thus, current research focuses not only on verifying the effect of novel plant-derived preparations on CNS neurotransmission, but also confirming the phytopharmacological activity in the mitigation of pro-inflammatory mediators and enzymes [271,272]. Therefore, the novel herbal antidepressants expected in the near future will not strive to rectify monoamine disturbances in the CNS, but will focus more on immunoregulatory effects, targeting immunological and hormonal disorders, which so far have been secondary pathophysiological targets of pharmacotherapy not covered by classical treatment with synthetic antidepressants.

PMC10003401

Sutpirat Moonmuang,Apichat Tantraworasin,Santhasiri Orrapin,Sasimol Udomruk,Busyamas Chewaskulyong,Dumnoensun Pruksakorn,Parunya Chaiyawat

The Role of Proteomics and Phosphoproteomics in the Discovery of Therapeutic Targets and Biomarkers in Acquired EGFR-TKI-Resistant Non-Small Cell Lung Cancer

02-03-2023

lung cancer,non-small cell lung cancer,EGFR-TKI resistance,proteomics,phosphoproteomics

The discovery of potent EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has revolutionized the treatment of EGFR-mutated lung cancer. Despite the fact that EGFR-TKIs have yielded several significant benefits for lung cancer patients, the emergence of resistance to EGFR-TKIs has been a substantial impediment to improving treatment outcomes. Understanding the molecular mechanisms underlying resistance is crucial for the development of new treatments and biomarkers for disease progression. Together with the advancement in proteome and phosphoproteome analysis, a diverse set of key signaling pathways have been successfully identified that provide insight for the discovery of possible therapeutically targeted proteins. In this review, we highlight the proteome and phosphoproteomic analyses of non-small cell lung cancer (NSCLC) as well as the proteome analysis of biofluid specimens that associate with acquired resistance in response to different generations of EGFR-TKI. Furthermore, we present an overview of the targeted proteins and potential drugs that have been tested in clinical studies and discuss the challenges of implementing this discovery in future NSCLC treatment.

The Role of Proteomics and Phosphoproteomics in the Discovery of Therapeutic Targets and Biomarkers in Acquired EGFR-TKI-Resistant Non-Small Cell Lung Cancer The discovery of potent EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has revolutionized the treatment of EGFR-mutated lung cancer. Despite the fact that EGFR-TKIs have yielded several significant benefits for lung cancer patients, the emergence of resistance to EGFR-TKIs has been a substantial impediment to improving treatment outcomes. Understanding the molecular mechanisms underlying resistance is crucial for the development of new treatments and biomarkers for disease progression. Together with the advancement in proteome and phosphoproteome analysis, a diverse set of key signaling pathways have been successfully identified that provide insight for the discovery of possible therapeutically targeted proteins. In this review, we highlight the proteome and phosphoproteomic analyses of non-small cell lung cancer (NSCLC) as well as the proteome analysis of biofluid specimens that associate with acquired resistance in response to different generations of EGFR-TKI. Furthermore, we present an overview of the targeted proteins and potential drugs that have been tested in clinical studies and discuss the challenges of implementing this discovery in future NSCLC treatment. Lung cancer is the most common type of cancer and the main cause of cancer deaths globally, with non-small cell lung cancer (NSCLC) accounting for over 80% of all cases [1]. Although surgery is a very effective treatment option for treating early-stage NSCLC, most cases are diagnosed after the cancer has spread and surgical resection is no longer feasible, resulting in an unsatisfied overall 5-year relative survival rate of 26% and only 8% in metastasis [2]. Even though platinum-based chemotherapy (PBC) is a standard treatment for patients with advanced NSCLC, the outcomes are dismal, with an objective response rate (ORR) of around 30% and a median progression-free survival (PFS) of about 5–6 months [3,4,5]. The identification of oncogenic driver mutations in the epidermal growth factor receptor (EGFR) gene was a breakthrough in NSCLC diagnosis and treatment. These activating mutations, which occur in up to 50% of NSCLC patients, result in ligand-independent downstream signaling of EGFR, promoting increased malignant cell survival, proliferation, invasion, and metastasis [6]. Over the past decade, tyrosine kinase inhibitors (TKIs) have been recommended as a treatment for several types of cancers [7]. Among them, the inhibitor targeting EGFR tyrosine kinase (EGFR-TKI), which inhibits EGFR signaling overactivation, has demonstrated remarkable efficacy in NSCLC patients with EGFR-activating mutations. Although EGFR-TKIs have a satisfying therapeutic response that shifts NSCLC treatment strategy to a targeted strategy, most patients will develop the progressive disease within one year of treatment due to drug resistance [8]. Inherent and acquired resistance in EGFR-mutated lung adenocarcinomas constitutes a significant obstacle to improving lung cancer treatment outcomes [9]. The initial inefficacy of EGFR-TKIs is typically referred to as “intrinsic resistance”. Several studies of non-response to EGFR-TKIs have been reported in the context of non-classical sensitizing EGFR mutations and rarely in classical EGFR mutations, despite the fact that the mechanisms of intrinsic resistance are not fully investigated [9]. In-frame insertions of base pairs in exon 20 of the EGFR gene are the most common intrinsic resistance mechanisms to EGFR TKIs, accounting for 4–10% of all EGFR mutations observed in NSCLC [10]. Patients with EGFR exon 20 insertion had very poor response rates to erlotinib, gefitinib, and afatinib therapy, ranging from 3 to 8% [11]. Additionally, existing molecular or genetic changes that may possibly impair the sensitivity to EGFR-TKI therapy might result in intrinsic resistance [9]. The deletion polymorphisms or low levels of messenger RNA (mRNA) of the proapoptotic Bcl-2 family member, BIM, enabled the tumor to resist the apoptosis effects of EGFR-TKI [12]. The acquired EGFR T790M mutation in exon 20 is the most prominent alteration related to the emergence of resistance to the first and second generations of EGFR-TKI. Although Osimertinib, the third generation of EGFR-TKI, was employed to address lung cancer with the T790M mutation and has shown excellent effectiveness in this setting, the acquired resistance to the third generation of EGFR-TKI, which involves the cysteine residue at codon 797, has been observed. The activation of alternate pathways or downstream targets of EGFR signaling and histological transformation are additional acquired resistance mechanisms [13]. With the advancement of mass spectrometry (MS)-based protein analysis technology, large-scale protein analysis has become increasingly popular. Especially in cancer research, proteomic analysis of cancers is critical for gaining a comprehensive understanding of dynamic molecular aberrations, including protein phosphorylation, protein–protein interactions, protein structure, and protein function [14,15]. Discovery proteomics enables the detection of protein dynamics in biological states and pathological situations as well as the large-scale identification of proteins [16]. Furthermore, with advancements in technology for sample preparation and data processing, as well as increases in the sensitivity and resolution of MS instrumentation, such an approach has become a key technology for illustrating proteins related to cancer drug resistance [17]. These allow the discovery of novel therapies as well as potential biomarkers for predicting patient prognosis, stratifying high-risk patients, and responding to specific medicines. Here, we emphasize the proteome and phosphoproteomic research of EGFR-TKI-resistant NSCLC cells, which gives significant details on the acquired resistance mechanisms for each EGFR-TKI generation. The mechanisms of EGFR-TKI resistance and prospective therapeutic approaches have been comprehensively described, including alterations in key signaling pathways as well as the metabolome and lipidome profiles of resistant cells [18,19,20,21]. In addition to the well-known acquired EGFR-TKI resistance, the proteome analysis sheds light on important resistant mechanisms, such as the posttranslational modifications of EFGR and antigen-presenting pathways. We also discuss the proteome analysis of biofluid samples, which have clinical potential as biomarkers for patient stratification and prognostic indication. EGFR, also known as HER1, belongs to the ErbB family of receptor tyrosine kinases (RTK) [22], consists of an extracellular ligand binding domain for the EGF family, a single α-helical transmembrane domain, an intracellular tyrosine kinase domain, and a carboxy-terminal region that contains autophosphorylation sites. Upon ligand interaction, the dimerization of EFFR enhances its intracellular protein tyrosine kinase activity, resulting in autophosphorylation thereby activating signal cascades including RAS/RAF/MEK/ERK, PI3K/AKT/mTOR, and STAT pathways [23]. Exon 19-microdeletions (exon 19dels) or deletion-insertions (exon 19 delins) or the p.L858R (L858R) point mutation in exon 21 of EGFR, which accounts for roughly 90% of all EGFR mutations in NSCLC [6], were the most commonly associated with classic EGFR activating mutations. However, these mutations cause constitutive activation of ligand-independent downstream signaling of EGFR [24], causing enhanced malignant cell survival, proliferation, invasion, and metastasis (6). Thus, the application of TKIs targeting EGFR mutations has accelerated the evolution of NSCLC therapy. To date, EGFR-TKIs have been extensively explored and played critical roles in the treatment of EGFR-mutant NSCLC patients, as summarized in (Table 1). The conformational change that destabilizes the dormant form of the EGFR induced by the classical EGFR mutations results in constitutive activation of downstream signaling pathways [24]. The first-generation EGFR-TKIs target this conformational alteration, leading to the inhibition of EGFR signaling. The findings of randomized clinical trials in advanced NSCLC patients with classical EGFR mutations showed the outperforming of first-generation reversible EGFR-TKIs over platinum-based doublet chemotherapy (PBC) and a much larger increase in second-generation irreversible EGFR-TKIs. Regardless of the promising activity of first- and second-generation EGFR-TKIs, the acquired resistance due to EGFR T790M mutation hampered the efficacy of treatment by interfering with the binding of first- and second-generation TKIs to the ATP-binding site and has been identified approximately 50% of EGFR-TKI resistant patients during the treatment. The T790M mutation, on the other hand, occurred in a patient who had previously been untreated with EGFR TKIs, implicating an additional role in intrinsic resistance to first- and second-generation TKIs [25,26,27]. Because of the high prevalence of T790M mutation and the low efficacy of first- and second-generation EGFR inhibitors due to the steric hindrance effected by T790M [28], third-generation EGFR-TKI was initially developed. The FDA has authorized osimertinib, a third-generation irreversible EGFR-TKI, to treat patients with the EGFR T790M mutation who have developed resistance to first- and second-generation EGFR TKIs [29]. Recently, the FLAURA trial demonstrated the superiority of osimertinib over gefitinib or erlotinib in the first-line setting of EGFR-mutant NSCLC as shown in an improved mOS and mPFS for advanced EGFR mutant NSCLC [30,31]. Because of the limited penetration of first- and second-generation EGFR TKIs into the blood–brain barrier, about 40% of NSCLC patients with EGFR mutations develop CNS metastases. Notably, in the phase I trial (BLOOM), osimertinib revealed considerable treatment benefits in the CNS and a tolerable safety profile in patients with leptomeningeal metastases from EGFR-mutated advanced NSCLC [32]. The evidence showed no T790M mutation after applying osimertinib as the first-line setting [33]. Thus, T790M mutation as a resistance mechanism has become less clinically significant. Instead, acquired resistance in other EGFR-dependent and EGFR-independent bypass pathways was developed. Despite the fact that the cysteine-797 (C797) residue in the ATP binding site of the EGFR kinase is the target of third-generation EGFR TKIs, in preclinical models and clinical samples, acquired EGFR T790M/C797S mutation was eventually developed [34] and C767 mutations have been observed in 15% of second-line osimertinib patients and 7% of first-line osimertinib patients [35]. As a result, there is an urgent need to identify inhibitors that can bind to sites other than the ATP binding cleft of the EGFR-TK-domain in order to overcome the resistance related to third-generation EGFR inhibitors. To date, a novel class of allosteric mutant-selective fourth-generation EGFR-TKIs which can bind to the site other than the ATP binding cleft of EGFR, have been discovered to overcome third-generation EGFR-TKIs resistance and introduced for clinical evaluation [36]. Long-term exposure to inhibitors exerts selective pressure on tumor cells to become resistant to therapy, including EGFR-TKIs [37]. Proteomic analysis has grown in importance in molecular sciences since it provides large-scale protein information, including protein expression profiles in drug-resistant cancer cells. Mass spectrometry-based proteomics has evolved into a promising technique for investigating numerous pathways of drug resistance in cancer cells, allowing for the global identification and quantification of proteins related to drug resistance [17,38]. Such approaches are being employed to uncover the fundamental differences between sensitive and resistant cancers, which reveal drug resistance mechanisms and biomarkers for predicting response to the regimen [17,38], leading to the development of novel therapeutics that target proteins that are specifically expressed in resistant cancers [39]. In recent decades, proteomic studies of EGFR-TKI-resistant NSCLC have been largely investigated (Table 2). In the field of proteomics, MS-based protein analysis technology has dominated. In most studies, this approach, combined with either labeling or non-labeling quantitation methods, was extensively used to reveal global changes in the proteome and phosphoproteome following EGFR-TKI treatment in NSCLC. Due to the limitation of surgically resected tissues from patients with EGFR-TKI resistance, the proteome and phosphoproteome profiles of EGFR-TKI resistance were widely investigated in the in vitro model. The majority of the research compared EGFR-TKI-resistant cell lines to EGFR-TKI-sensitive cell lines. According to the findings of proteomic and phosphoproteomic investigations of acquired EGFR-TKI resistance, a wide range of dysregulated proteins and signaling pathways are involved in the activation of bypass and crosstalk signaling pathways and changes in histological phenotype from NSCLC to SCLC or epithelial to mesenchymal transition (EMT). Furthermore, the study of proteome profiles of liquid biopsy samples unveiled the potential biomarkers for NSCLC patient stratification that are currently being applied in the clinic. The investigation of the tyrosine phospho-proteome of EGFR-TKI-sensitive PC9 cells vs. erlotinib-resistant PC9GR cells showed activation of several receptor tyrosine kinases (RTKs), including Met, IGF, and AXL signaling pathways, as shown in Figure 1 [58]. Even though amplification of the MET gene is reported in tumors resistant to first-line erlotinib, gefitinib, or afatinib and osimertinib [60], the activation of Met signaling observed in this phospho-proteomic study is independent of MET gene amplification. The study also unveiled the extensive signaling crosstalk involving the acquired resistance mechanism to the EGFR-TKI treatment. Almost half of the statistically significant phospho-tyrosine peptides were increased in response to the treatment of erlotinib. The acquired resistance mechanism of NSCLC was explored through the use of a TK activity-representing peptide library-based multiple reaction monitoring (TARPL-MRM) to determine tyrosine kinase (TK) activity in response to osimertinib treatment [41]. The results indicated a rewiring of TK activity and that the phosphorylated activation loops of SRC family proteins, including SRC, ACK, FER, and FYN, were significantly increased in H1975 cells treated with osimertinib at different time points. Network analysis of TK alteration of sensitive and resistant cells also confirmed the SRC family was a key mediator in the resistant NSCLC cells. The proteome analysis revealed an increased expression of the receptor tyrosine kinase AXL in erlotinib-resistant cell lines and aberrant expression of FGFR1, FRS-2, and PRAS40, indicating the activation of the FGFR1-Akt pathway [44]. A combination of FGFR1 and Akt inhibitors synergistically inhibited EGFR-TKI-resistant NSCLC cells with FGFR1 overexpression. The tumor growth rate was significantly inhibited upon the co-treatment of an FGFR1 inhibitor and an Akt inhibitor in EGFR-TKI-resistant NSCLC xenograft models. Furthermore, high FGFR1 mRNA expression levels were a statistically significant prognostic marker for progression-free survival of EGFR-TKI-treated patients. According to array-based and MS-based proteomic analysis, FAK signaling has been reported for its involvement in the acquired EGFR-TKI resistance mechanism of the first- and second-generation of EGFR-TKI. The proteome profiler array was used to examine the expression of human soluble receptors and related proteins in gefitinib-sensitive parent cells and gefitinib-resistant cell lines [48]. The study demonstrated that osteopontin (OPN) was the most significantly overexpressed in gefitinib-resistant NSCLC cells. OPNs have been shown to interact with various integrins through RGD-mediated integrin recognition sequences. OPN contributes to the acquired EGFR-TKI resistance mechanism by increasing integrins αv and β3 levels. The downstream FAK/AKT and ERK signaling pathways were subsequently activated, which enhanced NSCLC cell proliferation [48]. A p-FAK inhibitor dramatically improved the susceptibility of gefitinib-resistant cells to gefitinib. A combination of gefitinib and p-FAK inhibitors effectively inhibited gefitinib-resistant cell growth. The findings were further verified in a mouse xenograft model, where tumor growth was suppressed by a combination regimen more potent than a single gefitinib treatment. In addition, the MS-based quantitative proteomic analysis of osimertinib-sensitive parent cells and osimertinib-resistant cell lines demonstrated that LAMA5 (Laminin α5) was the highest fold change in osimertinib-resistant cells [42]. Enhanced expression of LAMA5 was associated with high plasma IL-6 levels and in osimertinib-resistant NSCLC cells with high IL-6 levels. Furthermore, the activation of FAK, a downstream effector of LAMA5, was observed exclusively in osimertinib-resistant cells with high IL-6 levels. A combination treatment of osimertinib and ibrutinib efficiently reversed the drug resistance in osimertinib-resistant cell lines, through inhibition of IL-6 and lamininα5/FAK signaling [42]. Integrative analysis of the proteome and phosphoproteome has been used to study aberrations of signaling pathways in both second- and third-generation EGFR-TKI. Mulder and colleagues employed a multi-omic approach to investigate the alteration of the proteome, kinome, and phosphoproteome profiles of NSCLC cells during afatinib treatment (1 to 7 days) [52]. Upon the initial afatinib treatment, NSCLC cells adapt to afatinib inhibition by using Ca2+/calmodulin-related signaling and adhesion signaling pathways as a resistance mechanism. Phosphoproteomic data also demonstrated reactivation of the PI3K/mTOR and MEK/ERK signaling pathways within days after afatinib treatment. A combination of mTORC1 inhibitor (rapamycin) and afatinib had cytostatic effects on the growth of NSCLC cells, in which cell growth was significantly inhibited with no alteration in the amount of apoptotic cells. Interestingly, the effects of MEK inhibitor (selumetinib) and afatinib co-treatment induced apoptosis in NSCLC cells, which is beneficial for use as an anti-tumor agent. The global proteome and phosphoproteome of the third generation of EGFR-TKI resistance mechanism of NSCLC were investigated in osimertinib- and rociletinib-resistant cells vs. sensitive cells [46]. The phosphorylation levels of phosphatase PTPN11 (SHP2) important sites were reduced in all resistant cell lines, resulting in inactive phosphatase activity and consequent activation of PI3K/AKT pathways and suppressed RAS/MAPK signaling [46]. The treatment of dactolisib, a dual PI3K/AKT and mTOR inhibitor, as a combination agent with osimertinib inhibited resistant NSCLC cells both in vitro and in animal models. Persistent activation of ERK signaling was also observed in osimertinib-resistant cell lines after osimertinib treatment [54]. The study performed a phospho-kinase array to analyze 43 different kinase phosphorylation patterns in both parental and osimertinib-resistant NSCLC cells in the presence of osimertinib. The phosphorylation of WNK1, a regulator of MAPK in EGFR signaling and involved in cell proliferation, was induced after osimertinib treatment in osimertinib-resistant cells [54]. A combination of MEK inhibitor and osimertinib efficiently inhibited resistant cell viability and induced apoptosis by suppressing ERK phosphorylation. Furthermore, the combination of two inhibitors significantly inhibited tumor growth more potently than the treatment with a single agent. Proteomic and phosphoproteomic studies of the acquired resistance mechanisms of NSCLC cells to multiple generations of EGFR-TKI revealed a plasticity transformation from epithelial to mesenchymal cells in EGFR-TKI-resistant NSCLC cells. The proteome and phosphoproteome study of the first generation of EGFR-TKI has been performed using reverse phase protein arrays (RPPA), and immunoaffinity enrichment of pTry phosphopeptides combined with LC-MS/MS. Integrated proteomic analysis of RPPA, gene expression, and drug resistance analysis demonstrated that mesenchymal cancer cells were more resistant to EGFR-TKI and PI3K/Akt pathway inhibitors, independent of EGFR mutation status, compared with epithelial cells [59]. The overexpression of the Axl protein was found in mesenchymal cell types compared with epithelial cells [59]. Proteomic analysis of T790M-negative erlotinib-resistant NSCLC cell lines revealed a link between EMT and the EGFR-TKI resistance mechanism, with mesenchymal markers AXL and ZEB1 overexpression and epithelial markers E-cadherin and -catenin expression lower in EGFR-TKI resistant cells [49]. The tyrosine phospho-proteome analysis also demonstrated that multiple Src/FAK pathway kinases were aberrantly phosphorylated in mesenchymal cells [57]. Using unbiased drug sensitivity screening, the Abl/Src inhibitor dasatinib was demonstrated as the most potent anti-cancer agent for erlotinib-resistant mesenchymal cells. Furthermore, using an integrative analysis of transcriptomic, proteomic, and drug screening data, the activation of the yes-associated protein (YAP) and forkhead box protein M1 (FOXM1) axis has been found as a driver of EMT-associated EGFR TKI resistance and upregulated the expression of spindle assembly checkpoint (SAC) proteins [49]. Quantitative proteomic and phosphoproteomic analyses of the third generation of EGFR-TKI were performed in resistant EGFR-mutant NSCLC cells and sensitive cells. iTRAQ-based quantitative proteomics and whole-transcriptome sequencing demonstrated that NSCLC cells harboring the EGFR C797S mutation are associated with a mesenchymal-like cell state with elevated expression of AXL receptor tyrosine kinase [47]. Enrichment analysis of the biological processes of differentially expressed proteins indicated a strong relationship with EMT, cytoskeletal rearrangement, and migratory and invasive properties. The inhibition of AXL effectively suppressed the growth of NSCLC cells with the EGFR C797S [47]. Global SILAC quantitative mass spectrometry demonstrated that expression levels of several translational regulator proteins, including EIF proteins and EMT signature proteins, were much more altered in rociletinib-resistant cells than in osimertinib-resistant cells [46]. CDH1 expression, which is linked with the epithelial state, was reduced in resistant cells. Autophagy is an intracellular catabolic process that eliminates cytoplasmic materials or malfunctional components via a lysosome-dependent mechanism. Translation-related proteins have been reported for their roles in erlotinib resistance. The eIF3c, a eukaryotic translation initiation factor (eIF), was highly upregulated in T790M-negative PC9/ER and mechanistically enhanced autophagic activity through increasing an autophagy marker, LC3B-II [50]. Erlotinib-induced autophagy is inhibited by eIF3c suppression, showing that eIF3c is a critical regulator of erlotinib-induced autophagy [50]. Similarly, applying the quantitative global proteome and diGly proteomics, which combine antibody-based capture of “diGly remnant” peptides and SILAC, the results showed that thousands of differentially expressed proteins and ubiquitylation were associated with gefitinib resistance [53]. Furthermore, HMGA2 and ALOX5, which are involved in promoting tumor metastasis [61] and aberrantly expressed in several tumor types [62], respectively, were chosen and subsequently validated. HMGA2 overexpression or ALOX5 knockdown suppressed gefitinib resistance in NSCLC cells by inhibiting autophagy [53]. Employing pan-HLA class I antibody-based affinity purification-mass spectrometry (AP-MS) provided the evidence that osimertinib resistance in EGFR mutant lung cancer resulted in widespread suppression of HLA peptide processing and presentation, which was demonstrated by a decrease in the HLA class I-presented immunopeptidome as well as the antigen presentation core complex (e.g., TAP1 and ERAP1/2) [43]. Furthermore, through integrated pathway analysis, the alteration of the immunoproteasome, several key elements in autophagy, caspases, or phagosome signaling affected the source of antigen in osimertinib-resistant lung adenocarcinoma cells [43]. iTRAQ-based quantitative proteomic analysis has been used for the identification of differentially expressed proteins among gefitinib-resistant PC9/GR cells and the corresponding parental PC9 cells. Nicotinamide N-methyltransferase (NNMT) was the most significantly upregulated in PC9/GR cells [40]. The upregulation of NNMT in NSCLC patients who received EGFR-TKI treatment was associated with lower progression-free survival and poor survival outcomes. the knockdown of NNMT in PC9/GR and HCC827/GR cells significantly increased sensitivity to gefitinib and erlotinib, and induced cell apoptosis. Furthermore, the overexpression of NNMT significantly decreased the sensitivity of NSCLC cells to the third-generation EGFR TKI inhibitor, osimertinib. The upregulation of NNMT mediates EGFR-TKI resistance by regulating the glycolysis mechanism of NSCLC cells by increasing c-myc expression via SIRT1-mediated c-myc deacetylation. In NSCLC cells, the combination of NNMT inhibitor and EGFR-TKI effectively overcomes EGFR-TKI resistance [40]. The MS-based proteomic study of the third-generation EGFR-TKI, almonertinib, identified increased expression of glutamine transporter (SLC1A5) in NSCLC cells treated with almonertinib (57). The inhibition of glutamine influx by siRNA knockdown of SLC1A5 and SLC1A5 effectively decreased NSCLC cell proliferation and glutamine uptake. A combination of the SLC1A5 inhibitor and almonertinib could improve in vivo anti-tumor activity with no severe liver or renal toxicity. Understanding the functional significance of glycosylation-mediated disease necessitates extensive characterization of the glycoproteome, which is extremely difficult due to the intrinsic complexity of glycoproteins. Recent studies have found that glycosylation has a significant role in lung cancer resistance. For example, sialylation of EGFR has been demonstrated to alter susceptibility to TKIs [63,64]. However, a comprehensive glycoproteome study in a lung cancer cell is yet substantially unexplored. Waniwan et al. implemented lectin nanoprobe-based affinity mass spectrometry for complementary glycotope-specific enrichment and site-specific glycosylation analysis of the glycoproteome [51]. They discovered a significant quantity of glycopeptides, particularly fucosylated glycopeptides, in the resistant PC9-IR cells [51]. Aberrant fucosylation mediates EGF-mediated cellular growth response and gefitinib sensitivity by influencing either the binding affinity of EGFR to the EGF ligand or the ability of the EGFR to dimerize [51]. Liquid biopsy proteome profiling has been intensively studied for the discovery of biomarkers for predicting and monitoring EGFR-TKI response in NSCLC patients. The proteomic approach, which included a gel-based [65], antibody-based [66], and MS-based technique [67], was performed to analyze biofluid samples from NSCLC patients who responded differently to EGFR-TKI as summarized in (Table 3). The use of 2D-DIGE for studying serum proteome profiles at the baseline and progression of the disease showed that alpha-1-antitrypsin (AAT) was highly upregulated in progressive diseases (PD) compared to baseline levels in advanced NSCLC patients treated with erlotinib or gefitinib [65]. AAT1 levels were lower in patients with partial responses to EGFR-TKI. The proteome profiles of the serum of advanced NSCLC patients treated with erlotinib were determined using a 41,472 antibody microarray and LC-MS/MS [66]. The results showed an association between levels of isoform 2 of fibrinogen alpha chain (FGA2) and EGFR-TKI response. FGA2 levels were decreased in the PR group but increased in the PD group. Interestingly, FGA2 was not detected in lung cancer cells but in hepatocytes. Hepatocellular carcinoma cells treated with erlotinib decreased the expression and secretion levels of FGA2. This finding might at least in part explain the fluctuations of serum FGA2 levels upon the treatment of erlotinib in NSCLC patients. Proteome profiles of pleural effusion (PE) were determined using iTRAQ labeling coupled with LC/MS-MS [67]. The specimens were derived from NSCLC patients carrying EGFR mutations with a differential response to EGFR-TKI treatment. PE levels of soluble cadherin-3 (sCDH3) were higher in patients resistant to EGFR-TKI. Serum levels of sCDH3 were also determined at baseline and 1 month after EGFR-TKI treatment. The results demonstrated lower sCDH3 levels in PR patients. Furthermore, serum sCDH3 showed its independent prognostic power, in which sCDH3 levels were linked with the progression-free survival (PFS) of NSCLC patients. The most extensive studies on the discovery of EGFR-TKI response predictive markers are the detection of unique proteomic spectra using high throughput MALDI-TOF mass spectrometry. The use of the MALDI MS algorithm based on eight distinct m/z features called “VeriStrat” was applied primarily in the baseline serum of NSCLC patients for stratification of NSCLC patients into good vs. poor responders for the treatment of Erlotinib or Gefitinib [68]. A later study demonstrated the efficiency of VeriStrat in monitoring gefitinib responses, in which “good” VeriStrat classification was linked to longer overall survival independently of other clinical factor confounders [69]. Specific proteins were further identified from the eight MALDI TOF MS signals between poor and good responders using LC MS/MS [70]. Serum amyloid A protein 1 (SAA1) was higher expressed in the plasma of the NSCLC patients who poorly responded to gefitinib treatment, in which case SAA1 generated four out of the eight MS mass signals composing the VeriStrat algorithm. This test has been commercially launched as VeriStrat, and its clinical relevance has been validated in clinical trials [71,72,73,74,75,76]. Additionally, Yang et al. applied MALDI-TOF-MS and ClinProTools software to identify serum peptides and proteins associated with EGFR gene mutation status in stage IIIB or IV NSCLC patients with EGFR gene TKI-sensitive mutations and wild-type EGFR genes [77]. The serum proteomic classifier established was examined for EGFR gene mutation status and verified in an independent validation cohort, demonstrating high concordance and sensitivity with tumor biopsies. Furthermore, the classifier was also consistent with tests in tumor tissue for identification of response to EGFR-TKI treatment [77]. Given the rapid progression of disease in patients with acquired resistance to EGFR-TKI treatment, there is a significant unmet need for novel therapeutic alternatives. Based on protein and pathway alteration from the proteome and phosphoproteome analysis, we summarized targeted proteins and potential drugs that have been tested in clinical studies. AXL is overexpressed in many types of cancer, including NSCLC, breast, gastric, colorectal, and prostate cancer [79]. The overexpression of AXL has been linked to drug resistance to a variety of inhibitors, including an EGFR inhibitor [80]. In NSCLC, AXL upregulation has been associated with EMT, with AXL being overexpressed in mesenchymal cancer cells compared to epithelial cancer cells [40,43,45,52,54,55,59]. The downregulation of AXL expression inhibited EMT while increasing the response to EGFR-TKI [81]. Several studies on the efficacy of agents targeting AXL, including small molecule inhibitors, monoclonal antibodies, and antibody-drug conjugates, have been conducted in preclinical and clinical phases [82]. In preclinical studies both in vitro and in vivo, the expression of AXL was induced in response to the treatment of EGFR-TKIs in NSCLC cells carrying an EGFR mutation. The combination of AXL inhibitors and EGFR-TKIs could synergistically overcome this resistance [83,84,85]. Several potent AXL inhibitors have recently been evaluated in early-phase clinical trials [82]. A phase I clinical study of the combination of DS-1205c with Gefitinib for metastatic or unresectable EGFR-mutant NSCLC (NCT03599518) demonstrated no serious adverse events directly related to DS-1205c [86]. A phase I/II trial of the oral selective AXL inhibitor bemcentinib (BGB324) in conjunction with erlotinib in patients with advanced EGFR mutation NSCLC (NCT02424617) revealed the feasibility and well-acceptability of this combination, with benefit found in a subgroup of patients who had progressed on an EGFR inhibitor or were receiving erlotinib simultaneously in remission in the first line [87]. However, a clinical trial combining ASP2215 and erlotinib in EGFR-positive NSCLC patients following EGFR inhibitor treatment (NCT02495233) was halted due to significant serious adverse effects associated with the combination medication. SRC is a member of the non-receptor tyrosine kinase family (Src Family Kinases, SFKs) and plays a critical role in cell adhesion, invasion, proliferation, survival, and angiogenesis during tumor development [88]. Src activation is important in the acquisition and maintenance of resistance to EGFR inhibitors in lung cancer [41], in addition to the well-established involvement of Src kinases in tumor growth. Interestingly, EGFR-TKI-resistant cells had drastically reduced cell survival and migration after treatment with the SFK inhibitor dasatinib, demonstrating that Src inhibitors may overcome EGFR inhibitor resistance in lung cancer cells [89]. In this phase I trial (NCT0199998), Dasatinib revealed high tolerance in cancer patients who progressed after EGFR inhibitors and feasibility in advanced NSCLC at biologically active dosages in conjunction with afatinib. Despite this, pleural effusion remained a significant major adverse effect. In an open-label, dose-escalation phase I/II trial (NCT01999985) with two-stage expansion, This combination demonstrated a low toxicity profile and lowered the incidence of EGFR mutations and T790M variant alleles in cell-free DNA, but no objective clinical responses were reported [90]. Another clinical trial (NCT02954523, phase I/II) evaluated the effects of the third-generation EGFR-TKI, osimertinib in combination with dasatinib, in EGFR mutant NSCLC patients who developed resistance to the first-generation EGFR-TKIs and assessed serum biomarkers to monitor clinical outcomes upon Src inhibitor treatments. Although the combination of osimertinib and dasatinib had anti-tumor efficacy in patients with EGFR-mutant NSCLC in the front-line setting, the treatment was limited by chronic toxicities, which were primarily due to dasatinib [91]. The alterations of the PI3K-AKT-mTOR pathway occur through the activation of tyrosine kinase receptors, PIK3CA amplification, and mutations in downstream signaling [92]. Clinical studies have shown that EGFR mutant patients with PI3K pathway activation have a shorter PFS and a lower OS [93,94,95]. The mTOR inhibitors, including everolimus, have been approved for cancer treatment including neuroendocrine tumors and, as a combination therapy, HER2-positive breast cancer, as well as certain tuberous sclerosis complex-related tumors [96]. In preclinical studies, everolimus was shown to overcome EGFR drug resistance and provide a cooperative impact with EGFR inhibitors in various human cancer cell lines resistant to EGFR inhibitors [97]. Everolimus synergized with gefitinib to restore the EGFR-TKI resistance in NSCLC cell lines [98,99]. The combination therapy of everolimus and EGFR-TKIs was evaluated for feasible dosages for tolerable toxicity and disease control in NSCLC patients carrying EGFR mutations [100,101]. Everolimus was used as a second-line treatment in a patient with an EGFR mutation who had failed to respond to EGFR-TKI and had tumor regression [102]. Acquired resistance remains a challenge for the effective treatment of NSCLC. Due to the limited availability of repeated tissue biopsies, the proteomics and phosphoproteomics analysis of cancer cells with in vitro treatment of EGFR-TKI has been widely performed for the discovery of therapeutic targets and biomarkers. The validation of the proteome and phosphoproteome data in in vitro and in vivo models is crucial for identifying the best candidates for further clinical studies. Furthermore, an integrative analysis of genomics and proteomics will provide more insight into the system biology of EGFR-TKI resistance mechanisms in NSCLC patients.

PMC10003402

Tomasz Jędrzejewski,Małgorzata Pawlikowska,Justyna Sobocińska,Sylwia Wrotek

COVID-19 and Cancer Diseases—The Potential of Coriolus versicolor Mushroom to Combat Global Health Challenges

02-03-2023

Coriolus versicolor,cancer,COVID-19,immunomodulation,angiogenesis,inflammation,fever

Coriolus versicolor (CV) is a common species from the Polyporaceae family that has been used in traditional Chinese herbal medicine for over 2000 years. Among well-described and most active compounds identified in CV are polysaccharopeptides, such as polysaccharide peptide (PSP) and Polysaccharide-K (PSK, krestin), which, in some countries, are already used as an adjuvant agent in cancer therapy. In this paper, research advances in the field of anti-cancer and anti-viral action of CV are analyzed. The results of data obtained in in vitro and in vivo studies using animal models as well as in clinical research trials have been discussed. The present update provides a brief overview regarding the immunomodulatory effects of CV. A particular focus has been given to the mechanisms of direct effects of CV on cancer cells and angiogenesis. A potential use of CV compounds in anti-viral treatment, including therapy against COVID-19 disease, has also been analyzed based on the most recent literature. Additionally, the significance of fever in viral infection and cancer has been debated, providing evidence that CV affects this phenomenon.

COVID-19 and Cancer Diseases—The Potential of Coriolus versicolor Mushroom to Combat Global Health Challenges Coriolus versicolor (CV) is a common species from the Polyporaceae family that has been used in traditional Chinese herbal medicine for over 2000 years. Among well-described and most active compounds identified in CV are polysaccharopeptides, such as polysaccharide peptide (PSP) and Polysaccharide-K (PSK, krestin), which, in some countries, are already used as an adjuvant agent in cancer therapy. In this paper, research advances in the field of anti-cancer and anti-viral action of CV are analyzed. The results of data obtained in in vitro and in vivo studies using animal models as well as in clinical research trials have been discussed. The present update provides a brief overview regarding the immunomodulatory effects of CV. A particular focus has been given to the mechanisms of direct effects of CV on cancer cells and angiogenesis. A potential use of CV compounds in anti-viral treatment, including therapy against COVID-19 disease, has also been analyzed based on the most recent literature. Additionally, the significance of fever in viral infection and cancer has been debated, providing evidence that CV affects this phenomenon. Natural products have played a vital role in health care since ancient times. In academic medicine, there are many examples of drugs (including chemotherapeutic agents) that originated from plants and mushrooms, e.g., topotecan [1], etoposide, teniposide [2], docetaxel, and paclitaxel [3]. Interestingly, the Nobel Prize in Medicine 2015 was awarded for artemisinin—the active ingredient of the medicinal herb ‘sweet wormwood’—which is an effective anti-malarial therapy [4]. Mushrooms have long been regarded as a healthy source of nutritional value [5]. Additionally, they have emerged in recent years not only as a source of drugs, but also as adjuvants to conventional treatments. Their potential to reduce side effects related to chemotherapy or radiotherapy is of special interest. In this regard, the best investigated medicinal mushroom is Coriolus versicolor (L.) Quél. (1886), also known as Trametes versicolor (L.) Lloyd (1920), Polyporus versicolor (L.) Fries (1821), Turkey Tail, Agaricus versicolor, Boletus versicolor, Polystictus versicolor, Poria versicolor, Yun-Zhi (Chinese), and Kawaratake (Japanese) [6]. An ancient Chinese formulation of Coriolus versicolor (CV) has been used in traditional Chinese herbal medicine for over 2000 years. It is believed that CV promotes health, strength, and longevity. In traditional Chinese medicinal practice, the CV mushroom is considered useful for removing toxins, strengthening, increasing energy, improving liver and spleen function, promoting diuresis, and enhancing the immune response. It is also used to damp heat jaundice, hypochondriac pain, poor appetite, lassitude, and weakness [7]. Many studies have reported that CV has anti-oxidant, hypoglycemic, and immune-enhancing effects, and therefore, its benefits in liver disease and diabetes are expected. Indeed, in China, Japan, and the United States, CV is used as an important dietary supplement that protects the liver [8]. Among more than 270 recognized species of mushrooms with immunotherapeutic properties, 50 are described as non-toxic and have been tested in animal models, and 6 of these species have been studied in human cancers. The CV mushroom is the only one among these 6 species which has been studied in phase I, II, and III randomized clinical trials in stomach, colorectal, esophageal, and breast cancer patients [9]. In Japan and China, the extract from CV is prescribed routinely to radio- or chemotherapy-treated patients suffering from different types of cancer. It has been found that CV increases survival rates and improves activity of immune cells. Moreover, it counters the immunosuppressive effects of conventional anti-cancer therapies and reduces cancer treatment-related symptoms, such as fatigue, loss of appetite, vomiting, and pain, thereby improving the quality of life of cancer patients [10,11]. All these effects make CV extract a commonly used drug by many naturopathic physicians and integrative oncologists in the USA [12]. The number of publications on CV reflects great interest in the medical application of this mushroom. Over 400 publications concerning CV have been deposited in PubMed within the last 5 years. The aim of this review is to research advances in the field of CV-induced effects that can be useful in a treatment of one of the most actual medical challenges of 21st century i.e., cancer and COVID-19. Since mushrooms, in contrast to animals, do not have any adaptive immune system, their chemical shield must protect them from the entire spectrum of pathogens that exist in their natural environment. The study on the composition of CV shows that it contains many compounds, such as proteins [13,14], fatty acids [15], polysaccharides [16,17], polysaccharopeptides [18,19], glucans [20,21], amino acids [15,22], vitamins [8,15], and a variety of inorganic salts [15,23]. The chemical structures of the main CV active compounds described in this review are presented in the Supplementary Materials (Figures S1–S5) [24,25,26,27]. Polysaccharopeptides exert many physiological effects that are useful in the treatment of cancer, inflammation, and diabetes, such as promoting immune function and providing anti-tumor, anti-inflammation, and anti-diabetes effects [28]. Among polysaccharopeptides, polysaccharide peptide (PSP) and polysaccharide krestin (PSK) are the most studied ones for their anti-cancer and immune-enhancing properties. PSK was extracted by salting out with ammonium sulphate from the hot water extract in Japan in the 1960s and is a soluble protein-bound polysaccharide derived from the CM-101 strain of the fungus. PSP was extracted using alcohol precipitation from the hot water extract in China in the 1980s and is a polysaccharide-peptide derived from the COV-1 strain [19]. Both compounds are light or dark brown powders that are soluble and stable in water. The molecular weights of the two molecules are about 100 kDa with a respective polysaccharide-to-peptide balance of 90–10% in PSP and 60–40% in PSK. The carbohydrate moieties of each compound consist of mannose, xylose, and galactose, in addition to fructose in PSP or arabinose and rhamnose in PSK [18]. The toxicity of these compounds was tested on a variety of animals (dogs, monkeys, guinea pigs) showing no genetic and reproductive effects [29]. Importantly, neither teratogenic nor mutagenic effects of PSP have been observed in female reproductive and embryonic development in animal models [30,31]. Coriolus versicolor contains a high number of polysaccharides, including heteroglycan macromolecules. The main monosaccharide that builds these polysaccharides is glucose, followed by small amounts of mannose, rhamnose, glucuronic acid, and fructose [16]. Polysaccharides possess many physiological activities, such as promoting immune function and providing anti-tumor and anti-inflammatory effects [28,32]. They are effective in protecting the liver by increasing the activity of antioxidant enzymes and glutathione and the brain during cerebral ischemia reperfusion. Additionally, beneficial effects in diabetes and anti-bacterial activities have also been observed [16,33,34,35,36]. Numerous studies have shown that polysaccharides from CV can scavenge free reactive oxygen species (ROS) [37,38,39]. These effects may be useful in diseases, such as arteriosclerosis, Alzheimer’s disease, and cardiovascular and cerebrovascular diseases [40]. Among polysaccharides derived from CV, β-glucans are the principal components. Due to their non-starch and non-digestible natures, they can be utilized as dietary fibers by gut probiotic bacteria in the large intestine. Therefore, they are considered as potential prebiotics with anti-obesity properties [41,42,43]. Beta-glucans are believed to be one of the most well-established and potent derivatives of mushrooms that have anti-tumor, immunomodulatory, anti-viral, and anti-bacterial properties [21,44,45,46,47,48]. Notably, due to their confirmed complex mode of action, β-glucans are recognized as biological response modifiers. They induce epigenetic programming in innate immune cells to produce a more robust immune response and act as pathogen-associated molecular patterns (PAMPs), binding to specific pathogen recognition receptors. In consequence, innate and adaptive immune responses are induced [49,50]. Coriolus versicolor contains pharmacologically active secondary metabolites belonging to small molecules. Wang et al. reported the isolation of four new spiroaxane sesquiterpenes, tramspiroins A-D, one new rosenonolactone 15,16-acetonide, and the known drimane sesquiterpenes isodrimenediol and funatrol D [51]. Moreover, Janjušević et al. identified 35 phenolic compounds belonging to the flavonoid (flavones, flavonols, flavanone, flavanols, biflavonoids, isoflavonoids) and hydroxy cinnamic acids, which exhibit anti-radical and acetylcholinesterase inhibitory properties. Therefore, CV extract can be eventually used as drug-like compounds or food supplements in the treatment of Alzheimer’s disease [52]. Among small molecules present in the CV extract, Yang et al. isolated a compound of about 10 kDa molecular weight named as a small peptide of Coriolus versicolor (SMCV). This compound inhibits in vitro proliferation of various human cancer cells, such as gastric cancer, leukemia, hepatoma and colon cancer, more significantly than PSP or PSK. Moreover, pre-treatment of SPCV decreases the proliferation of tumor cells in mouse and has an immunostimulating effect manifested by increase in white blood cells and IgG levels [53]. Another small molecule purified by Kuan et al. from CV is a 12-kDa non-glycosylated protein comprising 139 amino acids, including an 18-amino acids signal peptide. This protein, called YZP, has the ability to induce an increase in interleukin (IL) 10 secretion by B lymphocytes and suppress the production of pro-inflammatory cytokines by lipopolysaccharide (LPS)-activated macrophages [14]. Recently, He et al. characterized a novel 12-kDa protein named musarin. This protein shows significant growth inhibition on multiple human colorectal cancer cell lines in vitro. In the animal model, oral ingestion of musarin significantly inhibits tumor colorectal development at the similar level to gefitinib (a tyrosine kinase inhibitor used in oncology), but with a lower number of side effects [54]. The analysis of the literature has shown that mushrooms contain many compounds that can activate the adaptive and innate immune system. The immunomodulating effects of CV have been studied intensively in in vitro and in vivo models. Clinical trials on this subject are also in progress [28,29,55]. Studies have shown that macrophages are one of the main target cells of CV extract. In vitro experiments demonstrated the direct effect of β-glucans and PSP derived from CV on the activation of macrophages, which is manifested by the increased expression of inducible nitric oxide synthase (iNOS) and production of reactive nitrogen intermediates and reactive oxygen intermediates [48,56]. The best reported immunomodulatory effect of CV is induction of cytokine productions. The water-extracted CV compounds, such as PSP and PSK, stimulate in vitro the secretion of IL-1β, IL-6, and tumor necrosis factor α (TNF-α) in different macrophage lines [57,58,59]. Moreover, the peritoneal macrophages isolated from the PSP-treated mice exhibit also increased release of prostaglandin E2 [58]. Considerable levels of research have been devoted to understanding how active compounds of CV mushroom interact with macrophages. Several studies have shown that the effect of the whole CV extract as well as PSP and PSK is mediated through Toll-like receptor (TLR) 4 signaling pathway, including the induction of nuclear factor κB (NF-κB) [57,59,60] and TRAF6 transcription, phosphorylation of c-Jun (a component of the transcription factor called activator protein 1 (AP-1)) [59,60], and increased expression CD14 glycoprotein (co-receptor especially required for LPS recognition by TLR4) [57]. It has been also shown that the whole CV extract induces production of cytokines, which is mediated by the phosphoinositide 3-kinase pathway [57]. In addition to TLR4, TLR2 and dectin-1 receptors are also involved in CV recognition by macrophages. Quayle et al. demonstrated that during stimulation of macrophages with PSK, a β-glucan fraction is recognized by the dectin-1 receptor, whereas lipid fraction towards TLR2 [47]. The ability of PSK to induce TNF-α production by macrophage as a result of TLR2 activation was also observed by Coy et al. [61]. Moreover, the dectin-1 signaling pathway, triggered by β-glucans isolated from CV, elicits TNF-α, nitric oxide and iNOS production leading to activation of macrophages toward phagocytosis [45,46]. Induction of phagocytosis in macrophages upon stimulation with β-glucans is also related to the increased expression of the scavenger receptor B1 (SR-B1) [20]. Numerous studies have shown that the CV extract affects all populations of peripheral blood mononuclear cells (PBMCs) as well as single cell population. One of the most documented effects of CV compounds (i.e., PSP and polysaccharides) and whole CV extract on PBMCs is the increased proliferation response. This mitogenic effect has been observed for human and rat PBMCs [62,63], human and rat lymphocytes [64,65], murine splenic lymphocytes [66], murine B lymphocytes [17] and human monocytes [67]. Numerous studies have shown that CV compounds, such as polysaccharopeptides and both aqueous and solid fractions of the CV mycelium, stimulate PBMCs to the secretion of predominantly pro-inflammatory cytokines. The CV extract-induced production of IL-1β, IL-2, IL-6, IL-12, and TNF-α was demonstrated in rat PBMCs [63], rat lymphocytes [65,68], and murine splenic lymphocytes [66]. Similarly, it was also reported that human PBMCs derived from healthy donors stimulated with polysaccharopeptides derived from CV secrete TNF-α [62], IL-1α, IL-2, IL-6, IL-8, IL-10, macrophage inflammatory protein 1 (MIP-1), granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF) [69,70], and interferon-γ (IFN-γ) [70,71]. Interestingly, human PBMCs isolated from breast cancer patients also exhibit an increased expression of TNF-α, IL-6, and IL-12 in response to PSP [71]. Several studies have shown that the effect of CV compounds on PBMC activation is mainly mediated through TLRs. Human PBMCs isolated from healthy donors and treated with PSP show upregulated expression of TLR4, TLR5, TLR6, and TLR7 as well as increased levels of multiple key molecules of TLR signaling pathway, such as TRAM, TRIF, and TRAF6 [69]. Interestingly, PSP also activates the TLR4-TIRAP/MAL-MyD88 signaling pathway in PBMCs derived from breast cancer patients [71]. The polysaccharides from CV exert immunoregulatory effects on B cells also via TLR4 involvement, and in consequence, inducing activation of the mitogen-activated protein kinase (MAPK) and NF-κB signaling pathways [17]. In contrast, PSK activates NK cells and monocytes to produce cytokine through binding to TLR2 [72,73]. Moreover, it has been also reported that CV compounds, including polysaccharides and PSK, are able to enhance antibody production in B cells after binding to the B cell receptor [17,74] (Figure 1). Among the bioactive properties of compounds derived from CV, their anti-viral activity against numerous viruses is well described. The high therapeutic index of CV extract was discovered against herpes simplex virus (HSV) type 1 and HSV type 2 in the experiments conducted on the kidney epithelial cells in vitro (EC50 = 77 µg/mL measured for the both HSV types) [75]. Liu et al. revealed that PSK can inhibit Epstein–Barr virus (EBV)-infected B and T cells and activate natural killer (NK) cells [76]. It has also been reported that PSP has an inhibitory effect against human immunodeficiency virus (HIV) type l reverse transcriptase and protease that are two enzymes of paramount importance to the life cycle of HIV (IC50 = 150 μg/mL and IC50 = 6.25 μg/mL measured for the interaction between HIV-1 gp120 and immobilized CD4 receptor and for the potent inhibition of recombinant HIV-1 reverse transcriptase, respectively) [77]. Rodriguez-Valentín et al. observed that PSP exerts an anti-HIV activity mediated by TLR4 and promotes the upregulation of specific anti-viral chemokines (RANTES, MIP-1) and stromal cell-derived factor 1 (SDF-1α)) known to block HIV-1 co-receptors [78]. Furthermore, oral administration of β-glucans from CV improves survival and reduces lung viral titers and weight loss in chickens and mice infected with the influenza virus [21]. CV-based vaginal gel is also available for treating women with cervical uterine high-risk human papillomavirus (HPV) infection [79,80]. Since CV compounds possess anti-viral properties against numerous viruses, it is likely that bioactive metabolites from CV might be considered as an anti-viral option against the novel coronavirus SARS-CoV-2. SARS-CoV-2 belongs to the family of coronaviruses that contains positive-sense single-stranded RNA [81]. The main viral protease, which plays an essential role in the viral life cycle, has been proposed as a key therapeutic target for drug development against coronavirus [82,83]. Since there are no effective anti-SARS-CoV-2 drugs, the natural products isolated from CV can be considered for the prevention and treatment of COVID-19. Hetland et al. believe that CV may be utilized directly against SARS-CoV-2 infection as well as to prevent the immunological overreaction and harmful inflammation associated with COVID-19 [84]. According to Saxe, who is leading the MACH-19 (Mushrooms and Chinese Herbs for COVID-19) ongoing clinical trials approved by the Food and Drug Administration (FDA), the combination of CV with another fungus–agarikon (Fomitopsis officinalis) offers physiologically plausible immunomodulating capabilities against SARS-CoV-2 through the interaction with T lymphocyte receptors [85]. Rangsinth et al. examined 36 mushroom-derived bioactive compounds that potentially serve as the inhibitors of SARS-CoV-2 main protease. Indeed, 25 of 36 candidate compounds displayed the potential to inhibit this main viral protease. The most promising seems to be a betulinic acid derived from CV [86]. It is well established that COVID-19 is characterized by noticeably high concentrations of pro-inflammatory factors, such as IL-1, IL-2, IL-6, IL-8, TNF-α, monocyte chemoattractant protein-1 (MCP-1), G-CSF, GM-CSF, and many others [87]. Uncontrolled production of pro-inflammatory cytokines leads to cytokine storm in the lungs, which is initiated by the binding of the SARS-CoV-2 virus to the TLRs [88]. High levels of pro-inflammatory factors along with oxidative stress in patients with COVID-19 lead to fatal effects, such as acute respiratory distress syndrome (ARDS), pulmonary fibrosis, and death [87]. Zhang et al. demonstrated that anti-inflammatory therapy, including suppression of pro-inflammatory cytokine production, might have a therapeutic effect on viral diseases [89]. Numerous in vitro studies revealed the anti-inflammatory effects of both whole CV extract and its compounds, i.e., polysaccharopeptides, and proteins on PBMCs [63], B cells [14] and macrophages [14,57,90]. The anti-inflammatory properties of CV extract are associated, among others, with its ability to block the physical associations of pro-inflammatory factor, such as LPS with the specific receptors on immune cells (e.g., TLR4 or CD14 receptor) and decreasing the expression of these receptors. In consequence, a downregulation of NF-κB activity and pro-inflammatory cytokine production has been observed [57,90,91]. As an anti-inflammatory agent, CV extract has shown benefit in experimental animal models of osteoarthritis [35], inflammatory bowel disease [92], and traumatic brain injury [93]. Besides anti-inflammatory effects, the active compounds from CV, such as polysaccharides and protein-bound polysaccharides, also exhibit anti-oxidant properties by inducing the radical scavenging activity of superoxide dismutase and glutathione peroxidase, which was confirmed in vitro [39,94] and in vivo [37,95,96]. Published data indicate that active compounds of CV extract have the ability to inhibit inflammation and oxidative stress that is involved in the severe course of COVID-19. Furthermore, since natural products derived from CV show high efficiency in the treatment of many viruses, such as HIV, HPV, HSV, EBV, and influenza, the efficiency of CV compounds in the treatment of COVID-19 should be further investigated. There are evidences that, in response to the both whole CV extract and its polysaccharopeptides treatment, immune cells produce cytokines with anti-viral properties, such as IL-12 [66,71,97,98], IFN-γ [66,70,99], and IL-2 [90,98]. The role of these cytokines in the treatment of COVID-19 is widely discussed, showing that IFN-γ is key for restraining SARS-CoV-2 infection [100]. IL-12 is required to maintain NK cell numbers in the early phase of SARS-CoV-2 infection [101] and IL-2 deficiency appears leading to serious effects, such as weak response for our immune system against SARS-CoV-2 [102]. All these findings indicate that the ability of CV compounds to induce anti-viral cytokine production by immune cells can be considered as a potential mechanism of its action against SARS-CoV-2 (Figure 2). The compounds from CV, such as protein-bound polysaccharides, also induce dendritic cell maturation as well as anti-viral cytokine production by activated dendritic cells [97,103,104] (Figure 1), and they have the ability to enlarge draining lymph nodes with the higher number of activated dendritic cells [97]. This adjuvant-like activity of CV compounds may have potential therapeutic value in the preparation of a more effective COVID-19 vaccine. It is also an important issue since dendritic cells have an essential role in defending against SARS-CoV-2 infection [105,106,107] (Figure 2). Nowadays, chemotherapy, hormonotherapy, and targeted therapy are regarded as one of the most promising cancer systemic treatment approaches [108,109]. However, oncogene mutations, epigenetic changes, or changes within the tumor microenvironment may, among others, trigger a strong resistance of cancer cells to various modern anticancer drugs, resulting in increased tumor cells invasion and metastases [108,110]. Therefore, for these tumors, additional treatment potentiating inhibition of their proliferation and progression may increase the survival time of patients. There are many studies that show that bioactive compounds of CV mushroom sensitize cancer cells towards the cytotoxic effects of chemotherapeutic agents [24,111,112,113] and additional drugs used in cancer therapy [114]. Protein-bound polysaccharides from CV enhance the apoptotic machinery induced by doxorubicin and etoposide in estrogen receptor (ER) negative human breast cancer [24] and leukemia cells, where this effect is associated with an induction of S-phase cell cycle arrest and caspase 3 activation [111,115]. The PSP pre-treatment increases also the response of human leukemia cells to camptothecin (CPT), where likewise by induction of cell cycle arrest in the DNA synthesis phase, PSP sensitizes the cancer cells to undergo apoptosis induced by CPT [116]. The combination therapy of PSK and docetaxel, examined in murine model of human prostate cancer, revealed that CV components augmented tumor regression and apoptosis of cancer cells compared to the activity of this chemotherapeutic agent alone [113]. Studies performed on other animal cancer models also described PSK-boosted effects of docetaxel-induced tumor cell apoptosis [117,118]. A recent report of the study performed using intratibial breast cancer murine model also demonstrated that CV alone is effective in decreasing tumor progression, whereas in combination with zoledronic acid (ZOL), which is used in adjuvant therapy for breast cancer [119], it shows significant anti-tumor, anti-metastasis, and anti-osteolytic effects [114] (Figure 3). There are plenty in vitro and in vivo studies demonstrating that CV compounds, among them PSP and PSK, besides cancer cells sensitization to various chemotherapeutic agents, can also induce tumoricidal effects [65,91,98,115,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134] and have inhibitory effect on tumor growth and metastasis in animal models [66,98,120,135,136]. These effects are associated with reduced proliferation mainly via cell cycle arrest [120,123,124,131,137,138] and induction of different mode of cancer cells death, such as apoptosis, necrosis, or necroptosis [120,121,122,124,125,127,128,133,134,136]. In the literature, discrepancies of CV outcomes towards cancer cells are easy to observe. This may result from the preparation and extraction methods of whole CV extract, the use of its single isolated compound as well as its concentration and cancer cell type [139] (Table 1). However, direct inhibition of tumor cell proliferation induced by CV extract and its compounds, such as PSK, PSP, and CV peptide, has been reported for leukemia [134,140], breast cancer [65,68,91], melanoma [120,128], colon cancer [129], and human esophageal carcinoma [131]. The molecular mechanism of this inhibition is still under constant investigation. The disruption of CV-treated cancer cell cycle progression and arrest at G0 phase [138], G0/G1 phase [120,124,131,137], or G1/S [111,112,123] and G2/M [123] phases have been reported. The observed anti-proliferative and cytotoxic effects of CV towards cancer cells are comparable to those induced by chemotherapeutic agents and are associated with oxidative stress that induces cancer cell death [91,127,128]. Pawlikowska et al. have found that CV-induced ROS generation trigger non-pigmented melanoma cells death [128], whereas Jędrzejewski et al. have also confirmed the ROS-dependent cytotoxic activity against breast cancer cells in the pro-inflammatory environment created by LPS [91]. The in vitro and in vivo molecular studies revealed that CV extract acting alone can induce cancer cell death through different cell death modalities. The apoptotic machinery is triggered by CV components in leukemia [115,121,125,134,136], breast cancer [98,122,124], and human esophageal carcinoma cells [131]. The components of CV extract are shown to induce mitochondria-mediated apoptosis pathway, since the release of cytochrome c, activation of caspases (-3, -8, and -9), and upregulation of the expression of Bax with a concomitant downregulation of Bcl-2 is observed [115,123,136]. The study of Ho et al. also implicates that the p53 protein might differentially act as a major upstream transcriptional apoptosis activator in different cancer cell types, among them breast cancer ones [122]. Additionally, Hirahara et al. have proven that apart from caspase-3 triggering, the activation of p38 MAPK signaling cascade is involved in the PSK-induced apoptosis [134]. The upregulation of early transcription factors such as AP-1, EGRI, IER2, and IER5, and the downregulation of NF-κB transcription pathways were also found to be involved in the PSP-mediated apoptosis [133]. Besides apoptosis, induction of necrosis as a model of cell death by CV extract has also been observed [120]. The CV-stimulated melanoma cells, which are known to be relatively resistant to drug induced apoptosis [141], were found to possess both apoptotic and necrotic tumor cell death features [120]. More recent analysis also revealed that CV-induced cell death of melanoma cells is regulated by receptor-interacting protein-1 (RIPK1) and ROS, and that this process is modified by melanin content in melanoma cells [128]. The CV extract has been also reported to induce RIPK1/RIPK3/MLKL-mediated necroptosis in non-pigmented melanoma cells and depigmented (with suppressed melanogenesis) melanoma cells, since co-treatment of the cells with necroptosis inhibitors abrogated the CV-induced cell death [126,127]. The necroptotic cell death mediated by activation of TNF-α/TNFR1 pathway was also observed in CV-stimulated ER-positive breast cancer cells [126]. The extract derived from CV, besides anti-proliferative and cytotoxic activity, also has anti-migratory and anti-invasive potentials against numerous tumor cells, including triple-negative breast cancer [98,142], estrogen receptor (ER)-positive breast cancer [91], colon cancer [129,130], pancreatic and gastric cancer [143], and melanoma [144]. The inhibition of the invasive activity of human tumor cells mediated via suppression of matrix metalloproteinase (MMP) activates, especially those of MMP-2 and MMP-9, is postulated [98,129,130,143]. Recently, Yang and co-workers revealed that CV extract and its bioactive molecules (i.e., SMCV) may reduce cancer cell invasion directly or indirectly through the suppression of TNF-α induced MMP-3 production by inactivating the p38 MAPK pathway in malignant cells [132] (Figure 3). The importance of angiogenesis in cancer progression is well established [150]. The inhibition of this multi-stage process, defined as the new and abnormal blood vessels network development, involves endothelial cells proliferation and organization, migration as well as invasion [116,151]. Since contemporarily used anti-angiogenic drugs, based on the blockade of vascular endothelial growth factor (VEGF) signaling pathway, so far have not displayed a clinically significant benefit either as monotherapy or as a combined anticancer treatment, other methods of endothelial cell inhibition are still sought as valuable new approach to cancer therapy [152,153]. Apart from the improvement of these strategies, several other anti-angiogenic approaches are currently being investigated, such as the use of natural non-toxic phytochemicals as anti-angiogenic agents in cancer disease [154,155]. More than three decades ago, Kanoh et al. and subsequently Wada et al., using murine model of angiogenesis and a rat cornea assay as an in vivo model of fibroblast growth factor (bFGF)-induced angiogenesis, respectively, revealed that PSK from CV suppresses tumor-induced capillary vessel formation [135,156]. Further in vitro analysis showed that PSK inhibits the proliferation of endothelial cells in the presence or absence of basic bFGF as well as suppresses the bFGF-induced MAPK kinase phosphorylation [156]. The evidence of anti-angiogenic activities of PSP were also confirmed in in vivo sarcoma tumor-bearing mouse model [157], where PSP-treated tumor displayed a vasculature of few blood vessels of much less density than controls. This anti-angiogenic effect was mediated via suppression of VEGF gene expression [157]. A recent report revealed that CV compounds have the ability to decrease the release of pro-angiogenic cytokines, such as IL-6 and IL-8, in the chronic inflammatory environment, where this effect is accompanied by a decreased expression of TLR4 and phospho-IκB [91]. The CV effect on the tumor-associated macrophages (TAMs), which are the major source of angiogenic factors boosting the angiogenic switch [158] was proven in co-culture studies, where the CV-induced disruption in the crosstalk between breast cancer cells and macrophages has been reported [142]. By altering TAMs from M2 to M1 subtype, the protein-bound polysaccharides can indirectly reduce the amount of MMPs in the tumor microenvironment. The inhibitory effect on the production of angiogenesis-related factors (MCP-1 and VEGF) in macrophages was also observed [142] (Figure 3). Fever is caused by the immune contact with PAMPs that is sensed by TLRs. The existence of a large number of TLRs enables the innate immune system to detect various PAMPs, including those of bacterial and viral origin. Stimulation of TLRs by PAMPs induces activation of signal transduction cascades. This cascade leads to translocation of NF-κB to the nucleus and activation of interferon regulatory factors 3/7 (IRF3/7) and/or activator AP-1, which cooperate to induce transcription of various cytokines including IFNs (IFNα/β) to counteract infections [159,160]. Thus, fever is not only an increase in body temperature, it is a mechanism that triggers production of many factors that are involved in immune response against many dangers, including viruses and cancer cells. Fever is one of the main presenting symptoms of COVID-19 [161], but little public attention has been given to it as a defense mechanism. This issue was addressed in a review paper highlighting that using non-steroidal anti-inflammatory drugs (NSAIDs) to inhibit SARS-CoV-2 fever in the early stages of infection may contribute to worse outcome [162]. Since fever is a well-recognized immunostimulant, numerous reports on infections show improved survival in organisms that develop fever [161,163]. This effect is a result of fever-triggered activation of the anti-viral response [164]. Additionally, a decrease in replication of various viruses [161], including SARS-CoV-2 [165,166], has been observed in febrile temperatures. Thus, an effectively functioning immune system utilizes fever during infections. Interestingly, cancer patients reveal a history of fewer fevers during infectious diseases than people without cancer [167]. It seems unfavorable for them, since it is known that high fever is inversely related to cancer incidence [168,169]. To date, it is not known what makes it impossible to generate fever in cancer patients in response to pyrogens. Therefore, it seems necessary to find agents that can restore the ability to induce fever in cancer patients. The analysis of CV-induced cytokines in animals showed an increase in the production of pro-inflammatory cytokines, such as IL-6, and TNF-α, typically involved in fever induction [170]. However, it has been found that CV extract alone (in a dose of 50–200 mg/kg) does not provoke fever, but induces a significant decrease in body temperature [171]. Different effects were observed in models of inflammation, when CV was administered together with endotoxin, such as LPS. Pre-injection of CV extract before LPS administration extended the duration of endotoxin fever in rats. This phenomenon was accompanied by a significant elevation of IL-6 level in plasma and pre-treatment of these rats with anti-IL-6 neutralizing antibody prevented this prolongation of endotoxin fever [170]. If an organism is exposed to endotoxin several times, a phenomenon called endotoxin tolerance develops. In this state, a decrease in the expression of pro-inflammatory cytokines is observed. In agreement, it was demonstrated that PBMCs isolated from LPS-tolerant rats produced significantly less IL-6 than the cells isolated from control animals in response to LPS stimulation in vitro. Importantly, the injection of CV extract partially prevented endotoxin tolerance development, and therefore, febrile increase in body temperature accompanied with an increased level of IL-6 was observed [172]. Pawlikowska et al. investigated whether fever-range temperatures affect CV action. It has been found that blood-derived lymphocytes cultured in fever range-hyperthermia (39.5 °C) display remarkable decrease in cell proliferation induced by protein-bound polysaccharides isolated from CV extract. This effect corresponded to the downregulation of mRNA expression of pro-inflammatory cytokines, such as IL-1β and IL-6. Furthermore, expression of these cytokines was also downregulated compared to cells cultured at 37 °C and stimulated with CV extract alone. Interestingly, in the cells which underwent combined treatment compared to ones stimulated with CV extract alone, the mRNA of TNF-α was slightly increased [68]. Despite PSK produced by Kureha Chemicals (Iwaki, Japan) and PSP being introduced on the market [173] in Japan in 1977 and China in 1987 [29], its clinical use in Europe and USA is still not approved by the European Medicines Agency (EMA) and FDA. Furthermore, in addition to in vitro studies and those using animal models on the role of CV administration during cancer and infectious diseases, only few clinical trials were performed or are ongoing. Torkelson et al. observed that in breast cancer patients treated with radiotherapy, the administration of CV extract increases NK cytotoxic function and lymphocyte counts [12]. In the other clinical trials, the breast cancer patients who have taken PSP and Danshen (another herbal derivative from Salvia miltiorrhiza) respond to the treatment with the increase in T-helper lymphocytes (CD4+) and B lymphocytes number [174]. An elevation in leukocyte and neutrophil counts, as well as serum IgG and IgM levels, were also observed in non-small cell lung cancer patients treated with PSP [175]. In addition, Bao et al. noticed lower lymphopenia during radiotherapy of patients with nasopharyngeal carcinoma after the administration of combination of PSP-Danshen [176]. Clinical trials conducted in gastric, lung, or colorectal cancer patients have shown that simultaneous PSP/PSK treatment along with chemotherapy boosts their immune function, including NK cell activity [13,177,178]. Both molecules have been reported to possess a beneficial effect on extending the survival rate in cancer patients [13]. Moreover, trials involving patients with advanced hepatocellular carcinoma with malfunction of the liver confirmed the positive effect of daily consumption of CV capsules on their quality of life [179]. Polysaccharides from CV are also promising in the treatment of hepatitis B as well as HPV [29,180]. Serrano et al. demonstrated that Papilocare (Procare Health, Valencia, Spain), which is a CV-based vaginal gel has given a better clinical benefit than the conventional treatment in clinical practice for high-risk HPV patients in terms of its efficacy to treat HPV-related cervical lesions and to clear all HPV strains after a single 6-month period of use [181]. Another clinical trial, conducted by Scuto et al., showed that CV supplementation minimizes consequences associated with neurodegeneration, neuroinflammation, and oxidative stress of cochleovestibular system pathologies, including Meniere’s disease [182]. Anti-oxidative properties of CV were also noticed in clinical trials involving patients with breast cancer [95,96]. In addition, polysaccharopeptides from CV have been clinically tested as a prebiotic on the gut microbiota of healthy volunteers [42] and in patients with inflammatory bowel diseases (CV powder as an ingredient of Mycodigest supplement [183]). Furthermore, in a clinical trial database approved by FDA [183], there are two ongoing clinical trials related to COVID-19. One of them concerns testing mushroom-based products as a drug for COVID-19. The influence of 14-days consumption of CV or Fomitopsis officinalis (Fo) capsules on recovery patients with COVID-19-positive test with mild-to-moderate symptoms, who do not require hospitalization will be assessed. Taking into account data on the immunomodulating and immunostimulating properties of mushroom extract, the scientists from the University of California, decided to use CV or Fo capsule as an adjunct to COVID-19 vaccination. The randomized, double-blind clinical trial to evaluate the effect of dietary supplementation of CV or Fo capsule on titration of antibody and on mild side-effects after vaccination is planned. Apart from clinical trials conducted on cancer or infectious patients, the beneficial immunostimulating effect of CV extract was also confirmed in healthy volunteers in a randomized, double-blind clinical trial conducted by Wong and co-workers [184]. The elevation of PBMC gene expression of IL-2 receptor, increase in absolute counts of T helper cells and ratio of T helper/T suppressor and cytotoxic cells as well as enhancement of ex vivo production of IFN-γ by activated PBMCs have been observed. Importantly, CV consumption had no adverse effects on liver or renal functions, and therefore, it can be considered beneficial for the immunological defense of healthy subjects [184]. Since the current most common challenges in medicine, among which COVID-19 and cancer, are still fatal, there is an urgent need for finding new remedies. Medicinal mushrooms have been always an important source for the discovery of new therapeutics for human diseases. An ancient Chinese formulation of CV has been used in traditional Chinese herbal medicine for over 2000 years. In recent years, scientific research into its health-promoting properties has intensified. This mushroom shows a wide spectrum of benefits, which may be useful in combating modern medical challenges. Herein, we have presented data determining the proof of strong anti-viral, anti-inflammatory, anti-oxidative, and immunostimulating properties of CV. Simultaneously, other reports confirmed the impressive anti-cancer response of CV extract and its compounds directed towards wide range of cancer types and revealed the molecular background of this process. By induction of different cell death modalities, such as apoptosis or necroptosis, CV extract appears to be an effective adjuvant therapy. Moreover, analysis of other reports revealed that CV also affects fever, the innate immunity mechanism beneficial for both cancer and viral infections recovery. This review has some limitations resulting mainly from the procedures of CV preparation performed by a variety of research groups. The authors used different doses of either whole CV extract or its single compounds. Furthermore, they often used different extraction methods, which can result in inconsistent compositions of an extract, even if the same material was used. Moreover, many papers do not provide detailed information regarding the composition of the CV extract, which makes it impossible to clearly compare the results obtained by different authors. Furthermore, research showing a direct effect of CV extract in the treatment of SARS-CoV-2 are needed to clearly confirm its potential as an effective agent against COVID-19 disease. Despite the discrepancies mentioned above, Coriolus versicolor belongs to standard oncologic treatment in the mainstream modern Japanese cancer system. The Western countries’ oncologists have only recently begun to turn their attention to immune potentiating therapies. Therefore, in order to proceed with clinical trials in the United States and Europe, the immunological and anti-cancer mechanisms must be well-established to justify proceeding with the prospective human clinical trials. In this review, a wide spectrum of research data showing the potential of CV in the treatment of COVID-19 and cancer diseases was presented. The dissemination of this knowledge is important to plan randomized clinical trials confirming all these beneficial effects in patients.

PMC10003410

Valentina Artusa,Luana Calabrone,Lorenzo Mortara,Francesco Peri,Antonino Bruno

Microbiota-Derived Natural Products Targeting Cancer Stem Cells: Inside the Gut Pharma Factory

05-03-2023

cancer stem cells (CSCs),drug resistance,gut microbiota,microbiota-derived metabolites,bioactive compounds,natural products

Cancer stem cells (CSCs) have drawn much attention as important tumour-initiating cells that may also be crucial for recurrence after chemotherapy. Although the activity of CSCs in various forms of cancer is complex and yet to be fully elucidated, opportunities for therapies targeting CSCs exist. CSCs are molecularly distinct from bulk tumour cells, so they can be targeted by exploiting their signature molecular pathways. Inhibiting stemness has the potential to reduce the risk posed by CSCs by limiting or eliminating their capacity for tumorigenesis, proliferation, metastasis, and recurrence. Here, we briefly described the role of CSCs in tumour biology, the mechanisms involved in CSC therapy resistance, and the role of the gut microbiota in cancer development and treatment, to then review and discuss the current advances in the discovery of microbiota-derived natural compounds targeting CSCs. Collectively, our overview suggests that dietary intervention, toward the production of those identified microbial metabolites capable of suppressing CSC properties, is a promising approach to support standard chemotherapy.

Microbiota-Derived Natural Products Targeting Cancer Stem Cells: Inside the Gut Pharma Factory Cancer stem cells (CSCs) have drawn much attention as important tumour-initiating cells that may also be crucial for recurrence after chemotherapy. Although the activity of CSCs in various forms of cancer is complex and yet to be fully elucidated, opportunities for therapies targeting CSCs exist. CSCs are molecularly distinct from bulk tumour cells, so they can be targeted by exploiting their signature molecular pathways. Inhibiting stemness has the potential to reduce the risk posed by CSCs by limiting or eliminating their capacity for tumorigenesis, proliferation, metastasis, and recurrence. Here, we briefly described the role of CSCs in tumour biology, the mechanisms involved in CSC therapy resistance, and the role of the gut microbiota in cancer development and treatment, to then review and discuss the current advances in the discovery of microbiota-derived natural compounds targeting CSCs. Collectively, our overview suggests that dietary intervention, toward the production of those identified microbial metabolites capable of suppressing CSC properties, is a promising approach to support standard chemotherapy. Nowadays, several highly successful cancer therapies are available, with the majority of regimens combining surgery, radiotherapy, and medicine, which includes chemotherapy, targeted therapy [1], and most recently, immunotherapy [2]. The type and stage of the cancer being treated determine which techniques should be employed. One of the most important goals in cancer biology is to discover cells and signalling pathways that are essential for tumour regression, thus developing novel drugs that can abrogate the growth and metastasis of malignant tumours. Among medications, conventional cancer chemotherapy remains one of the most widely used approaches. Traditional chemotherapy is an aggressive form of cytotoxic drug therapy that destroys all rapidly proliferating cells, whether they are malignant or not. Thus, this method also destroys perfectly healthy cells. On the contrary, mechanism-based therapies, such as targeted therapy and immunotherapy, are designed to find and slow the growth of cells that possess a specific cancerous phenotype. Compared to the scatter-gun approach of chemotherapy, targeted therapy appears more sniper-like, accurately destroying its target without causing any collateral harm to otherwise healthy cells. Because targeted therapies only target cancer cells, some patients report fewer side effects than those with chemotherapy, which in turn presents many bottlenecks, including a lack of specificity, which has an impact on healthy tissues, as anticipated, but also rapid drug metabolism and both intrinsic and acquired drug resistance, all contributing to decreased efficacy [3,4]. In this scenario, understanding the molecular mechanisms of cancer and tumour cell biology represents an area of investigation that poses a unique challenge to clinical oncologists and cancer researchers. Here, after introducing CSCs and their role in cancer biology, we briefly describe the mechanisms involved in CSC therapy resistance. Next, we focus our attention on the gut microbiota and its relationship with cancer development and treatment. The main purpose of our review is to provide a comprehensive summary of the currently available literature describing microbiota-derived natural compounds targeting CSCs. CSCs describe a class of stem-like cells of tumour origin that behave similarly to normal stem cells in their ability to regulate their cell cycle by switching between a quiescent and a differentiation state. This includes key stem cell features, such as self-renewal [5] and the capability to differentiate into parental tumour cells. Moreover, CSCs participate in fundamental processes of tumour growth and progression, including cancer cell proliferation, metastatic spread, and immune evasion. According to the literature, CSCs exist in most haematological and solid tumours. A cluster of differentiation (CD)133+ CSC population was revealed in colorectal cancer (CRC) in 2007 [6,7] after CSCs were first identified in 1994 in acute myeloid leukaemia (AML) [8]. Since then, their significance in solid cancer has been thoroughly researched. To date, the advent of modern flow cytometry and cell sorting techniques has allowed for the identification of cell populations with CSC features, based on their expression of specific markers. Indeed, human CSCs were recognised in other solid tumours, including breast [9], brain [10], prostate [11,12], lung [13], and pancreatic [14,15] tumours. Notably, in non-obese diabetic/severe combined immunodeficient (NOD/SCID) mice, as few as 100 CSCs were sufficient to produce tumours [9]. Nowadays, CSCs are identified and classified according to the markers they express, including cell surface antigens, stemness-related markers (OCT4, SOX2, and NANOG), or high aldehyde dehydrogenase (ALDH) activity. To complicate the picture, CSC surface marker expression varies by tissue type and even by tumour subtype. For example, CD44+CD24−/low and ALDH+ CSCs were characterised in breast cancer [16,17], along with CD133+CD44+ in colon [18,19], brain [20], and lung [21] cancer; CD34+CD8− in leukaemia [22]; CD44+ in head and neck tumours [23]; CD90+ in liver cancer [24]; and CD44+/CD24+/ESA+ in pancreatic cancer [25]. CSCs were at first thought to make up only a small portion of a solid tumour’s overall cell population; however, according to some estimates, up to 25% of cancer cells may display CSC characteristics [26]. Regarding the genesis of CSCs, a variety of theories have been proposed. According to one theory, CSCs develop from healthy stem/progenitor cells when they undergo a specific genetic mutation or environmental change that confers to them the capacity to cause tumours. In terms of cellular characteristics, phenotype, activity, and also cell surface markers, certain CSCs exhibit similarities to typical stem/progenitor cells, thus lending credence to this notion [27]. A second explanation describing the origin of CSCs contends that they originate from healthy somatic cells that undergo genetic and/or heterotypic changes to develop stem-like properties and malignant behaviour. Emerging data showing that CSCs are resistant to standard chemotherapy and radiation treatment and are very likely to be the cause of cancer recurrence and metastasis have enhanced the clinical significance of CSCs [5,28,29]. Chemoresistance, recurrence, and metastasis remain the primary causes of cancer mortality, advances in therapeutic development notwithstanding. Numerous investigations have revealed that a small subgroup of cancer cells, called CSCs, is the cause of the tumour’s recurrence. Some regulatory signalling pathways, including the Wnt/β-catenin, Sonic Hedgehog (SHH), and Notch pathways, which are important in the self-renewal process, are shared by CSCs and regular stem cells [30]. Accumulating evidence has shown that the expression of markers related to stemness is crucial for tumour maintenance and that these molecules also mediate cancer therapy resistance. Furthermore, resistant CSCs might cause metastasis at a distant site, resulting in the formation of a metastatic tumour [31]. The mechanisms through which CSCs adapt to escape cancer therapy are summarised in Figure 1 and further discussed below. Strong proof of a connection among CSCs, tumour cell plasticity, cell-cycle quiescence, and immune suppression in cancer originates from a wide range of publications. Several studies have shown that CSCs can conceal themselves from the immune system at the onset, avoiding detection during the immunosurveillance phase. Cell cycle is a multi-phased, intricate, and tightly regulated process. Cell cycle control requires the phase-specific transcription of cell cycle genes. Mutations in cell cycle genes can make healthy cells more inclined to acquire a malignant phenotype [32]. In a very elegant study, Agudo et al. [33]. demonstrated that fast-cycling cells, such as Lgr5+ stem cells detected in the stomach, ovaries, and mammary glands, experienced immune clearance. Conversely, slow-cycling stem cells, such as those in muscle and hair follicles, were resistant to just EGFP death-inducing (Jedi) T-cell eradication. Furthermore, the ability of latent stem cells to autonomously downregulate the antigen-presentation pathway via the transactivator NLRC5 is crucial for immunological escape. Notably, the process is reversible once stem cells enter the cell cycle [34]. It has been speculated that cancer cells use the characteristics of dormant stem cells to evade immune cell identification (Figure 1A). In this regard, it was recently shown that CSCs have immune-evasive properties when they enter quiescence [35]. Accordingly, in xenotransplant investigations, leukaemia CSCs were discovered to be chemotherapy-resistant and to be in the G0 (resting) phase of the cell cycle [36]. We can therefore envisage that the immunologically privileged status of CSCs is dependent on their capacity to adopt a quiescent state. Indeed, CSCs’ pharmacological resistance results from a mismatch between their relatively slow cell cycle [37] and the rapidly proliferating cancer cells that multiple chemotherapeutic treatments are designed to target. Organelles, protein aggregates, and intracellular pathogens are the types of cellular cargo that are engulfed by double-membraned vesicles called autophagosomes during the evolutionarily conserved catabolic process known as autophagy, which results in their destruction and recycling after fusion with the lysosome [38]. CSCs exhibit autophagy reliance equal to that in tissue-resident stem cells (Figure 1B). For example, it was demonstrated that the secretion of interleukin (IL)-6 from CD44+/CD24low/− breast cancer cells is dependent on autophagy and necessary for CSC maintenance [39]. In addition, autophagy is induced by a wide range of cancer therapies. For example, Imatinib™, a small molecule tyrosine kinase inhibitor used to treat metastatic gastrointestinal stromal tumour (GIST), causes the induction of autophagy in GIST cells [40]. According to preclinical data, stress-induced autophagy helps CSCs survive, while blocking autophagy can help in overcoming CSC resistance [41]. In the case of Imatinib™-treated GIST cells, tumour cell apoptosis was induced by inhibiting autophagy, using the lysosomotropic drug chloroquine (CQ) [40]. Moreover, in prostate cancer, clomipramine (CMI), CQ, or metformin treatment enhanced apoptosis and dramatically reduced cell viability by blocking autophagy in enzalutamide-resistant cells, overcoming the resistance to enzalutamide, an inhibitor of the androgen receptor signalling pathway used for the treatment of metastatic castration-resistant prostate cancer [42]. As per normal stem cells, CSCs are frequently found in anatomically separate locations, hidden niches within the tumour microenvironment (TME) that provide a protective physical and chemical environment from direct contact with drugs and the host immune system. In tumour niches, intricate interactions between cells and the extracellular matrix (ECM) create a complex environment that determines stem cell resilience and the preservation of stemness. ECM remodelling also impacts CSC survival (Figure 1C). On one hand, a physical barrier created by enhanced ECM stiffness can protect CSCs from chemotherapeutic drugs. On the other hand, ECM degradation by matrix metalloproteinases (MMPs) can allow for the release of cytokines and growth factors that enhance tumour cell invasion, metastasis, and angiogenesis [43]. Moreover, solid tumours are commonly affected by hypoxia. The capacity of the pre-existing blood vessels to meet the oxygen requirement is frequently exceeded in cases of uncontrolled cell multiplication [44]. When under hypoxic and therapeutic stress, CSCs use a variety of signalling pathways that are modulated by hypoxia-inducible factor (HIF) signalling to modulate their stemness. HIF-induced gene products include epithelial-to-mesenchymal transition (EMT) programmers, glycolysis-associated molecules, drug resistance-associated molecules, miRNAs, and VEGF [45]. Therefore, by maintaining CSCs in their undifferentiated stem cell state, which enables self-renewal and the accumulation of epigenetic and genetic mutations, hypoxic environments may promote the formation of malignant clones [46]. In addition, the TME has been shown to have an acidic extracellular pH, which is a consequence of lactate accumulation via increased anaerobic glycolysis in hypoxic conditions [47]. In that respect, it was recently demonstrated that extracellular acidosis may cause cancer cells to develop stem-like characteristics and aid in the proliferation of the CSC subpopulation [48]. Lastly, tumour cells, inflammatory cells, cancer-associated fibroblasts, and CSCs are just a few of the cell types that belong to the specialised microenvironment known as the perivascular niche, which is found right next to blood vessels. Here, the stemness features of CSCs, such as their capacity for self-renewal, multipotency, and tumorigenic potential, are maintained by molecular interactions among various cell types [49]. CSC chemoresistance has also been linked to intracellular drug inactivation (Figure 1D). A class of detoxifying enzymes known as ALDHs is frequently upregulated in cancer cells leading to treatment resistance. ALDHs are overexpressed in cancer cell clusters with stem-like characteristics, where they contribute to the defence of cancer cells by converting harmful aldehydes into more soluble and less reactive carboxylic acids [50]. For example, ALDH is crucial for contrasting the effects of diverse chemotherapeutic agents, such as cyclophosphamide, irinotecan, temozolomide, paclitaxel, doxorubicin (DOX), and epirubicin [51,52,53,54,55]. In addition, ALDH has been a widely used marker for CSC identification. Increased metabolic activity, along with conventional anticancer drugs, leads to aldehyde generation, which results in DNA double-strand breaks (DSBs) via reactive oxygen species (ROS) and lipid peroxidation. Thus, the overexpression of ALDH is essential for CSC survival. Moreover, it can inhibit immunogenic cell death (ICD) and cause the activation and growth of immunosuppressive regulatory T cells (Tregs), thus influencing immune cell activity in the TME [50]. Additionally, in NOD/SCID mice, acute myeloid leukemic cells that possess increased ALDH activity seem to have more capacity for engraftment compared to their ALDH-negative counterparts [56]. Moreover, the epigenetic inhibition of thymidine phosphorylase has been observed in CSCs, resulting in the therapeutically inefficient transformation of active 5-fluorouracil (5-FU) and methotrexate [55,57,58]. Finally, CSCs use thiol glutathione to inactivate platinum [59]. One of the primary defence mechanisms for CSCs is the transcription of multifunctional efflux transporters from the ATP-binding cassette (ABC) gene family (Figure 1E) [60]. By using the energy of ATP hydrolysis to adenosine diphosphate (ADP) [61], these transporters actively efflux peptides, inorganic anions, amino acids, polysaccharides, proteins, vitamins, and metallic ions [62]. Intrinsic CSC-chemoresistance has been associated with their ability to express proteins of the family of ABC transporters, which results in drug extrusion and loss of effectiveness. Increased ABC transporter expression, including ABCB1 (P-glycoprotein/MDR1), ABCC1 (MRP1), and ABCG2 (BCRP), is one of the most well-established strategies for cancer cells to acquire multidrug resistance (MDR) [63]. A plethora of drugs that modulate MDR-ABC transporters have been developed during the past years, and some of them have also demonstrated significant efficacy in clinical trials [63]. However, one must bear in mind that in addition to promoting the growth of tumours, stem cell-driven tissue repopulation also promotes the growth of adult-specific normal tissues, such as the bone marrow, digestive tract, and hair follicles; thus, the complete inhibition of ABC transporters could have severe drawbacks. A large number of chemotherapy treatments, including platinum-based drugs and radiation, kill cancer cells by causing DNA damage. Studies have demonstrated that CSCs are incredibly effective in repairing DNA damage (Figure 1F) [64]. CSCs’ resistance to DNA-damaging therapies is thought to be caused by this enhanced DNA damage response (DDR). DDR is an extremely intricate network made up of numerous pathways, each of which exhibits cross-talk both within the network and with other signalling pathways [65]. When compared to non-stem tumour cells, CSCs have a higher capability for DNA repair either through increased DNA repair pathways or through delayed cell-cycle progression [66]. The MRE11–RAD50–NBS1 (MRN) protein complex, a major sensor of DNA double-strand breaks, is expressed in both normal and cancerous cells, as well as CSCs. However, the MRN function is improved in CSCs through interactions with the CSC-related molecules Notch1, ALDH1A1, CD44, SHH, and BMI1, in contrast to that in non-stem tumour cells [67], or through CD171, which boosts CSCs’ radioresistance and selectively triggers the DNA damage checkpoint [68]. The resting activation status of checkpoint kinases could serve as a crucial defence mechanism for CSCs against genotoxic chemicals when coupled with the induction of DNA repair. Not unexpectedly, several DDR-inhibitory drugs are currently undergoing pre-clinical and clinical testing [66]. In addition, stem cells regulate self-renewal and differentiation via differential configurations of the chromatin structure; thus, it is expected that histone changes and chromatin remodelling following DNA damage differ between stem cells and developed cells. In recent years, it has been evident that chromatin’s epigenetic dysregulation plays a significant role in CSCs development and frequently plays a crucial part in CSCs’ self-renewal throughout tumour growth [69]. Several fundamental features of cellular physiology undergo modifications as a result of the epithelial-to-mesenchymal transition (EMT) program, including alterations to cell morphology, which are related to changes in the cytoskeletal organisation; the dissolution of epithelial cell-cell junctions; loss of apical-basal polarity and concomitant gain of front-rear polarity; acquisition of the ability to breakdown and reorganise the ECM, thus enhancing motility and allowing cell invasion; and alterations to the expression patterns of at least 400 different genes [70]. The relationship between the EMT program and the CSC state raises the possibility that non-CSCs can become CSCs by enacting this program (Figure 1G) [71,72]. Indeed, EMT has been also linked to chemoresistance [73,74]. Worthy of note, an EMT-associated gene-expression signature has been strongly linked with treatment resistance, based on examinations of the relationships between the clinical outcomes of individuals and the gene-expression profiles of the associated tumour samples [75,76]. Moreover, by activating the EMT program, cancer cells can form metastatic colonies [74,77]. More specifically, according to recent studies, cells undergoing partial EMT may exhibit hybrid E/M phenotypes, possess more stem cell-like features, and exhibit more resistance to drugs than cells undergoing complete EMT. Additionally, partial EMT facilitates collective cell movement as clusters of circulating tumour cells or emboli, enhancing cancer cells’ capacity for metastasis and tumour genesis at the secondary regions [78]. There is a unanimous understanding that solid tumours require a sufficient blood supply to grow. The term vasculogenic mimicry (VM), first coined by Maniotis [79], describes the ability of aggressive cancer cells to form de novo perfusable, matrix-rich, vasculogenic-like networks in a way that differs from traditional tumour angiogenesis in that it does not rely on endothelial cells. These new patterns of tumour microcirculation assist in perfusing rapidly growing tumours, removing fluid from leaky arteries, and/or integrating with the body’s endothelial-lined normal vessels [80]. The link between VM and poor clinical outcomes in patient malignancies suggests that VM confers a survival advantage to the aggressive tumour cell phenotype [81,82]. Additionally, preclinical pharmacological studies have shown that VM is connected to anticancer therapy resistance [83]. A significant amount of data suggests that CSCs aid in the development of VM (Figure 1H) [84]. The VM phenotype of tumour cells has a molecular signature that includes upregulated expression of genes related to embryonic progenitors, endothelial cells, vessel formation, matrix remodelling, and coagulation inhibitors, as well as downregulated expression of genes primarily related to lineage-specific phenotype markers [80,85]. It has been shown that chemotherapy and radiation both foster CSC traits in non-stem cancer cells and might even cause non-stem cancer cells to become CSCs [86,87] (Figure 1I); thus, the issue of CSCs not responding to conventional cancer treatments goes beyond the simple inability of these treatments to eradicate CSCs. The plasticity of cancer cells enables the transient acquisition of stemness-related traits. After receiving carboplatin treatment, hepatocellular carcinoma cells developed stem-like characteristics, including the ability to self-renew and the expression of stemness-related genes (SOX2 and OCT3/4), which demonstrated the potential for chemotherapy to generate stemness [88]. Moreover, after being exposed to the chemotherapeutic drug 5-FU, human gastric cancer cell lines demonstrated resistance to 5-FU, as well as characteristics of stemness, such as tumorigenicity and the ability to self-renew [89]. Despite chemotherapy substantially eliminating a large portion of the tumour volume, there cannot be a noticeable clinical improvement if CSCs have not been eradicated to provide long-term disease-free survival. Therefore, CSCs are thought to be a significant target for the development of new anticancer drugs, being that CSC-focused therapy is a key driver for any effective anticancer strategy. In addition to synthetic drugs targeting CSC pathways (reviewed in [30]), dietary components, mostly (poly)phenolic compounds, have shown the ability to inhibit tumour progression [90] and angiogenesis [91]. Nearly all of these naturally occurring phytochemicals with chemopreventive activities also have antioxidant and anti-inflammatory effects. Interestingly, several mechanisms involved in the anticancer effects of dietary phytochemicals target pathways involved in CSC stemness maintenance [92]. Of note, human-ingested nutrients can be transformed by the gut microbiota into useful microbial compounds that closely link diet to cancer [93]. Indeed, the microbiota-derived metabolome has the potential to encourage or prevent carcinogenesis in organs distant from the gut. An emerging field in anticancer research examines the intricate interactions between particular gut microbial metabolites and the advancement or inhibition of cancer cell proliferation [94]. The gut microbiota comprises a multitude of microorganisms, mainly bacteria across over 500 species, of which the number reaches 1013–1014, similar to the number of cells in an adult human [95,96]. The majority of them (about 90%) is represented by two bacterial phyla, the Gram-positive Firmicutes (Bacillus spp., Lactobacillus spp., and Clostridium spp.) and the Gram-negative Bacteroidetes (Bacteroides spp. and Prevotella spp.) [97,98]. In their entirety, gut bacteria have several functions, including food fermentation, vitamin production, protection against pathogens, and immune response stimulation; thus, the intestinal microbial balance is highly relevant to human health [99]. It has been established that the breakdown of the host’s and gut microbiota’s symbiotic relationship can facilitate the onset of numerous disorders, including autoimmune disease [100,101] and cancer [102]. In this scenario, the molecular basis of various long-established epidemiological relationships between certain bacteria and cancer are presently being studied [103]. For instance, the correlation between Helicobacter pylori and the risk of the development and progression of gastric cancer, but also the case of Fusobacterium nucleatum, of which the role in the setting of CRC has been extensively studied [104,105,106,107,108,109,110]. Bacterial infections were associated with cancer stemness in both cases. In the former case, Bessède et al. observed that following H. pylori infection, gastric epithelial cells overexpressed CD44 and acquired CSC features, while in the latter case, Cavallucci et al. revealed that F. nucleatum can contribute to the microbiota-driven colorectal carcinogenesis by directly stimulating colorectal CSCs [111,112]. Additionally, Ha and colleagues provide evidence that EMT and cancer stemness acquisition are induced in oral cancer cells by prolonged infection with Porphyromonas gingivalis [113]. Moreover, there have been documented indirect effects of the gut microbiota on the growth of tumours in tissues outside of the gastrointestinal tract [110]. It is fascinating to note that the gut microbiota, by releasing bacterial products that can enter the bloodstream, can practically influence all host organs and systems and eventually affect cancer progression. This expanding knowledge points out that intestinal dysbiosis may cause carcinogenesis in localised gastric and intestinal cancers and tumours located in distant regions of the body [103,110]. For instance, lipopolysaccharide (LPS), a component of the Gram-negative bacterial cell wall, which is recognised by Toll-like Receptor 4 (TLR4), is one of the molecules derived from gut bacteria that has been demonstrated to promote cancer [110]. In a model of chronic injury-induced liver cancer, LPS-induced TLR4 stimulation increased the expression of the hepatomitogen epiregulin in stellate cells, which had a pro-tumorigenic effect [114]. Additionally, deoxycholic acid (DCA), a metabolite produced by gut bacteria, has also been linked to an increased risk of developing hepatocellular carcinoma when its level is increased due to dietary- or hereditary obesity-induced shifts in the gut microbiota composition [115]. On the other side of the coin, recent studies have observed that the gut microbiota can also exert immunomodulatory and anti-tumoral effects in cancers. For instance, in a rat model, the probiotic bacteria Lactobacillus acidophilus have been found to decrease the occurrence of CRC [116]. Moreover, exopolysaccharides from Lactobacillus spp. were able to slow down cell division in a time-dependent fashion and trigger apoptosis by upregulating the expression of Bax and caspase 3 and 9, while downregulating Bcl-2 and survivin, in a colon cancer cell line (HT-29) [117]. Abdelghani et al. provided a comprehensive list of anti-cancer compounds derived from microbial metabolism and their anticancer activities, which range from apoptotic, anti-proliferative, and cytotoxic activity to chemosensitisation to 5-FU [118]. Along with the investigation of the links between the gut microbiota and cancer, the microbiota of tumours themselves has received some consideration. Interestingly, more research into the microbiota revealed that it was also present within tumour tissues that were previously assumed to be sterile [119]. Furthermore, the local microenvironment and the tumour immunological context seem to interact with the tumour-associated microbiota, or microbial communities found in the tumour or inside its body compartment, ultimately affecting cancer growth and the response to therapy [120]. The intratumoral microbial community further complicates the cancer–microbiota–immune axis, which significantly impacts T-cell-mediated killing and anti-tumour immune surveillance [121]. Recently, Zhou et al. reviewed the hitherto neglected but significant impacts of the small molecules derived from tumour microbiota metabolism on the TME and their essential roles in cancer development [122]. Not only that, numerous instances of the microbiota altering drug metabolism and interfering with immunotherapy have been reported [123,124,125,126], and it is expected that research in this area will continue. From the perspective of “therapeutic microbiology”, the host’s health status can be improved through a variety of approaches: (a) by introducing living, beneficial bacteria (known as probiotics), influencing the microbial composition (probiotics) [127]; (b) providing non-digestible substances, such oligofructose, oligosaccharides, inulin, raffinose, and stachyose (known as prebiotics), which are fermented by endogenous colonised probiotics in the large intestine (colon), promoting the establishment of beneficial microbiota [128]; (c) administering microbial metabolites with low molecular weights (<50, 50–100, and <100 kDa) that have positive effects on health (postbiotics) [129,130]. A significant number of published studies that discuss the capability of postbiotics to regulate different cellular processes and metabolic pathways have been published in the literature and reviewed elsewhere [130,131]. However, the microbiota remains an untapped avenue for finding small-molecule drugs for cancer treatment. Diet and environmental exposures, as well as lifestyle, have a major role in influencing the human gut microbiota composition and its metabolic activity, which can have an impact on health [132,133,134]. CSCs are very dependent on their surroundings for their energy supply; thus, nutrients play a pivotal role in modulating CSC growth or stemness. Over the past few decades, numerous studies have attempted to clarify the processes governing CSCs’ response to diet [135]. The anaerobic microbial population ferments undigested dietary components and host products, primarily mucin, to produce a remarkably wide range of metabolites that reflect both the chemical diversity of the dietary substrates and the microbiota’s unique metabolism [136]. As outlined above, microbiota metabolites, defined as intermediate end products of microbial metabolism, are key players in the microbiota–cancer relationship. These metabolites can be categorised based on two different parameters: origin (intracellular or extracellular) and function (primary or secondary), respectively. While secondary metabolites are produced close to the stationary phase of growth and are not essential for growth, reproduction, or development, primary metabolites are required for the optimal growth of bacteria. Several studies were conducted to assess the health-promoting effects of microbial products; in those cases, researchers described them as ‘biogenic’, ‘cell-free supernatant’, ‘abiotic’, ‘metabiotic’, ‘paraprobiotic’, ‘ghost probiotics’, ‘pseudoprobiotic’, ‘supernatant’, etc. [137]. Only in 2013, the term “postbiotics” was created to describe soluble components secreted by living bacteria or released following bacterial lysis, including enzymes, peptides, teichoic acids, muropeptides derived from peptidoglycan, polysaccharides, cell surface proteins, and organic acids [129]. This definition also gained support from further reports [138,139]. A detailed and exhaustive description of the range of metabolites produced by gut microbial metabolic activity and their roles in health and diseases is beyond the scope of this review and can be found elsewhere [140]. Here, we focus exclusively on the documented effects of microbiota-derived metabolites that specifically target CSCs and their features. Traditional approaches to identifying novel bioactive natural products include extraction, fractionation or isolation, chemical characterisation, and, ultimately, an assessment of the potential beneficial effect through the execution of biological assays [141]. In this connection, cell-free supernatant (CFS), a solution that contains metabolites produced as a result of microbial growth, represents an invaluable metabolite-rich source. For instance, the antioxidant, antimicrobial, and anticancer properties of CFS have been demonstrated [142,143,144]. In 2016, An and Ha showed that the expression of particular CSC markers, CD44, CD133, CD166, and ALDH1, can be inhibited by Lactobacillus plantarum (LP) supernatant. Besides that, combined treatment with LP supernatant and 5-FU: (1) prevented CRCs from surviving and caused cell death by inducing caspase-3 activity; (2) prompted an antitumor mechanism by inactivating the Wnt/β-catenin signalling pathway in chemoresistant CRC cells; and (3) decreased the formation and volume of colonospheres [145]. Later in 2020, the same authors also demonstrated that in 5-FU-resistant CRC cells (HCT-116/5FUR), Lactobacillus plantarum-derived metabolites (LDMs) boost drug sensitivity and have antimetastatic effects as well. By reducing the expression of claudin-1 (CLDN-1), co-treatment of HCT-116/5FUR with LDMs and 5-FU decreased chemoresistance and metastatic activity. Their findings suggested that targeting 5-FU-resistant cells with LDMs and 5-FU cotreatments can be effective [146]. Moreover, Maghsood et al. treated human colon cancer stem-like cells enriched from an E-cadherin shRNA-engineered HT-29 cell line (HT29-ShE) with size-fractionated Lactobacillus reuteri CFS. Their results showed that crude and >50 kDa fractions of CFS significantly decreased the expression of COX-2, a crucial factor in the maintenance and function of CSCs. In addition, they demonstrated that colon cancer stem-like cell apoptosis and cell proliferation were both suppressed by L. reuteri CFS [147]. Diet plays a major role in cancer aetiology and prevention; thus, a healthy diet can be a game-changer factor [148,149,150,151,152]. Moreover, food is a significant source of substrates for the production of microbial metabolites. Amongst the vastness of microbiota-derived metabolites, some have been identified as potential CSC-targeting molecules (Figure 2). Non-digestible carbohydrates, including resistant starch, non-starch polysaccharides, and certain soluble oligosaccharides, reach the large intestine without undergoing any digestion, because of the upper intestine tract lacks certain food-digesting enzymes [153,154]. Short-chain fatty acids (SCFAs) and gases are produced through the anaerobic degradation of such non-digestible fibres by gut microorganisms. SCFAs are aliphatic carbon-based acids, with acetate (C2), propionate (C3), and butyrate (C4) being the most abundant [155]. Several studies have found a link between a high-fibre diet and a lower risk of colon cancer [156,157,158]; this drove scientists toward the investigation of SCFA’s role in carcinogenesis prevention. However, when studying butyrate, researchers faced a contradictory effect: if butyrate effectively inhibited the proliferation of undifferentiated, highly proliferative adenocarcinoma cells while promoting differentiation and death, butyrate treatment did not affect the normal proliferation and regeneration of the injured epithelium in healthy cells, differentiated cultures, or in vivo experiments [159]. This phenomenon was dubbed “the butyrate paradox” [160,161,162]. Later, a possible explanation was suggested by the disclosure of the butyrate molecular mechanism which comprises the following: (a) activation of the G protein-coupled receptor 109a (GPR109a)–AKT signalling pathway, which leads to the remarkable inhibition of glucose metabolism and DNA synthesis in CRC cells, via reducing the amount of membrane G6PD and GLUT1 [163]; (b) the inhibition of AKT/ERK signalling in a histone deacetylase (HDAC)-dependent manner [164]. In malignant colonocytes, where glycolytic metabolism prevails over oxidative phosphorylation, butyrate accumulates and functions as an HDAC inhibitor, slowing the cell cycle progression through altered gene expression [165]. Thus, distinct metabolic pathways for cellular energy in differentiated and undifferentiated colonocytes are likely to be responsible for ‘the butyrate paradox’ [166]. During the coevolution of the microbiota with its hosts, mammalian crypt architecture has been developed to protect stem/progenitor cell proliferation from the potentially harmful effect of microbially derived butyrate; differentiated colonocytes establish a metabolic barrier that uses butyrate to produce a butyrate gradient [167]. Interestingly, butyrate, but not propionate or acetate, had a significant inhibitory effect on stem cell proliferation. This may be the reason why colonocytes, to protect intestinal stem cells, preferentially break down butyrate over the other SCFAs propionate and acetate, which are also present in high concentrations in the colon [167]. According to the mentioned theories, Lee et al. found out that metformin-butyrate (MFB), a new metformin derivative, showed more effective targeting of the CD44+/high/CD24−/low CSC-like (undifferentiated) population in breast cancer in vitro and in vivo and the inhibition of mammosphere formation, compared to that with metformin [168]. Of note, when butyrate and 5-FU were administered together, the chemotherapeutic effectiveness of 5-FU on CRC cells increased, suggesting a role of butyrate in sensitising CRC cells to chemotherapy [163]. Moreover, in 3D-cultured organoids derived from CRC patients, when compared to that with the administration of radiation alone, butyrate dramatically increased radiation’s ability to cause cell death and improve therapeutic effects [169]. Dietary fatty acids may increase the ability of intestinal stem cells and progenitor cells to self-renew, as well as their capability to initiate tumours [170]. Bile acids are crucial signalling molecules that aid in the digestion and absorption of dietary lipids by acting as emulsifiers [171]. Cholic acid and chenodeoxycholic acid, the two primary biliary acids (BAs), are produced from cholesterol via a series of enzymatic processes that occur mostly in the liver. After being synthesised, these BAs are conjugated with glycine or taurine and subsequently secreted and stored in the gallbladder. Less than 5% of the BA pool enters the colon each day in humans due to an active transport mechanism that predominantly recycles BAs in the terminal ileum. The gastrointestinal microbiota metabolises BAs that enter the colon, converting primary BAs into secondary BAs, deoxycholic acid (DOC or DCA), and lithocholic acid (LCA). Hence, the circulating BA pool comprises approximately 30 to 40% of cholic acid and chenodeoxycholic acid, 20 to 30% of DOC, and less than 5% of LCA (in the conjugated form when it leaves the gallbladder and subsequently de-conjugated after it enters the colon via the action of bacterial enzymes) [172]. Secondary BAs are potent signal molecules that regulate a variety of processes (both physiological and pathological), through the modulation of several signalling pathways. Gut dysbiosis can alter the homeostatic levels of primary and secondary bile acid pools and produce distinct pathophysiological bile acid profiles [173]. Moreover, the gut microbiota–bile acid axis can control immune cells to indirectly promote tumours. Secondary BAs can inhibit the function of anti-tumour immune cells, such as macrophages, dendritic cells, B cells, and natural killer (NK) cells, while enhancing the function of Tregs, which are known to encourage the development of immunosuppressive microenvironments and the growth of tumours [174]. According to Bayerdorffer et al., there is a positive association between the colon-derived unconjugated fraction of DCA and colorectal adenoma formation, which are the precursors of CRC. The finding of this connection provided evidence in favour of the theory that DCA has a detrimental impact on colon cancer development [175]. Later, the mechanisms through which secondary BAs control carcinogenesis were described by Farhana et al. [176]. They discovered that the unconjugated secondary bile acids, notably DCA and LCA, alter muscarinic acetylcholine receptor M3 (M3R) and Wnt/β-catenin signalling promoting cancer stemness in colonic epithelial cells. Moreover, according to another study, secondary BAs can encourage the development of CSCs from both cancer and non-cancerous cells [174]. Farnesoid X receptor (FXR) is the nuclear receptor responsible for the negative feedback control of bile acid synthesis in the ileum and liver. Besides this role, FXR is also a crucial regulator of the proliferation of intestinal stem cells. In 2019, Fu et al. demonstrated that DCA and tauro-β-muricholic acid (T-βMCA) antagonise intestinal FXR, functioning as strong promoters of CSC proliferation able to induce DNA damage [177]. In their study, the authors also suggest that FXR activation could potentially impede tumour progression. They used the FXR agonist drug Fexaramine D to prove their theory, showing that when intestinal FXR is specifically activated, adenomas and adenocarcinomas in treated mice develop more slowly. A few years earlier, another research group identified two bacterial strains capable of directly modulating the activation of intestinal FXR [178]. They demonstrated that Bacteroides dorei and Eubacterium limosum cell-free supernatants trigger FXR activity and the expression of FXR-dependent genes in in vitro cell-based reporter assays and diet-induced obese (DIO) mice. Taken together, these results suggest that those two bacterial strains could have a beneficial role as probiotics, especially in those cases in which the (high-fat) diet is responsible for an imbalance in the BA pool that could favour CRC onset. A recent report suggests that in the presence of metastatic lesions, a healthy diet and/or proper pharmacological intervention aimed at re-establishing physiological bile acid levels could reduce cancer cell invasion, migration, and adhesion [173]. Lysine decarboxylase (LDC), a peculiar microbial enzyme, catalyses the decarboxylation of lysine to produce the bacterial metabolite cadaverine. Although cadaverine can also be produced by human cells, it appears that bacterial cadaverine production predominates over human biosynthesis [179]. Kovács et al. administered cadaverine in breast cancer cell lines within the standard range for serum (100–800 nM) and found that cadaverine exposure prevented mesenchymal-to-epithelial transition, inhibited invasion, and decreased mitochondrial oxidation, all hallmarks of stemness. Moreover, smaller and lower-grade primary tumours, together with reduced metastasis, were generated in Balb/c female mice transplanted with 4T1 breast cancer cells and treated with cadaverine [179]. L-tryptophan (Trp) is one of the nine essential amino acids for humans, and therefore, it must be introduced with the diet. Trp and other amino acids are released from dietary and endogenous luminal protein by bacterial proteases and peptidases. Three rate-limiting enzymes convert the Trp into kynurenine (Kyn): liver tryptophan-2,3-dioxygenase (TDO) and peripheral tissue indoleamine 2,3-dioxygenase 1/2 (IDO1/IDO2) [180]. Through the action of the bacterial enzyme tryptophanase, the intestinal microbiota mostly converts Trp into indole [181]. For human health, Trp metabolism through the Kyn pathway and gut microbial metabolism to indolic compounds is essential. For instance, breast cancer and breast cancer survival are strongly correlated with Trp and indole metabolism. In this regard, tumour TDO/IDO overexpression is a marker of poor prognosis [182,183]. Indeed, patients with breast cancer benefit from indole derivatives in terms of survival; of note, the levels of indole derivatives decrease with disease progression [184]. Reduced activity of the indolic pathway was seen in colon cancer, which also exhibits alterations in microbial indole synthesis [185]. As per Kovács et al., Sári and colleagues also employed the Aldefluor Stem Cell kit to measure the impact of treatment with indolepropionic acid (IPA), a bacterial Trp metabolite, on ALDH activity in 4T1 cells. What they discovered was a reduction in the percentage of aldehyde dehydrogenase-positive cells together with induced mesenchymal-to-epithelial transition (MET) in IPA-treated cells [184]. The health-promoting potential of plant extracts and plant-derived secondary metabolites is widely recognised [186,187,188]. Numerous beneficial effects of polyphenols on human health, such as antioxidant [189,190,191,192,193], anti-inflammatory [194,195,196], immunomodulatory [197,198,199], cardioprotective [200,201,202], neuroprotective [203,204,205], anti-carcinogenic [206,207,208], and prebiotic properties [209], have been reported. Thanks to the plethora of chemical structures they exhibit, natural anticancer compounds may act as cytotoxic agents [210,211,212], anti-mitotic agents [213], angiogenesis inhibitors [214,215], topoisomerase inhibitors [216], apoptosis inducers [217] and cancer invasion [218], migration [219] and proliferation inhibitors [220,221,222]. The identification of plant-derived secondary metabolites that could target CSCs’ peculiar signalling has received much attention in current anticancer drug discovery approaches [223,224,225,226,227,228,229,230,231,232,233,234,235,236,237]. Very recently, a growing understanding of the impact of secondary polyphenol metabolites derived from gut microbial metabolism in the context of carcinogenesis has emerged. It is worth noting that the portion of dietary polyphenol that is absorbed at the small intestine level and enters the blood circulation is estimated at around 10%. Hence, many ingested polyphenols reach the large intestine, where intestinal bacteria convert them to phenolic acids [238]. Lactobacillus rhamnosus, an obligatory anaerobic homofermentative lactic acid producer, has been identified as predominant bacteria in the human gut [239]. The fermentation of polyphenol-rich dried black chokeberry (Aronia melanocarpa) powder using L. rhamnosus led Choi et al. to the isolation of a CSC inhibitor of which the structure was established as 1,2-dihydroxybenzene, also known as catechol [240]. In particular, they found that catechol inhibits proliferation and mammosphere formation in the human breast cancer cell lines MCF-7 and MDA-MB-231. Moreover, the percentage of breast cancer cells expressing CD44high/CD24low, as well as the protein and transcript levels of signal transducer and activator of transcription 3 (STAT3) and IL-6, are reduced by catechol treatment. Finally, catechol was found to reduce the expression of self-renewal genes, such as NANOG, SOX2, and OCT4, in CSCs, hence reducing their stemness and proliferative capacity. Urolithins are secondary polyphenol metabolites generated via the activity of gut bacteria on ellagitannins (ET) and ellagic acid-rich foods, such as pomegranates, raspberries, strawberries, and walnuts [241]. The acid hydrolysis of ellagitannins releases free ellagic acid [242], which is further processed by gut microbiota that converts ellagic acid into urolithins [238]. The composition of a person’s gut microbiota affects how ellagitannins and ellagic acid are metabolised into urolithins; accordingly, individuals can be categorised into three groups of polyphenol-metabolising phenotypes called metabotypes [243]. Núñez-Sánchez and colleagues evaluated the effects of mixed ET-derived colonic metabolites on colon CSC-associated markers [244]. The authors investigated the ability of two separate mixtures of compounds—ET metabolites, ellagic acid (EA), and the gut microbiota-derived urolithins (Uro)—that, in proportion and concentration, mimic those detected in vivo in individuals with metabotype-A or metabotype-B. According to their study, the mixture resembling the metabotype-A that contains mostly Uro-A (85% Uro-A, 10% Uro-C, 5% EA) was more successful at suppressing CSCs’ molecular (ALDH activity) and phenotypic (number and size of colonospheres) traits, whereas the mixture mimicking the metabotype-B containing less Uro-A but IsoUro-A and Uro-B (30% Uro-A, 50% IsoUro-A, 10% Uro-B, 5% Uro-C, 5% EA) seemed to have some effects on colonosphere size and number, but not on ALDH activity levels. Uro-A, the predominant metabolite in the metabotype-A mixture, may be the main factor causing the discrepancies seen between the two mixtures. Interestingly, González-Sarrías et al. also reported that Uro-A is a substrate of drug efflux transporter breast cancer resistance protein (ABCG2/BCRP), highlighting the role of Uro-A in targeting CSCs [245]. In addition, the finding that the anticancer activity of 5-FU can be enhanced by Uro-A in human colon cancer cells supports the hypothesis that using phytochemicals in combination with traditional cytotoxic drugs to target CSCs may be a new cancer treatment approach [246]. Diet is the primary source of vitamin A since it cannot be synthesised by animal tissue and has to be introduced with food. Retinoids (including vitamin A, all-trans retinoic acid, and related signalling molecules) were shown to promote the differentiation of diverse stem cell types [247]. Retinoic acid (RA), a well-known vitamin A metabolite, regulates the fate of neighbouring cells. The availability of vitamin A (retinol), the activity of the enzymes necessary for RA synthesis (retinol dehydrogenases and aldehyde dehydrogenases), and the catabolism of RA by CYP26 enzymes all affect the levels of RA [248]. Retinoid signalling is frequently impaired early in carcinogenesis, suggesting that a decrease in retinoid signalling may be essential for tumour growth [249]. Although RA has frequently been regarded as a cell differentiation inducer, depending on the type of cell, RA might prevent cell differentiation and induce stemness [248]. Recent discoveries of retinoids as chemo-preventive and molecular-targeted antitumour agents reveal that RA agents may be considered efficient therapies for treating human solid tumours [250]. Among retinoids, all-trans retinoic acid (atRA) was found to be a promising therapeutic compound capable of targeting CSCs in different cancer settings, such as gastric [251], brain [252], head and neck [253], and breast [254] cancer. For instance, a significantly improved anti-cancer effect towards breast cancer was achieved when atRA and DOX were simultaneously delivered, encapsulated in the same nanoparticle [255]. This combinational drug delivery system aims to target both non-CSCs and CSCs. With their studies in vitro and in vivo, Sun et al. demonstrated that the atRA-induced differentiation of CSCs into non-CSCs can decrease their capacity for self-renewal and enhance their sensitivity to DOX, improving the inhibition of tumour growth while simultaneously decreasing the incidence of CSCs. Moreover, in A549GSC and H1650GSC cells, treatment with atRA was shown to dramatically lower the IC50 values for gefitinib, an ATP-competitive EGFR tyrosine kinase inhibitor used in non-small cells lung cancer (NSCLC) treatment, and the high expression of ALDH 1 family member A1 (ALDH1A1) and CD44 [256]. Additionally, conventional PKC inhibitor (Gö6976) and atRA combined treatment reduced tumour growth, metastatic dissemination, and the frequency of breast CSCs in vivo while impairing the proliferation, self-renewal, and clonogenicity ability of breast CSCs [257]. Interestingly, both products and substrates of the RA pathway, 5 μM atRA and 1 μM ROL, respectively, were shown to inhibit ALDH1+ CSC populations in cisplatin-resistant NSCLC cells [258]. Recently, Bonakdar et al. showed the importance of gut bacteria and their ability to metabolise vitamin A to produce a variety of retinoids with pharmacological activity [259]. In particular, they compared the retinoid metabolomes from caecal contents from germ-free (GF), conventional (CV), and antibiotic-treated mice (CV + Abx) and demonstrated that (1) GF mice had notably reduced amounts of all-trans-retinol (atROL), atRA, and 13-cis-retinoic acid (13cisRA) compared with those in CV mice and (2) when compared to that in control mice, CV animals treated with an antibiotic cocktail displayed a marked decrease in concentrations of all vitamin A metabolites except for RE. These results indicate that dietary vitamin A can be converted into ROL and its active metabolites, atRA and 13cisRA, by the gut microbiota. Besides the above-mentioned anticancer potential of atRA, it is worth noting that 13cisRA, also known as isotretinoin, is a key treatment for treating high-risk neuroblastoma and for dermatology. The presence of 13cisRA in the mouse caecum of CV mice but not GF or CV + Abx mice, as well as its in vitro production by caecal bacteria, indicates that 13cisRA is a particular retinoid derived exclusively from microorganism metabolism [259]. The identification of CSCs as a significant contributor to and driver of cancer development mechanisms, such as tumour growth, recurrence, metastasis, and therapy resistance, constitutes a significant advancement in the study of cancer and offers researchers the opportunity to develop new CSC-centric approaches for cancer treatment. The failure of cancer therapy is mostly due to CSC cell-mediated drug resistance. Characterising the differences between non-neoplastic tissue stem-cell programs and those of neoplastic tissue stem cells will be critical in developing therapeutic strategies to selectively target CSCs without negatively affecting non-neoplastic tissue stem cells. The development of mechanism-based methods for cancer drug discovery, including targeted therapies and immunotherapies, has been aided by remarkable improvements in our understanding of the molecular basis of cancer and tumour cell biology. However, there is a pressing need for the development of therapeutic approaches that are more successful in overcoming CSC cell-mediated resistance. In this regard, efforts are currently being made to find effective, affordable, and safe anticancer medicines of natural origin. There are now several strong connections among the host’s nutrition, the composition of the gut microbiota, and the host’s physiology. Particularly, numerous reports have underlined the key role of diet in cancer prevention [260,261]. For instance, it has been proven that the Mediterranean diet regimen significantly lowers the risk of several cancers, particularly colorectal and aerodigestive [262,263,264], gastric [265], pancreatic [266], breast [267,268,269], nasopharyngeal [270], lung [271], prostate [272], and bladder cancer [273]. The impact of the human microbiota on both short- and long-term human health has been amply shown during the last few decades [274,275,276,277,278]. In recent years, growing evidence has indicated the causal relationship between intestinal microbial dysbiosis and colorectal cancer aetiology [279]. In this perspective, to reverse established microbial dysbiosis, a range of approaches has been employed, including probiotics, prebiotics, postbiotics, antibiotics, and faecal microbiota transplantation (FMT) [280]. Currently, the small molecular weight compounds (postbiotics) released by the microbiota, which provide the host with many physiological health benefits, are given much attention. The host’s biochemical versatility is increased by the large metabolic repertoire of the microbial population, which supports the activity of mammalian enzymes and allows the host to metabolise a variety of food substrates [281]. This diet–microbial metabolism feedforward loop modulates a broad spectrum of events. Here, we reviewed the emerging roles of microbiota-derived metabolites as CSC-targeting anticancer agents. The body of evidence provided suggests that postbiotics, bioactive substances derived from gut beneficial microbiota, might be considered novel promising agents to be used in personalised medicine approaches to re-establish gut eubiosis while also targeting CSCs. This strategy may encompass the steering of diet–microbiota interactions toward the production of certain metabolites that could maximise health benefits. Furthermore, the synergistic effect of diverse microbial products with standard anticancer agents may suggest their further employment to sensitise CSCs in chemo-/radiotherapy regimens. In this perspective, postbiotics are superior to probiotics for industrial production because they are easier to use and store, have a longer shelf life, are stable across a wide pH and temperature range, and do not produce bioamine. However, before postbiotics can be employed as probiotic substitutes, more investigation is needed into the production, distribution mechanisms, and safety standards of medicines and functional foods [137]. Moreover, a crucial aspect to take into account from the viewpoint of postbiotic-based therapeutics is their targeted delivery in vivo. Indeed, it is crucial to ensure that a biomolecule given orally, intravenously, or topically can be transferred to its site of action without being altered via pharmacokinetics or digestive processes. In this regard, a recent summary of possible methods for the in vivo delivery of postbiotics was provided by Abbassi et al. [131]. In conclusion, the reviewed literature highlights that the microbiota is a valuable resource for the discovery of novel small-molecule drugs, and metabolites originating from the microbiota may find extensive use in the treatment of cancer, thanks to their ability to target CSCs. In this respect, further study of the pharmacological interaction between conventional chemotherapeutic drugs and gut microbiota-derived compounds will undoubtedly be necessary for the development of improved therapeutic approaches to eliminate CSCs. For the current review, data were gathered from English-language scientific publications using different combinations of the following keywords: ‘cancer stem cells’, ‘cancer’, ‘stemness’, ‘signalling pathway’, ‘microbial products’, ‘microbiota metabolites’, ‘bacterial products’, ‘bacterial metabolites’, ‘probiotic ghosts’, ‘postbiotics’ as keywords in search queries of different databases and electronic search engines. Publications addressing CSC-associated mechanisms of therapeutic resistance, and articles describing the activity of gut microbiota bioactive metabolites toward CSC features were selected.

PMC10003411

Chunyang Wang,Di Shen,Yingqiu Hu,Jie Chen,Jingyun Liu,Yufei Huang,Xuebin Yu,Haiying Chu,Chenghong Zhang,Liangwei Yin,Yi Liu,Haiying Ma

Selective Targeting of Class I HDAC Reduces Microglial Inflammation in the Entorhinal Cortex of Young APP/PS1 Mice

02-03-2023

Alzheimer’s disease,β-amyloid,HDAC inhibitor,synaptic protein,entorhinal cortex,inflammation

BG45 is a class Ⅰ histone deacetylase inhibitor (HDACI) with selectivity for HDAC3. Our previous study demonstrated that BG45 can upregulate the expression of synaptic proteins and reduce the loss of neurons in the hippocampus of APPswe/PS1dE9 (APP/PS1) transgenic mice (Tg). The entorhinal cortex is a pivotal region that, along with the hippocampus, plays a critical role in memory in the Alzheimer’s disease (AD) pathology process. In this study, we focused on the inflammatory changes in the entorhinal cortex of APP/PS1 mice and further explored the therapeutic effects of BG45 on the pathologies. The APP/PS1 mice were randomly divided into the transgenic group without BG45 (Tg group) and the BG45-treated groups. The BG45-treated groups were treated with BG45 at 2 months (2 m group), at 6 months (6 m group), or twice at 2 and 6 months (2 and 6 m group). The wild-type mice group (Wt group) served as the control. All mice were killed within 24 h after the last injection at 6 months. The results showed that amyloid-β (Aβ) deposition and IBA1-positive microglia and GFAP-positive astrocytes in the entorhinal cortex of the APP/PS1 mice progressively increased over time from 3 to 8 months of age. When the APP/PS1 mice were treated with BG45, the level of H3K9K14/H3 acetylation was improved and the expression of histonedeacetylase1, histonedeacetylase2, and histonedeacetylase3 was inhibited, especially in the 2 and 6 m group. BG45 alleviated Aβ deposition and reduced the phosphorylation level of tau protein. The number of IBA1-positive microglia and GFAP-positive astrocytes decreased with BG45 treatment, and the effect was more significant in the 2 and 6 m group. Meanwhile, the expression of synaptic proteins synaptophysin, postsynaptic density protein 95, and spinophilin was upregulated and the degeneration of neurons was alleviated. Moreover, BG45 reduced the gene expression of inflammatory cytokines interleukin-1β and tumor necrosis factor-α. Closely related to the CREB/BDNF/NF-kB pathway, the expression of p-CREB/CREB, BDNF, and TrkB was increased in all BG45 administered groups compared with the Tg group. However, the levels of p-NF-kB/NF-kB in the BG45 treatment groups were reduced. Therefore, we deduced that BG45 is a potential drug for AD by alleviating inflammation and regulating the CREB/BDNF/NF-kB pathway, and the early, repeated administration of BG45 can play a more effective role.

Selective Targeting of Class I HDAC Reduces Microglial Inflammation in the Entorhinal Cortex of Young APP/PS1 Mice BG45 is a class Ⅰ histone deacetylase inhibitor (HDACI) with selectivity for HDAC3. Our previous study demonstrated that BG45 can upregulate the expression of synaptic proteins and reduce the loss of neurons in the hippocampus of APPswe/PS1dE9 (APP/PS1) transgenic mice (Tg). The entorhinal cortex is a pivotal region that, along with the hippocampus, plays a critical role in memory in the Alzheimer’s disease (AD) pathology process. In this study, we focused on the inflammatory changes in the entorhinal cortex of APP/PS1 mice and further explored the therapeutic effects of BG45 on the pathologies. The APP/PS1 mice were randomly divided into the transgenic group without BG45 (Tg group) and the BG45-treated groups. The BG45-treated groups were treated with BG45 at 2 months (2 m group), at 6 months (6 m group), or twice at 2 and 6 months (2 and 6 m group). The wild-type mice group (Wt group) served as the control. All mice were killed within 24 h after the last injection at 6 months. The results showed that amyloid-β (Aβ) deposition and IBA1-positive microglia and GFAP-positive astrocytes in the entorhinal cortex of the APP/PS1 mice progressively increased over time from 3 to 8 months of age. When the APP/PS1 mice were treated with BG45, the level of H3K9K14/H3 acetylation was improved and the expression of histonedeacetylase1, histonedeacetylase2, and histonedeacetylase3 was inhibited, especially in the 2 and 6 m group. BG45 alleviated Aβ deposition and reduced the phosphorylation level of tau protein. The number of IBA1-positive microglia and GFAP-positive astrocytes decreased with BG45 treatment, and the effect was more significant in the 2 and 6 m group. Meanwhile, the expression of synaptic proteins synaptophysin, postsynaptic density protein 95, and spinophilin was upregulated and the degeneration of neurons was alleviated. Moreover, BG45 reduced the gene expression of inflammatory cytokines interleukin-1β and tumor necrosis factor-α. Closely related to the CREB/BDNF/NF-kB pathway, the expression of p-CREB/CREB, BDNF, and TrkB was increased in all BG45 administered groups compared with the Tg group. However, the levels of p-NF-kB/NF-kB in the BG45 treatment groups were reduced. Therefore, we deduced that BG45 is a potential drug for AD by alleviating inflammation and regulating the CREB/BDNF/NF-kB pathway, and the early, repeated administration of BG45 can play a more effective role. Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with declining cognitive function associated with age [1]. Morbidity from AD dramatically increases after the age of 65 and shows a growing trend [2]. The main histological characteristic of AD is the accumulation of extracellular amyloid β (Aβ), evident as senile plaques and intracellular neurofibrillary tangles (NFTs) caused by hyperphosphorylated tau [3]. Evidence has shown that the degree of dementia is closely connected to the level of soluble oligomers of Aβ species in AD patients’ brains [4]. The Aβ oligomer, formed by redundant Aβ42, can contribute to the damage of ion channels and calcium homeostasis, reduced energy metabolism, and glucose regulation [4,5], as it disrupts neuronal regulation and synaptic plasticity and causes eventual neuron death. Studies have reported that Aβ oligomers first appeared in the brain in 2-month-old APP/PS1 mice [6], senile plaques were detected in 4-month-old mice [7], and the numbers and areas of plaques increased with age. Therefore, the early treatment of AD is crucial. The classical lesions of AD can occur as early as 20 years prior to the development of symptoms and disease indicators [8]. These early changes are likely to occur at the epigenetic level, where gene expression is controlled [9]. Histone acetylation is a common form of genetic post-translational modification and plays an important role in histone transcription regulation [10]. Histone deacetylases (HDACs) are a superfamily of enzymes that are key parts of the epigenetic regulation of gene expression and cellular activity [11]. In normal neurons, histone acetyltransferase (HAT) and HDAC protein levels and their corresponding activities are always maintained at a high balance [12]. They play crucial roles in regulating gene expression, which is associated with normal neurophysiological functions such as long-term potentiation, learning, and memory [13,14]. In neurodegenerative diseases, however, acetylation homeostasis is disrupted and synaptic plasticity is injured [15,16]. The classical HDAC family can be divided into three types according to the homology of yeast: class I HDACs (HDAC1, 2, 3, and 8), class II HDACs (HDAC4, 5, 6, 7, 9, and 10), and class III HDACs [17,18]. Studies have demonstrated that HDAC2-overexpressing mice will have deregulated gene expression and damaged synaptic plasticity, learning, and memory [19], and HDAC2 KO mice have increased dendritic spine density and numbers of synapses [20]. Moreover, HDAC3 overexpression in the hippocampuses of APP/PS1 mice can increase Aβ levels, activate microglia, and injure synaptic plasticity [21,22]. HDAC inhibitors (HDACIs) represent prototypical “epigenetic” agents that act by modifying gene expression to restore the normal differentiation or death programming of transformed cells [23]. There is powerful evidence suggesting that HDACIs may be useful in the treatment of AD and AD-like pathologies [24,25]. HDACI can activate CREB-CBP-dependent transcription [11]. cAMP response element binding protein (CREB), a transcriptional coactivator with HAT activity, has been proved to be associated with synaptic plasticity and long-term memory [26,27]. Studies have suggested that HDACI improves gene transcription ability and facilitates the phosphorylation of CREB at serine 133, driving CRE-mediated transcription [13]. The CREB transcription factor family regulates the transcription of brain-derived nerve factor (BDNF), especially the activation of BDNF promoter IV [28]. Moreover, BDNF levels can affect the chronic inflammatory state of the brain by influencing the release of TNF-α and IL-1β [29]. Aβ deposition can activate microglia, which will release pro-inflammatory cytokines such as TNF-α, IL-1β, and IL-6, leading to tau hyperphosphorylation and neuronal loss [30]. Therefore, HDACI may improve synaptic plasticity by regulating inflammation. BG45, a novel class I HDAC inhibitor (C11H10N4O, 214.22), has been evidenced to selectively inhibit the expression of HDAC3 (IC50 = 289 nM). It also inhibits HDAC1 and HDAC2 with reduced potency [31]. The entorhinal cortex has been shown to be an interface between the hippocampus and neocortical regions, and it plays a crucial role in the formation and consolidation of memory [32,33]. In our previous studies, we found that BG45 can reduce Aβ deposition, increase the expression of synaptic proteins, and upregulate the expression of α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor subunits (GluR2, GluR3, and GluR4) [34,35]. We hypothesized that BG45 might be a promising factor to rescue synaptic plasticity in AD. In this study, we explored the timing of Aβ deposition and the increased activation of glial cells in the entorhinal cortex. Subsequently, we investigated the effect of BG45 treatment on these changes at different times. We discovered that BG45 reduced the number of degenerative neurons and the activation of microglia and astrocytes in the entorhinal cortexes of 6-month-old mice if they were treated with BG45 at 2 months of age. Immunohistochemistry revealed the differences in the Aβ depositions of the mice of different ages. Positive Aβ deposition in the entorhinal cortex was first identified in 3-month-old APP/PS1 mice, which gradually accumulated with age. However, there was no significant Aβ immunoreactivity in 2-month-old to 8-month-old Wt mice (Figure 1). Using immunohistochemistry, microglia and astrocytes with the corresponding IBA1 and GFAP antibodies were detected in the entorhinal cortexes at different ages. The results showed that the positive expression of IBA1 and GFAP was significantly increased in 3-month-old mice as they got older. However, compared with 2-month-old Wt mice, there were no significant changes in the IBA1-positive microglia and GFAP-positive astrocytes in the 8-month-old Wt mice (Figure 2). The effects of BG45, a class I HDAC inhibitor, on H3K9K14/H3 acetylation and HDAC1, HDAC2, and HDAC3 expression were evaluated by Western blot analysis. As shown in Figure 3A,C, H3K9K14/H3 acetylation was decreased in the Tg group compared with the Wt group (p < 0.05). However, compared with the Tg group, H3K9K14/H3 acetylation was increased to different degrees in the three BG45 treatment groups (p < 0.05, p < 0.001, and p < 0.05, respectively), and the levels of H3K9K14/H3 acetylation in the 2 and 6 m group were the highest. As shown in Figure 3B,D–F, HDAC1, HDAC2, and HDAC3 expression was increased in the Tg group compared with the Wt group (p < 0.05, p < 0.05, and p < 0.01, respectively). HDAC1 expression in the 2 m and 2 and 6 m groups was decreased compared with the Tg group (p < 0.01 and p < 0.01, respectively). However, there was no significant difference between the 6 m and Tg groups. HDAC2 and HDAC3 expression in three BG45-treated groups was decreased compared with the Tg group (p < 0.05, p < 0.05, and p < 0.05, respectively, and p < 0.001, p < 0.001, and p < 0.05, respectively). The severity of neuronal degeneration was evaluated by Fluoro-Jade C (FJC) straining. We found that there were many more positive FJC-stained cells in the entorhinal cortexes of the Tg group than there were in the Wt group (p < 0.001). Compared with the Tg group, the number of FJC-positive cells decreased in the three groups receiving BG45 treatment (p < 0.001, p < 0.001, and p < 0.01) (Figure 4). As shown in Figure 5A, Aβ deposition in all BG45-treated groups (2 m, 2 and 6 m, and 6 m) was decreased compared with the Tg group (p < 0.001, p < 0.001, and p < 0.01, respectively). More Aβ deposition was found in the entorhinal cortexes of the mice treated at 6 months of age than in the mice treated at 2 months of age (p < 0.001), and the least amount was found in the mice treated twice at 2 months and 6 months of age. In addition, tau protein phosphorylation levels were also detected. The results indicated that p-tau expression was lower in all treated groups than in the Tg group (p < 0.01, p < 0.001, and p < 0.05, respectively), and it was lowest in the 2 and 6 m group (Figure 5B,C). To verify the protective effect of the synaptic plasticity of BG45, several synapse-related proteins were detected by Western blot analysis. The results showed that compared with the Wt group, the expression levels of PSD95, SYP, and spinophilin were decreased in the Tg group (p < 0.05, p < 0.05, and p < 0.05, respectively). However, the expression levels of SYP were higher in the 2 m and 2 and 6 m groups than in the Tg group (p < 0.01 and p < 0.05, respectively). In all BG45-treated groups, PSD95 and spinophilin were increased compared with the Tg group (p < 0.01, p < 0.001, and p < 0.05, respectively, and p < 0.001, p < 0.01, and p < 0.05, respectively), and PSD95 and spinophilin expression levels were higher in the 2 and 6 m group than in the two other treated groups (Figure 6). Neuroinflammation is considered to be a critical driver of the cognitive deficits associated with AD. Overactivated neuroglial cells, such as microglia and astrocytes, contribute to neuroinflammation and neurodegenerative disorders. Both the microglia and astrocytes in the entorhinal cortexes of the 2 m, 2 and 6 m, and 6 m groups were decreased compared with the Tg group (p < 0.001, p < 0.001, and p < 0.01, respectively, and p < 0.001, p < 0.001, and p < 0.001, respectively). Moreover, the amount of IBA1-positive microglia and GFAP-positive astrocytes was the lowest in the 2 and 6 m group, and there were more positive cells in the 6 m group than in the 2 m group (p < 0.01 and p < 0.001, respectively) (Figure 7). RT-qPCR was used to detect the gene levels of inflammatory cytokines in the entorhinal cortex samples. The results showed that the mRNA levels of IL-1β and TNF-α were higher in the Tg group than in the Wt group (p < 0.001 and p < 0.001, respectively), and the levels of IL-1β and TNF-α gene expression in the 2 m and 2 and 6 m groups decreased compared with the Tg group (p < 0.01 and p < 0.01, respectively, and p < 0.01 and p < 0.01, respectively), but there was no significant difference between the 6 m group and the Tg group (Figure 7). In order to investigate the potential mechanism by which BG45 alleviated the inflammatory factors and improved the levels of synaptic proteins, the key factors in the CREB/BDNF/NF-kB pathway were detected. The results revealed that p-CREB/CREB, BDNF and its receptor, TrkB, and p-NF-kB/NF-kB showed significant differences between the Tg group and the Wt group. Compared with the Tg group, the levels of p-CREB/CREB in the 2 m, 2 and 6 m, and 6 m groups were upregulated (p < 0.001, p < 0.001, and p < 0.01, respectively), and they were the highest in the 2 and 6 m group. At the same time, BG45 upregulated the expression of BDNF and TrkB in all the treated groups compared with the Tg group (p < 0.01, p < 0.001, and p < 0.05, respectively, and p < 0.001, p < 0.01, and p < 0.01, respectively). However, the p-NF-kB/NF-kB level was inhibited by BG45 treatment. Similarly, they both showed more significant changes in the 2 and 6 m group compared with the other two treatment groups (Figure 8). Both amyloid precursor protein (APP) and presenilin (PSEN) gene mutations are associated with familial Alzheimer’s disease (FAD) and with the early onset of the disease. A mouse model of amyloid is used around the world to study the cognitive, behavioral, and neuropathological changes related to AD [36]. This study mainly explored the therapeutic effects of BG45 on APP/PS1 transgenic mice at different months of age before and after Aβ plaque formation. Previous studies have found that chronic local inflammatory responses occur in pathologically vulnerable areas of the AD brain, such as the frontal lobe and hippocampus [33]. Microglia have two different effects on the development of AD. On the one hand, they can clean Aβ peptides and reduce Aβ plaque accumulation, which, in turn, protects neurons [37]. On the other hand, microglia also have a negative influence on neurons. For example, they can injure synapses and thus contribute to neuronal death by secreting inflammatory factors or activating astrocytes [37]. In this study, we found that the number of amyloid plaques consistent with IBA1-positive microglia and GFAP-positive astrocytes gradually increased from 3 to 8 months, confirming that Aβ plaques and the activation of microglia and astrocyte are closely associated in the studied region of the entorhinal cortex in AD (Figure 1 and Figure 2). Studies have shown that persistent epigenetic changes may affect gene expression patterns and lead to neurodegenerative disorders, including AD [38,39]. Acetylation is dysregulated in AD and associated with various impairments in signaling, inflammation, and neuronal plasticity, contributing to negatively impacted memory and cognition [40]. In a study on post-mortem AD brains, the protein levels of the total histones H3 and H4 were significantly increased [41]. Klein et al. verified the positive correlation between H3K9 acetylation and transcriptional activity in the human cortex. H3K9 acetylation level is broadly associated with tau pathology [42]. In the entorhinal cortex, AD-associated differentially acetylated peaks were enriched in some processes related to Aβ metabolic processes and synaptic proteins, and this included regions annotated to genes (APP, PSEN1, and PSEN2) involved in AD pathologic hallmarks [43]. It was reported that HDAC3 inhibitors increased histone H3 and H4 acetylation and relieved memory impairment [21]. HDAC3, a class I HDAC, plays a crucial role in the pathology of AD because it is expressed not only in the nucleus but also in the cytoplasm, unlike other HDACs. HDAC3 overexpression can impair long-term memory and lead to the death of neurons [21,22]. The previous studies proved that BG45 can rescue the expression of synaptic proteins in the prefrontal cortex of APP/PS1 transgenic mice [44]. Consistent with the situation in the hippocampus and the prefrontal cortex [34,44], in this study, our data showed that BG45 rescued synaptic proteins and neuronal degeneration in the entorhinal cortexes of APP/PS1 mice. The expression levels of HDAC1, HDAC2, and HDAC3 in the entorhinal cortexes were higher in the APP/PS1 mice than in the Wt mice (Figure 3). Further research found that BG45 effectively reduced the levels of HDAC1, HDAC2, and HDAC3 in the APP/PS1 mice by increasing the ratio of H3K9K14 to H3, i.e., the 9 and 14 double positions of histone 3, possibly resulting in dissociating histone octamers from DNA and facilitating gene transcription, as well as contributing to increased synaptic proteins, such as PSD95, spinophilin, and SYP [34]. Therefore, epigenetic mechanisms related to BG45 may contribute to gene expression events for memory and regenerative growth. HDACIs are a group of small molecules with HDAC-inhibitory activity and can increase the level of histone acetylation to modulate biological functions [45]. It can acetylate the lysine 9 and 14 positions of H3 of CBP, accelerating the dissociation of histone, which can promote the phosphorylation of CREB [46]. CREB, located in promoter IV of BDNF, can promote gene transcription and boost the protein level of BDNF [28,47]. Increased BDNF promotes the phosphorylation of GSK-3β at the ser9 site to inhibit GSK-3β activity through the PI3K/AKT pathway and, subsequently, tau phosphorylation at multiple sites [48,49,50]. In addition, the change in the BDNF/TrkB pathway may indicate memory deficits and injured synaptic plasticity and neurons [51,52]. At the same time, BDNF can inhibit microglia from releasing NF-kB, which can reduce the expression of TNF-α and IL-1β and the activation of microglia and astrocytes [53,54]. In this study, we detected the key factors in the CREB/BDNF/TrkB pathway in Tg mice with or without BG45 treatment. The results showed that BG45 downregulated the inflammatory cytokines TNF-α and IL-1β. The increased levels of p-CREB/CREB, BDNF, and TrkB and the reduced p-NF-kB/NF-kB levels with BG45 treatment demonstrated that the regulation of glial cells and inflammation by BG45 involves the CREB/BDNF/TrkB pathway (Figure 8). Recent reports have also shown that HDAC3 expression and activity are associated with the expression of several AD-related genes, pro-inflammatory TNF-α and IL-6 and GFAP [40], while the neuroprotective effect of HDAC3 inhibitor (RGFP966) on modulating neuronal memory [55] and extensive neurite outgrowth [56] increases histone H3 and H4 acetylation, reducing Aβ expression and the level of tau phosphorylation [21]. Together, these studies suggest that HDAC3 inhibitors may be a promising epigenetic therapy for AD. Importantly, in this study, we found that some pathological changes in AD mice were better improved with BG45 treatment at the age of 2 months compared to those treated at 6 months of age, and BG45 significantly reduced the activation of microglia in the 2 and 6 m group, in which the mice were injected twice with BG45 at 2 and 6 months of age. Therefore, this demonstrated the effectiveness of early and repeated interventions with AD therapy at the epigenetic level. In summary, the molecular mechanisms of AD are complicated. More and more studies are reporting novel hypotheses such as mitochondrial defects, the phosphorylation of tau protein, molecular genetics and etiology, inflammation, oxidative stress and free radical, virus theory, etc. However, the unbalanced production or discharge of Aβ caused by various factors, including neuroinflammation, is still the focus of AD research [57]. Amyloid β can cause neuron death by causing the leakage of ions, disruption of the cellular calcium balance, and losses in membrane potential [58]. BG45, a class I HDAC inhibitor, increased H3K9K14/H3 acetylation and alleviated the pathology of the entorhinal cortexes in APP/PS1 mice by reducing Aβ deposition and upregulating the expression of synaptic proteins. We deduced that this positive effect may be due to BG45 inhibiting the activation of microglia and astrocytes and reducing the levels of inflammatory factors through the CREB/BDNF/NF-kB pathway. Therefore, it is worth further studying BG45 as a promising HDAC inhibitor for the treatment of AD. To perform the omics analysis to find the interactions of the signaling pathways involved in the role of BG45 would provide more favorable evidence for its use as a therapeutic target. The APP/PS1 transgenic (Tg) mice were purchased from the Nanjing Biomedical Research Institute of Nanjing University. All mice were raised under a 12 h light/dark cycle at 22 °C with free access to food and water. All procedures were approved by the Institutional Animal Care and Use Committee of Dalian Medical University (AEE18086). Wild-type C57BL/6 mice were used as normal controls (Wt group). Two-month-old male, 20–22 g APP/PS1 mice were randomly divided into 4 groups, and 3 of the groups were intraperitoneally injected with BG45 (Selleck, 926259-99-6, Houston, USA) at different times, as follows: Tg group, control; 2 m group, injected at 2 months of age; 6 m group, injected at 6 months of age; and 2 and 6 m group, separately injected at 2 and 6 months of age. The mice in all treatment groups were injected with BG45 once a day for 12 days (30 mg/kg of BG45, 0.2 mL per mouse, where the BG45 was first dissolved into a 1 mg/mL stock solution in DMSO and then diluted 1:1000 with normal saline for use). The Tg group and the Wt group were also injected with same volume of vehicle. There were 5 mice in each group. All mice were killed within 24 h after the last injection at 6 months. Their entorhinal cortexes were harvested for subsequent experiments. The sections were deparaffinized and rehydrated, and antigen retrieval was performed. Blocking endogenous peroxidase solution (SP-9100, ZSGB-BIO, Beijing, China) was added to each section, and they were incubated for 15 min at room temperature to block endogenous peroxidase [59]. The sections were blocked with a goat serum solution (SP-9100, ZSGB-BIO, Beijing, China) for 15 min at room temperature. Then the sections were incubated with primary antibody Aβ1–42 (NBP2-13075, Novus Biologicals, Littleton, CO, USA), IBA1 (1094-1-AP, Proteintech, Wuhan, China), or GFAP (80788, Cell Signaling Technology, Boston, MA, USA) at 4 °C overnight. After being washed with PBS (SW132-01, Seven, Beijing, China), the sections were incubated with an appropriate amount of biotin-labeled goat anti-mouse/rabbit IgG for 15 min at room temperature. Subsequently, the sections were incubated with streptozotocin-peroxidase for 15 min at room temperature. Diaminobenzidine (DAB) (ZLI-9018, ZSGB-BIO, Beijing, China) solution was added to the sections for 10 s to 5 min. Finally, hematoxylin was used to stain the nuclei [59]. Three random slices were selected from each group, and three random visual fields in the entorhinal cortex of each slice were observed [59]. The expression of Aβ1–42, IBA1, and GFAP was quantified by ImageJ software (U. S. National Institutes of Health, Bethesda, MD, USA). All samples from the entorhinal cortex were thawed and washed in PBS buffer (SW132-01, Seven, Beijing, China). Then, the samples were sonicated in RIPA lysis buffer (SW104, Seven, Beijing, China) and incubated on ice for 30 min [60]. The proteins were extracted by centrifugation at 10,000× g for 10 min at 4 °C, and the concentrations were detected using a BCA Protein Assay Kit (P0010, Beyotime Biotechnology, Shanghai, China). The proteins were separated by 10 or 12% SDS PAGE and transferred to polyvinylidene difluoride membranes, which were blocked in 5% skim milk. Next, the membranes were incubated with rabbit polyclonal antibodies synaptophysin (SYP) (ab32127, Abcam, London, UK); BDNF (ab108919, Abcam, London, UK); P-CREB/CREB (9197, Cell Signaling Technology, Boston, MA, USA; ab32096, Abcam, London, UK); postsynaptic density protein 95 (PSD-95) (ab18258, Abcam, London, UK); p-tau (Ser404) and tau (20194 and 46687, Cell Signaling Technology, Boston, MA, USA); spinophilin (ab18561, Abcam); HDAC1, HDAC2, and HDAC3 (34589, 57156, and 85057, Cell Signaling Technology, Boston, MA, USA); H3K9K14 (GTX122648, GeneTex, San Antonio, TX, USA); H3 (17168-1-AP, Proteintech, Wuhan, China); NF-kB and p-NF-kB (Ser536) (10745-1-AP, Proteintech, Wuhan, China; 3033, Cell Signaling Technology, Boston, MA, USA); TrkB (4603, Cell Signaling Technology, Boston, MA, USA); and β-actin (AC026, ABclone, Wuhan, China) for 12 h at 4 °C. Then, the membranes were blotted with horseradish peroxidase (HRP)-conjugated secondary antibody at the room temperature for 1 h and imaged using a ChemiDoc XRS System and Image Lab software (Bio-Rad Laboratories, Inc., Hercules, CA, USA). The sections were dewaxed per the immunohistochemistry protocol and washed with ddH2O twice for 1 min each time [61]. The dilution, which was mixed with solution B (potassium permanganate, Merck Millipore, Massachusetts, USA) and ddH2O (1:9), was added to each section, and the sections were incubated in the dark for 10 min. Then, the solution was replaced with 0.5% Triton for 30 min. The sections were washed with ddH2O twice for 1 min each time. Then, one part of solution C (Fluoro-Jade C) was mixed with 1 part of DAPI and 8 parts of ddH2O, and the mixture was added to the slices to incubate for 10 min in the dark. After being washed 3 times for 1 min each time, the slices were placed in a drying oven at 50–60 °C for 5 min. The dried sections were immersed in xylene for at least 5 min. The sections were observed by a Nikon Eclipse 800 microscope. Three random slices were selected from each group, and for each slice, 3 random fields were counted. The data are expressed as the numbers of degenerative neurons. All samples were homogenated by TRIzol reagent (Takara, Kyoto, Japan). After adding chloroform to accelerate the RNA extraction, the solution was centrifuged for separation. The supernatant was transferred into an EP tube and isopropanol was added to make the RNA precipitate. After washing precipitate three times with the 75% ethyl alcohol, the precipitate was dried at room temperature. The concentration of RNA was measured, then transcribed using a reverse transcription kit (Transgene, Strasbourg, France). Samples of mRNA were added to the solution, which was mixed with primer and 2× TransStart Top Green qPCR SuperMix (Transgene, Strasbourg, France), amounting to 20 µL. The qPCR reaction system was operated according to the manufacture’s protocol (Transgene, AQ601, Strasbourg, France) (30 s at 94 °C and 5 s at 95 °C, followed by 45 cycles for 30 s at 60 °C). The primer sequences were as follows: TNF-α 5-GACGTGGAACTGGCAGAAGAG-3 5-TTGGTGGTTTGTGAGTGTGAG-3 IL-1β 5-GCCCATCCTCTGTGACTCAT-3 5-AGGCCACAGGTATTTTGTCG-3 GAPDH 5-GAGCCCTTCCACAATGCCAAAGTT-3 5-TGTGATGGGTGTGAACCACGAGAA-3 All values are expressed as means ± standard deviations (SDs) from three independent experiments. One-way analysis of variance (ANOVA) followed by Tukey’s post hoc tests were used to analyze the differences between means of several subgroups of a variable, and a t-test was used for comparisons between two groups using GraphPad Prism8 (GraphPad Software, La Jolla, CA, USA). Significance was accepted at p < 0.05.

PMC10003413

Mariaenrica Tinè,Ylenia Padrin,Matteo Bonato,Umberto Semenzato,Erica Bazzan,Maria Conti,Marina Saetta,Graziella Turato,Simonetta Baraldo

Extracellular Vesicles (EVs) as Crucial Mediators of Cell-Cell Interaction in Asthma

28-02-2023

airway inflammation,signaling,microRNA (miRNA),endotypes

Asthma is the most common chronic respiratory disorder worldwide and accounts for a huge health and economic burden. Its incidence is rapidly increasing but, in parallel, novel personalized approaches have emerged. Indeed, the improved knowledge of cells and molecules mediating asthma pathogenesis has led to the development of targeted therapies that significantly increased our ability to treat asthma patients, especially in severe stages of disease. In such complex scenarios, extracellular vesicles (EVs i.e., anucleated particles transporting nucleic acids, cytokines, and lipids) have gained the spotlight, being considered key sensors and mediators of the mechanisms controlling cell-to-cell interplay. We will herein first revise the existing evidence, mainly by mechanistic studies in vitro and in animal models, that EV content and release is strongly influenced by the specific triggers of asthma. Current studies indicate that EVs are released by potentially all cell subtypes in the asthmatic airways, particularly by bronchial epithelial cells (with different cargoes in the apical and basolateral side) and inflammatory cells. Such studies largely suggest a pro-inflammatory and pro-remodelling role of EVs, whereas a minority of reports indicate protective effects, particularly by mesenchymal cells. The co-existence of several confounding factors—including technical pitfalls and host and environmental confounders—is still a major challenge in human studies. Technical standardization in isolating EVs from different body fluids and careful selection of patients will provide the basis for obtaining reliable results and extend their application as effective biomarkers in asthma.

Extracellular Vesicles (EVs) as Crucial Mediators of Cell-Cell Interaction in Asthma Asthma is the most common chronic respiratory disorder worldwide and accounts for a huge health and economic burden. Its incidence is rapidly increasing but, in parallel, novel personalized approaches have emerged. Indeed, the improved knowledge of cells and molecules mediating asthma pathogenesis has led to the development of targeted therapies that significantly increased our ability to treat asthma patients, especially in severe stages of disease. In such complex scenarios, extracellular vesicles (EVs i.e., anucleated particles transporting nucleic acids, cytokines, and lipids) have gained the spotlight, being considered key sensors and mediators of the mechanisms controlling cell-to-cell interplay. We will herein first revise the existing evidence, mainly by mechanistic studies in vitro and in animal models, that EV content and release is strongly influenced by the specific triggers of asthma. Current studies indicate that EVs are released by potentially all cell subtypes in the asthmatic airways, particularly by bronchial epithelial cells (with different cargoes in the apical and basolateral side) and inflammatory cells. Such studies largely suggest a pro-inflammatory and pro-remodelling role of EVs, whereas a minority of reports indicate protective effects, particularly by mesenchymal cells. The co-existence of several confounding factors—including technical pitfalls and host and environmental confounders—is still a major challenge in human studies. Technical standardization in isolating EVs from different body fluids and careful selection of patients will provide the basis for obtaining reliable results and extend their application as effective biomarkers in asthma. Asthma is a chronic respiratory disorder that is estimated to affect 300 million persons worldwide, a figure that is projected to sharply increase with 100 million further cases by 2025. It is currently the most common chronic condition in the pediatric population, affecting 5–10% of children and adolescents [1]. Although some studies suggest that the rise may have subsided in some countries, asthma continues to pose a substantial socio-economic burden (impact on quality of life, days lived with disability, absence from school and from work). The increase in asthma prevalence has been paralleled by a similar increase in other allergic conditions such allergic rhinitis and eczema. Clinically, asthma is defined by a history of respiratory symptoms that include wheezing, shortness of breath, chest tightness, and cough, and is associated with variable airflow limitation. Both symptoms and airflow limitation characteristic of asthma vary over time and in intensity [2] and can be triggered by several factors including allergen exposure, exercise, laughter, irritants, weather changes, and viral infections [2]. The delineation of comorbidities is also an important share in the burden of the disease, because comorbidities can contribute to poor control of asthma and may affect the natural history of the disease and the therapeutic approach [3,4]. Major impact comorbidities are: (1) rhinitis (particularly allergic rhinitis), which results in upper airway inflammation and contribute to exacerbate asthma [5]; (2) gastroesophageal reflux which may aggravate airway inflammation [6]; (3) obesity, which affects respiratory mechanics but also induces a systemic pro-inflammatory status [7]; and (4) bronchiectasis, which increases the risk of exacerbations due to pulmonary infections [8]. Asthma is a heterogeneous disease with different underlying pathogenetic pathways [2] that results from complex interactions between individual genetic susceptibility, host factors, and environmental exposures. Defining these pathways, the asthma endotypes, has become a key task in asthma, as the endotype-driven approach offers a way to better diagnose, monitor, and refer patients to the most appropriate therapeutic strategies [9]. Airway inflammation is the main recognized mechanism, and the typical inflammatory setting is characterized by the presence of eosinophils in the submucosa. Other cell types that populate the inflammatory infiltrate are mast cells, basophils, neutrophils, monocytes, and macrophages [10]. The canonical inflammatory response—the so-called type 2 inflammation—is fueled by T helper 2 lymphocytes that produce Interleukin (IL)-5, IL-4, and IL-13. It occurs in as many as 80% of children and it is also seen in the majority of adults with asthma in association with sensitization to environmental allergens, such as those from dust mites, fungi, pets, and pollens [11,12,13,14]. Besides classic allergic asthma, T2-high asthma also includes aspirin-exacerbated asthma with chronic rhinosinusitis/nasal polyposis. On the other side of the spectrum, T2-low asthma (sometimes referred to as non-eosinophilic asthma) encompasses both inflammatory endotypes where T2 cytokines are not involved in driving asthma pathobiology: neutrophilic and paucigranulocytic. Neutrophilic asthma is usually associated with obesity and the key cytokines involved are IL-17, IL-8, and IL-6 [15,16]. Paucigranulocytic asthma is characterized by the presence of significant airway remodeling in the absence of concomitant airway inflammation. Bronchial wall remodeling is another key pathogenetic trait of asthma that has been described as an abnormal tissue reparation process responsible for chronic lesions to the normal airway structure. It is now evident that remodeling occurs very early in the natural history of asthma, starting in infancy before the age of two years [17,18] and may have a negative impact on long-term functional outcomes. The most important remodeling features include epithelial shedding, fibrosis of subepithelial basement membrane (BM thickening), smooth muscle hypertrophy/hyperplasia, and neoangiogenesis [19,20] (Figure 1). In the classic T2-high asthma, the epithelial-derived cytokines initiate the process by driving dendritic cell activation and phenotypic changes in the airways, followed by their migration to secondary lymphoid tissues where they present the allergen to naïve T cells and orient them towards a T2 profile, characterized by the production of IL-4, IL-5, and IL-13 among others. The main target of IL-5 is the eosinophil: through its receptor, IL-5 can activate different signal transduction pathways, inducing growth, bone marrow maturation, peripheral migration, and the activation and survival of eosinophils [21]. On the other hand, IL-4 is mainly directed toward B lymphocytes with activation, immunoglobulin production, and isotype switching towards IgE. IL-4 also induces the differentiation of CD4+ T lymphocytes into the Th-2 subtype with an autocrine mechanism and acts on structural cells (epithelium, goblet cells, fibroblasts, smooth muscle) [22,23]. IL-13 has an action partially redundant to IL-4: indeed, they share a common receptor (IL4/IL-13R) and the same targets (mainly B lymphocytes, epithelium, endothelium, smooth muscle). IL-4/IL-13 are therefore implicated both in the amplification of the inflammatory process and have a strong involvement in the processes of airway remodeling and neoangiogenesis [24]. Innate immune responses were traditionally considered responsible for the release of acute mediators of inflammation during an asthma attack. Resident innate cells (mainly mast cells and macrophages) produce histamine, serotonin, and substance P that are stored in preformed granules and immediately released after the encounter with the triggering factor. They will promote the contraction of smooth muscle, production of mucus, and increase in vascular permeability, which results in edema [25]. More recently, innate immune responses have gained a central stage in asthma also for their immune modulatory role after the discovery of type 2 innate lymphoid cells (ILC2) [26,27,28]. Unlike lymphocytes, ILCs do not express antigen-specific receptors, but are instead activated by a broad range of signaling molecules. They concentrate at barrier surfaces such as the skin, gut, and airways, at which site ILC2s are the dominant subset [29,30,31,32]. Upon exposure to cytokines, allergens or viruses, ILC2s accumulate in the submucosa, close to epithelial cells and T cells, and have been involved in the development and maintenance of type 2 inflammation in asthma [33,34,35,36,37]. In the context of innate responses, alarmins, e.g., IL-25, Thymic stromal lymphopoietin (TSLP) and IL-33, are the most important players. IL-25 is expressed as a preformed cytokine, stored in granules, by the airway epithelium and is rapidly released upon cell stimulation by environmental triggers, including allergens [38]. TSLP is also released in response to epithelial stimuli (e.g., allergens, viruses, bacteria, pollutants, and smoke) and initiates multiple downstream innate and adaptive pathways involved in asthma. Inhibition of TSLP represents a novel approach to treat the diverse endotypes of asthma [38]. IL-33 is a central component for activation of both the innate and adaptive arms of immunity [39]: it is responsible for inducing early immune development and polarization toward type 2 T cell inflammation [40] through activation of resident dendritic cells (DC), but also independently of DCs [41]. Of interest, there is recent evidence suggesting that IL-33 is essential to the process of airway remodeling observed in asthma through the upregulation of cluster of differentiation (CD)146, thus promoting epithelial mesenchymal transition [42]. The contribution of epithelial tissues to fibrosis through the process of epithelial–mesenchymal transition (EMT) has previously been demonstrated in lung cancer as well as in fibrotic diseases (of the lung, kidney, eye, liver, and intestine). These data expanded the knowledge of the mechanisms regulating the EMT process in asthma and substantiate the hypothesis that structural abnormalities in the asthmatic airway epithelium could lead to enhanced signaling to underlying mesenchymal and immune cells, driving the abnormal responses to environmental stimuli in the asthmatic airway [43]. In such a complex pathogenetic scenario, where several cell types cooperate to provoke the clinical manifestations of asthma, understanding the mechanisms of cell–cell interactions rises up as a crucial issue. In parallel with canonical signaling, a new army of submicroscopic messengers has been identified and is catalyzing scientific interest: The extracellular vesicles (EVs). Chargaff et al., in 1946, first argued the existence of cytoplasmic debris released from platelets characterized by functional thromboplastic activities [44]. Later, in 1967, the advent of electron microscopy allowed for the identification of such components, minute platelet-derived particulates rich in lipid content they termed “platelet dust” [45]. In the following decades, small vesicles secreted or shed by the cell membrane were detected in cell culture, plasma, and body fluids. According to the size, origin, and surface markers [46], these particles were distinguished into: exosomes: 30–200 nm diameter; generated by inward budding of the membrane (endocytosis), subsequent formation of multivesicular bodies, and release by exocytosis; and characterized by tetraspanins (CD9, CD63, CD81, and CD82) and other surface markers derived from the multivesicular body. microvesicles: 100–1000 nm diameter; released by budding and shedding from the plasma membrane of activated cells. They share the same membrane components with the parent cell. apoptotic bodies: 1000–4000 nm diameter; released through blebbing of apoptotic cell membrane by cells undergoing apoptosis; and enriched in phosphatidylserine, annexin V. These different types of vesicles are exemplified in Figure 2 in a bronchial epithelial cell. Nonetheless, methodological issues (i.e., lack of specific markers, overlapping vesicles size) and the trend to focus on their content more than on their classification supported the recommendation of using of the umbrella term “extracellular vesicle” to describe all the anucleated particles naturally released from the cell delimited by a lipid bilayer [47,48]. Indeed, the charm of EVs stands in their ability to mediate intercellular cross-talk and quietly influence the inflammatory milieu. Once released, the EVs can be internalized via endocytosis or membrane fusion, releasing their contents into “recipient” cells [49]. EV cargo includes proteins, sugars, lipids, immune molecules (MHC), cytokines, hormones, and a wide variety of genetic materials, such as DNA, mRNA, and non-coding RNAs, a content protected from proteases and nucleases in the extracellular space by the limiting membrane [50]. EVs are able to convey cell messages not only to the tissue microenvironment but also throughout the body, representing both harmful and homeostatic ambassadors. Circulating blood cell-derived EVs were initially linked to coagulopathies and cardiovascular disorders [51]. A peculiar increase in circulating EVs is common among different conditions associated with increased cardiovascular risk factors, such as smoking [52], diabetes mellitus [53], and hypertension [54]. Indeed, EVs might exert a pro-inflammatory action favoring atherosclerosis development, as suggested by some in vitro evidence. EVs can stimulate cytokine release from endothelial cells promoting monocyte adhesion to the endothelium and their migration to the plaque [55,56] and increase endothelial permeability [57]. These mechanistic in vitro studies help with understanding the importance of these vesicles in the development of atherosclerotic lesions. In fact, both microparticles [58] and exosomes [59] have been described in the plaque, and the levels of circulating procoagulant EVs are increased in patients with acute coronary syndrome compared to those with stable coronary disease and healthy controls [60,61,62]. Increased levels of pro-coagulant microparticles—filled with tissue factor and phosphatidylserine—have long been detected in the plasma of patients with pulmonary embolism [63,64,65,66]. Recently, the abundance of platelet and leukocyte-derived EVs was acknowledged as a possible contributor in hypercoagulability and trombophilic risk in severely ill COVID-19 patients [67]. Beyond coagulopathies, an increase in peripheral EV level was observed in many inflammatory conditions, including connective tissue diseases [68], inflammatory bowel diseases [69], and vasculitis [70]. There is accumulating evidence that EVs may be key players in the respiratory system as well, in regulating both homeostatic and pathologic conditions [71], especially in lung cancer where EVs represent not only a perfect target for liquid biopsy but also key effectors of tumor development as key regulators of tumor microenvironment [72]. We will then review the current knowledge delineating the possible contribution of EVs in the pathogenetic mechanisms of asthma: From the evidence in preclinical studies to their detection in tissue, blood, Bronchoalveolar Lavage (BAL), and other samples of patients with asthma with the intent to explore their possible applications from identification of specific disease endotypes to monitor disease activity and evaluate response to therapies. Accumulating evidence from preclinical studies supports the hypothesis that EVs are crucial mediators of cell–cell interaction in asthma as in many other immune-mediated diseases [73]. In most studies, EVs produced by the immune cells were the main focus of research in the EV field. However, multiple kinds of non-immune cells have been shown as efficient EV sources: epithelial cells, fibroblasts, smooth muscle cells, and mesenchymal cells. These are often significant contributors to the ongoing immune response. Pulmonary epithelial cells appear to be the main source of EVs in the lungs [74] (Figure 2). Such production is not steady since lung inflammation can significantly alter EVs content and release from epithelial cells, as observed in cell cultures [75]. Different well-known triggers of inflammation in asthma have the potential to modify EV release from airway epithelial cells: Allergic inflammation: Increased levels of EVs, mainly of epithelial origin, were detected in the BAL of mice with allergic airway inflammation compared with controls [76]. Such a finding was later confirmed by complementary techniques in another study that analyzed the EV content of BAL fluid in mice. The authors observed that 80% of the alveolar EVs were of epithelial origin and that, after lung allergen challenge, hematopoietic cell-derived EVs doubled along with miRNAs selectively expressed by immune cells, such as miR-223 and miR-142a [77], supporting the key interplay between immune and non-immune cells mediated by lung EVs. Indeed, when treated with IL-13, bronchial epithelial cells released exosomes that promoted monocyte proliferation and chemotaxis [76]. A subsequent study suggested that epithelial-derived EVs released under IL-13 stimulation are enriched in 16 specific miRNAs that might influence Th2 polarization and dendritic cell maturation [78]. Mechanical stress: Bronchoconstriction, simulated in vitro by a compressive stress under regulated pressure, triggers the release of EVs bearing Tissue Factor, a molecule specifically increased in the BAL of asthmatics compared to healthy controls [79]. Mechanical compression of human bronchial epithelial cells is associated also with release of tenascin C carrying EVs [80]. Tenascin C is an extracellular matrix glycoprotein that modulates cellular processes such as cell adhesion, proliferation, and migration during embryonic development and tissue repair. Its expression is mostly absent in physiologic conditions and increases with tissue remodeling and disease, particularly in asthma, where tenascin C is abundant in the subepithelial basement membrane at baseline and further increased in response to allergen challenge [81]. Respiratory infections: Respiratory tract infections are common causes of asthma exacerbations. Rhinovirus infection can promote the release of EVs containing tenascin-C, which, in addition to the already enlisted functions, activates local cytokine synthesis. Such pathways are highly activated in the airways of people with asthma upon virus stimulation [82]. Furthermore, exosomes isolated from cells infected with respiratory syncytial virus are able to activate innate immune responses by inducing cytokine and chemokine release from human monocytes and airway epithelial cells [83]. Animal models suggest that EVs released during infectious events have mainly a pro-inflammatory role and favor persistent lung damage. Indeed, a first study in 2010 suggested that, after lipopolysaccharide (LPS) stimulation, epithelial-derived EVs are enriched in BAL and that these EVs are characterized by surface exposure of the inflammatory marker, Major Histocompatibility Complex (MHC) class II [84]. Conversely, it was later observed that sterile stimuli (oxidative stress, acid aspirations) mainly induced the accumulation of epithelial-derived-EVs in mice BAL [85], whereas infectious stimuli (LPS, gram negative bacteria) mainly promoted the release of alveolar macrophage-derived EVs [86]. Whatever the prevailing parental cell, EVs released during an infectious event are known to activate and amplify the inflammatory response. Indeed, LPS-induced EVs were found to enhance the production of Th1- and Th17-polarizing cytokines (IL-12p70 and IL-6, respectively) by lung dendritic cells [84]. On this line, IL-17A and Tumor Necrosis (TNF) alpha co-stimulation of epithelial cells was found to promote the accumulation of EVs able to enhance neutrophil chemotaxis [87]. In addition, the EVs released in the lung under infectious conditions might not only be amplifiers of infective exacerbations but might also be implied in infection prevention/resolution. Indeed, Kesimer et al. observed that epithelial cells released exosome-like vesicles with a neutralizing effect on human influenza virus [88]. Moreover, epithelial cell-derived EVs contain membrane mucins that are known to be part of the mucociliary clearance systems and innate immunity that protects the respiratory tract from environmental pathogens and xenobiotics [89]. Pollutants: air pollution has been proven, both in vitro and in vivo, to elicit EVs release [90]. Nonetheless, the quality of available evidence is limited by the wide variety of models, time of exposure, and EV characterization techniques. Stassen et al. have shown that EV production is induced regardless of Particulate Matter (PM) size (PM2.5 or PM10) but the mechanism involved seems different and could imply discrepancies in the ability of these PMs to form reactive oxygen species (ROS) [91]. Neri et al. reported that a large amount of EVs are secreted by mononuclear and endothelial cells treated with urban PM [92]. Furthermore, pollutants exposure is known to have a strong impact on vesicular miRNA content both in vitro and in vivo [93,94]. Cigarette smoke: A number of studies have shown that the exposure to cigarette smoke extract leads to increased secretion of EVs from cultured human bronchial epithelial cells [95,96]. Such EVs can mediate interaction with the airway vasculature by promoting endothelial cell survival [97]. These and other studies (summarized in reference [98]) suggest that EVs induced in response to cigarette smoke might modulate inflammation, thrombosis, tissue remodeling, endothelial dysfunction, and angiogenesis. As described above, several triggers can promote EV release from epithelial cells. Further insights on the functional significance of epithelial cell production of EVs are suggested by a recent study which compared the differential EV release from the apical and basolateral side of bronchial epithelial cells from either asthmatics or healthy controls. In an air–liquid interface model, the authors isolated EVs from both the apical and the basolateral side, finding significant differences. Of interest, the EV populations isolated from the apical cell side were mainly composed of vesicles with diameters matching the size range of the exosomes. Conversely, on the basolateral cell side, median vesicle diameters were noticeably larger, consistent with the size of the microvesicles rather than with the exosomes. Furthermore, 236 miRNAs were differentially expressed depending on the EV secretion side, regardless of the disease phenotype. A pathway analysis predicted mTOR (mammalian target of rapamycin) and MAPK (mitogen-activated protein kinase) signaling pathways as potential downstream targets of apically secreted miRNAs. In contrast, miRNAs specifically detected at the basolateral side were associated with pathways of T and B cell receptor signaling, suggesting a profound effect on the regulation of submucosal inflammation. Even if differences in miRNA profiles were more pronounced in comparing apical versus basolateral sides, some alterations were also observed in the comparison of asthmatics with healthy controls in the levels of certain EV-associated miRNAs (or their families). The study proves a compartmentalized packaging of EVs by bronchial epithelial cells supposedly associated with site-specific functions of cargo miRNAs, which are considerably affected by disease conditions such as asthma [99]. In vitro studies have shown that EVs are released by all the main inflammatory cell types involved in asthma pathogenesis including mast cells [100], eosinophils [101,102,103], monocyte/macrophages [104], neutrophils [105], T lymphocytes [106], and dendritic cells [107,108]. Eosinophils purified from peripheral blood have the potential, when stimulated with Interferon (IFN)γ, to release EVs [109]. Eosinophil-derived EVs were shown to up-regulate reactive-oxygen species and nitric oxide production in eosinophils and to enhance their chemotaxis and adhesion by Intercellular Adhesion Molecule 1 (ICAM-1) and integrin-2 [102]. Along this line, the same group observed that eosinophil-derived EVs could increase the apoptosis of small airway epithelial cells and reduce their wound healing capacity [103]. Similarly, mast cells, which naturally store histamine, proteoglycans, and other fast acting inflammatory mediators [110], were shown to release EVs in blood capable of boosting lung allergic reaction [111]. As for alveolar macrophages, it was shown that mouse resident AM could blunt inflammatory signalling in alveolar epithelial cells by transcellular delivery of suppressor of cytokine signalling 3 (SOCS3) within EVs [112]. Indeed, SOCS3 levels were reduced in a murine model of chronic asthma and macrophage-derived EVs enriched in SOCS3 inhibited the activation of transcription in epithelial cells challenged with IL-4/IL-13 [113]. Primary human macrophages and dendritic cells have the potential to promote granulocyte migration through EV release [104]. They are also active on T-lymphocytes by the release of exosomes expressing OX40 ligand (OX40L), which is able to promote proliferation and differentiation of CD4+ T cells towards a Th2 phenotype [114]. Supporting further implications of involvement of EVs in asthma, exosomes with the potential to be pathogenic were isolated from lymphocytes as well. Indeed, EVs isolated from B cells can present allergen-derived peptides to T cells and induce their proliferation and production of Th2-like cytokines [115] either in a direct manner [116,117] or in cooperation with dendritic cells [118,119]. Furthermore, T cells could promote mast cell degranulation even at distant inflammatory sites by releasing EVs in the bloodstream [120]. In contrast with eosinophilic asthma, which is extensively investigated, neutrophilic inflammation characterizes the most challenging phenotype of asthmatic patients [121,122]. The studies aiming at investigating EVs released from neutrophils are scarce in asthma. Nevertheless, emerging evidence suggests that neutrophil-derived EV might promote the growth of airway smooth muscle cells, thus favoring airway remodeling, as suggested by co-cultures of neutrophil-derived exosomes and smooth muscle cells in a natural model of equine asthma [105,123]. At variance with the growing evidence on inflammatory/immune cell-derived EVs, less is known on the role of the EVs released from non-immune cells in asthma development. The EVs detected in the culture media from severe asthmatics’ fibroblasts, mainly exosomes, have been shown to be filled with cytokines and chemokines that are easily uptaken by bronchial epithelial cells promoting their proliferation. Of interest, the mRNA and protein levels of transforming growth factor (TGF)-β2 secreted from fibroblasts were similar in patients with asthma compared to controls, whereas TGF-β2 content in exosomes was differentially expressed [124]. Such discrepancy suggests that exosomal carrying of TGF-β2, a well-known regulator of cellular growth, is specifically impaired in severe asthma and could contribute to airway remodeling. Indeed, available asthma treatments can mostly control inflammation but have limited effects on airway remodeling, which cannot be reversed [125]. Promising results addressing airway remodeling come from studies in mice in which mesenchymal cells were able to reduce smooth muscle hypertrophy and vascular hyperemia [126]. Recent evidence suggests that the systemic administration of EV derived from mesenchymal cells could vehicle beneficial effects in asthma (as do the intact parental cells), including reduced collagen fiber deposition and decreased TGF-β levels in lung tissue [127]. When co-cultured, adipose tissue mesenchymal stromal cells release exosomes that can be internalized by airway smooth muscle cells, promote smooth muscle cells apoptosis and suppress inflammatory mediators secretion from muscle cells [128]. Dong et al. observed that the administration of mesenchymal cell-derived EVs, especially when released under hypoxia, prevented mouse chronic allergic airway remodeling, as suggested by the decreased expression of pro-fibrogenic factors α-smooth muscle actin, collagen-1, and the TGF-β1-p-smad2/3 signaling pathway [129]. Collectively, these results support the prospect that mesenchymal cell-derived EVs will provide a future therapeutic approach in respiratory diseases, as reviewed in reference [130]. An overview of current evidence on EVs functions from immune and non-immune cells is summarized in Table 1. Today, the search for effective biomarkers, meaning easily measurable and reproducible sensors of disease phenotype and prognosis to personalize the approach to asthma patients, has fostered clinical and scientific interest in EVs. Indeed, the presence of these particles in body fluids has long been related to specific disease, suggesting their use as sensors of disease activity. The first studies on asthma EVs were inspired from those on cardiovascular diseases [63,64,65,66] and focused on circulating microparticles. Such particles share surface markers with parental cells, a feature that makes them easily detectable in blood by immunoassays and cytometric analysis. Duarte et al. compared circulating levels of platelet and endothelial-derived microparticles in asthmatics and control patients and found that the number of platelet-derived EVs was higher in asthma [131]. On the same line, high levels of circulating endothelial-derived microparticles (CD31+/CD41−) and other inflammatory markers have been reported in asthmatic patients in Beijing and are associated with air pollution. Following the remarkable improvement in air quality achieved during the 2008 Olympic games, microparticles decreased in asthmatics and reached controls’ levels, a consistent benefit that was confirmed after 2 months [132]. Nonetheless, a similar involvement was observed in several inflammatory diseases [68,69,70,133,134] mining the specificity of blood-derived microparticles as a biomarker specific for asthma. Wagner et al. characterized plasma EVs according to surface markers, particles and protein concentrations, and cytokine content in allergic patients. By this approach, they showed that the pro-allergic cytokines IL-4 and IL-5 were higher in plasma EVs of patients with allergies than in healthy controls combined with the pro-inflammatory cytokines IL-6 and TNFalpha [135]. Another valuable option is the search for vesicular miRNA profiles. Plasma exosomal miR-124, miR-125b, miR-133b, miR-130a, and miR-125b-1-3p differed between asthmatics and controls and were related to CRP and IgE levels [136]. Of particular interest was miR-125b, who’s levels not only differed between patients and controls but also significantly increased with asthma severity (intermittent, mildly persistent, moderately persistent, and severely persistent asthma) [137]. However, another study detected no differences in miR-125 levels in moderate asthmatic patients compared to the healthy controls, whereas miR-223 and miR-21 were significantly up-regulated [138]. Plasma EV miR-122-5 was increased in patients with uncontrolled asthma compared to controls, and its expression was related to eosinophil and neutrophil count [139]. Of note, the levels of mi-RNA-126, which are increased in peripheral blood exosomes of patients with atopic asthma, were also increased in the lungs of an allergic asthma mouse model [140]. Another interesting finding is that inflamma-miRNAs (i.e., miRNA released by inflammatory T cells) could label distinct endotypes of asthma, being differentially expressed in serum exosome samples of T2 high and T2 low asthmatic patients [141]. Although these approaches represent a significant step forward supporting the application of circulating EVs as biomarkers of disease endotypes in asthma, peripheral blood is still far from being a reliable surrogate of lung pathology and inflammation [17,18]. Limited but valuable evidence is available on the presence and the main immunological role of EVs in the BAL of asthmatic patients. Admyre’s group firstly isolated EVs with major histocompatibility complex class II in healthy volunteers’ BAL, suggesting that floating EVs might activate the T-cell mediated immune response [142]. Hough and colleagues showed that asthmatics’ EVs presented increased frequencies of Human Leukocyte Antigen (HLA)-DR, an MHC-II molecule as compared to healthy controls, and that EVs concentrations were related to eosinophilia and serum IgE [143]. Furthermore, the EVs isolated in asthmatics’ BAL were characterized by lipid abundance, suggesting that they might actively transfer lipidic inflammatory mediators to alveolar cells [143]. On this line, BAL exosomes from asthma patients contain enzymes for leukotriene biosynthesis and have been proven, in vitro, to promote leukotriene 4 and IL-8 release from bronchial epithelial cells [144]. Moreover, Levanen and colleagues identified a pool of 24 exosomal miRNAs isolated from BAL that differed between asthmatics and control subjects [145]. Bronchoalveolar lavage, though informative, has a limited use both for research and in routine clinical practice, especially in severe asthma. Looking for less invasive techniques, Bahmer and colleagues profiled the EV-miRNA signature in plasma of patients with asthma, reporting differential expression of several miRNAs, particularly miR-122-5p. In a pilot study performed in sputum, they confirmed the results obtained in plasma EVs [139]. A recent study applied proteomic analysis to analyze the aerosol of droplet particles that are formed from the epithelial lining fluid when the small airways close and re-open during inhalation succeeding a full expiration detected. The asthmatic patients’ proteome, compared to healthy controls, was enriched in extracellular proteins associated with extracellular exosome-vesicles and innate immunity [146]. Furthermore, a reduced expression of miR-34a, miR-92b, and miR-210 was detected in the nasal lavage of asthmatic children compared to healthy controls, and their levels were associated with the obstruction of large and small airways [78]. In addition to sputum, droplets, and nasal lavage, the presence of EV was recently confirmed also in the saliva of a cohort of children with asthma, opening further opportunities for research in this emerging landscape [147]. Host’s EVs are not alone in the lung milieu. Of interest, airway and gastro-intestinal tract microbiota show peculiar aspects in asthma, and accumulating evidence supports the existence of a link microbiome—inflammatory endotypes as well as a possible role of microbiome in disease pathogenesis [148,149]. The following studies have tested the potential of EVs to mirror the complexity of the human microbiota. By 16 s rDNA amplification and sequencing of plasma EVs isolated from 260 patients with asthma and 190 healthy controls, Lee et al. caught a frame of the bacterial composition. Whether the increased abundance of bacteroidetes in asthmatics’ plasma results from differences in the microbiota of the lung or gut is still unknown since no parallel assessment of respiratory/intestinal samples was performed [150]. Overcoming the intrinsic limitations of studying the microbiome on plasma EVs, An et al. focused on the exhaled breath condensate obtained from 58 healthy controls and 251 patients with asthma. Based on EV populations, they found higher complexity and biodiversity in asthma but no association was identified between airway microbiota and specific inflammatory/clinical phenotypes [151]. Further expanding such investigations, metagenomic analysis of EV has been applied to the urine samples collected from children with allergic airway disease who shared unique features when compared to atopic and healthy controls [152,153]. Children with allergic airway disease shared the highest level of urine EVs derived from Klebsiella and Haemophilus, and their level was positively related to total IgE and eosinophil percentage [153]. Nucleic acid sequencing of EV cargo detected in non-invasive samples might offer, in the next feature, a novel platform to study dysbiosis in the pathogenesis of asthma. Nonetheless, studies are still in their infancy, and several concomitant confounding factors need to be ascertained when investigating bacteria-derived EVs, including environmental and dietary factors. Accumulating evidence on EV features, biogenesis, and release in asthma hold out promises for effectively understanding the role of these subcellular particles in disease progression. EVs are released in the lung microenvironment by both immune and structural cells, mainly epithelial cells and fibroblasts. In the context of epithelial responses, the packaging of EVs is associated with the distinct functions of their cargo miRNAs depending on the specific site of release (damage sensing in the apical side, immune regulation in the basal side). EVs have been proven in experimental models to modulate several pathways, mainly through the delivery of miRNAs, proteins, and lipid mediators. Collectively, available evidence mainly suggests a pro-inflammatory and pro-remodelling role of EVs in asthma pathogenesis, whereas a minority of reports indicate protective effects. Of particular interest are mesenchymal cells-derived EVs, which have shown promising results when administered as a therapeutic strategy to contrast airway remodeling. Unraveling the role of EVs in different clinical phenotypes of asthma will allow to exploit their high diagnostic and prognostic potential as biomarkers. In an attempt to improve their specificity as biomarkers, researchers are working on identifying unique combinations of surface markers and cargoes that characterize distinct EVs subtypes. Furthermore, biological samples reflecting more directly the airway milieu rather than peripheral blood are emerging as a source for the study of EVs: bronchoalveolar and nasal lavage, sputum, saliva, and droplets from the epithelial lining fluid. Expanding knowledge indicates that EV release can be potentially influenced by a vast number of factors, all relevant to the pathogenesis of asthma, including repeated mechanical stress, respiratory infections, air pollution, cigarette smoke, and microbiome. Thus, an exhaustive phenotypical characterization of the study subjects and a detailed evaluation of all possible confounding factors are essential to decipher the language of EVs in asthma.

PMC10003415

Jörg Fahrer,Markus Christmann

DNA Alkylation Damage by Nitrosamines and Relevant DNA Repair Pathways

28-02-2023

N-nitroso compounds,N-nitrosamines,DNA alkylation,DNA damage,DNA repair,MGMT,AAG,ALKBH,BER,NER,TLS

Nitrosamines occur widespread in food, drinking water, cosmetics, as well as tobacco smoke and can arise endogenously. More recently, nitrosamines have been detected as impurities in various drugs. This is of particular concern as nitrosamines are alkylating agents that are genotoxic and carcinogenic. We first summarize the current knowledge on the different sources and chemical nature of alkylating agents with a focus on relevant nitrosamines. Subsequently, we present the major DNA alkylation adducts induced by nitrosamines upon their metabolic activation by CYP450 monooxygenases. We then describe the DNA repair pathways engaged by the various DNA alkylation adducts, which include base excision repair, direct damage reversal by MGMT and ALKBH, as well as nucleotide excision repair. Their roles in the protection against the genotoxic and carcinogenic effects of nitrosamines are highlighted. Finally, we address DNA translesion synthesis as a DNA damage tolerance mechanism relevant to DNA alkylation adducts.

DNA Alkylation Damage by Nitrosamines and Relevant DNA Repair Pathways Nitrosamines occur widespread in food, drinking water, cosmetics, as well as tobacco smoke and can arise endogenously. More recently, nitrosamines have been detected as impurities in various drugs. This is of particular concern as nitrosamines are alkylating agents that are genotoxic and carcinogenic. We first summarize the current knowledge on the different sources and chemical nature of alkylating agents with a focus on relevant nitrosamines. Subsequently, we present the major DNA alkylation adducts induced by nitrosamines upon their metabolic activation by CYP450 monooxygenases. We then describe the DNA repair pathways engaged by the various DNA alkylation adducts, which include base excision repair, direct damage reversal by MGMT and ALKBH, as well as nucleotide excision repair. Their roles in the protection against the genotoxic and carcinogenic effects of nitrosamines are highlighted. Finally, we address DNA translesion synthesis as a DNA damage tolerance mechanism relevant to DNA alkylation adducts. DNA alkylation lesions are one of the most common types of DNA damage and can be induced by endogenous compounds, environmental agents, and alkylating drugs used in anticancer therapy. These alkylating agents are mutagenic, toxic, clastogenic, and teratogenic and represent well-known human carcinogens [1]. Depending on the given alkylating agent, different positions in the DNA can be attacked via nucleophilic substitution (SN-reaction). Alkylating agents can act via a SN1 or a SN2 reaction. During the SN2 (second-order nucleophilic substitution) reaction, the addition of the nucleophile and the elimination of the leaving group occur simultaneously. In opposition to that, during the SN1 (first-order nucleophilic substitution) reaction, the addition of the nucleophile and the elimination of the leaving group occur in two separated steps. The SN1 reaction is more important when the targeted carbon atom within the alkylating agent is surrounded by interfering bulky groups. Generally, alkylating agents can form adducts at all O- and N-atoms of purines and pyrimidines (Figure 1), as well as at phosphotriesters of the DNA backbone. While alkylating agents of the SN1-type alkylate O- and N-atoms, SN2 reagents mainly alkylate N-atoms [2]. O-alkylations are highly mutagenic and cytotoxic [3]. Although only amounting to less than 8% of total alkylations [2], O6-alkylguanine represents the most critical type of DNA alkylation damage. O6-methylguanine (O6-MeG) and O6-ethylguanine (O6-EtG) can mispair with thymine, leading to GC → AT transition mutations following two rounds of replication [4]. O4-methylthymine (O4-MeT) also represents a pre-mutagenic DNA lesion, but is only induced in minor amounts. N-alkylations are predominantly cytotoxic and less mutagenic, although recent in vivo data indicate mutagenicity for the replication-blocking lesion N3-methyladenine (N3-MeA) [5]. Endogenous alkylation (methylation) can occur by the intracellular methyl group donor S-adenosyl-l-methionine (SAM) [6] via nitrosation [7]. Whereas SAM acts by a SN2 mechanism and generates N7-Methylguanine (N7-MeG) and N3-MeA [6,8], enzymatic nitrosation of glycine and glycine derivatives as well as of bile acids predominantly forms O6-alkylating agents [7,9,10]. In addition, it is well established that bacteria in the stomach and gut catalyze the nitrosation of various secondary amines derived from ingested food, thereby forming nitrosamines (see below). Most alkylating agents found in the environment belong to the class of nitrosamines. The class of nitrosamides is frequently used in basic research or as drugs for the treatment of various tumor entities. In addition, compounds such as alkylsulfonates and nitrogen mustards also act via DNA alkylation. Nitrosamines represent compounds with the chemical structure R1R2N−N=O (R = aryl or alkyl group). They are pro-carcinogens, which require metabolic activation to form alkylating agents. Nitrosamines undergo enzymatic α-hydroxylation by CYP450 monooxygenases to form dealkylated primary nitrosamines, which further decompose to diazonium ions. Rearrangement and subsequent elimination of nitrogen result in the formation of carbenium ions, the final DNA alkylating species (for details on nitrosamines chemistry, see [11]). Around 300 structurally different nitrosamines are known [12], whereof more than 20 were assessed by the International Agency for Research on Cancer (IARC) according to their carcinogenicity in humans [13]. Nitrosamines are ubiquitously present in the environment (water, air, food) and arise, for example, in tobacco smoke and during industrial processes. Important nitrosamines found in food, personal care products, and drugs are listed in Table 1. The first nitrosamine identified in the environment was N-nitrosodimethylamine (NDMA), representing the most prevalent N-nitroso compound (NOC) in the diet [14]. Nitrosamines were detected in smoked fish, bacon, sausages, and cheese, but also in beverages such as beer and drinking water [14]. Apart from NDMA, several other nitrosamines were detected in food (Table 1 and Figure 2), including N-nitrosodiethylamine (NDEA), N-nitrosopiperazine (NPIP), and N-nitrosopyrrolidine (NPYR) [15]. The curing process, the temperature, and the amounts of secondary amines are the major factors that influence nitrosamine formation in food [16]. Furthermore, NOCs can be generated endogenously in the gastrointestinal tract, particularly in the stomach and the large intestine [17]. The intake of dietary heme or heme-containing red meat was shown to increase endogenous NOC formation in both rodent models and human volunteers [18,19,20,21]. NOC levels were determined in feces as apparent total nitroso compounds (ATNCs), which include N-nitrosamines, S-nitrosothiols, and nitrosyl-iron as major constituents [19,21]. As mentioned above, N-nitrosamines have to undergo metabolic activation to cause DNA damage. NDMA is primarily metabolized by CYP2E1, but also by CYP2A6, via α-hydroxylation [22]. This gives rise to methyldiazonium-ions that react with DNA under the formation of N7-methylguanine (N7-MeG), N3-methyladenine (N3-MeA), and O6-methylguanine (O6-MeG) as the most abundant lesions (Figure 3A) [23]. O2-methylthymine (O2-MeT) and O4-Methylthymine (O4-Me) were only detected at very low levels [23]. NDEA was shown to be activated mainly by CYP2A6 via α-hydroxylation [24], which leads to the formation of the respective ethylated DNA bases, i.e., N7-EtG, N3-EtA, O6-EtG, O2-EtT, and O4-EtT, as prevailing adducts [25]. As a minor pathway, ß-hydroxylation of NDEA can occur (Figure 3B). This gives rise to a 2-hydroxyethyldiazonium ion and DNA adducts such as N7-HOEtG, which is, however, found only in trace amounts [26]. It is further noteworthy that more than 50% of the ethyl adducts were detected at the hydrogen-linked phosphotriester oxygen [25]. The metabolic activation and DNA adduct formation of NPIP and NPYR as well as of other food-relevant nitrosamines have been recently reviewed elsewhere [27]. N-nitrosodiethanolamine (NDELA) was found as the predominant nitrosamine impurity in cosmetics [28] and was reported to be a substrate for CYP2E1-mediated toxification [29]. The metabolism of NDELA can occur via both α- and ß-hydroxylation pathways. The ß-hydroxylation of NDELA results in the formation of N-nitroso-2-hydroxymorpholine, which subsequently gives rise to glyoxal, whereas α-hydroxylation yields 2-hydroxyethyldiazonium ions [30]. Therefore, both hydroxyethyl and glyoxal DNA adducts are formed [31]. Another source of N-nitrosamines is cigarette smoke, which contains tobacco-specific nitrosamines [32]. Among them, the nitrosation products of nicotine, namely N-nitrosonornicotine (NNN) and nicotine-derived nitrosamine ketone (NNK), have been shown to contribute to cancer risk [33,34,35]. Additionally, nitrosation of anabasine and anatabine generates N-nitrosoanabasine (NAB) and N-nitrosoanatabine (NAT). Reduction of NNK and NNA forms nicotine-derived nitrosamine alcohol (NNAL) and iso-NNAL, whereas oxidation of NNA generates iso-NNAC. NNK undergoes metabolic activation by hepatic CYP2A6 and respiratory CYP2A13, with the latter being much more efficient [36,37]. NNAL was also reported to be metabolized by lung CYP2A13 [38]. Metabolism of NNK produces either carbenium ions or pyridyloxobutylating (pob)-agents, which lead to the formation of DNA methylation adducts (N7-MeG, N3-MeA, N3-MeG, O6-MeG, O4-MeG) and various pob-adducts, with O(6)-[4-oxo-4-(3-pyridyl)butyl]guanine (O6-pobG) being among them [39]. Thus, O6-pobG represents the second frequent pyridyloxobutylation product after the corresponding N7 alkylguanine adduct 7-[4-(3-pyridyl)-4-oxobut-1-yl]-guanine (N7-pobG) in NNK-exposed rats [40]. NNN was shown to be metabolized by both CYP2A6 and CYP3A4 [41]. In opposition to NNK, NNN only induces pob-adducts, with O6-pobG being among them [42,43]. Both DNA methylation and DNA pyridyloxobutylation are important events in NNK- and NNN-induced carcinogenesis in the rat [44], whereas in the mouse lung, DNA methylation seems to be of higher relevance [45]. For further reading on the metabolism and DNA adduct formation of tobacco-specific nitrosamines, we recommend a recently published comprehensive review [39]. A couple of years ago, nitrosamines were detected in various batches of sartanes [46], which are angiotensine receptor blockers and frequently prescribed antihypertensive drugs. The sartanes (valsartan and others) contained up to 20 µg of NDMA per tablet [47], which raised a major concern, leading to one of the largest drug recalls across Europe and the US. Metformin, a drug used for the therapy of type 2 diabetes, was shown to contain NDMA in late 2019 [48]. A detailed analysis of more than 1000 samples consisting of metformin active pharmaceutical ingredient (API) and drug products revealed that roughly 18% of all samples exceeded the limit of 32 ppb of NDMA, which is based on the acceptable intake (AI) of NDMA (96 ng) multiplied by the maximum daily dose of the API [49]. The AI is defined according to the ICH guideline M7(R1) for genotoxic and potentially carcinogenic impurities in pharmaceuticals and represents the daily, lifelong intake level corresponding to a theoretical cancer risk of 10−5 [50]. Interestingly, most of the API samples had no NDMA impurity, while a substantial amount of the finished dosage form was contaminated with NDMA at levels above the AI. Nitrosamines were also found in other drugs including ranitidine, a histamine receptor antagonist, and the antibiotic rifampicin [51]. In addition to short nitrosamines such as NDMA and NDEA, more complex nitrosamines have been identified in APIs and their products, e.g., N-nitroso-N-methyl-4-aminobutanoic acid (NMBA), N-nitrosoethylisopropylamine (NEIPA or NIPEA), and N-nitrosomethylphenylamine (NMPA) [52]. Furthermore, nitrosamines derived from the API were detected. Varenicline, a partial nicotinic acetylcholine receptor agonist and a drug used as an aid to smoking cessation, contained the impurity N-nitroso-varenicline and was, thus, recalled [53]. Very recently, the drug Ventolin with the API salbutamol was recalled due to the impurity N-nitrososalbutamol in three batches [54]. Whether API-derived nitrosamines also occur in other drugs is currently a matter of intensive research. Nitrosamides represent compounds with the chemical structure R1C(=X)N(-R2)-N=O (R: hydrogen atoms or organic residues) and can be divided into the N-nitrosamides (R1-C(=O)N(-R2)-N=O) and the derivates N-nitrosoureas (R1R2N(=O)N(-R3)-N=O), N-nitrosoguanidines (R1R2N(=NH)N(-R3)–N=O), and N-nitrosocarbamates (R1-O-C(=O)N(–R2)–N=O). Opposite to nitrosamines, nitrosamides do not require metabolic activation, but decompose spontaneously in aqueous medium, forming diazonium ions and finally carbenium ions as alkylating species. The most relevant class among the nitrosamides are the N-nitrosoureas, which comprise highly mutagenic compounds used in basic research as well as multiple compounds used in anticancer therapy (Table 2 and Figure 4). N-Methyl-N-nitrosourea (MNU) and its glucose derivate streptozotocin (N-(methylnitrosocarbamoyl)-α-D-glucosamine) represent the first generation of methylating anticancer drugs, forming N7-MeG, N3-MeA, N3-MeG, and O6-MeG [55]. Chloroethylating agents such as carmustine and lomustine are used as anticancer drugs for the treatment of glioblastoma, astrocytoma, malignant melanoma, gastrointestinal and pancreatic cancer, and Hodgkin’s and non-Hodgkin’s lymphoma [56]. These drugs chloroethylate, among others, the O6-position of guanine, forming O6-chloroethylguanine (O6-ClEtG). This adduct is unstable and undergoes intramolecular rearrangement, forming the N1,O6-ethenoguanine adduct and subsequently a N1-guanine-N3-cytosine interstrand DNA crosslink [57]. Apart from the mentioned N-nitrosoureas, MNNG (N-Methyl-N’-nitro-N-nitrosoguanidine) was used as an SN1-methylating drug in multiple studies. As mentioned above, MNU was initially used as an anticancer drug. However, due to its unstable nature, it was replaced by the newly designed compounds procarbazine (PCB, PCZ, N-Methylhydrazine, Natulan®, Matulane®) and dacarbazine (DIC, Imidazole carboxamide, dimethyl-triazeno-imidazole-carboxamide, DTIC®-Dome), which generate similar reactive alkylating species (Table 3 and Figure 5) [55]. However, metabolic activation by cytochrome P450 is necessary, which might be an obstacle for anticancer therapy. The latest-generation drug is temozolomide (TMZ, Temodal®, Temodar®), which does not require metabolic activation and is used in the clinic, preferentially for the treatment of malignant gliomas [58]. TMZ decomposes spontaneously into methyltriazenoimidazole carboxamide (MITC), finally giving rise to methyl carbenium ions [59] similar to those generated by NDMA. Additional alkylating agents not belonging to the group of nitrosamides and nitrosamines are alkylsulfonates such as ethyl methanesulfonate (EMS), methyl methanesulfonate (MMS), and Busulfan, the methanesulfonate diester of 1,4-butanediol. These alkylsulfonates act in an SN2 reaction and, therefore, produce mainly N7-MeG and N3-MeA [60]. The different DNA adducts produced by alkylating agents can be repaired by multiple DNA repair mechanisms (Figure 6). Generally, straight-chain alkyl lesions at the N3-A, N3-G, and N7-G position are removed by base excision repair (BER) initiated by the alkyladenine glycosylase (AAG). The AlkB homolog (ALKBH) demethylases directly revert N1-MeA, N1-MeG, N3-MeT, and N3-MeC, while the O6-methylguanine-DNA methyltransferase MGMT removes alkyl adducts from the O4-G and O6-G position. Among them, MGMT can also remove O6-ClEtG. However, after the formation of crosslinks, MGMT is not effective and the crosslink has to be resolved by the interstrand crosslink repair mechanism. Besides these mechanisms, the nucleotide excision repair pathway (NER) is involved in the repair of bulky alky adducts, and replication-blocking DNA alkylation lesions can be bypassed by translesion synthesis (TLS). Among the adducts induced by alkylating compounds, alkylations at the O6-position and O4-position are removed by the DNA repair protein MGMT. The MGMT gene is located at chromosomal position 10q26.3 and encodes an mRNA of 866 nucleotides and a protein containing 207 amino acids with a molecular weight of 24 kDa [61,62]. MGMT can remove methyl groups from O4-MeG and O6-MeG, but not from methylphosphotriesters [63,64]. However, the repair of O6-MeG is between 105 and 103 times faster than that of O4-MeG [65]. Besides methyl adducts, longer alkyl adducts can also be repaired by MGMT, such as ethyl-, n-propyl-, n-butyl-, 2-chloroethyl-, 2-hydroxyethyl-, iso-propyl-, and iso-butyl adducts. However, in this case, the repair efficiency decreases with increasing size of the alkyl group [66,67]. Importantly, O6-pobG can also be repaired by MGMT [68,69,70,71] and, if not repaired, induces G→A and G→T mutations [72]. Although being only a minor alkylation product with less than 8% of total alkylations, O6-MeG represents the most carcinogenic lesion. Thus, it was shown that the neurotropic carcinogenic activity of MNU depends on the lack of repair of O6-MeG [73]. In addition, transgenic mice overexpressing MGMT in their skin are protected against tumor formation upon exposure to MNU and nimustine (ACNU) [74,75,76]. Data obtained in different mouse models also revealed that MGMT protects against methylation-induced liver cancer [77], lung cancer [78,79], thymic lymphomas [80,81], and colon cancer [82,83]. A landmark study demonstrated that MGMT causes a threshold in NOC-induced colon cancer formation at low methylation dose levels [84]. Wild-type DNA-repair-proficient mice showed a non-linear tumor formation, whereas MGMT-deficient mice developed tumors in a linear, dose-dependent manner [84]. Intriguingly, these findings correlated very well with the NOC-induced O6-MeG levels and γH2AX formation in colorectal tissue [84,85]. Transgenic mice with high expression levels of the bacterial MGMT homolog Ada showed decreased liver tumor formation after treatment with the nitrosamines NDMA and NDEA [77]. Consistent with this finding, MGMT knockout mice revealed a higher frequency of GC → AT transition mutations in the liver and lung upon treatment with the tobacco-specific nitrosamine NNK [86]. This correlated very well with increased levels of O6-MeG and O6-pobG in both organs of MGMT-deficient mice after NNK treatment [86]. Moreover, O6-alkylating agents are also highly toxic. Thus, repair by MGMT almost completely prevents cell killing at lower concentrations. In line with this, MGMT confers resistance to methylating and chloroethylating anticancer drugs during anticancer therapy in humans [87,88,89]. At high concentrations, other repair pathways, e.g., base excision repair, may become saturated and the N-alkylations then mediate cytotoxicity. Mechanistically, MGMT acts by direct damage reversal. The alkyl group is transferred from the O6-group of guanine onto a cysteine residue (Cys145) in the active center of MGMT in a one-step reaction, thereby restoring guanine [63,64]. Alkylated MGMT is thereafter ubiquitinated and degraded by the proteasome [90] (Figure 7A). Therefore, the repair capacity of O6-alkylation damage is determined by the cellular MGMT level. However, as O6-MeG does not interfere with replication, it is not toxic by itself and replication is required for toxicity [91]. If not repaired by MGMT, O6-MeG mispairs with thymine (T) during the first round of replication [92] (Figure 7B). Within the second round of replication, the generated O6-MeG-T mispair is converted into an A→T transversion in one of the daughter cells, whereas the O6-MeG-T mispair is retained in the second. For toxicity, the O6-MeG-T mispair has to be processed by the mismatch repair (MMR) system [93]. However, MMR acts on the newly synthesized strand, where it removes the thymine, leaving the O6-MeG behind. As consequence, thymine is re-incorporated opposite O6-MeG at high frequency. Subsequent additional rounds of repair by MMR and reinsertion of T destabilizes the DNA in a futile repair cycle. Destabilization is caused by the large size of the DNA stretches removed by MMR [94]. The generated single-stranded DNA is quite unstable and can break, e.g., when encountering the replication machinery, leading to the formation of toxic DNA double-strand breaks (DSBs) [95]. We should note that it has been estimated that only ~1% of the endogenously formed SSBs can be converted into DSBs [96]. Concerning O6-MeG, it has been shown that treatment of A172 cells with 20 μM TMZ induces 14,000 O6-MeG adducts, which are converted into 32 DSBs determined as γH2AX foci, representing a conversion rate of 0.23% [97]. If not repaired by homologous recombination (HR) [98] in the post-treatment cell cycle [99], DSBs trigger downstream pathways, such as cell death and senescence (Figure 7B). As already mentioned, O6-MeG is not highly toxic, which is also observed in glioma cells exposed to TMZ. In this case, unrepaired O6-MeG and the subsequent DSBs trigger mostly senescence and little cell death [100,101]. O6-ClG adducts can also be repaired by MGMT. If not repaired, O6-ClG undergoes intramolecular rearrangement, forming the N1-O6-ethenoguanine adduct and subsequently a N1-guanine-N3-cytosine interstrand DNA crosslink [57]. If not removed, these interstrand crosslinks block DNA replication and lead to DSBs, with subsequent cell death induction [102]. Strong differences in MGMT activity and expression have been observed in humans [103]. The differential expression and activity of MGMT are most likely caused by multiple polymorphisms found in the MGMT gene and its promoter. However, an association between these polymorphisms and cancer risk has not been proven (for further reading, see [104]). Moreover, the MGMT expression can be regulated epigenetically and transcriptionally. In rodent cells, MGMT expression is regulated at the transcriptional level and its expression can be increased upon exposure of cells to alkylating agents. Thus, the basal MGMT expression depends on the transcription factors p53 and SP1 [105,106,107,108]. In this case, p53 has been shown to bind and sequester SP1 by preventing its binding to the MGMT promoter [109]. MGMT induction was also reported in rodent cells upon genotoxic stress such as UVC, ionizing radiation, and alkylating agents as well as corticosteroids [110,111,112,113,114,115] and in human HeLaS3 cells upon treatment with different activators of protein kinase C (PKC) such as phorbol-12-myristate-13-acetate (TPA) and 1,2-diacylglycerol (DAG) [115]. In human cells, transcriptional regulation of MGMT is also controlled by SP1 and upregulated by glucocorticoids, but not by genotoxic stress such as TMZ and radiation [116]. In humans, MGMT expression is regulated via epigenetic mechanisms. Thus, methylation of CpG islands localized between -249 and -103 as well as between +107 and +196 within the promoter induces transcriptional silencing [117,118,119,120,121]. As a consequence, the MGMT activity differs between different organs, being highest in the liver and lowest in the brain, myeloid tissue, and hematopoietic stem cells (for review, see [122]) and also between different individuals. Using peripheral blood mononuclear cells (PBMCs), high inter-individual but only moderate intra-individual variations were observed [123]. Concerning MGMT expression during development, it was shown that fetal liver has a lower MGMT activity than the corresponding adult tissue, whereas in most other paired tissues, the activities are in the same range [124]. Moreover, reduced MGMT expression was observed during cytokine-stimulated in vitro maturation of peripheral blood monocytes into dendritic cells [125]. Of note, MGMT promoter methylation with subsequent abrogated expression and activity is frequently observed in different tumors such as brain tumors [126]. Therefore, MGMT is a predictive marker for the effectiveness of methylating anticancer drugs, and clinical trials are underway analyzing the influence of MGMT inhibition on the therapeutic success (for further reading, see [127,128]). Apart from its epigenetic and transcriptional regulation, MGMT is influenced on the protein and activity level by natural compounds and drugs. On the one hand, antioxidants such as curcumin, cysteine prodrugs such as Oltipraz and N-acetylcystein, and coffee diterpenes were shown to increase MGMT levels and activity in cultured cells and in rat liver [129,130]. On the other hand, the disulfide compounds disulfiram and α-lipoic acid were identified as direct MGMT inhibitors that trigger MGMT depletion in cancer cells [131,132]. Furthermore, the nitric oxide donor S-nitroso-N-acetylpenicillamine was reported to downregulate MGMT expression in glioma [133], while the anti-estrogen tamoxifen was shown to promote MGMT degradation in colorectal cancer cells [134]. Changes in MGMT level and activity have a tremendous impact on the susceptibility of cells, tissues, and organs toward SN1 alkylating agents such as nitrosamines and anticancer drugs as pointed out above. Overall, MGMT represents the most important pathway in the repair of DNA alkylation damage at the O4 and O6 position of guanine, which is typically induced by nitrosamines. Apart from MGMT, a second direct reversal mechanism exists, which targets N-alkyl lesions and consists of the ALKBH demethylase family. These demethylases were first described in E. coli as part of the adaptive response [135]. During this response, upregulation of the MGMT-like repair protein Ada and the oxygenase AlkB was described. AlkB was shown to repair DNA alkylation damage such as N1-MeA and N3-MeC in an oxygen, alpha-ketoglutarate (α-KG), and Fe(II)-dependent reaction, by coupling oxidative decarboxylation of α-KG to hydroxylation of methylated DNA bases [136,137] (Figure 8A). N1-MeA and N3-MeC represent replication-blocking lesions. Thus, in AlkB-deficient cells, only ~12% of them are bypassed. Furthermore, N3-MeC is strongly mutagenic, inducing C → T and C → A mutations, whereas N1-MeA caused little mutagenicity [138]. Apart from N1-MeA and N3-MeC, AlkB also repairs N1-MeG and N3-MeT with lower efficiency [138]. Both lesions are also highly mutagenic. N1-MeG induces G→T, G→A, and G→C mutations, whereas N3-MeT induces T→A and T→C mutations. Whereas AlkB preferentially repairs N1-MeA and N3-MeC in single-stranded DNA (ssDNA), N1-MeG and N3-MeT are preferentially repaired in double-stranded DNA (dsDNA) [139]. Finally, exocyclic DNA adducts such as 1,N6-ethenoadenine (εA) and 3,N4-ethenocytosine (εC) are also substrates of AlkB [140,141,142]. In human cells, nine AlkB homologs (ALKBH1 to ALKBH8 and FTO) are known [143], but only ALKBH2 and ALKBH3 act as α-KG- and Fe(II)-dependent dioxygenases at N1-MeA and N3-MeC [144,145]. The ALKBH2 gene is localized at chromosome position 14q24.11, harbors 4 exons, contains a coding sequence of 786 bp, and encodes a protein consisting of 261 AS with a molecular weight of 33.1 kDa. ALKBH3 is located at position 11p11.2, harbors 10 exons, contains a coding sequence of 7861 bp, and encodes a protein consisting of 286 AS with a molecular weight of 37.9 kDa. As mentioned above, ALKBH2 and ALKBH3 have also been shown to repair εA [140,146], which is thought to occur via epoxide formation at the etheno bond followed by hydrolysis to a glycol derivative, giving rise to glyoxal and the restored adenine base (Figure 8B) [140]. ALKBH2 was also demonstrated to repair εC [147,148]. However, these etheno-adducts are not typical alkylation products, but rather produced by vinyl chloride or lipid peroxidation. Furthermore, N1-MeG and N3-MeT can be repaired, however at lower rates [138,149,150]. ALKBH2 and ALKBH3 are not only involved in DNA repair, but also in epigenetic regulation. Similar to the α-ketoglutarate (α-KG)/Fe(II)-dependent dioxygenase TET (ten-eleven translocation), ALKBH2 and ALKBH3 can oxidize 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC) [151]. Mouse embryonic fibroblasts (MEFs) derived from Alkbh2 and Alkbh3 knockout mice were ∼2-fold more sensitive to MMS-induced cytotoxicity as compared to wild-type cells [152]. While the spontaneous mutation frequency was not enhanced in both knockout MEFs, Alkbh2-deficient cells showed an increased mutant frequency after MMS treatment [152]. Another study showed that Alkbh2-deficient mice accumulate N1-MeA adducts in the genome [153]. This was not the case in Alkbh3-deficient mice, indicating that the reversal of N1-MeA is mainly mediated by ALKBH2 in mammalian cells. However, Alkbh2/Alkbh3 double-knockout mice are more susceptible than Alkbh2-deficient mice to alkylation-induced, inflammation-driven colon carcinogenesis and toxicity, strongly suggesting that both ALKBH2 and ALKBH3 are required for the repair of DNA alkylation damage [154]. This is supported by the finding that ALKBH2 and ALKBH3 show different substrate specificity. Thus, AKBH2 acts preferentially on dsDNA, whereas ALKBH3 acts on ssDNA [144]. In line with this, ALKBH2 but not ALKBH3 can interact with PCNA during replication [155,156]. In opposition to that, ALKBH3 interacts with the ssDNA-binding proteins recombinase A (RecA) and RAD51C [157]. This interaction is supposed to recruit ALKBH3 to alkylation lesions at the 3’-tailed DNA generated during homologous recombination. Novel findings indicate that the recruitment of ALKBH3 to the DNA is associated with transcriptional-coupled repair [158,159]. Thus, upon stalling of the RNA polymerase II, RNF113A ubiquitinates several transcription-associated proteins, leading to recruitment of the ASCC (activating signal co-integrator complex) via the ubiquitin-binding subunit ASCC2 [160]. In a subsequent step, the ASCC helicase subunit ASCC3 unwinds the DNA, thereby generating ssDNA, allowing ALKBH3 to target the alkylation lesion also in the context of dsDNA [161]. Importantly, deficiency in all ASCC components sensitizes cells to alkylating agents [158,159,160,161]. As mentioned above, ALKBH2/3 can revert N1-MeA and N3-MeC lesions. These lesions are not the major lesions induced by clinically used alkylating agents. Especially N1-MeA is thought to be non-cytotoxic because of the efficient repair by ALKBH proteins. Therefore, it is surprising that ALKBH2 has been reported to confer resistance against TMZ in human glioblastoma cells [162]. Moreover, a positive correlation between promoter methylation of ALKBH3 and cellular N3-MeC levels was shown in breast cancer cell lines, suggesting a role in alkylation-based chemotherapy [163]. In glioblastoma, the ALKBH-dependent repair might also be associated with the superior prognosis of IDH1 (Isocitrate dehydrogenase 1) mutant tumors. Mutant IDH1 can convert α-KG into the oncometabolite D-2-hydroxyglutarate, which can directly inhibit ALKBH-dependent repair [164] and sensitizes cells to alkylating agents such as MMS and MNNG [165] and even CCNU [166]. Taken together, repair by the ALKBH family plays only a role at minor DNA lesions such as N1-MeA, N3-MeC, N1-MeG, and N3-MeT. BER is a highly conserved pathway, which is responsible for the removal of N-methylated DNA adducts, such as N7-MeG and N3-MeA (Figure 9). Apart from that, BER is involved in the repair of oxidative DNA damage, e.g., 8-Oxoguanine, and DNA damage resulting from spontaneous deamination, such as the conversion of cytosine to uracil [167]. The N-methylated DNA lesions are detected by the enzyme AAG, which is also called N-methylpurine-DNA glycosylase (MPG) [168,169]. Further substrates of AAG include hypoxanthine (Hx), εA, and N1-MeG [170]. Both εA and N1-MeG are also substrates for ALKBH-mediated direct repair as mentioned above [140,150]. Whether larger N-alkyl adducts, such as N7-EtG, are removed by AAG has not been tested so far. However, it is known that N3-EtA and N7-EtG are prone to undergo spontaneous depurination, resulting in the formation of an apurinic site (AP site) [171]. This process also occurs with N7-MeG adducts, albeit with slower kinetics [172]. AAG null mouse embryonic stem (ES) cells are hypersensitive to alkylation-induced cell killing and chromosomal damage as shown after treatment with MMS and BCNU [173]. In line with that, an increased number of mutations was found in splenic lymphocytes of AAG-deficient mice exposed to MMS [174]. Furthermore, MEFs derived from AAG-/- mice are hypersensitive to the alkylating agent MeOSO2(CH2)2-lexitropsin [168]. This is a methylsulfonate ester covalently attached to N-methylpyrrolecarboxamide dipeptide, which displays DNA minor groove binding and, thus, predominantly induces N3-MeA [175]. Exposure of AAG-/- ES cells to MeOSO2(CH2)2-lexitropsin caused chromosomal aberrations, p53 accumulation, and apoptosis [176]. AAG-deficient ES cells were further reported to show higher initial N3-MeA levels upon MNU treatment and a strongly attenuated repair as compared to wild-type ES cells, highlighting the role of AAG-mediated repair [177]. On the other hand, overexpression of AAG was demonstrated to render cells hypersensitive to DNA alkylation damage by MMS, resulting in increased chromosomal instability [178]. This study provided the first evidence that imbalanced AAG-mediated BER is detrimental to cells. The hypersensitivity phenotype was also observed after mitochondrial overexpression of AAG and MMS treatment [179]. Overexpression of AAG was further reported to increase the sensitivity of cells toward TMZ [180], which is potentiated by the BER inhibitor methoxyamine and Poly(ADP-ribose) polymerase (PARP) inhibitors [181]. Increased colon cancer formation was observed in AAG-/- mice initiated with the NOC-related compound azoxymethane (AOM) in combination with the tumor promoter dextran sodium sulfate (DSS) that triggers colitis [82,182]. Interestingly, dose–response studies with AOM revealed a non-linear colon cancer formation in AAG-deficient mice with a threshold similar to that of wild-type animals, but with increased tumor formation at higher AOM doses [84]. A very recent study investigated the role of AAG in liver carcinogenesis induced by NDMA [5], which causes N7-MeG, N3-MeA, and O6-MeG as the most abundant lesions. As N7-MeG is of minor relevance due to its spontaneous depurination and O6-MeG is removed by MGMT, the observed effects were primarily attributed to the induced N3-MeA and its replication-blocking properties. The lack of AAG increased mutation rates in liver and promoted liver cancer formation, whereas AAG overexpression resulted in fewer mutations, but more liver tissue damage and lethality [5]. The latter phenotype is very likely due to the fast removal of N3-MeA in mice with AAG overexpression, which leads to an accumulation of SSBs as repair intermediates. These SSBs can then collide with the replication fork, thereby causing replication fork collapse and DSB formation [183]. These findings illustrate the importance of balanced AAG levels to prevent mutagenicity on the one hand and tissue damage on the other hand after exposure to alkylating agents such as nitrosamines. Intriguingly, AAG levels in PBMCs were reported to vary up to 10-fold between human individuals [184,185]. On the biochemical level, AAG is a monofunctional enzyme that harbors only a DNA glycosylase activity, whereas bifunctional DNA glycosylases such as OGG1 (8-oxoguanine DNA glycosylase 1) possess an additional AP lyase activity [167]. AAG catalyzes the hydrolysis of the N-glycosidic bond between the damaged DNA base (e.g., N7-MeG or N3-MeA) and the deoxyribose moiety [168,186] (Figure 9). This process may be stimulated by UV-DDB, as shown very recently for the AAG substrates εA and Hx in vitro [187]. The release of the damaged base generates an AP site. Subsequently, AP endonuclease (APE1) catalyzes the incision of the phosphodiester backbone at the AP site. This reaction generates a DNA nick with a 5′-deoxyribose-5-phosphate (5′-dRP) and a free 3′-OH group [188]. The 5`dRP moiety is eliminated by DNA polymerase ß (Pol ß) via its intrinsic lyase activity, which produces a 5′-phosphate terminus [189]. BER is then typically completed via the so-called “short-patch” pathway, in which Pol ß catalyzes the incorporation of a new nucleotide using the 3′-OH group as a primer [190]. Finally, the remaining nick is sealed by DNA ligase III in a complex with the scaffold protein X-ray repair cross-complementing protein 1 (XRCC1), which stabilizes DNA ligase III [191,192]. Furthermore, XRCC1 interacts with Pol ß, which was shown to be required for efficient BER [193]. It should be mentioned that DNA ligase I may substitute for DNA ligase III in short-patch BER, which occurs in an XRCC1-independent manner [194]. If the 5′-dRP moiety is chemically modified and is, therefore, no substrate for Pol ß, BER proceeds via the “long-patch” pathway. Long-patch BER is also the prevailing pathway during the S-phase of the cell cycle and at low ATP levels [167,195,196]. This pathway involves additional factors including Pol δ and ε, PCNA, flap endonuclease-1 (FEN1), and DNA ligase I [197]. First, Pol δ and ε catalyze strand displacement synthesis with a stretch of 2-13 nucleotides, thereby generating a so-called 5′-flap structure [198]. In the next step, this flap structure is removed by FEN1 [195] and the remaining nick is sealed by DNA ligase I [199]. Furthermore, the nuclear protein PARP-1 is an important factor that accelerates BER, although not being essential for this process [200,201]. PARP-1 is a DNA damage sensor and activated by DNA strand breaks, including SSB intermediates arising during BER [202,203]. Upon activation, PARP-1 catalyzes the synthesis of poly(ADP-ribose) (PAR) with consumption of NAD+ [204]. The formed biopolymer is covalently attached to PARP-1 itself and to other acceptor proteins, such as histones, chromatin remodelers, and DNA repair factors [205,206]. This results in direct or indirect modulation of the local chromatin structure, thereby facilitating the BER process [201]. Furthermore, PARP-1 recruits XRCC1 and other repair proteins through their PAR-binding motif, allowing for a non-covalent interaction with high affinity [207,208,209]. PAR binding to XRCC1 is indispensable for XRCC1 function in BER and SSB repair [210]. On the other hand, XRCC1 in its complex with Pol ß and DNA ligase III has recently been shown to curtail excessive PARP-1 activation at formed SSB intermediates, which can result in PARP-1-mediated cytotoxicity [211]. The relevance of PARP-1 for DNA alkylation damage was demonstrated in PARP-1 null mice and MEFs derived thereof, which are hypersensitive towards both MNU and MMS with increased levels of DNA damage [212,213,214]. This was also illustrated in colorectal cancer cells with PARP-1 deficiency, which display increased DNA strand break levels after treatment with TMZ [215]. Loss of PARP-1 in vivo caused increased levels of deletion mutations following exposure to N-nitrosobis(2-hydroxypropyl)amine (BHP) [216]. In line with this finding, PARP-1-deficient mice were shown to be susceptible to BHP-induced liver cancer [217]. Furthermore, PARP-1-/- mice exposed to the NOC-related compound AOM develop a higher number of colonic tumors and liver nodules [218]. Colon tumor induction upon AOM/DSS challenge was potentiated in MGMT and PARP-1 double knockout mice [215], demonstrating the important roles of these proteins in the protection against NOC-induced genomic instability and cancer. However, this study further revealed that PARP-1 promotes inflammation-driven tumor progression, highlighting the opposing functions of PARP-1 during tumorigenesis [215]. Overactivation of PARP-1 in response to severe DNA damage results in PARP-1-mediated cell death [185,219]. This is associated with NAD+ depletion and rapid ATP loss, which is caused by PARP-1-dependent suppression of glycolysis via PARylation of hexokinase I [220,221]. In line with this notion, genetic or pharmacological abrogation of PARP-1 protected against MMS-induced, AAG-dependent tissue damage and neuronal degeneration [185,219]. PARP-1 overactivation can directly trigger cell death via its product PAR, which is called PARthanatos [222]. This PARP-1-dependent cell death pathway is observed particularly in neuronal cells, e.g., following oxidative injury or glutamate excitotoxicity, and is characterized by a PAR-triggered release of apoptosis-inducing factor (AIF) from mitochondria [222,223,224,225]. AIF was shown to translocate to the nucleus, where it interacts with macrophage migration inhibitory factor, resulting in neuronal cell death [226]. More recently, PARP-1 was also demonstrated to play a central role in PARthanatos observed in cancer cell lines following treatment with the alkylating agents MNNG and MMS, which was dependent on the MGMT level [227]. Overall, these studies illustrate the close connection of the DNA repair proteins AAG, MGMT, and PARP-1 in genome protection and cell death. Taken together, BER is the main DNA repair pathway for DNA alkylation adducts formed at the N-position of nucleotides by both SN1 (e.g., nitrosamines and nitrosoureas) and SN2 alkylating agents (e.g., MMS or EMS). The mechanism of NER has been described in detail in multiple review articles [228,229,230] and is summarized below. NER can repair intrastrand-crosslinks such as UV-light-induced photolesions ((6–4) photoproducts (6-4PPs) and cyclobutene pyrimidine dimers (CPDs)) as well as bulky chemical adducts, induced mostly by natural compounds such as the mycotoxin aflatoxin and the main product of incomplete combustion of organic material, benzo(a)pyrene (B[a]P). Moreover, NER is involved in the repair of interstrand-crosslinks, which can be induced by anticancer agents such as chloronitrosoureas and cisplatin. The repair of interstrand-crosslinks is highly complex and utilizes, besides the NER pathway, homologous recombination, translesion polymerases, and the Fanconia Anemia components (for details on interstrand-crosslink repair, see [231,232]). Factors involved in NER belong to different complementation groups such as xeroderma pigmentosum (XP), Cockayne’s syndrome (CS), and trichothiodystrophy (TTD), which are associated hereditary disorders of the same name. NER can be divided in two distinct pathways. The global genomic repair (GGR) removes lesions from the non-transcribed regions of the genome and the non-transcribed strand of transcribed regions, whereas the transcription coupled repair (TCR) removes RNA-polymerase-blocking lesions from the transcribed strand of expressed genes (Figure 10). During GGR, lesions strongly distorting the DNA structure are recognized by the XPC–HR23B complex and thereafter verified by the RPA–XPA complex. Lesions that do not strongly distort the DNA helix are recognized by the complex DDB1–DDB2 (XPE). As an example, XPC–HR23B recognizes (6–4)PPs [233], whereas the DDB1–DDB2 complex recognizes CPDs [234]. After recognition of the lesion, the transcription factor TFIIH unwinds the DNA around the lesion [235]. TFIIH consists of two helicase subunits, XPB and XPD, and several accessory components (GTF2H1, GTF2H2, GTF2H3, GTF2H4, CDK7, CCNH, and MNAT1). After unwinding and formation of an open complex, the XPF–ERCC1 complex performs an incision 5′ of the DNA lesion. Thereafter, DNA synthesis by PCNA and the DNA polymerases (δ, ε, and/or κ) leads to the formation of a flap, which is removed by XPG-mediated 3′ incision and the nick is sealed by DNA ligase I, or the Ligase-III-XRCC1 complex [236]. However, if the damage load is too high, DNA synthesis is inhibited and the 3′ incision by XPG does not occur. In this case, XPG can be replaced by EXO1, which further excises the DNA, generating long single-stranded DNA stretches, activating the DNA damage response [237]. During TCR, the DNA lesion blocks the RNAPII, leading to assembly of CSA, CSB, and the transcription factor TFIIH at the site of the lesion. CSB uses its DNA translocase activity to remove the RNAPII complex from the lesion [238]. However, it is still unclear whether this is mediated by degradation or backtracking of the RNAPII. Nevertheless, after TFIIH is displaced from the lesion, the lesion becomes accessible and is excised by the exonucleases XPF–ERCC1 and XPG. Again, the DNA polymerases (δ, ε, and/or κ) together with DNA ligase I or the Ligase-III-XRCC1 complex restore the DNA. Based on the NER mechanism, it seems obvious that especially bulky adducts might be subject to repair. However, as mentioned above, even bulky adducts such as pyridyloxobutyl (pob) DNA adducts are preferentially repaired by MGMT. Thus, multiple studies have shown that MGMT can remove the pob group from O6-pobG [239,240,241,242]. However, despite the efficient repair of O6-pobdG by MGMT, the mutation rate following exposure to NNKOAc was not affected in CHO cells [241]. NNKOAc (4-(acetoxymethylnitrosamino)-1-(3-pyridyl)-1-butanol) is an activated form of NNAL, which is used experimentally because it forms exclusively pob adducts in the presence of cellular esterases. This study indicated that other large adducts, which are not repaired by MGMT and tolerated by translesion synthesis (TLS; see section below), may contribute to mutagenesis. Besides O6-pobG, tobacco-specific nitrosamines also generate other pyridylbutylating products and the corresponding pyridylhydroxybutylating (phb) products [240,243,244,245,246]. These are the O-adducts O2-[4-(3-pyridyl)-4-oxobut-1-yl]-cytosine (O2-pobC), O2-[4-(3-pyridyl)-4-oxobut-1-yl]-2′-deoxythymidine (O2-pobT), O4-[4-(3-pyridyl)-4-oxobut-1-yl]-thymidine (O4-pobT), O4-[4-(3-pyridyl)-4-hydroxylbut-1-yl]-thymidine (O4-phbT), O2-[4-(3-pyridyl)-4-hydroxylbut-1-yl]-thymidine (O2-phbT), and O6-[4-(3-pyridyl)-4-hydroxylbut-1-yl]-2’-deoxyguanosine (O6-phbG) and the N-adducts N7-pobG, N7-phbG, N6-(4-oxo-4-(3-pyridyl)-1-butyl)-2′-deoxyadenosine (N6-pobA), and N6-(4-hydroxy-4-(3-pyridyl)-1-butyl)-2′-deoxyadenosine (N6-phbA). Furthermore, pyridylbutylating and pyridylhydroxybutylating products on the phosphate backbone were detected [247,248]. Using an in vitro NER assay with pyridyloxobutylated plasmid DNA as a substrate, it was shown that nuclear extracts from human lymphoid cell lines deficient in XPA and XPC were less active at repairing pyridyloxobutyl adducts than extracts from normal cells. Moreover, the NER-deficient cells were hypersensitive to NNKOAc [249]. However, as, in the used plasmids, 7-pobG, O2-pobC, O2-pobT, and O6-pobG comprised 31.2%, 22.7%, 25.5%, and 20.6% of the total POB adducts, respectively, an association of these effects with a specific adduct was not possible. Additionally, LC-MS/MS-based measurement of these four pob-adducts was compared in MGMT-deficient, MGMT/BER-deficient, and MGMT/NER (XPD)-deficient CHO cells upon NNKOAc treatment [241]. The results showed a reduced repair of only O2-pobT in NER-deficient cells. The reduced repair was associated with increased AT→TA transversions, suggesting that these mutations are caused by O2-pobdT. The differential repair of pob-adducts may also be responsible for differences in the susceptibility to NNK-induced carcinogenesis in different organs of the mouse. Thus, binding of XPA and XPB to pob adducts was increased in liver extracts following NNK treatment, whereas it was decreased in lung extracts [250]. Similar results were also observed for pyridylhydroxybutylated adducts. A recent study showed that, among the different PHB adducts induced by NNALOAc (4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol), NER counteracts the formation of O2-phbdT and O4-phbdT, whereas MGMT repairs predominantly O6-phbdG and, with lesser efficiency, O4-phbdT [251]. NER also seems to be involved in the repair of smaller adducts. Initial results indicating a removal of O6-n-butyl-guanine (O6-BuG) by NER were obtained in bacteria [252,253]. Further experiments in DNA repair-deficient eukaryotic cells also showed that the repair of O6-BuG (induced by N-n-butyl-N-nitrosourea (BNU)) was not correlated with MGMT activity, but rather with NER efficiency [254,255,256]. In line with this, XPA-deficient cells showed a decreased bypass efficiency of branched-chain lesions (O6-iPr-dG and O6-iBu-dG, O6-sBu-dG) but not on their straight-chain counterparts (O6-nPr-dG and O6-nBu-dG) [257]. Using MGMT or NER-deficient cells, it was shown that O6-EtG was repaired predominantly by MGMT and more slowly by NER [258]. In opposition to that, O2-EtG and O4-EtG were neither repaired by MGMT nor NER. Moreover, MGMT and NER participate in the repair of O6-carboxymethylguanine (O6-CMeG) [259,260]. This DNA alkylation adduct was found to be associated with red meat intake [18] and is induced by azaserine as well as N-nitrosoglycine [261,262]. Interestingly, a crosstalk between NER and BER on alkylated DNA bases has been observed recently. Here, UV-DDB (DDB1/DDB2 complex) was shown to recognize ϵA and stimulated AAG activity [187]. Overall, in contrast to the involvement of MGMT, ALKBH proteins, and BER, only limited data suggest an important role for NER in the repair of and protection against DNA alkylation damage. With the exception of small methyl or ethyl adducts, larger and more complex O6-alkyl-dG lesions strongly block DNA replication. If not repaired, these lesions can cause DSBs and cell death. To avoid this, replication-blocking lesions can be tolerated by a specific bypass mechanism, the translesion synthesis (TLS) (Figure 11). As an example, knockdown of the TLS polymerase eta (Pol η) results in sensitivity to the chloroalkylating anticancer drugs fotemustine and CCNU in melanoma and glioblastoma cells, respectively [263], and knockout of Rev3L leads to hypersensitivity against TMZ and fotemustine [264]. Moreover, RAD18 is required for bypassing TMZ-induced O6MeG MMR intermediates in the S-phase [265]. TLS utilizes specified polymerases, namely Y-family polymerases (Pol η, Pol ι, Pol κ, and REV1), B-family polymerase (Pol ζ), and A-family polymerases (Pol θ and Pol ν), which can insert nucleotides opposite DNA lesions [266]. In this process, replicative polymerases such as polymerase delta (Pol δ) and polymerase epsilon (Pol ε) are blocked by the lesion. This leads to RAD18/UBE2A-dependent ubiquitination of PCNA at residue K164, and exchange of the replicative polymerase with one of the Y-family polymerases Pol η, Pol ι, or Pol κ. These polymerases can synthesize across the damaged DNA; however, due to their low processivity, they can insert only a few nucleotides [266]. In most cases, only one or two nucleotides are inserted and the Y-family polymerases are thereafter exchanged with the B-family polymerase zeta (Pol ζ, consisting of the subunits Rev3 and Rev7), which (together with Rev1) can extend the newly synthesized DNA. Pol θ can perform both insertion and extension. Finally, the TLS-polymerases are exchanged with the replicative polymerase and normal replication restarts [266]. However, the Y-family polymerases show a weak selectivity and exert no proofreading 3′→5′ exonuclease activity. Therefore, depending on the type of DNA lesion and TLS-polymerase, wrong nucleotides can be inserted and mutations may arise (Figure 11). Among all O6-alkyl-dG lesions, only O6-MeG and O6-EtG do not strongly block replication and can be bypassed by replicative polymerases [267]. However, it has been shown that also O6-MeG can slow down Pol α [268] and Pol δ [269] and that Pol η efficiently bypasses O6-MeG [269]. In this process, all polymerases can insert cytosine or thymine opposite to O6-MeG, with Pol η acting more accurately, i.e., inserting cytosine. Similar results are obtained for O6-EtG, which can slow down Pol α and Pol η, leading to error-prone synthesis by both polymerases [270]. In contrast, larger and more complex O6-alkyl-dG lesions strongly block replicative polymerases. Whereas O6-MeG did not impede DNA replication, the efficiency of the bypass decreased with the size of the alkyl group [257]. Moreover, the G→A mutation frequency also decreases with the adduct size. In both processes, branched-chain lesions (O6-iPr-dG and O6-iBu-dG, O6-sBu-dG) exerted stronger effects than their straight-chain counterparts (O6-nPr-dG and O6-nBu-dG). Concerning TLS, REV1 is involved in bypassing all of these lesions except O6-MeG. Whereas straight-chain lesions were mainly bypassed by Pol η and extension was performed by Pol ζ, the branched-chain lesions were predominantly bypassed by Pol ι and Pol κ. Another O6-alkyl-dG lesion bypassed by TLS is O6-CMeG. Thus, O6-CmeG can be bypassed by Pol η in an error-prone manner and by Pol κ, which performs an error-free insertion [271]. The subsequent extension step was carried out by Pol η, Pol κ, and Pol ζ. Data indicate that bulky pyridylbutylating products are also subject to TLS if not repaired by MGMT or NER. Thus, a strong blockage of replicative polymerases was also observed for O6-pobG, which can be bypassed by Pol η and induces G→A transitions [272]. Furthermore, using recombinant REV1, a one-base incorporation opposite O6-MeG and O6-BzG but not O6-pobG was observed [273]. In this case, REV1 preferentially incorporated dCTP opposite O6-MeG and O6-BzG. In opposition to O6-MeG, O2-MeT and O4-MeT have been shown to strongly block DNA replication. Moreover, O4-alkylthymidines have been shown to primarily induce T→C mutations [274], and the exonuclease-free Klenow fragment of E. coli DNA polymerase I was shown to incorporate both dATP and dTTP opposite O2-ethylthymidine [275]. Using different recombinant polymerases, TLS of O2/O4-alkyl-dT lesions was further analyzed. In the case of O2-alkyl-dT lesions, straight-chain lesions (O2-methylthymidine (O2-MeT), O2-ethylthymidine (O2-EtT), O2-propylthymidine (O2-PrT), O2-butylthymidine (O2-BuT)) and corresponding branched-chain lesions (O2-iPrT, O2-nBuT, O2-iBuT, O2-sBuT) were bypassed by Pol η and, to a lesser degree, Pol κ, but not by Pol ι [276]. Moreover, Pol η was more efficient in incorporating the correct nucleotide opposite O2-alkyldT lesions with a branched-chain alkyl group than the corresponding lesions with a straight-chain alkyl group [276]. In the case of O4-alkyldT, all straight-chain lesions besides O4-MeT and all branched-chain lesions were shown to moderately block DNA replication and to be bypassed by Pol η or Pol ζ, but not by Pol κ or Pol ι [277]. A replication block was also observed for O2-pobT and O4-pobT, which can be bypassed by Pol η and Pol ζ and predominantly induce T→A transversion and T→C transition [278]. Compared to O6-pobG, this block was more pronounced. As mentioned above, among methylated nucleotides, N1-MeA and N3-MeC are the most critical replication-blocking lesions. Therefore, it is obvious that these lesions are also subject to TLS. It has been shown that multiple TLS polymerases are involved in the bypass of N1-MeA [279,280]. (i) Pol ι inserts a nucleotide opposite N1-MeA and Pol θ performs the extension. (ii) Pol η mediates both insertion and extension. (iii) Pol λ inserts a nucleotide opposite N1-MeA and Pol ζ performs the extension. In all cases, TLS is predominantly error-free. Similar results were obtained for N3-MeA. Using 3-deaza-3-methyladenine (3-dMeA), a stable analog of N3-MeA, three different mechanisms were described [281]. (i) Pol ι inserts a nucleotide opposite N3-MeA and Pol κ extends synthesis. (ii) Pol θ can perform both insertion and extension. (iii) Pol ζ extends synthesis by an as-yet-unidentified polymerase. Using different recombinant polymerases, Choi and Guengerich analyzed TLS of oligonucleotides containing guanine differentially methylated at the N2-position (N2-methylguanine (N2-MeG), N2-ethylguanine (N2-EtG), N2,N2-dimethylguanine (N2,N2-diMeG), N2-isobutylguanine (N2-IbG), N2-benzylguanine (N2-BzG), N2-naphtylguanine (N2-NaphG), N2-9-anthracenylguanine (N2-AnthG), or N2-6-benzo[a]pyrenylguanine (N2-BPG)) [272,273,282]. The data indicate that Pol η effectively bypassed N2-MeG, N2-EtG N2-IbG, N2-BzG, and N2-NaphG, but not N2-AnthG and N2-BPG, whereas Pol δ only bypassed N2-MeG and N2-EtG [282]. Pol ι bypassed N2-MeG as well as N2-EtG, and partially bypassed N2-IbG, N2-BzG, and N2-NaphG, but was blocked by N2-AnthG and N2-BPG [283]. Misinsertion of T increased with the adduct size. Besides Pol η and Pol ι, Pol κ also mediated the bypass of N2-MeG, N2-EtG, N2,N2-diMeG, N2-IbG, N2-BzG, N2-NaphG, N2-AnthG, and N2-BPG. Overall, Pol κ is more efficient than Pol η or Pol ι in incorporating dCTP opposite large N2-G adducts (N2-AnthG and N2-BPG) [284]. Finally, REV1 was shown to perform one base incorporation opposite N2-MeG, N2-EtG, N2,N2-diMeG, N2-IbG, N2-BzG, N2-NaphG, N2-AnthG, and N2-BPG [273]. REV1 preferentially incorporated dCTP opposite G and all of the modified G adducts, with a relatively low misinsertion frequency [273]. Another N2-adduct is 1,N2-Etheno(ε)guanine (εG). Whereas Pol δ was completely blocked by this adduct, Pols ι and κ showed similar rates of incorporation of dTTP and dCTP in vitro. Pol η was most active, and showed the highest error frequency [285]. Finally, εA has also been shown to be subject to TLS. Thus, in human cells, Pol ι can insert a nucleotide opposite εA and Pol ζ performs the extension [286]. Alternatively, Pol θ can perform both insertion and extension. In both cases, TLS is predominantly error-free. Nitrosamines are genotoxic and carcinogenic compounds that occur not only in food, cosmetics, and tobacco smoke, but have also recently been found in drugs as by-products of the API synthesis or even as an API derivative. The DNA adduct formation pathways are well described for food-borne nitrosamines such as NDMA, the cosmetics-related nitrosamine NDELA, as well as tobacco-specific nitrosamines such as NNN and NNK. However, many other nitrosamines, particularly those found in drugs, are insufficiently studied so far with respect to DNA damage induction, or have hitherto even been unknown, thus leaving a data gap. More studies are required to understand the structure–genotoxicity relationship of more complex nitrosamines, such as nitrosamines with larger, branched alkyl residues and API-derived nitrosamines. The DNA repair pathways involved in the removal of small DNA alkylation adducts, such as N7-MeG, N3-MeA, or O6-MeG, are comprehensively understood and mainly involve BER as well as direct damage reversal by MGMT, while ALKBH-mediated repair plays a minor role. The repair of larger O6-alky adducts caused by tobacco-specific nitrosamines, e.g., O6-pobG, is also well studied, requiring both MGMT and the NER pathway. In contrast to that, the repair of other DNA alkylation adducts induced, for example, by NDEA or NDELA is hardly characterized so far. Another knowledge gap concerns the repair of adducts generated by complex nitrosamines, such as those found as drug impurities. It is, therefore, necessary to investigate relevant DNA repair pathways in much more detail for those compounds. Such experimental data are eagerly awaited and will be instrumental for in silico approaches to predict the genotoxic (and carcinogenic) potency of poorly characterized or hitherto unknown nitrosamines. Finally, this will be helpful for the risk assessment of nitrosamines to derive AIs for drugs.

PMC10003417

Zhiyi Wang,Xiaorong Yang,Siqi Zhou,Xishan Zhang,Yingzhi Zhu,Biao Chen,Xiuqin Huang,Xin Yang,Guohui Zhou,Tong Zhang

The Antigenic Membrane Protein (Amp) of Rice Orange Leaf Phytoplasma Suppresses Host Defenses and Is Involved in Pathogenicity

24-02-2023

phytoplasma,antigenic membrane protein,insect vector,pathogen-host interaction,HR response

Phytoplasmas are uncultivable, phloem-limited, phytopathogenic bacteria that represent a major threat to agriculture worldwide. Phytoplasma membrane proteins are in direct contact with hosts and presumably play a crucial role in phytoplasma spread within the plant as well as by the insect vector. Three highly abundant types of immunodominant membrane proteins (IDP) have been identified within the phytoplasmas: immunodominant membrane protein (Imp), immunodominant membrane protein A (IdpA), and antigenic membrane protein (Amp). Although recent results indicate that Amp is involved in host specificity by interacting with host proteins such as actin, little is known about the pathogenicity of IDP in plants. In this study, we identified an antigenic membrane protein (Amp) of rice orange leaf phytoplasma (ROLP), which interacts with the actin of its vector. In addition, we generated Amp-transgenic lines of rice and expressed Amp in tobacco leaves by the potato virus X (PVX) expression system. Our results showed that the Amp of ROLP can induce the accumulation of ROLP and PVX in rice and tobacco plants, respectively. Although several studies have reported interactions between major phytoplasma antigenic membrane protein (Amp) and insect vector proteins, this example demonstrates that Amp protein can not only interact with the actin protein of its insect vector but can also directly inhibit host defense responses to promote the infection. The function of ROLP Amp provides new insights into the phytoplasma-host interaction.

The Antigenic Membrane Protein (Amp) of Rice Orange Leaf Phytoplasma Suppresses Host Defenses and Is Involved in Pathogenicity Phytoplasmas are uncultivable, phloem-limited, phytopathogenic bacteria that represent a major threat to agriculture worldwide. Phytoplasma membrane proteins are in direct contact with hosts and presumably play a crucial role in phytoplasma spread within the plant as well as by the insect vector. Three highly abundant types of immunodominant membrane proteins (IDP) have been identified within the phytoplasmas: immunodominant membrane protein (Imp), immunodominant membrane protein A (IdpA), and antigenic membrane protein (Amp). Although recent results indicate that Amp is involved in host specificity by interacting with host proteins such as actin, little is known about the pathogenicity of IDP in plants. In this study, we identified an antigenic membrane protein (Amp) of rice orange leaf phytoplasma (ROLP), which interacts with the actin of its vector. In addition, we generated Amp-transgenic lines of rice and expressed Amp in tobacco leaves by the potato virus X (PVX) expression system. Our results showed that the Amp of ROLP can induce the accumulation of ROLP and PVX in rice and tobacco plants, respectively. Although several studies have reported interactions between major phytoplasma antigenic membrane protein (Amp) and insect vector proteins, this example demonstrates that Amp protein can not only interact with the actin protein of its insect vector but can also directly inhibit host defense responses to promote the infection. The function of ROLP Amp provides new insights into the phytoplasma-host interaction. Phytoplasmas are wall-less bacteria that are members of the class Mollicutes and cause important insect-transmitted diseases in a diverse variety of crops worldwide [1]. These pathogens are restricted to the plant phloem and cause growth disorders, leaf and floral alterations, and abnormal proliferation, sometimes leading to plant death [2]. Plant pathogens, including phytoplasmas, typically employ a range of effectors to modulate the defense and developmental processes of the host plant to benefit their infection [3]. As phytoplasmas inhabit the cytoplasm of the immature and mature sieve cells that constitute the phloem, these bacteria secrete effectors directly into the host cytoplasm of sieve cells via the Sec (secretion pathway)-dependent protein translocation pathway and target other plant cells by symplastic transport [2,3,4]. SecA-secreted proteins are candidate effectors and can be identified by the presence of a signal peptide [2,5] that is cleaved to yield a mature protein during export [6]. Since phytoplasmas are unculturable bacterial pathogens, it is difficult to characterize infection mechanisms at the molecular level [5]. Recently, a couple of phytoplasma effectors have been functionally characterized, and most of them play a crucial role in symptom development and host defense responses [4,7,8,9]. Phytoplasmas are transmitted by a narrow range of phloem-feeding insect species, mainly including leafhoppers, planthoppers, and psyllids, whereas their plant host range is usually broader [10]. Insect vector specificity plays a key role in the epidemiology of several vector-borne pathogens [11,12]. A class of membrane proteins in phytoplasmas have been identified as immunodominant membrane proteins (IDPs), which can directly affect vector insects and host plants and play a crucial role in plant and insect vector transmission [2,13]. Based on chromosomal gene organization and membrane anchor structure, IDPs derived from several phytoplasmas have been classified into three types: immunodominant membrane protein (Imp), immunodominant membrane protein A (IdpA), and antigenic membrane protein (Amp) [14,15]. Imp has a hydrophobic region at the N-terminus as the transmembrane domain and a hydrophilic region at the C-terminus outside the cell [7,16,17]. Imp of Candidatus Phytoplasma mali was reported to interact and colocalize with actin in plant cells, indicating its role in the movement of the phytoplasma in host plants [18]. IdpA proteins have an extracellular hydrophilic region in the middle and two hydrophobic regions as the transmembrane domains at both the C-terminus and N-terminus [19,20]. However, the interaction between IdpA and host factors has been less reported. Amp proteins also have a hydrophilic region in the middle, which is located outside the cell; a C-terminal hydrophobic region as the transmembrane domain, which anchors the Amp protein to the cell membrane of the phytoplasma; and an N-terminal hydrophobic signal peptide region which is cleaved during protein procession and translocation [6,21]. However, besides the majority of IDPs, there are several immunogenic membrane proteins present at the surfaces of the phytoplasmas, such as the variable membrane protein, A (VmpA) [22,23]. VmpA proteins possess a putative signal peptide and a potential C-terminal transmembrane domain, and are likely to be anchored in the phytoplasma membrane with a large N-terminal hydrophilic part exposed to the phytoplasma cell surface [24]. VmpA of flavescence dorée (FD) phytoplasma specifically interacted with Euscelidius variegatus insect cells in culture and promoted the retention of VmpA-coated beads to the midgut of E. variegatus [22]. To date, only a few biological functions of Amp have been studied. Amp of Candidatus Phytoplasma asteris, onion yellows strain (OY), has been reported to interact with the microfilament complexes of its vector leafhopper but not with non-vector leafhoppers [25]. Amp of Chrysanthemum yellow phytoplasma (CYP) was also found to interact with the ATP synthase and actin of its vector, but not with the homologous proteins of non-vectors [26,27]. These findings suggest that the complex interaction network between Amp and the proteins of insects determines the vector specificity of phytoplasmas. However, we know little about the role of Amp in regulating host plant gene expression. Rice orange leaf phytoplasma (ROLP), a member of the “Candidatus Phytoplasma asteris” 16SrI-B subgroup, is mainly transmitted by the leafhoppers, Recilia dorsalis and Nephotettix cinticeps [28]. Rice plants infected with ROLP show yellow and orange streaks appearing from the leaf apex, followed by leaf orange and leaf scorch and, sometimes, even the death of whole plants. Rice orange leaf disease (ROLD) caused by ROLP has been found in several east Asian countries, including Thailand, India, the Philippines, Malaysia, China, and other Asian countries [28,29,30]. Recently, the genome of ROLP has been sequenced, and it is predicted to encode 647 proteins [31]. A gene encoding the Imp of ROLP has been cloned and sequenced, and, using Imp-specific antibodies, researchers have clarified the infection characteristics of ROLP [31,32]. In this study, we used a combination of genome-wide bioinformatics and subsequent functional analyses of the ROLP-encoded proteins to describe an IDP in rice orange leaf phytoplasma, which has been identified as a potential Amp based on protein structure prediction. Protein interaction assay showed that it can interact with the actin protein of its vector leafhopper and confirmed this is an Amp protein. Although Amp was shown to bind to host proteins and could be essential for phytoplasma transmission by insect vectors, its function in plants has not yet been described. Because phytoplasmas propagate in both insect and plant hosts, the study of the function of phytoplasma proteins expressed in plants is required. In this study, we generated transgenic rice plants expressing the Amp, and the protein was also transiently expressed in Nicotiana benthamiana by the potato virus X (PVX) system. We found that ROLP Amp can enhance the proliferation of ROLP and PVX and cause severe symptoms in rice and N. benthamiana plants, respectively. In addition, we proved that ROLP Amp can inhibit defense responses in rice plants. These data first suggested that ROLP Amp is responsible for phytoplasma pathogenicity in plants and suppressing host defense responses. Phytoplasmas are wall-less pathogens; therefore, their membrane proteins can directly contact the cells of their host plant or vector. Among these proteins, Amp is thought to play an important role in the interaction between host plants and vector insects. To identify the Amp of ROLP, we screened the whole genome sequence of ROLP and compared it with the sequences of Amp genes from other phytoplasmas. Through the comparison, a protein encoded by ROLP (NCBI accession number: WP071345415.1) with high homology with Amp from other phytoplasmas was found. The phylogenetic tree further revealed that the Amp of ROLP shared 98.6% and 95.5% sequence similarity to the Amp of OY-M and CYP, respectively (Figure 1A). Furthermore, we predicted the structure of the ROLP Amp using Protter (http://wlab.ethz.ch/protter/ (accessed on 25 April 2022)). Results revealed that it has an N-terminal hydrophobic signal peptide region and a C-terminal hydrophobic region as the transmembrane domain, which is the typical Amp protein structure (Figure 1B and Figure S1). A previous study has suggested that the Amp may be involved in the specific recognition of phytoplasma by its vectors [25]. To investigate whether ROLP-encoded potential Amp has a similar function, we used a yeast two-hybrid (Y2H) assay to identify the interaction between ROLP-encoded Amp and its vector insect-encoded actin. The results showed that ROLP-encoded Amp interacts with the actin of its vectors, R. dorsalis and N. cincticeps (Figure 1C). The interaction between Amp and the actin of vectors was further confirmed by the GST pull-down assay (Figure 1D, E). The results showed that we have identified an Amp of ROLP. We first investigated ROLP accumulation in rice plants and R. dorsalis. Results showed that the accumulation of ROLP increased from 15 to 30 days post inoculation (dpi) and reduced at 45 dpi (Figure 2A) in rice plants. We then used the phytoplasma conserved NusA gene as internal controls, and the expression level of Amp was investigated. The results showed that the expression level of Amp was relatively higher at 15 dpi and 45 dpi, and lower at 30 dpi (Figure 2B). Similarly, we investigated ROLP accumulation in R. dorsalis. Results showed that the accumulation of ROLP gradually increased from 15 to 35 days post-acquisition (dpa) (Figure 2C), while the expression of Amp gradually decreased (Figure 2D). These results indicated that Amp expression was opposite to ROLP accumulation in the host and vector, suggesting that Amp plays an important role in promoting the infection of ROLP in the early stage. To investigate the role of Amp in ROLP infection, we generated Amp-overexpression (Amp-OE) transgenic rice plants, which constitutively express ROLP Amp without its signal peptide but fused with a 4 × Myc tag on its N-terminus (Figure S2). The Amp-OE transgenic lines showed a normal growth phenotype compared with wild type (WT) (Figure 3A), and the expression of Amp in the transgenic lines was confirmed by RT-qPCR (Figure 3B) and Western blot (Figure 3C). Then, we inoculated the WT and Amp-OE plants with ROLP by leafhopper inoculation. We found that, at four weeks post-inoculation (wpi), the Amp-OE lines exhibited much more severe disease symptoms (Figure 3D). The ROLP-infected Amp-OE plants had more orange leaves compared to the WT plants (Figure 3E). Consistent with the observed phenotypes, the accumulation of ROLP was higher in Amp-OE rice plants than in WT plants (Figure 3F). These results convincingly demonstrate that Amp plays a positive role in ROLP infection. Since Amp can promote the infection of ROLP in rice plants, we intended to test whether Amp was a functional effector involved in plant immunity. Hypersensitive response (HR) is commonly used as an indicator for effector-triggered immunity (ETI), and HR accompanies H2O2 accumulation [33]. We investigated whether the Amp could induce H2O2 accumulation in rice plants. DAB staining showed that the deep brown color was observed neither in the leaves of Amp-OE plants nor in WT plants (Figure 4A), which indicates that Amp does not induce H2O2 accumulation or trigger the immunity defense through HR. Then, we examined the expression of ETI and PAMP-triggered immunity (PTI)-related genes in Amp-OE and WT plants. Firstly, we performed qRT-PCR analysis of the pathogenesis-related gene OsNPR1. Results showed that the expression level of OsNPR1 was not significantly different between Amp-OE and WT plants (Figure 4B). Since many plant pathogens actively manipulate plant defense hormone pathways for pathogenesis, we next investigated the expression of several plant hormone biosynthesis and response-related genes. Results showed that the SA synthesis gene OsPAD4 [34,35] and the ethylene biosynthesis-related enzyme OsACS2 [36] were significantly reduced in Amp-OE plants than in WT plants (Figure 3C,D). Furthermore, we detected the expression of the SA-regulated genes OsPR1 and OsPR5 [37], and the ET downstream genes OsERF063 and OsERF073 [38]. Expression of all the genes was significantly reduced in Amp-OE plants compared to WT (Figure 3E–H). Together, these results suggest that ROLP-encoded Amp probably suppresses SA and ethylene-mediated disease resistance. To further verify the pathogenicity of Amp, we then used the PVX vector to express Amp in tobacco plants. The recombinant PVX-Amp was infiltrated into N. benthamiana leaves, and leaves infiltrated with PVX without an insert were used as controls. At 12 dpi, the leaves infiltrated with PVX-Amp showed obviously more curl and mosaic than the leaves infiltrated with PVX (Figure 4A,D). RT-PCR results indicated that Amp was expressed in the viral progeny (Figure 4B). qRT-PCR results showed that the PVX CP transcript level was significantly higher in PVX-Amp-infected plants than in their PVX-infected counterparts (Figure 4C). To investigate whether the increased accumulation of PVX-CP is accompanied by hypersensitive responses, the accumulation of H2O2 was examined in a DAB staining assay. The upper, non-infiltrated leaves of PVX- and PVX-Amp-infected plants at 12 dpi were analyzed. The PVX-Amp-infected leaves accumulated higher amounts of H2O2 than the PVX-infected leaves (Figure 4D). Cell death was also examined by trypan blue staining. The leaves were only lightly stained, with no significant differences between the PVX- and PVX-Amp-infected leaves, indicating that Amp does not induce cell death (Figure 4D). These data suggest that ROLP-encoded Amp can promote the infection of other pathogens and increase the H2O2 content in tobacco plants. Arthropod-borne pathogens are transmitted by specific arthropod vectors (mainly insects). As an important type of arthropod-borne pathogen, phytoplasma has shown highly specific interactions with its insect vector. Phytoplasma-encoded Amp is anchored on the membrane of phytoplasma cells and is in direct contact with hosts or vector factors, which are presumably involved in determining vector specificity during the penetration of phytoplasma across gut and salivary gland barriers in the vector [25,27]. For instance, OY phytoplasma-encoded Amp formed a complex with insect microfilaments, including actin, the heavy chain and light chain of myosin, from its vector leafhopper species but not from non-vector species [25]. Similar results were obtained from chrysanthemum yellow (CY) phytoplasma, the Amp of which selectively interacted with actin and the ATP synthase of its vector leafhopper species but not with that of non-vector species [27]. In this study, we identified an Amp of ROLP, and through protein–protein interaction assays, we confirmed the interaction between the ROLP-encoded Amp and the actin from the leafhopper vectors, R. dorsalis and N. cincticeps, suggesting the interaction might be involved in the vector specificity of ROLP. Further experiments are required to verify the interaction of ROLP Amp with the actin from non-vector and to confirm whether Amp determines the vector specificity of ROLP. The genome sequence of ROLP has significantly contributed to our understanding of ROLP biology. Studies have shown that differential regulation of phytoplasma gene expression plays an important role in adaptation to various environments encountered within its hosts [39]. The expression levels of OY-M PAM064 and PAM695 genes in OY-infected leafhoppers were significantly higher than those in OY-infected plants [40]. In addition, the PME2 (Protein in Malus Expressed 2) of apple cluster phytoplasma (Candidatus Phytoplasma mali, Ca.P. mali) is expressed only in the roots and leaves of susceptible apple trees [41]. Moreover, the expression level of AY-WB Amp was 3-fold higher in plants than in vector insects [39]. In this study, we investigated the accumulation of Amp during ROLP infection in R. dorsalis and rice plants. Results showed that the expression level of Amp was relatively higher at 15 dpi and 45 dpi and lower at 30 dpi. Since Amp is a membrane protein, we assumed that 15 dpi is an early stage of ROLP infection and that a higher expression level of Amp can help ROLP establish a faster infection, whereas at 30 dpi, ROLP mainly replicates and accumulates in the plant cells, so it needs to secrete many more other effectors to conquer plant immunity. At 45 dpi, ROLP has a higher accumulation in infected plants; this is the time for ROLP to transmit, so it secretes more Amp proteins to help ROLP establish infection in insects that are feeding on the sap of infected plants. Although Amp has been shown to bind to insect Actin [25,27], this binding has not been reported to exhibit any negative effect on the life cycle of the vector insect. Therefore, the results of our study support the hypothesis that binding of an immunodominant protein to vector Actin could be beneficial for phytoplasma survival (probably for colonization, infection, and transmission). Amp has played an important role in the evolution of phytoplasmas, and there is a strong positive selection of Amp in phytoplasmas [14]. Generally, it is believed that pathogen genes that are subject to positive selection play important functions in host immunity and defense responses [3]. In this study, we generated ROLP-encoded Amp transgenic rice plants. Through ROLP infection, we found that the Amp transgenic plants showed more severe symptoms and accumulated higher ROLP titers than WT plants, indicating that Amp may promote ROLP infection in rice plants. The effectors of pathogenic microbes often interfere with plant defense responses such as pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) [42]. Three well-studied phytoplasma effectors (SAP11, SAP54, and TENGU) have been shown to function mainly in manipulating plant development and/or suppressing plant defense responses against their insect vectors. SAP05 mediates the degradation of multiple developmental regulators through a ubiquitination-independent mechanism, leading to delayed plant aging and simultaneous proliferation of vegetative tissue and shoots [9]. SAP11, secreted by aster yellows phytoplasma strain witches’ broom (AY-WB), can not only induce smaller rosettes, severely crinkled leaves, crinkled siliques, and witches’ broom phenotypes in plants but can also down-regulate the expression of LOX2 and JA synthesis in SAP11-transgenic plants [43]. TENGU, another witches’ broom-inducing effector belonging to OY-M, can suppress auxin signaling and biosynthesis pathways in Arabidopsis [29]. Another AY-WB effector, SAP54, transforms the flowers of Arabidopsis into leaf-like vegetative tissues, and plants with a SAP54-induced phenotype are more attractive for colonization by phytoplasma leafhopper vectors [44]. However, this phenomenon was not observed in N. benthamiana plants expressing the Imp of Candidatus Phytoplasma mali [18], and such IDP pathogenicity has not been investigated yet. In this study, we also found that overexpressing Amp in rice plants did not exert any remarkable change in phenotype compared with the WT plant, suggesting that immunodominant membrane proteins are not involved in growth deformations. To further investigate whether Amp regulates defense responses in plants, we conducted a PVX-based expression assay to determine the pathogenicity of Amp. Our data suggested that ROLP-Amp can enhance PVX pathogenicity by increasing PVX RNA accumulation (Figure 5). We also found that PVX-Amp-infected plants can induce hypersensitive responses, whereas the Amp-OE rice plants do not trigger the immunity defense through HR (Figure 4A). Since a higher accumulation of viruses is always accompanied by hypersensitive responses [45], the HR induced in PVX-Amp is probably due to the higher accumulation of PVX and not the Amp itself. Rice plants cv. Nipponbare were grown inside a greenhouse maintained at 28–32 °C and 60 ± 5% relative humidity with a 12 h photoperiod. Transgenic rice plants (cv. Nipponbare background) were generated at the Biogle Genome Editing Center, Jiangsu, China. N. benthamiana were grown in environmental growth chambers maintained at 23 °C with a 16 h photoperiod, 6000 lux of light intensity, and 65% relative humidity. ROLP-infected rice plants and leafhopper, R. dorsalis, were maintained in our laboratory. To obtain ROLP-infected leafhoppers, ~30 R. dorsalis, 3–4 larval nymph stage, were transferred to ROLP-infected rice plants for 35 days. The R. dorsalis adults were used for experiments or transferred to rice seedlings (~30 seedlings) to generate new batches of ROLP-infected plants and leafhoppers. Briefly, two-week-old seedlings were exposed to the ROLP-carrying leafhoppers (2–3 insects per plant for 14 days). Fourteen days after inoculation, the insects were removed, and the plants were kept in the same conditions. For the detection of ROLP in infected rice plants and leafhoppers, total DNA was extracted from the leaves of rice plants or leafhoppers by the cetyl trimethylammonium bromide (CTAB) method [46]. A PCR assay was performed to detect the FisH1 gene to verify ROLP-infected rice plants and insects according to our previous description [47]. The full-length ORF of Amp was cloned into the pENTR/D-TOPO vector (ThermoFisher Scientific, Waltham, MA, USA). The cloned sequences were then transferred into the pBA35S-FlagMyc4 vector (under the control of the cauliflower mosaic virus 35S promoter) [48] using a Gateway LR reaction kit (ThermoFisher Scientific, Waltham, MA, USA) as instructed. The resulting plasmids were transformed into Agrobacterium tumefaciens strain GV3101. The bacterial cell suspension was used for the generation of Amp transgenic rice plants (cv. Nipponbare background) as described previously [49]. The T0 transgenic plants were screened by quantitative real-time PCR, and the primers are given in Supplemental Table S1. For the quantification of ROLP accumulation in insects and rice plants, total DNA was extracted using the CTAB method. Three independent samples of ROLP-infected rice plants were tested using qPCR. Since gene expression varies widely among individual insects, fourteen independent samples of ROLP-infected insects were tested using qPCR. The phytoplasma-conserved NusA gene was detected as a target [50], and OsEF1α and Actin in rice and insects, respectively, were used as internal controls. For detection of Amp expression level in ROLP-infected plants and insects, three independent ROLP-infected rice plants or six independent ROLP-infected insects were randomly chosen for qRT-PCR. To verify that Amp-OE#4 and #7 were overexpressed, three independent plants from each line were selected and proceeded for qRT-PCR. For the determination of the expression level of defense-related genes, four independent rice plants from each line were randomly chosen for qRT-PCR. For comparison with the PVX accumulation level, three PVX and PVX-Amp-infected plants were randomly chosen for qRT-PCR. The total RNA of all the samples was extracted from the leaves of plants or insects with Total RNA Extraction Reagent (Vazyme, Nanjing, China) according to the manufacturer’s instructions. cDNA was synthesized using the isolated total RNA, an oligo (dT) primer, and a reverse transcriptase (Takara, Dalian, China). Quantitative PCR reactions were carried out on a CFX96 Touch real-time PCR detection system (Bio-Rad, Hercules, CA, USA) using the SYBR Premix Ex TaqTM II kit (Takara, Dalian, China). Briefly, 2 µL of template cDNA, 5× SYBR Green, and 10 mM of each primer were mixed together in a total volume of 10 µL, and PCR reactions were run as follows: 10 min at 96 °C, followed by 40 cycles of 60 s at 95 °C, 60 s at 60 °C, and 30 s at 72 °C; 10 min at 72 °C. The NusA gene of ROLP, OsEF1α of rice, and NbPP2A of tobacco were used as internal controls, and the relative expression levels were calculated by the 2−ΔΔC(t) method [51]. Three technical replicates were run for each biological replicate. All the experiments were performed at least three times with similar results, and a representative group of results is displayed. Primers used for qRT–PCR are listed in Supplemental Table S1. The full-length Amp and Actin of different insect species were amplified by PCR with the primers listed in Supplemental Table S1. The amplified products were inserted into the yeast expression vectors, pGADT7 and pGBKT7, to generate the constructs for the Y2H assay. To examine protein–protein interactions, different combinations of pGBK and pGAD plasmids were transformed into yeast strain Y2HGold cells (Weidi, Shanghai, China). The transformants were cultivated on the SD/-Leu/-Trp (SD-L-T) medium and then on the SD/-Leu/-Trp-His-Ade (SD-L-T-H-A) selection medium to determine the protein-protein interaction. Yeast cells were photographed 3 days post-incubation at 30 °C. All the experiments were repeated three times with similar results. The pull-down assay was performed as previously described with minor modifications [52]. The full-length Amp was amplified and inserted into the pMBP28 vector, and the actins of R. dorsalis and N. cincticeps were amplified and inserted into the pGEX4T1 vector. The recombinant GST- and MBP-tagged proteins were purified using glutathione Sepharose 4B beads (GE Healthcare, Uppsala, Sweden) and amylose resin (New England Biolabs, Ipswich, MA, USA) as instructed by the manufacturer. Then, 4 μg purified MBP or MBP-Amp was incubated with 2 μg purified GST-actin in 200 µL PBS buffer (10 mM Na2HPO4, 2 mM NaH2PO4, 135 mM NaCl, 4.7 mM KCl, pH 7.0), and then incubated with 20 μL glutathione Sepharose 4B beads at 4 °C for 2 h. After five washes with reaction buffer, the resin-bound proteins were boiled in SDS buffer for Western blotting analysis with anti-GST and anti-MBP antibodies. Total protein was extracted from 0.2 g leaf samples with 200 µL extraction buffer (50 mM Tris-HCl (pH 6.8), 9M urea, 4.5% SDS, and 7.5% β-mercaptoethanol). Samples were centrifuged at 12,000× g for 2 min, and the upper liquid phase of each sample was analyzed via electrophoresis on SDS-PAGE gels. The separated proteins were transferred to PVDF membranes (Millipore, Billerica, MA, USA) and detected using antibodies against MBP, GST, Myc, or tubulin (Abmart, Shanghai, China). The detection signal was then visualized using the Immobilon Western Chemiluminescent HRP Substrate as instructed (Millipore, Bedford, MA, USA) and visualized on ChemiDoc XRS+ (Bio-Rad, Hercules, CA, USA). The bands of tubulin were used as the loading control. The full-length ORF of Amp was inserted into the pGR107 vector [53] to generate PVX-Amp, which was transformed into A. tumefaciens strain GV3101. Cultures of transformed GV3101 cells were grown in LB medium containing rifampicin (50 mg/mL) and kanamycin (50 mg/mL) at 28 °C for 48 h. Transformants were identified based on colony PCR. The cells of a GV3101 culture for PVX or PVX-Amp were resuspended in infiltration medium (5 mg/mL glucose, 10 mM MES, 10 mM MgCl2, and 200 mM acetosyringone) for an optical density at 600 nm (OD600) of 0.6. The Agrobacterium cultures carrying PVX-Amp and PVX infiltrated seven 3-week-old N. benthamiana plants, respectively. Total RNA was extracted 7 d after inoculation, and viral RNAs were detected by primers targeting the coat protein (CP) of PVX. For the DAB and Trypan blue staining experiments, leaves were collected from each of the seven plants infected with PVX or PVX-Amp. To detect the accumulation of H2O2, the leaves were stained with 3,3′-diaminobenzidine (DAB) solution. Leaves were collected at 7 d post-inoculation (dpi) and infiltrated in 1 mg/mL DAB solution (pH 5.7) for 8 h in darkness. The leaves were discolored by boiling 95% ethanol for 10 min and then analyzed. To detect cell death, the leaves were boiled for 3 min in Trypan blue solution (1 mg/mL Trypan blue in water: glycerol:lactic acid:phenol, 1:1:1:1 v/v). Then, the leaves were infiltrated overnight in a chloral hydrate solution (250 g chloral hydrate dissolved in 100 mL water). All the stained leaves were observed with a Nikon microscope (A1 HD-25). Differences were analyzed using a two-way analysis of variance (ANOVA) with Tukey’s honest significant difference (HSD) test for multiple comparisons or a one-way t-test for comparisons between two means. A p-value ≤ 0.05 was considered statistically significant. All analyses were performed using SPSS version 2.0 (SPSS, Inc. Chicago, IL, USA). In summary, we identified the Amp encoded by ROLP and clarified its function as a pathogenicity-related protein. Additionally, the molecular mechanisms of Amp induction or the suppression of host defense responses need to be thoroughly investigated in the future. The data presented here may be useful for elucidating the ROLP infection cycle and may be relevant for the development of improved methods for the prevention and control of this pathogen.

PMC10003427

Beatriz Gutiérrez-Miranda,Isabel Gallardo,Eleni Melliou,Isabel Cabero,Yolanda Álvarez,Marta Hernández,Prokopios Magiatis,Marita Hernández,María Luisa Nieto

Treatment with the Olive Secoiridoid Oleacein Protects against the Intestinal Alterations Associated with EAE

04-03-2023

multiple sclerosis,EAE,oleacein,intestinal permeability,inflammation

Multiple sclerosis (MS) is a CNS inflammatory demyelinating disease. Recent investigations highlight the gut-brain axis as a communication network with crucial implications in neurological diseases. Thus, disrupted intestinal integrity allows the translocation of luminal molecules into systemic circulation, promoting systemic/brain immune-inflammatory responses. In both, MS and its preclinical model, the experimental autoimmune encephalomyelitis (EAE) gastrointestinal symptoms including “leaky gut” have been reported. Oleacein (OLE), a phenolic compound from extra virgin olive oil or olive leaves, harbors a wide range of therapeutic properties. Previously, we showed OLE effectiveness preventing motor defects and inflammatory damage of CNS tissues on EAE mice. The current studies examine its potential protective effects on intestinal barrier dysfunction using MOG35-55-induced EAE in C57BL/6 mice. OLE decreased EAE-induced inflammation and oxidative stress in the intestine, preventing tissue injury and permeability alterations. OLE protected from EAE-induced superoxide anion and accumulation of protein and lipid oxidation products in colon, also enhancing its antioxidant capacity. These effects were accompanied by reduced colonic IL-1β and TNFα levels in OLE-treated EAE mice, whereas the immunoregulatory cytokines IL-25 and IL-33 remained unchanged. Moreover, OLE protected the mucin-containing goblet cells in colon and the serum levels of iFABP and sCD14, markers that reflect loss of intestinal epithelial barrier integrity and low-grade systemic inflammation, were significantly reduced. These effects on intestinal permeability did not draw significant differences on the abundance and diversity of gut microbiota. However, OLE induced an EAE-independent raise in the abundance of Akkermansiaceae family. Consistently, using Caco-2 cells as an in vitro model, we confirmed that OLE protected against intestinal barrier dysfunction induced by harmful mediators present in both EAE and MS. This study proves that the protective effect of OLE in EAE also involves normalizing the gut alterations associated to the disease.

Treatment with the Olive Secoiridoid Oleacein Protects against the Intestinal Alterations Associated with EAE Multiple sclerosis (MS) is a CNS inflammatory demyelinating disease. Recent investigations highlight the gut-brain axis as a communication network with crucial implications in neurological diseases. Thus, disrupted intestinal integrity allows the translocation of luminal molecules into systemic circulation, promoting systemic/brain immune-inflammatory responses. In both, MS and its preclinical model, the experimental autoimmune encephalomyelitis (EAE) gastrointestinal symptoms including “leaky gut” have been reported. Oleacein (OLE), a phenolic compound from extra virgin olive oil or olive leaves, harbors a wide range of therapeutic properties. Previously, we showed OLE effectiveness preventing motor defects and inflammatory damage of CNS tissues on EAE mice. The current studies examine its potential protective effects on intestinal barrier dysfunction using MOG35-55-induced EAE in C57BL/6 mice. OLE decreased EAE-induced inflammation and oxidative stress in the intestine, preventing tissue injury and permeability alterations. OLE protected from EAE-induced superoxide anion and accumulation of protein and lipid oxidation products in colon, also enhancing its antioxidant capacity. These effects were accompanied by reduced colonic IL-1β and TNFα levels in OLE-treated EAE mice, whereas the immunoregulatory cytokines IL-25 and IL-33 remained unchanged. Moreover, OLE protected the mucin-containing goblet cells in colon and the serum levels of iFABP and sCD14, markers that reflect loss of intestinal epithelial barrier integrity and low-grade systemic inflammation, were significantly reduced. These effects on intestinal permeability did not draw significant differences on the abundance and diversity of gut microbiota. However, OLE induced an EAE-independent raise in the abundance of Akkermansiaceae family. Consistently, using Caco-2 cells as an in vitro model, we confirmed that OLE protected against intestinal barrier dysfunction induced by harmful mediators present in both EAE and MS. This study proves that the protective effect of OLE in EAE also involves normalizing the gut alterations associated to the disease. Multiple sclerosis (MS) is an immune-mediated, chronic neurodegenerative disease characterized by a persistent inflammatory and oxidative state that leads to axon demyelination and neuroaxonal degeneration [1,2]. The etiology is not well understood, but arises from a complex interplay between genetics and environmental factors [3]. The heterogeneity of the MS symptoms includes muscle weakness, spasticity, paralysis, blurred vision, and gastrointestinal problems, among others [4]. Bladder and bowel symptoms have been rated as the third most important after spasticity and incoordination. Alterations of gut-derived products, intestinal permeability, and enteric nervous system functions have been described in MS patients, and the gut-brain axis is being considered as a key player in MS pathogenesis [5,6]. Thus, intestinal mucosal barrier breakdown will allow microorganisms, pathogens, and potentially large antigenic molecules to pass through; it will destroy the immune homeostasis and, subsequently, trigger systemic inflammatory response, and participate in the development of autoimmune diseases in the final [7]. At present, no cure for MS is known, and current therapies are directed towards modulation of the immune response to reduce the severity and relapses of the disease. However, given the increasing evidence that support oxidative stress as an important component in the pathogenesis of MS, other treatment regimens, including antioxidants, might confer beneficial effects [2,8]. Furthermore, looking for non-canonical targets may guide the field towards future therapeutic approaches in MS. Experimental autoimmune encephalomyelitis (EAE) induced with a myelin oligodendrocyte glycoprotein (MOG) peptide is one of the most popular experimental models used for studying MS [9]. The MOG35-55-induced EAE in rodents closely resembles the clinical and immunopathological features of the human disease, including some intestinal alterations [10,11]. Oleacein (OLE) is one of the main secoiridoids of extra virgin olive oil (EVOO). OLE is released during the mechanical extraction process by the action of the olive fruit enzymes acting on precursor molecules such as oleuropein. Many of the beneficial health properties of EVOO have been attributed to a high content of monounsaturated acids, as well as to other minor components, among which phenolic alcohols and secoiridoid derivatives such as the OLE are found [12,13]. Although OLE does not exist in the intact olive leaves, it can be very easily produced from them, as has recently been shown [14]. OLE can be produced during the extraction procedure by the combined action of oleuropein glucosidase and demethylase, which are present in the leaves, on oleuropein, which is the most abundant secoiridoid in the olive leaves. The production of OLE from olive leaves using a large-scale and affordable method of selective extraction has offered easy access to this molecule for further investigation and also for development as an ingredient of food supplements or potential new drugs. OLE has demonstrated to possess antioxidant, anti-inflammatory, anti-proliferative and immunomodulatory bioactivities that are partially responsible for the beneficial effects of EVOO on human health [13,14,15,16,17,18]. Moreover, in vivo administration of OLE did not exhibit signs of toxicity [19]. The wide spectrum of its biological activities includes cardioprotective, antimicrobial, neuroprotective, and anti-cancer effects [15,20,21]. In a recent preclinical study, we observed that, by targeting immune–inflammatory and oxidative responses, OLE improved clinical signs and motor deficits of EAE mice, suggesting a protective role of this secoiridoid against this neurodegenerative disorder. However, the effect of OLE on the intestinal alterations linked to MS/EAE has not been addressed. In this study, we focused on EAE-intestinal dysfunction and we unraveled the impact of OLE treatment on gut barrier protection. In previous research, we demonstrated that OLE administration to EAE mice protected CNS tissues from inflammatory damage and was sufficient to ameliorate the classical EAE neurological signs. Herein, we addressed the OLE effect on EAE-associated gut intestinal dysfunction. The study was performed on day 24 after EAE induction (acute phase of the disease): Mice of the untreated-EAE group showed one-sided hind limb paralyses (clinical score 2), at minimum, and mice in the OLE-treated EAE group showed an inability to curl the distal end of the tail (clinical score 0.5) (Figure 1B and Figure S1). EAE disease severity was quantified using a standard numerical scale as described in Methods [22]. Although OLE treatment significantly reduced the disease severity in EAE mice, no major changes were found on disease incidence (Untreated EAE, 10/10; OLE-treated EAE mice, 9/10). Firstly, we performed a macroscopic inspection of the intestine. We did not observe significant differences in the ratio colon length/body weight among mice of the different experimental groups (Figure 1C,D). Besides, cecal examination showed that the full cecal weight, as well as the ratio full cecum weight/body weight (cecal index), were higher in EAE mice, and OLE treatment prevented this increase (Figure 1E,F); this change may warrant further investigation. Next, to investigate the impact of OLE treatment on intestinal barrier function on EAE mice, we evaluated ex vivo the intestinal permeability to 40 kDa FITC-labelled dextran in a non-everted gut sac model using two different segments of intestine: colon and ileum (Figure 2A,B). Colonic and ileal sacs from EAE mice tissues exhibited an increased paracellular permeability when compared to those of the control group (p < 0.001). However, intestinal sacs from OLE-treated EAE mice displayed a reduced FD40 passage demonstrating that OLE was able to preserve the gut barrier function. In addition, we evaluated surrogate serological markers of impaired intestinal permeability and microbial translocation; the intestinal fatty acid-binding protein (iFABP) and sCD14. As shown in Figure 2C, EAE induction significantly increased the serum levels of iFABP and sCD14 compared with healthy control mice (p < 0.001), whereas OLE treatment significantly attenuated this response (p < 0.01). Next, AB-PAS staining was conducted to determine changes in mucins content in the colon of mice of the different experimental groups. As shown in Figure 3A, OLE treatment prevented the significant decrease in the overall AB/PAS staining detected in colon sections from untreated-EAE mice. Although we observed a significant reduction in the expression of both acidic and neutral mucins in colon of EAE mice, the ratio acidic/neutral mucin species between the healthy control and EAE mice kept constant at 2:1. The expression levels of galectin-3 (Gal-3), a protein linked to mucin expression, were decreased in colon from EAE mice, compared with healthy control mice (p < 0.01), whereas treatment with OLE prevented this reduction, keeping values similar to those of the control group (Figure 3B). In contrast, higher Gal-3 levels were found in the serum of EAE mice when compared with the control group, and OLE administration protected them from this rise (Figure 3C). In addition, the expression levels of the glial-derived neurotrophic factor (GDNF), a novel regulator of the intestinal epithelial barrier function, was diminished in both colon and serum of EAE mice, and OLE treatment abolished this reduction (Figure 3B,C) [23]. It is worth noting that OLE administration to the control group did not significantly affect any of the above studied parameters. We also examined parameters of intestinal inflammation in the different experimental groups. We found that OLE significantly reduced the levels of the pro-inflammatory cytokines TNFα and IL-1β, which were observed up-regulated in colon tissue from EAE mice (Figure 4). Additionally, the expression levels of the two potent type-2 inducing cytokines IL-33 and IL-25 were down-regulated in colon from EAE mice, compared to healthy control mice; and OLE treatment protected against this decrease (Figure 4). To measure intestinal stress injuries, superoxide anion (O2·−) accumulation was measured in situ using the DHE stain (Figure 5A). We observed elevated red fluorescence in colon sections from EAE mice compared to control mice (p < 0.001), which indicated excess superoxide levels. In contrast, OLE treatment prevented these increases (p < 0.001). Other parameters which indirectly reflect the oxidative extent of cells/tissues, the levels of MDA (as a lipid peroxidation marker) and AOPP (as an oxidative modified proteins marker) were also found significantly augmented in colon from EAE mice (p < 0.001; Figure 5B,D), whereas FRAP levels (as an indicator of non-enzymatic antioxidant status) were significantly decreased when compared with the healthy control group (p < 0.001; Figure 5C). In contrast, in the OLE-treated EAE mice, both the MDA and AOPP levels were remarkably lowered (p < 0.001 and p < 0.05, respectively), and the FRAP levels were found notably elevated (p < 0.01), reaching levels close to those in the normal group. Fecal DNA was isolated from mice of the different experimental groups to check whether OLE treatment could modulate gut microbioma in EAE mice. 16S rDNA sequencing analysis revealed diverse microbial populations in the experimental groups, but no significant differences were detected among them in the assessed α-diversity metrics: Chao1, Shannon and Simpson indexes (Figure 6A). In Figure 6B are shown the microbioma profiles according to taxonomic classification at different levels. No major differences could be seen in the composition of gut microbiota at the phylum, order, and family levels among mice of the different experimental groups. At the phylum level, Bacteroidetes and Firmicutes were major phyla in the gut bacteria of all groups with the combination of the two phyla making up approximately 90% of the total community. Proteobacteria and Verrucomiceobia showed low abundance. Though not statistically significant, the Firmicutes abundance dropped approximately 1.4 fold, from 48% in untreated-control mice to 34% in OLE-treated mice. Thus, the ratio Firmicutes to Bacteroidetes in the OLE-treated groups tended to decrease compared to the control group, as shown in Figure 6C, but no significant difference was found (p > 0.05). Some differences were observed at family level among the experimental groups, but only those of Akkermansiaceae, which belong to phylum Verrucomicrobia, achieved significant relevance. Compared to the untreated groups, the relative abundance of Akkermansiaceae was significantly higher in the OLE-treated groups (Figure 6D). The Bacteroidaceae, a family in the phylum Bacteroidota, was also increased in the OLE-treated mice, though not significantly, when compared to untreated ones (as it can be appreciated in the family graph of Figure 6B). Finally, to study whether the protective intestinal effects observed in OLE-treated EAE mice also involved direct actions on cells that are essential for maintaining a functional intestinal barrier, mono-cultures of Caco-2 cells were exposed to OLE. We treated Caco-2 cell monolayers with the oxidants hydrogen peroxide (H2O2) and tert-butyl hydroperoxide (t-BOOH), as well as with some relevant inflammatory cytokines such as TNFα and IL-1β, which were found to be enhanced in the EAE mice model. Firstly, we demonstrated that the presence of OLE had no significant influence on the viability of Caco-2 cells (Figure 7A). Then, we evaluated the ability of OLE to protect Caco-2 cell monolayers from oxidative stress. H2O2 and t-BOOH stimulation induced a significant ROS accumulation in Caco-2 cells compared to untreated ones, and OLE pretreatment abolished this response (Figure 7B). We also investigated the ability of OLE to regulate the secretion of proinflammatory cytokines, such as IL-8, a crucial inflammatory mediator of intestinal injury that exerts deleterious effects on the intestinal mucosa [24]. As shown in Figure 7C, the exposure of cells to IL-1β led to an increasing secretion of IL-8, whereas the presence of OLE inhibited this up-regulated response in a dose-dependent manner. Moreover, we studied the effect of OLE on Caco-2 cells, and epithelial barrier function was assessed by measurements of TEER and FD-40 permeability (Figure 7D). The presence of OLE at 5 and 10 µM did not affect Caco-2 epithelial barrier function. However, TNFα stimulation induced a significant decrease in TEER and a significant increase in FD-40 permeability on Caco-2 cells. As expected, cell pre-treatment with OLE attenuated the epithelial barrier dysfunction induced by TNFα. Growing evidence supports the role of the gut-brain axis in MS pathogenesis [5,6,7]. Therefore, it is interesting to explore new therapeutic strategies that can restore/prevent intestinal alterations in MS and its preclinical model, EAE. Intestinal barrier integrity is essential for the maintenance of intestinal health and homeostasis of internal environment [25]. We had previously observed that EAE causes inflammation and oxidative stress in the intestine of mice, resulting in tissue injury and increased intestinal permeability [11]. OLE, a natural antioxidant and anti-inflammatory active substance, has been shown to be effective in the prevention and treatment of EAE, and we have now demonstrated the capability of OLE to prevent barrier defects and inflammation, as well as oxidative stress, in intestinal tissue of EAE mice. In line with the in vivo data, OLE suppressed IL-1β-induced inflammatory IL-8 production, as well as TNFα-induced barrier dysfunction in human intestinal Caco-2 cell monolayers. Therefore, our findings shed new light on the beneficial role of OLE on intestinal homeostasis, specifically in pathologies, such as EAE/MS, but also with potential use in other diseases associated with intestinal barrier dysfunction [26]. Some gastrointestinal diseases, where the intestinal barrier is impaired, have also been associated with CNS demyelination [27]. Although a causal link between intestinal barrier breakdown and CNS demyelination cannot be concluded with certainty in these cases, there appears to be an association not solely explained by their shared epidemiological and immunological characteristics. The association between these entities is certainly complex and requires further study. OLE is a secoiridoid derivative present in EVOO. Recently, several studies have also highlighted the positive EVOO actions on gut health. Although specific beneficial effects of some of its phenolic compounds, such as hydroxytyrosol, tyrosol, and oleuropein, have already been examined at the intestinal level, OLE effectiveness on protecting intestinal barrier has not yet been investigated [27,28,29,30,31]. Currently, it has been described that the small intestine plays an important role in OLE absorption, and herein, our study demonstrates the beneficial effect of OLE mitigating gut damage in EAE mice, but it does not address the presence of OLE in intestinal tissue [32,33]. Further research to investigate this point is needed, in order to clarify whether the biological effects attributed to it are due to OLE itself or its biotransformed metabolites. Although OLE is an ingredient of olive oil from which it has been isolated in the past, a recent new method permitted its isolation from olive leaves [14]. In the current application of the new isolation method, we used olive leaves with elevated oleuropein content, which was used as precursor molecule for the production of oleacein during the extraction procedure. For this purpose, and after the screening of olive leaves from several different varieties, we identified a population of wild olive trees that showed high oleuropein content, which were used as the starting material for the production of OLE with yield > 1% w/w of dried leaves. The currently applied method permitted the isolation of OLE through a selective extraction procedure without the need for expensive and laborious chromatographic methods. In many chronic inflammatory diseases afflicting humankind, both gastrointestinal and non-gastrointestinal increase in intestinal permeability is pointed out as a key element, by allowing the entrance of pathogenic components into the lamina propria and later on into systemic circulation. In MS patients, and likewise in its preclinical models, an increased gut permeability has been widely reported [5,6,10,34]. In MOG35-55-induced EAE in C57BL/6 mice, the disease is characterized by intestinal barrier disruptions and the presence of flawed goblet cells [10,11]. In this study, we found that OLE effectively exerted an inhibitory effect on these alterations, showing a reduced FITC-dextran translocation using the ex vivo non-everted gut sac model. Accordingly, Caco-2 cells, stimulated with TNFα to induce cell monolayer permeability, confirmed the protective effect of OLE. TNFα is an inflammatory cytokine found notably elevated in colon from EAE mice, which, in intestinal Caco-2 cells, decreases the transepithelial electrical resistance (TEER) while increasing FITC-dextran permeation [35]. Therefore, we confirm that OLE pretreatment was effective in maintaining the Caco-2 cell monolayer integrity, proving its ability to maintain the integrity of the intestinal barrier. In addition to the permeability analysis, variations in leaky gut-related markers were also evaluated in serum samples. In EAE mice, a previous study by our group reported that the serum levels of surrogate biomarkers of these events, sCD14 and iFABP, augmented significantly compared to control mice. I-FABP is an intracellular protein specifically expressed in enterocytes and it is released into the circulation when intestinal mucosal damage occurs; and sCD14 is a soluble LPS co-receptor released from monocytes in response to bacterial translocation into plasma, also a sign of an active inflammatory response [36,37,38,39]. In the present study, we observed that EAE-increased levels of these markers were significantly attenuated by OLE treatment. Additionally, we found that OLE treatment also diminished EAE-induced goblet cell damage in colon. Goblet cells are mucin-secreting epithelial cells that play vital roles in sustaining the intestinal mucosal barrier [40]. Clinical observations and data from experimental animal models have reported the presence of defective goblet cells and a reduced production of mucosal barrier-related molecules, as critical factors in the triggering of the disorders affecting the gastrointestinal tract [41,42,43].. It is interesting to note that OLE administration to EAE mice not only preserved goblet cells mucins in intestinal tissues, but it was also able to prevent the reduction in galectin-3 levels observed in the colon of untreated mice. Since cell surface-associated mucins form strong complexes with galectin-3, preserving the integrity of the mucosal barrier, these results show how OLE might be contributing to the restoration of the epithelial barrier in EAE [44]. We also found that the expression levels of the neurotrophic factor GDNF were down-regulated in the colon of EAE mice, but when daily treated with OLE, levels were restored. A similar expression pattern was observed in serum samples. Although GDNF is mainly secreted by enteric glial cells, another crucial component of the intestinal mucosal defense system also enterocytes synthesize significant amounts of this neurotrophic factor [45]. GDNF has protective roles on barrier functions by modulating its maturation, as well as the proliferation and apoptosis of the intestinal epithelial cell [23,46]. Reduced levels of GDNF lead to morphological and functional abnormalities of the intestinal barrier function, both in patients with intestinal diseases and in preclinical models [47,48]. Our findings in the EAE model are consistent with these considerations. Interestingly, some phytochemicals, such as polyphenols, have shown neurotrophic factor-like activity by binding to neurotrophic factor receptors; future research should unravel whether OLE also possesses neurotrophic functions through a direct agonistic effect on these receptors [49,50]. A compromised intestinal barrier function has unequivocally been associated with inflammatory conditions in the gut [51,52]. In accordance, high levels of the inflammatory TNFα and IL-1β were observed in the colon of EAE mice, compared to control. An increased presence of pro-inflammatory cytokines has been observed in patients and preclinical models of intestinal diseases, and treatments suppressing the inflammatory response alleviated the intestinal dysfunction [53,54,55,56,57,58]. Consistent with these data, the current study demonstrated that OLE treatment decreased the pro-inflammatory cytokine levels in the colon of EAE mice. In addition, the immunoregulatory cytokines, IL-33 and IL-25, were preserved in the colon of OLE-treated EAE mice. A protective function has already been described for these cytokines on mucosal tissue. In line with our observations, decreased IL-25 levels have been found in the intestine of both IBD patients and preclinical models, and IL-25 treatment inhibits experimental intestinal damage in mice [59,60]. Regarding IL-33, this cytokine is associated to goblet cells proliferation and mucin expression, hence, it promotes epithelial integrity and restoration of intestinal homeostasis [61,62]. Moreover, IL-33 and IL-25 possess the ability to influence innate and adaptive immunity, promoting protective Th2 cytokine-mediated responses [59]. In EAE, deviation of the immune system towards a Th2 response correlates with disease resistance. Accordingly, treatment with either IL-25 or IL-33 protects mice from EAE diseases, whereas its deficiency or blockade results in an accelerated/exacerbated EAE phenotype [63,64,65,66,67]. Thus, taking together these reports, preserving the expression of these cytokines may be valuable for OLE-induced protection to EAE mice. Although precise molecular mechanisms involved in these protective actions of OLE have not been addressed in this study, regulation of CD14/TLR4/CD14/MyD88 axis, JAK/STAT, MAPKs and inflammasome, as well as post-translational modification in histone H3 are signaling mediators modulated by OLE that deserve further investigation in the EAE context [18,68]. Since oxidative stress and inflammation is a feedback, another essential factor in the pathogenesis of gastrointestinal mucosal diseases is ROS over-accumulation [69,70]. The amelioration of the oxidative response exerted by OLE in gut tissues was also evidenced, when oxidative stress markers were evaluated. In MS patients a reduced antioxidant capacity has been observed [71]. Accordingly, in EAE mice tissues, including gut, oxygen radicals are overproduced, shifting the endogenous oxidant/antioxidant balance, which is consistent with our present findings [11]. Some of the beneficial effects of OLE might be ascribed to its strong antioxidant capacities [72,73,74] and, herein, it has been demonstrated that OLE significantly reduced ROS accumulation in the colon of EAE mice, as well as the levels of MDA and AOPP indicating that OLE lowered the degree of lipid and protein oxidation to suppress intestinal oxidative stress. In consonance, FRAP values, which reflect the overall redox status, were increased in colon of EAE mice treated with OLE, highlighting its protective antioxidant effect. A direct protective effect of OLE against oxidative stress was also observed in Caco-2 cells, after these cells were incubated with OLE, which significantly attenuated ROS accumulation following exposure to the stressors, hydrogen peroxide or tert-butyl hydroperoxide. Therefore, the antioxidant activity of OLE contributes to the above-mentioned gut-integrity strengthening effect. Another disturbance we observed in the gut of EAE mice was an increase in the cecal index and OLE treatment prevented this enhancement. Usually, full cecum increases are associated to increased fermentation, consequently, to changes in microbial metabolism. Further investigations are required to elucidate whether these observed changes are due to alterations in the cecal microbe composition or in the bacterial enzymatic expression and activity [75]. Likewise, regarding the protective effect of OLE, its direct impact on cecal microbioma should be considered, as well as its actions on proteins involved in microbial activities [76] Studies on MS patients and the EAE mouse model suggest that the gut microbiome plays a significant role in both disease progression and severity [77,78,79]. In our experimental condition to examine the effects of OLE administration on mice gut microbiota, specific changes in the abundance of Akkermansiaceae, a family of mucin-degrading bacteria, were detected in fecal samples from mice treated with OLE, EAE-induced or not. Interestingly, the bacteria Akkermansia muciniphila (the better studied member of the Akkermansiaceae family with epithelium remodeling properties) positively correlates with mucus layer thickness and intestinal barrier integrity, and promotes the development of host innate and adaptive immune systems with anti-inflammatory effects [80]. Decreased contents of these bacteria in the intestine are associated with the development of several intestinal diseases, whereas increasing its proportion in gut microbiota through dietary modification or pharmacological intervention has beneficial effects in host health. In our study, it might suggest that OLE increasing the Akkermansiaceae family abundance favors a protective gut environment. In line, recent studies have suggested that dietary polyphenols play a role in the modulation of the gut microbiota that may favor positive outcomes [81]. Thus, polyphenols from black tea, red wine grape extract/grape pomace extract or cranberry extract stimulate the growth of beneficial bacteria in the gut microbiota such as Akkermansia, belonging to the Verrumicrobiota phylum [81]. Although the exact mechanisms of action have not yet been fully established, differences in susceptibility between bacterial groups may depend on resistance to any of the mechanisms by which polyphenols interact with bacteria [82], e.g., through short-chain fatty acids production, which stimulates the goblet cells to produce more mucus to preserve intestinal barrier integrity. Focusing on the olive bioactive constituents, a recent study has shown that the diminished abundance observed in bacteria belonging to the phyla Bacteriodetes and Verrumicrobiota in mice fed with a high fat diet, were also restored by treatment with an olive leaf extract [83]. Moreover, the authors point that this microbiota restauration is associated with the improvement of the gut barrier function, as well as with the beneficial effect induced by the extract on the metabolic and vascular alterations associated to obesity. In this study, we found that the OLE-mediated increase in the relative abundance of the Akkermansiaceae family paralelled the prevention of the intestinal barrier damage induced in EAE mice. However, a causal relationship should be stated by the oral administration of these bacteria (i.e., as a probiotic), or a family member such as Akkermansia muciniphila, in future studies. Additionally, in our study we noted a trend toward an increase in Bacteroidaceae family in mice of OLE-treated groups, but those changes were not significant. Interestingly, other investigations, in EAE mice and MS patients, reported that a dietary intervention that confers protection in the EAE model and improves the disability status scale of the disease on MS patients, also significantly increased the Bacteroidaceae family richness [77,78]. Therefore, our findings from the OLE-treated mice are worthy of attention, it being possible that using a higher dose of OLE or a different administration route, the changes in Bacteroidaceae family richness could achieve a significant impact. We should also consider that in our experimental design, mice were sacrificed at a time where perturbations to the gut microbial populations have not reached a maximum. Additional work should be performed to test these possibilities. Female 8 to 10-week-old C57BL/J6 mice (from Charles River Laboratories, Barcelona, Spain) were housed in the animal care facility at the Medical School of the University of Valladolid and provided with food and water ad libitum. All animal care and experimental protocols were reviewed and approved by the Animal Ethics Committee of the University of Valladolid (3008787) and complied with the European Communities directive 86/609/ECC and Spanish legislation (BOE 252/34367-91, 2005) regulating animal research. EAE was induced according to our previous study [21]. EAE-immunized mice received an intraperitoneal injection with vehicle control (DMSO/saline, n = 9) or 10 mg/kg/day of OLE (n = 9) starting from immunization day until the end of the experiment, when untreated EAE mice showed hind limb paralysis (about day 24 post-immunization). Control mice (without EAE induction) were also injected daily with OLE (n = 9) or vehicle control (n = 9) for an equivalent timeframe. OLE was dissolved in normal saline containing 5% DMSO. Animals were monitored blindly and daily by two independent observers and neurological signs were assessed on a scale of 0 to 5, with 0.5 points for intermediate clinical findings as previously described: grade 0, no abnormality; grade 0.5, partial loss/reduced tail tone, assessed by inability to curl the distal end of the tail; grade 1, tail atony; grade 1.5, slightly/moderately clumsy gait, impaired righting ability or combination; grade 2, hind limb weakness; grade 2.5, partial hind limb paralysis; grade 3, complete hind limb paralysis; grade 3.5, complete hind limb paralysis and fore limb weakness; grade 4, tetraplegic; grade 5, moribund state or death, [11,22]. Blood and intestinal sections were collected. Tissues were frozen at −80 °C for protein studies or fixed in 4% paraformaldehyde in PBS, followed by paraffin embedding or OCT embedding then frozen. Fresh olive leaves (2 kg) were collected from wild trees growing in Volvi Estate, the largest compact population of wild olive trees in Northern Greece. The leaves were manually separated by the stems and air-dried at room temperature for 10 days until the moisture content was less than <10% (w/w). Then the intact leaves were mixed with water (10 L) at 25 °C and cut into small pieces in the presence of water using a blender. The mixture remained at 25 °C for 30 min and then it was filtered. The aqueous phase was collected and extracted with dichloromethane (5 L). The organic phase was collected and evaporated using a rotary evaporator under reduced pressure affording a viscous liquid containing oleacein (14 g, purity 95% (w/w)) with NMR data in accordance with those previously described [14]. In Figure 1A the oleacein structure is shown. Ex vivo detection of intestinal permeability was performed using “intestinal sacs” and following the protocol of Zhong et al. with some modifications [84]. Colon tissue samples were extracted into Krebs-Henseleit bicarbonate buffer (KHBB) containing 8.4 mM HEPES, 119 mM NaCl, 4.7 mM KCl, 1.2 mM MgSO4, 1.2 mM KH2PO4, 25 mM NaHCO3, 2.5 mM CaCl2, and 11 mM glucose (pH 7.4). Then, one end was sutured and from the other end 100 μL of fluorescein-labeled dextran-40 (FD-40, MW 40 kDa, 10 mg/mL) was injected using a gavage needle, and tied to form a 5 cm sac. After a quick dip in KHBB to remove the presence of fluorophore on the outside, the intestinal sac was incubated in 2 mL of new buffer, at 37 °C for 20 min. Finally, the fluorescence of the FD-40 transferred from the intestinal lumen to the incubation solution (Ex./Em. 485/530 nm) was measured in a fluorimeter. Intestinal permeability was expressed in micrograms of extravasated FD-40/cm/min. For histological analysis, mouse colons were fixed in 4% paraformaldehyde, processed and embedded in paraffin. 5-μm-thick tissue sections were stained with Periodic acid-Schiff (PAS) and Alcian blue (AB) (Sigma-Aldrich) to stain general intestinal carbohydrate moieties. Acidic mucins stain blue with AB (pH 2.5), neutral mucins stain pink with PAS, and mixtures of neutral and acidic mucins appear purple. The sections from all experimental groups were stained in one single batch to ensure that differences in the staining pattern were not due to technical manipulations, thereby allowing the comparability of the different samples. The evaluation was performed, in a blinded fashion, in each specimen to control the changes that occurred along the treatment. Histopathological examination was performed with a Nikon Eclipse 90i (Nikon Instruments Inc., Amstelveen, The Netherlands). For quantitative analysis, images were acquired from at least three random fields of view per slice and processed using the ImageJ image analysis program (NIH, Bethesda, MD, USA). The area AB/PAS positive was identified as the ratio to the total tissue area Colon segments were collected and frozen immediately in Tissue-Tek O.C.T. To evaluate the intracellular superoxide anion (O2·−) the oxidative fluorescent dye dihydroethidium (DHE, Invitrogen Life Technologies, Burlington, Canada), was used as previously described [11]. Briefly, frozen samples cut into 12-μm thickness sections using a cryostat were equilibrated in Krebs-HEPES buffer (NaCl 130 mM, KCl 5.6 mM, CaCl2 2 mM, MgCl2 0.24 mM, HEPES 8.3 mM, glucose 11 mM, pH 7.4) in a humidified and light-protected chamber at 37 °C. The sections were then incubated with 5 μM of DHE for 30 min at 37 °C. Fluorescence signals were viewed using a fluorescence microscope (Nikon TE2000, Japan) under a 10× objective (100× final magnification) and a 20× objective (200× final magnification). At least five images of each colon sample were captured for analysis using a fixed exposure time for all groups. The intensity of fluorescence signals was quantified using ImageJ software (NIH, Bethesda, MD, USA). A single researcher who was unaware of the experimental groups performed the analysis. Serum and colon tissue samples were collected from animals on day 24 after immunization. Colon tissues were weighed and homogenized (1:10, w/v) in ice-cold PBS supplemented with 0.4 M NaCl, 0.05% Tween 20, 1% EDTA and a protease inhibitor cocktail containing PMSF, leupeptin and aprotinin (Sigma-Aldrich, St Louis, MO, USA), and centrifuged at 10.000 rpm for 10 min at 4 °C. All samples were immediately stored at −80 °C. Mouse TNFα, IL-1β, pro-IL-1β, and IL-25 ELISA kits from eBioscience (San Diego, CA, USA). Mouse sCD14, IL-33 and Galectin-3 (Gal-3) DuoSet ELISA Kits were from R&D (R&D Systems, Minneapolis, MN, USA). Mouse iFABP and GDNF ELISA kit were from Cusabio (Cusabio Biotech Co., Ltd., Wuhan, China). Mice n = 5–7 per group. Colon homogenate samples were used to measure the total antioxidant activity using the FRAP assay following the method described by Benzie and Strain [85]. FRAP values were calculated according to the calibration curve for FeSO4·7H2O and expressed as µM of Fe2+ equivalents. Colon homogenate samples were assessed in duplicates to determine the presence of lipid peroxidation products as malondialdehyde (MDA) concentration. The lipid peroxidation level was measured spectrophotometrically by the estimation of MDA concentration based on the reaction with thiobarbituric acid [86]. Briefly, colon supernatans were added to a reaction mixture consisting of 0.373% thiobarbituric acid, 15% trichloroacetic acid and 0.015% BHT. Then, the mixture was heated at 95 °C for 40 min, and cleared by centrifugation at 3.800 rpm for 10 min. The absorbance was measured at 532 nm using a 96-well plate. Colon homogenate samples were assessed in duplicates to determine the presence of advanced oxidation protein products (AOPP) as a biomarker of oxidative stress. 20 µL colon supernatant samples were pipetted into a 96-well microplate and diluted into 100 µL in PBS. Then, 10 µL of 1.16 M KI, and 20 µL absolute acetic acid were added to each well of the microtiter plate. The absorbance of the reaction mixture was immediately read at 340 nm on the VERSAmax microplate reader against a blank containing 100 µL PBS, 20 µL acetic acid, and 10 µL KI solution. AOPP were calibrated with a chloramine-T solution (0–100 µM) that absorbs at 340 nm in the presence of 10 µL of 1.16 M potassium iodide. AOPP concentrations were expressed as µM chloramine-T equivalents. Bacterial DNA was extracted from 220 mg of the fecal content from each animal using QIAamp Fast DNA Stool Mini Kit (Qiagen, QIAGEN Iberia, S.L. Spain) according to manufacturer’s instructions with prior disruption using silica beds in a Fastprep® device (QBiogene, Carlsbad, CA, USA). The DNA concentration was determined using a Qubit® fluorimeter (Invitrogen, Waltham, MA, USA). Microbial diversity was studied by sequencing the amplified V3–V4 region of the 16S rRNA gene using previously reported primers and PCR conditions [87]. Sample multiplexing, library purification, and sequencing were carried out as described in the “16S Metagenomic Sequencing Library Preparation” guide by Illumina. Libraries were sequenced on a MiSeq platform, leading to 300-bp, paired-end reads. Demultiplexed fastq files were processed using QIIME2 ™ pipeline version 2022.8 for quality filtering of the reads, merging of the paired ends, chimera removal, and assignation of amplicon sequence variants (ASV) [88]. Cell culture: Human Caco-2 cells (kindly provided by Dr. E. Arranz, IBGB-UVa/CSIC, Spain) were routinely maintained in DMEM (glutamine, high glucose), supplemented with 10% FCS, 100 U/mL penicillin and 100 pg/mL streptomycin (Life Technologies, Carlsbad, CA, USA), and were incubated at 37 °C in 5% CO2. Medium was changed every 2 days and cells were used between passage 19 and 35. The monoculture of Caco-2 cells formed tight junctions at day 17–21 post-confluence. Differentiated cell layers showing high transepithelial resistance (TEER) values (~400–500 Ω × cm2), were measured with Millicell electrodes (Millicell-ERS, Millipore, Billerica, MA, USA). Viability assay: Cell viability was evaluated by using the Promega kit (Madison, WI, USA), Cell Titer 96® Aqueous One Solution Cell Proliferation Assay, according to the manufacturer’s recommendations. Briefly, Caco-2 cells were seeded in 96-well plates (10 × 103 cells/well) and serum starved for 24 h. Then, cells were incubated in the presence of different doses of OLE. After 24 h of incubation, formazan product formation was assayed by recording the absorbance at 490 nm in a 96-well plate reader (OD value). Formazan is measured as an assessment of the number of metabolically active cells. Three different assays were each performed in triplicate. Cytokines analysis: Supernatants of Caco-2 cells stimulated with 25 ng/mL of IL-1β for 48 h in the presence of different doses of OLE were used to quantify IL-8 production. The specific human IL-8 ELISA Ready-Set-Go kit (eBioscience, San Diego, CA, USA) was used according to the manufacturer’s protocol. Measurement of intracellular reactive oxygen species (ROS) levels: ROS levels were measured with the probe dichlorodihydrofluorescein diacetate (DCFH-DA; Molecular Probes, Eugene, OR). Briefly, Caco-2 cells were seeded in 96-well microplates at 1 × 104/well and after serum starvation, cells were incubated overnight at 37 °C with the indicated doses of OLE. Then, cells were loaded with 10 μM of DCFH-DA for 30 min at 37 °C. After that, cells were stimulated with 500 μM of H2O2 or 400 μM of tert-butyl hydroperoxide (t-BOOH) for 1 h. The fluorescent signal was measured at Ex. 485 nm-Em. 530 nm, using a plate reader Fluoroskan Ascent FL (Thermo Electron Corporation, Waltham, MA, USA). Results were expressed as an n-fold increase over the values of the control group. Transepithelial electrical resistance (TEER) measurement: The integrity of a Caco-2 monolayer was determined by measuring the TEER value [89]. Cells were grown in 24-well plates and seeded at 1 × 105 cells/insert onto polycarbonate membrane Transwell inserts with 0.4 μm pore size, and 0.33 cm2 growth surface (Corning, Inc.; Lowell, MA, USA). Cells were cultured for 21 days to reach differentiation. After that, Caco-2 cell monolayers were pretreated with the indicated doses of OLE for 30 min (apical) and then stimulated with 100 ng/mL of TNFα for 24 h at 37 °C. TEER values were measured with Millicell electrodes (Millicell-ERS, Millipore, Billerica, MA, USA). TEER recorded in unseeded Transwell inserts was subtracted from all values. TEER measures were normalized to untreated-control cell and expressed as a percentage of control. Permeability studies: Permeability of the cell monolayer was determined by using the macromolecular tracer FITC-labeled Dextran (FD-40, Sigma Chemical Co. St. Louis, MO, USA). Confluent and differentiated Caco-2 cell monolayers were pretreated with the indicated doses of OLE for 30 min (apical) and then stimulated with 100 ng/mL of TNFα for 24 h. Then, the medium was aspirated and both chambers were washed with HBSS. After that, 200 μL of 10 mg/mL FITC-dextran dissolved in HBSS was added at the apical compartment of each insert. After 1 h incubation at 37 °C, 200 μL aliquots were taken from the basolateral chamber and plated into a black, flat-bottom 96-well plate. The fluorescence intensity was measured in a Fluoroskan Ascent FL microplate reader (Thermo Electron. Corporation, Waltham, MA, USA) with the setting of Ex. 485 nm and Em. 530 nm. The amount of FITC-Dextran transported into the basolateral compartment (permeability flux) was extrapolated from a standard curve and expressed as mg/mL/h. Results were expressed as apparent permeability coefficient (Papp) and defined as cm/h. “Papp” is derived from the ratio of flux rate (mg/mL/h) to that of initial concentration (in mg/mL) and surface area of the membrane. Data analyses were performed using one-way ANOVA (for multiple comparisons) or two-way ANOVA (for four-groups comparisons). The Bonferroni test was utilized for post hoc analysis among multiple groups where appropriate. Results described as mean ± SD. p < 0.05 were considered statistically significant. Statistical analyses were performed using the GraphPad Prism Version 4 software (San Diego, CA, USA). In conclusion, our findings demonstrate for the first time that OLE effectively regulates intestinal oxidative stress, inflammation, and permeability when administered to EAE mice. Since OLE also ameliorates MS classical clinical signs in EAE, this study remarks the probable relevance of the intestinal alterations in the evolution of the disease. Additional studies are necessary to check whether OLE can be used to improve MS and MS-related disorders in patients, but our data strongly support the therapeutic potential of OLE for the treatment of gastrointestinal diseases where the intestinal barrier is impaired, including those associated with CNS demyelination.

PMC10003434

Anqi Peng,Keke Yu,Shuwei Yu,Yingying Li,Hao Zuo,Ping Li,Juan Li,Jianan Huang,Zhonghua Liu,Jian Zhao

Aluminum and Fluoride Stresses Altered Organic Acid and Secondary Metabolism in Tea (Camellia sinensis) Plants: Influences on Plant Tolerance, Tea Quality and Safety

27-02-2023

aluminum and fluoride,organic acid,secondary metabolite,tea quality,tea safety

Tea plants have adapted to grow in tropical acidic soils containing high concentrations of aluminum (Al) and fluoride (F) (as Al/F hyperaccumulators) and use secret organic acids (OAs) to acidify the rhizosphere for acquiring phosphorous and element nutrients. The self-enhanced rhizosphere acidification under Al/F stress and acid rain also render tea plants prone to accumulate more heavy metals and F, which raises significant food safety and health concerns. However, the mechanism behind this is not fully understood. Here, we report that tea plants responded to Al and F stresses by synthesizing and secreting OAs and altering profiles of amino acids, catechins, and caffeine in their roots. These organic compounds could form tea-plant mechanisms to tolerate lower pH and higher Al and F concentrations. Furthermore, high concentrations of Al and F stresses negatively affected the accumulation of tea secondary metabolites in young leaves, and thereby tea nutrient value. The young leaves of tea seedlings under Al and F stresses also tended to increase Al and F accumulation in young leaves but lower essential tea secondary metabolites, which challenged tea quality and safety. Comparisons of transcriptome data combined with metabolite profiling revealed that the corresponding metabolic gene expression supported and explained the metabolism changes in tea roots and young leaves via stresses from high concentrations of Al and F. The study provides new insight into Al- and F-stressed tea plants with regard to responsive metabolism changes and tolerance strategy establishment in tea plants and the impacts of Al/F stresses on metabolite compositions in young leaves used for making teas, which could influence tea nutritional value and food safety.

Aluminum and Fluoride Stresses Altered Organic Acid and Secondary Metabolism in Tea (Camellia sinensis) Plants: Influences on Plant Tolerance, Tea Quality and Safety Tea plants have adapted to grow in tropical acidic soils containing high concentrations of aluminum (Al) and fluoride (F) (as Al/F hyperaccumulators) and use secret organic acids (OAs) to acidify the rhizosphere for acquiring phosphorous and element nutrients. The self-enhanced rhizosphere acidification under Al/F stress and acid rain also render tea plants prone to accumulate more heavy metals and F, which raises significant food safety and health concerns. However, the mechanism behind this is not fully understood. Here, we report that tea plants responded to Al and F stresses by synthesizing and secreting OAs and altering profiles of amino acids, catechins, and caffeine in their roots. These organic compounds could form tea-plant mechanisms to tolerate lower pH and higher Al and F concentrations. Furthermore, high concentrations of Al and F stresses negatively affected the accumulation of tea secondary metabolites in young leaves, and thereby tea nutrient value. The young leaves of tea seedlings under Al and F stresses also tended to increase Al and F accumulation in young leaves but lower essential tea secondary metabolites, which challenged tea quality and safety. Comparisons of transcriptome data combined with metabolite profiling revealed that the corresponding metabolic gene expression supported and explained the metabolism changes in tea roots and young leaves via stresses from high concentrations of Al and F. The study provides new insight into Al- and F-stressed tea plants with regard to responsive metabolism changes and tolerance strategy establishment in tea plants and the impacts of Al/F stresses on metabolite compositions in young leaves used for making teas, which could influence tea nutritional value and food safety. Tea is one of the most consumed non-alcoholic beverages and has become increasingly popular because of its rich tastes and potential health benefits, which are largely attributable to the high levels of tea-characteristic secondary metabolites, including catechins, caffeine, and theanine [1,2]. Tea plants are also a typical aluminum ion (Al in short) and fluorine anion (F in short) hyperaccumulator because tea plants used to grow in acidic soils containing high concentrations of Al and F in the tropical and subtropical regions of mountainous areas [3,4,5,6]. The average content of F in the soils of tea plantations in China is 540, ranging between 190 and 1100 mg/kg in most areas, but in southwest provinces with F mines or polluted soils, such as GuiZhou, the soil F content can be over 2000 mg/kg [7,8,9,10]. F is easily dissolved in acidic water and readily taken up by tea plant roots, and F concentrations in soils are highly correlated with F levels in tea leaves [7,8,9]. Tea plant leaves can accumulate up to 20,000 mg Al/kg and 1000–3000 mg F/kg in mature and old leaves and more than 600 mg Al/kg, 100–300 mg F/kg in young leaves, which are hundreds of times higher than in other crops [11]. Over-uptake of these elements by drinking teas, particularly teas made from old leaves and stems such as brick tea, can cause serious health problems, such as permanent damage to key enzymes and the circulatory, renal, brain, bone, and central neuron systems [5,12,13,14]. However, soils in many regions where large acreages of tea plants are planted are very acidic, contain high levels of F and Al, and are contaminated with carcinogenic heavy metals [8,9,12,15]. As one of the major factors that cause Al and F rhizotoxicities, the low pH values of tea plantation soils could be reduced continuously due to NH4 fertilization, proton and acid secretion by tea roots, and more frequently occurring acid rain under global climate changes [16,17,18]. Moreover, the accumulation of high levels of Al and F in tea leaves transported from tea roots also has been shown to negatively affect plant growth and development [19,20,21,22]. Excessive F causes both cell wall dysfunctions and intracellular damages [20,21,23]. Excessive Al entering into the plant cells destroys plant cell membrane, chloroplast structures, and enzyme activity, and causes metabolic process distortion, eventually resulting in early leaf loss or plant death [19].The biosynthesis and accumulation of major tea secondary metabolites, such as catechins and theanine, could be inhibited by Al and F stresses, which thereby reduces tea nutritional quality [12,23,24]. Therefore, there is a great need to reduce Al/F and other heavy metal accumulation in tea leaves through the genetic improvement of tea plant cultivars. However, so far, the understanding of the tea root uptake, vascular translocation, and leaf accumulation of Al/F and these toxic heavy metals are very limited, which largely prevents us from looking for efficient solutions for the breeding of safer tea plants [23]. Under Al stress, plant roots can secret organic acids to form Al-organic acid complexes, but it is not known whether F stress induces the exudation of organic acids to the tea root rhizosphere [3,4,25]. The Al can form different conjugates in tea plant tissues, such as Al-F in old leaves (AlF2+, AlF30 and AlF4− exist together) [26], Al-oxalate in root tips and saps, Al-citrate in shoot xylem saps, or Al-catechins in roots, which are considered as mechanisms of Al/F-hyperaccumulation and tolerance in tea plants [3,4,25,27,28]. Al and F stresses significantly modulated flavonoids, theanine, caffeine, and other amino acids in tea roots and leaves, which may contribute to Al and F detoxification on site [23,29,30,31,32]. Theanine is primarily synthesized in tea roots and could be translocated to the shoot tips, similar to Al and F translocation from tea roots to shoot tips [23,33]. While organic acids were widely considered as Al/F tolerant mechanism in many crops, the tricarboxylic acid cycle (TAC) and its metabolism in tea roots is not reported [23,34,35] in terms of enhancing plant tolerance to Al/F stresses and facilitating the transport and accumulation of Al/F and heavy metals to shoots, thereby impacting the food safety and nutrition quality of tea [14,20,36]. Thus, it is of particular interest to understand them for many purposes. In this study, we studied organic acid biosynthesis in roots, their secretion into the root rhizosphere, and their possible connections to catechins, theanine, and caffeine biosynthesis pathways in both tea roots and shoots under Al and F stresses. By integrating transcriptome data and the relevant metabolite profiling of tea roots and leaves under Al and F stresses, we were able to look into their intriguing connections to consider tea nutritional quality and safety. The study shed new light on the root TAC, amino acid, and secondary metabolism in tea plant response Al/F stresses, tolerance strategies, and their potential effects on tea safety and nutritional quality. After pretreatment of the medium samples to remove excessive salts and interfering chemicals, media samples were concentrated and used for the measurement of organic acids in a high-performance liquid chromatography (HPLC) (Figure 1). We detected organic acids in the tea-growth hydroponic media and found oxalic acid, tartaric acid, shikimic acid, and citric acid (Figure 1A,B). The most abundant one was oxalic acid, along with traces of tartaric acid, shikimic acid, and citric acid detected in the tea root-culture media (Figure 1B, Supplemental Figure S1, Table S1). While 0.4 mM Al only induced drastic oxalic acid at 48 h, 2.5 mM Al treatment induced a drastic secretion of oxalic acid from 12 h to 48 h. F treatment initially induced low oxalic acid secretion at 12 h and 24 h, but there was a drastically increased section at 48 h (Figure 1D). A synergistic effect on oxalic acid secretion was observed with Al + F treatment at 12 h, when the content of oxalic acid secretion was at the highest. Furthermore, the secretion of tartaric acid and shikimic acid were slightly induced by 0.4 mM Al at 48 h, but drastically increased by the 2.5 mM Al, 10 mM F, and Al + F treatments (Figure 1E,F). The levels of shikimic acid under Al + F treatment were also synergistically increased at 24 h and 48 h (Figure 1E,F). Al + F treatment induced the highest tartaric acid release at 12 h and 24 h after treatment, significantly higher than both Al and F treatment alone (Figure 1F). With treatment up to 24 h to 48 h, tartaric acid concentrations decreased, but shikimic acid contents in the media increased in the Al + F treatments (Figure 1E,F). Thus, while F treatment displayed toxicity on root organic acid secretion, Al and F treatment together had complex effects on organic acid secretion. We also analyzed organic acid contents in the roots upon Al and F treatments. In tea roots, oxalic acid, citric acid, and malic acid were the major detected organic acids, while tartaric acid and shikimic acid were the minor components in our assays, with an unidentified peak (Figure 1C, Supplemental Table S1). In roots grown in regular Shigeki Konishi (SK) nutrient solutions containing 0.4 mM of Al, the organic acids displayed the same trends of increasing during the cultivation. The tartaric acid, citric acid, malic acid and shikimic acid contents increased at 24 h and 48 h in the 0.4 mM Al treatment compared to the control (Figure 1H–K), whereas oxalic acid contents only significantly increased at 48 h treatments (Figure 1G). Upon 2.5 mM Al treatment, oxalic acid, tartaric acid and malic acid contents were significantly increased in the roots (Figure 1G–J). Citric acid content increased significantly at 12 h and 24 h (Figure 1H,I), whereas shikimic acid contents sharply increased at 48 h under 2.5 mM Al treatment (Figure 1K). In 10 mM F treatment, all organic acid contents were drastically increased. Between 24 h and 48 h, citric acid, malic acid, and shikimic acid content increased, while oxalic acid and tartaric acid content decreased under F treatment (Figure 1G–K). In Al and F combination treatment, most organic acids, such as oxalic acid, tartaric acid and citric acid, reached the highest content at 12 h after treatment (Figure 1G–I). Other organic acids, such as malic acid and shikimic acid, also were increased by Al + F treatment (Figure 1J,K). TAC is a core metabolic system composed of a series of enzymes for the substrate and energy connection of carbohydrate, lipid, and protein biosynthesis and catabolism [37]. Pyruvate is the direct precursor for amino acid and fatty acid biosynthesis, and a plastidial pyruvate dehydrogenase (PDH) and a mitochondrial PDH enzyme complex both catalyze the oxidative decarboxylation of pyruvate to acetyl-CoA, which not only provides the entry point into the TAC cycle, but also supplies acetyl-CoA for acetyl-CoA carboxylase (ACCase) and for malonyl-CoA synthesis, which can be used for fatty acid and flavonoid biosynthesis. Pyruvate dehydrogenase kinase (PDK) regulates the catalytic activity of the mitochondrial pyruvate dehydrogenase complex and links glycolysis with the TAC and ATP generation. Three CsPDKs were up-regulated by the F and Al + F treatments (Figure 2A). The pyruvate dehydrogenase complex is composed of multiple copies of three enzymatic components: pyruvate dehydrogenase (PHDE1), dihydrolipoamide acetyltransferase (PDCE2) and lipoamide dehydrogenase (PDCE3). The E1 component of the pyruvate dehydrogenase complex catalyzes the overall conversion of pyruvate to acetyl-CoA and CO2 [38]. In plants, exogenous acetate is readily converted into acetyl-coenzyme A (acetyl-CoA) by acetyl-CoA synthase. Plastidic acetyl-CoA synthase is responsible for the majority of the conversion of acetate to acetyl-CoA for use in other metabolic pathways [39] (Figure 2A, Supplemental Figures S2 and S3, Table S2). Acetyl-CoA is the starting precursor in the TAC cycle (Figure 2A). Acetyl-CoA and oxaloacetate are condensed into citrate by citrate synthetase (CSY). Among the many transcripts from the transcriptome, two highly expressed and increased transcripts—CsCSY1 and CsCSY2—encoding the CSY enzyme were slightly up-regulated by Al stress. CsCSY2 was also up-regulated by F stress (Figure 2B). Citrate was then converted to cis-aconitate, which is an intermediate that can be further converted to isocitrate by the same enzyme aconitase (ACO). Aconitase catalyzes the first dehydration and then rehydration, and its three transcripts were steadily up-regulated by Al and F stresses. Isocitrate is converted to α-ketoglutarate by isocitrate dehydrogenase (IDH), whose four transcripts were mostly up-regulated by Al stress (Figure 2B). An α-ketoglutarate dehydrogenation complex catalyzes the fourth step in the reaction, in which α-ketoglutarate is converted to succinyl-CoA by α-ketoglutarate dehydrogenase (OGDC), and succinyl-CoA is converted to succinate by succinyl-CoA synthetase (SCS) (Figure 2A). Succinate is converted to fumaric acid by succinate dehydrogenase (SDH), which was encoded by multiple transcripts. Most of them were highly expressed in tea roots (Supplemental Figure S3). The hydration of the C=C double bond that occurs in fumaric acid is catalyzed by fumarate hydratase (FH) to give malate, which is further dehydrogenated to produce oxaloacetate by malate dehydrogenase (MDH). Oxaloacetate further reacts with acetyl-CoA to create citrate to start another round of the TAC cycle. Most of the above genes were up-regulated by Al stress but repressed by F stress, except for CsIDH1, 4, 5, 7 and CsOGDC3 being up-regulated by F stress (Figure 2B). Reversibly, citrate could directly feed FA synthesis via citrate hydrolysis to acetyl-CoA and oxaloacetate via ATP citrate lyase (ACL). ACL transcripts were expressed to a greater extent only upon F and F + Al treatment (Figure 2B). In the glyoxylate cycle, isocitrate lyase (ICL) is the first key enzyme of the glyoxylate cycle, and it catalyzes the reversible aldol cleavage of isocitrate to glyoxylate and succinate (Supplemental Figures S2 and S3, Table S2). The glyoxylate cycle is a variation of the tricarboxylic acid cycle and is an anabolic pathway occurring in plants, bacteria, and fungi [40]. The glyoxylate cycle centers on the conversion of acetyl-CoA to succinate for the synthesis of carbohydrates. Oxalate synthesis includes secondary reactions in glyoxylate cycle. Glycolate oxidase (GOX) is considered as an important player in oxalate accumulation in plants (Figure 2A, Supplemental Figures S2 and S3, Table S2). Indeed, several CsGOX genes were induced by Al stress. The tea glyoxylate reductase 1 (CsGR1) and 2 were slightly enhanced by Al treatment (Figure 2B). The CsGOX3 and 4 transcripts were increased by F stress. The tea oxalyl-CoA reductase 1 (CsOCS1) was also up-regulated by F stress. Interestingly, several oxalate oxidase (OXO) genes were significantly induced by F and Al stresses. Among them, CsOXO1, 2 and 3 were up-regulated by the Al + F, F and Al treatments, whereas CsOXO4 and 5 were drastically up-regulated by Al (Figure 2B, Supplemental Figures S2 and S3, Table S2). Therefore, a whole set of genes involved in oxalate synthesis and metabolism were up-regulated by F stress, supporting that F treatment stimulates oxalate synthesis and secretion into the apoplastic space or culture medium. Activation of oxalate degradation through OXO generates CO2 and H2O2 [40], which is usually regarded as a pathogenesis reaction observed in many plant defense responses to pathogen infections. Oxalate can also be converted to oxalyl CoA by oxalate-CoA ligase (OCL) and then degraded by oxalyl-CoA decarboxylase (OADC) into formyl-CoA and CO2 [40]. It would be very interesting to know why Al and F stresses could activate this and trigger the secretion of oxalate into the apoplastic space. This may be related to the modification of the cell wall, such as in pectin modification and oxidative burst. The serine-glyoxylate aminotransferase (SGAT), glutamate-glyoxylate aminotransferase (GGAT) and hydroxypyruvate reductase (HPR) genes were also differently regulated by the Al and F treatments (Figure 2B). To understand and validate the biosynthesis and secretion of tartaric acid in tea roots, transcriptome data on genes putatively involved in a general pathway towards tartaric acid biosynthesis, which was proposed based on studies on grape and other plants, were collected [41,42,43]. Most studies in plants have shown that tartaric acid biosynthesis in plants is derived from ascorbic acid (Vitamin C), which is also derived from mannose or Myo-inositol [42,44,45]. The majority of the early genes putatively involved in Vitamin C biosynthesis, such as tea phosphomannose isomerase 1 (CsPMI1) and 2, phosphomannomutase 1 (CsPMM1) and 2, as well as GDP-D-mannose pyrophosphorylase 1 (CsVTC1) and GDP-D-mannose epimerase 2 (CsGME2) homolog genes were up-regulated by low or higher concentrations of Al (Figure 3A, Supplemental Figures S4 and S5; Table S2). One CsGME1, two CsVTC1s, GDP-L-galactose phosphorylase 2s (CsVTC2s), and one L-galactose-1-phosphate phosphatase (CsVTC4-1) were also up-regulated by the F treatment (Figure 3B). The most tea L-gulonolactone oxidase (CsGLOX) and myo-inositol-3-phosphate synthase (CsMIPS) homolog genes were clearly up-regulated by Al stress only, whereas tea myo-inositol oxidase (CsMIOX) homolog genes were drastically up-regulated by both Al and F stresses (Figure 3B). Tea D-glucuronic acid reductases 1 (CsGluUR1), 2, and 4 were up-regulated by 0.4 mM Al and F, and only CsGluUR3 was specifically up-regulated by Al stress. Tea L-galactose dehydrogenase 1 (CsL-GalDH1) and L-galactono-1,4-lactone dehydrogenase 1 (CsGLDH1) were similarly induced by Al stress, but they were repressed by F treatment. Meanwhile, tea ascorbate peroxidase (CsAPX) and 2-keto-L-gulonate reductase (Cs2KGR), L-idonate dehydrogenase (CsL-IDH) homolog genes were expressed differentially in response to Al and F stresses, most tea monodehydroascorbate reductase (CsMDAR) and dehydroascorbate reductase (CsDHAR) genes were more significantly induced by 2.5 mM Al stress, and the tea transketolase (CsTK) genes were repressed by F stress at 12 and 48 h after treatment (Figure 3B). Thus, these transcriptome data supported the fact that while Al stress clearly induced most Vc and tartaric acid synthesis genes, F could also up-regulate sets of genes for the biosynthesis of Vc and tartaric acid in tea plant roots. The shikimic acid pathway uses metabolic precursors, phosphoenolpyruvate from glycolysis and erythrose 4-phosphate from the pentose phosphate cycle to generate 3-deoxy-D-arabino-heptulosonic acid 7-phosphate (DAHP) through a condensation enzyme DAHP synthase (DAHPS), which further generates multiple important metabolites and bioactive molecules. The shikimic acid pathway essentially leads to the biosynthesis of folic acid, salicylic acid and aromatic amino acids (tryptophan, phenylalanine, and tyrosine), as well as other intermediates such as gallic acid, which is glycosylated into β-glucogallin for the biosynthesis of galloylated catechins after condensation reactions with catechins [1]. As a very essential pathway for both primary and secondary metabolite biosynthesis, the shikimic acid pathway genes were more diverse in their expression patterns in response to Al and F stresses (Figure 4A,B, Supplemental Figures S4 and S5; Table S2). It appeared that Al and Al + F treatment induced a more significant up-regulation of most genes, from some isoforms of tea CsDAHPS, 3-dehydroquinate dehydratase (CsDHD), 3-dehydroquinate synthase (CsDHQS), to downstream shikimate kinase (CsSK) and chorismate synthase (CsCS) genes (Figure 4B). F treatment caused the repression of more gene isoforms than other treatments, suggesting that F toxicity inhibited gene expression, whereas Al treatment up-regulated the largest number of genes among these treatments. For genes involving the phenylpropanoid pathway that led to lignin and flavonoid biosynthesis, especially for the biosynthesis of flavonoids in tea plants, Al treatment also resulted in up-regulation to the largest extent, and the most gene isoforms for the pathways from tea phenylalanine ammonia-lyase (CsPAL) to serine carboxypeptidase-like Clade 1A (CsSCPL) (Figure 4B, Table S2). Particularly, it became more obvious that the majority of the genes involved in flavonoid biosynthesis were up-regulated to the biggest extent in Al-treated roots for 12 and 24 h. Only a small number of genes, including tea chalcone isomerase 5 (CsCHI5) and flavonoid 3′ 5′-hydroxylase 1 (CsF3′5′H1), and anthocyanidin reductase 2 (CsANR2), as well as several genes putatively involved in lignin biosynthesis, such as CsPAL2 and 3, cinnamate 4-hydroxylase 1 (CsC4H1) and 2, and 4-coumarate CoA ligase 1 (Cs4CL1) and 2 were most drastically up-regulated by Al + F and F treatment alone (Figure 4B). Again, 10 mM F treatment repressed more structural genes than other treatments (Figure 4B), indicating the inhibitory effects of F on the biosynthesis of catechins or other flavonoids. We then assayed the contents of catechins and insoluble proanthocyanidins (also, PAs or condensed tannins) in roots to further understand how Al and F stresses affected their accumulation. Tea roots usually contain large amounts of insoluble PAs as the major form of PAs. Catechins in roots, mainly present in the forms of epicatechin (EC), epigallocatechin gallate (EGCG), gallocatechin gallate (GCG), epigallocatechin (EGC), and catechin (C), and others such as gallocatechin (GC) and epicatechin gallate (ECG), are very minor components. As a minor component of the catechins in tea roots, GC contents were stimulated by F and Al + F treatments (Figure 5A). However, one of the major components in tea roots, EGC, was stimulated by 0.4 mM and 2.5 mM Al, as well as Al + F treatments (Figure 5B). C contents were stimulated by both 0.4 mM and 2.5 mM Al and by Al + F stresses at 2 and 3 days after treatment (Figure 5C). However, EC contents can be generally stimulated to higher levels under 2.5 mM Al, but EGCG contents were reduced by the 2.5 mM Al treatment at Day 3 and by the F treatments (10 mM F alone and Al + F combination) drastically (p < 0.05 or 0.01) (Figure 5D,E). GCG contents were also promoted by 2.5 mM Al at 6 and 12 h. ECG contents were, however, mostly repressed by the 2.5 mM Al, F and Al + F treatments (Figure 5G). While these soluble PAs were mostly not drastically changed, insoluble PAs were promoted by 2.5 mM Al and 2.5 mMAl + 10 mM F, indicating that increased stress intensity promoted the accumulation of insoluble PAs in the tea roots (Figure 5H). We also measured two major N-containing secondary metabolites, caffeine and theanine, in tea roots under Al and F stresses. Organic acid metabolism and amino acid synthesis are fundamentally connected in many pathways as a whole primary metabolic network in most organisms [37,46,47]. For instance, glutamate is formed through the reductive amination of 2-oxoglutarate (2OG) by glutamate dehydrogenase (GDH). The amidation of glutamate to form glutamine by glutamine synthetase (GS) is followed by the reductive transfer of the amide group to 2OG by glutamate synthetase (GOGAT) [1]. The 2.5 mM Al and 2.5 mM Al + 10 mM F could promote the accumulation of amino acids, including glutamine, glutamate, and theanine (Figure 6A, Table S2). However, 10 mM F treatment alone repressed most of these amino acids in the roots (Figure 6A). Correspondingly, two NADH-GOGAT genes were up-regulated by Al and Al + F, and transcripts of Fe-GOGAT genes were increased by Al treatment, as were CsGSIa, c, d, and tea theanine synthetase I (CsTSI), and CsGSIIa genes, which were consistent with increased levels of amino acids in the Al treatment (Figure 6A–C). Correspondingly, a NADH-GOGAT2 and two each of CsGDH1 and 3 were activated by the F treatment (Figure 6C), and they might have been negatively correlated with theanine and glutamine synthesis; this would be consistent with the negative effects of F on theanine contents in tea shoot tips and the negative impact on tea nutritional quality. The compound γ-ABA is an important bioactive amino acid and signaling molecule in the plant stress response [48]. Tea glutamate decarboxylase 1 (CsGAD1) and 2 were differentially up-regulated by F and Al stresses (Figure 6C), indicating that they differentially contributed to γ-ABA biosynthesis through the degradation of glutamate. Meanwhile, γ-ABA-shunted genes, including tea succinic semialdehyde dehydrogenase 3 (CsSSADH3), GABA transaminase (CsGABA-T) and L-theanine hydrolase 2.1 (CsPDX2.1) and ornithine decarboxylase 2 (CsODC2), were activated by F stress and Al treatment (Figure 6C), indicating that they also were attributable to γ-ABA accumulation by the prevention of γ-ABA degradation. Other γ-ABA-shunted genes were up-regulated by Al + F and 0.4 mM Al treatments. Arginine cycle genes, including biosynthesis genes for ornithine, citrulline, arginine, and ammonium (NH3), were also altered by Al and F stresses (Figure 6A). It has been reported that caffeine is found in tea root extrudes under Al stress [25]. Our data also showed that 0.4 mM or 2.5 mM Al drastically up-regulated major caffeine-biosynthesis genes, such as tea caffeine synthase 2 (CsTCS2), 3, 4, 8, theobromine synthase 4 (CsMXMT4), 5, 7-methylxanthosine synthase (CsXMT), AMP deaminase (CsAMPD), inosine monophosphate (IMP) dehydrogenase (CsIMPDH), as well as other up-stream biosynthesis genes, including S-adenosylmethionine synthases 1 (CsSAMS1), 2, S-adenosylhomocysteine hydrolase (CsSAHH), and amidophosphoribosyltransferase (CsPPAT) genes (Figure 6E,F). On the other hand, F treatment repressed most of these gene drastically, consistent with the inhibited caffeine accumulation in F- and F + Al-treated tea roots. We then examined the Al and F and the tea secondary metabolite contents in young leaves (apical bud and 1st leaf) after 10 days of treatments of Al, F, and Al + F, in comparison with those in the first day of treatments. The tea seedlings grown in 0.4 mM or 2.5 mM Al contained higher Al accumulation in young leaves after 10 days of cultivation compared to the beginning, indicating that Al can quickly accumulate in the young leaves, likely translocated from the roots. However, F treatment alone slightly reduced Al accumulation, whereas F treatment with 2.5 mM Al significantly reduced Al accumulation in young leaves, as compared with 2.5 mM Al treatment alone (Figure 7A), as did F contents in F and Al + F treatment, in which Al treatment reduced F contents in young leaves (Figure 7B). We measured for catechins in the tea young leaves to check the effects of Al and F treatments on tea nutrients. While most of the treatments did not change the contents of the catechin molecules, only the 2.5 mM Al treatment slightly increased the EGC and EC contents at 10 days, but the F treatment inhibited EC and EGCG contents (Figure 7C). For caffeine contents, both the 10 mM F and 2.5 mM Al + 10 mM F treatments reduced the caffeine content in young leaves, perhaps as a result of F accumulation in the young leaves at 10 days after treatments. The 0.4 mM Al tended to increase caffeine levels (Figure 7D). Similarly, theanine contents in 0.4 and 2.5 mM-Al-treated young leaves tended to increase as compared to their control. However, F treatment, either alone or together with Al, reduced the theanine content in the young leaves (Figure 7E). We also validated the expression patterns for the genes involved in TAC and organic acid and amino acid biosynthesis, and those involved with the catechin, caffeine, and theanine biosynthesis pathways in the tea roots under Al and F treatments. The genes encoding these secondary metabolic enzymes, such as amino acid metabolic genes CsGDH3 and CsGSId; flavonoid metabolic genes CsCHI4 and CsDFR4; tea caffeine synthase CsTCS4; and TAC genes CsCSY1, CsGOX1, CsOADC1, CsL-IDH1, and CsTK1, were examined for their responsive expression patterns to Al and F stresses (Supplemental Figure S6). Most genes displayed altered expression patterns in response to Al and F stresses, which were mostly consistent with transcriptome data (Supplemental Figure S6). The genes encoding for the transporters involved in the secretion of organic acids, including multidrug and toxin extrusion (MATE) and aluminum-activated malate transporter (ALMT), CsMATE1 and CsALMT1, displayed increasing transcript levels from the 2.5 mM Al treatment (Supplemental Figure S6). Although we only observed trace levels of citric acid but no malic acid in the culture media under Al and F stresses, that was probably because they were chelated with Al3+ and formed insoluble complexes in the tea root apoplast spaces. The continuously lowering pH of tea plantation soils is caused by multiple factors, including tea’s characteristic H+ secretion mechanism, Al and F stresses, NH3 fertilization, and organic acid secretion, or the raising of atmosphere CO2/acidic rains. Soil acidification becomes particularly severe after the long-term cultivation of tea plants for 20–30 years, which causes more heavy metal ions to become bioavailable and causes stronger rhizotoxicity in plant roots. The negative impacts of soil acidification and Al and F stresses on tea nutrition value and food safety have been reported. However, the details and mechanisms behind this are not understood. The present study showed that under Al and F stresses, tea roots continuously synthesize and secret oxalic acid, tartaric acid, and minor levels of citric acids, which may chelate extracellular Al for the detoxification of Al/F rhizotoxicity. Catechins, caffeine and theanine biosynthesis were differently stimulated by Al but repressed by F stresses. More importantly, increased Al and F accumulation and generally decreased catechins, caffeine, and theanine contents were observed, indicating that high Al and F concentrations could substantially affect tea nutritional quality and safety. Tea roots take up a wide range of inorganic elements or small organic molecules from the soil the aboveground parts of tea plants through vascular tissue transport. Meanwhile roots receive carbohydrates from source leaves through the shoots’ vascular tissue to develop root architectures and support root physiological activities. Understanding the glycolysis, TAC and organic acid metabolism and secretion, as well as the related phenylpropanoid pathway and amino acid metabolism in tea plant roots is critical for the genetic improvement of tea plants for safer teas of higher quality. The TAC, organic acid and amino acid metabolism pathways provide precursors for the majority of plant primary and secondary metabolism and energy re-generation [49]. As the core metabolic pathway, TAC provides precursors for the biosynthesis of fatty acid for lipids, amino acids for proteins, nucleic acids, polysaccharides for cell walls, the phenylpropanoid pathway towards both lignin and flavonoids, and other plant structures [37]. In plant roots, sources-derived carbohydrates undergo glycolysis to provide energies such as NADPH/NADH, ATP, and metabolic intermediates or precursors for TAC and other metabolism. Under abiotic stress, these pathways improve plant adaptability to survive the adversary environments since defense responses spend energy and cost metabolites [50]. The root organic acids, such as citric acid, malic acid, and oxalic acid, are also involved in plant stress responses by exudation by roots into the rhizosphere and soil, which can improve soil mineral uptake by releasing P ions from the Al-P precipitate and chelating and detoxifying toxic metals such as Al3+ [51,52,53]. Both Al and F treatments could induce the secretion of tartaric acid, shikimic acid and oxalic acid from roots. With the F treatment time extended, oxalic acid content decreased in the roots and increased in the media, indicating that oxalic acid may have been exported from the roots into the medium for detoxification (Figure 1D,G). Over time up until 24 h to 48 h, the tartaric acid contents in the media and roots were decreased, indicating that tartaric acid biosynthesis may be suppressed by 2.5 mM Al (Figure 1E,H). Under Al or F treatment, the shikimic acid contents in the roots were similarly changed with those in the media, indicating that shikimic acid was consistently biosynthesized in the root tissues and secreted into the medium (Figure 1F,K). The role of these extracellular organic acids for chelating excessive Al to detoxify Al toxicity is well documented [54,55]; however, their roles in tea roots and the rhizosphere in response to F stress are not clear. Obviously, the secretion and accumulation patterns of these organic acids induced by Al and F stresses are different. It is posited that these extracellular organic acids may inhibit F uptake as competing anions, or may compete with F to form salts with other metal ions such as Al, Fe, Ca, and Mn enriched in acidic soils [7,8,9,20], which is worthy of further investigation. MATE and ALMT are well-known for the plant root secretion of citric acid and malic acid, respectively, in response to Al or other heavy metal stresses [54,55]. The Al induction of these genes’ expression is regarded as one of the major Al tolerance mechanisms in many plants [51]. Indeed, an overexpression of TaALMT1 and HvACCT1 increased the exudation of malate and citrate, respectively, and enhanced aluminum tolerance [56,57]. An overexpression of MDH gene enhanced the enzyme activity of MDH, which also increased organic acid synthesis and improved the resistance of alfalfa roots to Al [58]. Our transcriptome data also showed the Al-induced up-regulation of many CsMATE and CsALMT genes. It has also been reported that tartaric acid can be sequestrated into the vacuole by VvALMT9 in grape berry, indicating that ALMTs could transport both malic acid and tartaric acid [59]. VvALMT9 homolog genes in the tea genome were also up-regulated at the highest threshold by Al stress; thus, CsALMT9 homologs could be involved in tartaric acid secretion by tea roots. Although so far, no report on the oxalic acid transporter has been reported, studies showed that two aquaporin transporters, MsPIP2;1 and MsTIP1;1, were positively affected by oxalate secretion from the root tips and Al accumulation in alfalfa root tips [60]. These organic acids also facilitate internal Al detoxification by being transported into root cells for a long-distance transport from roots to shoots through the xylem in the forms of various Al-organic acids complexes [25,54,55]. Thus, they affect eventual F and Al accumulations in tea leaves and thereby affect tea safety. Furthermore, it is clear that under normal conditions, tea roots also actively release organic acids to the root rhizosphere and soils for dissolving mineral elements and for root absorption, or to affect the microbiota in the rhizosphere and the soil for protection roles. Therefore, the release of organic acids by tea roots has multiple roles and is unnecessarily connected to Al or F tolerance. The analysis of the transcriptome data for the TAC and oxalate synthesis pathways revealed that Al treatment induced the expression of most metabolic genes, whereas F inhibited the expression of these genes, and Al treatment attenuated the inhibitory effects of F treatment on the expression of many genes, such as CsCSY1, CsMDH3, which were reported most often in regard to TAC and organic acid metabolism in tea and other plants under Al stress [35,50]. On the other hand, F treatment actually also up-regulated a set of these metabolic genes, which explained why F treatment also induced the root secretion of oxalate and tartaric acid. Interestingly, the genes induced by F treatment were simultaneously repressed by Al stress, including CsOADC2, indicating that Al and F stresses targeted different stress signaling pathways, both of which led to the secretion of oxalic and tartaric acids in the roots by activating oxalate synthesis genes. There was an antagonistic effect between Al and F on the TAC and the oxalic and tartaric acid biosynthesis pathway genes. Also, F treatment inhibited the expression of the CsL-IDH2, CsMIPS1 and CsMDAR1 genes involved in the tartaric acid synthesis pathway, and Al treatment up-regulated these genes; however, an Al + F combined treatment could alleviate the inhibition effects of F treatment (Figure 3). Reports have shown that high concentrations of F supplies inhibit the secretion of organic acids by tea roots [35]. Meanwhile, organic acids secreted by roots stimulated by Al stress could further solve and release more F, Pi and Al from the rhizosphere soil for tea plants [35]. In the detected organic acids, oxalic but not tartaric acids and citric acids were the major organic acids secreted to the medium, although tea roots produced high levels of citric acid, which could be transported to the stem through vascular tissues. Our study showed that Al stress up-regulated TAC genes such as MDH, CS and GOX involved in the biosynthesis of organic acids such as oxalic, tartaric, malic, and citric acids in tea roots and promoted the root secretion of oxalic and tartaric acids into the rhizosphere. These findings are somewhat consistent with previous studies [50,61,62]. MDH and CS activities were repressed by F stress (Figure 2 and Figure 4). For most genes involved in vitamin C and tartaric acid biosynthesis, 10 mM F stress and 2.5 mM Al stress seemed to counteract in the up-regulation and down-regulation of their expression. For instance, F treatment repressed CsMDAR2 and CsL-IDH2 genes, but Al drastically up-regulated their expression (Figure 3), suggesting that Al released the repression of gene expression by F treatment. Tea plants have evolutionarily adapted to acidic soils in tropical regions containing higher Al and F. Tea plants even require low levels of Al or F (<0.4 mM) to gain their optimal root development and growth [63]. Our data also showed that tea root’s most major secondary metabolites, such as catechins, theanine, and caffeine, were synthesized at the highest levels in the 0.4 mM SK media. Without the Al (0 mM Al control) or 2.5 mM Al concentration, there seemed to form a kind of stress on tea plant root growth and normal metabolism. The higher F stress (10 mM F) substantially reduced the accumulation of these secondary metabolites, particularly, theanine production (Figure 5A). This may be one of the reasons that high F causes the reduced tea quality of the young leaves by reducing theanine accumulation in the young leaves, since high F inhibited theanine biosynthesis in the tea roots and likely the translocation to the tea plants’ young leaves. Camellia sinensis (L.) O. Kuntze. cv. ‘Shuchazao’ and ‘Chuyeqi’ were used for gene expression analysis and Al and F treatment. Two-year-old tea seedlings were grown in hydroponic SK-nutrient solution in a greenhouse at 20–25 °C, with a light intensity of 1300 μmol m−2 s−1 and a photoperiod of 18 h per day/6 h per night until new tender roots emerged [15]. The healthy tea seedlings were transferred into fresh hydroponic solutions containing Al and F at different concentrations, e.g., 0, 0.4 mM Al, 2.5 mM Al in Al2(SO4)3, or 10 mM F (F was added to the in hydroponic solutions containing 0.4 mM Al) and 2.5 mM Al + 10 mM F (F was added to the in hydroponic solutions containing 2.5 mM Al) in NaF according previous report [15,64]. The hydroponic solutions were sampled at 0 h, 12 h, 24 h and 48 h for the determination of organic acids and metabolites. The roots and young leaves of these tea seedlings were collected and immediately stored in liquid nitrogen at various time for RNA analysis, ion measurement, and metabolite profiling. For each treatment, five different individual plants were collected for biological duplication under analyses. Details regarding the hydroponic cultivation are shown in the additional files (Supplemental Table S3), as described previously [33]. In order to understand how tea-plant roots respond to Al and F stresses, the roots of these tea seedlings were collected at various time intervals for organic acid analysis. The media were also collected for the measurement of the cumulative secretion of organic acids. HPLC (Agilent 1100, Santa Clara, CA, USA) was employed for the separation and determination of organic acids. A 5 mL sample was taken, lyophilized, re-dissolved with 0.25 mL hydrochloric acid solution with pH = 1.0, then passed through a 0.45 μm filter membrane, and then tested on the machine. Standard solutions of oxalic acid, citric acid, malic acid, succinic acid, shikimic acid and tartaric acid were prepared with 0.01 mol/L potassium dihydrogen phosphate as solvent. Liquid phase conditions: analytical column—BEH-C18 column (2.1 mm × 50 mm, 1.7 μm). Mobile phase: 0.01 mol/L potassium dihydrogen phosphate solvent. UV detector: G4212-60008 diode array detector. Detection wavelength: 210 nm. Flow rate: 1 mL/min; column temperature: 30℃. Injection volume: 20 μL. The experiment was repeated three times, and an ANOVA test was used for data analysis. RNA isolation from tea roots treated with Al and F in various manners were conducted with kits, as described previously [65]. The mRNA quality and purity were assessed using a NanoDrop 2000 spectrophotometer and RNA analyzer (Thermo Scientific, Wilmington, DE, USA) before being used for the construction of libraries using the Illumina TruseqTm RNA Sample Prep Kit method. The RNA sequencing was performed on an Illumina HiSeq2500 platform in triplicate for each sample. The clean data were mapped to the tea plant genome up to 80% by using TopHat2 software (version 2.1.0). Three Fragments per kilobase of transcript sequence per million base pairs sequenced (FPKM) were introduced to qualify the expression levels of the transcripts. The original data had been submitted to the NCBI database with the number PRJNA748249. The number of reads per kilobase per million mapped reads (RPKM) and read counts were calculated using express. Transcriptome data were analyzed and visualized using TBtools (version V1.108). RNA extraction from tea root samples was performed using polysaccharide polyphenol Plant Total RNA Extraction Kit (Tiangen Biotech, Beijing, China). The qRT-PCR analysis was performed using cDNA synthesized using the SweScript RT I First Strand cDNA Synthesis Kit (Takara, Dalian, China) according to the manufacturer’s instruction [66,67]. The house-keeping gene CsACTIN (TEA019484) and CsGAPDH (TEA003029) were used as an internal reference to normalize target gene expression levels. The SYBR Green qPCR Premix (Universal) was used for qRT-PCR with 20 μL reaction system; ddH2O: 8.2 μL, SYBR Green qPCR Premix: 10 μL, forward primers: 0.4 μL, reverse primers: 0.4 μL, and cDNA: 1 μL. Each sample was set up in triplicate, and the relative gene expression was calculated by the 2−ΔΔCt method. SPSS software (version 18) was used for data analysis. The primers are shown in Supplemental Table S4. All amino acids were extracted and quantified using an L-8900 high-speed amino acid analyzer (Hitachi, Ibaraki, Japan) following the protocol [33]. The amino acid standards, such as theanine, glutamine, glutamate, ornithine, and others, were all purchased from Aladdin (Shanghai, China) and Wako Pure Chemical Industries, Ltd. (Osaka, Japan). Catechins and caffeine were profiled with high-performance liquid chromatography (HPLC) according to the method described previously [68,69]. Reference standards EC, EGC, EGCG, C, CG, and GCG were purchased from Sigma-Aldrich (Steinheim, Germany). The data were from at least three experiments with biological repeats. Statistical analysis was performed using either Student’s two-tailed t-test when comparing treatments with controls or multiple comparisons together with the ANOVA multiple range test at the 0.05 probability level. The confidence limits 95 or 99% were defined as the significant between two-tailed data in the Student’s t-test. In summary, the present study showed that both Al and F stresses altered the TAC, organic and amino acid metabolism, and biosynthesis of secondary metabolites, such as catechins, theanine, and caffeine in tea roots and young leaves differentially. This was because tea plants are grown in the acidic soils of tropic/subtropic regions and tend to acidify tea plantation soils by the secretion of H+ under high Al and F concentrations. Our study not only presented the tea root responses to Al/F toxicities via the synthesis and secretion of organic acids to chelate and detoxify excess intercellular or intracellular Al and acidify the rhizosphere, but also the impact on extracellular pH value, inorganic phosphorous and other heavy metals’ solubility and availability to tea roots. Al–F stress-activated TAC and organic acid synthesis or secretion could also affect the biosynthesis of tea secondary metabolites in the tea roots. Moreover, high Al and F stresses negatively affected the accumulation of tea secondary metabolites in the young leaves and thereby their nutrient value. Comparisons of transcriptome data in combination with metabolite profiling did reveal the corresponding metabolic gene expression, which supported and explained the metabolite changes in the tea roots and young leaves under high concentrations of Al and F stress. This study provides new insights into the molecular aspects of Al- and F-stressed tea plants with regards to responsive metabolism changes, tolerance strategy establishment in tea plants, and also their impacts on metabolites in tea leaves that could influence tea nutritional quality and food safety. This study may also facilitate the future genetic improvement of low-Al and -F tea plant varieties.

PMC10003438

Liufeng Zhang,Yuancheng Wei,Shengtao Yuan,Li Sun

Targeting Mitochondrial Metabolic Reprogramming as a Potential Approach for Cancer Therapy

04-03-2023

cancer,mitochondria,metabolic reprogramming,drug development

Abnormal energy metabolism is a characteristic of tumor cells, and mitochondria are important components of tumor metabolic reprogramming. Mitochondria have gradually received the attention of scientists due to their important functions, such as providing chemical energy, producing substrates for tumor anabolism, controlling REDOX and calcium homeostasis, participating in the regulation of transcription, and controlling cell death. Based on the concept of reprogramming mitochondrial metabolism, a range of drugs have been developed to target the mitochondria. In this review, we discuss the current progress in mitochondrial metabolic reprogramming and summarized the corresponding treatment options. Finally, we propose mitochondrial inner membrane transporters as new and feasible therapeutic targets.

Targeting Mitochondrial Metabolic Reprogramming as a Potential Approach for Cancer Therapy Abnormal energy metabolism is a characteristic of tumor cells, and mitochondria are important components of tumor metabolic reprogramming. Mitochondria have gradually received the attention of scientists due to their important functions, such as providing chemical energy, producing substrates for tumor anabolism, controlling REDOX and calcium homeostasis, participating in the regulation of transcription, and controlling cell death. Based on the concept of reprogramming mitochondrial metabolism, a range of drugs have been developed to target the mitochondria. In this review, we discuss the current progress in mitochondrial metabolic reprogramming and summarized the corresponding treatment options. Finally, we propose mitochondrial inner membrane transporters as new and feasible therapeutic targets. Mitochondria, as important organelles in cells, produce ATP through oxidative phosphorylation [1]. In addition, mitochondria perform many other biological functions, including producing reactive oxygen species (ROS), reduction-oxidation (REDOX) molecules and metabolites, participating in anabolic metabolism, and regulating cell signaling and cell death [2]. Previous studies have shown that cancer is a mitochondrial metabolic disease [3]. The Warburg effect makes aerobic glycolysis the main source of energy for cancer cells [4], but new research results show that mitochondria in malignant cells are still active and closely related to the occurrence of cancer [5]. The role of mitochondria in the context of metabolic reprogramming is gradually being revealed, which has led to an increasing focus on targeted mitochondrial therapy. In this review, we summarize recent progress in our understanding of mitochondrial involvement in metabolic reprogramming. We describe the different targets and small molecule compounds that have been developed for mitochondria, summarize the characteristics of the various research and development ideas, and discuss the research and development difficulties caused by the high impenetrability of the inner mitochondrial membrane. Finally, we propose and collate therapeutic strategies that use mitochondrial intima transporters as therapeutic targets to enhance the efficacy of targeted mitochondria. Routine oxygen and nutrient supplies cannot meet the demands of cancer cells in solid tumors, which leads to significant metabolic stress [6] and necessitates metabolic reprogramming. It is widely accepted that metabolic reprogramming is a hallmark of cancer. Metabolic reprogramming is not stable and the interaction between several oncoproteins and tumor suppressors changes cellular metabolic pathways, thereby promoting tumor progression. Metabolic reprogramming alters the use of carbohydrates, lipids, and amino acids in cancer cells [6]. Glucose is the main carbon source and energy for cell growth and proliferation. Glucose undergoes three main pathways for energy conversion, including aerobic oxidation, glycolysis, and pentose phosphate pathway. Glucose metabolism is significantly different in cancer cells. Warburg effect is the dominant method of glucose metabolism in cancer cells. Tumor cells absorb a large amount of glucose by overexpressing glucose transporter 1 (GLUT1). Glucose is eventually converted into pyruvate, as the end product of aerobic glycolysis [7]. Subsequently, pyruvate is mostly converted into lactate. Lactate is then transported to the extracellular space by a monocarboxylate transporter 4 (MCT4) transporter and acidifies the tumor microenvironment [8]. Mitochondrial pyruvate carrier (MPC) transports the remaining pyruvate to mitochondria, where it is converted into Acetyl-CoA as a substrate for the tricarboxylic acid (TCA) cycle. Transcriptional activation of mitochondrial pyruvate dehydrogenase kinase 1 inactivates pyruvate dehydrogenase (PDH), ultimately preventing Acetyl-CoA production in mitochondria in tumor cells [9]. In addition, tumor cells overexpress pyruvate kinase M2, thereby blocking the conversion of phosphoenolpyruvate to pyruvate and enhancing other biosynthetic pathways to promote tumor cell proliferation [10]. The Warburg effect also increases nicotinamide adenine dinucleotide (NADH) generation and activates the pentose phosphate pathway to provide nicotinamide adenine dinucleotide phosphate (NADPH), which maintains REDOX homeostasis of cancer cells [11]. NADPH is used for reducing reactions in the synthesis of biomolecules, such as fatty acids, cholesterol, deoxyribose, tetrahydrofolate, and other substances. NADPH is also needed for the reduction of oxidized glutathione to maintain the REDOX balance in cancer cells [12]. Therefore, the abnormal pentose phosphate pathway has also become a hot spot in cancer research. Metabolic reprogramming of glucose implies that cancer cells bypass mitochondrial respiration and use aerobic glycolysis for energy supply. The Warburg effect explains glycolysis under aerobic conditions. Recent findings suggest that saturation of NADH shuttling, but not the need for cancer cell proliferation, facilitates aerobic glycolysis [13]. Increased mitochondrial respiration in breast tumor cells after lactate dehydrogenase A (LDHA) inhibition suggests that cancer cells retain the ability to oxidize glucose through oxidative phosphorylation (OXPHOS) in their mitochondria [14]. Glucose oxidation by the TCA cycle in tumor cells in isotope tracing experiments also confirmed the above thesis [15]. Lipid metabolic reprogramming mainly affects fatty acid biosynthesis, oxidation, intake, and modification [16]. Cellular lipids are mainly composed of fatty acids, triglycerides, sphingolipids, phospholipids, and cholesterol. Most lipids are derived from fatty acids. Lipids are the building blocks of cell membranes, second messengers, and cellular energy sources. In normal cells, extracellular uptake of lipids is the main pathway of providing cellular lipids, while in cancer cells, the PI3K/Akt signaling pathway upregulates enzymes required for fatty acid synthesis [17]. Increased de novo synthesis of fatty acids changes the composition of intracellular lipids. For instance, it decreases polyunsaturated fatty acid (PUFA) and increases monounsaturated fatty acid (MUFA). Overproduction of MUFA attenuates the damage caused by PUFA peroxidation in the presence of ROS [18]. Mitochondria are deeply involved in lipid reprogramming in tumor cells. As an intermediary for the TCA cycle, Acetyl-CoA is involved in the regulation of lipid metabolism in cancer cells [19]. Acetyl-CoA is an important substrate for fatty acid synthesis. Acetyl-CoA is regulated by three intracellular enzymes, including acyl-CoA synthetase short-chain family member 2 (ACSS2), ATP citrate lyase (ACLY), and Acetyl-CoA carboxylase (ACC). Furthermore, ACSS2 catalyzes the conversion of extracellular acetic acid to Acetyl-CoA, which is highly consumed by cancer cells [20]. Mitochondrial citric acid is transported to the cytoplasm via SLC25A1 and converted to Acetyl-CoA by ACYL [21]. On the other hand, ACC converts Acetyl-CoA into malonyl CoA during fatty acid synthesis [22]. ACLY connects lipid and glucose metabolism in tumor cells and forms a complex metabolic network. Tumor cells immensely need amino acids for protein synthesis. As an important component of tumor metabolic reprogramming, glutamine metabolic reprogramming plays an important role in maintaining tumor cell energy homeostasis, ROS balance, and the continuous activation of mTOR [23]. Some tumor cells consume large amounts of glutamine to meet their metabolic needs. Extracellular glutamine intake provides carbon and nitrogen for anabolism and energy production. Intracellular deamination of glutamine and its conversion into glutamate is catalyzed by phosphate-dependent glutaminases (GLS1 and GLS2) [24]. Glutamate is further catabolized through the TCA cycle. It is catalyzed to α-ketoglutaric acid (α-KG) by glutamate dehydrogenase (GDH) or aminotransferase or directly by glutathione cysteine ligase. Glutathione synthetase catalyzes the formation of glutathione (GSH) to maintain intracellular REDOX homeostasis. αKG enhances the TCA cycle and maintains mitochondrial integrity and activity through succinyl-CoA oxidation and nicotinamide adenine dinucleotide (NAD+) reduction [25]. The abnormal expression of regulatory factors in tumor cells often affects glutamine metabolism. These regulators are usually oncogenes and tumor suppressor genes. Among them, Myc binds to the promoter elements of glutamine transporters (such as SLC7A5 and SLC1A5) to induce glutamine transportation [26]. When KRAS is activated, the GOT2-GOT1-ME1 pathway can overexpress genes involved in glutamine decomposition [27]. Therefore, glutamine becomes the main carbon source for the TCA cycle. In addition, by upregulating NRF2, KRAS induces the NRF2-mediated antioxidant system to maintain REDOX balance and promote tumorigenesis [28,29] (Figure 1). As we mentioned above, mitochondrial metabolic reprogramming supports the development and progression of tumors. Given the importance in cancer cells, mitochondrial metabolism can be a promising point for the development of anti-tumor drugs [30]. Accordingly, we focus on TCA cycle, OXPHOS, ROS and mtDNA to understand targeting mitochondrial for the therapy of cancers. Many studies have shown that the Warburg effect is pivotal for the development and progression of tumors. However, recent studies have shown that the role of the TCA cycle and OXPHOS in tumor metabolism cannot be ignored [31,32]. The TCA cycle refers to Acetyl-CoA oxidization to H2O and CO2. The TCA cycle occurs in the mitochondria, which are the final metabolic pathways for carbohydrates, lipids, and amino acids. Abnormal levels of isocitrate dehydrogenase (IDH) and succinate dehydrogenase (SDH) can lead to abnormal function of the TCA cycle, which may be related to tumorigenesis [33]. IDH has three subtypes, including IDH1, IDH2, and IDH3. IDH catalyzes the oxidation and carboxylation of isocitrate to produce α-KG. Mutations in IDH1 and IDH2 genes lead to increased production of D-2 hydroxy-glutarate (2HG), contributing to the development of various malignancies such as acute myeloid leukemia, chondrosarcoma, cholangiocarcinoma, and glioma [34,35,36]. IDH Mutations are associated with highly heterogeneous tumor microenvironments, suggesting that targeting IDH mutations may effectively treat cancer [37]. The novel role of IDH in various malignant tumors has led to the development of IDH inhibitors. Enasidenib and ivosidenib are approved IDH inhibitors, which have shown significant clinical benefits in acute myeloid leukemia and refractory cholangiocarcinoma [38,39,40]. SDH consists of four subunits, including SDHA, SDHB, SDHC, and SDHD. It catalyzes the conversion of succinic acid to fumarate. SDH deletion has been found in gastrointestinal stromal tumors and paragangliomas [41]. Studies have shown that the downregulation of SDHC promotes epithelial-mesenchymal transition (EMT) and is accompanied by structural remodeling of mitochondria. SDHC downregulation is also associated with malignant progression, tumor heterogeneity, and drug resistance [42]. Therefore, targeted SDH can potentially treat cancer. Tumor necrosis factor receptor-associated protein 1 (TRAP1) is a mitochondrial chaperone protein belonging to the heat shock protein 90 (HSP90) family. It is highly expressed in many types of tumors. TRAP1 inhibits mitochondrial complex II, downregulates SDH activity, and promotes tumor growth [43,44]. In addition to pseudohypoxia, TRAP1 protects tumor cells from oxidative stress [43]. Several TRAP1 inhibitors are already available. Gamitrinib, a small-molecule TRAP1 and HSP90 inhibitor, is currently passing its phase I clinical trial in patients with advanced cancer, and the results of animal experiments show that gamitrinib is a safe and effective anticancer therapy [45]. The mitochondrial osmotic drug, DN401, is a newly discovered pan-inhibitor of HSP90 that inhibits the HSP90 family, including TRAP1. It has stronger anticancer activity than other HSP90 inhibitors [46]. Honokiol bis-dichloroacetate (HDCA) is a small-molecule compound that specifically targets TRAP1. HDCA can restore the TRAP1-dependent downregulation of SDH, reduce tumor cell proliferation, increase mitochondrial superoxide levels, and inhibit tumor growth by selective inhibition of TRAP1 [47]. P53, a well-known tumor suppressor, can inhibit the expression of pyruvate dehydrogenase kinase 2 (PDK2), thus activating the oxidative metabolism of mitochondria and promoting the TCA cycle [48]. In addition, p53 can also induce mitochondrial GLS2 expression to enhance GSH synthesis and α-KG, thus promoting the TCA cycle [49]. P53 function is often impaired in tumors. Murine double minute 2 (Mdm2) and murine double minute X (MdmX) are major negative regulators of P53. They can independently or together inhibit p53 [50]. Blocking Mdm2 and MdmX is a potential strategy for treating tumors. Idasanutlin (RG7388) is a small-molecule Mdm2 inhibitor currently in phase III of trials. In vivo results showed that RG7388 effectively reduced cell proliferation and induced p53-dependent pathways, cell cycle arrest, and apoptosis, thereby inhibiting tumor growth [51]. Milademetan is also a small-molecule inhibitor of Mdm2. It has been used in the clinical trials of advanced solid tumors and hematological malignancies, such as liposarcoma and acute myeloid leukemia [52]. ALRN-6924 is a dual-target inhibitor of Mdm2/MdmX, which has been used in a phase I clinical trial. ALRN-6924 stably activates p53-dependent transcription at single-cell and single-molecule levels. It exhibited biochemical and molecular targeting activity in in vitro and in vivo studies of leukemia [53]. Current clinical trials have shown that ALRN-6924 is well tolerated and has antitumor activity in patients with solid tumors or lymphomas carrying wild-type TP53 [54]. FL118 is a camptocamptoid analog. FL118 can change the targeting specificity of the Mdm2-MdmX E3 complex from p53 to MdmX, thereby accelerating MdmX degradation and activating p53-dependent aging in colorectal cancer (CRC) cells [55]. The combination of FL118 and cisplatin can synergically kill drug-resistant pancreatic cancer cells, prevent the globular formation of treatable pancreatic cancer stem cells, and overcome chemoresistance [56]. OXPHOS also plays an important role in tumor metabolism. OXPHOS converts oxygen to water and simultaneously releases energy for ATP production. Studies have shown that OXPHOS can provide ATP for tumor proliferation [57]. The electron transport chain (ETC) is an important component of OXPHOS. ETC is composed of complex I-IV, CoQ, and Cyt c. ETC is necessary for tumor growth. Mitochondrial complexes I and II transfer electrons to panquinone, resulting in panthenol production. Complex III oxidizes panthenol to panquinone. The absence of mitochondrial complex III impairs tumor growth. Tumor growth requires the ETC-mediated oxidation of panthenol [31]. Several types of tumors, including CRC, ovarian cancer, acute myeloid leukemia, and glioblastoma, have somatic mtDNA mutations of complex I, III, or IV [58]. In addition to ATP, mitochondrial respiration also produces biosynthetic precursors such as aspartic acid. ETC inhibition promotes activating transcription factor 4 (ATF4) and mTORC1 signaling pathways by consuming aspartic acid and asparagine. The combination of ETC inhibitor and restriction of aspartic acid impaired tumor growth in animal models [59]. Complex I is located at the frontline of the respiratory chain. As a major producer of proton gradients in ETC, complex I is a suitable target for the development of an OXPHOS inhibitor. As a marketed drug, metformin has received much attention for its ability to inhibit complex I, but its low potency has limited the potential for re-purposing [60]. BAY87-2243 was also promising, but severe vomiting in phase I trials prevented its further development. In recent years, more and more efficient and selective small-molecule drugs have been developed [61,62]. EVT-701, a novel small-molecule inhibitor targeting diffuse large B-cell lymphoma and NSCLC, has demonstrated good efficacy in vitro and in vivo. It should be emphasized that the original structure of BAY87-2243 was deliberately modified to prevent severe side effects in clinical trials [63]. Furthermore, Kazuki Heishima et al. found that the plant extract, petasin (PT), is a complex I inhibitor that mainly inhibits tumor growth in animal models, with high efficiency and low toxicity [64]. In addition, human epidermal growth factor receptor 2 (ERBB2) inhibitor, mubritinib, has anticancer properties by inhibiting complex I [65]. The steroid saponin Gracillin is a natural compound with potent antitumor activity. Its antitumor property depends on mitochondrial complex II inhibition [66]. In vitro studies have shown that Gracillin inhibits mitochondrial complex II-mediated energy production, thereby reducing the viability and colony formation of breast cancer cells. It has shown marked antitumor activity in animal models [67]. Atovaquone is an FDA-approved drug for the treatment of malaria. It is also a potent selective OXPHOS inhibitor with anticancer properties through mitochondrial complex III inhibition [68]. Arvinder et al. showed that atovaquone can inhibit ovarian cancer cell proliferation and growth in vitro and in vivo [69]. Two complex IV inhibitors have been approved for cancer treatment: mitotane for adrenocortical cancer, and arsenic trioxide for acute promyelocytic leukemia. Arsenic trioxide has shown promising results in the preclinical studies of glioblastoma (GBM) [70]. In addition, loss of BTB and CNC homology1 (BACH1) has been reported to increase the sensitivity of some types of cancer to ETC inhibitors (such as metformin). It indicates that combined inhibition of ETC and BACH1 may effectively treat cancer [66,71]. Electron leakage in ETC results in the conversion of O2 to O2− in the mitochondrial matrix. O2− is one of the ROS with strong oxidizing properties. Normal cells use antioxidant enzymes (catalase, peroxidase, glutathione peroxidase, and superoxide dismutase) and small molecules of antioxidants (vitamin C, vitamin E, and beta-carotene) to remove ROS. Cancer cells produce high levels of ROS, which disrupt REDOX homeostasis and activate many oncogenic signaling pathways [72,73]. On the other hand, ROS also exert anticancer activity. The absence of cysteine desulfurase (NFS1) significantly enhances the sensitivity of CRC cells to oxaliplatin. It induces apoptosis, necrosis, pyroptosis, and iron-mediated cell death by increasing ROS levels. High expression of NFS1 is likely related to MYC [74]. A series of compounds have been discovered to inhibit ROS. Lexibulin blocks ROS production and inhibits tumor growth through endoplasmic reticulum (ER) stress [75]. Bavachin can cause ROS accumulation and induce iron-mediated death via the STAT3/P53/SLC7A11 axis [76]. Darinaparsin, an organic arsenic molecule with anti-cancer activity, was approved in Japan in June 2022. It can induce G2/M cell cycle arrest and apoptosis in tumor cells by disrupting mitochondrial function and increasing ROS production [77]. Curcin C, a type I ribosome-inactivating protein, can increase ROS levels in osteosarcoma cells, alter mitochondrial membrane potential, and weaken the antioxidant system, thereby inhibiting the proliferation of various osteosarcoma cell lines [78]. Auriculasin also exerts anticancer effects through ROS. Auriculasin induces ROS production in a concentration-dependent manner to promote CRC cell apoptosis and iron-mediated death [79]. As a multi-copy genome, mtDNA is highly mutated and plays an important role in tumorigenesis and tumor progression [80]. The development of mitochondrial genome tools has markedly advanced research on mtDNA mutations. For example, mutations of the MT-ATP6 and MT-ND5 genes have been shown to increase ROS levels to promote tumor growth. Mutated mtDNA also enhances metastasis via ROS [81,82]. CCC-021-TPP was developed as a small molecule compound targeting ND6 A14582G mutation in mtDNA of non-small cell lung cancer. CCC-021-TPP can increase mitochondrial ROS production and induce mitochondrial autophagy to inhibit cancer progression [83]. Huang et al. designed and synthesized N-(N′,N′-diethanolaminopropyl) benzothiophenonaphthalimide (7C). They found that this compound effectively induces an mtDNA sequence named HRCC, thereby reducing mitochondrial membrane potential, increasing ROS production, and inhibiting tumor growth [84]. Inhibition of mitochondrial metabolism can effectively prevent tumor progression. However, there are several challenges. For example, ROS is a double-edged sword for cancer survival [85]. Although the accumulation of an excessive amount of ROS can undermine cancer cell survival, DNA damage caused by high levels of free radicals and genomic instability increase the risk of cancer [86]. In addition, inhibition of ROS alone has no significant effect on tumor growth [87], which means that extreme control of ROS production cannot be therapeutic. Developing compounds that target the p53 pathway is also extremely challenging. How p53 prevents tumor development is still unclear, and most tumor cells contain at least a dysfunctional tp53, making it an undruggable target [88]. Recent clinical studies have shown that targeting OXPHOS is not very feasible. IACS-010759, a small molecule inhibitor targeting complex I, had a narrow therapeutic index and serious side effects such as elevated lactic acid level and neurotoxicity in a phase I clinical study [89]. Therefore, it is necessary to monitor the toxicity of anti-tumor drugs targeting complex I. It is worth noting that the specific structure of mitochondria itself is also a source of difficulty in drug development. From the outside to the inside, mitochondria can be divided into five functional regions: outer mitochondrial membrane (OMM), intermembrane space, inner mitochondrial membrane (IMM), the cristae space and the mitochondrial matrix [90]. Even though the outer mitochondrial membrane appears to be highly permeable, when confronted with the inner mitochondrial membrane, there is tremendous difficulty for molecules. Therefore, the development of compounds that target intracellular mitochondrial membrane transporters is emerging as an efficient and effective option (Figure 2). Mitochondria utilize a variety of highly specific transporters to support molecules exchange. Currently, transporters located in the inner mitochondrial membrane mainly include members of the families SLC25, SLC56, SLC1 and MPC. Although the transport substrates vary between families and their members, the abnormal expression of several transporters has been found in cancer to varying degrees, making it possible to target mitochondrial endo-membrane transporters. The SLC25 family (mitochondrial carrier family, MCF) consists of 53 members and is the largest solute transporter family in humans [91]. All carriers possess a tripartite structure with three tandem repeats of homologous domains of about 100 amino acids. Each repeat contains two hydrophobic stretches [92]. MCs have six trans-membrane helices, with the N- terminal and C-terminal located on the cytosolic side. Three replicates are connected by two loops on the cytosolic side, and two transmembrane α-helices in each replicate are connected by three loops on the matrix side [93]. Based on substrate specificity, MCs are classified into four groups: amino acids carriers, nucleotides and dinucleotide carriers, carboxylates and keto acids carriers, and carriers of additional substrates [94]. Previous studies have revealed the close relationship between SLC25 and carbon sources in cancer cells. As the source of Acetyl-CoA, citrate plays a significant role in fatty acid synthesis in the cytoplasm. Meanwhile, citrate is involved in the Krebs cycle and oxidative phosphorylation in mitochondria [95]. SLC25A1, also named mitochondrial citrate/isocitrate carrier (CIC), is the only known transporter located in the inner mitochondrial membrane. CIC exchanges mitochondrial and cytosolic citrate [96]. Previous studies reported the overexpression of CIC in several types of cancers. In CRC, PPARγ co-activator 1α (PGC1α) upregulated CIC expression. In addition, low expression of SLC25A1 significantly inhibited the growth of CRC cells by inhibiting G1/S cell cycle progression and inducing apoptosis [97]. CIC enhanced de novo lipid synthesis and upregulated OXPHOS to sustain the survival of CRC cells [98]. In non-small cell lung cancer (NSCLC), CIC is highly expressed at metastatic sites or during acute and chronic hypoxia [99]. CIC enables CSCs to use citric acid for mitochondrial respiration and mitigates the deleterious effects of ROS produced by the activation of the IDH2-NADPH system [96]. SLC25A8, also known as mitochondrial uncoupling protein 2 (UCP2), uses four-carbon metabolites and Ca2+ as its substrates. UCP2 translocates mitochondrial glutamine-derived aspartate into the cytoplasm and supports pancreatic cancer growth [100]. Mitochondrial ROS are the main source of intracellular oxidative stress. ROS can damage biomolecules, induce the conversion of guanine to 8-oxo-guanine, oxidize amino acids, cysteine, and methionine, and facilitate lipid peroxidation [101,102,103]. UCP2 maintains ROS at acceptable levels and prevents mitochondrial and cellular dysfunction [104]. It plays a contradictory role in tumorigenesis. Loss of UCP2 leads to metabolic reprogramming of colonic cells and impairs REDOX homeostasis, facilitating malignant transformation [105]. On the other hand, UCP2 overexpression is observed in advanced tumors and is associated with decreased survival. UCP2 overexpression is thought to be associated with the Warburg effect [106,107]. UCP2 catalyzes the exchange of malate, oxaloacetic acid, and aspartate with phosphate and exports mitochondrial C4 metabolites to the cytoplasm [108]. Ectopic expression of UCP2 in cancer cells leads to the metabolic transition from mitochondrial oxidative phosphorylation to glycolysis [106]. SLC25A10, also known as dicarboxylate carrier, plays an important role in energy metabolism and REDOX homeostasis. It mainly transports malate, phosphate, succinate, sulfate, and thiosulfate, providing substrates for sulfur metabolism and gluconeogenesis. SLC25A10 is highly expressed in CRC, human osteosarcoma, ovarian cancer, and lung cancer. Knockdown of SLC25A10 can significantly inhibit the proliferation of cancer cells and increase their glutamine dependence [109,110,111,112]. SLC25A11 encodes the carrier of oxglutaric acid, and SLC25A12 encodes the carrier of aspartic acid-glutamate 1 [92,113]. Both of them are located in the inner mitochondrial membrane and together constitute the malate-aspartic acid shuttle system. Oxyglutaric acid carriers transport cytoplasmic malic acid to the mitochondrial matrix and export α-ketoglutaric acid from the mitochondrial matrix to the cytoplasm. Malate dehydrogenase converts mitochondrial malic acid into oxaloacetic acid. Then, aspartic aminotransferase converts oxaloacetic acid to aspartic acid, which will finally be transported to the cytoplasm by the aspartic acid-glutamate carrier 1 [114]. Due to the less permeable of IMM to NADH [115], malate dehydrogenase catalyzes the oxidation of malate to oxaloacetate and simultaneously reduces mitochondrial NAD+ to NADH/H+ to produce ATP. The malate-aspartic acid shuttle is essential for glycolysis. The expression level of SLC25A11 is closely related to cancer. The expression level of SLC25A11 in normal alveolar epithelial cells and inflammation transiently upregulates SLC25A11 in non-cancerous epithelial cells. However, the expression of SLC25A11 is much higher in NSCLC tissues than in normal lung tissue [116]. SLC25A11 increases mitochondrial membrane potential in cancer cells. Mitochondria rely on the malate-aspartate NADH shuttle (MAS) system for NADH transportation and ATP production. SLC25A11 knockdown significantly reduced ATP production and inhibited cancer cell proliferation by blocking the mTOR phosphorylation and downregulation of c-Myc and eIF4B [116]. SLC25A12 overexpression in liver cancer is associated with poor prognosis. Acetylated histones promote the expression of SLC25A12 by regulating cAMP response element-binding protein (CREB) function. Silencing of SLC25A12 resulted in G1/S cycle arrest of HepG2 cells and significantly impaired their proliferation [117]. However, low expression of SLC25A12 has been identified as a contributing factor to lung metastasis due to the deregulated folate pathway in aspartate/glutamate carrier 1 (AGC1) deficiency [118]. In addition, Zhang et al. indicated that the abnormal overexpression of SLC25A29 in cancer helps arginine transportation into mitochondria and upregulates mitochondrial NO, thereby suppressing mitochondrial respiration, enhancing glycolysis, and promoting cancer progression [119]. SLC25A51 is a newly identified mammalian mitochondrial NAD+ transporter [120]. Previous studies have confirmed that SLC25A51 is significantly overexpressed in human hepatocellular carcinoma (HCC) and enhances glycolysis and HCC progression by activating sirtuin 5 (SIRT5) [121]. SLC25A18 transports glutamate through the inner mitochondrial membrane. Increased expression of SLC25A18 inhibits the Warburg effect and cell proliferation through the Wnt/β-catenin pathway, leading to a better prognosis in CRC [122]. The SLC56 family, also known as sideroflexins (SFXN), contains five homologs: SFXN1, SFXN2, SFXN3, SFXN4, and SFXN5. All SFXN members are highly conserved mitochondrial transmembrane proteins, whose N-terminus and C-terminus have the same topological structure [123]. Recently, it was discovered that SFXN1 is a serine transporter [124]. SFXN1 and SFXN3 are highly homologs. SFXN1 is a transporter for serine, alanine, glycine, and cysteine [123]. As the main source of single carbon units for biosynthesis, serine can be catabolic into glycine by serine hydroxymethyltransferase 2 (SHMT2) in the mitochondria. Therefore, SFXN1 closely regulates serine and glycine levels and alanine synthesis in the mitochondria. SXFN1 is strongly associated with lung cancer. Compared with paracancerous tissues, the mRNA expression of SFXN1 is significantly increased in cancer tissues, and SFXN1 promotes the progression of NSCLC by activating the mTOR signaling pathway [125]. The mitochondrial shuttle process of pyruvate connects glycolysis and oxidative phosphorylation. In normal cells, pyruvate is mostly produced by glycolysis, and the cytoplasmic metabolism of pyruvate is controlled by the cellular microenvironment. Pyruvate is usually converted to pyruvate and transported to extracellular space under hypoxia. In the presence of sufficient oxygen, pyruvate is transported to the mitochondrial matrix by the mitochondrial pyruvate carrier and oxidized to Acetyl-CoA to participate in the TCA cycle. MPC belongs to the SLC54 family. Human MPC consists of the MPC1 and MPC2 dimer [126]. Loss of one MPC subunit leads to the degradation of the other MPC subunit, preventing pyruvate transportation to the mitochondria [127]. Unlike normal cells, pyruvate oxidation is often restricted in cancer cells because of downregulated mitochondrial carriers of pyruvate. In fact, both of these transporters, particularly MPC1, are downregulated or absent in most cancer cells, and low MPC expression is associated with poor survival. MPC1 overexpression in renal cell carcinoma inhibited tumor growth and invasion in vivo [128]. Increased expression of MPC1 restored the mitochondrial metabolism of pyruvate and inhibited glycolysis. Therefore, MPC1 is considered a tumor suppressor gene. MPC1 affects cancer progression by regulating tumorigenicity, tumor stemness, and chemoresistance [129,130,131]. Several molecules regulate MPC1 to interfere with cancer cell proliferation. Lysine demethylase 5A (KDM5A), a substance originally identified as a retinoblastoma-binding protein, regulates MPC1 expression by demethylating lysine 4 of histone H3 (H3K4) at the transcriptional level in pancreatic ductal cancer cells [132]. In hepatocellular carcinoma cells, PGC1α forms a complex with NRF1 and binds to the MPC1 promoter, ultimately increasing ROS formation and inducing apoptosis of HCC cells [133]. Up to now, several MPC inhibitors have been discovered. UK-5099 is a standard small-molecule MPC inhibitor that is specific for MPC at low concentrations and is often used as an instrumental drug in basic research [134]. Zaprinast is a specific MPC inhibitor that inhibits pyruvate-driven O2 consumption in brain mitochondria and blocks MPC in liver mitochondria [135]. 7ACC2 is also a potent MPC inhibitor that can continuously block extracellular lactate uptake by promoting intracellular pyruvate accumulation [136]. In addition, Wesley, T. et al. found through the pharmacophore model that carsalam, six quinolone antibiotics, and 7ACC1 and 7ACC2 shared pharmacophore, which was a new MPC inhibitor [137] (Figure 3). Han et al. revealed that SLC1A5 (ASCT2) transports glutamine to the mitochondria and plays an important role in cancer metabolism [138]. SLC1A5 is involved in the regulation of many oncogenic signaling pathways. Studies have shown that STAT3 regulates MYC expression in acute myeloid leukemia (AML), thereby controlling SLC1A5 transcription and OXPHOS and promoting the survival of leukemia stem cells [139]. Other studies have shown that neural precursor cells inhibit autophagy and mitochondrial metabolism by downregulating Unc51-like kinase 1 (ULK1) or ASCT2, thereby inhibiting the growth and survival of pancreatic cancer cells [138]. In addition, SLC1A5 expression was positively correlated with the number of tumor-infiltrating B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells in HCC and low-grade glioma (LGG), indicating its role in regulating tumor immunity [140]. In conclusion, SLC1A5 is a key target for cancer therapy. Recent findings on metabolic reprogramming highlight the importance of mitochondria. Mitochondria are involved in metabolic reprogramming, while the particularity of its structure and the diversity of its functions hinder the development of targeted drugs. The discovery of mitochondria-specific transporters supports mitochondrial phenotypic changes in tumor cells and provides new opportunities for developing new anticancer drugs.

PMC10003440

Tetiana Bukreieva,Hanna Svitina,Viktoriia Nikulina,Alyona Vega,Oleksii Chybisov,Iuliia Shablii,Alina Ustymenko,Petro Nemtinov,Galyna Lobyntseva,Inessa Skrypkina,Volodymyr Shablii

Treatment of Acute Respiratory Distress Syndrome Caused by COVID-19 with Human Umbilical Cord Mesenchymal Stem Cells

23-02-2023

COVID-19,acute respiratory distress syndrome,mesenchymal stem cells,cytokine,microRNA,correlation,dynamic changes

This study aimed to identify the impact of mesenchymal stem cell transplantation on the safety and clinical outcomes of patients with severe COVID-19. This research focused on how lung functional status, miRNA, and cytokine levels changed following mesenchymal stem cell transplantation in patients with severe COVID-19 pneumonia and their correlation with fibrotic changes in the lung. This study involved 15 patients following conventional anti-viral treatment (Control group) and 13 patients after three consecutive doses of combined treatment with MSC transplantation (MCS group). ELISA was used to measure cytokine levels, real-time qPCR for miRNA expression, and lung computed tomography (CT) imaging to grade fibrosis. Data were collected on the day of patient admission (day 0) and on the 7th, 14th, and 28th days of follow-up. A lung CT assay was performed on weeks 2, 8, 24, and 48 after the beginning of hospitalization. The relationship between levels of biomarkers in peripheral blood and lung function parameters was investigated using correlation analysis. We confirmed that triple MSC transplantation in individuals with severe COVID-19 was safe and did not cause severe adverse reactions. The total score of lung CT between patients from the Control and MSC groups did not differ significantly on weeks 2, 8, and 24 after the beginning of hospitalization. However, on week 48, the CT total score was 12 times lower in patients in the MSC group (p ≤ 0.05) compared to the Control group. In the MSC group, this parameter gradually decreased from week 2 to week 48 of observation, whereas in the Control group, a significant drop was observed up to week 24 and remained unchanged afterward. In our study, MSC therapy improved lymphocyte recovery. The percentage of banded neutrophils in the MSC group was significantly lower in comparison with control patients on day 14. Inflammatory markers such as ESR and CRP decreased more rapidly in the MSC group in comparison to the Control group. The plasma levels of surfactant D, a marker of alveocyte type II damage, decreased after MSC transplantation for four weeks in contrast to patients in the Control group, in whom slight elevations were observed. We first showed that MSC transplantation in severe COVID-19 patients led to the elevation of the plasma levels of IP-10, MIP-1α, G-CSF, and IL-10. However, the plasma levels of inflammatory markers such as IL-6, MCP-1, and RAGE did not differ between groups. MSC transplantation had no impact on the relative expression levels of miR-146a, miR-27a, miR-126, miR-221, miR-21, miR-133, miR-92a-3p, miR-124, and miR-424. In vitro, UC-MSC exhibited an immunomodulatory impact on PBMC, increasing neutrophil activation, phagocytosis, and leukocyte movement, activating early T cell markers, and decreasing effector and senescent effector T cell maturation.

Treatment of Acute Respiratory Distress Syndrome Caused by COVID-19 with Human Umbilical Cord Mesenchymal Stem Cells This study aimed to identify the impact of mesenchymal stem cell transplantation on the safety and clinical outcomes of patients with severe COVID-19. This research focused on how lung functional status, miRNA, and cytokine levels changed following mesenchymal stem cell transplantation in patients with severe COVID-19 pneumonia and their correlation with fibrotic changes in the lung. This study involved 15 patients following conventional anti-viral treatment (Control group) and 13 patients after three consecutive doses of combined treatment with MSC transplantation (MCS group). ELISA was used to measure cytokine levels, real-time qPCR for miRNA expression, and lung computed tomography (CT) imaging to grade fibrosis. Data were collected on the day of patient admission (day 0) and on the 7th, 14th, and 28th days of follow-up. A lung CT assay was performed on weeks 2, 8, 24, and 48 after the beginning of hospitalization. The relationship between levels of biomarkers in peripheral blood and lung function parameters was investigated using correlation analysis. We confirmed that triple MSC transplantation in individuals with severe COVID-19 was safe and did not cause severe adverse reactions. The total score of lung CT between patients from the Control and MSC groups did not differ significantly on weeks 2, 8, and 24 after the beginning of hospitalization. However, on week 48, the CT total score was 12 times lower in patients in the MSC group (p ≤ 0.05) compared to the Control group. In the MSC group, this parameter gradually decreased from week 2 to week 48 of observation, whereas in the Control group, a significant drop was observed up to week 24 and remained unchanged afterward. In our study, MSC therapy improved lymphocyte recovery. The percentage of banded neutrophils in the MSC group was significantly lower in comparison with control patients on day 14. Inflammatory markers such as ESR and CRP decreased more rapidly in the MSC group in comparison to the Control group. The plasma levels of surfactant D, a marker of alveocyte type II damage, decreased after MSC transplantation for four weeks in contrast to patients in the Control group, in whom slight elevations were observed. We first showed that MSC transplantation in severe COVID-19 patients led to the elevation of the plasma levels of IP-10, MIP-1α, G-CSF, and IL-10. However, the plasma levels of inflammatory markers such as IL-6, MCP-1, and RAGE did not differ between groups. MSC transplantation had no impact on the relative expression levels of miR-146a, miR-27a, miR-126, miR-221, miR-21, miR-133, miR-92a-3p, miR-124, and miR-424. In vitro, UC-MSC exhibited an immunomodulatory impact on PBMC, increasing neutrophil activation, phagocytosis, and leukocyte movement, activating early T cell markers, and decreasing effector and senescent effector T cell maturation. COVID-19 has expanded internationally, resulting in an ongoing pandemic that has infected over 755 million individuals and killed over 6.8 million people in over 200 nations (https://covid19.who.int/ (accessed on 14 February 2023)). COVID-19 causes fever, fatigue, muscular discomfort, diarrhea, and pneumonia, and it can be fatal in severe cases [1]. The levels of proinflammatory cytokines rise dramatically in peripheral blood plasma during COVID-19 progression [2]. The cytokine levels of IL-2, IL-6, IL-7, G-CSF, IP10, MCP1, MIP1A, and TNF-α are determined and were mostly found to be elevated in severe COVID-19 patients with ARDS development related to lung damage and tissue fibrosis [3]. This ‘cytokine storm’ syndrome is accompanied by a decline in the overall number of T cells, T helper (CD4+) and cytotoxic (CD8+) T cells, natural killer (NK) cells, and regulatory T cells, which compromises the immune system [4]. Furthermore, patients infected with SARS-CoV-2 had high levels of monocytes and neutrophils [5,6]. Therefore, the normalization of COVID-19-caused immune system imbalance is a promising task for the effective treatment of this disease. Nowadays, particular interest is focused on detecting circular plasma microRNA as key regulators of specific gene expression and diagnostic markers. Numerous studies indicate miR-146, miR-27, miR-221, miR-21, miR-126, miR-92a-3p, and miR-133 are dysregulated in COVID-19 [7]. miR-27a-3p was shown to inhibit M2 macrophage polarization in an acute lung injury model in mice [8]. miR424-5p is significantly upregulated in COVID-19 patients with thrombotic disease [9]. In addition, increased miR-21 expression was reported in neutrophils and macrophages in a sepsis model in mice [10]. Thus, studying the impact of the therapy with umbilical cord mesenchymal stem cells (UC-MSC) on the plasma levels of these miRNAs may help to understand their therapeutic effect on the development of acute respiratory distress syndrome (ARDS) caused by COVID-19. MSC therapy is a promising approach to preventing the development of ARDS and multiple organ dysfunction caused by COVID-19. Based on the results of already completed clinical trials, the safety and efficacy of MSC as a regulator of the cytokine storm in treating ARDS were proven [3,11,12,13,14,15,16,17,18,19,20,21,22,23]. In addition, the potential therapeutic effects of MSC include the reduction of inflammation, prevention of tissue fibrosis, protection of alveolar cells, and stimulation of the regeneration of inflamed tissue, which can be strongly beneficial for COVID-19-injured organs [24,25,26,27,28]. The MSC transplantation does not require HLA-typing, and these cells have weak immunogenicity [29,30]. The fetoplacental complex and umbilical cord (UC) in particular are rich sources of mesenchymal stromal cells (MSC) with high proliferative properties. UC-MSC possess great immunomodulatory properties, can alter immune cell function, modulate immune responses, and reduce inflammation-induced lung injury in different pre-clinical and in vitro models [31,32]. The analysis of the clinical trials suggests that MSC fail to exert significant anti-inflammatory effects in the context of COVID-19 [33], although the anti-inflammatory actions of MSC may attenuate inflammation in the lung through different mechanisms described earlier [34,35]. Previously, MSC were shown to modulate the development, activation, and chemotaxis of dendritic cells (DCs), T cells, and B cells. MSC may be used to augment and maintain the percentage of CD28+ T cells in humans [36]. Thus, the study of the influence of UC-MSC on the immune cells of COVID-19 patients could be promising for recognizing their therapeutic potential in the treatment of COVID-19-caused ARDS. However, different protocols are currently in use for treating COVID-19 with MSC therapy varying doses of injected cells, transplant rate, and intervals between MSC infusions [37]. Moreover, numerous data are collected about the impact of MSC on the levels of proinflammatory cytokines and different immune cell counts during COVID-19 development [28]. To date, the mechanism of the therapeutic effect of MSC on the course of ARDS, acute myocardial damage, and the state of the immune system in patients with COVID-19 have not yet been thoroughly studied. The levels of microRNAs in the plasma of patients with COVID-19, as key regulators of gene expression, have not yet been sufficiently studied, especially after MSC transplantation. In addition, the influence of UC-MSC in vitro on the transcriptome and secretome of peripheral blood mononuclear cells (PBMC) from patients with ARDS caused by COVID-19 as well as on the maturation of T cells has not yet been rigorously studied. Therefore, the investigation of changes in multiple biological molecules participating in pathophysiological processes will assist in identifying the main targets of MSC, expand our understanding of their therapeutic potential, and help adjust treatment protocols. A total of 28 patients with severe COVID-19 admitted to the Kyiv Clinical Hospital #4 were enrolled in this study after obtaining written informed consent. Detailed patient characteristics are shown in Table 1. The median ages for the MSC and Control groups were 58.0 [32–71] and 62.0 [32–73.0] years, respectively, and the intervals from illness onset to hospital admission for the MSC and Control groups were 12.3 ± 3.37 and 11.0 ± 2.69 days, respectively. The safety of the UC-MSC application was assessed using adverse events (AEs) that were recorded within 24 h after each infusion, including skin color and measurements of the patient’s blood pressure, body temperature, and pulse. Evaluation of the presence of any side effects was carried out from the moment of the first infusion until the end of the trial. The triple infusion of cells did not show significant side effects. The total lung computed tomography (CT) scores in both groups decreased gradually from all assessment periods and became significantly different on week 48 (p < 0.05) (Figure 1). At the same time, every point differed from another inside each group. However, for the Control group, the total score did not change in the time period from 24 to 48 weeks, when this parameter decreased for the MSC group (Figure S1). Blood parameter comparisons in patients with COVID-19, depending on the time of assessment, are presented in Figure 2. The differences in the white blood cells (WBC), granulocytes (Gra), and lymphocytes (Lym) counts as well as the neutrophil (Neu), eosinophils (Eo), and monocytes (Mo) percentages did not reach significance between the two groups, but the dynamic profile showed some fine changes. Thus, the count of WBC increased on day 7 with a subsequent decrease on day 28 in both the MSC and Control groups. In the MSC group, the count of granulocytes (Gra) decreased on day 28 compared to day 0 significantly, in contrast to the Control group. Neutrophil (Neu) percentages gradually decreased during the first 28 days in both groups, but the percentage of banded neutrophils on day 14 was significantly lower in the MSC group. A slight but significant increase in the percentage of eosinophils (Eo) on day 28 was observed in the MSC group compared to the beginning of observation. The percentage of Eo increased two-fold from days 14 to 28 in the Control group. The percentage of monocytes (Mo) did not change during the first four weeks in the Control group, whereas in the MSC group, it increased significantly from day 14. Compared to the beginning of hospitalization, the percentage of lymphocytes (Lym) increased in both groups and reached a significant difference between groups on day 28. Furthermore, the lymphocyte count doubled on day 7 in the MSC group and day 14 in the Control group, respectively. Compared to the initial day, ESR decreased in both the MSC and Control groups on days 7 and 28, respectively (Figure 2A and Figure S2). On the initial day, 5 out of 14 (35.71%) patients in the Control group and 2 out of 13 (15.38%) patients in the MSC group had leucopenia; 3 out of 15 (20,0%) patients in the Control group and 3 out of 13 (23.07%) patients in the MSC group had leukocytosis on day 7 (Figure 2B). Lymphopenia was observed in 12 out of 14 (85.71%) patients in the Control group and 7 out of 13 (53.84%) patients in the MSC group on day 7. On day 28, 1 out of 10 (10%) patients in the MSC group had lymphopenia, whereas no lymphopenia was observed in the Control group (Figure 2C). Cytokine levels’ changes depending on the time of assessment are presented in Figure 3 and Figure S3. C-reactive protein (CRP) levels started to normalize from day 0 and day 7 in the MSC group and Control group, respectively. In the MSC group, the level of interferon gamma-induced protein 10 (IP-10) decreased on day 7 compared to the beginning of hospitalization. IP-10 was significantly higher in the MSC group compared to the Control group on days 7 and 28. The plasma level of monocyte chemoattractant protein-1 (MCP-1) slightly increased on day 7 in the MSC group, while, in the Control group, the elevation of MCP-1 concentration in patients’ plasma was observed on days 14 and 28. The content of macrophage inflammatory protein-1 alpha (MIP-1α) was significantly higher on days 7 and 28 in the MSC group compared to the Control group. The level of interleukin-10 (IL-10) was significantly higher on day 7 in the blood of patients in the MSC group in comparison to the Control group. Granulocyte colony-stimulating factor (G-CSF) content gradually decreased during the observation period in patients from the Control group in contrast to the MSC group, in which it increased consistently throughout the observation period; it reached a significant difference between groups on days 14 and 28. Interleukin 2 (IL-2) and interleukin 6 (IL-6) did not change significantly during the observation period in both groups. Plasma concentrations of IL-2, IL-6, and MCP-1 did not differ significantly in the MSC and Control groups. The concentration of N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in the plasma of MSC patients rose significantly on day 28 compared to days 0 and 14. The insignificant elevation of the plasma level of NT-proBNP on day 28 was observed in the Control group. Troponin I (TnI) did not change in MSC patients, whereas in the Control group, it decreased significantly on days 7, 14, and 28 compared to the beginning of observation. After MSC transplantation, a significant decrease in surfactant D (SP-D) was observed in patients’ blood on days 7 and 28. Interestingly, in Control patients, there was an increase in SP-D level from the 14- to 28-day markers. Soluble form of the receptor for advanced glycation endproducts (sRAGE) was significantly reduced after 7 days in Control patients and increased on days 14 and 28. In the MSC group, there was a slight decrease in sRAGE over the entire period of hospitalization. Changes in the relative expression levels of miRNAs, depending on the time of assessment, are presented in Figure 4 and Figure S4. In the MSC group, the expression level of miR-27a-3p was significantly different on days 7 and 28 compared to the beginning of hospitalization. miR-146a-5p, miR-21-5p, and miR-221-3p decreased on days 7 and 28 in both groups compared with the beginning of hospitalization. For example, the relative expression level for miR-21-5p and miR-146a-5p decreased more than fourfold, and for miR-221-3p, it decreased more than threefold in the Control group but only twofold in the MSC group. On day 14 of observation, the relative expression level of miR-126-3p differed significantly from day 0 in the Control group, whereas in the MSC group, it did not change for 28 days. In the MSC group, the level of miR-133a-3p decreased threefold by day 7. The plasma levels of miR-92a-3p in patients of the Control group on days 0 and 7 of hospitalization were significantly lower compared to those in the MSC group. The expression levels of miR-92a-3p and miR-424-5p were elevated in both the Control and MSC groups over the observation period. All data on the correlation analysis are available in Table S1, and some are presented in Figure S5 in the Supplementary Materials. CRP levels correlated negatively with the percentage of lymphocytes (r = −0.562, p ≤ 0.0001) and positively with ESR (r = 0.628, p ≤ 0.0001) and neutrophil percentage (r = 0.411, p ≤ 0.01). SP-D levels correlated with ESR (r = 0.386, p ≤ 0.01) and the concentration of IP-10 (r = 0.310, p ≤ 0.05). IP-10 negatively correlated with lymphocyte count (r = −0.551, p ≤ 0.001), eosinophils (r = −0.384, p ≤ 0.01), and miR-27a-3p (r = −0.472, p ≤ 0.005). Troponin I levels correlated with the expression of miR-133a-3p positively (r = 0.372, p = 0.05) and that of eosinophils negatively (r = −0.352, p ≤ 0.05). sRAGE plasma levels positively correlated with MCP-1 concentration (r = 0.516, p ≤ 0.001) and MIP-1α (r = 0.299, p ≤ 0.05). MCP-1 concentration correlated negatively with miR-21-5p (r = −0.396, p ≤ 0.01). miR-92a-3p correlated negatively with CRP (r = −0.477, p ≤ 0.001), SP-D (r = −0.450, p ≤ 0.005), and IP-10 (r = −0.409, p ≤ 0.005). Negative correlations were found between miR-424-5p and CRP (r = −0.435, p ≤ 0.005), SP-D (r = −0.452, p ≤ 0.005), and IP-10 (r = −0.436, p ≤ 0.005). ESR was positively correlated with CT parameters of the lung on weeks 2 (r = 0.445, p ≤ 0.005), 24 (r = 0.457, p ≤ 0.005), and 48 (r = 0.398, p ≤ 0.05). The number of granulocytes positively correlated with lung fibrosis intensity on weeks 24 (r = 0.457, p ≤ 0.005) and 48 (r = 0.449, p ≤ 0.005). CRP levels positively correlated with lung damage on weeks 2 (r = 0.439, p ≤ 0.005), 8 (r = 0.386, p ≤ 0.05), 24 (r = 0.510, p ≤ 0.001), and 48 (r = 0.475, p ≤ 0.005). MCP-1 levels positively correlated with total score of CT on weeks 8 (r = 0.471, p ≤ 0.005) and 48 (r = 0.499, p ≤ 0.005). SP-D concentration correlated with CT total scores on week 2 (r = 0.373, p ≤ 0.05). The levels of RAGE positively correlated with CT scores on weeks 2 (r = 0.437, p ≤ 0.005), 8 (r = 0.436, p ≤ 0.01), 24 (r = 0.420, p ≤ 0.01), and 48 (r = 0.510, p ≤ 0.005). miR-424a-5p correlated negatively with lung damage degree on weeks 2 (r = −0.571, p ≤ 0.001), 8 (r = −0.426, p ≤ 0.01), and 24 (r = −0.351, p ≤ 0.05). miR-21a-5p levels negatively correlated with CT total score on weeks 2 (r = −0.412, p ≤ 0.01), 8 (r = −0.479, p ≤ 0.005), and 48 (r = −0.353, p ≤ 0.05). During week 2, CT total scores correlated negatively with relative expression levels of miR-92a-3p (r = −0.480, p ≤ 0.005). We compared the transcriptome profiles of PBMC co-cultured with and without UC-MSC to identify alterations in gene expression levels. Four thousand one hundred seventy-two genes were differentially expressed between UC-MSC and Control samples; of these, 2993 were upregulated and 1179 were downregulated in PBMC after co-culture with UC-MSC (Figure 5A,B). Gene ontology (GO) molecular function enrichment analysis of upregulated genes revealed that serine hydrolase, serine-type peptidase, serine-type endopeptidase, endopeptidase, and metallopeptidase activities were the most significantly overrepresented (Figure 5C). GO biological process analysis showed that genes involved in an extracellular matrix organization, angiogenesis, immune defense (especially in neutrophil-mediated immunity), and leukocyte migration were upregulated. GO molecular function showed that among the downregulated genes, the most relevant categories were catalytic activity, acting on DNA, chromatin binding, and tubulin binding. GO biological process enrichment analysis of downregulated genes demonstrated that genes involved in cell division were significantly underrepresented (Figure 5D). KEGG annotation revealed that UC-MSC induced inflammatory-associated signaling pathways (B-cell receptor and NF-kappa B signals) in PBMC. Furthermore, the enrichment of genes associated with phagosomes, cytokine–cytokine receptor interaction, protein digestions, and ferroptosis indicate the elevation of immune defense machinery in PBMC. Downregulated enriched categories analyzed by KEGG included genes associated with cell proliferation (especially DNA replication), the cell cycle, and the Fanconi anemia pathway. In addition, the apoptosis-associated genes in PBMC after co-culture with UC-MSC had decreased expression levels (Figure 5E,F). Flow cytometry analysis demonstrated the increase in CD69+CD25− and CD69+CD25+ cell subpopulations among CD3 T cells in PBMC after co-culture with UC-MSC. With UC-MSC, the percentage of effector T cells (CXCR3+), senescent effector CD8 and CD 4 T cells (CD57+CXCR3+), and memory CD8 T cells (CD57+CXCR3+CD45RO+) decreased in PBMC (Figure 6A). UC-MSC did not have any effect on the maturation of CD3+CD4+CD8−Th cells, cytotoxic CD3+CD4−CD8+ T cells, and regulatory T cells (CD3+CD4+CD8−CD25lowCD127low) during co-culturing with PBMC. An ELISA of conditioned media from PBMC and UC-MSC/PBMC cultures showed the significant increase of MCP-1, IL-6, and G-CSF as well as the remarkably attenuated secretion of MIP-1α, IL-10, and IL-12p70. The concentration of IL-2 and IP-10 did not change significantly in conditioned media collected from PBMC and UC-MSC/PBMC cultures (Figure 6B). Co-culturing with UC-MSC significantly decreased the proliferation of PBMC that coincides with the downregulation of genes involved in cell division (Figure 5D and Figure 6C). In the present study, we aimed to reveal the impact of human umbilical cord-derived mesenchymal stem cell transplantation on the safety and clinical outcomes of patients with COVID-19 in the context of changes in lung functional status, miRNA, and cytokine levels. The positive influence of MSC therapy on lungs in both short-term and long-term periods was shown previously in severe COVID-19 patients [37]. Furthermore, the improvement of chest CT results in the first month after MSC infusion in comparison to a placebo was published by other authors [20,23]. Herein, we observed a significant reduction in lung damage during a one-year follow-up in the MSC group compared to the Control group. In MSC patients, lung CT total scores gradually decreased from week 2 to week 48 of observation, demonstrating a beneficial long-term therapeutic effect of MSC on lung lesions, whereas in the Control group, an improvement was observed only up to week 24, with residual fibrotic changes occurring by week 48. In our study, the long-term (up to one year) benefits in ARDS patients’ lungs, as seen on CT, corresponded to data concerning MSC transplantation in COPD with high systemic inflammation [38]. According to prior research, after intravenous transplantation, MSC can accumulate in the lung capillaries for a short time and can minimize the damage of alveolar epithelium and lung fibrosis [3]. In addition, MSC may have a preventive impact when applied at the beginning of illness. Although numerous preclinical studies in ARDS have demonstrated that MSC transplantation can significantly attenuate inflammation and improve the repair of damaged lung tissue, the results of our and other clinical trials are ambiguous, highlighting the need to better understand these mechanisms in patients with ARDS caused by COVID-19. According to [39], patients with COVID-19 widely present myelocytosis and lymphopenia. However, on day 28, we found an increase in lymphocyte content after MSC therapy, which was also indicated in another study [12]. The boosted content of banded neutrophils in patients’ blood that contributed to COVID-19 severity was reported previously [40]. At the same time, a clinical trial reported that MSC transplantation significantly reduced neutrophil counts after two and four months [41]. In our study, we observed a significant decrease in the content of banded neutrophils on day 14 after the beginning of cell therapy. We supposed that an observed reduction in the range of these cells might indicate attenuation of the inflammatory process after MSC therapy. Cytokine over-release syndrome is one of the significant factors influencing COVID-19 mortality and morbidity, and it is brought on by immune cells generating pro-inflammatory cytokines in a positive feedback cycle. Elevated blood levels of CRP, pro-inflammatory cytokines, and ESR are characteristics of a ‘cytokine storm’ [42]. MSC transplantation may function as an immune modulator in the formation of a cytokine storm brought on by inflammation, according to earlier research [43]. In this study, the level of CRP in the blood of patients with COVID-19 in the MSC group positively correlated with lung damage score based on CT, ESR, and neutrophils, and it correlated negatively with percentages of lymphocytes, which was also described earlier in patients with conventional therapy [44]. Notably, we observed a 7-day delay in CRP decline in the Control group compared to the MSC group. Thus, we hypothesize that MSC transplantation suppressed inflammation caused by COVID-19 in a paracrine manner, improving lymphocyte recovery and leading to a rapid decrease in such inflammation markers as ESR and banded neutrophils. These data are consistent with results reported by other authors [12,14,21,36,45]. Clinical studies have recommended using serum SP-D levels as a biomarker in acute and chronic respiratory diseases, such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. SP-D is released by type II alveolar cells, and increased serum concentrations result from protein translocation emerging with impairment of the structural integrity of the alveolar–capillary membrane [46]. The type II alveolar epithelial is the main target of SARS-CoV-2 [47]; thus, inhibition of its injury may benefit from cell therapy. Furthermore, the positive correlation of SP-D with CRP was previously published [46]. We observed a positive correlation between SP-D and lung damage score on CT, inflammatory markers of ESR, and IP-10. In addition, the plasma level of SP-D decreased on days 7 and 28 after MSC transplantation, suggesting attenuation of lung inflammation and inhibition of type II alveolar epithelium death, as was also reported in [48]. The high concentration of a lung injury marker specific for type I alveolar epithelium, sRAGE, in the blood is a prognostic biomarker of the development of ARDS and severe stages of COVID-19 [48,49,50]. Corticosteroid therapy is known to reduce sRAGE in the blood of pediatric patients with ARDS [51]. We revealed that the concentration of sRAGE positively correlated with the plasma level of MCP-1, MIP-1α, and total CT score of MSC-treated patients. In our study, sRAGE slightly decreased after MSC therapy. In contrast, the elevation of sRAGE in the plasma of Control patients on days 14 and 28 compared to the initial day indicated the activation of inflammatory processes in the lungs. In addition, a significant reduction in sRAGE in Control patients coincided with the period of corticosteroid therapy. Decreasing the cytokine levels in the blood plasma may not reflect the reduction of lung inflammation or the improvement of the lung epithelium. Wick et al. showed that MSC reduces cytokine levels more in lung airspace compared to plasma [52]. IP-10 is a prognostic marker in COVID-19 [53], and its growth in plasma was reported in severe cases [54,55]. MSC transplantations did not affect IP-10 levels in critically ill COVID-19 patients [20,21]. However, in our study, the level of IP-10 decreased after MSC transplantation on day 7, but it remained higher in MSC patients than in Control patients on days 14 and 28. Opposite to findings reporting no changes in MIP-1α plasma level after MSC therapy, as described earlier [41], our findings showed higher levels of MIP-1α on days 7 and 28 in the MSC group. Our results regarding the high level of G-CSF in the MSC group on days 14 and 28 are contrary to the reported association of high levels of G-CSF with COVID-19 severity and the progression of inflammation in COVID-19 patients [56,57] because we did not observe any deterioration in MSC-treated patients. Even though IL-10 has anti-inflammatory properties, some studies show a pro-inflammatory effect in COVID-19 patients [58,59,60]. We observed a significant influx of IL-10 in the MSC group after final transplantation compared to the Control group. Thus, we were the first to show that MSC transplantation in severe COVID-19 patients led to the elevation of plasma levels of pro-inflammatory cytokines such as IP-10, MIP-1α, G-CSF, and IL-10 without disease aggravation. In the current study, we did not observe any effect of triple MSC transplantation on IL-2 levels. MCP-1 levels increased slightly during the first week but remained unchanged until day 28 in contrast to the Control group, in which it dramatically increased from the second week. Previously, three UC-MSC infusions led to a decrease in MCP-1 levels in a clinical trial [41]. Meta-analysis done by [61] shows that MSC transplantation for COVID-19 has a remarkable effect on efficiency without altering blood levels of CRP, IL-6, and IL-2. Interestingly, transplantation of MSC at stage IIa studies found no significant changes in IL-6, although the indicators of pneumonia on CT improved [20,36,62], which coincides with our results. The contribution of miRNAs to inflammation is supported by previous data on the upregulated expression of miR-221 in mice with LPS-induced acute lung injury [63], increased levels of miR-133a-3p in atherosclerotic thrombotic cerebral infarction and cardioembolic stroke [64], and higher miR-21 content in COVID-19 patients than in non-COVID-19 volunteers [65] and its upregulation in CD14+ cells among patients with axial spondyloarthritis [66]. Numeral studies indicate miR-146, miR-27, and miR-126 are potential inflammatory biomarkers for ARDS [67,68,69,70,71]. Circulatory miR424-5p is an inflammation marker detected after marathon runs [72]. MiR424-5p is elevated in acute myocardial infarction and autoimmune disease pemphigus [73,74]. In patients with asymptomatic COVID-19, this microRNA is less expressed than in symptomatic COVID-19 [75]. miR-92a-3p is considered an effective biomarker in diagnosing the acute exacerbation of chronic obstructive pulmonary disease, and its levels are elevated in the plasma of patients with COPD [76]. Increased levels of miR-92a-3p are observed in COVID-19, the development of acute lung damage from liposaccharides in animals, and other pathologies of the vascular system [77,78,79]. In our study, the plasma level of pro-inflammatory miR-146a, miR-27a, miR-126, miR-221, miR-21, and miR-133 did not differ between groups and decreased during the observation period. However, after conventional treatment withdrawal, we observed a significant elevation of miR-92a-3p and miR424-5p in patients of both the MSC and Control groups. We also showed that the plasma levels of miR-424-5p and miR-92a-3p negatively correlated with lung lesions. Furthermore, the plasma levels of both miR-92a-3p and miR-424-5p were negatively associated with CRP, SP-D, and IP-10, which, together with the data mentioned above, may indicate their compensatory role in the reduction of inflammation. The current study demonstrates that UC-MSC increases the expression of genes involved in the development of the immune response, particularly neutrophil activation, leukocyte migration, and phagocytosis, and decrease the expression of apoptosis-associated genes in PBMC from COVID-19 patients. Wharton’s jelly MSC are known to activate neutrophils. In particular, they increase respiratory burst and phagocyte activity and decrease apoptosis [80,81]. At the same time, the fact that UC-MSC reduced the expression of genes involved in proliferation in PBMC indicates it has a certain immunosuppressive effect. Interestingly, we observed an increase in the expression of genes associated with ferroptosis in COVID-19 leukocytes, which may have a positive impact because the increased expression of ferroptosis-related genes was reported in PBMC during the acute phase as well as decreased expression in the recovery phase [82]. Furthermore, it was already reported that the MSC-mediated immunomodulatory effect on PBMC occurs through the activation of NF-kappa B signaling [83]. In addition, we observed a twice-increased level of PD-L1 expression in PBMC under co-culture conditions (Table S3 in Supplementary Materials). MSC can orchestrate T-cell responses via cell–cell contact interactions and soluble factor secretion. Inhibition of T cell proliferation occurs due to the interaction of PD-1 with its ligand [84]. In addition, soluble factors such as PGE2 and IDO are involved in T cell inactivation, G0/G1 arrest, apoptosis, and inhibition of inflammatory cytokine production [84]. Interestingly, genes involved in the production of PTGES and IDO2 were upregulated in PBMC after being co-cultured with UC-MSC (Table S3 in Supplementary Materials). We show that the conditioned media from UC-MSC and PBMC co-cultures were rich in IL-6, MCP-1, and G-CSF and depleted in MIP-1α and IL-12, which tends toward accordance with the RNA-seq data on the expression levels of the relevant genes in PBMC. Similar data regarding the influence of MSC on the secretion of IL-6, MCP-1, MIP-1α, and IL-12 by PBMC were reported earlier [85,86]. On the other hand, the fact that UC-MSC led to a drop in IL-10 when co-cultivated with PBMC does not agree with the data when PBMC from healthy donors were used. Interestingly, decreased expression of IL-10 was observed after co-cultivation of PBMC from COVID-19 patients with dental pulp-derived MSC [87]. A putative mechanism of UC-MSC action on immune cells in patients compared to an in vitro model is presented in Figure 7. Our study shows that UC-MSC triggers the expression of CD69 as an early- and CD25 as a mid-stage T cell marker, as was previously demonstrated [36]. Interestingly, the percentage of effector T cells and effector senescent CD8 and CD 4 T cells decreased under UC-MSC’s influence, corresponding to the CXCR3 expression levels in PBMC seen in RNA-seq. Moreover, the reduction in the pool of effector T cells after co-culturing activated PBMC with UC-MSC was reported previously [88]. In this way, our experimental data reflects the multifunctional response of PBMC to the immunomodulatory effect of UC-MSC. Therefore, our findings show that MSC reduces lung fibrosis while not representing strong immunosuppressive properties; instead, they have an immunomodulating effect. Further research is needed to assess the therapeutic efficacy and mechanisms of UC-MSC infusion in patients with inflammatory airway disorders and ARDS, particularly that caused by COVID-19. A total of 28 confirmed cases of patients with COVID-19 at the Kyiv City Clinical Hospital #4 were included in this single-center, non-randomized, open-label study registered on clinicaltrials.gov (NCT04461925) [89]. Fifteen patients who had undergone conventional treatment were enrolled in the Control group, and in the MSC group, there were thirteen patients who, in addition to conventional therapy, were treated with three consecutive doses of umbilical cord-derived MSC. Some underlining comorbidities and basic characteristics of both groups are indicated in Table 1. The study protocol was designed following the Declaration of Helsinki and approved by the ethics committee of Kyiv City Clinical Hospital #4 (protocol #280, 23 April 2020). All subjects enrolled in the study signed informed consent statements. All patients met the criteria for moderate COVID-19 severity according to the interim guidelines from the WHO and the Novel Coronavirus Pneumonia Diagnosis and Treatment Plan issued by the National Health Commission of the People’s Republic of China (Provisional 7th Edition) [90]. Patients from both groups had the following conditions: respiratory distress, RR ≥ 30 times/min, and oxygen saturation (SpO2) ≤ 93% at rest, and two-sided pneumonia was observed in all enrolled participants. Patients with severe COVID-19 symptoms persisting after 7–11 days of standard treatment participated in this study. The major treatments for patients included drug therapy, such as antibiotic therapy and standard treatment with dexamethasone to inhibit the inflammatory response. No mechanical ventilation was applied, but patients got oxygen through a facial mask if necessary. Data from each patient were collected for 28 days (Figure 8). Exclusion criteria included the following: shift to other treatment modalities (according to the treating physician), pregnancy, breastfeeding, malignant tumors, other systemic severe diseases, psychosis, enrollment in other clinical trials, co-infection of HIV or syphilis, inability to provide informed consent or to comply with test requirements, invasive ventilation lasting more than 48 h, and the presence of other organ failures (need for organ support). Laboratory validation of SARS-CoV-2 was performed at the Kyiv City Clinical Hospital #4 using real-time polymerase chain reaction (RT-PCR). Briefly, throat swab samples were obtained from the upper respiratory tract and stored immediately in the viral transport medium. After extraction of total RNA, RT-PCR was performed to identify the virus. Genotyping of the SARS-CoV-2 virus was not performed, but the delta strain was the dominant one in Ukraine in that time. Umbilical cords (Ucs) delivered after Caesarean section were collected from 23- to 36-year-old donors at 39–41 weeks of gestation in the Kyiv city maternity hospital #3. All donors (n = 19) provided written informed consent for the sourcing and the usage of their Ucs for the approved clinical study. One week before Uc collection, apparent healthy donors passed the screening for infectious diseases using the serology (anti-HIV1/2, anti-HCV, anti-HBV, anti-Treponema pallidum, and anti-CMV IgG and IgM) and qRT–PCR (presence of nucleic acids of HIV1/2, HCV, and HBV) methods. Using validated PCR kits, UC tissues were tested for HSV-1/2, HHV-6, Ureaplasma spp., and Mycoplasma genitalium. Ucs were minced with scissors into small pieces (1–3 mm) and washed intensively on a shaker in Hanks’ balanced salt solution (HBSS) (Sigma, Irvine, UK) supplemented with 100 U/mL penicillin (Arterium, Kyiv, Ukraine) and 50 mg/mL streptomycin (Arterium, Kyiv, Ukraine) until the washing solution became colorless. UC pieces of tissue were plated into cell culture-treated flasks (Sarstedt, Nümbrecht, Germany) and covered with MEM alpha modification (Sigma, Irvine, UK) supplemented with 15% FBS (Sigma, Paraguay origin, Saint Louis, MO, USA), 1× RPMI amino acid solution (Sigma, Irvine, UK), and 1× streptomycin/penicillin (Sigma, Irvine, UK), referred as completed cultural media. Explants were incubated at +37 °C in the presence of 5% CO2 for 14 days, with media changed twice a week. When the outgrowth of cells reached 80–90% confluence in a monolayer, they were detached using 0.05% trypsin and 0.02% EDTA (Sigma, Irvine, UK), washed, counted, and passaged at the inoculation density of 4–5 × 103 cells/cm2 on culture-treated flasks, referred to as passage 1 (P1). UC-MSC at P3 were harvested and cryopreserved using a rate-controlled freezer at a final concentration of 5% dimethyl sulfoxide (Sigma Aldrich, Saint Louis, MO, USA) in HBSS (Sigma, Irvine, UK). Representative images of the proliferated UC-MSC, surface immunophenotype, differentiation, and karyotype analysis are presented in Figure S6. Aliquots from all samples were collected for quality control. This includes determination of viability by using the trypan blue exclusion method and expression of cell surface markers by using flow cytometry, cytogenetics analysis by using the GTG-banding method, microbiological tests (Bact/Alert 3D, Biomerieux, Durham, NC, USA), and detection of Mycoplasma spp. (KIT MycoAlert™ PLUS Mycoplasma Detection, Lonza, Rockland, Miami, FL, USA), according to the manufacturer’s instructions. These quality control tests were performed before each batch of cells was released. The release criteria for the clinical use of UC-MSC included the absence of contamination with pathogenic microorganisms (bacteria, mycoplasma, and fungi), a normal karyotype, identity, purity patterns characterized as positive (≥95%) for CD73, CD90, and CD105 and negative (≤2%) for CD45, and CD34 expression of cell surface markers according to the minimal criteria for multipotent mesenchymal stromal cells issued by ISCT [91]. During transplantation, we examined and evaluated the frequency and character of every adverse event to clarify if it was connected to the administration of the UC-MSC. For infusion, UC-MSC at P3 were thawed using a water bath preset at +37 °C until the liquid phase appeared. Cells were centrifuged at 300 g during 5 min RT, and pellets were resuspended in a final volume of 50 mL of vehicle solution composed of saline (Darnytsya, Kyiv, Ukraine) and 5% human serum albumin (Biopharma, Kyiv, Ukraine). The averages of cell viability were 87.8% ± 5.1% before infusion. Cells were infused in three consecutive doses on treatment days 0, 3, and 6 as 1 × 106 cells/kg intravenously. A standard blood transfusion system fitted with a 100 m pore size was used for the infusion. Within 20 min, the UC-MSC were infused dropwise while the patient was monitored electrocardiographically. At the infusion time and through the following 30 min, we continuously checked the patient’s blood pressure, body temperature, pulse, and skin color. Following admission, all patients in the supine position were subjected to high-resolution plain chest CT scanning using a Philips Brilliance CT 64 slice scanner (Philips Medical Systems Technologies Ltd., Haifa, Israel), applying a slice thickness of 1 mm with 120 kV and 335 mAs. CT images were analyzed on weeks 2, 8, 24, and 48. The processing and grading of CT images considered such radiologic features as ground glass opacity, reticulation, and honeycombing. The approach applied for the quantitative determination of the affected lung area was as described by Büttner et al. [92] with some changes. Briefly, the affected lung area was measured in polygonal regions of interest in one image at three levels (upper point—above the level of the carina, lower point—below the highest point of the right diaphragm, and middle point—between the previous two, right at the midpoint). Each image was divided into four quadrants and further divided into five sub-quadrants covering 5% of the total image area. The scale applied for evaluation included seven values: 0 (no involvement), 1 (≤10% involvement), 2 (11–20% involvement), 3 (21–30% involvement), 4 (31–40% involvement), 5 (41–50% involvement), 6 (>50% involvement). The total severity score was the sum of the scores of the five lung lobes. Blood samples (12–20 mL) of 28 patients with COVID-19 were collected on the day of admission (day 0) and on days 7, 14, and 28 after admission. Briefly, 5 mL was used for routine blood assays completed using a Swelab Alfa Basic hematology analyzer (Boule Medical AB, Spånga, Sweden) at the Kyiv City Clinical Hospital #4. The remaining portions of blood samples were immediately transported to the Institute of Cell Therapy, where the plasma and serum were separated, snap-frozen, and stored at −80 °C for cytokine detection and miRNA analysis. The C-reactive protein content in patient sera was determined using AccuBind (Monobind, Lake Forest, CA, USA) according to the manufacturer’s instructions. The detection limit was 0.014 µg/mL. For the detection of G-CSF, IL-2, IL-6, IP-10, MIP-1α, MCP-1, SP-D, sRAGE, and NT-proBNP, an enzyme-linked immunosorbent assay (ELISA) was performed using the Invitrogen kit according to the manufacturer’s instructions. The following ELISA and standard curves were employed to measure each parameter: human G-CSF (BMS2001INST), IL-2 (BMS221INST), IL-6 (BMS213INST), IP-10 (BMS284INST), MIP-1α (KAC2201), IL-10 (BMS215INST), IL-12p70 (KAC1568), TnI (EHTNNI3), and MCP-1 (BMS281INST) from Instant ELISA (Invitrogen, Thermo Fisher Scientific, Vienna, Austria), RAGE (RAB0007) from Sigma (Sigma-Aldrich Chemie GmbH, Steinheim am Albuch, Germany), and SP-D (DSFPD0) and NT-proBNP (DY3604-05) from R&D Systems (Bio-Techne Ltd., Abingdon, UK). The sensitivity levels were 11 pg/mL for G-CSF, 2.3 pg/mL for IL-2, 0.92 pg/mL for IL-6, 1 pg/mL for IP-10, 2 pg/mL for MIP-1α, 0.66 pg/mL for IL-10, 0.2 pg/mL for IL-12p70, 100 pg/mL for TnI, 2.31 pg/mL for MCP-1, 0.11 ng/mL for SP-D, and 3pg/mL for RAGE. The sensitivity level for NT-proBNP was not indicated by the manufacturer. All absorbance measurements were carried out using a HumaReader HS (Human GmBH, Wiesbaden, Germany). All assays were performed in duplicate. miRNA was extracted from the plasma of patients with COVID-19 and of the age-matched control group according to the instructions for the NucleoSpin miRNA Kit (Macherey-Nagel, Hoerdt, France) and stored at −80 °C. The concentration of isolated miRNA was measured using a NanoDrop 2000 spectrophotometer (Thermo Scientific Inc., Wilmington, DE, USA), and miRNA was reverse transcribed into cDNA using the miRNA 1st-Strand cDNA Synthesis Kit (Agilent Technologies, Lexington, MA, USA) with a universal reverse primer from the synthesis kit. Quantitative RT-PCR was conducted to detect miRNA levels using a 5× HOT FIREPolEvaGreen qPCR Mix Plus kit (no ROX) (Solis BioDyne, Tartu, Estonia) with a CFX96™ Real-Time PCR Detection System (BIO-RAD Laboratories, Inc., Singapore). For each sample, the qRT-PCR reaction consisting of a 15 min hot start at 95 °C for polymerase activation, followed by 44 cycles of 15 s at 95 °C and 20 s at 60 °C, was performed in triplicate. The 2ΔΔCq method [93] was used for miRNA quantification analysis, with U6 as a reference. The primer sequences are listed in Table S2. Human PBMC were isolated via separation with Ficol (Cytiva, Global Life Sciences Solutions, Marlborough, MA, USA) from peripheral blood samples of patients with ARDS caused by COVID-19. All PBMC (n = 6) were cryopreserved with 10% DMSO (Sigma, Saint Louis, MO, USA) in FBS (Sigma, Paraguay origin, Saint Louis, MO, USA) and stored in liquid nitrogen until processed. UC-MSC from three donors were thawed and cultured as described above. The cells were incubated with 20 µg/ml mitomycin C in completed cultural media for 2 h, detached using 0.05% trypsin and 0.02% EDTA (Sigma, UK), washed, counted, mixed in equal proportion (1:1:1), and passaged at the inoculation density of 1 × 105 per well of 24-well plate. PBMC were thawed in a water bath preset at +37 °C until the liquid phase appeared. Cells were centrifuged at 300× g during 10 min RT, and pellets were resuspended in an RPMI-1640 (Gibco, Life Technologies Corp., Carlsbad, CA, USA) with 10% heat-inactivated FBS. PBMC (5 × 105) were placed into 0.4 µmThinCerts™-TC insert (Greiner Bio-One, Monroe, NC, USA) in a total volume of 500 μL in the presence of Dynabeads® Human T-Activator CD3/CD28 (Life Technologies AS, Oslo, Norway) at a bead/cell ratio of 1:5. Cells were incubated at 37 °C over 6 days and collected for FACS and RNAseq analyses. The conditioned media from UC-MSC/PBMC were collected for further ELISA analysis. The samples were prepared in biological triplicate. RNA was extracted using a Nucleospin RNA isolation kit (Macherey–Nagel, Hœrdt, France) according to the manufacturer’s protocol. RNA-seq libraries were prepared using the Agilent SureSelect Automated Strand-Specific RNA Library Prep, with polyA selection by Novogene Co., LTD (Beijing, China). Prepared libraries were sequenced on an Illumina HiSeq2000, utilizing a paired-end 150 bp sequencing strategy (short-reads) and 20M read pairs per sample. Raw data (raw reads) of the fastq format were first processed through fastp software. In this step, clean data (clean reads) were obtained by removing reads containing adapters, reads containing poly-N, and low-quality reads from raw data. At the same time, the Q20, Q30, and GC content of the clean data were calculated. All of the downstream analyses were based on clean data with high quality. Raw paired-end sequence reads were mapped to the human transcriptome (ensembl_homo_sapiens_grch38_p12_gca_000001405_27) using Hisat2 v2.0.5. featureCounts v1.5.0-p3 was used to count the read numbers mapped to each gene. Then, the FPKM of each gene was calculated based on the length of the gene and the read count mapped to this gene. Differential expression analysis was performed using the DESeq2 R package (1.20.0). Genes with adjusted p-value < 0.05 and |log2 (FoldChange)| > 0 were considered differentially expressed. Gene Ontology (GO) enrichment analysis of differentially expressed genes and the statistical enrichment of differential expression genes in KEGG pathways were implemented by using the clusterProfiler R package. The differentially expressed genes are listed in Supplementary Table S3. Clean data were deposited in the NCBI Sequence Read Archive and can be accessed under PRJNA929329. The local version of the GSEA analysis tool (http://www.broadinstitute.org/gsea/index.jsp (accessed on 4 January 2023)) was used for Gene Set Enrichment Analysis (GSEA). GO and the KEGG data set were used for GSEA independently. SPSS version 27.0 software (IBM Corp. Released 2020. IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY, USA: IBM Corp.) was used for statistical analysis. GraphPad Prism software (version 7.0a, Inc. San Diego, CA, USA) was used for data visualization. The variables were presented as medians with interquartile ranges. The Wilcoxon signed-rank test was used to compare the time-dependent events. The Mann–Whitney U test was used to compare the differences between the groups at each time point. The paired t-test was applied to compare related groups. The Spearman rank test was performed to test the correlations between variables. Statistical significance was set at a two-tailed p-value of ≤0.05. Triple MSC transplantation in patients with moderate/severe COVID-19 was shown to be safe and to improve lung lesions over a one-year follow-up period. Although the majority of parameters did not show a significant difference between the MSC group and the Control group after treatment, combined data still indicate cell therapy tends to reduce inflammation and benefit the patients. MSC transplantation leads to a decrease in markers of inflammation in patients (ESR, CRP, and banded neutrophils), more rapid recovery of blood lymphocytes, and reduced SP-D as one of the main markers of lung injuries. On the other hand, the increased plasma levels of some pro-inflammatory cytokines such as IP-10, MIP-1α, G-CSF, and IL-10 could suggest a more immunomodulatory effect of MSC rather than immunosuppression in patients with ARDS caused COVID-19. In vitro, UC-MSC demonstrated an immunomodulatory effect on PBMC, namely, an increase in the activation of neutrophils, phagocytosis and migration of leukocytes, and activation of early markers of T cells, and a decrease in the maturation of effector and senescent effector T cells.

PMC10003441

36902476

Sharmin Aktar,Faysal Bin Hamid,Sujani Madhurika Kodagoda Gamage,Tracie Cheng,Nahal Pakneshan,Cu Tai Lu,Farhadul Islam,Vinod Gopalan,Alfred King-yin Lam

Gene Expression Analysis of Immune Regulatory Genes in Circulating Tumour Cells and Peripheral Blood Mononuclear Cells in Patients with Colorectal Carcinoma

06-03-2023

circulating tumour cells,KRAS,CTLA-4,immune checkpoint molecules,immune escape mechanism,molecular characterisation

Information regarding genetic alterations of driver cancer genes in circulating tumour cells (CTCs) and their surrounding immune microenvironment nowadays can be employed as a real-time monitoring platform for translational applications such as patient response to therapeutic targets, including immunotherapy. This study aimed to investigate the expression profiling of these genes along with immunotherapeutic target molecules in CTCs and peripheral blood mononuclear cells (PBMCs) in patients with colorectal carcinoma (CRC). Expression of p53, APC, KRAS, c-Myc, and immunotherapeutic target molecules PD-L1, CTLA-4, and CD47 in CTCs and PBMCs were analysed by qPCR. Their expression in high versus low CTC-positive patients with CRC was compared and clinicopathological correlations between these patient groups were analysed. CTCs were detected in 61% (38 of 62) of patients with CRC. The presence of higher numbers of CTCs was significantly correlated with advanced cancer stages (p = 0.045) and the subtypes of adenocarcinoma (conventional vs. mucinous, p = 0.019), while being weakly correlated with tumour size (p = 0.051). Patients with lower numbers of CTCs had higher expression of KRAS. Higher KRAS expression in CTCs was negatively correlated with tumour perforation (p = 0.029), lymph node status (p = 0.037), distant metastasis (p = 0.046) and overall staging (p = 0.004). CTLA-4 was highly expressed in both CTCs and PBMCs. In addition, CTLA-4 expression was positively correlated with KRAS (r = 0.6878, p = 0.002) in the enriched CTC fraction. Dysregulation of KRAS in CTCs might evade the immune system by altering the expression of CTLA-4, providing new insights into the selection of therapeutic targets at the onset of the disease. Monitoring CTCs counts, as well as gene expression profiling of PBMCs, can be helpful in predicting tumour progression, patient outcome and treatment.

Gene Expression Analysis of Immune Regulatory Genes in Circulating Tumour Cells and Peripheral Blood Mononuclear Cells in Patients with Colorectal Carcinoma Information regarding genetic alterations of driver cancer genes in circulating tumour cells (CTCs) and their surrounding immune microenvironment nowadays can be employed as a real-time monitoring platform for translational applications such as patient response to therapeutic targets, including immunotherapy. This study aimed to investigate the expression profiling of these genes along with immunotherapeutic target molecules in CTCs and peripheral blood mononuclear cells (PBMCs) in patients with colorectal carcinoma (CRC). Expression of p53, APC, KRAS, c-Myc, and immunotherapeutic target molecules PD-L1, CTLA-4, and CD47 in CTCs and PBMCs were analysed by qPCR. Their expression in high versus low CTC-positive patients with CRC was compared and clinicopathological correlations between these patient groups were analysed. CTCs were detected in 61% (38 of 62) of patients with CRC. The presence of higher numbers of CTCs was significantly correlated with advanced cancer stages (p = 0.045) and the subtypes of adenocarcinoma (conventional vs. mucinous, p = 0.019), while being weakly correlated with tumour size (p = 0.051). Patients with lower numbers of CTCs had higher expression of KRAS. Higher KRAS expression in CTCs was negatively correlated with tumour perforation (p = 0.029), lymph node status (p = 0.037), distant metastasis (p = 0.046) and overall staging (p = 0.004). CTLA-4 was highly expressed in both CTCs and PBMCs. In addition, CTLA-4 expression was positively correlated with KRAS (r = 0.6878, p = 0.002) in the enriched CTC fraction. Dysregulation of KRAS in CTCs might evade the immune system by altering the expression of CTLA-4, providing new insights into the selection of therapeutic targets at the onset of the disease. Monitoring CTCs counts, as well as gene expression profiling of PBMCs, can be helpful in predicting tumour progression, patient outcome and treatment. Circulating tumour cells (CTCs)—the subpopulations of primary tumour cells that are released into the bloodstream—are believed to be the key player in cancer metastases and recurrence [1]. Over the past decades, CTCs have been studied frequently for the clinical management of patients with localized, metastatic and recurrent disease, demonstrating the potential clinical significance of CTC counts in many cancers including colorectal carcinoma (CRC) [2,3]. Immune evasion by cancer cells is one of the major events in tumour progression. In an immunosuppressive setting in circulating blood, CTCs become susceptible to immune surveillance. It is reported that a high number of CTCs can hinder the antitumour immune responses via immune escape pathways, thereby promoting cancer progression [4]. Immune checkpoint inhibitors are important regulators that induce tumour cell immune escape mediated by CTCs [4,5,6]. In addition to CTC detection, molecular characterization of these cells is important to understand their biology, predict metastasis formation and select appropriate therapeutic interventions [7,8]. With the advent of immune checkpoint inhibitors, the cancer treatment paradigm has dramatically changed. On the other hand, accumulating evidence suggested that oncogene- and tumour suppressor gene-dependent signalling pathways might play an important role during the malignant transformation by altering the expression of immune checkpoint molecules [9,10,11,12,13,14,15,16]. For instance, Chen et al. (2017) demonstrated a correlation between high PD-L1 (programmed death-ligand 1) expression and KRAS (Kirsten rat sarcoma viral oncogene) mutation in non-small cell lung carcinoma, suggesting that blocking the programmed cell death protein 1(PD-1)/PD-L1 pathway could be a novel therapeutic option for lung cancer with genetic alteration in KRAS [17]. As CTCs have been studied a great deal as minimally invasive and reliable real-time liquid biomarkers in the clinical management of cancer patients, including CRC, tracking the number of CTCs before, during and after cancer treatment is important to better anticipate outcomes and provide insight into the efficacy of treatments such as molecular targeted therapy and immunotherapy in CRC. In addition, the surrounding haematopoetic cells may have impacts on CTCs. Thus, the gene expression profiling of their surrounding immune microenvironment can be used for translational applications, such as the selection of therapeutic targets, including immunotherapy, and monitoring patient response to treatment. However, the clinical relevance of cancer cell-intrinsic genetic events that may cause immune failure in patients with CRC during immunotherapeutic application remains largely unknown. More attention to this gap in knowledge is required to evaluate, and thoroughly to discuss, the unique perspective of CTCs and their surrounding immune cells on the relationship between the expression of genes involved in carcinogenesis of CRC and the molecules that involved in immune escape pathways. Therefore, this study aims to explore the expression profiling of the tumour suppressor genes p53 and APC (adenomatous polyposis coli), the oncogenes KRAS and c-Myc and selected immune checkpoints (PD-L1, CTLA-4 (cytotoxic T-lymphocyte-associated protein 4, CD152) and CD47 in CTCs and peripheral blood mononuclear cells (PBMCs) isolated from patients with CRC. The implications of clinicopathological factors in the expressions of these genes were also studied. The clinicopathological correlation between high versus low CTC-positive patients with CRC was also compared. Preliminary experiments had been performed previously, in which different numbers of colon cancer cell lines were added to peripheral blood collected from healthy donors to evaluate the sensitivity and specificity of the CTC enrichment technique (negative selection method) by estimating the recovery rate of CTCs from a 5 mL blood sample [18]. Screening for different subpopulations of CTC was also validated using a panel of six antibodies (EpCAM, CK18, SNAIL1, MMP-9, E-cadherin, and BCL-2) described in detail previously [18]. In this present study, we selected four epithelial and EMT-related markers from the panel of antibodies (EpCAM, SNAIL1, MMP-9 and E-cadherin) to characterise different subpopulations of CTCs in different patients. The detection images of CTCs and marker expression for different subpopulations are presented in Figure 1. Thirty-eight (61%) of the 62 patients with CRC were positive for at least one marker. Among the 38 patients who tested positive, EpCAM was detected in 35 (92%; mean 14.02, range 2–68), SNAIL1 in 19 (50%; mean 10.6, range 2–36), E-cadherin in 11 (28.9%; mean 5.2, range 2–24), and MMP-9 in 11 (28.9%; mean 4.8, range 2–24) patients (Figure 1B). In 38 patients with CTCs, 7 (18.4%) patients were positive for all four markers, 2 (5.3%) for three markers, 13 (34.2%) for two markers, and 16 (42.1%) for one marker. The cells which were positive for at least one of the markers (EpCAM, SNAIL-1, E-cadherin, and MMP-9) and which had an enlarged nucleus and cell size > 8 μm were considered as CTC positive. Among the 62 CRC-positive patients, 24 patients did not express any of the markers (no CTC), while 20 had < 10 CTCs (low CTC group) and 18 showed ≥ 10 CTCs (high CTC group) in their blood samples (Figure 1C). For the downstream analysis of this study, the population was categorized into two groups: low CTC-positive and high CTC-positive. However, cells isolated from the peripheral blood of healthy donors (n = 6) were also screened for CTCs. We found only one healthy donor positive for EpCAM. Although there is no universal standard cut-off value for CTC positivity, to avoid false-positive counts, the cut-off of ≥2 CTCs/5 mL was chosen to define the presence of CTCs as positive, as described in the previous report [19,20]. Previously, Allard et al. observed that whereas eight of the 145 healthy volunteers recruited had one CTC (5.5%), they found that malignant patients had more than one CTC, suggesting that detection of more than two CTCs per 7.5 mL of blood might be unusual [20]. While a significant number of leukocytes (up to 3 log depletion rate) were removed during the CTC enrichment step, a substantial number of leukocytes were still detected in the CTC-enriched fractions from patients with CRC. In a subset of 27 patients with CTC, we counted the total numbers of nucleated cells in patients with CRC (n = 27, mean 6101.67, range 2272–14096) and heathy donors (n = 6, mean 4550.8, range 3309–5913) using NIS-element AR imaging software (version 5.20) via Widefield Microscope, Nikon Ti-2. Figure S1 shows the number of contaminating leukocytes in enriched fractions isolated from both healthy donors and patients. Due to leukocyte contamination, it is obvious that the target genes were still expressed to some extent in CTC-enriched fractions, which may have affected the gene expression level in a low number of CTCs against the thousands of leukocytes that remained after CTC enrichment. To eliminate the effects arising from contaminating cells, we processed 5 mL of blood from healthy donors (n = 6), performed in the same way as previously for peripheral blood samples from patients, and used this as the control. Next, we performed gene expression profiling in CTC-enriched fractions from the blood of patients with CRC and calibrated the results with those of samples prepared from healthy donors. The relative fold change (2–ΔΔCt) of p53, APC, KRAS, c-Myc and CD47, CTLA-4 in CTCs was calculated by subtracting the average delta Ct values derived from the HD group. If the fold change value was more than 1, the genes were considered as positively expressed. All the target genes except p53 were expressed at lower levels in the blood of healthy donors compared with that in CTC-enriched fractions from patients with CRC (Figure 2). We also evaluated the expression level of CD45 gene (PTPRC) in CTC-enriched fractions, which is a generic leukocyte marker, indicating the presence of contamination by leukocytes. Expression of CD45 was noted to be lower in the CTC-enriched fractions (Figure S2). Finally, we performed mRNA expression analysis of target genes in CTC-enriched fractions and PBMCs. The Ct values of < 35 for all target genes, and < 30 for housekeeping genes, were included for the gene expression analysis. Of the 38 CTC-positive patients, 8 patients were excluded from further research analysis who had no expression or lower expression because of poor mRNA quality in CTC-enriched fractions. In this study, we found increasing KRAS and CTLA-4 expressions in the low CTC-positive group and decreasing p53, APC, c-Myc and CD47 mRNA expressions in both high and low CTC-positive groups when compared with that of healthy donors (Figure 3). However, we found very few CTC-positive patients expressing PD-L1, hence we excluded PD-L1 from further analysis. We also analysed gene expression in PBMC samples from patients with CRC using the same panel of genes that were used for CTCs. Decreased expression was noted for most of the genes in the matched PBMC samples compared with that in CTCs, while higher expression of APC and CTLA-4 in both groups of patients was noted (Figure 3). Next, we compared the expression levels of p53, APC, KRAS and c-Myc with CD47 and CTLA-4 between CTCs and PBMCs. Interestingly, the mRNA expression of CTLA-4 was positively correlated with KRAS (r = 0.6878, p = 0.0002) expression in CTCs (Figure 4A). In addition, CTLA-4 gene expression level tended to be higher in CTCs and PBMCs in patients with KRAS mutation than in patients with KRAS wild type (data obtained from Gold Coast University Hospital and detected by next-generation sequencing on cancer tissue) (Figure 4B). A PCA plot was derived from normalised gene expression data to show variation between high and low CTC groups and PBMCs (Figure 5). However, we found no significant variation in mRNA expression level between these two groups. In addition, heat map imaging of the gene expression data was generated to demonstrate the heterogeneity of gene expression in CTC fractions and PBMCs, showing variable expression pattern and the percentage of positive expression among individual patients with CRC (Figure 6). The correlations between patients’ clinical characteristics and different groups of CTCs based on CTC counts are presented in Table 1. Approximately 64% (7/11) of patients with mucinous adenocarcinoma showed high levels of CTCs, while patients with conventional adenocarcinomas were often presented with lower levels of CTCs (41%, 21/51) (p = 0.019). Additionally, patients with advanced pathological stages (stages III or IV) reported high levels of CTC count when compared with those with early-stage (stage I or II) CRC (44% vs. 21%). Conversely, the high prevalence of zero or low CTC counts was noted among patients with early-stage CRC (44% vs. 30% and 36% vs 27%, respectively) (p = 0.045). In addition, half of the patients with higher CTC counts (9/18) had larger tumour sizes (50 mm or above), while approximately 80% of patients (35/44) with no or low CTC counts had smaller tumour sizes (below 50 mm) (p = 0.051). On the other hand, the number of CTCs had no association with the age or gender of the patients, or with the grade or microsatellite instability (MSI) status of the tumour. Clinical correlations were also evaluated with the mRNA expression level of tested genes. Samples that had no expression were excluded from the clinical analysis. Among those exhibiting mRNA expression, we found significant pathophysiological correlations between KRAS expression in CTCs. Table 2 shows the correlation of the mRNA expression of KRAS in CTCs with the clinical and pathological factors in patients with CRC. High expression of KRAS mRNA was predominantly seen among patients with early-stage compared with those with advanced-stage CRC (75% versus 25%, p = 0.004). Approximately 69% of patients having low CTCs had higher expression of the KRAS gene (approx. 69%, versus 31%, p = 0.039). KRAS gene expression was negatively correlated with lymph node metastasis and distant metastasis (approx. 67% versus 27%, p = 0.037, 61% versus 17%, p = 0.046). Around 58% (15/26) of patients without perforated CRC adenocarcinoma had high expression of the KRAS gene compared with those with cancer that showed perforation (p = 0.029). Conversely, in PBMCs, patients with high KRAS expression were less likely to have a small tumour size. However, we did not find any significant clinical associations. In addition, we found that higher CTLA-4 expression in CTCs was weakly correlated with those cancers with the KRAS mutant (p = 0.06) (Figure 4B), while in PBMCs, CTLA-4 was more likely have higher expression in patients detected with high CTC counts (64% vs. 93%, p = 0.046) and with lymph node metastasis (65% vs. 100%, p = 0.006) (Table 3). CTLA-4 expression was also correlated with pathological stages (63% vs 100%, p = 0.004). The expression levels of other genes did not significantly correlate with clinical or pathological features. The identification of CTCs and their specific gene profiles could offer new perspectives that may improve the prediction of metastasis formation, as well as representing a promising approach for determining better therapeutic targets. Previous studies have reported a significant correlation between CTC counts and pathological stages of various cancers, including CRC [2,18,19,21,22,23,24,25]. In this study, we noted that late-stage cancers more often had higher CTC counts when compared with early-stage cancers (p = 0.045). Patients with mucinous adenocarcinoma, a specific subtype of CRC characterized by over 50% tumour volume composed of extracellular mucin [26], were likely to have high levels of CTCs. In addition, CTC levels were higher in patients with larger tumours. It has been previously reported that patients with colorectal mucinous adenocarcinoma often present with advanced pathological stages and a larger tumour size compared with conventional CRC [27]. Taken together, these clinical correlations imply that a relatively high number of CTCs associated with pathological features of cancer patients can predict tumour aggressiveness and may become more pronounced over time. However, patients with distant metastases were not associated with high CTC counts, implying that the low number of metastatic patients in the study may be the contributing factor for this discrepancy. We did not perform survival analysis in this study due to the limited follow up time. The immune-suppressive microenvironment is significantly involved in CRC carcinogenesis [17]. Immune checkpoint molecules, such as PD-L1, CTLA-4 and CD47, are important regulators that induce tumour cell immune escape [5,6,7]. Immunotherapy using immune checkpoint inhibitors (ICIs) has revolutionised the treatment of many cancers [28]. However, cancer-causing genetic abnormalities determine the tumour immunological context and significantly contribute to therapeutic resistance, including immunotherapy [29]. In this study, we noted that the upregulation of the proto-oncogene KRAS was more prevalent in patients with low CTC counts. Significant correlation with clinical parameters (pathological stage, distant metastasis, lymph node status, perforation) was also noted, which is in line with a previous study suggesting that activation of the KRAS gene may be more prevalent and could be a significant prognostic factor in patients with early-stage cancer [30]. It is worth noting that decreased expression of p53 and APC expression lowers the tumour-suppressive capability of a cell and leads to cell cycle dysregulation and uncontrolled cell growth [31,32]. Further, reduced expression of c-Myc was noted and is well in line with other reports [33,34]. Steinert et al. noted that downregulation of c-Myc may indicate the state of dormancy of CTCs (if Ki-67 expression is also low) [34]. Though no significant variations were found between high vs. low CTC-positive groups, possibly due to the extensive heterogenous nature of CTCs [35], we found comparatively higher expression of these genes in patients detected with low CTC counts. Taken together, our findings suggest that changes in the mRNA expression level of tumour suppressor genes and oncogenes, especially KRAS in CTCs, may become more aggressive at the early stages; thus, CTCs could play a significant role in predicting targeted therapy at the onset of the disease. As the majority of patients with CRC are MSI-stable, discovering novel immunotherapeutic targets are vital in improving the efficacy of immunotherapy [9]. For the first time, we investigated CTLA-4 gene expression in CTCs in CRC, which is usually expressed in immune cells [36]. In a recent study, CTLA-4 expression was evaluated in CRC tissues and different cancer cell lines (HT-29, HCT-166, and SW480) [37]. Only one report found CTLA-4 expression in CTCs in metastatic prostate cancer (mPC), which was rare [6]. Interestingly, we found overexpression of CTLA-4 in patients detected with lower CTC count. In addition, a significant upregulation of CD47 in CTCs plays a potential role in immune escape and thus may also promote the spread of CRC and enhances the stemness of cancer cells [34,38]. However, our data showed decreasing expression level of CD47 in patients with CRC compared with healthy donors, though positive expression were seen in a number of individual patients. This may have happened because of the heterogeneous characteristics of CTCs [35]. The above findings may suggest that CTLA-4 is also expressed in CTCs along with other immune checkpoint molecules, so blocking these inhibitory molecules could improve their therapeutic efficacy. However, additional studies would help to confirm these findings. Current research evidence suggests a significant influence of genetic alterations of tumour suppressor genes and oncogenes in controlling tumour–immune system crosstalk in a variety of malignancies by modulation of the expression of immune checkpoint molecules [10,11,12,13,14,16,17,39]. It is suggested that these driver cancer genes may directly bind to the promoters of immune checkpoint molecules, thereby altering their expression [11]. The positive correlation between CTLA-4 and KRAS expression, and the higher CTLA-4 gene expression in CTC-positive patients having KRAS mutation, therefore, suggest that activation of KRAS may aid CTCs in evading immune surveillance by modifying the expression of CTLA-4. Due to the challenges in isolating and identifying rare CTCs from excessive background cells in peripheral blood, the gene expression profiling of PBMCs could be another hallmark in the clinical management of cancer patients [33]. Interestingly, our data showed a differential expression pattern for the tested genes in PBMCs compared with CTCs. Positive expression of CD47 was noted in a few patients, while APC and CTLA-4 positive expression levels were higher in PBMCs than those in CTCs. Thus, the above findings and the pathophysiological correlations between CTLA-4 gene expression levels suggest that haematopoietic cells may regulate the expression of these genes, providing important information in the clinical management of patients with CRC. It is already known that immune checkpoint molecules are expressed not only in tumour cells but also in a wide variety of haematopoietic cells [36,40], and we acknowledge that there was still a considerable number of leukocytes in the CTC enrichment fraction obtained from peripheral blood of patients with CRC, which might have affected the gene expression profiling of CTCs. Hence, gene expression profiling of single CTCs would be more beneficial in providing more accurate information. Nowadays, the molecular profiling of single CTCs in different cancers, including colorectal carcinomas, is receiving more attention [34,35,41,42]. As this study is an ongoing project, we have obtained some preliminary results with single CTCs isolated from individual patients, which further confirm our findings. Detailed studies are needed to validate and confirm these findings at single-cell level. Nevertheless, this study provides a preliminary concept for understanding that alteration in oncogene KRAS expression may regulate the expression of immune checkpoint molecules, which has a direct role in the initiation and maintenance of cancer gene-driven tumorigenesis. KRAS overexpression may be one general mechanism by which tumour cells upregulate the expression of the immune checkpoint regulator CTLA-4, thereby evading immune surveillance. Additional molecular biology investigations in a large cohort may be necessary to confirm and to elucidate the mechanism underlying this hypothesis. This study also revealed that CTC detection and gene expression profiling of PBMCs, especially for immune regulatory genes, can be another platform to study the cellular heterogeneities, resistance mechanisms and therapeutic targets in cancer. A total of sixty-two patients (35 males, 27 females) with pathologically confirmed CRC and six healthy individuals were prospectively recruited from Gold Coast University Hospital during the period of May 2017 to November 2021 for this study. Ethical approval was obtained from the Griffith University Human Research Ethics Committee (GU Ref No: MSC/17/10/HREC). These patients signed a written informed consent form before participating in the study. Clinical and pathological parameters, including age and gender of patient, as well as the size, location, histological subtype, and microsatellite instability (MSI) status of the patient’s tumour, as detected by immunohistochemistry and pathological staging, were recorded as previously reported [43]. Blood samples were collected from the patient on the day of resection and were processed within one hour of collection. From each of these patients, 15 mL of peripheral blood was collected in heparin-containing BD (Becton Dickinson, Franklin Lakes, NJ, USA) vacutainer tubes at the time of surgery for CRC. In this study, 5 mL of freshly collected blood from each patient was enriched for CTC isolation using a negative selection method (EasySepTM Direct Human CTC Enrichment Kit, STEMCELL Technologies., Vancouver, BC, Canada) according to the manufacturer’s protocol. Briefly, blood was incubated for 10 min twice with a cocktail of different antibody-labelled magnetic beads targeting CD2, CD14, CD16, CD19, CD45, CD61, CD66b, and glycophorin A surface markers at room temperature, allowing the enriched cell suspension collection in a new tube to obtain a pure suspension of CTCs. The enriched CTCs were centrifuged at 450 rcf (relative centrifugal force) for 7 min and resuspended in a CTC growth medium. Then, the enriched CTCs were seeded in a 96-well plate (50 µL per well) for immunofluorescence and in a 6-well plate for downstream analysis, followed by overnight incubation. The composition of CTC growth medium was described in a previously published article [18]. Peripheral blood samples from 6 healthy donors were processed as negative controls in the same way as previously performed for patients with CRC. Immunofluorescence staining was performed for the identification of CTCs using a cocktail of four primary antibodies for EpCAM (Thermo Fisher Scientific, Waltham, MA, USA), SNAIL1, E-cadherin and MMP-9 (Santa Cruz Biotechnology, CA, USA) as described previously [18]. In brief, the enriched cells were fixed with 100% methanol for 10 min at −20 °C and were permeabilised with 0.2% Triton X-100 for 10 min. Cells were then stained with primary antibodies followed by secondary antibodies: rabbit-anti-mouse IgG fluorescein isothiocyanate (FITC) and rabbit anti-goat IgG (H + L) Texas Red (Sigma Aldrich, St. Louis, MO, USA), and labelled with Hoechst 33,342 (ThermoFisher Scientific, Waltham, MA, USA) to stain the nucleus. The cells were counted using a Nikon Ti2 widefield microscope (Nikon Corporation, Tokyo, Japan). The size and fluorescent intensity of CTCs were measured using Nikon NIS-element AR imaging software, version 5.20 (Nikon Corporation, Tokyo, Japan). The number of total nucleated events was also counted using similar software to visualise, annotate and quantify the contaminating cells. High-resolution images were captured using an Olympus Fluoview FV1000 Confocal Microscope (Shinjuku, Tokyo, Japan) at 40× magnification. To avoid the overlapping results between the primary antibodies, we checked for possible cross-species binding of selected secondary antibodies (Figure S3). PBMCs were isolated from 5 mL peripheral blood using Histopaque®-1077 (Sigma Aldrich, St. Louis, MO, USA) gradient centrifugation, following the manufacturer’s guidelines. Briefly, 7 mL of Histopaque was pipetted into a 15 mL falcon tube. The blood sample was carefully layered over the Histopaque gradient and then centrifuged at 400 rcf for 30 min at room temperature. The PBMC layer was collected, and the cell pellet was washed twice in PBS-EDTA (ethylenediaminetetraacetic acid) (10 min/250 rcf at room temperature). The cell pellet was resuspended in RPMI stocking media and stored at −80 °C for further analysis. The total RNA from CTC fractions and PBMCs was extracted using the RNeasy mini kit (Qiagen, Hilden, North Rhine-Westphalia, Germany) according to the manufacturer’s instructions. DNase was used to remove contaminating genomic DNA from the RNA sample. cDNA synthesis was performed using the SensiFAST cDNA synthesis kit (Meridian Bioscience, Cincinnati, OH, USA) following the manufacturer’s guidelines. The resulting cDNA was diluted in nuclease-free water to a final concentration of 100 ng/μL and stored at –20 °C. The values for cDNA and RNA purity (260/280 ratio) and concentration (ng/μL) were measured using a nanoDrop (BioLab, Milford, MA, USA) spectrophotometer. Before performing gene expression analysis, we validated the technical feasibility of qRT-PCR (Figure S4). The pre-amplified products were then analysed for target gene expression using real-time quantitative PCR (qPCR) (QuantStudio, Thermo Fisher Scientific, MA, USA). qPCR was performed using the SensiFAST SYBR No-ROX kit (Meridian Bioscience) according to the manufacturer’s protocol. A total of nine primers for the 7 targets, PTPRC (CD45) and ACTB (β-actin) as endogenous control were purchased from Sigma Aldrich. The list and sequence of chosen primer sets are summarized in Table S1. The relative gene expression levels of target genes were estimated as log2 value of the fold change by the relative quantification 2−ΔΔCt method. Fold changes were calculated as previously reported [44,45]. The statistical analyses of gene expression levels were performed using GraphPad Prism Software 5.03 (GraphPad Software Inc., San Diego, CA, USA). The Kolmogorov–Smirnov non-parametric test was used to compare fold changes between the HD and CTC groups. A two-way ANOVA test (Bonferroni’s multiple comparisons test) was used to compare the various groups of CTCs and PBMCs based on the quantification of CTCs. The values were estimated from the log2 value of the relative quantification of each gene. Spearman’s rank test was performed to check the correlations of p53, APC, KRAS and c-Myc gene expression levels with CD47 and CTLA-4 in CTCs and PBMCs. Principal component analysis (PCA) plots of gene expression data in different groups were generated with log2 transformation of the data with a 95% confidence interval using the ClustVis web tool (https://biit.cs.ut.ee/clustvis/, accessed on 29 August 2022). Association of patient groups based on CTC numbers and gene expression level against clinicopathological parameters of each patient’s cohort were performed using IBM SPSS (Statistical Package for the Social Sciences) statistics, version 29 (International Business Machines, Armonk, NY, USA). The Chi-square test or likelihood ratio was used for categorical variables. A p-value of < 0.05 was considered statistically significant.

PMC10003443

Baohui Yao,Kang An,Yukun Kang,Yuchen Tan,Degang Zhang,Junhu Su

Reproductive Suppression Caused by Spermatogenic Arrest: Transcriptomic Evidence from a Non-Social Animal

27-02-2023

reproductive suppression,delayed testicular development,spermatogenesis,testosterone,AMH,plateau zokor

Reproductive suppression is an adaptive strategy in animal reproduction. The mechanism of reproductive suppression has been studied in social animals, providing an essential basis for understanding the maintenance and development of population stability. However, little is known about it in solitary animals. The plateau zokor is a dominant, subterranean, solitary rodent in the Qinghai–Tibet Plateau. However, the mechanism of reproductive suppression in this animal is unknown. We perform morphological, hormonal, and transcriptomic assays on the testes of male plateau zokors in breeders, in non-breeders, and in the non-breeding season. We found that the testes of non-breeders are smaller in weight and have lower serum testosterone levels than those of breeders, and the mRNA expression levels of the anti-Müllerian hormone (AMH) and its transcription factors are significantly higher in non-breeder testes. Genes related to spermatogenesis are significantly downregulated in both meiotic and post-meiotic stages in non-breeders. Genes related to the meiotic cell cycle, spermatogenesis, flagellated sperm motility, fertilization, and sperm capacitation are significantly downregulated in non-breeders. Our data suggest that high levels of AMH may lead to low levels of testosterone, resulting in delayed testicular development, and physiological reproductive suppression in plateau zokor. This study enriches our understanding of reproductive suppression in solitary mammals and provides a basis for the optimization of managing this species.

Reproductive Suppression Caused by Spermatogenic Arrest: Transcriptomic Evidence from a Non-Social Animal Reproductive suppression is an adaptive strategy in animal reproduction. The mechanism of reproductive suppression has been studied in social animals, providing an essential basis for understanding the maintenance and development of population stability. However, little is known about it in solitary animals. The plateau zokor is a dominant, subterranean, solitary rodent in the Qinghai–Tibet Plateau. However, the mechanism of reproductive suppression in this animal is unknown. We perform morphological, hormonal, and transcriptomic assays on the testes of male plateau zokors in breeders, in non-breeders, and in the non-breeding season. We found that the testes of non-breeders are smaller in weight and have lower serum testosterone levels than those of breeders, and the mRNA expression levels of the anti-Müllerian hormone (AMH) and its transcription factors are significantly higher in non-breeder testes. Genes related to spermatogenesis are significantly downregulated in both meiotic and post-meiotic stages in non-breeders. Genes related to the meiotic cell cycle, spermatogenesis, flagellated sperm motility, fertilization, and sperm capacitation are significantly downregulated in non-breeders. Our data suggest that high levels of AMH may lead to low levels of testosterone, resulting in delayed testicular development, and physiological reproductive suppression in plateau zokor. This study enriches our understanding of reproductive suppression in solitary mammals and provides a basis for the optimization of managing this species. Reproduction is the most essential life-history strategy for animals, and the success and efficiency of reproduction affect species survival, population continuation, and evolution [1,2,3]. Environmental change can lead to changes in organisms’ social status, population size, and the number of mates, causing them to adjust their reproductive activities until conditions are more favorable [1,2]. This inhibition of reproductive development, physiology, and/or behavior due to specific environmental or physiological conditions is known as reproductive suppression [1,2,3]. The occurrence of this suppression is sometimes active (the self-limitation hypothesis) [4], but also occurs in passive situations (the dominance control hypothesis) [5], as well as temporary suppression (e.g., interference with mating) [6] and long-term suppression (e.g., most physiological suppression, in the naked mole-rat (Heterochephalus glaber)) [7]. Although many advances have been made in understanding the patterns, processes, and mechanisms of reproductive suppression, these results have predominantly come from social animals. In social mammals, male reproductive suppression is caused primarily by behaviors [8] that include avoidance of inbreeding in the birth group [3,9], direct interference with mating [6], and infanticide [10], or the inability to find a suitable mate [9]. However, physiological suppression also occurs, and the physiological suppression of reproduction involves endocrine dysfunction of the hypothalamic–pituitary–gonadal (HPG) axis [11]. Physiological suppression is principally manifested in delayed puberty or arrested development of secondary sexual characteristics [12,13], impaired or delayed gonadal and gametic development [7,14,15], decreased reproductive hormone levels [10,16], and changes in the molecular environment (i.e., in the expression of reproduction-related genes) [17,18,19]. Some genes are downregulated in subordinate males compared to the dominant male naked mole-rats; for example, genes (PRM1, PRM2, ODF3, and AKAP4) involved in sperm maturation at the post-meiotic stage [17]. Genes involved in metabolic and energy-related processes, including lipid biosynthesis, redox processes, and steroid metabolism, as well as genes involved in endocrine signaling (SSTR3, TAC4, PRDX1, and ACPP), are downregulated [18]. Genes (CYP11A1, ABCG8, and SCARB1) involved in steroid hormone biosynthetic pathways are downregulated [19]. These diverse phenomena and mechanisms of reproductive suppression have been reported in social animals, with only isolated reports in solitary animals [2]. Revealing the mechanisms of reproductive suppression in more species would be essential to enriching both the theory and practical management of reproductive regulation. The plateau zokor (Eospalax baileyi) is a typical solitary subterranean rodent in the Qinghai–Tibet plateau (QTP), along with naked mole-rats belonging to Spalacidae [20]. Breeding occurs once a year in groups during the breeding season (mid-April to mid-June), while they live alone during the non-breeding season [21]. The plateau zokor acts as an ecological engineer at a natural population density [22]. As their population density increases, excessive underground excavation causes further damage to vegetation and soil, resulting in the plateau zokor being regarded as a pest [23]. Control practices, such as poison and arrow trap capture [24], have caused the zokor age structure to become younger, so more young individuals had the opportunity to reproduce [25]. These control measures have disrupted the original social structure of the plateau zokor, which may also affect population regulation and reproduction. After some individuals were removed, the remaining individuals’ reproductive opportunities increased. For males, the interference of dominant males with subordinate males was reduced when dominant males were removed. The population density decreased and the reproductive competition among males decreased. The territories, food resources, and nutrition became better, expanding males’ opportunities to find females. Likewise, opportunities for females to exert stricter mate choice also increased. Due to the high energy cost of cave dwelling underground, the cost of finding a mate and burrowing in subterranean species may be higher compared to surface species, potentially leading to variation in reproductive skew like that of naked mole-rats [26]. Surveys of plateau zokor breeding rates revealed that some adult males in undisturbed sample sites (sites of no control measures for plateau zokor) did not participate in breeding, and paternity analysis of offspring DNA found that 2–4 dominant males sired most of the offspring in a colony (12–18 per colony). Therefore, plateau zokors may exhibit reproductive suppression. We also found that testes size became larger with increasing body weight during the breeding season, but some adult males had smaller, undeveloped testes during the breeding season. Moreover, in the disturbed sample sites (sites with control measures for plateau zokor), the reproductive rate of plateau zokors was higher than in undisturbed sample sites [25]. Thus, reproductive suppression in plateau zokors may be physiological. Previous studies have reported genomic and transcriptomic analyses of reproductive repression in social species e.g., [17,18,19], but studies of solitary mammals are rare [2,4,6]. In addition, reproductive suppression was disturbed by improper control measures, which made species management more difficult. In this study, we analyzed testicular size, morphology, hormone levels, and RNA-seq transcriptome of male breeders and non-breeders during the breeding season. We collected testes of plateau zokor in the non-breeding season as a control. We aim to reveal the mechanism of physiological reproductive suppression by detecting differences in hormones, testicular development, spermatogenesis, and transcriptome in male plateau zokors. The study of reproductive suppression in solitary mammals will enrich the theory and case studies of reproductive suppression, allowing us to better understand the reproductive strategy, population regulation and population maintenance mechanisms, and management best practices of plateau zokor. We found that the external genitalia and male reproductive tract in male breeders (BSB), non-breeders in the breeding season (BSA), and non-breeding-season males (NBS) were normal, with the size being the only difference. There was a significant decrease in testicular weight (F = 99.62, p = 0.00) and testicular coefficient (F = 81.60, p = 0.00) in BSA and NBS compared to BSB. At the same time, there were no differences in testicular weight and testicular coefficient between BSA and NBS (p > 0.05) (Figure 1A,B). Observation of H&E staining sections then revealed a great many germ cells at all levels in the testes of BSB within the seminiferous tubule, including spermatogonia, primary spermatocytes, secondary spermatocytes, round spermatozoa, and long spermatozoa; whereas in BSA and NBS, only spermatogonia, Sertoli cells, and Leydig cells could be observed in the testes (Figure 1C–E). Serum GnRH (F = 8.78, p = 0.004) was higher in BSB than in BSA and NBS, but only the difference between BSB and NBS was significant (p < 0.05) (Figure 2A). Levels of LH (F = 7.06, p = 0.011) were highest in BSA; these were significantly different from NBS but not BSB (p < 0.05) (Figure 2C). The differences in serum FSH (F = 2.39, p = 0.142) levels between BSB, BSA, and NBS were not significant (Figure 2D). BSB serum testosterone (F = 26.44, p = 0.001) levels were significantly higher compared to BSA and NBS (p < 0.05), whereas there was no difference in serum testosterone levels between BSA and NBS (p > 0.05) (Figure 2B). To investigate the gene expression differences that lead to differences between BSA, BSB, and NBS, we analyzed the RNA-seq data to find differentially expressed genes (DEGs). By considering libraries, a total of 12,975 (upregulated: 5014, downregulated: 7961), 5672 (upregulated: 2369, downregulated: 3303), and 15,327 (upregulated: 8365, downregulated: 6962) DEGs were identified in BSA–BSB, BSA–NBS, and BSB–NBS plateau zokor testes, respectively (Figure 3A). From the cluster diagram, BSA and NBS were clustered into one group, significantly different from BSB (Figure 3B). Among the differentially expressed transcripts, Table 1 shows the ten most highly up and downregulated transcripts in BSA, BSB, and NBS. AMH is a marker of the action of FSH in the prepubertal testes (Figure 4A). Transcription factors bind to the AMH promoter, triggering AMH expression and increasing AMH production. The mRNA levels of AMH and its transcription factors SOX9 (F = 12.44, p = 0.007), SF1 (F = 22.50, p = 0.001), and GATA4 (F = 11.00, p = 0.010) were significantly higher in the BSA and NBS compared to the BSB (Figure 4B). To further analyze which stages of spermatogenesis arrest in plateau zokors, we imported clusters of spermatogenesis-related genes that were specifically expressed in mouse spermatogenesis (mitotic, meiotic, post-meiotic, and somatic clusters) from the Germonline database, and mapped them to the DEGs that were identified in the BSA, BSB, and NBS testes. A total of 2793 DEGs in BSA–BSB (Supplementary Table S1), 743 in BSA–NBS (Supplementary Table S2), and 2805 in BSB–NBS (Supplementary Table S3) were involved in different stages of plateau zokor spermatogenesis. In the BSA–BSB comparison, DEGs of somatic and mitotic clusters in BSA were larger than in BSB, while DEGs in meiotic and post-meiotic clusters were smaller than in BSB. In BSA–NBS, the DEGs of the meiotic and post-meiotic clusters in BSA were larger than in NBS. In BSB–NBS, DEGs of somatic and mitotic clusters in the BSB were smaller than in NBS, whereas DEGs of meiotic and post-meiotic clusters were larger than in NBS (Figure 5A). Furthermore, we mapped the expression level of all genes in these four clusters. In the BSA–BSB group, gene expression was downregulated at the meiotic and post-meiotic stages of spermatogenesis in BSA compared to BSB. In BSA–NBS, gene expression was upregulated in spermatozoa at the meiotic and post-meiotic stages in BSA compared to NBS. In BSB–NBS, gene expression was upregulated at the meiotic and post-meiotic stages of spermatogenesis in BSB compared to NBS (Figure 5B). Finally, to understand the characteristics of the spermatogenesis arrest in plateau zokor, we examined both pre- and post-meiotic gene markers of spermatogenesis. In BSA, BSB, and NBS, the mRNA expression levels of ZBTB16 (F = 0.36, p = 0.714) and STRA8 (F = 0.56, p = 0.601) (pre-meiotic markers) were not significantly different, and SYCE1 (F = 47.93, p = 0.000) and SYCP3 (F = 17.49, p = 0.003) (meiotic markers) in BSB were significantly greater than BSA and NBS. For the genes TEKT1 (F = 95.86, p = 0.000) and CATSPER1 (F = 324.38, p = 0.000) (post-meiotic markers), BSB was greater than BSA, BSA was greater than NBS, and the difference was significant (Figure 5C). Furthermore, we investigated the morphological differences in plateau zokor testes of different status using immunostaining analysis. From immunostaining analysis, we observed that ZBTB16 (PLZF) and KIT were expressed in spermatogonia in the BSA, BSB, and NBS testes (Figure 6A,B). SYCP3 was expressed in spermatocytes in the BSB testes. SYCP3 has not expressed in the BSA and NBS testes (Figure 6C). To study the correlation between genes differentially expressed in testes and germ-line function, we looked for GO term enrichment in the four clusters (Figure 7). In the somatic cluster, the downregulated genes in BSA–BSB and the upregulated genes in BSB–NBS were significantly enriched in GO terms related to cholesterol biosynthetic process, steroid biosynthetic process, and sterol biosynthetic process. In the somatic and mitotic clusters, the upregulated genes in BSA–BSB and the downregulated genes in BSB–NBS were significantly enriched in GO terms related to apoptotic process (including regulation of apoptotic process and positive regulation of apoptotic process), cell adhesion and response to estradiol. The downregulated genes in BSA–NBS were significantly enriched in GO terms related to regulation of apoptotic process and positive regulation of apoptotic process. In the meiotic and post-meiotic clusters, the downregulated genes in BSA–BSB and the upregulated genes in BSB–NBS were significantly enriched in GO terms related to spermatogenesis (including flagellated sperm motility, cilium assembly, spermatid development, and fertilization), sperm structure (including sperm flagellum, sperm midpiece, sperm principal piece, cilium, and acrosomal vesicle), meiotic cell cycle, and male meiosis. KEGG enrichment of differentially expressed genes in the four clusters of testes are shown in Figure 8. In the somatic and mitotic clusters, the upregulated genes in BSA–BSB and the downregulated genes in BSB–NBS were significantly enriched in Pathways in cancer, Focal adhesion, Relaxin signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, ECM-receptor interaction, Hippo signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. In the meiotic cluster, the downregulated genes in BSA–BSB and the upregulated genes in BSB–NBS were significantly enriched in Oocyte meiosis, Progesterone-mediated oocyte maturation, Amyotrophic lateral sclerosis, Glycerophospholipid metabolism, Glycerolipid metabolism, AMPK signaling pathway, and Ubiquitin mediated proteolysis. Nine genes (AMH, SOX9, SF1, ZBTB16, STRA8, SYCE1, SYCP3, TEKT1, CATSPER1) were selected for verification. The results showed that the change trends of these nine genes detected by qPCR were consistent with those from the RNA-seq data (Figure 9), confirming that the RNA-seq data were authentic. The qPCR validation further improves the reliability of the present study. By studying the testicular size, morphology, hormones, and transcriptome of plateau zokor breeders, non-breeders, and non-breeding-season males, we found that plateau zokors experience reproductive suppression. Non-breeder plateau zokors had small testes, low testosterone levels, and a unique gene expression profile, with the number and relative expression of testicular differentially expressed genes significantly decreased during meiosis. The results of H&E staining and immunohistochemistry sections showed that the germ cells of the non-breeders were spermatogonia. Thus, the spermatogenic arrest of the non-breeders occurred at the spermatogonia stage. The transcriptomic data obtained in this study will help to elucidate testes development in plateau zokors. Results of reproductive suppression in social mammals include reduced levels of reproductive hormones [10,14,16] and impaired or delayed gonadal and gamete development [7,12,13,15]. For example, compared with dominant naked mole-rats, testicular size was small in subordinate males, testosterone levels were lower in subordinate males, and genes involved in spermatogenesis were downregulated in subordinate males [7,17,18,19]. Our findings are consistent with these results. In this study, we investigated the physiological mechanism of reproductive suppression in solitary animals, which is valuable for understanding the reproductive strategies of mammals. AMH and its transcription factors are involved in pubertal development in humans [27,28]. We found that the mRNA levels of AMH and its upstream transcription factors SOX9, SF1, and GATA4 were significantly higher in BSA, and verified that all the test males were normal individuals (the external genitalia and male reproductive tract in BSB, BSA, and NBS were normal, with the size only difference). Through H&E staining, it can be observed that the germ cells of the testicular tissue of BSA plateau zokors stayed at the stage of spermatogonia, which is similar to the results of H&E staining of testicular tissue of our NSB plateau zokors, indicating that BSA plateau zokor is similar to NSB plateau zokors. Both testes and accessory gonad tissues of BSA degenerate, but they still have the potential to develop into a mature state during the breeding period and participate in reproduction. AMH is secreted by male fetal testicular Sertoli cells, inhibits the development of the Müllerian duct, and makes the mesonephric duct develop into the male reproductive duct under the action of testosterone. Compared with the level before puberty, testosterone in the testes affects the serum level of AMH through androgen receptors after the beginning of puberty and makes AMH decline continuously throughout puberty [29]. In normal puberty, androgens inhibit AMH expression more than FSH-dependent stimulation. In pubertal delay and defective androgen secretion or sensitivity, the lack of androgen secretion or action results in unrestricted activation of the transcription factors SOX9, SF1, and GATA4 of AMH [27], thus increasing AMH mRNA expression and serum AMH. However, intratesticular administration of AMH caused a decline in serum testosterone concentrations by decreasing the rate of testosterone biosynthesis, confirming that AMH can regulate adult Leydig cells androgen production [30]. High testosterone levels promote testicular development, spermatogenesis, and maturation, and dominant males with higher testosterone levels may have higher-quality semen than subordinate males [29]. After 8 weeks of testosterone injection into male plateau zokors during the non-breeding season, An et al. found that the testicular weight increased by 2.9 times compared with the control group [31]. Immunohistochemical results showed that Stra8, γH2AX, and SYCP3 positive cells increased. The results showed that testosterone could promote the differentiation of spermatogonia of plateau zokor in the non-breeding season [31]. Therefore, in this study, high levels of AMH may lead to low levels of testosterone, resulting in delayed testicular development, which physiologically inhibited reproduction in the non-breeder plateau zokor. As previous studies have been conducted to verify AMH and its upstream transcription factors SOX9, SF1, and GATA4 [28], our conclusions are well supported. In the non-breeding season, the expression of AMH was higher compared to the breeding season. AMH in the non-breeding season was also higher compared to the breeding season in the male plateau pika (Ochotona curzoniae) [32]. However, in naked mole-rats, there was no significant difference in AMH mRNA expression between breeders and non-breeders, according to the supplementary data of Bens et al. [18]. In this study, significant differences were found between the top 10 genes up- and downregulated in breeders, non-breeders, and non-breeding-season males. In BSA–BSB, the top 10 upregulated genes were mainly involved in the regulation of the blood–testes barrier (KLF6) [33] and inhibition of spermatogonial differentiation (SHISA6) [34]. The downregulated genes were involved in spermatogenesis and sperm motility (TNP [35], SPATA3 [36], CCIN [37], SPPL2C [38], ATP1A4 [39], and OXCT [40]). In BSA–NBS, the top 10 upregulated genes were mainly involved in spermatogenesis (SYT13 [41], SCNN1B [42], SPATA31D1 [43], TSPAN8 [44], PTN [45]). Downregulated genes were involved in spermatogenesis and sperm motility (CD38 [46], FGD2 [47]) and apoptosis (RRAD) [48]. In BSB–NBS, the top 10 upregulated genes were mainly involved in spermatogenesis (GSG1 [49], ODF1 [50], SPATA20 [51], SPATA18 [52], HSPA1L [53], DNAH17 [54], and ACTL7A [55]). Downregulated genes were involved in apoptosis (RRAD [48] and IFI27 [56]). Compared with BSB, BSA spermatogenesis-related genes were downregulated, indicating the spermatogenic arrest in BSA. In this study, we found that the gene expression profiles of breeders, non-breeders, and non-breeding season individuals differed significantly between somatic, mitotic, meiotic, and post-meiotic clusters. The differences at the transcriptome level in non-breeder testes compared to breeders were mainly at the meiotic stage. The KIT is a marker for differentiating spermatogonial stem cells in several species including mice and goats [57]. In mice, STRA8 is expressed in differentiated spermatogonia and pre-meiotic spermatocytes, and STRA8 knockout mouse spermatogonia can initiate meiosis but fail to complete it [58]. ZBTB16 (also known as PLZF) is expressed in undifferentiated spermatogonia and is generally used as a marker for undifferentiated spermatogonia [59]. SYCE1 (Synaptonemal Complex Central Element 1) is formed between homologous chromosomes during meiotic prophase and exists only during the first meiotic division [60]. SYCP3 (Conjugation Complex Protein) is required for the assembly of the conjugation complex and is expressed in human spermatocytes during prophase I of meiosis from spermatogonia to the coelomic phase [61]. TEKT1 is involved in the development of sperm axonemes and flagella in mice [62]. In humans, CATSPER1 (Cation Channel Sperm-Associated 1), a plasma membrane protein present in the sperm principal piece, is involved in sperm activation and acrosome reactions [63]. Based on our study of H&E staining and immunohistochemistry sections of the testes of breeders and non-breeders, we confirmed that the spermatogenic arrest of the non-breeders occurred at the spermatogonia stage. ZBTB16 and KIT were expressed in spermatogonia in the BSA, BSB, and NBS testes. SYCP3 was expressed in spermatocytes in the BSB testes, but not in BSA and NBS testes. By verifying the mRNA expression levels of meiosis-related markers, the results showed that pre-meiotic markers were not significantly different in non-breeder testes compared to breeder testes. In contrast, meiotic markers and post-meiotic markers were significantly decreased, confirming that the spermatogenic arrest of the non-breeders occurred at the spermatogonia stage. In our study, the physiological suppression of non-breeder plateau zokors was caused by the delayed testicular development. In contrast, differences in spermatogenesis in both breeding and non-breeding males were mainly at the post-meiotic stage in the naked mole-rat [17]. This was due to non-breeding naked mole-rats being primarily subject to behavioral suppression and spermatogenesis occurring between the breeding and non-breeding seasons. Nonetheless, non-breeding males show impaired post-meiotic sperm maturation [17]. Across mammals, the main reason for the prepubertal testicular size is the number of Sertoli cells. After puberty, testicular volume increases dramatically as spermatogenesis begins, germ cells start to differentiate and increase, and germ cells become more numerous [27,30]. The normal proliferation of Sertoli cells increases testes size, whereas premature cessation of Sertoli cell proliferation due to delayed testicular development results in smaller testes [64]. In our study, the small size and weight of the testes in non-breeders may be due to a lack of germ cell proliferation and premature cessation of Sertoli cells. An et al. [31] found that there was no significant difference in the FSH level of plateau zokor between breeding and non-breeding season, which was consistent with the results of our present study. Insufficient testosterone secretion caused the spermatogenic arrest. Low levels of testosterone in BSA and NBS maintain the survival of germ cells, and high levels of testosterone in BSB regulate spermatogenesis and animal reproductive behavior. Although the levels of LH and FSH in the BSA group were high. However, the non-breeder plateau zokors were in the puberty stage, with small testicles and incomplete testicular development. In addition, genes related to meiotic cell cycle, spermatogenesis, flagellated sperm motility, fertilization, sperm capacitation, and sperm structure in non-breeders were downregulated. Therefore, the testosterone level of the BSA group was low and spermatogenesis was incomplete. GO analysis of genes from somatic, mitotic, meiotic, and post-meiotic clusters revealed that genes related to cholesterol biosynthetic processes and steroid biosynthetic processes were significantly downregulated in the somatic clusters. In our study, we hypothesize that the downregulation of key genes in steroid biosynthesis processes caused an inadequate supply of energy in the testes of non-breeder plateau zokors. In contrast, genes involved in metabolic and energy-related processes such as lipid biosynthesis processes and steroid metabolism processes were also found to be primarily upregulated in the testes of dominant naked mole-rats, indicating increased energy demand in dominant males [18]. Cell adhesion is associated with the blood–testes barrier, which protects developing germ cells from autoimmune responses and exogenous substances [65]. Genes related to cell adhesion were significantly upregulated in somatic and mitotic clusters. This may prevent the separation of germ cells from the basement membrane and subsequent migration to the lumen of the seminiferous tubules in the non-breeders. Estrogen plays a crucial role in normal testicular development and spermatogenesis. It has been shown that 17β-estradiol acts through ESR1 and GPER to activate the EGFR/ERK/c-Jun pathway, and then induces the expression of apoptosis-related genes in germ cells [66]. In this study, genes related to response to estradiol were upregulated in the non-breeders compared to breeders, suggesting that apoptosis occurred in non-breeder spermatogenesis. Apoptosis is a physiological mechanism of programmed cell death that requires eliminating misplaced or damaged cells by genetic decision. It is essential for the normal formation and maintenance of germ cells in the testes. A large increase in germ cell apoptosis is involved in male idiopathic sterility [67]. In our study, genes involved in apoptotic processes were significantly upregulated in somatic and mitotic clusters in non-breeders, suggesting that apoptosis occurs in testicular germ cells of non-breeders, thereby affecting spermatogenesis. Spermatogenesis is a finely regulated process of germ cell proliferation and differentiation [68]. In this study, genes involved in spermatogenesis were downregulated in non-breeders, affecting normal sperm formation and testicular development. Meiosis was downregulated so that the spermatogenic arrest of the non-breeders occurred at the spermatogonia stage which affected normal sperm production. Apoptotic processes increased, and spermatogenesis decreased in non-breeders compared to breeders. Neither non-breeders nor non-breeding season testes were enriched for spermatozoa, suggesting that mature sperm production was not present in non-breeders. Through H&E staining and immunohistochemistry sections, it can be observed that the germ cells of the testicular tissue of non-breeders stayed at the stage of spermatogonia, which was similar to the results of non-breeding season testes. In conclusion, the spermatogenic arrest of the non-breeders occurred at the spermatogonia stage. Increased apoptosis, decreased spermatogenesis during meiosis, and inadequate energy supply may be manifested in the testes of infertile individuals. KEGG analysis of genes from the four expression clusters revealed that genes related to pathways in cancer, focal adhesion, MAPK signaling pathway, PI3K-Akt signaling pathway, and Hippo signaling pathway were significantly upregulated in the somatic and mitotic clusters in non-breeder plateau zokors. Upregulation of genes such as PI3K, AKT, and FOXO3 in the PI3k/Akt pathway leads to upregulation of CDKN1B, which encodes a protein that binds to and prevents activation of the cyclin E-CDK2 or cyclin D-CDK4 complexes, thereby controlling cell cycle progression in G1 [69]. Upregulation of CDKN1B inhibits testes Sertoli cell proliferation. The Hippo pathway regulates multiple cellular functions, e.g., cell proliferation, apoptosis, migration, and differentiation, inhibits excessive cell proliferation, and stimulates apoptosis during development [70]. It has been found that MST1 overexpression regulates the apoptotic cascade response of caspases, which further triggers apoptosis. In addition, increased YAP activity is usually associated with cell cycle entry and apoptosis inhibition. In the present study, both MST1 and YAP expression were upregulated in non-breeders, suggesting that testicular cells in the non-breeders were apoptotic. In the testes of non-breeders, genes involved in AMPK signaling pathway, Oocyte meiosis, and Progesterone-mediated oocyte maturation were downregulated during meiosis. The AMPK signaling pathway maintains the stability of the blood–testes barrier, and in Sertoli cells is a crucial regulator that provides lactate for the energy metabolism of germ cells and maintains spermatogenesis [71]. In contrast, in the present study, the AMPK signaling pathway was significantly downregulated during meiosis in the testes of non-breeders, suggesting that the blood–testes barrier and energy supply are disrupted in non-breeders. In our study, genes related to the oocyte meiosis pathway were also downregulated during meiosis. Although the oocyte meiosis pathway plays a role in female fertility, genes detected in this pathway also regulate sperm meiosis I and II in male spermatogenesis [72]. Downregulated genes of the oocyte meiotic pathway may thus impair sperm meiosis I and II in non-breeder plateau zokors. Genes related to progesterone-mediated oocyte maturation pathway were significantly downregulated during meiosis, and progesterone is a crucial step in stimulating the spermatogonia stage of spermatogenesis via this pathway [73]. Thus, the downregulation of genes in the progesterone pathway observed in our data may prevent spermatogenesis in non-breeders. We show that the main differences in testicular spermatogenesis between non-breeders and breeders in plateau zokors are associated with genes necessary for the meiotic stage. Compared to breeders, the genes of non-breeders at the meiotic and post-meiotic stages of spermatogenesis were significantly downregulated. The non-breeder cannot express key genes at the meiotic stage, resulting in reduced germ cell numbers, smaller testes, damaged and reduced spermatozoa, and reduced testosterone synthesis. In conclusion, our study of plateau zokor testes showed that non-breeders showed meiosis arrest of spermatogenesis. This can result in reduced and impaired sperm counts, which may account for their inability to participate in reproduction. In this study, we aimed to explore the molecular mechanism of gene expression in the spermatogenesis of plateau zokor testes. The next step will be to verify protein expression and function analysis. A normal population will have self-regulation of reproduction, and it is impossible to reproduce too much. Like most subterranean rodents, the density of plateau zokor has risen rapidly through the reproduction of survivors after control measures [74]. For subterranean rodents, reproductive suppression plays an important role in population self-regulation. Reproductive suppression may be a normal phenomenon in many species. In plateau zokor, it has been found that the proportion of reproductive suppression is higher in undisturbed sites compared with disturbed sites. This is because the population control measures (capturing, trapping, and poisoning) have altered the original social structure, making the age structure of the colony younger [25,75]. In this situation, the dominant males may be removed, so that the original reproductive suppression disappears, and subordinate males have the chance to reproduce. After population control measures, the average diffusion distance of plateau zokors was constant [21]. Therefore, the rapid recovery of plateau zokor populations after population control measures is not the result of diffusion and migration, but the result of reproductive compensation. One possible speculation is that the occurrence of plateau zokor damage on the Tibetan plateau may be due to human disturbance breaking the phenomenon of reproductive suppression. In the follow-up management, such reproductive suppression should be considered, or new prevention and control measures should be innovated from suppression and recovery to play more ecological roles. As plateau zokors are typically subterranean rodents, their activities generally occur underground and are difficult to observe. We have only been able to determine the reproductive suppression of plateau zokors through gonadal development and reproductive hormone levels. The reproduction and reproductive suppression of plateau zokors requires further research. We caught plateau zokors alive with tube traps (Baoji Ludixincheng Co. Ltd., Xi’an, China) during the breeding (end of April 2020) and non-breeding (October 2020) seasons in the alpine meadow–steppe area northeast of QTP in Tianzhu Tibetan Autonomous County, Gansu Province, China (37°19′ N, 102°75′ E). The tube trap is a cylinder with a mechanism at one end that can catch subterranean rodents alive so that the animals are not hurt. We found plateau zokor tunnels, dug into them, and put the tube trap into the tunnel. When plateau zokors passed through the tunnel, they were trapped in the tube trap. We checked the tube traps every 20 min. Generally, the age structure of wild rodents was identified on the basis of their body weight or carcass weight, and they were divided into sub-adult, adult, and elderly categories [25,75]. However, no study has been performed on the age determination of plateau zokors in terms of years. According to speculation and observation, plateau zokors generally live for 7–8 years. In addition, plateau zokors may be long-lived like naked mole-rats and other subterranean rodents [74]. During the breeding period, the plateau zokors were captured in the undisturbed sample plot, and 74 adult male plateau zokors were selected according to the age division of the plateau zokor by Su et al. [75]. Male plateau zokors were first examined for breeding status based on their testes; breeders have relatively larger testes, which can be palpated as a bulge in the inguinal pockets in the abdominal region [26]. Next, euthanized males were dissected to determine if they were breeders based on testicular weight. We found that the testes of 4 adult male plateau zokors did not develop, and the reproductive suppression rate was 5.40% (4/74). To verify the reproductive suppression rate, we found an undisturbed sample site for capture, and 39 adult plateau zokors were captured. We found that two of the captured plateau zokors that were altered had no development of sexual organs, and the reproductive suppression rate was 5.13% (2/39). Four males were non-breeders in the breeding season (BSA) and 20 were breeders in the breeding season (BSB) from 74 adult male plateau zokors. Another 20 adult males were captured in the non-breeding season (NBS). Thus, four BSA, 20 BSB, and 20 NBS were used for analysis. First, plateau zokors were euthanized under anesthesia with isoflurane inhalation. Secondly, plateau zokors were dissected, blood was collected, testes were weighed, and testicular coefficients (testicular coefficient = testicular weight/body weight × 100%) were calculated. Finally, one testis per animal was placed in a 10% formalin solution for fixation and sectioned for H&E staining. Another testis was immersed in liquid nitrogen and used to extract total RNA. This experimental protocol was reviewed and approved by the Animal Ethics Committee of Gansu Agricultural University (approval number GAU-LC-2020-014), and conducted in compliance with the ARRIVE guidelines. We used enzyme-linked immunosorbent assay kits for GnRH, LH, FSH, and testosterone from Cloud-Clone Corp. (Wuhan, China). Hormone determination and conditions followed those of Kang et al. [74]. Testicles were obtained from the 10% formalin solution stored samples, then embedded in paraffin wax. After the embedded was complete, 5 µm sections were sliced using a rotary slicer (Leica RM2255). The sections were respectively stained with hematoxylin and eosin solution. Finally, the sections were dehydrated with a graded ethanol and xylene series, respectively. The sections were sealed with neutral gum before microscopic examination and photography. Testes sections were deparaffinized and rehydrated with xylene and a graded ethanol series, respectively. Testes sections were soaked in sodium citrate buffer solution for antigen repair, and 3% H2O2 was used to eliminate endogenous peroxidase activity and washed with PBS. The experimental group was treated with rabbit anti-PLZF (Boaosen, Beijing, China, BS-5971R, 1:250), rabbit anti-KIT (Boaosen, Beijing, China, BS-0672R, 1:250), and rabbit anti-SYCP3 (Boaosen, Beijing, China, BS-106606R, 1:250), and the negative control was treated with PBS. Sheep anti-rabbit IgG and horseradish enzyme-labeled chain albumen working solution was then added, incubated at 37℃, and stained with DAB (Boaosen, Beijing, China, C-0010) and hematoxylin. Then, the sections were dehydrated using an ethyl alcohol series, cleared in xylene, and photographed using Motic Images Plus 3.0 software. Three testicular samples each from the BSA, BSB, and NBS groups were selected for transcriptome sequencing and sent to Beijing NovoGene Co., Ltd. (Beijing, China) for sequencing. Total RNA was isolated from the nine testicular tissues with an RNA Nano 6000 Assay Kit (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer’s protocols. The Agilent 2100 bioanalyzer and NanoPhotometer spectrophotometer were adopted to assess RNA integrity and concentration. Library preparation. Total RNA was used as input material for the RNA sample preparations. Briefly, mRNA was purified from total RNA using poly T oligo-attached magnetic beads, and cDNA was synthesized using mRNA as a template. Selected cDNA library fragments that were preferentially 370–420 bp in length were purified with the AMPure XP system (Beckman Coulter, Beverly, MA, USA). After PCR amplification, the PCR product was purified with AMPure XP beads, and the library was finally obtained. After construction, the library was initially quantified using a Qubit2.0 fluorometer. qRT-PCR was applied to accurately quantify the effective concentration of the library (higher than 2 nM) to ensure the quality of the library. Transcriptomic sequencing. After the library was quantified, the different libraries were pooled according to the effective concentrations and the target amounts of data produced and sequenced with the Illumina NovaSeq 6000 machine with 150 bp ends read. Quality control. The image data measured with the high-throughput sequencer were converted into sequence data (reads) using CASAVA base recognition. Raw data (raw reads) in fastq format were first processed through in-house perl scripts, and clean data (clean reads) were obtained by removing reads that contained adapters, reads containing N bases, and low-quality reads from the raw data. Q20, Q30, and GC content of the clean data were then calculated. All the downstream analyses were based on the clean, high-quality data. Read mapping to the reference genome. Reference genome (BioProjects: PRJNA254049; Nannospalax galili) and gene model annotation files were downloaded from the genome website directly. An index of the reference genome was constructed using Hisat2 (v2.0.5) and paired-end clean reads were aligned to the reference genome using Hisat2 (v2.0.5). Novel transcript prediction. The mapped reads of each sample were assembled with StringTie (v1.3.3b) in a reference-based approach. Quantification of gene expression level. FeatureCounts v1.5.0-p3 was implemented to count the read numbers mapped to each gene, and the FPKM for each gene was calculated based on the length of the gene and read count mapped to the gene. Differential expression analysis. Differential expression analysis of two conditions/groups (two biological replicates per condition) was performed using the DESeq2 R package (1.20.0). Padj ≤ 0.05 and |log2 (fold-change)| ≥ 1 were set as the threshold for significant differential expression. Gene clusters expressed at somatic (SO), mitotic (MI), meiotic (ME), and post-meiotic (PM) stages of mouse spermatogenesis were obtained from Germonline (v.4.0) [76] and mapped to the DEGs that were identified in the plateau zokor testes, following the methods of Mulugeta et al. [17]. The different stages of spermatogenesis DEGs were classified as upregulated or downregulated and plotted [17,77]. DAVID 6.8 (https://david.ncifcrf.gov, accessed on 14 May 2022) was used to perform GO and KEGG analysis in four gene clusters differentially expressed in testes [78]. Each cluster was matched with enriched GO terms and KEGG pathways that were ordered according to peak expression in SO, MI, ME, and PM clusters [77]. In order to validate the expression profile of genes from RNA-seq, we chose nine genes for further quantitative real-time PCR (qPCR) detection. Reverse transcription was performed using Evo M-MLV RT Premix for the qPCR kit (Accurate, Changsha, China). The cDNA was amplified by qPCR using TB Green® Premix Ex Taq™ II (Takara, Beijing, China) in a real-time PCR system (Light Cycler 96 System, Roche). The 2−ΔΔCq method was used to deal with the results of qPCR, and the relative expression level of each gene was corrected using the reference gene. A commercial sequencing system (TsingKe, Xi’an, China) was used to synthesize the primer sequences (Table 2). R (v.3.5.2) software was used for statistical analysis [79]. Testicular weight and serum hormones were compared using the aov function. For the comparison of relative gene expression of three sample groups, an ANOVA was applied followed by Duncan’s post hoc test. The threshold for significance was p < 0.05. We found that the testes of non-breeders are smaller in weight than those of breeders, and high levels of AMH may lead to low levels of testosterone, resulting in delayed testicular development, and physiological reproductive suppression in plateau zokor. Genes related to spermatogenesis are significantly downregulated in both meiotic and post-meiotic stages in non-breeders. Our study uncovered insights into testicular development and spermatogenesis under reproductive suppression in plateau zokors, which are of great value in enriching our understanding of reproductive suppression in solitary mammals.

PMC10003449

Abdullah Md. Sheikh,Shozo Yano,Shatera Tabassum,Shingo Mitaki,Makoto Michikawa,Atsushi Nagai

Alzheimer’s Amyloid β Peptide Induces Angiogenesis in an Alzheimer’s Disease Model Mouse through Placental Growth Factor and Angiopoietin 2 Expressions

24-02-2023

Alzheimer’s disease,amyloid β peptide,angiogenesis,placental growth factor,angiopoietin 2

Increased angiogenesis, especially the pathological type, has been documented in Alzheimer’s disease (AD) brains, and it is considered to be activated due to a vascular dysfunction-mediated hypoxic condition. To understand the role of the amyloid β (Aβ) peptide in angiogenesis, we analyzed its effects on the brains of young APP transgenic AD model mice. Immunostaining results revealed that Aβ was mainly localized intracellularly, with very few immunopositive vessels, and there was no extracellular deposition at this age. Solanum tuberosum lectin staining demonstrated that compared to their wild-type littermates, the vessel number was only increased in the cortex of J20 mice. CD105 staining also showed an increased number of new vessels in the cortex, some of which were partially positive for collagen4. Real-time PCR results demonstrated that placental growth factor (PlGF) and angiopoietin 2 (AngII) mRNA were increased in both the cortex and hippocampus of J20 mice compared to their wild-type littermates. However, vascular endothelial growth factor (VEGF) mRNA did not change. Immunofluorescence staining confirmed the increased expression of PlGF and AngII in the cortex of the J20 mice. Neuronal cells were positive for PlGF and AngII. Treatment of a neural stem cell line (NMW7) with synthetic Aβ1–42 directly increased the expression of PlGF and AngII, at mRNA levels, and AngII at protein levels. Thus, these pilot data indicate that pathological angiogenesis exists in AD brains due to the direct effects of early Aβ accumulation, suggesting that the Aβ peptide regulates angiogenesis through PlGF and AngII expression.

Alzheimer’s Amyloid β Peptide Induces Angiogenesis in an Alzheimer’s Disease Model Mouse through Placental Growth Factor and Angiopoietin 2 Expressions Increased angiogenesis, especially the pathological type, has been documented in Alzheimer’s disease (AD) brains, and it is considered to be activated due to a vascular dysfunction-mediated hypoxic condition. To understand the role of the amyloid β (Aβ) peptide in angiogenesis, we analyzed its effects on the brains of young APP transgenic AD model mice. Immunostaining results revealed that Aβ was mainly localized intracellularly, with very few immunopositive vessels, and there was no extracellular deposition at this age. Solanum tuberosum lectin staining demonstrated that compared to their wild-type littermates, the vessel number was only increased in the cortex of J20 mice. CD105 staining also showed an increased number of new vessels in the cortex, some of which were partially positive for collagen4. Real-time PCR results demonstrated that placental growth factor (PlGF) and angiopoietin 2 (AngII) mRNA were increased in both the cortex and hippocampus of J20 mice compared to their wild-type littermates. However, vascular endothelial growth factor (VEGF) mRNA did not change. Immunofluorescence staining confirmed the increased expression of PlGF and AngII in the cortex of the J20 mice. Neuronal cells were positive for PlGF and AngII. Treatment of a neural stem cell line (NMW7) with synthetic Aβ1–42 directly increased the expression of PlGF and AngII, at mRNA levels, and AngII at protein levels. Thus, these pilot data indicate that pathological angiogenesis exists in AD brains due to the direct effects of early Aβ accumulation, suggesting that the Aβ peptide regulates angiogenesis through PlGF and AngII expression. Alzheimer’s disease (AD) is a common dementia disease characterized by a progressive decline in cognitive functions [1]. Pathologically, amyloid plaques and intraneuronal neurofibrillary tangles are the main diagnostic criteria of AD [2]. Amyloid plaques primarily contain an aggregated form of amyloid β (Aβ), a 39–42 amino acids-long peptide fragment generated from membranous amyloid precursor protein (APP) by β- and γ-secretase enzyme activities [2,3]. This peptide is aggregation-prone and deposited in the brain parenchyma as oligomers or amyloid fibrils [4]. Aggregated Aβ shows neurodegenerative and neuroinflammatory properties [5,6]. These features (neurodegeneration and neuroinflammation) are always found in AD brains, indicating the potential importance of aggregation and deposition of the Aβ peptide in the pathology [3]. Probable causes of Aβ deposition are suggested to be increased production or decreased clearance [7]. After production, Aβ is cleared from the brain by enzymatic degradation and by phagocytic cells [8,9,10,11]. However, a bulk of the peptide is cleared through perivascular pathways [7]. Due to its high aggregation properties, Aβ may aggregate during its clearance and interfere with the perivascular pathways. Hence, the deposition of the peptide around the vessels could be an important feature of AD pathology. Indeed, deposition of Aβ is frequently seen around the vessels that cause amyloid angiopathy, along with AD pathology [12]. Such deposition causes the vessel to become fragile, resulting in microbleeds and associated inflammation [13]. In addition to neurodegeneration and neuroinflammation, increased angiogenesis is frequently seen in AD brains [14]. Aβ peptide demonstrated toxicity, not only towards neurons, but also towards the vascular cells, including endothelial cells and smooth muscle cells [15,16]. It is suggested that Aβ deposition might cause the dysfunction of vessel function, resulting in a hypoxic condition in AD brains [17]. Additionally, vascular dysfunction can induce an inflammatory response [18]. All these signals trigger the angiogenic process [14,19]. Hence, angiogenesis in AD is considered an indirect consequence of Aβ deposition-dependent vascular dysfunction. Such angiogenesis is mainly a pathologic type, which might cause the extravasation of blood constituents and the aggravation of the neuroinflammatory condition [10]. However, Aβ can directly induce inflammatory conditions [20]. Since inflammation and angiogenesis are intimately related [21], it is possible that Aβ can directly induce angiogenesis long before the occurrence of vascular dysfunctions and the related inflammation. Therefore, we hypothesized that angiogenesis is an early feature of AD pathology, which is a direct consequence of excess Aβ in the brain. In this study, we investigated the direct effects of Aβ on angiogenesis in AD using disease model mice and in vitro cell culture systems. To eliminate the role of vascular dysfunction in AD angiogenesis, we used young AD model animals prior to Aβ deposition in the vessels. We found that Aβ can directly induce pathological angiogenesis by altering the expression of several angiogenesis factors. Increased angiogenesis has been documented in AD brains due to vascular dysfunction and hypoxia [22,23]. Since Aβ deposition in vessel walls is considered a main pathological cause of vascular dysfunction and subsequent angiogenesis in AD [3,17], it was evaluated in APP transgenic mice (J20 strain) brains at an earlier time point (2 months). Immunostaining results showed that Aβ was mainly intraneuronal in the cortex and hippocampal areas at this time point, and very few vessels were Aβ immunopositive (Figure 1A and Supplementary Figure S1). The staining demonstrated a wide distribution pattern of Aβ in the cortex, but in the hippocampus CA1 areas, Aβ mainly positive in the pyramidal cell layer (Figure 1A). Quantification of the staining showed that at 2 months of age, the levels of Aβ in the J20 mice brains were higher than those in the wild-type mice (cortex Wt: 0.1 ± 0.09 vs. J20: 2.9 ± 1.2, p < 0.001; hippocampus Wt: 0.1 ± 0.09 vs. J20: 2.4 ± 0.75, p < 0.001), in which they was almost negative (Figure 1B). Then, double immunofluorescence staining was performed to identify Aβ-positive cells. The results demonstrated that Aβ was mainly positive in NeuN-positive neurons at this age (Supplementary Figure S1C). Since the antibody used for Aβ staining (6E10) can also detect amyloid precursor protein (APP) [24], immunostaining was performed using an APP-specific antibody. The results showed that at this time point, the staining pattern of APP was comparable to Aβ (Supplementary Figure S2). Moreover, APP-positive areas in the cortical and hippocampal areas of wild-type mice were similar to those of J20 (Supplementary Figure S2B). At 15 months of age, extracellular deposits of Aβ were found both in the cortical and hippocampal areas of J20 mice, and the immunopositive areas in both regions were increased compared to those of the 2-month-old mice (Supplementary Figure S1A,B). Since Aβ has the propensity to oligomerize, immunostaining was performed using an oligomer-specific antibody. The results showed that anti-oligomer immunopositive cells were mainly located in the cortical areas, with a few positive cells in the hippocampus (Figure 1C). Quantification of the staining revealed that the anti-oligomer immunopositive areas were increased both in the cortex and hippocampus of the J20 mice compared to the wild-type mice, in which they were almost negative (cortex Wt 0.19 ± 0.06 vs. J20 3 ± 0.76, p < 0.01; hippocampus Wt 0.22 ± 0.05 vs. J20 0.53 ± 0.17, p < 0.05) (Figure 1C,D). The vessel staining with STL showed that the number was increased only in the cortex (Wt: 30.5 ± 1.4 vs. J20: 43.7 ± 1.7, p < 0.001), but not in the hippocampal areas of J20 mice (Wt: 22.5 ± 2.1 vs. J20: 27.1 ± 4.5, p = 0.08) (Figure 1E,F). Endothelial cells, especially angiogenic endothelial cells, express CD105 [25]. Immunostaining of CD105 showed a round-shaped appearance, along with long vessel-like structures in the cortex of the mice. The areas of such round-shaped CD105 positive structures were increased in J20 mice at 2 months of age (Wt: 2.4 ± 0.38 vs. J20: 6 ± 0.59, p < 0.05) (Figure 2A,B). However, in the hippocampus, the CD105-positive areas appeared to be similar between the Wt and J20 mice (Figure 2A,B). Next, the types of newly formed vessels were evaluated by double immunofluorescence staining of CD105 and collagen4 (Col4), where Col4 was used as a basement membrane marker. The results demonstrated that in the cortex of the J20 mice brains, many CD105-positive vessels lacked Col4 (Figure 2C). First, the expression of angiogenesis regulators was evaluated at mRNA levels. The real-time PCR results showed that the mRNA of angiogenesis inducers such as VEGF was not increased in the cortex or hippocampal areas of J20 mice brains (cortex Wt: 0.88 ± 0.1 vs. J20: 0.81 ± 0.6, p = 0.044; hippocampus Wt: 0.74 ± 0.26 vs. J20: 1.32 ± 0.99, p = 0.23) (Figure 3A,B). However, the mRNA of PlGF, an angiogenesis inducer of the VEGF family [26], was increased in both the cortex and the hippocampus of J20 mice brains compared to those of their wild-type counterparts (cortex Wt: 1.17 ± 0.25 vs. J20: 2.94 ± 0.5, p < 0.01; hippocampus Wt: 1.12 ± 0.1 vs. J20: 5.2 ± 2.1, p < 0.05) (Figure 3A,B). Additionally, the mRNA of angiopoietin2 (Ang2), an angiogenesis regulator that destabilizes the vessels, was increased in those areas (cortex Wt: 1.47 ± 0.42 vs. J20: 3 ± 0.62, p < 0.05; hippocampus Wt: 2.19 ± 0.62 vs. J20 2.97 ± 0.15, p < 0.05) (Figure 3A,B). Conversely, the mRNA of Ang1 was not changed (cortex Wt: 0.87 ± 0.11 vs. J20: 0.78 ± 0.15, p = 0.21; hippocampus Wt: 1.06 ± 0.36 vs. J20: 1.61 ± 0.42, p = 0.08). Then, the expression of angiogenesis regulators in J20 mice brains at the protein level was evaluated. The immunostaining results showed that although the % immunopositive area of VEGF protein was increased in the cortical areas, it was not changed in the hippocampus of J20 mice brains compared to their wild-type counterparts (cortex Wt: 0.52 ± 0.17 vs. J20: 2.5 ± 0.66, p < 0.01; hippocampus Wt: 0.5 ± 0.6 vs. J20: 0.74 ± 0.23, p = 0.11) (Figure 4A,C and Supplementary Figure S3A). Moreover, the levels of VEGF and HIF-1α were very low in both the cortex and hippocampus of Wt and J20 mice at this time point (Figure 4B,C and Supplementary Figure S3B). Next, we evaluated the expression of PlGF and AngII in the J20 mouse brains at protein levels. Immunostaining results demonstrated that PlGF was expressed mainly in the neuron-like cells in the cortex (Figure 4D). Its expression in the hippocampus was lower than in the cortex. Quantification of immunostaining results showed that the % immunopositive area of PlGF protein was significantly increased in the cortex of J20 mice compared to their wild-type counterparts, whereas it was not changed in the hippocampus (cortex Wt: 1.36 ± 0.29 vs. J20: 4.84 ± 0.82, p < 0.01; hippocampus Wt: 2.05 ± 0.35 vs. J20: 1.56 ± 0.27, p = 0.39) (Figure 4F). In the case of Ang2, the staining pattern showed a round-shaped appearance (Figure 4E). Similar to PlGF, the % immunopositive area of Ang2 protein was higher in the cortex compared to the hippocampus. Compared to the wild-type, Ang2 was increased both in the cortex and hippocampus of J20 mice (cortex Wt: 0.52 ± 0.21 vs. J20: 4.2 ± 0.98, p < 0.01; hippocampus Wt: 0.07 ± 0.05 vs. J20: 1.8 ± 0.3.1, p < 0.01) (Figure 4F). To identify whether neurons expressed PlGF and AngII in J20 mouse brains, double immunofluorescence experiments were performed using NeuN neuronal labeling. The results showed that in J20 mice brains, many neurons were positive for PlGF in the cortex (Figure 5A and Supplementary Figure S4). Some of the neurons in the hippocampus were also positive (Figure 5A). Conversely, a few neurons were positive for AngII only in the cortical areas (Figure 5B and Supplementary Figure S5). Since neurons expressed both PlGF and AngII in vivo in J20 mice brains, we investigated the direct effects of the Aβ peptide on the expression of PlGF and AngII in a mouse neural stem cell line (NMW7) culture. After stimulating NMW7 with a synthetic Aβ1–42 peptide, the mRNA levels of both PlGF and AngII were significantly increased compared to moderately stimulated cells (PlGF: (−): 1.18 ± 0.19, Aβ: 3.28 ± 0.64, p < 0.05; AngII: (−): 1.08 ± 0.08, Aβ: 4.68 ± 1.8 p < 0.05) (Figure 6A). Evaluation of AngII expression at protein levels by immunocytochemistry also confirmed the Aβ1–42-induced increased expression of AngII in NMW7 culture (Figure 6B and Supplementary Figure S6). In this study, we demonstrated that a pathological angiogenesis process is active in AD model mouse brains from an early age, which is not dependent on vascular dysfunction or hypoxic condition. Moreover, we elucidated the underlying molecular mechanism of such an early angiogenesis process, where PlGF and AngII play an important role. Since this is a transgenic model that expresses an increased amount of APP, the probable cause of such angiogenesis could be increased levels of Aβ peptide. Further in vitro experiments confirmed that Aβ indeed has the ability to increase PlGF and AngII expression in neuron cultures. Angiogenesis, especially vascular dysfunction, and subsequent hypoxia-dependent pathological angiogenesis are reported in the brains of AD subjects, which is manifested as a redistribution of tight junction proteins and impaired blood-brain barrier function [27,28,29]. Such angiogenesis type and vascular dysfunction are suggested to play an important role in the development and progression of AD [14,17]. Hence, understanding the molecular mechanism of this process could be important for developing a new therapeutic intervention that targets angiogenesis and BBB restoration. Such therapy could not only inhibit the onset, but also slow the progression of AD pathology. In this respect, the findings of our study are important because we demonstrated that in addition to vascular dysfunction-mediated hypoxic angiogenesis, Aβ-dependent angiogenesis exists in the AD condition, and it appeared early in the pathology. Such findings may help to devise a more effective strategy to combat angiogenesis and thereby the onset and progression of AD pathology. Staining data of the vessels, especially endoglin-positive new vessels, showed that the numbers were increased in the cortical areas of APP transgenic mice, whereas in the hippocampal region, they were largely unaffected. These results suggest that angiogenesis starts mainly in the cortical region of the mice at early time points, which may then spread to hippocampal areas. Aβ positive neurons are widely spread in the cortical areas, whereas the positive cells were found in compact areas at the pyramidal cell layer and dentate gyrus of the hippocampus. Such distribution might initially increase the Aβ-induced expression of angiogenesis regulators in a wide area of the cortex. Indeed, angiogenesis regulators, including PlGF and AngII, were mainly increased in the cortex, emitting a strong signal that induces angiogenesis in these areas. In humans, cerebral amyloid angiopathy and related vascular dysfunction are suggested to affect small vessels in the cortical areas [30,31]. Moreover, amyloid deposits start in the cortical areas and spread to the hippocampal areas at a later stage [32,33]. These findings suggest that cortical areas are the initial target of Aβ-dependent vascular pathology and hypoxia-dependent angiogenesis. In this report, we demonstrated that PlGF-mediated angiogenesis signals exist in the same areas early in the disease process before the development of hypoxic conditions or vessel amyloid deposits. Another important aspect of this type of angiogenesis is that AngII levels were increased without affecting AngI levels. The balance and synchronized expression of AngI and AngII is necessary for effective angiogenesis, because AngI is known to stabilize newly formed vessels, and AngII antagonizes this effect [34,35,36]. Consequently, increased expression of AngII might prevent the stabilization of newly formed vessels, resulting in pathological angiogenesis. In addition, VEGF family proteins, including PlGF, are known to induce angiogenesis by destabilizing the vessels and reducing endothelial tight junction proteins [37]. Hence, the combined effects of increased PlGF and AngII might induce pathological angiogenesis at this early time point. Decreased basement proteins and endothelial tight junction complexes are considered markers of pathological angiogenesis [38,39]. Here, we showed that some of the newly formed vessels are devoid of basement membrane protein collagen4. Moreover, in a recent report, we have shown that tight junction protein claudin-5 levels are decreased in this AD model mouse at 2 months [40], indicating that here, angiogenesis is a pathological type. Although the cause of decreased tight junction protein claudin-5 in such pathological conditions could be due to increased PlGF protein, the reduction of collagen4 requires some protease activity. In angiogenesis conditions, proteases, including matrix metalloprotease 9 (MMP9), are considered important [41,42]. MMP9 has been shown to be increased in AD [43]. Such increased MMPs might participate in the angiogenesis process by degrading matrix proteins and tight junction complexes, along with other angiogenesis regulators. It will be interesting to investigate the regulations of protease activities at earlier time points in AD models, along with their relationships with the pathological processes. Several reports of both animal models and human post-mortem studies demonstrated the presence of pathological angiogenesis in AD, which is suggested to be the consequence of impaired cerebral blood flow seen in AD [27,44,45]. The cause of impaired blood flow could be due to Aβ deposition and subsequent pathological changes in cerebral blood vessels [46]. In response, the expression of hypoxia-inducing factor 1α (HIF-1α) and its downstream factors, including VEGF expression, are increased, leading to a pathological angiogenic condition [47]. In our model of AD, we find that Aβ deposition around cerebral vessels is not extensive at 2 months, at which time they mainly showed an intracellular localization in the neuron-like cells. Moreover, HIF-1α protein levels were low at this time point. These results suggest that at an early time point, HIF-1α- and VEGF-dependent angiogenesis might not be important. However, Aβ peptide is known to induce an inflammatory condition, such as the expression of IL-1β, that may induce VEGF expression [48,49]. Since the neuroinflammatory condition is found to increase with time in this mouse model, such neuroinflammation-induced angiogenesis might also be important, and it should be investigated in this model in a time-dependent manner. In vessel analysis experiments, we observed that both the total vessel numbers and the endoglin-positive new vessel numbers were increased in the APP transgenic mice cortex at 2 months of age. However, the difference in endoglin-positive new vessel numbers between APP transgenic mice and their wild-type counterparts was more pronounced than the difference in total vessel numbers. Such differences in total and new vessel numbers might be caused by the simultaneous presence of angiogenesis and vessel degradation signals in this area. The Aβ peptide showed a direct inhibitory effect on endothelial cell proliferation, and it induces apoptosis [15,27,50]. Hence, endothelial cell death by Aβ might have a negative effect on the difference in total vessel numbers between APP transgenic mice and their wild-type counterparts. As a source of PlGF and AngII, we found that neurons can produce both, especially in the cortical areas. PlGF was found to be almost exclusively expressed by neurons, whereas AngII-positive neurons were very few. The morphology of the majority of AngII-positive cells was round-shaped, indicating the microglial type. Although we did not evaluate the involvement of microglia, our in vitro neuronal culture study demonstrated that the Aβ peptide can directly increase the mRNA expression of both PlGF and AngII in the neurons. Previous studies showed that both AngII and PlGF expression can be regulated by NF-κB transcription factors [51,52]. In fact, NOX2-mediated ROS production is important for NF-κB activation and subsequent AngII expression [52]. In neurons, Aβ has the ability to increase NOX2 activity and ROS production [53]. Additionally, ROS can activate NF-κB in neurons [53]. Taken together, it is possible that Aβ-induced ROS production activates NF-κB in neurons, which leads to the induction of PlGF and AngII. PlGF can also be regulated by endoplasmic reticulum (ER) stress and inflammation [54,55]. Aβ can cause ER stress in the neurons and neuroinflammation [56]. Moreover, our immunostaining results showed that intracellular Aβ was oligomerized. Such oligomerized Aβ might regulate the ER stress and neuroinflammation in a way that affects the expression of PlGF. Nevertheless, a detailed study is necessary to understand the exact mechanisms of how Aβ regulates PlGF expression. In this study, B6.Cg-Zbtb20Tg(PDGFB-APPSwInd)20Lms/2Mmjax mice, commonly known as J20, were used as an AD model. Both J20 and their wild-type littermates were generous gifts from Dr. Makoto Michikawa of Nagoya City University, Japan. This transgenic mouse model expresses human amyloid precursor proteins harboring both the Swedish (K670N/M671L) and the Indiana (V717F) mutations. As a control, a non-transgenic littermate of the same age was used. All animal experimental procedures were approved by the ethical committee of Shimane University, and the animals were handled according to the guidelines of the Animal Institute of Shimane University and the guidelines of the Declaration of Helsinki. Animals were kept under a constant room temperature of 23 ± 2 °C under a 12 h light-dark cycle, with free access to water and normal chow. For immunohistochemical analysis, both J20 transgenic mice and their wild-type littermates at 2 months and 15 months (5 mice in a group) of age were deeply anesthetized with isoflurane and transcardially perfused with normal saline and 4% paraformaldehyde. The brains were extracted, postfixed, and cryoprotected, and 2 mm thick tissue blocks were prepared. For staining, 8 μm thick tissue slices were sectioned on a cryostat (Leica biosystem, Buffalo Grove, IL, USA). Tissue sections were treated with a blocking solution (5% normal goat or horse serum, 0.2% Triton X-100 in PBS) for 30 min, followed by incubation in anti-Aβ IgG (6E10, Rabbit, 1:200, Novus, Continental, CO, USA), anti-CD105 IgG (rat, 1:200, BioLegend, San Diego, CA, USA), anti-collagen4 IgG (rabbit, 1:200, Abcam, Cambridge, UK), anti-VEGF IgG (rabbit, 1:200, Santa Cruz, Dallas, TX, USA), anti-HIF-1α IgG (mouse, 1:200, Santa Cruz, CA, USA), anti-PlGF IgG (rabbit, 1:100, ProteinTech, Chicago, IL, USA), anti-APP IgG (rabbit, 1:100, AnaSpec, San Jose, CA, USA), anti-NeuN IgG (mouse, 1:200, Millipore), anti-oligomer IgG (A11, rabbit, 1:50, Invitrogen, Carlsbad CA, USA), or anti-AngII IgG (rabbit, 1:100, Novus) overnight at 4 °C. For the detection of immunoreactive proteins with fluorophores, the tissue sections were treated for 1 h at room temperature with species-specific IgG conjugated with Texas Red or FITC. During light microscopy, the section was treated with species-specific IgG conjugated with biotin (1:100, Vector, Ingold Road, CA, USA) at room temperature for 1 h. Then the tissue was treated with an avidin-biotin-peroxidase complex (ABC, Vector, Burlingame, CA, USA) for 30 min at room temperature. The immune reaction products were visualized with 3, 30-diaminobenzidine (DAB, Sigma, St. Louis, MO, USA) and counterstained with hematoxylin. Stained sections were examined under a fluorescent microscope (NIKON, ECLIPSE E600). Two tissue sections about 1 mm apart, starting from −1.54 mm from bregma to −2.7 mm, were used for the quantification of immunoreactive areas in the hippocampus. For the frontal cortex, two tissue sections of about 1 mm apart, starting from +0.5 mm to −0.5 mm from bregma, were used. Photomicrographs were taken at ×400 magnifications in five random microscopic fields of the designated areas. The immunoreactive areas were evaluated using ImageJ and expressed as a percent of the total area of the field. When immune reactions were detected by DAB, the IHC profiler Plugins of ImageJ were used for the quantification of the areas. To identify vessels in the brain tissues, FITC-conjugated STL was used. After a brief wash with PBS, an 8 μm thick brain tissue section was incubated with STL (1:200, Vector) for 1 h. The tissue was washed 3 times for 5 min with PBS, mounted with a water-based mount medium, and examined under a fluorescent microscope (NIKON, ECLIPSE E600). Photomicrographs were taken at ×400 magnifications in five random microscopic fields of the designated areas, and the vessels were counted using ImageJ. A neural stem cell (NSC) line (NMW7) was generated from a mouse fetal brain, as described previously [57]. The cells were cultured with medium containing high glucose DMEM (Wako Pure Chemicals, Richmond, VA, USA): F12 ham (Wako) 1:1, bFGF (PeproTech, Rocky Hill, NJ, USA), 20 ng/mL, EGF (peproTech), 20 ng/mL, N2 supplement (ThermoFisher, Waltham, MA, USA), and 2% FBS (Gibco, Invitrogen) in an attached culture condition. The NSC was sub-cultured every 48 h. During stimulation, high glucose DMEM medium containing 0.2% FBS, with or without indicated concentrations of Aβ1–42 (Peptide Institute, Osaka, Japan), was used. Aβ1–42 was added to the culture as a monomer, and the stimulations were continued for the indicated times. Total RNA was isolated from cultured cells after appropriate treatment, or from the cortical or hippocampal tissues of the mice using Trizol reagent (Invitrogen), according to the manufacturer’s instructions. To prepare the first strand cDNA, 2 μg of total RNA was reverse transcribed with reverse transcriptase enzyme (RiverTraAce, Toyobo, Osaka, Japan) in a 20 μL reaction mixture. To analyze mRNA levels, real-time PCR was performed with a SyBr green PCR system (Applied Biosystem, Warrington, UK) and appropriate gene-specific primers using an ABI Prism 7800 Sequence Detector system (Applied Biosystems). The mRNA level was normalized by corresponding GAPDH mRNA and quantified using the relative quantification method. For immunocytochemistry, NMW7 cells were cultured in the wells of 8-well chamber slides. After appropriate treatment, the cells were fixed with 4% paraformaldehyde in PBS for 10 min. Cells were incubated in a blocking solution (5% normal goat serum, 0.5% TritonX100 in PBS) for 30 min and then incubated with anti-AngII IgG (Novus) overnight at 4 °C. The cells were treated with goat anti-rabbit IgG conjugated with biotin (1:100, Vector) at room temperature for 1 h. Then, the tissue was treated with an avidin-biotin-peroxidase complex (ABC, Vector) for 30 min at room temperature. The immune reaction products were visualized with 3, 30-diaminobenzidine (DAB, Sigma, St. Louis, MO, USA) and counterstained with hematoxylin. For fluorescent microscopy, the immunoreactive protein was detected using FITC-conjugated goat anti-rabbit IgG (1:100, Santa Cruz), and the fluorescence signals were examined under a fluorescent microscope (NIKON, ECLIPSE E600). Nuclei were identified with Hoechst. The fluorescent intensities were quantified using ImageJ. All numerical data are presented here as average ± standard deviation (SD). The statistical analysis to evaluate the differences between the two groups was performed using T TEST (Microsoft Excel). In conclusion, our result demonstrated that a pathological angiogenesis process and the levels of angiogenesis regulators, including PlGF and AngII, were increased in an Alzheimer’s disease mouse model at an earlier time when HIF-1α expression was not changed. Such increased levels of angiogenesis regulators could be important for the pathology of Alzheimer’s disease.

PMC10003453

Rahul M. Nikam,Heidi H. Kecskemethy,Vinay V. R. Kandula,Lauren W. Averill,Sigrid A. Langhans,Xuyi Yue

Abusive Head Trauma Animal Models: Focus on Biomarkers

24-02-2023

abusive head trauma,animal model,biomarker,neurodegeneration,reactive oxygen,N-methyl-D-aspartate receptor,glia

Abusive head trauma (AHT) is a serious traumatic brain injury and the leading cause of death in children younger than 2 years. The development of experimental animal models to simulate clinical AHT cases is challenging. Several animal models have been designed to mimic the pathophysiological and behavioral changes in pediatric AHT, ranging from lissencephalic rodents to gyrencephalic piglets, lambs, and non-human primates. These models can provide helpful information for AHT, but many studies utilizing them lack consistent and rigorous characterization of brain changes and have low reproducibility of the inflicted trauma. Clinical translatability of animal models is also limited due to significant structural differences between developing infant human brains and the brains of animals, and an insufficient ability to mimic the effects of long-term degenerative diseases and to model how secondary injuries impact the development of the brain in children. Nevertheless, animal models can provide clues on biochemical effectors that mediate secondary brain injury after AHT including neuroinflammation, excitotoxicity, reactive oxygen toxicity, axonal damage, and neuronal death. They also allow for investigation of the interdependency of injured neurons and analysis of the cell types involved in neuronal degeneration and malfunction. This review first focuses on the clinical challenges in diagnosing AHT and describes various biomarkers in clinical AHT cases. Then typical preclinical biomarkers such as microglia and astrocytes, reactive oxygen species, and activated N-methyl-D-aspartate receptors in AHT are described, and the value and limitations of animal models in preclinical drug discovery for AHT are discussed.

Abusive Head Trauma Animal Models: Focus on Biomarkers Abusive head trauma (AHT) is a serious traumatic brain injury and the leading cause of death in children younger than 2 years. The development of experimental animal models to simulate clinical AHT cases is challenging. Several animal models have been designed to mimic the pathophysiological and behavioral changes in pediatric AHT, ranging from lissencephalic rodents to gyrencephalic piglets, lambs, and non-human primates. These models can provide helpful information for AHT, but many studies utilizing them lack consistent and rigorous characterization of brain changes and have low reproducibility of the inflicted trauma. Clinical translatability of animal models is also limited due to significant structural differences between developing infant human brains and the brains of animals, and an insufficient ability to mimic the effects of long-term degenerative diseases and to model how secondary injuries impact the development of the brain in children. Nevertheless, animal models can provide clues on biochemical effectors that mediate secondary brain injury after AHT including neuroinflammation, excitotoxicity, reactive oxygen toxicity, axonal damage, and neuronal death. They also allow for investigation of the interdependency of injured neurons and analysis of the cell types involved in neuronal degeneration and malfunction. This review first focuses on the clinical challenges in diagnosing AHT and describes various biomarkers in clinical AHT cases. Then typical preclinical biomarkers such as microglia and astrocytes, reactive oxygen species, and activated N-methyl-D-aspartate receptors in AHT are described, and the value and limitations of animal models in preclinical drug discovery for AHT are discussed. Abusive head trauma (AHT), also called non-accidental head injury or shaken baby syndrome, is a form of child abuse where a perpetrator violently applies repeated acceleration–deceleration forces to an infant with or without head blunt impact. AHT is the leading cause of death from trauma in children under the age of 2 years [1,2]. The median age of AHT victims is 4 months [3]. AHT has a high mortality rate of around 25% and morbidity incidence of 50% in survivors [4,5]. Subdural hematoma (SDH), cerebral ischemia, retinal hemorrhage, and skull fractures are the most common pathologic consequences of AHT [6]. In the United States, 13–36% of AHT victims die from injuries. In addition, most survivors suffer permanent physical, neurological, and mental disabilities including cerebral palsy, epilepsy, depression, anxiety, and posttraumatic stress disorder [7,8]. AHT in ages 0 to 4 years has been estimated to add USD 13.5 billion in societal costs each year [9]. Early and accurate diagnosis is critical, but correctly diagnosing AHT is challenging clinically and radiologically, even for experienced and astute physicians. Clinical symptoms may be subtle and histological data for the patients are often lacking. Jenny et al. [10] summarized the inflicted traumatic brain injury (iTBI) cases of 173 children younger than 3 years old and showed that physicians missed 31% of AHT cases on initial presentation. Among the missed patients, around one-third were injured again before the iTBI was confirmed, and 41% of the missed cases showed medical complications related to iTBI. Notably, four of the five deaths may have been preventable had the diagnosis been timely. Some studies also reported that approximately half of the children with iTBI did not present with any external trauma [11,12], while others showed only subtle indications of trauma. Conversely, an incorrect diagnosis may have significant implications on social and familial outcomes, such as infants being removed from their homes and parents losing child custody [10,13,14]. The missed and inaccurate diagnosis of AHT places the child at risk due to possible ongoing abuse and potentially life-threatening outcomes [10,15]. A particular diagnostic challenge is that abused children are usually too young to provide an adequate history to explain their symptoms [13,16]. Perpetrators are either unaware of the harmful behavior or unlikely to provide truthful confessions of trauma. Infants often show neither external signs of injury nor present a history of trauma, with non-specific symptoms such as vomiting and fussiness and a normal physical exam [11,12,17]. The diagnosis of AHT is a medical diagnosis formulated by a multidisciplinary collaborative effort considering all facts and evidence. It signifies that accidental and disease processes cannot plausibly explain the etiology of a child’s injuries. As aptly mentioned in the consensus statement on abusive head trauma in infants and young children by Choudhary et al., “A diagnosis of AHT is a medical conclusion, not a legal determination of the intent of the perpetrator or, in the false hyperbole of the courtroom and sensationalistic media, ‘a diagnosis of murder’” [18]. Imaging approaches pose additional diagnostic challenges because current imaging modalities do not provide independently specific or diagnostic results for AHT [18]. Computed tomography (CT) is the examination of choice in the initial evaluation of pediatric head trauma. However, early cranial CT in the setting of suspected AHT cases lacks sensitivity in detecting petechial hemorrhages, non-hemorrhagic strain, shear injury, ischemic edema, and ligamentous injuries of the craniocervical junction [19]. Conventional magnetic resonance imaging (MRI) is relatively less sensitive to subarachnoid hemorrhage and fractures and has a lower sensitivity for acute hemorrhage than CT. Sometimes, AHT does not show any visible findings on CT or MRI [2,20,21] since AHT cases are often asymptomatic. A missed diagnosis may lead to a catastrophic consequence; specifically, children younger than two years of age have a high mortality rate from AHT. In this review, we summarize the challenges physicians face in diagnosing AHT, evaluate the need for improved biomarker discovery, and discuss the potential of animal models in improving our understanding of molecular mechanisms mediating brain injury in AHT and preclinical drug discovery for AHT. Approximately 35 per 100,000 children younger than 1 years old are subject to AHT every year, and nearly 25% of children with AHT die [22,23]. It is challenging to diagnose AHT in terms of both social responsibility and medical accuracy. From the victim side, very young children (typically younger than 2 years old) are not able to provide verbal information about what happened to them. As a result, the caregiver may give inaccurate information and even fabricate a misleading history of the victim. In addition, clinicians may be biased in determining whether abuse occurred in a particular scenario. Failure to diagnose AHT puts a child at risk. Inaccurate conclusions, on the contrary, may wrongly remove a child from the custody of parents or guardians. In clinical practice, AHT cases usually present a spectrum of signs and symptoms, including such non-specific signs as vomiting and fussiness. All these scenarios make a timely and accurate diagnosis of AHT especially challenging. The externally validated clinical prediction rules, such as Predicting Abusive Head Trauma and the Pittsburgh Infant Brain Injury Score, which can help avoid unnecessary testing and misdiagnosis, are usually used for early recognition of AHT. These clinical prediction rules facilitate estimating AHT probability when screening high-risk children without a trauma history [24]. Surveying a complaint-directed history and physical exam are the critical initial steps in identifying AHT cases. Clinical signs that support a diagnosis of AHT include rib, long bone, and skull fractures. Most AHT victims show retinal and subdural hemorrhages [18]. Non-contrast head CT is considered the first imaging choice for unexplained brain injury due to its short scan time without sedation and rapid determination of the necessity of neurosurgical intervention. MRI is sensitive in detecting diffuse axonal damage and delineating ischemia, parenchyma injuries, and cerebral edema, which are common in AHT [24]. Limitations of MRI are that the child is not allowed to take any food several hours before an MRI scan, and sedation is usually required for pediatric patients, which raises concerns for the developing brain [25,26]. Compared with CT, MRI may help differentiate subdural hemorrhage from benign subarachnoid space injury. Disproportionately large heads supported by relatively weak necks in children make cervical injuries common in suspected AHT cases; therefore, spinal imaging of soft tissues with MRI is recommended to support the diagnosis of AHT [24]. In comparison, cranial ultrasonography that neither involves radiation exposure nor requires sedation lacks sensitivity and specificity in diagnosing suspected AHT [22,27,28]. Clinicians must evaluate the patient history, conduct a differential diagnosis, and perform an evidence-based, comprehensive analysis of all factors to minimize misdiagnosis. At the same time, no single imaging modality can precisely diagnose all AHT [18,29,30,31]. Due to the challenges of the clinical diagnosis of AHT, tremendous effort has been made to identify biomarkers that can aid in its clinical diagnosis. In 1998, Shannon et al. reported autopsy findings of 14 children (aged 1–27 months) who died from shaken baby syndrome [32]. Results showed β-amyloid precursor protein (β-APP)-positive axons in the cerebral white matter of all AHT cases, suggesting axonal injury. Cervical spinal cord and nerve injury with β-APP-positive axons were also present in most AHT cases, indicating that extension–flexion injury to the spinal cord may be critical in the pathogenesis of AHT. Dolinak and Reichard examined brains with an inflicted head injury in infants and young children for β-APP [33]. They found that β-APP immunohistochemistry was much more sensitive in detecting injured axons than hematoxylin and eosin or silver staining. In another short-surviving head injury study, even subtle morphologic axonal injury changes were detected as early as 2–3 h after injury by β-APP immunostaining [34]. Notably, while iTBI is sensitive to β-APP immunostaining to reflect axonal injury, other mechanisms causing axonal injury can also lead to positive β-APP immunostaining. Careful interpretation of β-APP immunoreactivity is critical since normal structures such as glia, dorsal root ganglion cells, and leptomeninges can also be positive. In addition, other factors such as global hypoxic-ischemic injury and children who survive resuscitation to ventilator support may also show extensive axonal staining. Therefore, β-APP staining should be interpreted carefully as a biomarker of AHT [35]. Since the β-APP immunostaining starts to fade about 7 to 10 days after injury, the authors proposed alternative biomarkers, such as the presence of macrophages and reactive astrocytes, to identify the injuries by staining for the cluster of differentiation 68 (CD68) and glial fibrillary acidic protein, respectively. In a study by Satchell et al., the concentration of cytochrome c, an electron transport chain component, was measured in 167 cerebrospinal fluid (CSF) samples of 67 children over 0–10 days after traumatic brain injury (TBI); among these, 15 patients were diagnosed with child abuse [36]. Results showed that increased CSF cytochrome c was independently associated with iTBI, indicating that the neuronal apoptosis associated with cytochrome c release is a prominent feature in child abuse cases. Monitoring CSF cytochrome c may be used to evaluate treatment therapy. In a similar study involving 37 patients with TBI (seven were diagnosed as AHT cases) admitted to the intensive care unit, the CSF level of cytochrome c was measured at four intervals (0–24 h, 25–48 h, 49–72 h, and >72 h after injury) by enzyme-linked immunosorbent assay [37]. Results showed that peak cytochrome c levels peaked at 49–72 h and were independently correlated with AHT. Increased cytochrome c levels in CSF predicted poor outcomes after TBI in pediatric populations, which indicated that apoptosis might play an important role in this particular population of pediatric brain injury [37]. Furthermore, the study found that the peak CSF cytochrome c level was significantly higher in AHT patients compared to accidental TBI cases. Neurotoxin biomarkers, including glutamate and quinolinic acid in CSF, have been reported in inflicted pediatric brain injury. The concentrations of neurotoxins in CSF of the inflicted brain injury were higher than those in non-inflicted TBI, yet neuroprotectant levels were less increased compared to non-inflicted TBI [38,39]. Newell et al. reported macrophage and lymphocyte activation in CSF after TBI [40]. This retrospective study included 66 patients with severe TBI; 17 were AHT cases (1 month–16 years old). CSF levels of macrophage activation marker-soluble CD163 (sCD163), iron deficiency marker ferritin, and soluble form of interleukin-2 receptor α (sIL-2Rα) were measured by enzyme-linked immunosorbent assay at two points (17 h and 72 h). Results showed that markers of macrophage/microglia activation (sCD163 and ferritin) increased following pediatric TBI. CSF ferritin was higher during the first time point assessed, while sCD163 was higher during the second time point. No difference was observed in CSF sIL-2Rα levels between TBI patients and the control group at the two points; however, the sIL-2Rα levels in the CSF were highly correlated with sCD163 and ferritin levels. Similar studies have shown that activated microglia [41] or oligodendrocytes [42] released ferritin early, followed by an sCD163 increase. These studies also found that young pediatric patients, including AHT patients and low Glasgow Coma Scale (GCS) cases, had high CSF ferritin levels, indicating that younger children and more severe injury cases had higher macrophage and microglial activation. A high CSF ferritin level was associated with poor outcomes at a young age, low GCS, and AHT cases. Su et al. reported on 27 TBI patients, including six AHT cases (7 weeks to 16 years old), and measured the CSF myelin basic protein (MBP) concentrations [43]. Results showed the overall MBP concentration of the TBI cases at 5 days postinjury (dpi) was significantly higher than the controls. The patients younger than 1 year had lower mean MBP concentrations than those older than 1 year due to a lower relative fraction of MBP in the immature brain of an infant. These findings imply that an MBP increase in infants may underestimate the injury severity compared with older pediatric patients or adults. The mean MBP concentrations in AHT patients were lower than in non-abusive TBI. However, in this study, the mean age of AHT cases was significantly lower than that of the non-abusive TBI, and brain maturity likely affects the MBP concentrations. The study demonstrated that axonal injury with increased MBP in pediatric TBI, including AHT, may represent a promising therapeutic target. While biomarkers in CSF provide helpful pathophysiologic information on AHT, it is challenging to obtain CSF from pediatric patients during a clinical visit for silent brain injury. More accessible serum markers including neuron-specific enolase (NSE), astrocytic marker S100 calcium-binding protein B, and MBP are under investigation. The comprehensive information of the three makers may provide insight into the timing of the injury or raise awareness in physicians that silent brain injury may have occurred [44]. Furthermore, in 2018 the U.S. Food and Drug Administration approved the first blood test to aid in diagnosing mild traumatic brain injury (mTBI) in adults. The test works by measuring the levels of two brain-specific protein biomarkers, ubiquitin C-terminal hydrolase-L1 and glial fibrillary acidic protein. The two proteins are released from the brain into blood and measured within 12 h of mTBI [45]. However, in a pediatric TBI study involving 49 children (1 week–12.4 years old, 39 TBI children including 10 AHT cases, 10 controls), the subjects had blood collected for biomarker evaluation within 24 h of presentation. Results showed the ubiquitin C-terminal hydrolase-L1 concentrations were significantly different between the controls and severe and moderate TBI cases. A significant difference was not observed in the mTBI cases, indicating the complexity of applying adult mTBI biomarkers to pediatric populations [46]. Gao et al. used two-dimensional difference gel electrophoresis combined with mass spectrometry to compare the serum protein profile of 18 pediatric patients with mild AHT to 20 age-matched controls [47]. Results showed that serum amyloid A levels were significantly increased in the AHT cases. The study also compared serum amyloid A expression levels in children with mild AHT and moderate-to-severe AHT. There was no correlation between the serum amyloid A levels and injury severity. Serum amyloid A may serve as a biomarker to identify infants with mild AHT that might be missed by traditional CT or MRI diagnosis. In addition, serum amyloid A probably has a much longer half-life than the serum biomarker S100 calcium-binding protein B, which is less than 60 min. NSE and MBP are the most promising biomarkers to screen for brain injury in well-appearing infants with AHT [48]. In addition to MBP, as mentioned earlier in CSF, MBP in serum has also served as a biomarker for pediatric brain injury. In a prospective case-control study including 98 well-appearing infants, Berger et al. reported that 14 patients were diagnosed with iTBI [49]. MBP has a specificity of 100% and sensitivity of 36% in identifying brain injury. MBP screening is expected to add additional value in evaluating AHT cases that might be missed at initial diagnosis [49]. In this study, the researchers found that it took a significantly longer time for the patients with iTBI to be sent to the hospital compared with caregivers of patients with no brain injury, highlighting the challenges in timely diagnosis of AHT with biomarkers and the increased risk of a repeat injury or death for children. A summary of typical biomarkers for AHT cases is outlined in Table 1. Inflicted head injury by shaking trauma is an important research topic. Few research groups are involved in animal research to simulate human AHT cases [50,51]. Most studies use mechanical shaking methods to simulate AHT scenarios in mice, rats, piglets, and lambs, and most utilize constrained head movement with a single-plane rotation. This methodology does not mimic clinical AHT cases in which the perpetrators randomly shake the heads of babies in multiple directions. This makes translation of preclinical findings to pediatric assessment challenging. It is widely accepted that the large size of gyrencephalic brains and relatively weak cervical muscles may better reflect clinical AHT cases. As a result, many animal models focus on pathologic changes found in AHT. Here, we introduce typical AHT animal models and biomarker changes after injury. Most preclinical studies use infant mice to study AHT. Rotational shaking is the primary mechanism to induce AHT in mice, while the shaking directions are variable. While not ideally imitating AHT in the clinic, the rodent models partially reflect the pathology in clinical cases such as symptomatic subdural and subarachnoid hemorrhage, SDH, cerebral ischemia, retinal hemorrhage, diffuse axonal injury, and neurological problems. Bonnier et al. reported an AHT model using 8-day-old mouse pups. The mouse pups were shaken for 15 s on a rotating shaker and sacrificed at different ages. The brains of the mouse pups were processed for histological analysis. Ex vivo analysis of the brain samples showed that at 31 days old, hemorrhage or cystic lesions of periventricular white matter, corpus callosum, brainstem, and cerebellar white matter were observed in 75% of the survivors. Hemorrhagic lesions were evident from postnatal day 13, while cysts developed gradually between days 15 and 31. Reactive astrogliosis and microgliosis, an indication of neuroinflammation, were observed in the focal destructive white matter lesions. The study found that pretreatment of the shaken mouse pups with the N-methyl-D-aspartate receptor (NMDA) receptor antagonist MK801 alleviated the white matter damage, suggesting NMDA receptor activation due to the excessive release of glutamate may play a role in the pathophysiology of the lesions [52]. Wang et al. reported rotational acceleration–deceleration TBI in developing mice [53]. The 12-day-old mice were subjected to 90° head extension–flexion sagittal shaking with an angular acceleration of 22,616.97 ± 3659.45 rad/s2 at 3 Hz frequency. Different repeats were used, including 30, 60, 80, and 100. Results showed that the repeats and severity of injury significantly impacted the mortality rate and return of the righting reflex. At 30 rotational acceleration–deceleration injuries (RADi), no mouse pups died; at 60 RADi of repeated head shaking, the mouse pups developed apnea and bradycardia immediately. A decreased survival rate was observed at a higher shaking speed. The expression levels of both astrocytes and microglia were significantly increased at 3 dpi, particularly in the ventral pons. These results demonstrated an endogenous pro-inflammatory response and glial activation after acceleration–deceleration injury. Neuronal degeneration by silver staining was observed in the cerebral cortex and olfactory tubercles at 30 dpi following an RADi of 60 pounds per square inch by 60 exposures. This rotational head acceleration–deceleration injury model in neonatal mice partially mimicked the pathophysiological and behavioral changes in pediatric AHT and provided a good model for long-term study of the secondary rotational acceleration–deceleration-induced brain injury in developing animals. Cerebral blood perfusion (CBP) was significantly reduced and had not fully recovered until 24 h. A severe reduction in CBP implies that secondary brain damage caused by ischemia/hypoxia exists. The sudden sagittal acceleration–deceleration rotational movement induced shear stress to damage superficial vessels, SDH, subarachnoid hemorrhage (SAH), and ventral brain injury. Reports showed that shear stress and hypoxia could change tight junction proteins of the endothelium, which leads to cerebral edema through BBB disruption and fluid extravasation [54,55]. In addition to pro-inflammatory changes and microglial activation in this rotational acceleration–deceleration animal models, other clinical AHT cases and animal models of brain injury reported an inflammatory response and diffuse gliosis [52,56]. Diffuse axonal injury (DAI) characterized by axonal swelling and varicosities has been reported in clinical cases with AHT [32,56,57,58]. In the reported rotational acceleration–deceleration mouse pup model, DAI was seldom observed 30 dpi; however, progressive neuronal degeneration in the cortex and olfactory tubercles was present. The researchers suggested that a long-term study may be required to confirm DAI because the injured axons in the developing brains exhibit a graded response to injury severity [59]. The neuronal degeneration probably affects long-term neurological and behavioral function since the report showed some neurobehavioral deficits in adulthood following TBI in pediatrics [60]. Kane et al. reported an impact acceleration mice model with mTBI under light anesthesia. No scalp incision and protective skull helmets were involved. In this animal model, skull fractures and intracranial bleeding are rare without evidence of seizure and paralysis. However, mild astrocytic activity and increased phospho-tau levels were observed with BBB disruption [61]. The brain structures of mice and humans are very different. The mouse AHT models are not ideal for simulating clinically obtained AHT. Unlike humans, mouse pups do not exhibit pericerebral bleeding. Correlating the time lag in mice between the shaking and the development of bleeding and atrophy with clinical findings is still poorly understood. Mouse AHT biomarkers center on reactive astrogliosis, microgliosis, and the NMDA receptor. Despite these limitations, mouse models have utility: they are low cost, easy to maintain, and partially reflect the pathology in clinical cases such as symptomatic brain hemorrhage, ischemia, and neurological outcomes. These models also usually do not require a craniotomy, simplifying the experimental operation. Furthermore, genetically modified mice are readily available compared to large animals, and the use of these mice can improve our knowledge of testing novel hypotheses, elucidating pathological mechanisms, predicting long-term response, and identifying new therapeutic targets in AHT. Among the mouse AHT models, most studies lack consistent and rigorous characterization of shaking mechanisms. The model reported by Wang et al. better represents clinical AHT cases [53]. The mouse model uses a repetitive rotational head acceleration–deceleration mechanism with predefined parameters to partially mimic clinical AHT pathophysiology and behavior, including brain hemorrhage, hematoma, neuronal injuries, and cognitive impairment. Furthermore, inflammatory biomarkers were significantly elevated in this model compared with sham brains. One limitation is the study only uses sagittal shaking, while clinical AHT may occur within multiple planes around the body axis. Bittigau et al. developed a model of head trauma in infant rats to study the mechanism of neurodegeneration in the developing brain. Two morphological types of brain damage were observed within 4 h and 6–24 h after trauma, respectively. This study showed that NMDA antagonists protected against primary excitotoxic damage but exacerbated the secondary apoptotic injury in 7-day-old rat pups. In the developing rat brain, apoptosis instead of excitotoxicity results in neuropathologic outcomes after head trauma. Radical scavengers and tumor necrosis factor inhibitors may help treat pediatric head trauma. Furthermore, the authors found that the severity of trauma-triggered apoptosis in the brains was age-dependent, and the immature brain was particularly vulnerable [62]. Huh et al. used the most common controlled cortical impact approach to mimic pediatric repetitive mild brain injury in the immature rats [63]. Postnatal day 11 rats were used to model AHT. A conventional controlled cortical impact tip or a customized rubber tip was used in the studies. In these models, the study was designed to avoid skull fractures. Axonal injury, neuroinflammation, and calpain activation were typically observed but seldom neuronal death. Repeated injury exacerbated the pathology as expected. Treatment with folic acid, minocycline, and FK506 was involved in several studies, but most showed limited efficacy compared with the adult TBI models in rodents [64,65]. Kawamata et al. used an experimental rat model of repeated mild shaking brain injury in rat pups to study neonatal cerebral microhemorrhages using susceptibility-weighted imaging and iron histochemistry. Results showed that postnatal day 7 rat pups had a significantly higher number of microhemorrhages than postnatal day 3 rat pups. In contrast, no microhemorrhages were detected in the control rat pups and pups 5 weeks after shaking. The staining pattern of iron-positive cells surrounding microhemorrhages lasted for a long time. Even the hemorrhagic signals disappeared, strongly suggesting focal hypoxic–ischemic insults. The open-field test showed that the shaken group had significantly lower numbers of line crossings and rearing events than those in the control group, indicating anxiety-related outcomes in adult rats [66]. Similar reports showed an excessive iron load increased anxiety-related behavior and caused brain injury via the formation of free radicals [67,68,69]. The strong iron-positive reaction probably indicated increased numbers of activated microglia and macrophages [70,71]. Recently, Daniel et al. used five-day-old Wistar rats to develop two AHT models [72]. The first model was subjected to low-intensity, high-duration rotating movements (one cycle per second, 15 min shaking per day for five consecutive days). The second model was subjected to high-intensity, low-duration anteroposterior movements (3.3 cycles per second with 10 periods of 6 s). The researcher compared the two models’ brain damage and biochemical marker changes. Results showed that hemorrhage was observed in 10% of the low-intensity, high-duration movements group, while this was much higher in the high-intensity, low-duration movements group (40%). The severity of brain damage is closely related to the magnitude of biochemical changes, including reactive oxygen or nitrogen species, oxidative stress, and energy metabolism. In addition to AHT model development, some researchers used drugs to study the trauma mechanism at a molecular level. Smith et al. reported a shaking plus hypoxemia AHT animal model using postnatal day 6 rat pups [73]. Results showed that shaking of the rat pups led to cortical hemorrhages, cortical tissue damage, and the production of oxidative stress markers. An early study by the same group reported that the anti-excitotoxic glutamate release inhibitor riluzole alleviated cortical neurodegeneration, in contrast to the antioxidant tirilazad, which was ineffective [74]. Hanlon et al. reported the effect of minocycline, a broad-spectrum tetracycline antibiotic, on the treatment of repetitive TBI in 11-day-old Sprague-Dawley rat pups [75]. Results showed repeated injuries led to spatial learning and memory deficits and increased brain microglial and macrophage expression. Acute administration of minocycline in this AHT model decreased microglial/macrophage activation in the corpus callosum at 3 dpi, but this effect disappeared at 7 dpi. Interestingly, minocycline did not affect the traumatic axonal injury or axonal degeneration. In turn, this drug showed exacerbated injury-induced spatial memory deficits, while in adult brain-injured mice, minocycline treatment demonstrated efficacy in reducing impairments and injury-induced deficits [76,77,78,79]. In adult TBI and neonatal stroke animal models, minocycline treatment effectively induced lesion areas in the cortex [79,80,81,82]. The data suggest that in the repeated injury neonatal model of AHT, minocycline may not be an effective drug candidate in treating the acute period. However, the authors also pointed out that the dosing paradigm and detailed study of the effect of minocycline on microglia/macrophage polarization (pro-inflammatory vs. anti-inflammatory) phenotypes may underlie this interesting finding. As with mouse AHT models, rats are cost-effective, and researchers can easily use innovative techniques to create genetically modified strains to screen therapeutic targets in AHT. However, the notable differences in brain geometry, craniospinal angle, and white-to-grey matter ratio may lead to substantially different responses to AHT from subject to subject. Overall, repetitive acceleration–deceleration forces are the most common cause of AHT. Daniel et al.’s low-intensity, high-duration rotating and high-intensity, low-duration shaking models in young rats clearly show morphological injuries and biochemical changes [72]. Furthermore, the severity of brain injuries is associated with the magnitude of the biomarker levels, which may provide some information on the relationship between the shaking forces, duration, and clinical outcomes. To better understand AHT, it is critical to use large animal models. The advantages of using large animal models, including monkey, lamb, and piglet models, are that these animals have a gyrencephalic brain supported by relatively vulnerable neck muscles, grey–white matter differentiation, and a physiological response similar to human infant brains. A 3- to 5-day-old piglet brain is roughly comparable to a 2- to 4-week-old infant in terms of activity, myelination, and growth. However, as with lambs, the piglet brains have an almost elliptical shape that is in line with the cervical spinal cord, significantly different from the rounder human brain forming a nearly 90° angle. Therefore, it is challenging to directly translate the studies to pediatric assessment due to the single direction rotation in most studies and different brain anatomy. Vester’s group recently reviewed animal models for shaking trauma and related findings on tissue damage. Their paper reviewed 12 articles published by two research groups involving lambs or piglets. Most animal studies only involved a single-plane rotational movement. Decreased axonal injury and death corresponded to increasing age and weight. The authors suggested that free movement in all directions simulating human infant shaking is required for future studies. In the review paper, the authors did not include shaking trauma animal models in rodents and claimed an inconclusive report of the methodology and result [83]. Friess et al. reported a moderate and non-impact rotational TBI model using 3- to 5-day-old piglets with multiple impacts at either 1 day or 1 week apart. Double rotation (average acceleration 55.2 and 54.3 krad/s2, respectively) by 1 day apart led to a significantly higher (43%) mortality rate compared with a single rotation (58.5 krad/s2) [84]. Meanwhile, the double rotation animals showed significantly longer unconsciousness duration than the control group on both day 0 and day 7. Retinal hemorrhage is one of the key features, and the surviving animals displayed behavioral deficits and axonal injury evaluated by β-APP staining [84]. Raghupathi and Margulies reported closed head injury in the neonatal pig of a 3- to 5-day-old model. The anesthetized piglets underwent rapid and inertial rotation (10–12 ms, single 110° axial rotation, average peak angular velocity of 250 ± 10 rad/s) of the head around the axial plane. Results showed five of the seven piglets were apneic without pupillary and pain reflexes immediately following injury. Severe coma was observed in all piglets, but they recovered by 6 h. SDH and SAH were evident in the frontal lobes, while limited intraparenchymal bleeding was present. Axonal injuries were observed in six of the seven studies of brain-injured piglets, which were mainly located in the central and peripheral white matter and middle brain. The study concluded that the immature piglet brain may be more vulnerable to traumatic axonal injury than the adult brain and therefore will have a higher mortality and morbidity rate. In addition to SDH, SAH, and traumatic axonal injury, the authors suggested that hypoxia may play a role in the distribution of traumatic axonal injury [85]. The researchers reported a follow-up study at different rotational speeds (mild level 142 rad/s and moderate level at 188 rad/s). Results showed behavioral deficits were observed in the moderate injury level during environmental exploration and visual-based problem solving. Furthermore, moderate injury levels led to axonal injury as determined by amyloid precursor protein immunohistochemistry [86]. Similar animal models were used to monitor cerebral blood flow, evaluate cerebral blood oxygenation [87], and assess treatment outcomes with folic acid [88]. The rotational direction and number of repetitions had significant consequences in the AHT cases. Coats et al. conducted ocular examinations in modest brain injury (shaking frequency of 2–3 Hz, the average peak-to-peak angular velocity of 22.71 ± 3.49 rad/s, and average peak angular acceleration of 606.21 ± 160.30 rad/s2) of infant piglets. Results showed ocular hemorrhages in 73% of the 51 piglets, of which about half were bilateral and primarily located near the vitreous area. Twenty-six cases with bilateral SDH showed ocular hemorrhages; only one had ocular hemorrhages in a unilateral SDH case. Ocular hemorrhages were accompanied by brain injury in all but two animals. However, the same group reported no ocular injury in a similar animal model, probably due to a much lower rotational velocity. Generally, all the above studies concluded that increasing force, duration, or repetition led to much greater frequency and more severe hemorrhages. Coronal shaking had less bleeding and axonal injury in frequency and severity compared with sagittal or transverse rotations [89,90]. While retinal hemorrhage is one of the principal findings in AHT, the exact cause of retinal hemorrhage from AHT is unknown. Umstead et al. hypothesized that retinal hemorrhages in AHT resulted from a combination of shaking forces and hypertension [91]. The team used eyes from young pigs to test the pressure required for sudden retinal hemorrhages. Subsequently, using either isolated shaking, hypertension, or combined conditions, the researchers created a computer model to simulate the loading. Results showed that hypertension or shaking alone did not generate adequate stress to induce retinal hemorrhages. Instead, combining the two forces without physical contact is a pivotal contributor to AHT. AHT is often associated with posttraumatic disorders, including epilepsy, cognitive defect, and motor dysfunction [92]. Costine-Bartell et al. reported a synergistic, multifactorial injury cascades animal model in one-week-old piglets and one-month-old piglets to study the age-dependent role of seizures and edema in longitudinal tissue injuries after AHT [93]. The piglets at two developmental stages simulate clinical infant and toddler AHT cases. The multifactorial and brain volume scaled injuries, including cortical contusion, mass effect, subdural hematoma placement, kainic acid administration, brief apnea, and hypoventilation [94], were used to reflect the physiologic cases in children with severe AHT. Results showed that the outcomes and injury patterns were age-dependent. App-positive neurons were correlated with the hypoxic–ischemic-type damage but with different patterns: a higher amount of APP-positive neurons was observed in the ipsilateral hemisphere in the toddler piglets, while it was equivalent in the injured infant piglets. Infant piglets were clinically worse, with lower neurological scores than their toddler counterparts, while the seizure duration was not different among developmental stages. Furthermore, the study found that infant piglets underwent endogenous mechanisms to alleviate the bilateral injuries, while toddler piglets tended to limit the damage to a unilateral pattern. Combined with clinically relevant biomarkers, the model may bridge the gaps between injuries and therapeutic outcomes. Several studies reported that the timeframe between two injuries and when to evaluate the impact postinjury might affect the trauma interpretation [84,89]. For example, more white matter injury and β-APP staining were detected for single rotated piglets surviving 5 days than those surviving 12 days [84]. At 6 h postinjury, no difference in the content of axonal injury was observed between episodic and continuous cyclic head rotations for 30 s [90]. However, at 24 h postinjury, the continuously rotated animals showed a significant increase in axonal injury. In the control group, no axonal injury was found. The axonal injury was found in all studies, although not always significantly differing compared with the control groups. Raghupathi and Margulies reported several shaking-related traumas and found no neuronal loss. There was no correlation between the velocity and density of axonal injury in the white matter tracts [85]. The same group reported that when the neonatal pigs were subjected to two consecutive rotations, the axonal injury was observed in the peripheral subcortical, central deep white matter of the parietal and temporal lobes, corpus callosum, hippocampus, and basal ganglia [59]. Specifically, more foci with multiple injured axons existed compared with a single rotation. In the moderately rotated piglets (average 62.9 krad/s2), Friess et al. found axonal injury in the olfactory tract, internal capsule, and germinal matrix. However, no axonal injury was observed in mildly rotated piglets (34.1 krad/s2) [86]. The same group reported that the most axonal injury was observed in the frontal lobes of injured animals with significantly higher β-APP levels in white matter [84]. Naim et al. had similar findings in a piglet injury model indicating the deep white matter of the frontal lobes, parietal and temporal lobes, or brainstem were the injured sites [88]. Eucker et al. found that the animal rotational direction significantly affected the outcomes: the transverse rotations resulted in more axonal injury than coronal or lower velocity horizontal rotations. More injuries were observed in both sagittal and transverse rotations than in coronal cycles. The latter showed minimal pathology. The axonal injury was more often observed in the anterior regions of the brain compared with other regional brain sections [95]. Coats et al. found that in cyclically rotated piglets, an injury occurred in 88.5% of the surviving animals. At 24 h postinjury, higher axonal injury was observed after continuous rotations for 10 s than 30 s. At the same time, compared with a single head rotation, the 30 s continuously rotated piglets had more hypoxic–ischemic injury [90]. Ibrahim et al. found that based on the mass scaled acceleration principle, there was a significant difference for both SAH scores and brain volumes of axonal injury when comparing the results of the 4-week-old piglets to published 5-day-old counterparts, while electroencephalogram responses between the two groups were similar [96]. Furthermore, higher rotational accelerations (61 krad/s2) resulted in more severe SAH, increased areas of ischemia, and more axonal injury compared with lower rotational acceleration (average 31.6 krad/s2) [96]. However, compared with real animal models of the two groups at similar acceleration rotations, the severity of SAH and axonal injury were similar. The authors concluded that the traditional mechanical engineering method of scaling by mass in the toddler does not apply to the developing infant brain. Treatment studies in piglet AHT models have also been evaluated. Naim et al. studied the function of folic acid in a neonatal piglet model of TBI with 3- to 5-day-old female piglets [88]. The brain injury model was set up by rapid axial head rotation without impact. Two injured groups were involved in the study: one group received folic acid at a dose of 80 µg/kg by intraperitoneal injection 15 min postinjury, which lasted for six consecutive days, and the other injured group received an intraperitoneal injection of saline at the same time as the first injured group. Meanwhile, the study included two uninjured control groups: one group injected with folic acid and the other with saline, all following the same timeline as the injured animals. Results showed the injured group had significantly longer unconsciousness durations. Extensive neurobehavioral and cognitive testing including behavior, memory, learning, and problem solving were conducted on days 1 and 4 postinjury. The piglets were sacrificed on day 6 postinjury, and brain samples were processed for histological analysis. Results showed that seven of the 24 injured animals died due to palate fracture, cervical spine hematoma, pulmonary edema, or large SDH. For the animals monitored until day 6, the folic acid treatment group showed higher exploratory interest, better motor function, learning, and problem solving compared with the saline treatment piglets in the injured group on day 1 postinjury. However, functional improvements were not observed on day 4, which indicated that folic acid might increase early brain functional recovery in the non-impact head trauma model. Limited piglet trauma models used multiple accelerations [90], which makes it less valuable for translating to human shaken babies because, in reality, many believe that the perpetrators shake the baby in a repeated and sudden acceleration–deceleration manner [97] instead of a single event. The head of the baby rotates in all directions although mainly in a sagittal plane along with possible chin–chest collisions [98]. While different shaken directions have been reported by several groups [89,90,95], none of the studies involved combining other rotation planes. The combination of various shaken planes at the same time may intensify the forces and deformations and exacerbate brain injuries. Therefore, most studies do not represent the main repeated back-and-forth movements in different directions and hardly translate to clinical diagnosis. In summary, piglets have a gyrencephalic brain supported by relatively vulnerable neck muscles, similar to human infant brains. In addition, the piglet’s eyes have greater similarities to infant human eyes than most other animals. However, most studies used single-plane rotation instead of different rotation planes, making it challenging to translate the preclinical results to pediatric assessment. The piglet model reported by Coats et al. that used cyclic head rotations is similar to clinical AHT scenarios [90], although this model does not represent free movements in all directions. In addition, the model creates mild pathological and clinical AHT symptoms instead of the repetitive, sustainable injuries observed in severe AHT in the clinic. In pediatric AHT, it is widely accepted that repeated sudden deceleration in combination with acceleration causes intracranial injury. Therefore, there are insufficient data to predict the extent to which the piglet model results could be translated to clinical findings. Axonal injury evaluated by β-APP staining is used in both piglet models and clinical cases and may serve as a biomarker for AHT evaluation. Infant lambs were also used in the mTBI model. Anesthetized 7- to 10-day-old lambs were used to model AHT by physical shaking [98,99,100]. The animals were held under the axilla, then manually subjected to vigorous and multiple-episode shaking for 30 min. Multiple injuries, including BBB disruption, axonal damage, brainstem injury, and craniocervical junction damage, were observed during the studies. Finnie et al. reported similar young lambs subjected to a free shaking mechanism (10 × 30 s in 30 min) by humans [101,102]. Results showed manual shaking caused extra-axial hemorrhages in all lambs. Significant β-APP-positive neuronal perikaryons were observed in all injured lambs. However, several major injury indexes, such as total injury scores, hypoxic edema, and C-Fos immunoreactivity, were higher in the younger lambs than in the older ones. In a subsequent study, the authors found that retinal injury with increased glial fibrillary acidic protein expression, inner nuclear layer neuron injury, and increased β-APP levels were more widely seen in the younger lambs. The shaken lambs typically showed brain, spinal cord, and eye injuries. The lower-weight and younger lambs had a higher mortality rate. For inflicted head injury by shaking trauma in shaken lambs, the animals were subjected to the acceleration–deceleration rotation without a direct impact on the head in any direction by adults, similar to the shaking of infants. Several studies used devices to measure the forces with a triaxial piezoresistive accelerometer and a motion-tracking sensor to monitor the accelerations [98,100]. The authors compared the animal models with 9-month-old infants based on their body weight. They concluded that trauma pathophysiology was comparable to young pediatric patients since both lamb and human infants have weak neck muscles, relatively large brains, and vast subarachnoid space, making brain movement within the skull relatively easy [97]. At the same time, both the infant and lamb brains have relatively higher water content and are not fully myelinated; therefore, the immature brain is more vulnerable to shearing injury [101,103]. However, the shape and orientation of the brains of lambs and human infants have significant differences: the lamb brain is in line with the cervical spinal cord and has a more elliptical shape; the human brain has a rounder shape and is almost vertical to the spinal cord. The difference may cause different trauma effects during shaking. One limitation is that the same injured lambs and control group were used for the three publications. Larger populations when reproducing the study may result in a more accurate interpretation of the results. Overall, the free shaking mechanism applied by humans to the lambs in the study reported by Finnie et al. most closely resembled shaking in human babies. The lambs were held by adults with the head free for acceleration–deceleration rotation in any direction for a significant time (30 s) without a direct impact trauma. The studies partially answer the shaking outcomes in human conditions. Both human infants and lambs have weak neck muscles, a relatively larger brain compared with the entire body, and a higher brain water content, leading to likely shearing injury. The β-APP biomarker is also routinely used to evaluate clinical AHT cases, making the lamb model comparable to human infants. However, the lamb brain is more elliptically shaped and in line with the cervical spinal cord; in contrast, in humans, there is an almost 90° angle between the brain and the spinal cord. The brain shape and orientation of the two results in injury outcomes that are unclear. In addition, the small sample size and a lack of rigorous characterization of shaken kinematics make reproducibility a potential challenge and limit our ability to extrapolate these findings to human infants. Serbanescu et al. used an interesting natural shaking animal model to study retinal hemorrhages [104]. An 18 kg mixed-breed canine captured two 3- to 4-week-old kittens and one rabbit from a stray litter. The kittens and rabbit were bitten on the haunches and posterior spine, followed by four to six aggressive side-to-side shakes. The kittens and rabbit were killed by the canine and this was witnessed by one person. The deceased animals were subjected to pathological examinations after 1.5 weeks. Results indicated that the eyes of the two kittens and one rabbit did not show evidence of vitreous hemorrhage, retinal detachment, or retinoschisis. In addition, no retinal or optic nerve sheath hemorrhage was observed during the examination. The authors concluded that a more significant amount of force may be required for retinal hemorrhage due to their small eye size compared with a human infant. Another possible explanation is that the feline head and neck are better constructed to sustain acceleration–deceleration forces without injury [104]. Increased tau levels have been reported in pediatric TBI patients [105]. Alyenbaawi et al. set up an interesting TBI mode in a closed syringe with zebrafish larvae encoded with fluorescent tau protein. The team dropped a weight onto the plunger to mimic a shockwave-induced injury. Results showed the zebrafish larvae developed seizure symptoms, and the severity of seizures was correlated with the abnormal tau levels. Tau may serve as a potential biomarker for AHT, while further investigation in the AHT model with zebrafish larvae is required [106]. Eldridge et al. reported a focal impact TBI model in Xenopus laevis tadpoles with a pneumatic piston device. The model showed a secondary injury cascade, including neuroinflammation, oxidation, and BBB disruption [107]. A summary of typical biomarkers in preclinical animal models is outlined in Table 2. It is well known that an abusive environment in childhood is associated with individual anxiety behavior in adulthood. The biochemical changes in childhood of AHT animal models probably affect adults’ long-term neurological and behavioral functions. In a repeated mild shaking of the neonatal rat model, Kawamata et al. found that iron leakage surrounding microhemorrhages in the grey matter and iron-induced reactive oxygen species were observed, which caused long-term iron deposits and contributed to emotional abnormalities in adults and was an indication of anxiety-related behavior in adult rats. The animal model may shed light on the anxiety-prone state of AHT in adults [66]. In a subsequent study, the same group extensively studied how repeated shaking of neonatal rat pups affected long-term behavioral, hormonal, and neurochemical changes in adult rats [108]. The rat pups were shaken for 60 s, then rested for 60 s. The procedure was repeated five times. Half of the rat pups were shaken at postnatal days 3–7; the other half were shaken at postnatal days 8–14. The rat pups were housed until 8–10 weeks for further studies. Results showed transient microhemorrhages were observed in the grey matter of the hippocampus and medial prefrontal cortex. According to a similar animal model by the same group, leakage of free iron and iron-uptake cells surrounding microhemorrhages was presented [66]. Iron overload was reported to have long-term adverse effects [69,109], including increased superoxide production and mitochondrial dysfunction in the neonatal brain [110]. Behavioral tests showed the rat pups shaken on postnatal days 3–7 had significantly reduced locomotor activity and exploration behaviors than those shaken on postnatal days 8–14. Anxiety-like behavior was evident in the shaken group by the elevated plus maze (EPM) and the light/dark transition tests. Hormonal measurements in adult rats showed that the EPM induced significantly higher adrenocorticotrophic hormone and corticosterone responses. At the same time, the mineralocorticoid receptor expression level in the hippocampus was significantly reduced, which implied that downregulated mineralocorticoid receptors led to abnormal secretion of adrenocorticotrophic hormone and corticosterone. Neurochemical analyses showed the levels of dopamine, serotonin, 5-hydroxyindolacetic acid, and noradrenaline were increased in the dorsal part of the medial prefrontal cortex. This study clearly showed shaking of neonatal rat pups resulted in high anxiety-like behavior, an abnormal hormonal response, altered mineralocorticoid receptor messenger RNA expression, and monoamine in adulthood. Most recently, the same group assessed the change in sensitization in the anxiety–stress-related regions of adult rats by Fos immunohistochemistry after the neonatal rats were subjected to shaking brain injury. An EPM test was conducted to assess the psychological stress, including fear and anxiety, the rats naturally displayed. Results showed significantly increased Fos expression in the hypothalamus of the control and shaken groups when the rats were subjected to EPM, among which the shaken group had higher Fos expression than the control group. The results corroborated previous studies that the shaken rats exposed to the EPM had long-term hypersecretion of corticosterone and adrenocorticotrophic hormone in the serum of adults [108], which has been positively related to anxiety-like behaviors [111]. The study found that the psychological stressor EPM led to neuron activation in the ventral section of the bed nucleus of the stria terminalis. A positive correlation in Fos expression was observed between the ventral section of the bed nucleus of the stria terminalis and the parvocellular part in the shaken group, whereas the control group did not show such correlation. This study demonstrated that neonatal shaking brain injury caused persistent brain activity changes in adults when the rats were exposed to psychological stress. The data may provide meaningful information to study anxiety-prone states in shaken children. Given the high mortality and morbidity rate of AHT, robust and reliable translational investigations are clearly needed in pediatric abusive trauma. Using large animals to study AHT has been described by several research groups. The advantages of using large animals are their gyrencephalic brains mimicking the pediatric condition in terms of the amount of white matter, clinically relevant physiological monitoring, and pharmacological intervention. Limitations of rotational injury animal models include a lack of mechanical impact to obtain consistent and reproducible results, limited molecular tools in piglets and lambs, and less well-established behavioral outcome tasks than in rodent models. Most animal models selected for AHT are those likely to be appropriate to the specific neuropathology under investigation. However, large gaps still exist based on the currently utilized animal models. First, many studies lack consistent and reliable characterization of shaken mechanisms with low reproducibility or have difficulties with clinical translation. Second, the brain structures of rodents and large animals significantly differ from developing pediatric brains. Third, it is still unclear how secondary injuries impact the brain during the pediatric development period and long-term degenerative diseases. Several critical mechanisms in the secondary injury cascades were discussed [112]. The effect of the critical targets, including neuroinflammation, excitotoxicity, reactive oxygen species, axonal damage, and neuronal death on the different developmental stages in newborns, children, and adults, remain underinvestigated. A limited investigation was conducted on how genetic differences, including the basic sex variation, affect the outcomes. Another limitation is that most AHT models do not have a detailed description of the shaking (or rotational) angular velocity, acceleration, or if the injury was caused by random human force, which leads to reproducibility and rigor issues in preclinical studies. It is challenging for clinicians to translate and develop new therapies and extrapolate the animal study results to clinical AHT cases in a pediatric population for the following two major reasons: (1) the shaking mechanism in most animal models is not rigorously defined and (2) there are substantial structural differences between the developing infant brain and the animal brain. However, changes in biomarkers provide clues that the dysregulation may be related to brain injury in a more reliable and sometimes non-invasive way. To better understand the interdependency of the injured neurons and malfunction, an analysis of the cell types of the degenerated neurons and a study of long-term neurological outcomes during AHT in developmental brains are urgently needed. In addition to the currently reviewed key biomarkers in AHT (axonal injury, reactive oxygen species, activated NMDA receptor, microglia/astrocytes, hypoxic–ischemic), potential biomarkers detected in clinical AHT cases such as specific CSF concentration, S100, MBP, and cortisol level might be investigated to study the severity and predict the prognosis of AHT, serving as an alternative way of studying AHT. A positive screen may imply that the brain is injured and prompt the treating physician to perform further evaluation while confirmation of the diagnosis of AHT is being made. The reported rotational acceleration-deceleration models in animals may provide a good translational tool to identify biomarkers and evaluate therapeutic interventions related to pediatric AHT. Among the developed AHT animal models, the manual free shaking study reported by Coats et al. in lambs most closely resembled shaking in human infants [90]. The model allows maximal free movement of the head. Furthermore, the anatomical structures between infants and lambs are relatively similar: both have weak neck muscles, a proportionally larger brain compared with the entire body, and a higher brain water content, leading to likely shearing injuries and biomarker changes. β-APP is a favorable biomarker for axonal injury evaluation in AHT. Microglia and astrocytes are often assessed biomarkers to indicate brain inflammation during different stages in AHT models. The biomarkers may be helpful to prompt further screening for evidence of brain injury, although the markers are not specific to AHT. Improving the sample size in randomized animal studies, consistent and rigorous characterization of shaken mechanisms, longitudinal monitoring biomarker changes in serum and CSF, and validating the findings in the same species with different age ranges may improve the reproducibility of the model and translate the results to human infants. Furthermore, the biochemical changes in childhood of AHT probably affect adults’ long-term neurological and behavioral functions. Therefore, extensive neurobehavioral and cognitive testing in the favorable AHT models will greatly improve our understanding of the diagnosis, treatment, and management of clinical AHT. AHT is a severe form of TBI in children. The correct diagnosis of AHT is challenging and requires a multidisciplinary approach. Current animal models show limitations in replicating clinical AHT reliably. Biomarkers after secondary injury in AHT may be helpful in screening tests, and for predicting outcomes and stratifying children with increased risks of clinical deterioration. Changes in biomarker levels may help identify AHT where it is challenging to assess brain injury by traditional physical exams or neuroimaging approaches. However, it should be noted that no biomarkers are specific to AHT. Spatially and temporally correlating the biomarker changes in animal models with human findings is still a massive challenge in studying AHT.

PMC10003460

Meiqi Li,Xiaoyu Sang,Xiaohan Zhang,Xiang Li,Ying Feng,Na Yang,Tiantian Jiang

A Metabolomic and Transcriptomic Study Revealed the Mechanisms of Lumefantrine Inhibition of Toxoplasma gondii

03-03-2023

Toxoplasma gondii,lumefantrine,metabolomics,transcriptomics

Toxoplasma gondii is an obligate protozoon that can infect all warm-blooded animals including humans. T. gondii afflicts one-third of the human population and is a detriment to the health of livestock and wildlife. Thus far, traditional drugs such as pyrimethamine and sulfadiazine used to treat T. gondii infection are inadequate as therapeutics due to relapse, long treatment period, and low efficacy in parasite clearance. Novel, efficacious drugs have not been available. Lumefantrine, as an antimalarial, is effective in killing T. gondii but has no known mechanism of action. We combined metabolomics with transcriptomics to investigate how lumefantrine inhibits T. gondii growth. We identified significant alternations in transcripts and metabolites and their associated functional pathways that are attributed to lumefantrine treatment. RH tachyzoites were used to infect Vero cells for three hours and subsequently treated with 900 ng/mL lumefantrine. Twenty-four hours post-drug treatment, we observed significant changes in transcripts associated with five DNA replication and repair pathways. Metabolomic data acquired through liquid chromatography-tandem mass spectrometry (LC-MS) showed that lumefantrine mainly affected sugar and amino acid metabolism, especially galactose and arginine. To investigate whether lumefantrine damages T. gondii DNA, we conducted a terminal transferase assay (TUNEL). TUNEL results showed that lumefantrine significantly induced apoptosis in a dose-dependent manner. Taken together, lumefantrine effectively inhibited T. gondii growth by damaging DNA, interfering with DNA replication and repair, and altering energy and amino acid metabolisms.

A Metabolomic and Transcriptomic Study Revealed the Mechanisms of Lumefantrine Inhibition of Toxoplasma gondii Toxoplasma gondii is an obligate protozoon that can infect all warm-blooded animals including humans. T. gondii afflicts one-third of the human population and is a detriment to the health of livestock and wildlife. Thus far, traditional drugs such as pyrimethamine and sulfadiazine used to treat T. gondii infection are inadequate as therapeutics due to relapse, long treatment period, and low efficacy in parasite clearance. Novel, efficacious drugs have not been available. Lumefantrine, as an antimalarial, is effective in killing T. gondii but has no known mechanism of action. We combined metabolomics with transcriptomics to investigate how lumefantrine inhibits T. gondii growth. We identified significant alternations in transcripts and metabolites and their associated functional pathways that are attributed to lumefantrine treatment. RH tachyzoites were used to infect Vero cells for three hours and subsequently treated with 900 ng/mL lumefantrine. Twenty-four hours post-drug treatment, we observed significant changes in transcripts associated with five DNA replication and repair pathways. Metabolomic data acquired through liquid chromatography-tandem mass spectrometry (LC-MS) showed that lumefantrine mainly affected sugar and amino acid metabolism, especially galactose and arginine. To investigate whether lumefantrine damages T. gondii DNA, we conducted a terminal transferase assay (TUNEL). TUNEL results showed that lumefantrine significantly induced apoptosis in a dose-dependent manner. Taken together, lumefantrine effectively inhibited T. gondii growth by damaging DNA, interfering with DNA replication and repair, and altering energy and amino acid metabolisms. Toxoplasma gondii is an obligate apicomplexan protozoan that has a broad range of hosts. T. gondii can infect all warm-blooded animals, including humans, livestock, and wild animals and poses a threat to human and animal health. Thus far, one-third of the human population is chronically infected with T. gondii [1]. In China, the human infection rate is about 8% [2,3,4,5,6]. T. gondii is an opportunistic pathogen that is lethal to those with compromised immune systems such as AIDS patients, organ transplant recipients, and malignant tumor patients. Infection with T. gondii is one of the major causes of death in these patients [1,2,3,4,5,6]. Infection during pregnancy can cause vertical transmission, which could lead to spontaneous abortion, premature birth, or death of the fetus. In newborns, a wide range of birth defects can occur as a result of vertical transmission, including malformation, intracranial calcification, cognitive disorder, hydrocephalus, vision damage, and even death [7,8]. In addition, studies have implicated toxoplasmosis in the mental disorder of 1–10% of psychiatric patients. In particular, toxoplasmosis was linked to schizophrenia [9,10]. In animal husbandry, T. gondii infection can cause spontaneous abortion or death of domestic animals including pigs, sheep, and poultry, which causes tremendous economic losses [11]. More importantly, the high incidence of animal toxoplasmosis facilitates T. gondii transmission to humans and leads to a high infection rate in humans [12]. Therefore, it is imperative to develop therapeutics to alleviate the suffering inflicted by this notorious pathogen. To date, treatment of toxoplasmosis relies on pyrimethamine and sulfadiazine, clarithromycin, azithromycin, atovaquone, and epiroprim [13,14,15,16,17,18,19,20]. Pyrimethamine combined with sulfadiazine has been the gold standard therapeutic [17]. Pyrimethamine is an antifolate and acts against dihydrofolate dehydrogenase to affect the synthesis of DNA [16], and sulfadiazine can interfere with folate synthesis. Thereby the combined therapy can act synergistically against T. gondii [14]. In rare cases, the therapy can induce side effects such as agranulocytosis, Stevens-Johnson syndrome, and liver necrosis among other adverse effects [18]. The efficacy of clarithromycin and azithromycin in the treatment of T. gondii infections in immunocompromised patients has not been confirmed [20]. If these drugs were the last resort to treat toxoplasmosis, they must be used in combination with other drugs such as pyrimethamine. Atovaquone and epiroprim as the second-line drugs act through inhibition of cytochrome bc1 complex and dihydrofolate reductase, respectively [15]. The current treatment period for T. gondii is lengthy, ranging from a week to over a year with drugs often showing high toxicity to host cells [19]. Therefore, it is imperative to search for novel drugs that have low side effects and high efficacy and elucidate their mechanisms of action. One of the drug discovery efforts has been focusing on drug repurposing. Lumefantrine was an antimalarial synthesized by the Beijing Academy of Military Medical Sciences in the 1970s. In the treatment of malaria, lumefantrine has high efficacy, low toxicity, and side effects [21]. Lumefantrine, in combination with artemether, is recommended by WHO to be the first line of antimalarial for different types of malaria, severe or drug-resistant malaria due to its efficacy and safety [22,23]. Our previous study has shown that lumefantrine curtailed the growth of T. gondii RH growing in Vero cells in vitro and prolonged the survival time of infected mice [24]. However, despite its significance, the mode of action of lumefantrine is still unknown. Transcriptomics captures the complete transcript profile to study gene expression and regulation in cells or tissues under a certain biological condition [25,26]. Metabolomics is an innovative tool in drug target identification through accurate quantification of differential metabolites, systematic study of metabolites, metabolic pathways, and cellular metabolism of the parasites [27,28]. Therefore, transcriptome and metabolome can not only explain the “cause” and “effect” of biological processes but also reveal potential drug targets. Tewari et al. used transcriptomic and metabolomic approaches and showed that drug-treated parasites tuned carbohydrate metabolism and reduced metabolite flux through the pentose phosphate pathway, resulting in slower RNA synthesis and increased oxidative stress [29]. Jia et al. analyzed the mechanism of action of anlotinib on colon cancer cell line (HCT-116) through transcriptomic and metabolomic studies. Their results showed that anlotinib affected the protein synthesis of colon cancer cells by regulating amino acid and energy metabolism [30]. These studies demonstrate that a combined analysis of the transcriptome and metabolome can reveal the potential mechanism of the action of a drug. In this study, we analyzed the overall transcripts and metabolites of lumefantrine-treated T. gondii RH strain grown in Vero cells via RNA-sequencing and non-targeted metabolic sequencing technology (LC-MS). We delved into the potential mode of action of lumefantrine in T. gondii inhibition. The results of this study shed light on future research to elucidate the drug targets of antiparasitic compounds of various classes. To investigate the inhibitory effect of lumefantrine on T. gondii growth and its drug target, we designed and carried out four major experiments. We first determined the cytotoxicity of lumefantrine to Vero cells using the Cell Counting Kit-8 (CCK-8). A dose-response assay was carried out and intracellular parasite proliferation was measured via qPCR to determine the appropriate treatment concentration for downstream experiments. Subsequently, we prepared lumefantrine-treated parasites and conducted transcriptome and metabolome analysis. Lastly, we confirmed the apoptosis induced by lumefantrine using the TUNEL assay. CCK-8 assay was used to test the cytotoxicity of lumefantrine to Vero cells. Lumefantrine was 2-fold serially diluted from 3600 ng/mL to 225 ng/mL. 24 h or 36 h post-infection, lumefantrine did not show significant cytotoxicity to Vero cells (Figure 1A,B). To confirm the inhibitory effect of lumefantrine on T. gondii growth, we carried out qPCR and IFA. The qPCR results showed that lumefantrine inhibited 60% of T. gondii growth at 900 ng/mL (Figure 1C). IFA results were observed under the confocal fluorescent microscope. The number of parasites per parasite vacuole was recorded by examining at least 100 vacuoles. Lumefantrine-treated (900 ng/mL) vacuoles had a significantly smaller number of parasites (Figure 1D), indicating that lumefantrine inhibits T. gondii proliferation. To visually demonstrate the data from Figure 1D, we created Figure 1E. As shown in Figure 1E, under two different magnifications, most PVs contained 4 or 8 parasites in the drug-treated group, while the PVs containing 8 or 16 were prevalent in the no-drug control. To further analyze the effect of lumefantrine on T. gondii gene expression, a transcriptome analysis was performed. T. gondii were treated with 900 ng/mL lumefantrine for 24 h. Three biological replicates were set up for both the control (control 1, 2, and 3) and the drug treatment groups (LF1, LF2, LF3). To investigate the difference between groups and within groups, we conducted principal components analysis (PCA). The transcriptome profiles of the control groups and the drug-treated groups were separated on the PCA graph above and below PC2 = 0 (Figure 2A). This indicates that there is a significant difference between the drug-treated and non-treated groups. PC1 and PC2 showed 85% and 12% variation, respectively (Figure 2A). We used DESeq to analyze the 7646 detected genes. Compared with the control group, based on the criteria of p < 0.05, fold change >1, one hundred and seventy-five differentially expressed genes (DEGs) were marked as upregulation, and 216 DEGs were downregulated in the drug-treated group (Figure 2B). To verify the accuracy of RNA-seq data, we selected ten differentially expressed genes for qPCR analysis (Figure 2C and Table 1). Based on ToxoDB, these ten genes all have adequate expression levels with expression values (log2) of more than seven. Consistent with the results of RNA-seq, six genes were upregulated, and four were downregulated. Next, we performed gene ontology (GO) enrichment classification of differentially expressed genes (Figure 2D). Three functional aspects were included in GO analysis, namely, biological process, molecular function, and cellular component. Compared with the control group, biological processes that were significantly affected by lumefantrine included DNA replication (GO:0006260), DNA geometric change (GO:0032392), DNA duplex unwinding (GO:0032508), cell division (GO:0051301), cell cycle (GO:0007049), protein phosphorylation (GO:0006468), and phosphorylation modification (GO:0016310). The molecular functions that were altered by lumefantrine included transferase (GO:0016772), sphingosine N-acyltransferase (GO:0050291), protein kinase (GO:0004672), phosphotransferase (GO:0016773), kinase (GO:0016301), exonuclease (GO:0004527), DNA polymerase (GO:0034061), DNA helicase (GO:0003678), DNA—directed DNA polymerase (GO:0003887), and catalytic activity (GO:0140097) (Figure 2D). Three major cellular components of T. gondii were influenced by lumefantrine, namely, spindle (GO:0005819), microtubule organizing center (GO:0005815), and chromosomal region (GO:0098687) (Figure 2D). KEGG analysis revealed forty significantly enriched pathways. The top twenty most significantly enriched pathways were presented in Figure 2E. Among the most enriched pathways, pathways involved in genetic information processing were significantly impacted including DNA replication, base excision repair, nucleotide excision repair, homologous recombination, and mismatch repair. Pathways involved in toxoplasmosis and arachidonic acid metabolism were also significantly enriched. In the DNA replication and base excision repair, over 20% of the genes were DEGs. In summary, lumefantrine altered the expression of genes involved in DNA replication and repair systems of T. gondii. We classified the top thirty most enriched pathways into four categories based on transcriptomic data (Figure 3A). DNA replication is the most significantly altered pathway under lumefantrine treatment (Figure 3A). Next, we zoomed in on the DEGs in the DNA replication pathway. Among the thirty genes annotated in DNA replication, seven genes were found to be upregulated (p < 0.05) (Figure 3B). They are proliferating cell nuclear antigen PCNA2 (TGME49_320110), DNA polymerase (TGME49_280690, TGME49_268600, and TGME49_233820), a putative DNA replication licensing factor MCM2 (TGME49_214970), a putative DNA replication licensing factor MCM4 (TGME49_219700), and a putative helicase (TGME49_261850). To investigate how lumefantrine alters T. gondii metabolism, we performed liquid chromatography-tandem mass spectrometry (LC-MS) analysis. A total of 432 differential metabolites were identified using positive and negative ion mode LC-MS. To analyze differentially accumulated metabolites between groups, we used orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) (Figure 4A,B). OPLS-DA score plots showed the separation of the drug-treated group and the non-treated group in both positive and negative ion modes, which indicated that the metabolite profile in the drug-treated group was significantly different from that in the control group. As shown in Figure 4C, the overall distribution of DAM was relatively symmetrical. In particular, the biosynthesis of 29 metabolites was significantly affected, as shown in the volcano and heat maps shown in Figure 4C,E. Among the downregulated metabolites was thymidine. Thymidine exists exclusively in DNA and the T-loop of tRNA. Among the upregulated metabolites were cytidine and D-fructose-1,6-diphosphate. The former is a component of RNA and a precursor of uridine which is used in RNA synthesis and the latter is involved in glycolysis which affects the energy metabolism of T. gondii. Differentially accumulated metabolites were annotated to KEGG pathways. The KEGG analysis showed that differential metabolites were mainly enriched in 27 pathways (Figure 4D). The significantly impacted pathways include galactose metabolism, fructose and mannose metabolism, sulfur relay system, arginine, and proline metabolism, ABC transporters and phenylalanine, tyrosine, and tryptophan biosynthesis. Most of these pathways are related to energy and amino acid metabolisms. In summary, our data suggest that lumefantrine induced the metabolic disorder of T. gondii, affecting glucose catabolism and amino acid metabolism. To elucidate whether lumefantrine induces apoptosis, we used the TUNEL method to detect the integrity of DNA strands of lumefantrine-treated T. gondii. The red fluorescent signal increased with the lumefantrine concentration (900 ng/mL vs. 1800 ng/mL), while no fluorescent signal was observed in the control group (Figure 5A). This indicates that lumefantrine-induced DNA breakage of T. gondii. Quantitative analysis using confocal microscopy showed that the apoptosis rates in the drug-treated groups were significantly higher than that in the control. In addition, lumefantrine-induced apoptosis was dose-dependent as the apoptosis rate was significantly higher in T. gondii treated with 1800 ng/mL of lumefantrine compared to that with 900 ng/mL of lumefantrine (Figure 5B). The current work investigated the mechanism of the action of lumefantrine on T. gondii. Our data showed that lumefantrine-induced apoptosis in T. gondii interfered with DNA replication and repair, and caused metabolic alterations. We first studied the cytotoxicity of lumefantrine to Vero cells and determined the appropriate drug concentration for T. gondii treatment. We found that lumefantrine at 900 ng/mL reduced 60% of the intracellular proliferation of T. gondii. Transcriptomic data showed that lumefantrine altered transcripts involved in DNA replication and repair and caused metabolic changes. We found 41 differential pathways through transcriptomic study including 12 pathways that were DNA replication related, 5 RNA-associated pathways, and 23 pathways that were related to energy metabolism. The top three significantly impaired pathways were DNA replication, base excision repair, and nucleotide excision repair. T. gondii can propagate in a wide array of cell types and replicate every 6–8 h. Precise duplication of DNA ensures the sustainability and stability of T. gondii genetic material [31]. Base excision repair is the major mechanism of DNA repair, through which mutated bases or nucleotides were removed [32]. The highly conserved nucleotide excision repair system is used to restore genome integrity including repairing hydrogen bonds between strands [33]. In addition, it contributes to promoting mRNA synthesis or shaping the 3D architecture of chromatin [34]. Among the significantly altered pathways were DNA replication, base excision repair, and nucleotide excision repair. Proliferating cell nuclear antigen (PCNA) is an auxiliary protein of DNA polymerase δ and ε and is central to DNA replication and repair. Lima et al. have shown through transcriptome data that T. gondii infection-induced gene expression changes related to DNA replication and repair [35]. Their data showed that in T. gondii-infected human neutrophils, the PCNA transcript was upregulated which was consistent with our finding in lumefantrine-treated T. gondii. In their study, the PCNA transcript upregulation was linked to the delayed apoptosis of T. gondii-infected neutrophils. Minichromosome maintenance protein 2 (MCM2) and MCM4 play critical roles in DNA replication initiation. Recent studies have shown that MCM proteins play roles in replication elongation and genome stability [36]. MCM OB domain and MCM2/3/5 family were significantly affected by the deletion of T. gondii UBL-UBA shuttle protein which was found to regulate DNA replication [37]. We found the upregulation of PCNA, MCM2, MCM4, and DNA polymerase. It has been shown that DNA damage activated PCNA, and PCNA was involved in nucleotide excision repair, base excision repair, and mismatch repair [38]. DNA repair also requires the participation of DNA polymerase δ and/or ε. The upregulation of these proteins in our study implies DNA damage induced by lumefantrine treatment. The DNA-damaging effect discovered in this study is not uncommon among drugs. For example, artemisinin induced a DNA-damaging effect in Plasmodium falciparum, similar to the effect of methyl methanesulphonate, an alkylating agent [39]. In a recent study, artemisinin resistance was found to be associated with enhanced DNA damage repair [40]. The molecular mechanism of the DNA damage induced by lumefantrine in T. gondii is, however, yet to be investigated. It has been shown that the DNA damage induced by artesunate in P. falciparum was accompanied by an increased level of ROS (Reactive Oxygen Species) in the parasites and that artesunate exerted DNA breakage in a dose- and time-dependent manner [41]. Albendazole was shown to arrest the cell cycle at the G2/M phase in Giardia duodenalis and induced nuclei acid oxidative damage evidenced by the phosphorylation of histidine H2AX [42]. Among the pathways involving significantly enriched DAMs, the most significantly impacted is galactose metabolism. Galactose can be converted to glucose, lactose, and other sugar intermediates which can participate in a series of energy-related metabolic processes. It enters glycolysis through conversion to glucose-1-phosphate (G1P) [43]. Secondly, the ABC transporter pathway was significantly altered. The ATP-binding cassette (ABC) transporter proteins are a superfamily of membrane proteins that are responsible for the ATP-powered transportation of a wide range of substances [44], including cellular metabolites, drugs, lipids, and sterols. Multidrug-resistant protein 1 (MDR1), a member of the ABC transporter superfamily, was found to contribute to drug resistance in malaria. In the case of artemisinin and mefloquine, MDR1 delivers drugs into the digest vacuoles, preventing them from hitting the drug target. In the case of chloroquine, MDR1 transports the compound out of its site of action—the digestive vacuole. Mutations and copy number variations in MDR1 have been associated with drug resistance in Plasmodium falciparum [45]. The downregulation of ABC transporter is frequently found in drug resistance in cancer cells [30,46]. Out of the 13 ABC membrane transporters in T. gondii, TgABC.B1 is the most expressed and shows the highest similarity to the human MDR1 protein. The participation of this transporter in drug resistance in T. gondii has been proposed [47]. Our data suggest that lumefantrine altered the transportation of various metabolites through the ABC transporter. ABC transporter pathway could possibly participate in lumefantrine transportation in T. gondii. Thirdly, the fructose and mannose metabolism pathway was significantly affected which led to the poor utilization of host-sourced glucose and ultimately slowed down the replication of T. gondii [48]. The fourth noteworthy pathway is arginine and proline metabolism. Since T. gondii is an arginine auxotroph, the reduced arginine production in the parasite could restrict parasite reproduction [49]. Modulation of arginine metabolism toward ornithine, proline, and polyamines can be viewed as a parasite adaptation. The diversion of arginine metabolism toward arginase degradation and the reduction of iNOS- induced nitric oxide have been shown to curtail parasite proliferation [50]. In summary, the metabolic data showed that lumefantrine disturbed the sugar and amino acid metabolisms of T. gondii, especially galactose and arginine. Vero cells were cultured at 37 °C, 5% CO2 incubator in DMEM medium (MACGENE, Beijing, China) containing 100 U/mL penicillin, 100 μg/mL streptomycin (MACGENE, China), and 8% heat-inactivated fetal bovine serum (BI, Uruguay, Israel). T. gondii RH strain was cultured in DMEM medium supplemented with penicillin, streptomycin, and 2% heat-inactivated fetal bovine serum (BI, Uruguay, Israel). The cytotoxicity of lumefantrine (Sigma, Ronkonkoma, NY, USA) to Vero cells was evaluated using the Cell Counting Kit-8 (CCK-8) (Baisai, China). Vero cells (3 × 104) were seeded in each well of a 96-well plate and cultured in DMEM for 24 h. Lumefantrine was 2-fold serially diluted in DMEM from 3600 ng/mL to 225 ng/mL. The blank control was 110 μL of DMEM, and negative control was Vero cells with 110 μL of DMEM. After culturing for 24 or 36 h, 10 μL of CCK solution was added into each well and incubated for 1 h. Optical density (OD) was measured at 450 nm using a microplate reader. Immunofluorescent assay (IFA) was used to quantify the proliferation. T. gondii was inoculated onto Vero cells growing on slides inserted in a 12-well plate and allowed to infect for 2 h at 37 °C, 5% CO2. Cells were washed, supplied with serum-free medium or medium containing 900 ng/mL lumefantrine, and incubated for 20 h. Cells were then fixed with 4% paraformaldehyde for 15 min, permeabilized with 0.25% Triton X-100 for 15 min, and blocked with 3% bovine serum albumin for 30 min. Rabbit anti-TgALD was added as primary antibody and incubated for one hour. The secondary antibody (Alexa Fluor488 goat anti-rabbit) was added subsequently and incubated for one hour. Nuclear DNA was stained with DAPI for 10 min. Image and data acquisition was performed using Leica fluorescence microscope system (Leica, Wetzlar, Germany) at 189× and 124× magnifications. At least 100 parasite vacuoles per sample were examined to determine the number of parasites per vacuole. The inhibitory effect of lumefantrine on T. gondii was detected by qPCR. Vero cells were inoculated into a 6-well plate and allowed to grow for 12 h. 3 × 105 of newly released RH tachyzoites were used to infect Vero cells for 4 h at 37 °C. Cells were washed twice to rid of extracellular parasites. Parasites and cells were treated with lumefantrine (0, 900, and 1800 ng/mL) in DMEM for 24 h. Cells were scraped off and used for DNA extraction using a DNA extraction kit (Tiangen, Beijing, China). The proliferation of parasites was detected using the 2−∆∆t relative expression method. The primers targeting T. gondii GAPDH (housekeeping gene) were GAPDH-F (ATTTTGCTTGGGATTCGAGGA) and GAPDH-R (TGCAGGGTAACGATCAAAAAATG). Three sets of transcriptome samples were prepared. Vero cells grown in T25 flasks were infected with 1 × 107 tachyzoites for 3 h at 37 °C, 5% CO2. Media was replaced with serum-free DMEM with or without drug (900 ng/mL lumefantrine). After incubation for 24 h, cells were scraped off and syringed with a 22 G ½ inch needle on a 5 mL syringe to liberate parasites. We then passed the mixture through 3 μM of filter to obtain the parasites. After flash freezing in liquid nitrogen, cell lysates were ready for library preparation. The mRNA with polyA structure in the total RNA was enriched by Oligo(dT) magnetic beads. RNA was fragmented into pieces of roughly 300 bp. Using RNA as a template, the first strand of cDNA was synthesized with 6-base random primers and reverse transcriptase, and the second strand of cDNA was synthesized using the first strand of cDNA as a template. After the library was constructed, PCR amplification was used to enrich the library fragments. Fragments of around 450 bp were selected. Agilent 2100 Bioanalyzer was used for quality inspection, through which the total and effective concentrations of the library were obtained. The libraries containing different indexes were pooled which were then diluted to 2 nM and denatured by alkali. The pooled libraries were subjected to pair-ended Illumina sequencing. Among all differentially expressed genes, 10 genes identified by RNA-seq analysis were selected for validation by qRT-PCR. Samples preparation procedure was the same as described in Section 4.5. Total RNA was extracted using TRIzol, and then cDNA was synthesized from total RNA using PrimeScriptTM II First Strand cDNA Synthesis Kit (Takara, Dalian, China) according to the manufacturer’s instructions. All qRT-PCR experiments were performed in three technical replicates using GAPDH as the reference gene. The qRT-PCR primers used in this study were described in Table 1. The cycle conditions were 95 °C for 5 min, 40 cycles of 95 °C for 10 s, 60 °C for 10 s, and 72 °C for 15 s, and the melting curve temperature is 72~95 °C. Gene expression was calculated using the 2−∆∆t relative expression method. Seven groups of metabolome samples were prepared. Parasites were prepared in the same manner as shown in Section 4.5. After flash freezing in liquid nitrogen, parasites were mixed with tissue extraction solution (75% of methanol and chloroform at 9 to 1 ratio, 25% H2O), three steel balls, and ground in a high-throughput tissue grinder at 50 Hz for 60 s. The grinding process was repeated twice. The cell culture was then subjected to ultrasonication at room temperature for 30 min, subsequently placed on ice for 30 min, and centrifuged at 12,000 rpm, 4 °C for 10 min. Notably, 850 μL of the supernatant was taken and dried in a vacuum concentrator. In addition, 200 μL of 2-chlorobenzalanine solution made with 50% acetonitrile solution was added to redissolve the samples which were subsequently filtered through a 0.22 μm membrane. Notably, 20 μL of the filtrate from each sample was pooled into a QC sample to be used for data normalization. The remaining samples were used for LC-MS detection. LC-MS/MS was carried out with positive and negative ion mode electrospray ionization. Chromatographic separation was performed using ACQUITY UPLC® HSS T3 1.8 μm (2.1 × 150 mm) chromatographic column with the temperature of the autosampler set at 8 °C, the flow rate at 0.25 mL/min, and the column temperature at 40 °C. 2 μL of the sample was injected for gradient elution. The positive ion mobile phase consisted of 0.1% formic acid (solvent C) and 0.1% formic acid in acetonitrile (solvent D), and the negative ion mobile phase was comprised of 5 mM of ammonium formate (solvent A) and 20% acetonitrile (solvent B). The gradient elution program was as follows: 2% B/D (0~1 min), 2~50% B/D (1~9 min), 50~98% B/D (9~12 min), 98% B/D (12~13.5 min), 13.5~14 min, 98~2% B/D(13.5~14 min), 2% D—positive mode (14~20 min) or 2% B—negative mode (14~17 min). Ionization was accomplished with electrospray ionization source (ESI) in positive and negative ionization modes. Mass spectrometry was conducted with a positive ion spray voltage of 3.50 kV, a negative ion spray voltage of 2.50 kV, sheath gas of 30 arbs, and auxiliary gas of 10 arbs. The capillary temperature was 325 °C, full scan was performed with a resolution of 70,000, and the scan range was 81–1000. HCD was used for secondary decomposition, and the collision voltage was 30 eV. Dynamic exclusion was used to remove unnecessary MS/MS information. The obtained raw data were converted into mzXML format by Proteowizard software (v3.0.8789). The XCMS package of R (v3.3.2) was used for peak identification, peak filtration, and peak alignment including the following parameters, bw = 5, ppm = 15, peak width = c (5, 30), mzwid = 0.015, mzdiff = 0.01, method = “centWave”. A data matrix was obtained including mass-to-charge ratio (m/z), retention time, and peak area (intensity). 20,085 precursor molecules were obtained in positive ion mode, and 10,983 precursor molecules were obtained in negative ion mode, and the data were exported to excel for subsequent analysis. To make the data comparable, batch normalization of the peak area was performed. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) was used for multivariate statistical analysis using software package, SIMCA-P (v13.0) and the ropls package R. The data set was scaled using the pheatmap package of R (v3.3.2) by which a hierarchical clustering map of relative quantitative values of metabolites was obtained. TUNEL test can be used to detect DNA breakage in the final stage of apoptosis [51]. T. gondii was cultured in Vero cells for 48 h with 0, 900, or 3600 ng/mL of lumefantrine. Parasites were released from host cells with a 22 G ½ inch needle in a 5 mL syringe. After filtration through 3 μM filter, parasites were centrifugated at 1200 g for 5 min and resuspended with 200 μL of DMEM medium. Slides were inserted into a 24-well plate and treated with 200 μL of poly-L-lysine at 37 °C for 30 min. After repeated washing, parasites were added to the slides and incubated for 20 min. Parasites were fixed, premetallized, blocked, and stained with primary and secondary antibodies in the same fashion as described in Section 4.3. Hoechst solution (diluted 1:1000) was used for nuclei staining. Notably, 50 μL TUNEL detection solution (5 μL of TdT enzyme, 45 μL of fluorescent labeling solution, Biyuntian, China) was added to the slides and incubated at 37 °C in an immunohistochemical wet box for 60 min. After washing, the slides were sealed and observed under a fluorescent microscope. The nuclei of TUNEL-positive parasites should appear red. The ratio of the number of DNA-damaged parasites (red fluorescence) to the total number of tachyzoites (green fluorescence) was defined as the apoptotic rate. Ten fields were randomly selected for data acquisition and three technical replicates were included. Statistical analysis was performed using GraphPad Prism 8.0.2 software. All values were expressed as mean ± S.D. All data were analyzed using ANOVA or t-test. p values less than 0.05 were considered statistically significant. In summary, we identified the potential drug targets of lumefantrine on T. gondii through transcriptomic and metabolomic studies. Our data suggest that lumefantrine likely exerts its inhibitory effect on T. gondii through damaging DNA, impairing DNA replication and repair, and inducing metabolic alterations to hinder the efficient acquisition of energy and essential amino acids.

PMC10003462

Geon Kang,Seung-Hak Baek,Young Ho Kim,Dong-Hyun Kim,Ji Wan Park

Genetic Risk Assessment of Nonsyndromic Cleft Lip with or without Cleft Palate by Linking Genetic Networks and Deep Learning Models

25-02-2023

artificial neural network,genetic algorithm,genetic risk prediction,neural networks ensemble,machine learning,nonsyndromic cleft lip with or without cleft palate,polygenic risk score,single nucleotide polymorphism

Recent deep learning algorithms have further improved risk classification capabilities. However, an appropriate feature selection method is required to overcome dimensionality issues in population-based genetic studies. In this Korean case–control study of nonsyndromic cleft lip with or without cleft palate (NSCL/P), we compared the predictive performance of models that were developed by using the genetic-algorithm-optimized neural networks ensemble (GANNE) technique with those models that were generated by eight conventional risk classification methods, including polygenic risk score (PRS), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and deep-learning-based artificial neural network (ANN). GANNE, which is capable of automatic input SNP selection, exhibited the highest predictive power, especially in the 10-SNP model (AUC of 88.2%), thus improving the AUC by 23% and 17% compared to PRS and ANN, respectively. Genes mapped with input SNPs that were selected by using a genetic algorithm (GA) were functionally validated for risks of developing NSCL/P in gene ontology and protein–protein interaction (PPI) network analyses. The IRF6 gene, which is most frequently selected via GA, was also a major hub gene in the PPI network. Genes such as RUNX2, MTHFR, PVRL1, TGFB3, and TBX22 significantly contributed to predicting NSCL/P risk. GANNE is an efficient disease risk classification method using a minimum optimal set of SNPs; however, further validation studies are needed to ensure the clinical utility of the model for predicting NSCL/P risk.

Genetic Risk Assessment of Nonsyndromic Cleft Lip with or without Cleft Palate by Linking Genetic Networks and Deep Learning Models Recent deep learning algorithms have further improved risk classification capabilities. However, an appropriate feature selection method is required to overcome dimensionality issues in population-based genetic studies. In this Korean case–control study of nonsyndromic cleft lip with or without cleft palate (NSCL/P), we compared the predictive performance of models that were developed by using the genetic-algorithm-optimized neural networks ensemble (GANNE) technique with those models that were generated by eight conventional risk classification methods, including polygenic risk score (PRS), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and deep-learning-based artificial neural network (ANN). GANNE, which is capable of automatic input SNP selection, exhibited the highest predictive power, especially in the 10-SNP model (AUC of 88.2%), thus improving the AUC by 23% and 17% compared to PRS and ANN, respectively. Genes mapped with input SNPs that were selected by using a genetic algorithm (GA) were functionally validated for risks of developing NSCL/P in gene ontology and protein–protein interaction (PPI) network analyses. The IRF6 gene, which is most frequently selected via GA, was also a major hub gene in the PPI network. Genes such as RUNX2, MTHFR, PVRL1, TGFB3, and TBX22 significantly contributed to predicting NSCL/P risk. GANNE is an efficient disease risk classification method using a minimum optimal set of SNPs; however, further validation studies are needed to ensure the clinical utility of the model for predicting NSCL/P risk. Orofacial clefts (OC), which are the second most common congenital anomaly with a wide range of etiologies, can occur as an isolated form or as a syndrome. The prevalence of OC varies by region and ethnicity, with the highest incidence being observed in Asian populations [1]. According to a nationwide cohort study, the overall prevalence of OC in Korea was 1.96 per 1000 live births, and approximately 76.45% of all cases occur in the nonsyndromic form. Specifically, cleft lip only (CL), cleft lip with cleft palate (CLP), and cleft palate only (CP) accounted for 26.47%, 26.56%, and 52.97% of total cases, respectively [2]. As CP has been considered a distinct malformation, recent genetic studies have primarily focused on nonsyndromic cleft lip with or without cleft palate (NSCL/P), which is known to be more heritable [3]. From the 1990s to the early 2000s, family-based studies have provided evidence that chromosomal regions (such as 2p, 4q, and 6p) and genes (such as COL11A1 and TGFA) are linked with nonsyndromic OCs. However, genetic association studies have shown much greater statistical power in detecting susceptibility genes for complex diseases, and genes involved in craniofacial development, such as IRF6 and MSX1, have been identified to be associated with NSCL/P [4]. Since around 2010, genome-wide association studies (GWASs), which represent a hypothesis-free approach using millions of single nucleotide polymorphism (SNP) markers, have identified novel loci for NSCL/P, such as 8q24, 10q25.3, and 17q22 [5,6,7]. Although previous studies have been primarily conducted in populations with European ancestry, genetic heterogeneity among ethnic groups has become a major concern in identifying susceptibility variants for NSCL/P, as reported in a study of 8q24.21 and a Chinese GWAS [8,9]. With the accumulation of susceptibility SNPs discovered in GWAS, the demand for developing methods for predicting genetic risk is rapidly growing. Polygenic risk scoring (PRS), which is defined as a weighted sum of individual risk alleles, has been widely applied to predict multifactorial disease risk; however, its reliance on an additive model limits its application to elucidate complex interactions among genetic variants [10,11]. Furthermore, machine learning (ML) algorithms have been applied for the risk prediction of complex diseases, due to their strength in identifying patterns and interactions among multiple inputs by employing multivariate, nonparametric methods [12]. Zhang et al. (2018) evaluated seven ML techniques, including random forest (RF) and artificial neural network (ANN), by using forty-three NSCL/P-associated SNPs and reported that the logistic regression model had the highest classification performance in Han Chinese (AUC of 0.90) [13]. In a Brazilian study, RF and ANN effectively classified NSCL/P patients and normal subjects with greater than 94% accuracy by using 13 SNPs [14]. The recent advent of deep learning (DL) has further improved the classification capability for a disease by using individual SNP data, as was observed in a case–control study on obesity (AUC of 0.99) [15,16]. DL has been shown to be superior in mapping complex non-linear interactions and for integrating different types of data [17,18]; however, highly complex networks demand a large dataset to ensure sufficient predictive power and generalization of results [19,20,21]. Especially, given the difficulty of obtaining large numbers of human samples in the field of genomic medicine, appropriate feature selection directly affects model performance by reducing the noise and dimensionality of data in both traditional ML- and DL-based risk prediction methods [22,23,24]. The genetic algorithm (GA) is a promising method for optimizing feature selection. Tong and Schierz (2011) have successfully applied a hybrid genetic algorithm neural network (GANN) to extract highly informative genes from a microarray-based gene expression dataset [25]. In a separate study, Zhang et al. (2015) improved the performance of predicting immunogenic T-cell epitopes from epitope sequences through the use of an ensemble RF model that was trained on individual features selected with GA [26]. To the best of our knowledge, this study represents the first application of the GANNE approach to disease risk assessment and the first genetic risk prediction study for NSCL/P in the Korean population. Herein, we first performed a genetic association analysis by using 92 SNPs that were genotyped in 143 Korean children with NSCL/P and 119 healthy controls. We subsequently compared the predictive performance of the PRS and various ML methods. To improve predictive power, we proposed the use of a deep learning model that uses automatic feature selection for NSCL/P classification; specifically, we used the genetic-algorithm-optimized neural networks ensemble (GANNE). Finally, we functionally validated the genes selected by GANNE using pathway and network analyses. Four SNPs (rs10790330, rs906830, rs17104928, and rs3917211) demonstrated HWE p-values less than 0.05; however, none of the SNPs showed evidence of deviation from HWE (p > 0.01) in the control data, and the MAFs of all ninety-two SNPs were >1% in both the case and control groups. In the Fisher’s exact test, two intronic SNPs of IRF6 in linkage disequilibrium (LD) with a r2 value of 0.80 (rs2235373 and rs2235371) were found to be significantly associated with NSCL/P (p = 3.5 × and p = 4.5 × , respectively). Moreover, SNPs located near or within five other genes (RUNX2, ARNT, TGFB3, MTHFR, and TCOF1) also showed significant associations in Korean NSCL/P patients (p < 0.05) (Table 1). After accounting for pairwise LD ( < 0.8, see Table S1), we identified three SNPs that were associated with NSCL/P at the level of p < 0.01, as well as ten SNPs with nominal significance (p < 0.05) and sixteen SNPs with marginal significance (p < 0.1). The predictive performance of the PRS models for NSCL/P risk increased as the number of SNPs increased (accuracy = 0.676 and AUC = 0.711 for the 92-SNP model). When evaluating the models generated by the six traditional machine learning algorithms, the training accuracies significantly improved to above 95% for the 10-SNP model, especially for four of the ML algorithms. However, the testing accuracies remained in the 60% range. Out of the 18 models categorized by the number of SNPs and the type of machine learning algorithm, the SVM utilizing 10 SNPs demonstrated the highest predictive performance (test accuracy = 0.677, F1 = 0.678, AUC = 0.685). On the other hand, LightGBM demonstrated the lowest predictive performance among the machine learning algorithms (test accuracy = 0.565, F1 = 0.566, AUC = 0.568). We trained the four sets of SNPs by using the ANN deep learning algorithm but did not observe a significant improvement in predictive performance compared to PRS and the machine learning models (test accuracy = 0.63, F1 = 0.65, AUC = 0.71) (Figure 1). In the current study, we developed a model to improve NSCL/P classification by using the GANNE algorithm. We first prepared a set consisting of the top SNPs that were identified in the genetic association analysis, along with five optimal sets of SNPs that were selected by using GA, to be used as inputs for ANN deep learning. GANNE significantly improved predictive performance across all three SNP settings, especially the best model selected from six sets of ten SNPs (AUC of 88.2%), which increased AUC (∆AUC) by 17%, 23%, and 28.5%, respectively, compared to ANN, PRS, and RF (Figure 1). Despite the lower weighted F1-score of 0.76 compared to AUC, the 10-SNP GANNE model still demonstrated superior performance when accounting for class imbalance in the binary data. In addition, the test accuracy of the 10-SNP GANNE (74.2%) increased within the range of 6.5% (SVM) to 14.5% (RF) compared to other methods, and it increased by 11.3% compared to the deep-learning-based ANNs. GANNE models with three SNPs and sixteen SNPs exhibited similar test results (accuracy = 0.694, F1 = 0.709, AUC of approximately 0.744), but the 16-SNP GANNE demonstrated better training accuracy than the 3-SNP GANNE (Figure 1, Table 2). The GANNE utilized 46, 25, and 15 different SNPs that were located in 14, 12, and 8 genes, respectively, at least once for the 3-, 10-, and 16-SNP models. Five SNPs from IRF6 (including rs2013162), rs11204737 (ARNT), rs7715100 (TCOF1), rs16873348 (RUNX2), and rs3917192 (TGFB3) were used in all three SNP models. Among the SNPs that were selected for the 10-SNP GANNE models, rs2013162 (IRF6) was the most potent SNP included in all six sets, followed by rs3917192 (TGFB3) in five sets (Table S2). To verify the reproducibility of the deep learning models, we performed 100 iterations, and the average of the results in each iteration followed the trend of the best model results for each set of SNPs. As expected, the 10-SNP GANNE model produced the highest accuracy and AUC, even at 100 iterations (average training accuracy = 92.1%, average test accuracy = 65.4%, average test AUC = 75.2%), with the highest AUC of 89.5% (Table 2). By using DAVID, we identified a total of 52 GO terms that were significantly associated with 12 genes harboring 25 SNPs used at least once in the 10-SNP GANNE (p < 0.05 and FDR < 0.1). In particular, the most enriched GO term (GO:0009888~tissue development) was associated with the following nine genes: IRF6, RUNX2, TBX22, MTHFR, PVRL1, PAX9, TGFB3, TCOF1, and VAX1. In addition, four genes (RUNX2, PVRL1, PAX9, and TGFB3) showed significant enrichment in GO:0042476~odontogenesis. In the PPI network analysis, nine of the twenty candidate genes that were evaluated in this study showed multiple interactions with other genes based on experimental evidence of co-expression. In particular, MSX1 and IRF6 were the most important hubs in this network, and genes such as PAX9, TBX22, RUNX2, TGFB3, and VAX1 also appeared to interact with more than one gene. However, eight genes (TCOF1, NSF, ADH1C, RARA, WNT3, ARNT, ZNF385B, and BCL3) did not show an interaction at a confidence score of 0.45 (Figure 2). As the discovery of genetic variants associated with complex diseases increases, the demand for personalized health care services using genetic information is also rapidly increasing. To overcome the limitations of regression-based PRS and conventional ML algorithms, artificial intelligence (AI) has recently begun to be applied to risk prediction and the early diagnosis of complex diseases [11]. Unlike traditional machine learning algorithms, deep learning is helpful in solving complex problems with far more parameters but requires a large-scale dataset to avoid overfitting and to generalize results [27]. Therefore, state-of-the-art deep learning algorithms are not widely applied in genomic medicine due to the difficulty of large-scale sample collection. In the current study, we improved the classification ability for NSCL/P in Korean individuals by performing a deep-learning-based ANN with informative SNPs selected via GA to reduce dimensionality while also increasing test accuracy. GANNE performed best for all three SNP settings compared to the eight conventional methods for risk prediction. In conjunction with the results of the in silico functional analysis, we also demonstrated the possibility of explaining interactions among genetic features, which have been considered a black box in ML applications. The machine learning algorithms, including GANNE, showed the highest classification accuracy when using 10 SNPs but the performance declined as the number of input SNPs increased. On the other hand, PRS, a widely used method in predicting complex disease risk, exhibited a consistent improvement in its AUC with the addition of more SNPs. Despite the simplicity in implementation, logistic-regression-based methods, such as LR and PRS, may not be effective in dealing with non-linear or highly correlated input data [10]. Our findings underscore the issue of dimensionality, whereby the number of required datasets increases exponentially as the input dimensionality increases when using ML algorithms as genetic risk predictors [24]. Supervised machine learning algorithms, RF and SVM, tend to perform well in high-dimensional data, but are prone to overfitting and are computationally intensive [12]. In this study, we found SVM to be more suitable for the non-linear binary classification task, as it showed better predictive performance (F1 = 0.678) compared to RF (F1 = 0.598). Boosting algorithms, including XGBoost, Adaboost, and LightGBM, are ensemble techniques that combine multiple models with weak predictive performance to form a more potent model [28]. Among the nine classification methods used in this study, LightGBM exhibited the lowest predictive performance. Further studies are necessary to investigate the impact of the strengths and limitations of each ML algorithm on disease risk prediction accuracy. There have been attempts to improve predictive accuracy by combining results from different SNP models, but most statistical association analyses have limitations in selecting different subsets of SNPs [29]. Although there are 7 trillion possibilities to select a set of 10 SNPs out of 92 SNPs in our dataset, GANNE can efficiently select an optimal set of SNPs by initializing the first population with the best SNPs that were identified in the association analysis. In particular, the 10-SNP GANNE model showed excellent performance and improved the AUC by 28.6%, 23%, and 17% compared to the RF, PRS, and ANN methods, respectively, by including SNPs that did not show a strong association with NSCL/P, which was likely due to a lack of statistical power. GA selected the SNPs that were significantly associated with NSCL/P while also extracting SNPs (such as rs7103685 in the PVRL1 gene) that did not show significant associations but that were used in four of the six SNP sets (p = 0.46). Although a further evaluation of gene–gene interactions by using PLINK did not yield statistical significance, a functional protein association network analysis suggests that GA considers functional interactions of genes in SNP selection. The IRF6 gene that was most frequently selected by GA was also a major hub gene in the PPI network, and its association with NSCL/P has been reported in previous studies [30]. However, MSX1, which is another hub gene in the PPI network, was selected by GA in the 16-SNP subset but not in the 10-SNP subset. Moreover, all three SNP markers for the MSX1 gene were not statistically significant in this case–control analysis, but its association with NSCL/P remains controversial with inconsistent results, especially in Asian studies [31,32,33]. GANNE has demonstrated the potential to identify significant interactions among genes when used in conjunction with the PPI network analysis. Due to the fact that there may be valid interactions between SNPs that cannot be detected by using statistical analysis, neural-network-based genetic interaction studies using tools such as class activation mapping or attention modules may be needed in the future [34]. In this study, we demonstrated that GANNE, which is an ensemble neural network with automated feature selection, outperforms existing methods in predicting NSCL/P risk with genotype data by reducing the input dimension of each network through the use of a GA. Although GANNE achieves better generalization and robustness than other classification methods, given the number of samples that were trained in this study, further studies with larger samples are needed to validate the accuracy of the model. In genetic association studies, adjustments for age as a potential confounder are usually unnecessary, as differences in age between cases and controls may be associated with disease outcome but unlikely with genotype [35]. We evaluated 143 Korean NSCL/P patients (91 males and 52 females) from 258 Korean families with nonsyndromic OC who visited Seoul National University Dental Hospital and SAMSUNG Medical Center. At each hospital, an orthodontist diagnosed the types of NSCL/P in the cases (nine cases with cleft lip only, twenty-six cases with cleft lip and alveolus, and one hundred and eight cases with cleft lip and palate). As a control group, we selected 119 healthy Korean adults without OC (60 males and 59 females) from a community-based cohort that was jointly developed by Hallym University College of Medicine and Chuncheon Sacred Heart Hospital. A trained dentist or clinician interviewed the participants and collected peripheral venous blood samples after obtaining informed written consent. The Institutional Review Board of each institution approved this study protocol. The details of the data collection can be found elsewhere [36,37]. By using literature reviews, we identified nineteen candidate genes, including PAX9 and TGFA, and two chromosomal loci (8q24.21 and 10q250), which have been reported to be associated with NSCL/P in previous studies. By using a web browser known as, ‘TAG SNP selection (TagSNP)’ (https://snpinfo.niehs.nih.gov/snpinfo/snptag.html) [38], we identified SNP markers that were frequently found in East Asian populations among SNPs located within 2 kb from each of the 5′ and 3′ ends of the candidate genes. Genomic DNA was isolated from each blood sample by using a commercial DNA extraction kit (Quiagen Inc., Valencia, CA, USA) at the Samsung Biomedical Research Center, and genotype data were generated via SNP Genetics Inc. (Seoul, Republic of Korea) by using VeraCode Technology (Illumina Inc., San Diego, CA, USA). Details of these procedures are presented elsewhere [39]. We subsequently analyzed only 92 SNPs in Hardy–Weinberg equilibrium (HWE p-values greater than 0.01) with both genotype and sample call rates greater than 95% and a minor allele frequency (MAF) greater than 1%. After SNP quality control, a pairwise LD was estimated by calculating r2 via the Haploview program in the control group. The missing genotypes were imputed by considering the calculated LD [40]. We performed Fisher’s exact test by using PLINK 1.9 for genetic association analysis [41]. Based on the statistical significance obtained by the Fisher’s exact test, we selected four subsets of SNP markers for the binary classification of NSCL/P risk: three SNPs (p < 0.01), ten SNPs (p < 0.05), sixteen SNPs (p < 0.1), and ninety-two SNPs (all). SNPs in LD (r2 > 0.8) were excluded (except for the 92-SNP set). Of the 262 samples, we used 200 samples (100 cases and 100 controls) in the training process (180 samples for training and 20 samples for validation) and 62 samples (43 cases and 19 controls) for testing purposes. We calculated the PRS for each jth subject by using the equation , where M is the number of SNP markers, is the natural logarithmically transformed odds ratio (OR) of the ith susceptibility SNP, and is the count of the risk alleles (0, 1, or 2) at the ith SNP in the jth individual. We performed a logistic regression analysis on the PRS that was calculated to determine case–control status [42]. We evaluated the risk prediction performance of six commonly used machine learning algorithms: support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), logistic regression (LR), light gradient boosting model (LGBM), and adaptive boosting (ADA). This evaluation was performed by using the Python Scikit-learn package [43]. To classify NSCL/P cases, we constructed four ANN models for each given set of SNPs by using the Keras package of TensorFlow [44]. Our ANN contains two dense layers followed by a rectified linear unit (ReLU). We set the number of neurons in each layer to 8, 16, 32, and 64 for the 3-, 10-, 16-, and 92-SNP models, respectively. In addition, we constructed a dense output layer with sigmoid activations to classify NSCL/P and utilized the Adam method for optimization with an initial learning rate of and a decay rate of [45]. We trained each ANN model in the 100 epochs setting and measured the binary cross-entropy loss to evaluate the model performance. At the end of the training, each set was replaced with the best weight with low validation loss and high training accuracy. Our model implemented the GA that was proposed by Tong and Schierz [25] to extract an optimal set of SNPs for classification, followed by an ensemble of ANN results trained with each optimal set. Total cycles and population size were set to 30, and each population consisted of a fixed number of SNPs. To speed up the identification of the local minima, we initialized one population with a set consisting of the most significant SNPs that were found in the association analysis. The goodness-of-fit of the GA was calculated by adding the training loss and the validation loss. For each of the three settings (three, ten, and sixteen SNPs), we created six sets of SNPs, which consisted of five sets from GA and one set from the association analysis. The six SNP sets were trained on each ANN with the same settings as described above. The final value of the ensemble prediction was the average of the prediction values of multiple neural networks (Figure 3). As evaluation metrics, we calculated the accuracy, which represents the percentage of correctly classified samples, and the area under the receiver operating characteristic curve (AUC). The performance of the ML and DL models was further evaluated using the weighted average F1-score, which balances precision and recall. To address the potential for variability in the results of the ANN models when trained on a GPU server, we repeated the training process 100 times and calculated the average and 95% confidence intervals (95% CIs) of both accuracy and AUC for each model to ensure the reproducibility of the results. We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.8 to analyze gene ontology (GO) terms to identify the central function of the SNP markers [46]. We further examined the functional relevance between candidate genes with the protein–protein interaction (PPI) network by using STRING v11 [47]. GANNE, a deep-learning-based approach for disease risk classification, has shown promise in overcoming the sample size limitations of population-based genetic association studies by utilizing genetic algorithms to select the optimal set of SNP markers. Nevertheless, due to the limited sample size in this study, it is necessary to validate the results in larger, independent Korean populations, as well as to conduct comparative analyses of the model performance across different ethnic groups. With further validation studies, this GANNE model will realize its potential in enhancing NSCL/P genetic risk predictions.

PMC10003463

Sofie Eline Tollefsen,Ole Solheim,Patricia Mjønes,Sverre Helge Torp

Meningiomas and Somatostatin Analogs: A Systematic Scoping Review on Current Insights and Future Perspectives

01-03-2023

brain tumor,meningioma,somatostatin,somatostatin receptor,somatostatin analog,octreotide,pasireotide,lanreotide,treatment,therapy

Meningioma is the most frequent brain tumor, and the incidence is ever-increasing. Though often benign and slow growth, recurrence rates are substantial and today’s surgical and radiation-based treatment are not without complications. No drugs specific for meningiomas are hitherto approved and patients with inoperable or recurrent meningioma are left with few treatment options. Somatostatin receptors are previously detected in meningiomas and may inhibit growth when stimulated by somatostatin. Hence, somatostatin analogs could provide a targeted drug therapy. The aim of this study was to compile the current insights of somatostatin analogs for patients with meningioma. This paper adheres to the PRISMA extension for Scoping Reviews. A systematic search was conducted in the search databases PubMed, Embase via Ovid, and Web of Science. Seventeen papers adhered to the inclusion and exclusion criteria, and critical appraisal was conducted. The overall quality of evidence is low, as none of the studies were randomized or controlled. Various efficacy of somatostatin analogs is reported, and adverse effects are sparse. Due to the beneficial effects reported by some studies, somatostatin analogs may offer a novel last-option treatment for severely ill-patients. Nonetheless, only a controlled study, preferably a randomized clinical trial, could clarify the efficacy of somatostatin analogs.

Meningiomas and Somatostatin Analogs: A Systematic Scoping Review on Current Insights and Future Perspectives Meningioma is the most frequent brain tumor, and the incidence is ever-increasing. Though often benign and slow growth, recurrence rates are substantial and today’s surgical and radiation-based treatment are not without complications. No drugs specific for meningiomas are hitherto approved and patients with inoperable or recurrent meningioma are left with few treatment options. Somatostatin receptors are previously detected in meningiomas and may inhibit growth when stimulated by somatostatin. Hence, somatostatin analogs could provide a targeted drug therapy. The aim of this study was to compile the current insights of somatostatin analogs for patients with meningioma. This paper adheres to the PRISMA extension for Scoping Reviews. A systematic search was conducted in the search databases PubMed, Embase via Ovid, and Web of Science. Seventeen papers adhered to the inclusion and exclusion criteria, and critical appraisal was conducted. The overall quality of evidence is low, as none of the studies were randomized or controlled. Various efficacy of somatostatin analogs is reported, and adverse effects are sparse. Due to the beneficial effects reported by some studies, somatostatin analogs may offer a novel last-option treatment for severely ill-patients. Nonetheless, only a controlled study, preferably a randomized clinical trial, could clarify the efficacy of somatostatin analogs. Meningioma is the most frequently occurring tumor in the central nervous system [1] and incidence rates are rising, presumably much due to increased use of magnetic resonance imaging (MRI) [2,3]. The tumors are most often benign and slow-growing, and patients may live with the disease for decades without noticing any symptoms [4]. According to the Central Brain Tumor Registry of the United States (CBTRUS), the incidence rates for meningiomas is 9.51 per 100,000 population [5]. However, based on incidental findings after MRI scans, meningiomas may have a suggested prevalence of 1% in the adult population [2]. Meningiomas are classified according to the Central Nervous System World Health Organization (CNS WHO) 2021 classification, which is the first edition to also include diagnostic molecular pathology [6]. There are 15 subtypes of meningiomas and three CNS WHO grades, with benign CNS WHO grade 1 being the most frequent, accounting for 80.1% of all meningiomas [5,6]. Surgery is the primary treatment for most patients suffering from growing or symptomatic meningioma [7]. However, tumors involving important neurovascular structures, engulfing cranial nerves, exhibiting extensive intraosseous growth, or widespread or multifocal dural involvement can be difficult to resect [8,9], and severe complications may occur [10]. Radiotherapy can be an attractive alternative with good tumor control rates for smaller tumors, although complications can be seen [3,4,10,11]. Due to the increase in incidental findings of small asymptomatic meningiomas, active surveillance is increasingly used for these patients [10]. Despite often benign histology, recurrence rates after treatment are still substantial, not at least in CNS WHO grade 2 and 3 meningiomas [10,12]. As no drugs specific for meningiomas are approved by the United States Food and Drug Administration (FDA), patients are left with few treatment options except reoperations, irradiation or re-irradiation in cases of recurrent or anaplastic meningiomas [13]. Accordingly, establishment of pharmaceuticals would be an important step towards improved patient care. Somatostatin, a potent inhibitor that binds to somatostatin receptors (SSTRs), contributes to the regulation of tumor growth [14]. The membrane-bound G-protein coupled SSTRs use guanosine triphosphate (GTP) to trigger intracellular pathways. This leads to inhibition of adenylyl cyclase, activation of phosphotyrosine phosphatase (PTP) and modulation of mitogen-activated protein kinase (MAPK). Following this, cell cycle arrest is induced [15,16,17,18], illustrating the potential anti-proliferative effect of SSTRs in meningioma cells. Antitumoral effect may also be generated by activation of SSTRs on normal cells, as this may induce vasoconstriction, decreased secretion of growth factors, modulation of immune cell function and inhibition of angiogenesis, providing an antitumoral effect [15,16,18]. Hence, the discovery of SSTRs in meningiomas led to prospering hope of targeted drug therapy [19,20,21]. Due to the potent effect and short half time of somatostatin, synthetic somatostatin analogs were developed for drug trials [22,23]; with octreotide, pasireotide and lanreotide as the most prominent. As of today, the European Association of Neuro-Oncology (EANO) has not provided guidelines on the use of somatostatin analogs for meningiomas [7,24], and Norwegian guidelines consider somatostatin analogs as experimental treatment [25]. In this present systematic scoping review, we sought to address what is currently known and unknown about the potential for treatment of meningiomas with somatostatin analogs. This paper adheres to the PRISMA extension for Scoping Reviews (PRISMA-ScR) [26] and searched for all relevant peer-reviewed journal papers with no restrictions regarding language or publication date. The protocol for this systematic scoping review is not published. The following three search databases were used: PubMed, Embase via Ovid, and Web of Science. Two search concepts were applied: (a) meningioma and (b) somatostatin analogs. MeSH terms, Emtree terms and a free text search were utilized. Somatostatin analogs are known by several synonyms, including somatostatin receptor agonists, and search concept (b) also contained the generic names of the most relevant somatostatin analogs, e.g., octreotide, pasireotide, lanreotide and angiopeptin. Sandostatin® is a common brand name for octreotide and were therefore included in search concept (b). Identified MeSH terms and Emtree terms were applied for all somatostatin analogs. After combining relevant search terms for each search concept using the search operator OR, the two search concepts were combined using the search operator AND. The search was last updated on 11 November 2022. See Supplementary File S1 for detailed search history. Inclusion criteria for this systematic scoping review were (1) meningioma and (2) systemic treatment with a somatostatin analog. Exclusion criteria were (i) patients < 18 years old and (ii) studies on imaging or scintigraphy alone. All secondary research was excluded, including editorials, reviews, and commentaries. In vitro studies establish the knowledge foundation for later clinical studies and were therefore not excluded. After completing the searches, all obtained records were uploaded to the reference manager EndNote X9.2. All records were screened by title and evaluated for further inclusion adherent to the inclusion and exclusion criteria. Remaining records were then screened for inclusion by abstracts. Thereafter, full text papers were accessed for all remaining records before final assessment for inclusion to this systematic scoping review. For all included in vivo studies, the following data was registered: number of patients, CNS WHO grade and/or subtype, treatment received, clinical response, radiological response, the presence of SSTRs, and adverse effects. If stated, progression-free-survival at six months (PFS-6) was contained. Regarding in vitro studies, the aim of the study and a summary of the results were retrieved. The inclusion of papers and data charting were conducted by a medical research student (SET). Critical appraisal tools are essential to assess the quality of research. For this systematic scoping review, validated checklists for critical appraisal from the Joanna Briggs Institute (JBI) of The University of Adelaide, Australia, were used. JBI has designed their checklist according to study design and the following checklist were applied: “checklist for case reports” and “checklist for quasi-experimental studies” [27]. A PRISMA flow chart describing the selection of papers is presented in Figure 1. As seen, the systematic search identified a total of 800 records, of which 319 duplicates were removed. After reviewing all records by title, an additional 341 records were excluded following the inclusion and exclusion criteria. The remaining 140 records were screened by abstract resulting in the exclusion of another 123 records. Finally, a total of 17 studies were included in this systematic scoping review. All retrieved articles were written in English. Among the 17 reviewed studies, there were five case reports [28,29,30,31,32], three retrospective case studies [33,34,35], five prospective studies [36,37,38,39,40], and four in vitro investigations [41,42,43,44]. In this systematic scoping review, the diverse effect of somatostatin analogs in the clinical treatment of meningiomas are presented. Some studies report favorable results following treatment [28,30,31,36,40], while others report no response or disease progression after treatment [34,37,39]. Further on, everolimus combined with octreotide or pasireotide were found favorable [33,35,41,42]. A total of 129 patients were included in the 13 in vivo studies, of which 97 were included in prospective studies. Of the 129 patients, 115 (89.1%) had previously been operated and 96 (74.4%) patients had undergone radiotherapy. Only three (2.3%) patients were previously untreated. Data on previous treatments were missing for nine patients. An overview of the 17 included papers is found in Table 1 and Table 2. While Graillon et al. reported an octreotide dose-dependent inhibition of cell viability in vitro [43], Koper et al. observed a significant growth in cultured meningioma cells following exposure to octreotide [44]. The same discrepancy of effect was reported in the in vivo studies. While three prospective studies and one case report found no radiological and only sparse clinical effects following octreotide treatment [29,36,37,39], two case reports described clinical remission in their two patients after treatment [30,31]. An in vitro investigation found pasireotide to be a significantly better inhibitor of cell viability, when compared to octreotide [42]. In vivo, pasireotide was reported to be well tolerated by patients, but was unsuccessful in obtaining a radiological response [38]. In this systematic scoping review, we found no in vitro studies on lanreotide. Nevertheless, one clinical case report describes a radiological response, with a decrease of tumor volume by 35%, and progression free survival for more than two years following lanreotide treatment in a patient with progressing meningioma after multiple treatments [28]. In the identified studies, various endpoints were utilized to measure response to treatment. Several studies applied progression free survival as endpoint [33,35,36,38,39]. PFS-6 ranged from 17 to 60% in the included papers, with a median of 47.2%. Radiologic response was used as endpoint in several studies [36,37,38,39]. Chamberlain et al. reported a partial radiologic response (PR) in 31% of patients, with PR defined as >50% reduction in tumor size on consecutive MRI scans at least two months apart, with no increase in the patients’ neurological symptoms or need for corticosteroids [36]. However, Johnsen et al. did not observe any radiologic response, using similar criteria as Chamberlain et al, with partial response defined as a decrease in tumor size of >50% [37]. Simó et al. used radiological partial response, defined as decrease of ≥50% in two-dimensional maximum diameters, but no radiological partial responses were observed [39]. Neither Norden et al. found a radiological response following treatment, applying the modified MacDonald criteria [38]. Graillon et al. and Furtner et al. reported tumor growth rates as their endpoint. Graillon et al. found a major decrease, defined as >50% reduction in growth rate assessed at three months in 78% of the tumors [40], while Furtner et al. only found a slight reduction in tumor growth rate following somatostatin analog treatment [34]. All included papers were evaluated for critical appraisal according to JBI checklists for case reports and quasi-experimental studies. As for the clinical quasi-experimental studies, similarity within patient cohorts is inadequate as the patients differed in factors such as CNS WHO grade, previous treatment, Karnofsky status and treating hospital. None of studies included control groups. Most studies presented multiple outcome measures, and most commonly including both survival analyses and radiological response. Incomplete follow-ups were accounted for in all papers. The absence of randomization and control groups constitute a potential bias in all included clinical studies, and evaluation of potential effects on both survival and progression free survival is difficult. For the retrospective studies, inclusion of patients and selection of treatment was conducted by the treating oncologists, and there was no clear standardization in treatment (dosage and duration), imaging protocols, image intervals, or clinical management algorithms. This may cause latent bias as several non-controlled variables were not explored in the studies. Also, assessments of progression free survival will potentially be affected by image intervals and completeness of clinical documentation. All clinical case reports have adequate descriptions of demographics, patient pathways, clinical conditions, diagnostic tests, and interventions. The post-intervention condition of the patients and any adverse effects were clearly stated. Still, classification of adverse drug reactions was not standardized. Overall, the included quasi-experimental studies were considered of low quality with high risk for biases and high risk of confounding factors. Many of the included patients had previously been unsuccessfully treated with radiotherapy, but both temporary tumor-swelling and the late growth inhibition after radiotherapy may hamper causal interference of effects of subsequent treatment. Further, quantitative image assessment in post-treatment scans can be hampered by a number of other factors, including contrast enhancing scarring or enhancing post-surgical peritumoral infarctions, or ill-defined intraosseous or intravenous growth. Also, assessing progression or response above or below a certain percentage in irregular shaped tumors with some variation in image protocols is notoriously difficult. Perhaps most important, radiological assessment was not blinded in any of the studies. Somatostatin analogs bind to SSTRs with various affinity. Octreotide is known for its higher affinity to SSTR2 and SSTR5 [45], while pasireotide favors SSTR1, SSTR3 and SSTR5 [38]. Lanreotide binds to SSTR5, but mainly to SSTR2 [46]. Even though SSTR2 is established as present in most meningiomas, the distribution of the other SSTRs differs between publications [20,21,47,48]. Hence, identification of different SSTRs within the tumor biology could help decide on the most efficient somatostatin analog and influence the treatment response. Many studies have used OctreoScan, a radiolabeled octreotide scintigraphy, to decide on the presence of SSTRs in advance to treatment. Yet, as the epitope octreotide mainly binds to SSTR2 and the distribution of other SSTRs is not mapped, OctreoScan may not be sufficient to predict treatment response [36]. Also, DOTA-TATE positron emission tomography (PET) is octreotide-based and consequently has higher affinity for SSTR2. To identify the most efficient somatostatin analog, a more detailed mapping of the SSTRs expression profile of each individual tumor may be required. This could be conducted with techniques such as immunohistochemistry. SSTRs are membrane-bound G-protein coupled receptors composed of glycoproteins with seven alpha-helical transmembrane domains. The extracellular N-terminal ensures specific binding of the ligand somatostatin, while the intracellular C-terminal transmits signals through a heterotrimeric G protein consisting of α-, β-, and γ-subunits. This triggers intracellular pathways using guanosine triphosphate (GTP), leading to inhibition of adenylyl cyclase, activation of phosphotyrosine phosphatase (PTP) and modulation of mitogen-activated protein kinase (MAPK), which induces cell cycle arrest [15,16,17,18]. Only SSTR3 may induce PTP-dependent apoptosis followed by activation of p53 and Bax, a pro-apoptotic protein [15,18]. As described, apoptosis and cell cycle arrest may be mediated directly by SSTRs being present on tumor cells, such as meningioma cells. However, effects may possibly also be achieved indirectly by SSTRs present on normal cells. This is accomplished by promotion of vasoconstriction, inhibition of angiogenesis, modulation of immune cell function and decreased secretion of growth factors [15,16,18]. The ten-year relative survival rate for non-malignant meningiomas is 83.4% with age as an important variable, according to CBTRUS. In comparison, the relative survival rate for malignant (CNS WHO grade 3) meningiomas was 60% for all patients, and only 38.5% for patients over 75+ years old [5]. Nevertheless, these numbers include all patients with meningioma in the United States of America and may not provide representative numbers for the prognosis of patients with treatment-refractory meningiomas. To evaluate the efficacy of new drugs, one first must decide on the desired treatment response. Kaley et al recommend benchmarks of PFS-6 of 29% for CNS WHO grade 1 meningiomas and PFS-6 of 26% for CNS WHO grade 2 and 3 meningiomas in clinical trials. These benchmarks are based on the weighted average of progression free survival in studies published on various systemic treatment in surgery- and radiation-refractory meningiomas [49]. Several of the included studies use PFS-6 as a measure of treatment response, and most included studies presented PFS-6 values superior to the stated benchmarks [35,36,38,39,40], yet, some still report the treatment as unsuccessful. One such paper is published by Simó et al, where the radiological partial response (RPR) is set as the primary endpoint and PFS-6 as the secondary endpoint. None of the patients had RPR and PFS-6 of 44.4% is referred to as modest. The same authors also state the challenges of the partly unknown progression of untreated meningiomas, suggesting this as a limitation for clinical research [39]. Another issue, presented by Norden et al, is the absence of larger datasets for comparison [38]. The missing consensus on endpoints troubles the comparisons between studies. Also, standardized image protocols at regular intervals are needed for true assessment of progression free survival. Although radiological response may be a useful endpoint, unsystematic imaging and odd follow-up intervals limit radiological assessment, not at least in retrospective studies. Further on, somatostatin analogs are suggested as effective in prevention of cell proliferation, but not as inducers of cell apoptosis [43]. Hence, somatostatin analogs may be effective in prevention of further tumor growth but may not induce the apoptosis necessary to reduce the existing tumor mass. This could represent a potential limitation for radiological endpoints, at least if primarily looking for radiological responses. Combination therapy with a somatostatin analog and everolimus, a mammalian target of rapamycin (mTOR) inhibitor, is described by several of the studies, both in vivo [33,35,40] and in vitro [41,42]. In vitro, octreotide and pasireotide were found to enhance the effect of everolimus on decreasing cell viability and proliferation [41,42]. Pasireotide had the most favorable effect [42]. Everolimus inhibits mTOR, which is a serine/threonine protein kinase that regulates growth through general protein biosynthesis. The mRNA translation that encodes proteins that are necessary for S-phase initiation and G1 cell-cycle progression are controlled by the mTOR pathway. As a result, inhibition of the mTOR pathway, using drugs such as everolimus, may result in cell arrest in G1 phase or a prolonged G1 phase. The mTOR pathway serve as a gatekeeper, ensuring G1 phase progression only occur under nutrient-replete conditions [50,51]. Everolimus is currently approved by the United States FDA for treatment of adult patients with progressive, non- functional and well-differentiated neuroendocrine tumors of lung or gastrointestinal origin with locally advanced, unresectable or metastatic disease [52]. As for further clinical use, combination therapy may be an option for heavily pre-treated patients with meningioma [35], and just as prosperous as Sunitinib, a multi-targeted receptor tyrosine kinase inhibitor [33]. Most of the included patients had already undergone substantial treatment for their meningioma, including surgery and/or radiation [31,35,39]. Hence, their meningioma may be defined as treatment-refractory as the tumor does not respond to treatment. There is no consensus on how to define treatment-refractory meningiomas, and the included studies present a heterogenous group of patients in terms of variables such as age, prior treatments, time since treatments, and comorbidity. As a result, and without adequate control groups, the efficacy of somatostatin analogs might prove difficult to evaluate. As mentioned, responses may not be expected since somatostatin analogs do not induce apoptosis. Thus, slowing or halting growth may perhaps be what we can hope for. Prior treatments could be confounding factors when evaluating both treatment responses and life expectancy following treatment with somatostatin analogs. Further on, several studies only included patients with a Karnofsky status above a pre-decided limit. Patients with higher Karnofsky status may have an overall better ability to tolerate treatment with somatostatin analogs and, hence, also suffer from less adverse effects. On the contrary, other studies only included terminally ill patients with short life expectancy. Both situations may result in selection bias potentially limiting the external validity of results. Any co-medication is poorly described in most studies and could influence clinical results. For instance, patients included in the study conducted by Chamberlain et al could receive dexamethasone, a glucocorticoid, for control of any neurologic symptoms [36]. The duration of treatment with somatostatin analogs is another unexplored factor. For pituitary macroadenomas causing acromegaly, six months of treatment result in treatment responses in approximately 2/3 [53], but optimal treatment algorithms may be very different in meningiomas. Also, somatostatin analog treatment has so far been used experimentally in treatment-refractory tumors. To be remembered, other effective and established treatments have failed in this situation and expecting a response to drugs in this treatment-refractory state may be unfair or at least less likely. Efficacy could potentially be easier to detect in treatment naïve settings. As the incidence of incidental asymptomatic meningiomas increase, active surveillance, also known as “wait and see”-strategies, is increasingly used for these patients, as treatment, such as surgery, may at times impose more severe complications than the tumor itself [3,10]. Still, the IMPASSE study found stereotactic radiosurgery superior to active surveillance in offering tumor control without risking short term neurological deficits in asymptomatic patients [3]. As a supplement to active surveillance or stereotactic radiosurgery, the potential anti-proliferative effect of somatostatin analogs might be exploited in prevention of further tumor growth. Side effects of octreotide are described as modest or absent in the included studies. The most frequently reported side effects were abdominal pain and diarrhea [29,37,39,40]. This might be explained by the regulatory role of somatostatin in the endo- and exocrine pancreas, and the gastrointestinal tract. Somatostatin are synthesized and released by nerve cells and endocrine cells in pancreas and the gastrointestinal tract, where the peptide acts paracrine, autocrine or neuronal to inhibit smooth-muscle contractility, glandular secretion, absorption of nutrients, neurotransmission and activated immune cells [54]. Despite often continuous treatment, most symptoms are resolved spontaneously within two weeks as normal organs rapidly adjust their SSTR2 levels and hereby prevent side effects [23,54]. Yet, one case report described autoimmune mediated focal demyelination after treatment with octreotide [32]. Still, octreotide is known as well-tolerated for other diseases, such as acromegaly and gastroenteropancreatic neuroendocrine tumors [23]. In recent years, theranostics utilizing SSTRs have made its marks in neuro-oncology, including meningiomas, and have recently been recognized by EANO [7]. By using peptide receptor radionuclide therapy (PRRP) with 177Lu-DOTATATE or 90Y-DOTATOC, imaging and therapy is combined, as one radionuclide emits positrons or photons suitable for imaging, while the other emits particles for anti-tumoral effect [55]. Although there are promising preliminary reports for treatment-refractory meningiomas, the efficacy of PRRP is still much unexplored [55,56,57,58,59,60,61]. Furthermore, several issues need resolving, such as the number of cycles, intervals between the cycles and the optimal activity to be administered [55]. According to the Norwegian guidelines for meningiomas, some PET-protocols have demonstrated a high sensitivity in detecting meningiomas, though, the diagnostic and clinical use is still limited. Still, the guidelines underline a potential use for PET scans in atypical and malignant meningiomas, and in relation to targeted radiotherapy [25]. Theranostics utilizing SSTRs is not mentioned in the Norwegian guidelines. Critical appraisal is the systematic evaluation of scientific research to judge its value, trustworthiness, and relevance in a specific context. This systematic scoping review used validated checklists from JBI as a tool for critical appraisal. One question from the critical appraisal checklist is the similarity of the included study participants, which is a question of definition. The studies often included all three CNS WHO grades, yet the study populations still presented with similarities of mostly having treatment-refractory meningiomas with short life-expectancy, regardless of their CNS WHO grade. To be remembered, the effect of any intervention, including the established treatment modalities may be greatly underestimated if only treatment-refractory patients are studied. All studies are non-randomized without control groups and include few patients. Non-randomization presents a clear risk for confounding bias. Retrospective and/or multicenter studies had less standardization in treatment (duration and dosage), imaging protocols and clinical management algorithms. Unexplored and non-controlled variables could present latent bias. Overall, the included studies are of low quality and have a substantial risk of bias. This is also supported by a recently published review on somatostatin analogs in treatment-refractory meningiomas [62]. There is no published randomized clinical trial (RCT) on treatment with somatostatin analogs for patients with meningioma. RCT is the gold standard for drug trials and the absence of a RCT study presents a substantial missing piece for the knowledge on somatostatin analogs in meningiomas. As for limitations of this systematic scoping review, two independent reviewers for the inclusion process could have been advisable. However, precise exclusion and inclusion criteria were set to ensure reproducibility. In conclusion, various efficacy of somatostatin analogs is reported by the included studies. None of the studies are randomized or controlled, and the overall quality of evidence is low. Further, the lack of standardized endpoints, imaging protocols and heterogenous case selection, and variation in drugs and doses limit the comparison of results across studies. In any case, the reported side effects of somatostatin analogs are sparse and well-known from other patient groups. Given the possible effect observed in some studies, somatostatin analogs may present a safe last-option treatment in severely ill patients with treatment-refractory meningiomas. However, only a properly controlled study, preferably a RCT study could clarify the efficacy on somatostatin analogs. Also, detection of potential treatment effects may perhaps be easier if done in a treatment-naïve and not a treatment-refractory clinical setting.

PMC10003465

Tadeja Kuret,Mateja Erdani Kreft,Rok Romih,Peter Veranič

Cannabidiol as a Promising Therapeutic Option in IC/BPS: In Vitro Evaluation of Its Protective Effects against Inflammation and Oxidative Stress

06-03-2023

interstitial cystitis,bladder pain syndrome,cannabidiol,urothelial cells,inflammation,oxidative stress,PPARγ/Nrf2/NFκB signaling pathways

Several animal studies have described the potential effect of cannabidiol (CBD) in alleviating the symptoms of interstitial cystitis/bladder pain syndrome (IC/BPS), a chronic inflammatory disease of the urinary bladder. However, the effects of CBD, its mechanism of action, and modulation of downstream signaling pathways in urothelial cells, the main effector cells in IC/BPS, have not been fully elucidated yet. Here, we investigated the effect of CBD against inflammation and oxidative stress in an in vitro model of IC/BPS comprised of TNFα-stimulated human urothelial cells SV-HUC1. Our results show that CBD treatment of urothelial cells significantly decreased TNFα-upregulated mRNA and protein expression of IL1α, IL8, CXCL1, and CXCL10, as well as attenuated NFκB phosphorylation. In addition, CBD treatment also diminished TNFα-driven cellular reactive oxygen species generation (ROS), by increasing the expression of the redox-sensitive transcription factor Nrf2, the antioxidant enzymes superoxide dismutase 1 and 2, and hem oxygenase 1. CBD-mediated effects in urothelial cells may occur by the activation of the PPARγ receptor since inhibition of PPARγ resulted in significantly diminished anti-inflammatory and antioxidant effects of CBD. Our observations provide new insights into the therapeutic potential of CBD through modulation of PPARγ/Nrf2/NFκB signaling pathways, which could be further exploited in the treatment of IC/BPS.

Cannabidiol as a Promising Therapeutic Option in IC/BPS: In Vitro Evaluation of Its Protective Effects against Inflammation and Oxidative Stress Several animal studies have described the potential effect of cannabidiol (CBD) in alleviating the symptoms of interstitial cystitis/bladder pain syndrome (IC/BPS), a chronic inflammatory disease of the urinary bladder. However, the effects of CBD, its mechanism of action, and modulation of downstream signaling pathways in urothelial cells, the main effector cells in IC/BPS, have not been fully elucidated yet. Here, we investigated the effect of CBD against inflammation and oxidative stress in an in vitro model of IC/BPS comprised of TNFα-stimulated human urothelial cells SV-HUC1. Our results show that CBD treatment of urothelial cells significantly decreased TNFα-upregulated mRNA and protein expression of IL1α, IL8, CXCL1, and CXCL10, as well as attenuated NFκB phosphorylation. In addition, CBD treatment also diminished TNFα-driven cellular reactive oxygen species generation (ROS), by increasing the expression of the redox-sensitive transcription factor Nrf2, the antioxidant enzymes superoxide dismutase 1 and 2, and hem oxygenase 1. CBD-mediated effects in urothelial cells may occur by the activation of the PPARγ receptor since inhibition of PPARγ resulted in significantly diminished anti-inflammatory and antioxidant effects of CBD. Our observations provide new insights into the therapeutic potential of CBD through modulation of PPARγ/Nrf2/NFκB signaling pathways, which could be further exploited in the treatment of IC/BPS. Interstitial cystitis/bladder pain syndrome (IC/BPS) is a debilitating disease of the urinary bladder characterized by chronic inflammation without bacterial infection or an identifiable pathologic cause [1]. Typical clinical symptoms and signs of IC/BPS include discomfort or pain in the bladder and surrounding pelvic region associated with increased urinary frequency, urgency, and nocturia [1,2]. Although the occurrence of IC/BPS is common (the estimated prevalence is 45–300 per 100,000 women and 8–30 per 100,000 men) [3], the majority of currently available treatments focus primarily on alleviating clinical symptoms, and to date there is no therapeutic option available that would ensure long-term beneficial effects in all patients [4,5]. IC/BPS is considered a multifactorial disease with a complex pathobiology ultimately leading to chronic inflammation, bladder fibrosis and pain [6]. Several potential mechanisms for disease development have been proposed, beginning with damage and dysfunction of urothelial cells [6], highly specialized transitional epithelial cells that line the wall of most of the urinary tract [7,8]. Damage to the urothelial cell layer increases permeability, allows urinary solutes, such as urea and potassium, to enter the bladder wall, and leads to activation of an inflammatory response with increased production of various pro-inflammatory mediators [9,10,11]. A marked inflammatory response is evident in the bladders of IC/BPS patients, as infiltration with immune cells is frequently observed [12,13,14,15] and several transcriptome studies have identified an upregulated inflammatory gene signature in bladder biopsies from patients [15,16,17,18,19]. In addition, increased levels of pro-inflammatory cytokines and chemokines have been detected in urine samples from IC/BPS patients compared to controls [20,21,22,23,24,25]. Both urothelial cell damage and a sustained inflammatory response can trigger oxidative stress and excessive production of reactive oxygen species (ROS), which can in-turn stimulate and potentiate the inflammatory response, thus initiating a self-reinforcing vicious cycle that leads to chronic inflammation [26,27]. Increased ROS production is also well documented in IC/BPS, as Jiang et al. [28,29] showed increased levels of urinary oxidative stress biomarkers (8-OHdG, 8-isoprostane), whereas Ener et al. [30] found significantly lower total antioxidant capacity in serum samples from IC/BPS patients compared to controls. For successful future treatment of patients with IC/BPS, it would be beneficial to discover and evaluate the therapeutic effects of compounds that can modulate both IC/BPS-related processes, oxidative stress, and inflammation, e.g., the cannabinoids with cannabidiol (CBD) being the main pharmacologically active phytocannabinoid most frequently used in medical treatment [31]. CBD is not psychoactive and exerts a number of beneficial pharmacological effects, including anti-inflammatory and antioxidant [32,33]. These properties, together with its low systemic toxicity, make CBD an interesting multi-target drug candidate for the treatment of IC/BPS [34]. CBD has already been shown to be effective in alleviating symptoms of IC/BPS in experimental animal models [35,36,37,38,39] and evidence suggests that CBD reduces inflammation and oxidative stress by downregulating the expression of pro-inflammatory mediators [36,40] and increasing activities of antioxidant enzymes [40] in bladder tissue. However, the exact effects of CBD specifically in urothelial cells, as well as the molecular mechanisms and downstream signaling pathways by which CBD exerts its function, remain to be elucidated. In this study, we investigated the potential of CBD to attenuate inflammation and oxidative stress damage in tumor necrosis α (TNFα)-stimulated normal human urothelial cells SV-HUC1, which is a well described model of inflammation that mimics inflammatory changes appearing in the bladders of patients with IC/BPS [41,42,43]. We analyzed the mRNA and protein expression of various pro-inflammatory cytokines and chemokines, investigated the phosphorylation of downstream transcription factor NFκB, and determined cellular ROS generation and the expression of oxidative stress sensitive transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2), as well as antioxidant enzymes, including superoxide dismutase (SOD) 1 and 2 and hem oxygenase 1 (HO1). Overall, our study provides new information about the potential effects of CBD on the attenuation of inflammation and oxidative stress and gives additional insight into the currently known mechanism of action of CBD that could be further exploited in treating IC/BPS and other related chronic inflammatory diseases. Recent reports have shown that the effects of CBD are mediated not only by the binding and activation of its best known targets, the cannabinoid receptors CB1 and CB2, but also by several other CBD-related receptors, such as the nuclear peroxisome proliferator-activated receptor gamma (PPARγ), the transient receptor potential vanniloid 1 (TRPV1) channel, the G protein-coupled receptor GPR55, and the 5-HT1A serotonin receptors [44,45,46,47] (Figure 1A). To select the most promising CBD targets for further investigation, we first searched a publicly available transcriptomic database of urothelial cells (accession number GSE2025769) and discovered that the expression of CB1, CB2, TRPV1, and PPARγ, but not GPR55 and 5-HTA1 receptors was reported [48]. Next, we therefore focused only on these four receptors (normalized counts higher than zero) and confirmed that their mRNA and protein levels (except for TRPV1) could be detected by qPCR and Western blot in SV-HUC1 cells (Figure 1B,C). mRNA and protein expression of PPARγ was significantly higher compared to the expression of other CBD-related receptors tested (Figure 1B,C). Based on our results showing higher protein expression of CB2 and PPARγ receptors compared to CB1 in urothelial cells (Figure 1C) and results from previous studies [37,38], identifying the CB2, but not CB1, receptor as a promising target to reduce symptoms of experimental cystitis and bladder inflammation in animal models, we speculated that CB2 and/or PPARγ are the receptors most probably targeted by CBD in SV-HUC1 cells. To investigate this further, we evaluated the biological effects of GP1a, a specific CB2 receptor agonist, in addition to CBD. First, we performed a viability assay with increasing concentrations of tested compounds and incubation periods of 24 and 72 h to select the most optimal concentration of CBD and GP1a and incubation time. We confirmed that DMSO, used to prepare stock solutions of CBD and GP1a, had no significant effect on the viability of SV-HUC1 cells (Supplemental Figure S1). After 24 h of treatment, sensitivity to CBD (Figure 2A) and GP1a (Figure 2B) was similar in the SV-HUC1 cell line, with IC50 values of 18.93 µM and 16.68 µM, respectively. There was no statistical difference in IC50 value obtained in SV-HUC1 cells after 24 h or 72 h exposure to GP1a (p = 0.204). However, the IC50 value obtained after 72 h of exposure to CBD was significantly lower compared to 24 h exposure (p = 0.0041). Based on these results, we treated SV-HUC1 cells with concentrations of CBD and GP1a lower than their IC50 values for 24 h in our further experiments. Previous studies have observed anti-inflammatory effects of CBD in bladder tissues of animal models with induced IC/BPS [35]. However, how CBD affects the inflammatory response of urothelial cells has not yet been investigated. Here, we focused on measuring the most promising pro-inflammatory mediators previously reported to be significantly upregulated in an in vitro model of IC/BPS [48] and repeatedly found to be elevated in bladders [15,16,17,18,19] and urine samples from IC/BPS patients [20,21,22,23,24,25]. mRNA and protein levels of selected pro-inflammatory mediators were measured in SV-HUC1 treated simultaneously with TNFα (20 ng/mL) and CBD (5 µM) or GP1a (5 µM) for 24 h and compared with levels determined in cells treated with TNFα alone or untreated cells. Our results show that CBD was able to significantly downregulate TNFα-upregulated mRNA expression of inflammatory cytokines IL8, IL1α, and IL6, as well as chemokines CXCL1 and CXCL10, but no effect was observed on serum amyloid A1 (SAA1) mRNA expression (Figure 3A). In contrast, GP1a, a selective CB2 agonist, was able to significantly downregulate only the mRNA expression of IL8 and CXCL1 (Figure 1A). Additionally, CBD significantly decreased TNFα-driven protein release of IL8, IL1α, and CXCL1. Lower protein levels of CXCL10 were also observed after treatment with CBD and TNFα in comparison to TNFα alone, but significance was not reached. GP1a significantly attenuated the TNFα-stimulated protein release of IL8 and CXCL1 (Figure 3B). Our findings showing that simultaneous treatment with TNFα and CBD significantly attenuated IL8 release compared to TNFα alone were also confirmed using an additional urothelial cell line RT4 (Supplemental Figure S2). To determine the potential mechanism by which CBD and GP1a may confer the observed anti-inflammatory effects, we next investigated the phosphorylation of NFκB, a known signaling pathway downstream of TNFα-stimulation [49]. In the absence of stimuli, NFκB is associated with IκBα, and therefore not activated. TNFα causes the degradation of IκBα and enables the activation of NFκB through phosphorylation [50]. In our model, we observed increased phosphorylation of the NFκB p65 subunit stimulated by TNFα, whereas CBD was able to significantly reduce this TNFα-mediated effect (Figure 3C). The relative protein expression of phosphorylated NFκB p65 subunit was normalized to the levels of unphosphorylated p65 (Figure 3C), as well as GAPDH (Supplemental Figure S3), showing the same statistical differences. No significant effect on NFκB phosphorylation was observed in the presence of GP1a (Figure 3C). Several studies suggest that inflammation leads to increased production of ROS [27] and that CBD can protect bladder tissue from oxidative stress in experimental animal models of IC/BPS by increasing the expression and activity of antioxidant enzymes [40]. Hence, we were interested to determine whether this is also true in human urothelial cells in vitro. TNFα stimulation increased ROS production in SV-HUC1 cells, as determined by the DCFDA assay kit and fluorescence microscopy, compared to untreated cells, and this could be attenuated by concomitant treatment with CBD, but not with GP1a (Figure 4A). We next focused on possible molecular mechanisms that could be responsible for this CBD-mediated effect. Nrf2 is a key cellular oxidative stress sensor that can induce transcription of antioxidant genes and thus protect cells from oxidative stress [51]. Our results show that TNFα stimulation decreased the expression of Nrf2 and SOD1 but increased the expression of COX2 compared to untreated cells. Simultaneous treatment with CBD and TNFα increased the expression of Nrf2 and the antioxidant genes SOD1, SOD2, and HO1, as well as decreased the expression of COX2 compared to TNFα-treated cells (Figure 4B,C). No significant effects of TNFα or CBD were observed for the mRNA expression of other oxidative stress-related genes, including NQO1 and KEAP1 (Supplemental Figure S4). Since our results consistently showed that CBD is capable of eliciting more prominent anti-inflammatory and antioxidant effects compared to GP1a, a selective CB2 receptor agonist, we speculated that the PPARγ receptor, which is one of the CBD-related receptors most highly expressed in SV-HUC1 cells (Figure 1B,C), might be involved in the observed effects. We first determined the expression of PPARγ in SV-HUC1 cells, treated with TNFα and/or TNFα in combination with CBD or GP1a and/or CBD and GP1a alone. Our qPCR analysis showed a slight, although not significant, upregulation of PPARγ mRNA expression in SV-HUC1 cells in the presence of CBD, whereas no difference was observed when cells were exposed to TNFα or GP1a compared to untreated cells (Figure 5A). To determine whether the observed CBD effects were mediated by PPARγ, we treated SV-HUC1 cells with GW9662, a selective PPARγ antagonist, for 2 h prior to treatment with CBD and TNFα. The CBD-mediated anti-inflammatory effects were almost completely abolished when the PPARγ receptor was inhibited, resulting in significantly increased protein release of IL8 and CXCL1 (Figure 5B) compared to CBD treatment without PPARγ inhibition. In contrast, no effect of GW9662 on protein levels of IL8 and CXCL1 was observed when cells were treated with GP1a (Supplemental Figure S5), indicating a specific inhibitory effect on PPARγ. Moreover, pretreatment with the PPARγ antagonist reversed the antioxidant effect of CBD, resulting in the increased formation of ROS (Figure 5D) compared to CBD treatment without GW9662 preincubation. Overall, our results show that CBD suppresses pro-inflammatory and oxidative stress-related signaling in TNFα-stimulated urothelial cells through activation of the PPARγ receptor, which has been shown to directly interact with the p65 subunit of NFκB [52,53] and regulate Nrf2 transcription factor expression [53,54]. Pharmacologically active plant compounds, including CBD, show promising but underexplored potential in the prevention and treatment of chronic inflammatory diseases. CBD is nonpsychotropic and, due to its anti-inflammatory and antioxidant properties, may represent a prototype for future drug development for those human diseases in which both persistent inflammation and oxidative stress play key roles in their development and progression [55]. One of these diseases is IC/BPS, a multifactorial inflammatory disease of the urinary bladder, for which no safe, and effective therapeutic approach currently exists [56]. Several studies have already investigated the use of CBD in experimental animal models of IC/BPS, demonstrating a significant reduction in pain severity and inflammation, increased activity of the antioxidant defense mechanism, and reduced bladder damage [37,38,39,40]. However, very few data are available on the protective effects and mechanism of action in urothelial cells, the main effector cells in IC/BPS pathobiology [57]. CBD exerts its pharmacological function by binding and activating its receptors. The most well-described are the cannabinoid receptors CB1 and CB2 [58]. However, CBD has also been shown to act on a variety of other receptors, including but not limited to PPARγ [59] and TRPV1 [60]. The expression of functional CB1 and CB2 receptors has been demonstrated in normal human [61,62], rat, and mouse bladder urothelium [62], as well as in the normal human urothelial cell lines HCV29 and UROtsa [63] and the transformed RT4 cell line [64], whereas no reports to date exist regarding the expression of CBD-related receptors in normal urothelial cells SV-HUC1, which are often used as an in vitro model of IC/BPS [35,41,42,43]. We show that SV-HUC1 cells express CB1, CB2, and PPARγ receptors, but PPARγ expression was significantly higher compared to CB1 and CB2 expression (Figure 1). PPARγ is expressed in the healthy human urothelium, especially in the superficial layer [65] and plays a critical role in inducing terminal differentiation of urothelial cells, by upregulating cytokeratins CK13 and CK20, tight junction-associated claudin 3, and uroplakins UPK1a and UPK2 [66,67,68]. Since terminally differentiated urothelial cells are absent or present only in limited numbers in the bladders of IC/BPS patients due to urothelial denudation [57] and PPARγ is also importantly involved in regulation of inflammatory response to urinary tract infection [69], we suggest that it might play an important, but not yet fully investigated, role in sustained inflammation, characteristic for IC/BPS. Based on results from other studies, showing that CB2, but not CB1, activation is involved in attenuation of bladder inflammation and the severity of experimental cystitis [37,38], we speculated that CB2 and PPARγ are the most probable targets of CBD in SV-HUC1 cells. Therefore, we examined the biological effects of GP1a, a selective CB2 receptor agonist, in addition to CBD. The purpose of including GP1a was to determine whether CBD primarily binds and activates the CB2 or PPARγ receptor in urothelial cells. We discovered that both tested compounds were able to modulate inflammation in TNFα-stimulated SV-HUC1 cells, with significant attenuation of protein release of IL1α, IL8, and CXCL1, after CBD treatment. These results confirm a previous study on IC/BPS, which showed decreased expression of IL1α and IL8 in mouse bladders after CB2 receptor activation [36]. The suppressive in vitro inhibitory effects of CBD on the production and release of IL1, IL8, and CXCL1 have also been previously shown in other pre-clinical in vitro inflammatory models using various cell types, including monocytes [70], macrophages [71], epithelial cells, and fibroblasts [72,73], stimulated with LPS or TNFα. A previous study showed that CBD has a similar anti-inflammatory effect to dexamethasone in macrophages by attenuating the LPS-induced production of NO, IL6, and TNFα through inhibition of NFκB p65 phosphorylation [74]. Since the molecular mechanism underlying the observed anti-inflammatory effects of CBD in urothelial cells has never been studied before, we next investigated the activation of the transcription factor NFκB, which plays a central role in chronic inflammatory diseases characterized mainly by an inflammatory and innate immune response, including IC/BPS [75,76,77,78]. We show that CBD suppresses the phosphorylation of the p65 subunit of NFκB, promoted by TNFα stimulation, (Figure 3). Our results are in line with previous studies that identified NFκB as a key transcription factor affected by CBD, particularly in neuroinflammatory diseases [79,80]. Similarly, CBD inhibited NFκB phosphorylation in UV-irradiated skin keratinocytes [81], LPS-stimulated RAW 264.7 macrophages [74], as well as in mouse models of endometriosis [82] and alcoholic fatty liver disease [83]. Overall, our data suggest that CBD has potent immunosuppressive effects on key transcription factors and inflammatory mediators that are major constituents and perpetuators of the immune response in IC/BPS. Given that the production of ROS is central to the progression of many inflammatory diseases [27] and has already been identified as an important underlying feature in IC/BPS pathobiology [28,84,85], we herein evaluated the effects of TNFα on the production of ROS and how this is affected by concomitant treatment with CBD. The production and maintenance of controlled levels of intracellular ROS are critical for cells to perform a number of physiological functions, including maintenance of redox homeostasis, cell cycle signaling, and hormone production [86]. When this homeostasis is disrupted, either by the overproduction of ROS or an inefficient ROS scavenging system, it leads to oxidative stress and eventually cell death and tissue destruction [87]. First, our study confirmed that TNFα stimulates the production of ROS (Figure 4). This is a well-documented effect that has been observed in various TNFα-stimulated cell types, including endothelial cells [88,89], epithelial cells [90,91,92], hepatic cells [93], fibroblasts [94], and cardiac myocytes [95]. On the other hand, we show that CBD was able to significantly attenuate these TNFα-mediated effects (Figure 4). CBD has previously been shown to have considerable antioxidant effects in a variety of tissue types and cell models, such as keratinocytes [81,96], endothelium [97,98], and microglia [99], mainly by increasing the expression and activity of the redox-sensitive transcription factor Nrf2, which was also shown in our study (Figure 4). On the other hand, pro-oxidant capacity of CBD has also been reported, depending on the cell model, concentration of CBD and time of incubation [87]. For example, CBD was shown to increase ROS production in human monocytes [100], breast cancer cells [101], and glioma cells [102]. In the present study, the possible differences in anti-inflammatory and antioxidant effects of CBD that would depend on its dose or time of incubation or CBD were not evaluated. This should be studied in the future, implementing different in vitro models, using various urothelial cell lines or animal models with experimentally induced IC/BPS in order to draw more prominent conclusions and justify the use of CBD in a clinical trial for patients with IC/BPS. Nrf2 was recently identified as one of the contributors to IC/BPS by Ni et al. [85]. They showed that nrf2 knockout mice with an experimentally induced cystitis developed more severe symptoms of IC/BPS and bladder injury with structural destruction of the urothelium compared to wild type mice [85]. In addition, D’Amico et al. [94] have shown that the use of bioactive olive oil compounds to treat mice with induced cystitis reduces bladder damage and oxidative stress by upregulating the Nrf2/HO1 pathway, restoring levels of antioxidant enzymes, and reducing lipid myeloperoxidation in the bladders [103]. Nrf2 binds to antioxidant response elements (AREs) to orchestrate the expression of antioxidant enzymes, including SOD and HO1, to promote a reduction in ROS [51]. In addition to Nrf2, CBD has also been shown to increase the expression of SOD and HO1 in keratinocytes [96], adipose tissue-derived mesenchymal stem cells [104], neuroblastoma cells [105], and smooth muscle cells [106]. A previous study not only showed increased expression and activity of phosphorylated Nrf2, but also increased expression and activity of various antioxidant enzymes, including SOD, following CBD treatment in the keratinocytes of control rats as well as in keratinocytes from skin exposed to both UVA and UVB radiation [80]. All of this is also evident in our study, in which CBD increased mRNA levels of the antioxidant genes SOD1, SOD2, and HO1 in urothelial cells (Figure 4), presumably through activation of Nrf2. However, to confirm our findings, protein levels as well as the activity of antioxidant enzymes should be measured, along with analysis of phosphorylation and nuclear translocation of Nrf2 and/or using Nrf2 knockdown cell lines. Numerous data suggest that HO1 has diverse antioxidant and anti-inflammatory abilities, making HO1 inducers such as CBD promising therapeutic agents [107]. Interestingly, Nrf2 and NFκB pathways co-regulate cellular responses to oxidative stress and inflammation [108]. Pharmacological and genetic studies suggest that there is a functional interaction between these two important signaling pathways. The absence of Nrf2 can enhance NFκB activity, leading to increased cytokine production, whereas NFκB can modulate Nrf2 transcription and activity, with both positive and negative effects on target gene expression. The Nrf2-NFκB crosstalk enables fine-tuning of dynamic responses to different environmental stimuli [109,110]. Therefore, it could be suggested that CBD-mediated alterations in Nrf2/NFκB pathways are one of the key points in modulating intracellular redox homeostasis and determining cellular response under oxidative stress and associated chronic inflammation [111]. Finally, we show that the effects of CBD on human urothelial cells are probably not, or are only slightly CB2 receptor-dependent, because the effects of GP1a, a selective CB2 agonist, were not as apparent as the effects of CBD. Instead, PPARγ receptor was highly expressed in unstimulated, as well as TNFα-stimulated SV-HUC1 cells with slight upregulation in the presence of CBD. We proved that inhibition of PPARγ resulted in reduced anti-inflammatory and antioxidant effects of CBD (Figure 5). CBD is an agonist of PPARγ [53], which has been shown to regulate NFκB signaling, either by binding directly to NFκB, which prevents its interaction with promoter regions of target genes, or alternately, by binding to the promoter region of NFκB target genes to prevent their activation [32]. While the direct mechanism by which PPARγ controls NFκB in the urothelium is unclear, current evidence suggest that PPARγ is involved in the modulation of inflammation by regulating the expression of NKκB p65 subunit after urinary tract infection, which leads to inhibition of pro-inflammatory gene expression such as COX2, IL1, and IL8 [52,69], which was also shown in this study. In addition, PPARγ also cooperates with Nrf2 by binding to the specific elements in the promoter region of Nrf2 as well as the genes it regulates, including HO1 and SOD [32,112,113]. In addition, CBD can stimulate the production and activity of the endocannabinoids anandamide and 2-arachidonoyl-glycerol, which are also PPARγ agonists, further contributing to the attenuation of inflammation and ROS generation [114]. Our study has its limitations. First, the majority of our conclusions were drawn after obtaining results from only one urothelial cell line (SV-HUC1), and a second cell line should be employed for confirmation in the future studies. Second, to validate our findings regarding the roles of the PPARγ receptor and the Nrf2 transcription factor in CBD-mediated effects, future studies should implement a PPARγ/Nrf2 knockdown cell line or a PPARγ/Nrf2 knockdown mouse model with induced IC/BPS. Third, the expression of antioxidant enzymes (SOD1, SOD2, and HO1) was only determined on mRNA but not on protein levels. To confirm that the effects of CBD are indeed mediated through increased activity of the antioxidant defense mechanism, the protein levels as well as enzymatic activity should be determined in future studies. In addition, we determined the activation of NFkB only by measuring the protein levels of the phosphorylated form of the p65 subunit. However, to confirm its activation, its translocation to the nucleus should also be determined. To the best of our knowledge, our study provides the first in vitro characterization of CBD-mediated anti-inflammatory and antioxidant effects in human urothelial cells after inflammatory challenge with TNFα and gives additional insight into the currently known mechanism of action of CBD. CBD might exhibit anti-inflammatory and antioxidant effects by either directly or indirectly modulating the PPARγ-NFκB-Nrf2 signaling axes in urothelial cells, which may be important for breaking the vicious and self-reinforcing cycle of oxidative stress and inflammation in IC/BPS. Given the great interest in the identification of natural compounds for the prevention and/or progression of inflammatory diseases, the results of the present study may offer novel perspectives for development of an optimal therapeutic approach in IC/BPS and other chronic inflammatory diseases. Human normal urothelial cells SV-HUC1 (CRL-9520, ATCC, Manassas, VA, USA) were grown in 75 cm2 cell culture flasks in basal media consisting of equal parts of advanced Dulbecco’s modified Eagle’s medium (A-DMEM) (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) and F12 (HAM) (Sigma Aldrich, St. Louis, MO, USA), supplemented with 5% fetal bovine serum (FBS) and 4 mM GlutaMAX (both Gibco, Thermo Fisher Scientific, Waltham, MA, USA). Cells repeatedly tested negative for mycoplasma infection using MycoAlert mycoplasma detection kit (Lonza, Basel, Switzerland). For the experiments, SV-HUC1 cells were seeded into appropriate plates/chambers at a seeding density of 3 × 104 cells/cm2 and grown until reaching 70–80% confluency (approximately 3–4 days) before performing experiments. All experiments were performed in serum-free basal media. Human recombinant TNFα was purchased from Cayman Chemicals, USA, reconstituted in sterile PBS to a stock concentration of 25 mg/mL, aliquoted and stored at −80 °C. Working concentration of 20 ng/mL was prepared in serum-free cell culture media. CBD, CB2 receptor agonist GP1a, and selective PPARγ antagonist GW966 were purchased from Tocris, Bio-Techne Ltd., Abingdon, UK, reconstituted in DMSO to a stock concentration of 25 mM (CBD and GP1a) or 10 mM (GW9662), aliquoted and stored at −20 °C (CBD) or room temperature (RT; GP1a, GW9662). Working concentrations were prepared in serum-free culture media. Final concentrations used in experiments were 5 µM for CBD and GP1a and 20 µM for GW9662. To mimic a proinflammatory environment, cells were treated with 20 ng/mL human recombinant TNFα (Cayman Chemicals, Ann Arbor, MI, USA) for 24 h in serum-free basal media, as previously described [48]. Untreated cells grown in serum-free basal media served as controls. To evaluate the effect of CBD and GP1a, cells were treated simultaneously with TNFα (20 ng/mL) and CBD (5 µM) or GP1a (5 µM) or with CBD (5 µM) or GP1a (5 µM) alone for 24 h in serum free media, unless otherwise stated. To assess the role of PPARγ receptor in CBD-mediated effects, cells were pre-treated with PPARγ inhibitor GW9662 (20 µM) for 2 h followed by the addition of TNFα (20 ng/mL) in combination with CBD (5 µM) for another 24 h. To evaluate the effect of DMSO in which stock solutions of CBD, GP1a, and GW9662 were prepared, cells were treated with 0.02% DMSO, corresponding to the working concentration used in the experiments, in the presence/absence of TNFα for 24 h. For viability assays, SV-HUC1 were seeded in 96-well plates and grown until reaching 70–80% confluency. Subsequently, cells were treated with increasing concentrations of CBD or GP1a (0.5–100 µM) or DMSO (0.002–0.4%) in serum-free basal media for 24 h and 72 h with fresh cell media replacement every 24 h. Cell viability was determined using CellTiter-Glo® Luminescent Cell Viability Assay (Promega, Madison, WI, USA) following manufacturer’s instructions. Luminescent signal proportional to the amount of ATP present was subsequently measured using a microplate reader (Safire; Tecan, Mannedorf, Switzerland). A viability assay was performed in triplicate in three independent experiments. The results were expressed as percentage of luminescence signal intensity of untreated controls (set to 100). Total RNA was isolated from SV-HUC1, grown on 24-well plates, treated with/without TNFα, CBD, or GP1a for 24 h, using Quick-RNA Microprep Kit (Zymo Research, Irvine, CA, USA), according to manufacturer’s instructions with on column genomic DNA digestion. The concentration and purity of isolated RNA were assessed with a Qubit RNA Broad Range Assay Kit on Qubit Flex Fluorimeter (both Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) and NanoDropTM 1000 (Thermo Fisher Scientific), respectively. Reverse transcription of 1 μg of total RNA/sample was performed with Promega Reverse Transcription System Kit (Promega, Madison, WI, USA) following manufacturer’s instructions. qPCR analysis was performed in triplicates on LightCycler® 480 PCR System in LightCycler® 480 Multiwell Plates 384 (both Roche, Basel, Switzerland), using self-designed primers (Integrated DNA Technologies, Coralville, IA, USA) and 5× HOT FIREPol EvaGreen qPCR Mix Plus (Solis BioDyne, Tartu, Estonia). Sequences of primers used for qPCR are listed in Supplemental Table S1. Expression of GAPDH was used as endogenous control to normalize the data. Data were analyzed with the comparative 2−∆∆Ct method and presented as log2fold change of TNFα-, CBD-, and GP1a-treated cells vs. untreated controls (set to 0). The results showing differences in CBD-related receptor expression in SV-HUC1 cells were analyzed with the comparative Ct method relative to the expression of endogenous control (GAPDH) and presented as negative ∆Ct between the Ct of gene of interest and the Ct of endogenous control. The supernatants of SV-HUC1 cells, seeded in 12- or 24-well plates and treated with/without TNFα, CBD, GP1a and/or PPARγ receptor inhibitor GW9662 for 24 h, were collected, centrifuged (200× g, 5 min, RT) and stored at −80 °C until analysis. Enzyme-linked immunoassays (ELISA) were performed using commercial ELISA kits in duplicates, according to manufacturer’s instructions. Absorbance at 450 nm with a reference wavelength set at 570 nm was measured on a microplate reader (Safire; Tecan, Mannedorf, Switzerland). The following ELISA kits were used in the present study: human IL8 ELISA MAX™ Deluxe Set, human IL1α MAX™ Deluxe Set, human CXCL10 ELISA MAX™ Deluxe Set (all Bio Legend, San Diego, CA, USA), human CXCL1 Duo Set Kit (R&D Systems, Minneapolis, MN, USA), and human IL6 ELISA Kit (Cayman Chemicals, Ann Arbor, MI, USA). For Western blots, SV-HUC1 cells were seeded in 12-well plates and treated with/without TNFα, CBD, and GP1a for 24 h. After the treatment, the cells were collected and lysed in ice-cold RIPA lysis buffer (Merck, Kenilworth, NJ, USA), containing a Halt™ Protease and Phosphatase Inhibitor Cocktail (Thermo Fisher Scientific, Waltham, MA, USA). Total protein levels were quantified using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific, USA). Equivalent concentrations of protein (25 µg/lane) were separated using 4–20% Novex WedgeWell Tris-Glycine Gels (Invitrogen, Carlsbad, CA, USA) and then transferred onto a nitrocellulose membrane (Sigma-Aldrich, St Louis, MO, USA). The membranes were blocked in blocking buffer consisting of 5% skim milk or 5% BSA in 0.1% Tris Buffered saline/Tween 20 (TBS-T) for 2 h at RT and incubated overnight at 4 °C with primary antibodies against CB1 receptor (diluted 1:200 in 5% BSA/TBS-T; 101500, Cayman Chemicals, Ann Arbor, MI, USA), CB2 receptor (diluted 1:500 in 5% BSA/TBS-T, 101550, Cayman Chemicals, USA), PPARγ (diluted 1:500 in 5% skim milk/TBS-T; sc7273, Santa Cruz, Dallas, TX, USA), TRPV1 (diluted 1:200 in 5% 5% BSA/TBS-T; orb13755, Biorybt, Cambridge, UK), Nrf2 (diluted 1:500 in 5% skim milk/TBS-T; D1Z9C, Cell Signaling, Danvers, MA, USA), NFκB p65 (diluted 1:1000 in 5% BSA/TBS-T; D14E12, Cell Signaling, Danvers, MA, USA), phospho NFκB p65 (diluted 1:1000 in 5% BSA/TBS-T; 93H1, Cell Signaling, Danvers, MA, USA), and GAPDH (diluted 1:1000 in 5% BSA/TBS-T; sc47724, Santa Cruz, Dallas, TX, USA). The next day, the membranes were washed with TBS-T and immediately incubated for 1 h at RT with mouse or rabbit secondary antibodies conjugated with horseradish peroxidase (diluted 1:1000 in 5% BSA/TBS-T, A4412 and A6154, Sigma-Aldrich, USA). Visualization of the protein bands was performed using the SuperSignal West Pico or Femto Chemiluminescent Substrate (Thermo Fisher Scientific, USA), and the iBright FL1500 imaging system (Thermo Fisher Scientific, USA). iBright Firmware 1.7. (Thermo Fisher Scientific, USA) was used to perform the densitometric analysis, normalized to the expression of GAPDH, used as loading control, unless otherwise stated. The ROS formation in SV-HUC1 cells was detected by utilizing the cell-permeable reagent 2′,7′-dichlorofluorescein (DCFDA), which is oxidized by ROS to form a fluorescent compound (ab113851; Abcam, Cambridge, UK), according to the manufacturer’s instructions. For quantification, 50,000 cells/well were seeded in 96-well plates and grown for 24 h. Subsequently, cells were treated with/without TNFα and/or CBD, GP1a, or PPARγ inhibitor GW9662 for 24 h, washed, incubated with 25 µM of DCFDA solution for 45 min at 37 °C in the dark, and rinsed with the dilution buffer. Fluorescence was measured at excitation wavelength of 485 nm end emission wavelength of 529 nm on a microplate reader (Safire; Tecan, Mannedorf, Switzerland). For immunofluorescence microscopy, cells were seeded in chamber slides with a removable 8 well chamber (Ibidi, Fitchburg; Dane County, WI, USA) at a seeding density of 3 × 104/cm2, grown until reaching 70–80% confluency, and treated with/without TNFα and/or CBD, GP1a, or PPARγ inhibitor GW9662 for 24 h. After treatment, cells were incubated with 25 µM of DCFDA solution for 45 min at 37 °C in the dark, and washed with the dilution buffer. The samples were imaged with a fluorescence microscope AxioImager.Z1 equipped with ApoTome (Carl Zeiss MicroImaging GmbH, München, Germany). Statistical analysis was performed using Graph Pad Prism software 8.01 (Graphpad Software Inc., San Diego, CA, USA). The normality of data distribution was investigated by the Shapiro–Wilk test. Due to the normal distribution of the data, summary statistics are expressed as means and standard deviations (SD) unless otherwise stated. Multiple group comparisons were performed by analysis of variance (normal distribution) test with adjustments for multiple comparisons using Dunn’s post hoc test. Nonlinear regression analysis of the mean cytotoxicity values for CBD and GP1a was used for IC50 determination. All tests were two-tailed and p values of <0.05 were regarded as statistically significant.

PMC10003467

Colleen McSweeney,Miranda Chen,Fengping Dong,Aswathy Sebastian,Derrick James Reynolds,Jennifer Mott,Zifei Pei,Jizhong Zou,Yongsheng Shi,Yingwei Mao

Transcriptomic Analyses of Brains of RBM8A Conditional Knockout Mice at Different Developmental Stages Reveal Conserved Signaling Pathways Contributing to Neurodevelopmental Diseases

27-02-2023

exon junction complex,nonsense-mediated decay,RBM8A,RNAseq,autism,schizophrenia

RNA-binding motif 8A (RBM8A) is a core component of the exon junction complex (EJC) that binds pre-mRNAs and regulates their splicing, transport, translation, and nonsense-mediated decay (NMD). Dysfunction in the core proteins has been linked to several detriments in brain development and neuropsychiatric diseases. To understand the functional role of Rbm8a in brain development, we have generated brain-specific Rbm8a knockout mice and used next-generation RNA-sequencing to identify differentially expressed genes (DEGs) in mice with heterozygous, conditional knockout (cKO) of Rbm8a in the brain at postnatal day 17 (P17) and at embryonic day 12. Additionally, we analyzed enriched gene clusters and signaling pathways within the DEGs. At the P17 time point, between the control and cKO mice, about 251 significant DEGs were identified. At E12, only 25 DEGs were identified in the hindbrain samples. Bioinformatics analyses have revealed many signaling pathways related to the central nervous system (CNS). When E12 and P17 results were compared, three DEGs, Spp1, Gpnmb, and Top2a, appeared to peak at different developmental time points in the Rbm8a cKO mice. Enrichment analyses suggested altered activity in pathways affecting cellular proliferation, differentiation, and survival. The results support the hypothesis that loss of Rbm8a causes decreased cellular proliferation, increased apoptosis, and early differentiation of neuronal subtypes, which may lead ultimately to an altered neuronal subtype composition in the brain.

Transcriptomic Analyses of Brains of RBM8A Conditional Knockout Mice at Different Developmental Stages Reveal Conserved Signaling Pathways Contributing to Neurodevelopmental Diseases RNA-binding motif 8A (RBM8A) is a core component of the exon junction complex (EJC) that binds pre-mRNAs and regulates their splicing, transport, translation, and nonsense-mediated decay (NMD). Dysfunction in the core proteins has been linked to several detriments in brain development and neuropsychiatric diseases. To understand the functional role of Rbm8a in brain development, we have generated brain-specific Rbm8a knockout mice and used next-generation RNA-sequencing to identify differentially expressed genes (DEGs) in mice with heterozygous, conditional knockout (cKO) of Rbm8a in the brain at postnatal day 17 (P17) and at embryonic day 12. Additionally, we analyzed enriched gene clusters and signaling pathways within the DEGs. At the P17 time point, between the control and cKO mice, about 251 significant DEGs were identified. At E12, only 25 DEGs were identified in the hindbrain samples. Bioinformatics analyses have revealed many signaling pathways related to the central nervous system (CNS). When E12 and P17 results were compared, three DEGs, Spp1, Gpnmb, and Top2a, appeared to peak at different developmental time points in the Rbm8a cKO mice. Enrichment analyses suggested altered activity in pathways affecting cellular proliferation, differentiation, and survival. The results support the hypothesis that loss of Rbm8a causes decreased cellular proliferation, increased apoptosis, and early differentiation of neuronal subtypes, which may lead ultimately to an altered neuronal subtype composition in the brain. The maturation of RNA transcripts is a tightly regulated process. Pre-mRNAs usually undergo extensive modifications including splicing, polyadenylation at the 3′ end, and addition of guanosine nucleotide cap at the 5′ end before becoming translatable, mature mRNA. Diverse groups of RNA-binding proteins (RNPs) are responsible for these different RNA modifications and control RNA splicing, transport, translation, and stability, within the cell. RBM8A, also known as Y14, is a protein that was first identified by its RNA-binding sequence [1]. RBM8A participates in an assembly of proteins known as the Exon Junction Complex (EJC), which contains the protein factors eukaryotic translation initiation factor 4A3 (EIF4A3), Magoh, cancer susceptibility candidate 3 (Casc3), and many other peripherally associated factors [2]. The EJC and its general functions are conserved across a wide range of species, with homologs being studied in different models including yeast, fly, worm, zebrafish, mouse, and human [3,4,5,6,7,8,9,10,11]. Spliceosomes assemble the EJC on spliced pre-mRNA [12]. The EJC can direct further splicing and regulate transcription or mRNA transport and translation when it accompanies the mature transcript out of the nucleus [2]. In addition to binding and modifying transcripts, the EJC has been shown to participate in Nonsense Mediated mRNA Decay (NMD), which identifies mRNA with premature termination codons (PTCs) during translation and causes the faulty mRNA to be degraded. The core components of the EJC also play their independent roles and bind to differential targets out of the EJC complex [3,13,14]. RBM8A mutations have been implicated in a variety of clinical phenotypes. Compound mutations in RBM8A have been found to cause thrombocytopenia with absent radius syndrome (TAR syndrome) [15,16,17]. This disorder is characterized primarily by low blood platelet counts (thrombocytopenia), and missing radii bones. Additional features of TAR patients include short ulnas, low megakaryocyte numbers, the axial root of the kidney, renal and heart defects, agenesis of the corpus callosum, and hypoplasia of the cerebellum [18,19,20,21]. In a case study, a TAR patient exhibited partial seizures, psychomotor retardation, and cerebral dysgenesis [20]. The genetic cause of TAR syndrome was found to have compound mutations with a microdeletion of around 200 bp in the 1q21.1 region of the genome (including RBM8A) on one inherited chromosome, and a low-frequency noncoding SNP in RBM8A on the other inherited chromosome 1 (rs139428292 or rs201779890) [15,17]. In addition to clinical phenotypes of TAR syndrome, RBM8A is also associated with various neuropsychiatric disease cases. RBM8A is located in the 1q21.1 region of the genome, which is highly associated with neuropsychiatric diseases as a result of copy number variations (CNVs) (both duplication and deletions) [22,23,24,25]. Additionally, de novo mutations in RBM8A have been associated with autism spectrum disorders (ASD) [26] and the Mayer–Rokitansky–Küster–Hauser (MRKH) syndrome (MIM 277000) [27,28]. However, how different variants of RBM8A give rise to different clinical symptoms remains unknown. To investigate the role of RBM8A in the nervous system, our lab previously demonstrated that the mouse homolog Rbm8a is crucial in regulating neural progenitor cell (NPC) populations and that genes downstream of Rbm8a expression include risk genes for intellectual disability, schizophrenia, and autism spectrum disorder [29]. Dysregulation of RBM8A leads to anxiety behaviors [30]. Consistent with its essential role in neurodevelopment, we and other groups have developed Rbm8a cKO mouse lines and showed that Rbm8a is required for the proliferation of cortical NPC and interneuron progenitors at the ganglionic eminence as well as megakaryocyte differentiation [31,32,33]. However, the underlying molecular mechanism causing these defects is still unclear. The p53 activation has been shown to mediate the cell cycle defects observed in the EJC cKO mice [33,34,35]. To further examine how the downstream molecular mechanism of Rbm8a causes abnormal development of the brain at different developmental periods, in this study, we analyze the changes in the transcriptome of mice with Rbm8a haploinsufficiency in the brain during embryonic and postnatal stages. We identified over 300 transcripts that showed significant fold changes between WT and Rbm8a cKO mice, including 34 genes with known functions in nervous system development. This provides a starting point for choosing a narrower subset of genes or cellular processes to observe in future studies. We further observed that neural transcription factors were upregulated in the early postnatal brain, accompanied by gene expression typically associated with mature neurons in the adult brain. Considering these results, we believe that Rbm8a is required to delay cell differentiation and maturation, allowing the precursor cells of the nervous system to proliferate and fully populate their organs. Our previous results indicate that RBM8A is essential for neural development, and more specifically, is a positive regulator of NPC proliferation [29]. However, these observed effects are limited to a small portion of the cortex, due to the limitations of in utero electroporation. To further probe this developmental role of RBM8A, and to examine its effects on the entirety of the nervous system, we generated a cKO mouse [31]. The mouse line contains the homozygous loxP allele, Rbm8af/f, on a C57BL/6 background (Figure 1A). The Rbm8af/f mice contain loxP sites that guide Cre recombinase to delete three exons in the Rbm8a gene (Figure 1A). To create brain-specific Rbm8a cKO mice, the Rbm8af/f mice were crossed with nestin-Cre (Nes-Cre) transgenic mice from the Jackson Laboratory, B6.Cg-Tg (Nes-Cre) 1 Kln/J, stock number 003771 [36]. The Nes-Cre mouse line has hemizygous Cre recombinase driven by a nestin promoter. Nestin has heavily biased expression in embryonic neural stem cells, allowing nervous system-specific expression of Cre at early embryonic day 10 (E10). This enabled us to examine all of the cortex, and other areas of the nervous system, and to examine how Rbm8a deletion in the brain affected mouse brain structure and behavior. Although nestin has been reported in a few cells in the heart or kidney, our study used the brain tissues for RNAseq to avoid contamination of other cells. The resulting progeny consisted of 50% Nes-Cre; Rbm8af/+ mice and 50% Rbm8af/+ mice. This indicates that the mice that are haploinsufficient for Rbm8a are born at the expected Mendelian ratio. Littermates without nestin can be used as comparative controls. As reported previously [31], the resulting Rbm8a haploinsufficient mice were significantly smaller compared to littermate controls (Figure 1B) and had microcephaly, which is a greater than 50% reduction in brain size at P17 (Figure 1C). A large, visible gap between the two cerebral hemispheres was typical of the cKO brains, in contrast to the tightly aligned hemispheres in the WT brains. Most of these Nes-cre; Rbm8af/+ pups only survived until postnatal day 20 (P20). As these mice have thin cortices, we hypothesized that they also had perturbations in the cortical layers. This could manifest in the form of thinner layers, or disorganized cortical layers (cells migrating to the wrong layer). To test this, we immunostained the coronal brain section of P17 Nes-Cre; Rbm8af/+ mice and littermate controls with deep cortical layer marker FOXP2. FOXP2 staining was revealed to be abnormal; instead of staining layers 5/6 as in the control, FOXP2 labeling was found in the middle cortex, spanning to layers 3–6 (Figure 1D). Next, we sought to determine the molecular pathways that govern Rbm8a’s role in brain development. To do this, we utilized RNAseq to determine transcriptomic changes in Rbm8a haploinsufficient mouse brains at P17. RNA was isolated from the whole brain of P17 mice (control and cKO) and converted to cDNA and sequences using the Illumina HiSeq 2500. In the P17 whole brain, 19,622 genes have quantifiable transcript readings that were plotted in a volcano plot (Figure 2A). A total of 251 DEGs show a significant false discovery rate (FDR) (q < 0.05), and 140 of them had expressional changes of twofold or more in either direction. This list of differentially expressed transcripts was then used for further analysis. To obtain an overall assessment of the features of these DEGs, we used the online ShinyGO analytic tool [37]. First, we determined that the DEGs are primarily protein-coding RNAs (98.1%) and lincRNAs (1.9%), which is significantly different from the expected transcript distribution pattern (Figure 2B). This is consistent with the fact that EJC factors have little effect on small noncoding RNAs, such as miRNA and snRNAs. Second, DEGs from the P17 RNAseq dataset are generally evenly distributed across different chromosomes (Supplemental Figure S1B). However, we identified four regions in chromosomes 11 and Y that are enriched with DEGs (FDR < 0.05) (Supplemental Figure S1A). Interestingly, DEGs have longer coding sequences, transcript, 5′ untranslated region (UTR), 3′ UTR, and higher GC contents (Figure 2C–G). However, the number of exons (Supplemental Figure S1C) and the number of transcript isoforms per coding gene (Supplemental Figure S1D) were as expected in all genes. To further examine which functions these differentially expressed transcripts mediate, we tested them in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway [38] and looked for functional clusters that were enriched for genes in our DEG dataset. Consistent with our previous findings that Rbm8a is critical for interneuron development [31], the KEGG pathway analysis revealed that three major signaling pathways are enriched: neuroactive ligand–receptor interaction, complement and coagulation cascades, and the GABAergic synapse (Figure 3). DEGs relevant to neural functions are shown in the neuroactive ligand–receptor interaction (Supplemental Figure S2) and the GABAergic synapse (Supplemental Figure S3). Particularly, GABA-A receptor subunits, such as Gabrd and Gabrq genes, are enriched in the GABAergic synapse pathway, suggesting an imbalance of excitation and inhibition (E/I) that are prevalent in patients with neurodevelopmental disorders. This characterization of DEGs helps determine potential functions that can lead to changes in neurodevelopment by RBM8A. At P17, upregulated and downregulated CNS-related DEGs were examined with the GO Enrichment Analysis tool in ShinyGO. The downregulated DEGs are significantly enriched in multiple biological processes (Figure 4A,B), including fear response, chemical synaptic transmission, neuron development, neurogenesis, and transcriptional regulation. Using a network plot in which two pathways (nodes) are connected if they share 20% (default) or more genes, we detected two major clusters (Figure 4B). One regulates behavior and the other regulates neurodevelopment, which is consistent with the neurodevelopmental phenotypes of Nes-Cre; Rbm8af/+ mice (Figure 1). When DEGs were examined in the GO cellular component analysis, which is defined as “A location, relative to cellular compartments and structures, occupied by a macromolecular machine when it carries out a molecular function” in GO term [39,40,41], they are significantly enriched in several cellular compartments, such as dendrites, vesicle lumens, and neuronal spines (Figure 4C,D), suggesting a critical role of RBM8A in synaptic transmission. Although the cellular distributions of DEGs are enriched in dendritic compartments, the GO molecular functions of these DEGs are clustered in transcriptional factors (Figure 4E,F). Among the downregulated group, two transcription factors stood out: Neuronal differentiation 1 (Neurod1) and Engrailed 2 (En2). Neurod1 is a transcription factor critical for neurodevelopment [42,43]. It promotes neuronal cell phenotypes when overexpressed in stem cells, and in neurons [44,45,46]. En2 also promotes the differentiation of neuronal subtypes [47,48,49]. With these observations, it is possible that Rbm8a is required for the activity of neural transcription factors, which allows more NPCs to remain in the progenitor pool and proliferate. Consistent with previous observations [29,31,32], if neuronal differentiation is impeded by Rbm8a, the competing process of brain development would be impaired. Next, we investigated the upregulated DEGs at P17 in the GO analysis. Intriguingly, Rbm8a cKO significantly increases genes that participate in kidney development, blood vessel development, and ion transport (Figure 5A,B). Network analysis revealed two separate biological processes that are involved in ion transport and tube morphogenesis (Figure 5B). These results suggest that Rbm8a cKO in the nervous system suppresses the expression of neural genes, yet promotes other organ development, such as the renal system. Major cellular components were identified in the plasma membrane and extracellular matrix (Figure 5C,D). Interestingly, the serotonergic synapse, platelet alpha granule, and cell surface compartment are separated from other clusters in network analysis (Figure 5D). Consistent with GO cellular component analysis, upregulated DEGs are involved in active transmembrane transporters and growth factor binding (Figure 5E,F). Among the top upregulated DEGs, transthyretin (Ttr) encodes a homo-tetrameric carrier protein to transport thyroid hormones or vitamin A in the plasma and cerebrospinal fluid [50]. Mutations in Ttr can lead to several deadly diseases such as cardiomyopathy and neuropathy, which affect autonomic, motor, and sensory systems [51]. Folate receptor 1 (Folr1) is a cell surface marker of midbrain dopaminergic neuron precursor cells and immature neurons of the same type [52]. These results further support the crucial role of RBM8A in neural and other organ development. RBM8A is primarily known for its role in RNA regulation, including NMD and splicing. Therefore, we decided to investigate whether Rbm8a cKO led to changes in alternative splicing. We used MISO to determine if any alternatively spliced transcripts are significantly changed in our RNAseq results [53]. A total of 71 alternative splicing events in 62 genes were identified, with the majority being skipped exons (Figure 6A). Interestingly, the gene list did not overlap with any DEGs, suggesting that the levels of DEGs are not regulated by AS. The genes that were alternatively spliced were identified and input into GO analysis to determine if they mediate any biological functions. Intriguingly, the alternatively spliced genes in Nes-Cre; Rbm8af/+ mice at P17 affected functional pathways mediating gliogenesis, oligodendricyte development, and translational readthrough (Figure 6B,C). Together, these analyses reveal that RBM8A could regulate multiple neural functions and processes via controlling transcript abundance and AS. Our previous study conducted RNAseq analysis on the E12 cortex of control and Nes-Cre; Rbm8af/+ mice [31]. As the Rbm8a cKO mouse also has a small hindbrain (Figure 1B), we further tested the gene expression in the E12 hindbrains using RNAseq (Figure 7, supplemental Figure S4). We were interested in whether different groups of genes would be affected by Rbm8a cKO in the different brain regions. A volcano plot was generated to display all genes that had quantifiable readings in both the WT and KO hindbrains (Figure 7A). About 28,000 genes were plotted in the graph. A total of 25 DEGs had significant q-values (<0.05), and 23 of them had expressional changes of twofold or more in either direction (Figure 7A). The heatmap for these 23 DEGs was compared between the WT and KO mice in Supplemental Figure S4. Similarly, these DEGs from E12 hindbrains are enriched in protein-coding genes (Figure 7B). Because the number of DEGs is low, they are localized in chromosomes 1, 2, 4, 5, 6, 7, 10, 11,17, X, and Y (Supplemental Figures S5 and S6A). Four enriched regions were identified in chromosomes 2, 6, and Y (Supplemental Figure S5). The only significant feature of DEGs from E12 hindbrains is the 5′ UTR length compared to the overall genome (Figure 7C). No significant changes were identified in the number of exons (Supplemental Figure S6B), or the number of isoforms per coding gene (Supplemental Figure S6C). In contrast to the P17 whole brain data, DEGs from E12 hindbrains have normal lengths in the coding sequence (Supplemental Figure S6D), transcript length (Supplemental Figure S6E), 3′UTR (Supplemental Figure S6F), and normal GC content (Supplemental Figure S6G). To further examine the functions of these DEGs, we tested them in the KEGG pathway [38]. Intriguingly, the KEGG pathway analysis revealed only one enriched major signaling pathway—the P53 pathway (Figure 7D, Supplemental Figure S7)—suggesting a defect in the P53-mediated cell death pathway during embryonic neurodevelopment. To examine the affected pathways, we further examined the DEGs from E12 hindbrain data in GO analysis. Among 25 DEGs, 8 DEGs are downregulated and no significant Biological Process is detected. We only identified some cellular components, such as translational initiation factor 2 complex and P granule (Figure 8A), and molecular function on histone H3 trimethylation (Figure 8C), in GO analyses. However, we were able to identify more enriched functions from upregulated DEGs (Figure 8C–H). Consistently, GO biological function analysis identified apoptosis, DNA damage, P53-mediated signal transduction, and epithelial cell maturation (Figure 8C,D), suggesting an increase in cell death during embryonic hindbrain. These DEGs are localized in various compartments (Figure 8E), but mainly in the two clusters centered in neuronal projection and protein kinase signaling complexes such as the TOR complex (Figure 8F). In addition to the kinase signaling pathways, GO molecular function analysis found more neural-related functions in dopamine β-mono-oxygenase activity, and opioid peptide activity (Figure 8G). These molecular functions are loosely connected in the network analysis (Figure 8H). Compared to the E12 time point, even with hindbrain and cortex DEGs combined, many more genes showed significant expressional changes at P17. However, fewer genes overlapped between the P17 whole brain and the E12 brain regions than between the two E12 regions (Figure 9). Nrgn and Anoctamin 3 (Ano3) were upregulated in the E12 cortex but in the opposite direction at P17. Ano3 is a calcium-dependent phospholipid scramblase highly expressed in the brain and skin [54]. Meanwhile, Top2a was downregulated at both E12 and P17, whereas Spp1 and Gpnmb were upregulated at both E12 and P17. These findings suggest that some downstream effects of Rbm8a cKO are temporally distinct, while others may underlie a long period of development in the CNS. In all the time points/brain regions, Fam212b was significantly changed. However, the exact pathways implicating Fam212b are not yet known. In the embryonic brain, Fam212b is expressed by rapidly proliferating NPCs, while in the postnatal brain, it is expressed in limited, immature neuronal subtypes [55]. This increase in Fam212b could indicate a larger population of proliferating NPCs, contradicting our other findings, but it could also be the product of a compensatory mechanism among a dwindling pool of NPCs. Overall, when we compared the hindbrain dataset with our E12 cortex dataset, fewer DEGs were significant at any level in the E12 hindbrain than in the cortex. Ten DEGs overlapped between those detected in the cortex and hindbrain; all of these were upregulated. Their names and functions are presented in Supplemental Table S1. Of note, six of these ten common upregulated DEGs are known to directly influence cellular proliferation. These were Cdkn1a [56], Ccng1 [57], and Phlda3 [58], which are known to slow or arrest the cell cycle. Sesn2, which protects cells from programmed death during stress [59]; Eda2r, which increases programmed cell death [60]; and Fam212b [55], which is highly expressed in rapidly proliferating NPCs in the embryonic mouse brain. In this study, three RNAseq datasets were analyzed to explore the altered transcriptome of Rbm8a cKO mice. Transcriptomes were assessed at E12 and P17, and at E12, the brain was split into cortex and hindbrain for separate sequencing. The results showed that the different brain regions and time points had many expressional changes, with little overlap between them. Therefore, loss of Rbm8a has temporally and spatially restricted effects during CNS development. At E12, in the cortex, 19 DEGs significant at q < 0.05 were known to be implicated in the CNS [31]. They affect many aspects of nervous system development ranging from cell proliferation to myelin maintenance to calcium signaling. The hindbrain at E12 shared ten upregulated DEGs with the cortex, more than half of which could modulate the rate of cell proliferation and turnover. Some of them were pro-apoptotic and some were anti-apoptotic, while others regulated the progression of the cell cycle. Based on this data alone, it is not possible to conclude whether cell populations increased or decreased. However, the small body size and microcephaly of the mice suggest that the cells were less proliferative or more prone to dying [31]. At P17, a much different set of CNS-related DEGs was identified. Significant Neurod1 and En2 upregulation at P17, as well as downregulation of several genes associated with the immature CNS, indicates that neurons were possibly reaching terminal differentiation long before the CNS should have stopped developing. There was also evidence that the distribution of cell types was abnormal in the Rbm8a cKO brains, based on the decrease in Lhx8 expression, which regulates the NPC’s decision to differentiate into a GABAergic versus a cholinergic neuron [61,62,63]. These results correlate with our previous findings that Rbm8a generally suppresses NPC differentiation. Apparently, loss of Rbm8a may also disrupt the ratios of NPCs that differentiate into each neuronal subtype. A few of the significant DEGs from E12 reappeared in the P17 cKO brains. Notably, three of them had changed significantly at both E12 and P17. Spp1 and Gpnmb were upregulated at both ages in cKO than control mice, while Fam212b was downregulated at P17 and upregulated at E12. This supports that some pathways are not continuously active, but rather are active on different timelines. Interestingly, both Spp1 and Gpnmb play important roles in microglia and macrophage during brain damage and many other pathological conditions [64,65,66,67]. Upregulation of Spp1 and Gpnmb indicates activation of microglia and neuroinflammatory responses in Rbm8a-deficient brains [68]. Their expressional changes could also be compensatory for other disruptions in the CNS. Additionally, both Spp1 and Gpnmb participate in bone and tissue remodeling [69]. Fam212b was the only DEG that is upregulated at E12 but downregulated at P17 (q < 0.05). According to previous explorative studies, Fam212b is expressed by highly proliferative NPCs, immature neurons in the postnatal developing brain, and very specific subtypes of mature neurons in the adult forebrain [55]. Unfortunately, the exact pathways that this protein participates in are unknown. Further investigation is necessary to elucidate the role of Fam212b in CNS development, and its relation to Rbm8a. Enrichment analysis showed that several pathways were affected by Rbm8a cKO in the brain. A few patterns that appeared across the three RNAseq datasets were enrichments in genes related to cellular differentiation, regulation of RNA transcription, proliferation, and cell death. Changes in differentiation pathways can result in delayed differentiation, premature differentiation, or an unbalanced distribution of cell types at maturity. Among enriched and depleted pathways, cell fates including oligodendrocytes, osteoblasts, neurons, and specific neuronal subtypes were named. Considering that several genes expected to be expressed in the adult brain were upregulated in the embryonic cortex, as well as the fact that negative regulation of photoreceptor differentiation was depleted, we hypothesized that the Rbm8a cKO mouse nervous system differentiates prematurely, resulting in the underdevelopment of nervous system tissues. Closely tied to differentiation is the renewal of progenitor cell populations, regulated by signals for cell cycle progression versus arrest, and survival versus apoptosis. In the E12 cortex, genes for the cell division process were depleted; likewise in the hindbrain, negative regulation of proliferation was increased, and neural precursor proliferation was specifically determined to be depleted. This falls in line with our previous observations that Rbm8a promotes the renewal of NPCs and inhibits the differentiation of neuronal subtypes. In the P17 brain, it appears that the nervous system gets a head start and develops quickly in Rbm8a cKO mice: neuronal development genes are enriched, and pathways pertaining to synaptic plasticity and behavior are more active. However, these could also be the results of premature differentiation of neurons. At a stage when the nervous system should still be expanding, the neurons are settling into their mature roles, approaching terminal differentiation. Furthermore, synaptic plasticity and behavior changes are observed in both juvenile and adult animals. Increased activity of these pathways is not necessarily an advantage for animals at such an early developmental stage. Intriguingly, Rbm8a cKO mice die at the postnatal stage even with another intact copy of the Rbm8a gene, which is different from human patients with 1q21 deletion or TAR syndrome who can live to adulthood. Although the mouse model can recapitulate some aspects of human disease, species variances between human and mouse models exist. This difference could be a lack of unknown compensatory mechanisms in mice. RBM8A modulates mostly protein-coding genes that likely play a large role in the observed phenotypes, but RBM8A also regulates a proportion of lincRNAs. In the future, the location of the lincRNAs should be further investigated to determine which protein-coding genes they potentially modulate. This insight may lead to clues to the overall mechanism of RBM8A’s developmental role. Taken together, the DEG analysis and GO enrichment analysis support our hypothesis that RBM8A maintains renewal of the neural precursor population and inhibits differentiation. Additionally, we uncovered specific genes and pathways for further investigation that may be critical to early CNS development. Finally, our RNAseq analysis featured several genes whose functions have not been elucidated in the context of early brain development, including Spp1, Gpnmb, and Fam212b. We hope that these data will provide the lead for further studies of brain development in mice and other mammalian models. Wild-type male and female C57/BL6N mice were obtained from Taconic (Germantown, NY, USA) C57BL/6N male mice were housed 2–4 mice per cage in a room with a light/dark cycle at 12 h intervals (lights on at 7:00 am), and provided ad libitum access to food and water. All procedures on mice were reviewed and approved by The Pennsylvania State University IACUC Committee, under IACUC protocol, 44057, to Yingwei Mao. Sample preparation for RNA sequencing was done by Dr. Yingwei Mao. Eight mouse embryos at E12 were collected for RNA sequencing. Four of them were Rbm8afl/+, and the other four were Nes-Cre; Rbm8afl/+. The hindbrain and cortex regions were dissected from the rest of the brain and stored separately. Six more mice, three for each condition, were euthanized on postnatal day 17 (P17); their whole brains were collected. These three sets of brain samples were sent to the Penn State Genomics Core Facility for sequencing with the Illumina HiSeq 2500 on a paired-read protocol. A total of 20 million paired reads were run per sample, producing 40 million total reads per sample. Raw reads were processed with paired-end analysis. Three sequencing datasets were obtained, corresponding to the E12 cortex, E12 hindbrain, and P17 whole brain. The raw Illumina output was processed by the Penn State Bioinformatics Consulting Center, in collaboration with Dr. István Albert. Using TopHat (version 2.0.6), reads were aligned to the NCBI Mus musculus genome, assembly GRCm38.p6, available to the public through the NCBI Genome database. Subsequently, Cuffdiff was used to calculate the statistical significance of expressional changes. After sorting DEGs by significance, DEGs were compared between the E12 cortex and hindbrain regions, as well as between the E12 and P17 time points. We identified genes that were significant at q < 0.05 in both conditions being compared and noted whether these shared DEGs had changed in the same direction. The E12 cortex and P17 DEGs were further sorted to distinguish those pertinent to the CNS and establish targets of interest for further investigation in Rbm8a cKO animals. The CNS-related DEGs of the E12 cortex were categorized manually, based on literature reports of their known functions and expressional patterns. This was less feasible for the large number of DEGs at P17 because the analysis named all CNS-related genes it recognized from the submitted DEGs. Therefore, we instead used the Gene Ontology (GO) enrichment analysis tool to classify CNS-related genes DEGs in the P17 data. Overrepresented gene clusters and pathways were identified among significantly upregulated and downregulated DEGs using the Gene Ontology Consortium’s free online resource, GO enrichment analysis [39,40], and the ShinyGO analytic tool [37]. GO enrichment analysis groups genes by function and pathway, then estimates how many genes from each group are expected in a list of a given number of genes. If the actual number of genes from the same group greatly exceeds the expected number, then that group of genes is determined to be enriched. The software requires an input list with a sufficient number of genes to accurately identify gene cluster enrichments; we began by inputting the DEGs significant at q < 0.05. The E12 cortex and hindbrain and the P17 whole brain were analyzed individually, with inputted DEGs further separated by direction of change (upregulation or downregulation). The PANTHER Overrepresentation Test was used to recognize groups of genes within the DEGs that occurred at significantly higher or lower counts than expected, relative to all known expressional patterns in the mouse genome. For the alternative splicing analysis, all bam files created by TopHat [70] were merged into a single file using samtools (version 1.1) [71]. The total number of reads that support the individual variants associated with each of the predicted functional alternative splicing events was determined using the MISO (Mixture of Isoform) package (version 0.5.3) [53] using events annotated as of 26 June 2013. Significant differentially spliced events were determined by requiring a Bayes’ factor > 10 and Δψ > 0.2 in a comparison of control and Rbm8a cKO. Each event was required to pass the default MISO minimum read coverage thresholds.

PMC10003471

Alexander Kaiser,Gabriele Eiselt,Joachim Bechler,Otmar Huber,Martin Schmidt

WNT3a Signaling Inhibits Aromatase Expression in Breast Adipose Fibroblasts—A Possible Mechanism Supporting the Loss of Estrogen Responsiveness of Triple-Negative Breast Cancers

28-02-2023

aromatase,breast cancer,breast adipose fibroblast,Wnt signaling,LEF-1 (lymphoid enhancer binding factor 1),TCF-4 (T-cell factor 4),β-catenin,gene regulation

Estrogen-dependent breast cancers rely on a constant supply of estrogens and expression of estrogen receptors. Local biosynthesis, by aromatase in breast adipose fibroblasts (BAFs), is their most important source for estrogens. Triple-negative breast cancers (TNBC) rely on other growth-promoting signals, including those from the Wnt pathway. In this study, we explored the hypothesis that Wnt signaling alters the proliferation of BAFs, and is involved in regulation of aromatase expression in BAFs. Conditioned medium (CM) from TNBC cells and WNT3a consistently increased BAF growth, and reduced aromatase activity up to 90%, by suppression of the aromatase promoter I.3/II region. Database searches identified three putative Wnt-responsive elements (WREs) in the aromatase promoter I.3/II. In luciferase reporter gene assays, promoter I.3/II activity was inhibited by overexpression of full-length T-cell factor (TCF)-4 in 3T3-L1 preadipocytes, which served as a model for BAFs. Full-length lymphoid enhancer-binding factor (LEF)-1 increased the transcriptional activity. However, TCF-4 binding to WRE1 in the aromatase promoter, was lost after WNT3a stimulation in immunoprecipitation-based in vitro DNA-binding assays, and in chromatin immunoprecipitation (ChIP). In vitro DNA-binding assays, ChIP, and Western blotting revealed a WNT3a-dependent switch of nuclear LEF-1 isoforms towards a truncated variant, whereas β-catenin levels remained unchanged. This LEF-1 variant revealed dominant negative properties, and most likely recruited enzymes involved in heterochromatin formation. In addition, WNT3a induced the replacement of TCF-4 by the truncated LEF-1 variant, on WRE1 of the aromatase promoter I.3/II. The mechanism described here may be responsible for the loss of aromatase expression predominantly associated with TNBC. Tumors with (strong) expression of Wnt ligands actively suppress aromatase expression in BAFs. Consequently a reduced estrogen supply could favor the growth of estrogen-independent tumor cells, which consequently would make estrogen receptors dispensable. In summary, canonical Wnt signaling within (cancerous) breast tissue may be a major factor controlling local estrogen synthesis and action.

WNT3a Signaling Inhibits Aromatase Expression in Breast Adipose Fibroblasts—A Possible Mechanism Supporting the Loss of Estrogen Responsiveness of Triple-Negative Breast Cancers Estrogen-dependent breast cancers rely on a constant supply of estrogens and expression of estrogen receptors. Local biosynthesis, by aromatase in breast adipose fibroblasts (BAFs), is their most important source for estrogens. Triple-negative breast cancers (TNBC) rely on other growth-promoting signals, including those from the Wnt pathway. In this study, we explored the hypothesis that Wnt signaling alters the proliferation of BAFs, and is involved in regulation of aromatase expression in BAFs. Conditioned medium (CM) from TNBC cells and WNT3a consistently increased BAF growth, and reduced aromatase activity up to 90%, by suppression of the aromatase promoter I.3/II region. Database searches identified three putative Wnt-responsive elements (WREs) in the aromatase promoter I.3/II. In luciferase reporter gene assays, promoter I.3/II activity was inhibited by overexpression of full-length T-cell factor (TCF)-4 in 3T3-L1 preadipocytes, which served as a model for BAFs. Full-length lymphoid enhancer-binding factor (LEF)-1 increased the transcriptional activity. However, TCF-4 binding to WRE1 in the aromatase promoter, was lost after WNT3a stimulation in immunoprecipitation-based in vitro DNA-binding assays, and in chromatin immunoprecipitation (ChIP). In vitro DNA-binding assays, ChIP, and Western blotting revealed a WNT3a-dependent switch of nuclear LEF-1 isoforms towards a truncated variant, whereas β-catenin levels remained unchanged. This LEF-1 variant revealed dominant negative properties, and most likely recruited enzymes involved in heterochromatin formation. In addition, WNT3a induced the replacement of TCF-4 by the truncated LEF-1 variant, on WRE1 of the aromatase promoter I.3/II. The mechanism described here may be responsible for the loss of aromatase expression predominantly associated with TNBC. Tumors with (strong) expression of Wnt ligands actively suppress aromatase expression in BAFs. Consequently a reduced estrogen supply could favor the growth of estrogen-independent tumor cells, which consequently would make estrogen receptors dispensable. In summary, canonical Wnt signaling within (cancerous) breast tissue may be a major factor controlling local estrogen synthesis and action. In postmenopausal women, the production of estrogens is located mainly in extragonadal tissue, preferentially in breast adipose fibroblasts (BAFs) [1]. Estrogen synthesis from androgens depends on three consecutive oxidation steps, which are catalyzed by the cytochrome P-450 enzyme aromatase, encoded by the CYP19A1 gene [2,3]. Estrogens are the most important female sex hormones, but they can also act as important growth factors in breast cancers. BAFs in the desmoplastic area, in the environment of estrogen receptor (ER)-positive breast tumors, increasingly express the aromatase enzyme and synthesize estrogens [1]. Mechanistically, the expression of aromatase in BAFs, which mainly comprise preadipocytes, is regulated at the transcriptional level. Different tissue-specific aromatase promoters have been identified as regulating expression of coding exons II-X [4]. In this context, specific signaling factors from ER-positive breast cancer cells have been shown to activate aromatase promoters I.3 and II in BAFs. Thus, promoters I.3 and II are responsible for 80–90% of aromatase expression in the tumor environment [1]. Consequently, aromatase inhibition has emerged as an efficient therapy for ER-positive breast cancers [5]. On the other hand, long-term prognosis and therapeutic options are much poorer in triple-negative breast cancers (TNBC), which by definition do not express ERα and progesterone receptor (PR), and do not overexpress the receptor tyrosine-protein kinase erbB-2 (HER2). A key role in these tumors is attributed to the Wnt signaling pathway [6,7,8,9]. Wnt signaling is essential for many developmental processes, whereas deregulation of pathway-related factors contributes to oncogenesis (e.g., in colorectal cancers [10]). Nineteen different Wnt ligands induce β-catenin-dependent canonical (e.g., WNT1, WNT3A and WNT8), or β-catenin-independent noncanonical (e.g., WNT5A and WNT11), signaling [6]. In canonical signaling, high mobility group (HMG)-box transcription factors of the TCF/LEF family (TCF: T-cell factor; LEF: lymphoid enhancer factor) are the main binding partners for β-catenin in nuclear gene regulation. A high diversity of TCF/LEFs variants mediates a broad spectrum of activating and inhibitory functions. For example, promoter switching to more 3′-regions in the TCF/LEF genes results in isoforms without β-catenin binding domains (dnLEF-1, dnTCF-4) acting as dominant-negative proteins [11,12,13,14]. Active Wnt signaling is not only associated with the normal development of the mammary gland, but also with the loss of ERα, or a lack of HER2 amplification in TNBC [15,16,17]. In addition, active Wnt signaling also contributes to tumor–stroma interactions in TNBC [18]. However, there is little knowledge about the mechanism, if any, of aromatase regulation in these tumors. Interestingly, a recent study provides evidence for aromatase expression in only a limited number of TNBC [19]. Furthermore, there is evidence that canonical Wnt signaling inhibits follicle stimulating, hormone-mediated aromatase expression in primary cultures of rat granulosa cells [20]. Therefore, we set out to elucidate the potential relationship of Wnt signaling and aromatase expression in BAFs. Using conditioned media from the WNT3a-secreting TNBC cell line MDA-MB231 [18], and from WNT3a-overexpressing L-M(TK-) cells, we provide evidence for, growth stimulatory and aromatase suppressing activity of Wnt signaling in BAFs. Furthermore, we identified Wnt response elements in the breast cancer relevant aromatase promoter I.3/II region, and identified a switch in promoter occupancy from TCF-4 to a LEF-1 variant, which appears to be involved in the WNT3a induced suppression of aromatase in BAFs. Proliferation of breast adipose fibroblasts (BAFs), in response to conditioned medium (CM), was measured using the fluorescein diacetate (FDA) viability assay. In pilot experiments, a significant and dose-dependent increase in BAF growth was detectable when cells were cultured in the presence of serum-free CM from ERα-negative MDA-MB231 breast cancer cells (more than 2-fold increase at 50% CM, Figure 1A). This WNT3a-expressing cell line served as a model for TNBC [18]. In contrast, conditioned medium from the ERα-positive MCF-7 breast cancer cell line did not induce significant proliferation (Figure 1A). To clarify whether secretion of factors promoting the proliferation of BAFs is mainly a property of TNBC cells, the growth promoting activities of four TNBC cell lines, and four lines expressing various combinations of the respective receptors, were compared (Table 1). Whereas all TNBC cell line CM significantly stimulated BAF growth, the effects of CM from receptor-positive cell lines varied considerably (Figure 1B). These results are in accordance with the microscopic assessment of the cultures immediately before the FDA assay was started (Appendix A, Figure A1). When the mean effects of the subgroups were compared, TNBC cell lines solidly stimulated BAF growth over a wide range of CM concentrations, whereas the receptor-positive cell lines only marginally stimulated BAF growth (Figure 1B). We tested additional features of the cell lines for their influence on BAF proliferation: source of cell line (primary breast cancer, pleural effusion), tumor type (adenocarcinoma, invasive ductal carcinoma, ductal carcinoma), and (over)expression or mutation of cellular tumor antigen p53 (TP53). None of these classifications is associated with stronger or weaker promotion of BAF growth. To test whether Wnt signaling may contribute to the growth promoting effect of tumor cell CM, WNT3a CM, obtained from L-M(TK-)WNT3a cells, was used [24]. WNT3a was chosen because it is a prototypical ligand stimulating the canonical Wnt signaling pathway [6], and because this producer cell line provides high titers of bioactive ligand. Indeed, WNT3a CM also dose-dependently induced significant BAF proliferation, resulting in a more than 2.5-fold stimulation with 50% WNT3a CM (Figure 1C). Microscopy confirmed these findings (Appendix A, Figure A1). To verify the expression of Wnt isoforms, RNA was isolated from all cell lines after three days of media conditioning—both in the presence and absence of serum. WNT1 mRNA expression was detectable in MDA-MB468, HCC-1143, MDA-MB231, MCF-7, and T-47D cells kept in fetal bovine serum (FBS)-containing media (Appendix A, Figure A2A). WNT3A mRNA expression was detectable in all investigated cell lines in the presence of FBS (Appendix A, Figure A2B). The expression patterns of WNT1 and WNT3A were only marginally altered under serum-free conditions (Appendix A, Figure A2C,D), indicating constitutive expression of these genes in the cell lines. Correlation analysis of the BAF proliferation stimulating activity of CM with WNT gene expression yielded no positive association of WNT1 or WNT3A expression with BAF growth (Appendix A, Figure A2E,F). This indicates that both, WNT1 and WNT3a, may contribute to the growth promotion, but are not the sole factors in the CM doing this. Aromatase activity in BAFs was stimulated with forskolin, in order to mimic the tumor–stroma situation in the vicinity of breast tumors [1]. Under these conditions, the aromatase activity of BAFs was inhibited dose-dependently by MDA-MB231 CM, to less than 40% of controls (Figure 2A). WNT3a CM (50%) had no major effect on basal aromatase activity in BAFs. By contrast, it revealed a strong inhibition (90%) of forskolin stimulated aromatase activity (Figure 2B). This effect was strongly dose-dependent (Figure 2C). WNT3a CM inhibited full-length aromatase mRNA expression by up to 90% in BAFs (Figure 2D), indicating that WNT3a exerts its effect on aromatase gene expression at the transcriptional level. Furthermore, the expression levels of aromatase mRNA transcripts with 5’-ends, typical for transcription controlled by promoters I.3 or II, decreased similarly to that of the full-length aromatase gene expression level (Figure 2E,F). This means that WNT3a massively antagonizes the breast cancer relevant mechanism of aromatase induction in BAFs, here experimentally mimicked by forskolin stimulation. Canonical Wnt signaling is activated by inhibition of glycogen synthase kinase-3β (GSK-3β). Indeed, inhibition of GSK-3β by BIO (Figure 2G) or lithium chloride (Figure 2H) dose-dependently reduced aromatase activity to less than 50% and 40%, respectively. Toxic effects of the inhibitors were excluded by FDA tests. In summary, this indicates an involvement of the canonical Wnt signaling pathway, and the β-catenin/TCF transcription complex, in inhibition of aromatase expression in BAFs. The activity of the β-catenin/TCF transcription complex is modulated by multiple interaction partners associated with epigenetic regulation, including histone acetyltransferases (HATs) and histone deacetylases (HDACs) [25,26]. In this context we observed that aromatase activity in BAFs increased significantly after nonselective HDAC inhibition by panobinostat under breast cancer mimicking conditions (forskolin stimulation, Figure 2I). A less pronounced effect was seen under basal conditions (without forskolin). Therefore, HDACs must be involved in promoter I.3- and II-dependent aromatase expression. Importantly, WNT3a stimulation led to an inhibition of aromatase activity in BAFs—even in the presence of an HDAC inhibitor, i.e., in a state of de-repression of transcription (Figure 2I). Thus, both WNT3a-treatment and active HDACs, resulted in an inhibition of aromatase activity. Putative target DNA elements of (canonical) Wnt signaling in aromatase promoter I.3/II were identified in silico, by MatInspector (Genomatix, Munich, Germany) database searches, revealing three Wnt response elements (WRE1, WRE2, WRE3) up to 495 bp upstream of the promoter II transcriptional start site (Figure 3). The sequence matching best was WRE1 (position −495/−480; MatInspector score: 0.981), and is located directly downstream of an AP-1 element. WRE3 (position −346/−330) overlapped with a C/EBP1 element. Both the AP-1 and C/EBP1 elements are known to be involved in activation of the aromatase promoter I.3/II region [1]. WRE2 presents as a combination of two binding sites (position −408/−387), and is located between WREs 1 and 3. As an established model for studies on the regulation of aromatase [27], and due to their unlimited availability, murine 3T3-L1 preadipocytes were used for detailed evaluation of the putative WREs. In nuclear extracts from 3T3-L1 cells, mediators of Wnt signaling, TCF-4, LEF-1 and β-catenin were detectable by Western blotting (Figure 4A). For TCF-4, the smaller isoform (apparent MW 60 kDa) increased after WNT3a stimulation. An even more pronounced change of isoform expression during WNT3a stimulation was found for LEF-1. The larger isoform markedly decreased in intensity, whereas expression of a short variant of LEF-1 increased strikingly. To elucidate whether native LEF-1 and TCF-4 were able to bind to the putative WREs identified in the aromatase promoter I.3/II region in vitro, an immunoprecipitation-based oligonucleotide binding assay was established. In contrast to the Western blot experiments, epitopes of antibodies used for immunoprecipitation were located within the N-terminal regions, to avoid interference of antibody binding with DNA-binding. TCF-4 and LEF-1 immunoprecipitates bound all three WREs (Figure 4B–D). The specific DNA-binding was inhibited by nonfluorescent WRE competitor oligonucleotides, with the same sequences. Remarkably, WNT3a treatment inhibited specific DNA-binding of LEF-1 and TCF-4 immunoprecipitates to WRE1 and WRE2, whereas this effect was not detectable with WRE3. This indicates that, at least WREs 1 and 2 are responsive to Wnt signaling. The evidence obtained so far indicated a possible role of WRE-bound transcription factors of the TCF-4/LEF-1 family in the WNT3a-induced inhibition of transcription from the aromatase promoter I.3/II region. To analyze their role in vivo, chromatin immunoprecipitation (ChIP) experiments were performed with forskolin stimulated BAFs, in the presence or absence of WNT3a CM. The antibodies used for the immunoprecipitations were those used for Western blotting, thus allowing differentiation between the large and small variants of TCF-4 and LEF-1, respectively. Because WRE1 is almost identical to the WRE-consensus sequence (see Figure 3), primer sets for polymerase chain-reaction (PCR) were constructed, to differentiate WRE1-mediated binding of proteins from binding to the other WREs (Figure 5A). With primer set 1, TCF-4 binding to the WRE region of aromatase promoter I.3/II significantly decreased upon WNT3a stimulation (Figure 5B,C). In contrast, LEF-1 binding tended to increase under WNT3a stimulation. When the ratios of band intensities obtained for WNT3a-treated and -untreated BAFs were calculated for each antibody target examined, both the reduction in TCF-4 binding, and the increase in LEF-1 binding, triggered by WNT3a were statistically significant (Figure 5D). When transcription factor binding was analyzed analogously with primer set 2 lacking WRE1, no effect of WNT3a treatment was observed (Figure 5E,F). For β-catenin binding, no effect of WNT3a treatment was detectable, using either primer set. In summary, TCF-4 and LEF-1 bind to WREs in aromatase promoter I.3/II region in vivo. On WRE1 TCF-4 binding dominates under nonstimulated conditions, whereas LEF-1 binding dominates after WNT3a stimulation. The evidence obtained so far indicated a major role of WRE1-bound transcription factors of the TCF-4/LEF-1 family in the WNT3a-induced inhibition of transcription at the aromatase promoter I.3/II region. The functional relevance of putative WREs was analyzed further in luciferase reporter gene assays, in 3T3-L1 cells transfected with reporter constructs containing wildtype or WRE-mutated promoter sequences. Starting from the plasmid pGL3-PII-522, where luciferase expression is under the control of the aromatase promoter regions I.3 and II, constructs with individually mutated WREs were generated. These mutations were designed so as to preclude TCF/LEF-binding. Mutation in WRE1 or WRE2 increased promoter activity in WNT3a-stimulated cells, which is in agreement with a role of these WREs in transduction of the inhibitory effect of WNT3a on aromatase promoter I.3/II activity (Figure 6A). Interestingly, in the absence of WNT3a, TCF/LEF binding to WRE2 seems to significantly contribute to full forskolin-dependent activation (Figure 6A). This suggests that WNT3a stimulation might switch WRE1 and WRE2 from an activating to an inhibitory mode. Mutation of WRE3 had no effect on firefly luciferase activity. For an in-depth analysis of their roles, expression plasmids for full-length or N-terminally truncated variants of TCF-4 or LEF-1 were co-transfected with the aromatase promoter I.3/II reporter plasmids. TCF-4, or ΔN-TCF-4, overexpression resulted in significantly decreased firefly luciferase activities in forskolin stimulated cells, both without and with WNT3a treatment (Figure 6B). This inhibition was also observed, when WREs in the aromatase promoter were individually mutated (Figure 6C). In summary, the inhibitory function of TCF-4 is independent from its N-terminal β-catenin binding region, and is mediated by more than a single WRE (i.e., at least two WREs mediate inhibition by TCF-4). The ChIP experiments suggested that aromatase promoter I.3/II inhibition might be triggered by increased LEF-1 binding to WRE1. We used LEF-1 constructs, fused to the VP16 transactivation domain from Herpes simplex virus. Previous studies have shown that these constructs activate Wnt target gene transcription, independent of β-catenin [28]. In contrast to TCF-4, full-length LEF-1-VP16 overexpression induced a significant increase in aromatase promoter activity in WNT3a-treated, but not in untreated cells (Figure 6D). Deletion of the N-terminal β-catenin binding region (in the construct ΔN-LEF-1-VP16) eliminated this activating effect of LEF-1-VP16, and transformed it into an inhibitory factor, which acts independently from WNT3a-treatment. In contrast, overexpression of the ΔΔN-LEF-1-VP16 construct, with an in addition deleted context-dependent regulatory domain, increased luciferase activity (up to 400%) (Figure 6D). This construct contains the DNA-binding domain of LEF-1 fused to the transactivation domain of VP16. Taken together, this indicates that the context-dependent regulatory domain (which is present in ΔN-LEF-1 but absent in ΔΔN-LEF-1) is responsible for inhibition of reporter gene activity. The LEF-1 part of the ΔN-LEF-1 construct, therefore, should functionally resemble the lower molecular weight variant upregulated in response to Wnt3a treatment (see Figure 4A). Unlike in cases of TCF-4 overexpression, the effects of LEF-1-VP16 and ΔN-LEF-1-VP16 overexpression under WNT3a treatment depended on a single WRE. Mutation of WRE1 (almost) eliminated the stimulatory action of full-length LEF-1-VP16 on the aromatase reporter gene (Figure 6E), and it (more than) abolished the inhibitory action of ΔN-LEF-1-VP16 (Figure 6F). Taken together, WRE1 is responsible for the antagonistic actions of LEF-1 isoforms. To evaluate the effects of TCF-4 and LEF-1-VP16 overexpression on an independent reporter system, the function of both proteins was analyzed by co-transfection of 3T3-L1 preadipocytes with the TOPflash reporter vector, where multiple optimized WREs control luciferase expression. As expected, WNT3a stimulation significantly increased luciferase activity (Figure 6G,H). Co-transfection of LEF-1-VP16 massively increased WNT3a-dependent and -independent luciferase activity in transfected 3T3-L1 cells (Figure 6G), whereas TCF-4 overexpression did not further increase the luciferase activity (Figure 6H). These results indicate that, at least in the 3T3-L1 cell model, a truncated isoform of LEF-1 is the critical factor for Wnt signaling. In triple-negative breast cancers (TNBC), active Wnt signaling [15,16,17] is associated with poor prognosis [29,30]. Furthermore, Wnt signaling in neighboring adipose tissue may lead to cellular de-differentiation and stabilization of a developmental state of breast adipose fibroblasts (BAFs) [31,32]. Therefore, it is assumed that Wnt signals contribute to the desmoplastic reaction in breast cancers. In this respect, we observed that WNT3a-conditioned media induced an increased growth rate of human BAFs. Similar effects were obtained with conditioned media from all TNBC cell lines. In contrast, conditioned media from receptor-positive cell lines induced heterogenous behavior. Whereas the ER-positive MCF-7 cell line and the HER2-positive SK-BR-3 cell line had no significant effects on cell growth, the ER-positive T-47D and BT-474 cell lines stimulated the growth of BAFs. Therefore, we conclude that canonical Wnt signaling induces BAF accumulation, not solely by forced de-differentiation of adipocytes [31,32], but apparently, in addition, directly promotes BAF proliferation, which would intensify the desmoplastic reaction in the microenvironment of TNBC. Furthermore, clinical trials revealed a reduced relapse-free period in cases of stromal cell accumulation in TNBC [33], whereas stromal accumulation in ER-positive breast cancers predicted better survival [34]. Hence, the size of the stromal compartment has predictive value regarding the long-term outcome in both of these breast cancer types. The developmental mechanisms underlying the etiology of diverse breast cancer entities have been increasingly elucidated in recent years, and it has become clear that Wnt signaling is massively involved in normal mammary gland development, as well as in oncogenic dysregulation, as reviewed in, e.g., [35]. For ER-positive tumors, effective treatments are well established. On the other hand, their recognized limitations (e.g., development of endocrine resistance) lead to further optimization of therapies [36]. However, the mechanism(s) responsible for the loss of ERα (and estrogen-dependent growth) in TNBC is (are) currently not clear. These tumors rely on other signaling pathways for growth stimulation, e.g., combined Wnt and Met signaling [37]. In addition, there is a massive discrepancy between ER-positive tumors and triple-negative tumors concerning local estrogen metabolism. In ER-positive tumors the intra-tumoral estrogen concentration can be 10-fold higher than the blood concentration of estrogens [38], and in most cases there is a gradient of aromatase expression towards the tumor in the affected breast (reviewed in [1]). In contrast, in triple-negative cancers, aromatase expression is found only in a minority of samples (and surprisingly is associated with strong androgen receptor expression) [19]. With this background we reasoned that factors driving the growth of TNBC might also be involved in the suppression of aromatase expression in these tumors. Therefore, based on its growth-promoting activities discussed above, and its well-established role in breast (tumor) development [15,16,17], we tested WNT3a for its effect on aromatase induction. Indeed, WNT3a-conditioned medium led to a strong inhibition of aromatase activity in human BAFs. This inhibitory effect correlates with a reduction in aromatase mRNA levels of a similar magnitude, which results from a proportionate decrease in the transcription regulated by the cAMP-dependent aromatase promoters I.3 and II. cAMP-mediated transcriptional activation of aromatase is typical in the vicinity of ER-positive breast cancers [39,40]. Moreover, conditioned medium from triple-negative MDA-MB231 (WNT3a-secreting) cells also inhibited forskolin-induced aromatase activity, and promoter I.3/II mediated aromatase gene expression, however in a less potent manner. This could be due to lower WNT3a levels compared to the conditioned medium from overexpressing L-M(TK-) cells, which were selected for their high WNT3a secretion. Besides that, MDA-MB231 cells may express other canonical Wnt ligands, which are more or less strongly expressed in other breast cancer cell lines [21]. In addition, the known secretion of glucocorticoid-dependent aromatase stimulating factors by MDA-MB231 cells [41], acting via promoter I.4 in target cells (BAFs), may partially antagonize WNT3a-mediated inhibition. Our results suggest that breast cancer-associated aromatase activity, and estrogen production, not only depend on activating factors from different sources [1], but also on the absence of inhibitory signaling molecules, such as WNT3a. Such a bifunctional model of regulation of breast cancer-associated aromatase expression has not yet been clearly described in the literature. However, it should be noted that a limited number of factors inhibiting aromatase induction in BAFs under certain conditions have been reported. Progesterone can act as a physiological antagonist for glucocorticoid-mediated aromatase induction, via promoter I.4 [42]. In addition, pharmacological doses of RU486 [43] or thiazolidinedione drugs [44] have been shown to repress promoter I.4- and I.3/II-mediated aromatase transcription. Furthermore, some cytokines partially (at best 50%) inhibit induction at of these promoters [1]. However, up to now, no physiological factor has been reported that equals the potency of WNT3a in aromatase inhibition observed in this study. As a consequence of the results discussed above, it can be concluded that the absence of WNT3a-induced signaling (or effective antagonism, for example by non-canonical Wnts [21]) towards BAFs appears to be of crucial importance for aromatase expression in ER-positive breast cancers. By analogy, this should also hold true for other activators of the canonical Wnt pathway. For an estrogen-dependent tumor, in consequence this implies that the secretion of factors leading to activation of promoter I.3/II-mediated aromatase expression in BAFs is not sufficient to secure a constant supply of estrogens for the tumor cells. Thus, this suggests that ER-positive tumors promote a desmoplastic reaction via factors that concomitantly induce aromatase [1,40], whereas triple-negative tumors drive the desmoplastic reaction predominantly via factors that inhibit aromatase induction. Such a mechanism of differential growth factor secretion also may support a facilitated loss of ERα in initially estrogen-dependent (ER-positive) breast cancers, thereby promoting them to develop a typical TNBC signature. So, if Wnt signaling is activated in BAFs, in a tumor micro-environment rich in non-estrogenic growth factors, the resulting estrogen starvation would favor the growth of cells relying on other growth factors, which would reciprocally make the ER dispensable. Signals that induce BAFs to secrete WNT proteins, in addition to tumor cells, could lead to some basal autocrine Wnt signaling [45]. Nuclear accumulation of β-catenin is dependent on an active canonical Wnt signaling pathway [6], and was observed in cells irrespective of treatment with WNT3a-conditioned media. This suggests that aromatase expression in the vicinity of breast tumors is controlled by a rather labile signaling environment, where Wnt signaling above a critical threshold will result in a switch-off of estrogen responsiveness/aromatase expression. Experiments with GSK-3β inhibitors indicated that activation of canonical Wnt signaling is involved in the suppression of aromatase induction in BAFs. It could lead to silencing of aromatase transcription mediated by the promoter region I.3/II via any (combination) of three in silico identified putative Wnt responsive elements (WREs), in this promoter region. Surprisingly, WNT3a treatment, and associated signaling, did not result, as expected, in enhanced association of β-catenin to the WREs, when analyzed by ChIP. In contrast, both in reporter gene assays, and in ChIP experiments, the decisive step for the WNT3a effect on aromatase induction was a switch in WRE1 occupancy from TCF-4 to LEF-1. Western blots with nuclear extracts from controls and WNT3a-treated cells revealed a change of the expression patterns of TCF-4 and LEF-1, specifically of a WNT3a-induced increase in the levels of an alternative, lower molecular weight LEF-1 variant. The increased expression of the small LEF-1 variant was accompanied by a similar reduction in the amount of the larger variant. DNA binding assays, with immunoprecipitated nuclear transcription factors, proved that each of the putative WREs can be bound by TCF-4 or LEF-1 in vitro. Unexpectedly, in immunoprecipitates from WNT3a-treated cells, binding to WRE1 and WRE2 was apparently lost. This effect could be traced back to the antibodies used for these immunoprecipitations, which were directed against the N-termini of the proteins, and therefore are not able to bind N-terminally truncated variants. The endogenous full-length TCF-4 or LEF-1 proteins from WNT3a-treated cells seem to lack sufficient ability to bind to WRE1 and WRE2, and preferentially bind to WRE3. In light of the ChIP results, this strongly suggests that Wnt signaling induces preferential binding of an N-terminally truncated LEF-1 variant to WRE1. Taken together, the findings discussed so far do not perfectly fit to a direct role of canonical Wnt components in the suppression of aromatase induction [6,7,8,9]. Therefore, we systematically analyzed the role of WREs, and various variants of TCF-4 and LEF-1, in reporter gene assays. The emphasis was on N-terminally truncated variants, because these are known for potential antagonistic activities, in comparison to the full-length proteins [46]. Western blot results indicated a WNT3a-induced switch from the full-length LEF-1 isoform to a shorter isoform, which must be truncated N-terminally (because the antibodies used for Western blotting bind more C-terminal regions of their targets than the antibodies discussed in the preceding paragraph). Therefore, N-terminally deleted variants of TCF-4 and LEF-1 were tested for their effects on aromatase promoter I.3/II. Overexpression of full-length LEF-1 resulted in promoter activation, whereas overexpression of ΔN-LEF-1 suppressed luciferase reporter gene activity, both via WRE1. This was the only combination of full-length/truncated factors with a WRE that revealed a switch of the mode of action. How does alteration of the LEF-1 isoforms produce that switch? Here, comparison of ΔN-LEF-1 with a further truncated variant, ΔΔN-LEF-1, which had lost the β-catenin binding domain, together with the context-dependent regulatory domain, is instructive. The latter domain is crucial for transducin-like enhancer of split (TLE) repressor binding [25,47,48,49]. The inhibitory effects on gene expression of LEF-1 are lost if the association of TLE together with histone deacetylases (HDACs) [50] is lost. The VP16-fusion proteins were used in order to make this effect visible. Consistent with this, the WNT3a-induced suppression of aromatase activity was partially abolished by HDAC inhibition. Therefore, inhibitory HDAC activity, which is very often associated with TLE, cooperates with inhibitory Wnt signaling on the aromatase promoter I.3/II region in BAFs. In contrast to LEF-1, both the full-length and an N-terminally truncated variant of TCF-4 suppress aromatase promoter I.3/II-dependent reporter gene activity. TCF-4 lost WRE binding ability upon WNT3a treatment of 3T3-L1 cells, or BAFs, in the immunoprecipitation in vitro binding assay (WRE1 and WRE2), and in the ChIP experiments (at least WRE1). Furthermore, using the TOPflash Wnt reporter system, overexpression of TCF-4 does not increase luciferase activity, whereas LEF-1-VP16 does. Taken together, TCF-4 function must be modified in a WNT3a-dependent way, in both 3T3-L1 cells and BAFs. Finally, the still open question is, “How is this switch from TCF-4 to LEF-1 mediated?” We assume that WNT3a-induced signaling will affect not only aromatase expression in BAFs, but will also induce further changes. In this respect, Wnt signaling was shown to regulate differential expression of LEF-1 and a dominant-negative N-terminally shortened (dnLEF-1) variant. Activation of the Wnt pathway was shown to trigger the switching from promoter 1 utilization (full-length) in the LEF1 gene, to promoter 2 activation (dnLEF-1) [46]. Although we could not directly verify the identity of the N-terminally shortened LEF-1, and the ΔN-LEF-1 or dnLEF-1 (both lacking the β-catenin binding domain), or the way in which the shortened variant is generated. Our data fit into a unifying model for the mechanism underlying WNT3a-triggered suppression of aromatase expression in BAFs (Figure 7). (1) Canonical Wnt signaling does not directly “activate” the aromatase promoter I.3/II, but instead either induces a promoter switch in the LEF1 gene, leading to accumulation of dnLEF-1, or induces processing of full-length LEF-1 to the shortened variant. (2) TCF-4 binding to certain WREs (among them WRE1 and WRE2) must be blocked by an unknown, WNT3a-dependent, mechanism, in preadipocyte-like cells (3T3-L1 and BAFs), or may alternatively be outcompeted by the large amount of the short LEF-1 variant. (3) The short LEF-1 variant occupies WRE1 in the promoter I.3/II region. (4) The short LEF-1 variant recruits TLE/HDAC to silence the aromatase promoter. All chemicals used were of analytical or cell culture grades. All oligonucleotides were from Metabion (Planegg/Steinkirchen, Germany). The 3T3-L1 cells and breast cancer cell lines were obtained from the ATCC (Manassas, VA, USA). The molecular classifications and the culture media for the breast cancer cell lines are summarized in Table 1. Several of these cell lines are known to express various Wnt ligands [21], MDA-MB231 cells are known to secrete WNT3a [18]. The 3T3-L1 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) (Sigma, Taufkirchen, Germany) containing 10% (v/v) fetal bovine serum (FBS) (Sera Plus, PAN-Biotech, Aidenbach, Germany) and 40 µg/mL gentamicin. Furthermore, L-M(TK-) cells (parental and WNT3a expressing) were cultured in DMEM containing 10% (v/v) FBS, 40 µg/mL gentamicin, and 100 µg/mL G418, before being used for production of conditioned media. The production of high titers of WNT3a protein by these cells was verified previously [55]. Human BAFs were isolated from adipose tissue of healthy patients undergoing cosmetic breast reduction surgery. The study was conducted in accordance with the Declaration of Helsinki, and patients gave informed consent according to a protocol approved by the ethics committee of the Jena University Hospital (Ref.-Nr. 4285-12/14). BAFs were isolated and cultured in medium 199, containing 10% (v/v) FBS and 40 µg/mL gentamicin, as described previously [56]. Confluent primary human BAFs, resembling almost exclusively preadipocytes, were subcultured only once. All cultured cells were maintained at 37 °C in a humidified atmosphere; 5% CO2 and 95% air content were used for all cells and media, except for 3T3-L1 preadipocytes, where the atmosphere contained 7.5% CO2 and 92.5% air, during culture in serum-containing growth medium. If not indicated otherwise, all treatments of cells with stimulators or inhibitors were performed for 24 h, in serum-free medium, consisting of DMEM and Ham’s F12 medium at a ratio of 3:1 (without phenol red and with 7.5 mM HEPES, pH 7.2), which was supplemented with gentamicin (40 μg/mL), transferrin (2 μg/mL), pantothenate (17 μM), biotin (1 μM), and insulin (1 nM) [56]. A general activation of aromatase promoter I.3 and II was obtained by forskolin (10 µM; Cayman Chemicals, Ann Arbor, MI, USA). Furthermore, cells were treated with L-M(TK-)WNT3a or breast cancer cell line conditioned medium (CM), in the concentrations indicated. The conditioned media were collected under serum-free conditions (serum-free medium as used for BAFs) after 3 days conditioning time, and stored at 4 °C after centrifugation. Intracellular processes were inhibited by the broad-spectrum histone deacetylase inhibitor panobinostat (LBH589, IC50 = 5–20 nM, Selleck Chemicals, Houston, TX, USA), and GSK-3β inhibitors lithium chloride (IC50 = 2 mM) and BIO (6-bromoindirubin-3′-oxime, IC50 = 5 nM, Merck, Darmstadt, Germany). When appropriate, DMSO and ethanol solvent controls were carried out in parallel. The fluorescein diacetate (FDA) test was carried out as described previously [57]. Two days after passaging of BAFs into 24-well plates (average 5000 cells/cm2), the cells were stimulated by up to 50% conditioned media. The conditioned media were mixed with medium 199, containing 10% (v/v) FBS and 40 µg/mL gentamicin, to ensure a basal growth rate. Stimulations were repeated after 2, 4, and 6 days. On day 8, the FDA test was carried out. After 90 min FDA incubation under cell culture conditions, fluorescence was measured (excitation 480 nm; emission 525 nm, cut off 495 nm) on a SpectraMax M2 plate reader (Molecular Devices, Sunnyvale, CA, USA). All conditions were tested in triplicate or quadruplicate per experiment. mRNA expression was quantified by real-time PCR (qPCR). BAF or breast cancer cell mRNA was isolated using the RNeasy Mini Kit (Qiagen, Hilden, Germany) with DNAse digestion. Subsequently, cDNA was synthesized with the High-Capacity cDNA Archive Kit (Applied Biosystems, Darmstadt, Germany), using random hexameric primers. WNT1 and WNT3A expression were analyzed by quantitative real-time PCR (qPCR), in a StepOnePlus cycler (Applied Biosystems), using GoTaq qPCR Master Mix (Promega, Mannheim, Germany), and the following primers (Gene symbol, forward primer, reverse primer): WNT1, 5′-GGCAAGATCGTCAACCGAG-3′, 5′-GTCACACGTGCAGGATTCGAT-3′; WNT3A, 5′-TTTGGTGGGATGGTGTCTCG-3′, 5′-ACCAGCATGTCTTCACCTCG-3′; and GAPDH, 5′-AGCCACATCGCTCAGACAC-3′, 5′-GCCCAATACGACCAAATCC-3′. After 2 min denaturation, 40 cycles of denaturation (15 s), annealing (30 s) and elongation (30 s), were performed. The identities of the products were determined by sequencing and melt-curve analysis. Full-length aromatase mRNA expression and utilization of promoters I.3 and II, respectively, was analyzed by qPCR, as described in detail previously by Wilde et al. [27], using the Universal Probe Library system (Roche, Mannheim, Germany). All conditions were tested in triplicate per experiment. Evaluation of qPCR results was performed by the ΔΔCT-method [58]. The in vivo evaluation of aromatase activity in BAFs was performed using the tritium water release assay, in 24-well plates. The method was carried out as described previously [56,59]. After 18 h in 500 µL serum-free stimulation medium, 1 µCi/well (80 nM) [1β-3H]androstenedione (PerkinElmer, Rodgau, Germany) was added as a substrate for the aromatase enzyme 6 h before the incubation was terminated. Aromatase activity was given as pmol androstenedione used per 6 h and mg protein. All conditions were tested in triplicate per experiment. The preparation of soluble nuclear extracts was based on a method published by Wilde et al. [27]. The protein concentration was quantified by the Bradford method [60]. Soluble nuclear extract proteins (50 µg) were pre-incubated with 20 µL pre-cleared protein G-Sepharose 4 Fast Flow (GE Healthcare, Freiburg, Germany), in soluble nuclear extract buffer, at 4 °C, in a rotator, to eliminate proteins binding nonspecifically to protein G. After centrifugation of the pre-incubated samples (20 s, 12,000× g, 4 °C), the supernatants were transferred into new tubes and incubated with antibodies for 24 h, at 4 °C, under constant rotation. The antibodies were, mouse anti-TCF-4 (L40C3) (directed against a peptide around Glu81 of human TCF-4; Cell Signaling Technology, Frankfurt, Germany) or mouse anti-LEF-1 (2D12) (directed against amino acids 1–85 of human LEF-1; nanoTools, Teningen, Germany). After antibody incubation, 20 µL of pre-cleared protein G-Sepharose 4 Fast Flow was added and incubated for 4 h, at 4 °C, under constant rotation. For final isolation of TCF-4 or LEF-1 immunoprecipitates, respectively, the samples were washed three times in a three-fold volume of DNA-binding buffer C (20 mM HEPES pH 7.9, 1 mM EDTA, 1 mM EGTA, 1 mM DTT, 1 mM PMSF), with centrifugation after each step (20 s, 12,000× g, 4 °C). The final immunoprecipitates were resuspended in 8 µL buffer C. The DNA-binding reaction was a modification of the sample preparation protocol for electrophoretic mobility shift assays described by Taylor et al. [61]. Immunoprecipitates in buffer C (8 µL) were mixed with 1.7 µL 10-fold binding buffer (500 mM Tris/HCl pH 7.5, 1 M NaCl, 1 mM EDTA, 50 mM β-mercaptoethanol). For normal binding reactions, the premix was added to 2 µL Cy5-labeled double-stranded oligonucleotides (25 pmol/µL; WRE1: 5′-GAGTCACTTTGAATTCAAT-3′, WRE2: 5′-ACTTACTATTTTGATCAAAAAAGTCATT-3′, WRE3: 5′-CTTTTTGTTTTGAAATTGATTTGGCTTCA-3′, only sense sequences given) and 5.3 µL water. For binding reactions in the presence of competitor, 8 µL immunoprecipitate, 2 µL fluorescence-labeled double-stranded oligonucleotides, and 5.3 µL unlabeled competitor double-stranded oligonucleotides (250 pmol/µL; same sequences like fluorescence-labeled oligonucleotides) were mixed. After incubation for 30 min with rotation, at room temperature in the dark, the samples were washed three times in a three-fold sample volume of wash buffer (50% buffer C, 10% 10-fold binding buffer, 40% water), followed by a 20 s centrifugation at 12,000× g at room temperature. Finally, the oligonucleotide bound immunoprecipitates were resuspended in 17 µL wash buffer, and transferred to a well of a 96-well plate for fluorescence measurement (excitation 600 nm; emission 670 nm, cut-off 630 nm). As a control, unspecific binding of fluorescent oligonucleotides to protein G-Sepharose 4 Fast Flow beads treated as described above, in the absence of antibodies, was analyzed, resulting in negligible fluorescence signals. All conditions were tested in triplicate per experiment. Soluble nuclear extracts (100 µg) of 3T3-L1 cells or BAFs were precipitated with trichloroacetic acid (TCA) and separated on 10% SDS-polyacrylamide gels. Proteins were transferred onto PVDF membranes using semi-dry blotting at 0.8 mA/cm2 for 40 min. After blocking in WP-T buffer (10 mM Tris/HCl pH 7.5, 100 mM NaCl, 0.1% (v/v) Tween 20) with 5% (w/v) skimmed milk powder, the membrane was incubated overnight with the primary antibodies (1:1000 each): mouse anti-β-catenin (clone 14, 610154, BD Biosciences, Heidelberg, Germany), rabbit anti-TCF-4 (directed against amino acids 486–610 of human TCF-4; H125, sc-13027, Santa Cruz Biotechnology, Heidelberg, Germany), or mouse anti-Lamin A/C (clone 14, 612163, BD Biosciences). Rabbit anti-LEF-1-292 was generated by sequential immunization of a rabbit with purified recombinant LEF-1 (amino acids 1–292) protein [62,63]. After washing in WP-T buffer and blocking in WP-T buffer with 5% (w/v) milk powder again, the appropriate HRP-conjugated secondary antibodies were added (1:10,000 goat anti-rabbit, 1:5000 goat anti-mouse, Santa Cruz). Proteins were detected using enhanced chemiluminescence. Wnt response elements (WREs) were mutated (mWRE) in a pre-existing plasmid, containing firefly luciferase under the control of aromatase promoter region I.3 and II (pGL3-PII-522 WT) [27], by use of the Phusion site-directed mutagenesis protocol (New England Biolabs, Frankfurt, Germany). Primers: mWRE1 (forward) 5′-GTGAGTCACTcgcgATTCAATAGACAAACTGATGGAAGGC-3′, mWRE1 (reverse) 5′-TCAGGCCATCTCTAGTGAC-3′; mWRE2 (forward) 5′-cgcgAAAAGTCATTTTGGTCAAAAAGG-3′, mWRE2 (reverse) 5′-cgcgAATAGTAAGTTTCTACAGTAAGAAC-3′; mWRE3 (forward) 5′-TGTTTTGAAAcgcgTTTGGCTTCAAGGGAAGAAGATTG-3′, mWRE3 (reverse) 5′-AAAAGGCAATCTCCCAAC-3′ (lowercase indicates mutated nucleotide positions). All constructs were verified by sequencing. Half confluent 3T3-L1 preadipocytes, in 24-well plates, were transfected using Roti-Fect Plus (Carl Roth, Karlsruhe, Germany) for liposome-mediated uptake of DNA, according to the manufacturer’s instructions. The cells were stimulated 24 h later. To quantify promoter activities, the firefly luciferase, containing pGL3-Basic plasmids with wildtype or mutated aromatase promoter I.3/II (pGL3-PII-522-WT, pGL3-PII-522-mWRE1, pGL3-PII-522-mWRE2, pGL3-PII-522-mWRE3, each 800 ng/well), or TOPflash plasmid ([64], kindly provided by Dr. Bert Vogelstein), expressing luciferase under the control of optimized synthetic WREs (150 ng/well), were used. When indicated, cells were co-transfected with plasmids containing either full-length or truncated variants of human TCF-4 or murine LEF-1, respectively (each 400 ng/well): pCMV-FLAG-TCF-4 (596 amino acid protein encoded by GenBank sequence Y11306.2) or pCMV-FLAG-ΔN-TCF-4 (amino acids 32–596 of the aforementioned protein, lacking only the β-catenin binding domain) [65]. Alternatively, pCS2+-LEF-1-VP16 (397 amino acid protein encoded by RefSeq sequence NM_010703.4), pCS2+-ΔN-LEF-1-VP16 (amino acids 57–397, lacking only the β-catenin binding domain), or pCS2+-ΔΔN-LEF-1-VP16 (amino acids 265–397, lacking β-catenin binding domain and context dependent regulatory domain), all fused to the VP16 activation domain as internal control, were used, which were described previously [28,65]. All conditions were tested in triplicate per experiment. The chromatin immunoprecipitation protocol is a modified version of that published by Weinmann and Farnham [66,67]. BAFs from four 10 cm dishes per condition were used. For protein G-based immunoprecipitation, 1 µg/reaction rabbit anti-LEF-1 292, rabbit anti-TCF-4X (H125), or mouse anti-β-catenin (clone 14) antibodies were used. Primer set 1 amplifies the region containing the three putative WREs in aromatase promoter I.3/II: 5′-TGAAGTCACTAGAGATGGCCTG-3′ (forward), 5′-GCTCATTCCAGAGGTGGAGTC-3′ (reverse). Primer set 2 amplifies a region containing putative WRE2 and WRE3, but not WRE1: 5′-GGCTCTGAGAAGACCTCAACG-3′ (forward), 5′-GTAGAGTGACGTGCATTCCCA-3′ (reverse). PCR was performed using Paq5000 DNA polymerase (Agilent Technologies, Santa Clara, CA, USA), and PCR-products were analyzed on 12% (w/v) polyacrylamide gels stained with ethidium bromide, as described previously [27]. Statistical analyses of all experiments, and creation of diagrams, were performed with the SigmaPlot 13 or 14 software (Systat, Erkrath, Germany). Data are presented as means ± SEM or using box plots, where appropriate. Initially, normal distribution of values was tested by the Shapiro–Wilk method. Normally distributed values were compared to another group by the two-tailed Student’s t-test (if not explicitly indicated otherwise in text/legends). In the case of non-normally distributed values, two groups were compared by the Mann–Whitney rank sum test, if indicated. For all tests, the significance criterion p < 0.05 was used. All numbers of replications (n) in figure legends refer to biological replicates. Canonical Wnt signaling toward BAFs can induce change in a breast tumor environment in two ways: it can initiate/enhance the desmoplastic reaction, and thus increase the amount of altered stroma; and it can suppress local estrogen production in the BAFs. Therefore, breast tumors, which secrete Wnt ligands may cut themselves off from a sufficient estrogen supply for growth promotion. Lacking estrogen signaling consequently will make ERα dispensable, and thus supports development into a hormone receptor-negative tumor.

PMC10003477

Clemens M. Gehrer,Anna-Maria Mitterstiller,Philipp Grubwieser,Esther G. Meyron-Holtz,Günter Weiss,Manfred Nairz

Advances in Ferritin Physiology and Possible Implications in Bacterial Infection

28-02-2023

ferritin,compartmentalization,immune metabolism,exosome,nutritional immunity,regulation,Salmonella Typhimurium,iron,macrophage,liquid-liquid phase separation

Due to its advantageous redox properties, iron plays an important role in the metabolism of nearly all life. However, these properties are not only a boon but also the bane of such life forms. Since labile iron results in the generation of reactive oxygen species by Fenton chemistry, iron is stored in a relatively safe form inside of ferritin. Despite the fact that the iron storage protein ferritin has been extensively researched, many of its physiological functions are hitherto unresolved. However, research regarding ferritin’s functions is gaining momentum. For example, recent major discoveries on its secretion and distribution mechanisms have been made as well as the paradigm-changing finding of intracellular compartmentalization of ferritin via interaction with nuclear receptor coactivator 4 (NCOA4). In this review, we discuss established knowledge as well as these new findings and the implications they may have for host–pathogen interaction during bacterial infection.

Advances in Ferritin Physiology and Possible Implications in Bacterial Infection Due to its advantageous redox properties, iron plays an important role in the metabolism of nearly all life. However, these properties are not only a boon but also the bane of such life forms. Since labile iron results in the generation of reactive oxygen species by Fenton chemistry, iron is stored in a relatively safe form inside of ferritin. Despite the fact that the iron storage protein ferritin has been extensively researched, many of its physiological functions are hitherto unresolved. However, research regarding ferritin’s functions is gaining momentum. For example, recent major discoveries on its secretion and distribution mechanisms have been made as well as the paradigm-changing finding of intracellular compartmentalization of ferritin via interaction with nuclear receptor coactivator 4 (NCOA4). In this review, we discuss established knowledge as well as these new findings and the implications they may have for host–pathogen interaction during bacterial infection. Bacterial infection has been a major public health concern for a long time. Accordingly, a recent study has estimated that deaths associated with 33 common bacterial genera or species would rank as the second leading cause of death globally in 2019 [1,2]. During infection, pathogens and the host are entangled in a fight for their respective lives, whereby the host as well as the pathogen use intricate mechanisms to ensure their survival, such as the complement system, quorum sensing, which is the ability of cells, e.g., bacteria, to adapt their metabolism in response to cell population density [3,4,5]. Furthermore, the host and pathogens both compete for nutrients during infection. Thereby, the host attempts to deprive invading microorganisms from essential nutrients by a distinct set of mechanisms, while the pathogen tries to circumvent these efforts. This part of the non-adaptive immune response, termed nutritional immunity, has been shown to be essential in fighting off pathogens [6,7,8,9]. The research concerning this matter has gained momentum in recent years. In this context, iron is regarded as one of the central nutrients involved in nutritional immunity, because it is essential for nearly all forms of life [10]. The constant demand for iron is based on its pivotal role in a wide array of enzymatic processes. For example, DNA synthesis, reactive oxygen species (ROS) defense and energy metabolism require iron due to its advantageous redox properties. However, iron is not only the boon, but also the bane of cellular metabolism, because it has the ability to produce ROS via Fenton chemistry. Therefore, iron is stored intracellularly in the protein ferritin, which can bind large quantities of iron and thus diminish the generation of ROS. Recent insights demonstrated that intracellular ferritin is present in its own membrane-less compartment inside the cytoplasm separated via liquid-liquid phase separation. Furthermore, increasing evidence of the mechanisms of ferritin trafficking has accumulated in the last decade. In this review, we discuss the currently known mechanisms of mammalian ferritin’s function, regulation, compartmentalization and trafficking, as well as the possible implications they might have in host–pathogen interaction. Thereby, we put the focus on infection with the intracellular bacterium Salmonella enterica serovar Typhimurium (S.Tm), but we will also discuss other intracellularly occurring pathogens. We will not discuss the function of prokaryotic mini- and maxi-ferritins, because a comprehensive overview has recently been provided by Bradley et al. [11]. Mammalian ferritin is a spheric protein, which can consist of two types of subunits, namely the ferritin H-chain (FTH, ~21 kDa in humans) and the ferritin L-chain (FTL, ~19 kDa in humans) [12]. These two subunits assemble into hollow 24-meric nanocages in variable ratios. Therefore, the molecular weight of the assembled protein is variable depending on the tissue specific H/L-ratio, but is generally around 480 kDa for the iron-free protein, named apoferritin. Although the ferritin subunits are able to assemble to homopolymers, most ferritin is found as a heteropolymeric protein in vivo. With this in mind, ferritin isolated from the brain, heart, kidney, pancreas, muscle, thymus and red blood cells is rich in FTH, while ferritin from liver and spleen is rich in FTL [12,13,14,15,16]. A special case is serum ferritin, which has been proposed to contain only minute amounts of FTH, and which is thought to contain only little amounts of iron, with one study in humans even proposing that it might represent apoferritin [17,18,19,20,21]. The reasons for the tissue-specific subunit composition are hitherto unclear. However, it is generally thought that H-rich ferritin occurs in tissues with a higher demand for anti-oxidative capacity and L-rich ferritin occurs in tissues, which are more involved in the storage of iron [22,23,24]. This idea arises from the distinct functions of these two proteins. FTH possesses a ferroxidase active site, which catalyzes the oxidation of ferrous to ferric iron (vide infra) [15]. In contrast, FTL does not have this catalytic site, but has negatively charged amino acid residues, which serve as nucleation sites for the formation of the iron core within the ferritin complex [25,26]. Furthermore, FTL supports the ferroxidase activity of the FTH by increasing the iron turnover at the catalytic center [27]. Once assembled, mammalian ferritin forms two kinds of channels, localized between the subunits connecting the environment with the cavity of ferritin. Thereby, there are eight channels with a three-fold symmetry and six channels with a four-fold symmetry. The three-fold channels are hydrophilic, as they are lined with six negatively charged residues and are regarded as the entry point of iron into ferritin [28,29,30,31]. In contrast, the four-fold channels are hydrophobic and not thought to transport iron, but are still involved in the incorporation of iron into ferritin. This is because changes in the residues of the four-fold channel interfere with ferritin’s ability to deposit iron inside its core [32,33,34]. The suggested function of the four-fold channels is to transfer protons, generated during the formation of the core, from the inside ferritin to the environment [29,35]. However, this proposed function comes from in-silico analyses of the electrostatic properties of ferritin, but experimental data confirming this function are lacking. Furthermore, the amino acids adjacent to the four-fold channel are important for the assembly and the stability of ferritin [33,34]. In addition to the inter-subunit channels, there is also a small channel in each FTH, which connects the outside of ferritin with the ferroxidase site [36]. This channel was proposed to be important for oxygen transport to the ferroxidase site, but this could not be confirmed by experimental data, as a change in the key amino acid Tyr 29 did not result in an altered iron incorporation into ferritin [37,38]. A detailed depiction of ferritin structure is provided by Ebrahimi et al. [39]. The main function of ferritin is regarded to be the intracellular detoxification of iron through the incorporation of the metal and the concomitant prevention of ROS formation [40]. Iron is taken up via the three-fold pore and then transported to the ferroxidase active site [41]. There, it is oxidized under consumption of oxygen or hydrogen peroxide before it starts forming the core by binding to specific nucleation sites on the inside of the ferritin shell [25,26]. The rates of oxidation with H2O2 are much faster than with oxygen, ~3-times faster in H-rich ferritin and ~120-times faster in L-rich ferritin [27]. Furthermore, the mineral core can facilitate the oxidation and subsequent core formation enzymatically, when it reaches a size of approximately 200 iron atoms [27,42,43]. These reactions can be summarized in three equations [27]: As the sum of reactions (1) and (3) is the same as reaction (2), these reactions cannot be distinguished [27]. The end product of these reactions is a core, which has been shown to mainly consist of ferrihydrite and hematite with traces of magnetite and maghemite [44]. In addition to the ability of ferritin to detoxify H2O2, the core of ferritin has been proposed to harbor superoxide dismutase activity [45]. Aside from its function in ROS detoxification and iron storage, ferritin is involved in immunomodulation. In this context, FTH was found to act as a pro-inflammatory signal in liver cells independent of its iron content via activation of the nuclear factor (NF)-ĸB-pathway [46]. However, studies in other cells could show that binding of FTH correlates with impaired B-cell maturation and immunoglobulin production as well as reduced T-cell proliferation [47,48,49]. Furthermore, FTH has pro- as well as anti-inflammatory effects depending on the cell type. CD8+ T-cells express interferon-γ (IFN-γ) upon stimulation with FTH. In contrast, regulatory T-cells, in contact with dendritic cells, prestimulated with FTH, secrete the anti-inflammatory cytokine interleukin (IL)-10 [50]. However, the role of ferritin in immunomodulation is also under debate as some findings have been controversial [51,52]. One study has shown that FTH is necessary for disease tolerance in a cecal ligation and puncture sepsis model, but did not affect cytokine expression [52], while another study using the same sepsis model showed an FtH knockout to enhance survival in mice via a blunted immune response [51]. However, while one study showed that the addition of exogenous horse spleen apoferritin reduced septic lethality [52], the other study showed apoferritin or recombinant human FTL mitigated LPS-mediated macrophage activation [51], which indicates an immunosuppressive function of ferritin. In contrast, a recent study could show that administration of horse spleen holoferritin results in hepatic as well as systemic inflammation, which is mediated via the ferritin receptor Scavenger receptor class A member (SCARA)1 and subsequent neutrophil extracellular trap formation [53]. These contrasting findings might be explained by the iron content of ferritin or changes in the protein during the removal of iron from ferritin by the manufacturer and by the different models used. Of note, another study found that macrophage specific depletion of FTH resulted in impaired control of Salmonella infection in iron-loaded mice which could be traced back to induction of inflammasome activation and IL-1β formation. Accordingly, Caspase-1 inhibition or anti-IL-1 treatment could overcome this survival disadvantage indicating that ferritin is an important radical detoxifying molecule in the setting of pathologic inflammation and infection [54]. Furthermore, this study also found that peritoneal macrophages lacking FTH demonstrate a higher baseline secretion of pro-inflammatory cytokines, which is independent of iron stimulation [54]. Nevertheless, these studies indicate there to be an immunomodulatory function of ferritin, albeit still unresolved whether it acts pro- or anti-inflammatory or even both. The regulation of ferritin expression is very complex and involves transcriptional and post-transcriptional mechanisms [10]. An extensive review of factors influencing ferritin expression has been given by Torti et al. [55]. In that review, they describe a wide array of transcriptional and post-transcriptional regulation through iron, oxidative stress, inflammatory signals, hormones, growth factors, second messengers and cell differentiation. Herein, we will focus on the former three, as they seem the most important ones in the context of our review. A simplistic schematic depiction of the mechanisms explained below is provided in Figure 1. Generally speaking, the regulation of ferritin is regarded to occur mostly on a post-transcriptional level by facilitating the transfer of ferritin mRNA from a mostly inactive pool to polyribosomes in order to initiate the translation of the protein [56]. Thereby, ferritin translation is regulated by iron through iron regulatory protein (IRP) 1 and 2 [55,57]. When the cellular iron content is low, the IRPs bind to the iron responsive element (IRE) in the 5′ untranslated region of the H- and L-ferritin mRNA [58,59,60,61], thus preventing translation [62]. The inhibition of translation by IRP1 and presumably also IRP2 happens at the stage of initiation, as IRP1 has been shown to prevent the interaction of the eukaryotic translation initiation factor (eIF) complex eIF4F with ribosomes [63]. When there is a sufficient amount of cellular iron, IRP1 contains an iron-sulfur cluster, becoming cytoplasmic aconitase [64], and IRP2 is degraded. The latter pathway is facilitated by F-box and leucine-rich repeats protein 5 (FBXL5) in an iron and oxygen-dependent manner [65]. Consequently, in the presence of surplus iron, the IRPs move away from the IRE of ferritin mRNA, permitting the translation of the protein for iron storage. Interestingly, a recent study has shown that FTL, but not FTH, expression is post-transcriptionally repressed by eIF3, which is distinct from the regulation via the IRP system [66]. However, the binding of IRPs to IRE can be modulated via ROS and reactive nitrogen species (RNS), but the findings are controversial and subject to debate, as has been reviewed by Cairo et al. [67]. H2O2 promotes IRP1 binding to IRE, most likely through phosphorylation or an energy-dependent mechanism rather than by direct attack [68,69]. Furthermore, IRP1 activity is regarded to be increased by NO [70,71,72,73,74,75], while its effect on the IRE-binding activity of IRP2 is less clear. Some studies found IRP2 activity to be enhanced by NO [71,76], while others found a reduction in IRP2 activity [73,74,77]. In this context, Kim et al. have proposed that the distinct effect of the NO congeners NO+ and NO. may be responsible for these paradoxical findings [74]. The distinct effects of these two nitrogen species have also been shown experimentally [78]. Furthermore, IRP1 seems to be only transiently activated by ROS and RNS with a subsequent inactivation and concomitant enhanced ferritin translation [73,79]. Besides the post-transcriptional regulation by ROS, ferritin is induced on a transcriptional level via the binding of nuclear factor erythroid 2-related factor 2 (Nrf-2) to an antioxidant responsive element (ARE) in the promoter regions of ferritin [80,81]. It is of note that most the studies on the influence of ROS/RNS on IRP1 and 2 have mostly been conducted in vitro under standard cell culture conditions, and therefore, might be of limited relevance for the physiological environment, which has roughly 3–7% oxygen [82]. Ferritin regulation has also been shown to be influenced by inflammatory stimuli other than ROS and RNS [83,84,85,86,87]. Specifically, the cytokines tumor necrosis factor α (TNF-α), IL-1β, IFN-γ, IL-6 and the anti-inflammatory IL-10 [88] induce ferritin expression. In the case of TNF-α and IFN-γ this happens on a transcriptional level, whereby H-ferritin mRNA expression is upregulated [87,89]. On the other hand, IL-1β does not increase ferritin mRNA, but facilitates ferritin translation by binding to a G and C rich region in the 5′ UTR, which is also present in the mRNAs of other acute phase proteins [84,85,87]. IL-10 also promotes ferritin expression on a post-transcriptional level, but the exact mechanism is not clear [88]. In the case of IL-6, an enhanced ferritin protein expression has been reported, but the effect on mRNA transcription was not assessed [86]. In addition to enhancing ferritin expression, TNF-α as well as IFN-γ enhance the flux of newly acquired iron into ferritin, while the overall iron uptake is reduced [87,90]. However, another study has demonstrated that the overall ferritin-bound iron is reduced upon stimulation with IFN-γ and that infection with S.Tm further decreases the amount of ferritin-bound iron [91,92]. Taken together, multiple mechanisms control ferritin expression and many of these are deeply involved in inflammation and infection. While post-transcriptional regulation via the IRP/IRE system is at the regulatory center of ferritin protein expression, transcriptional and IRP-independent post-transcriptional mechanisms play an important role for cellular ferritin concentration. Furthermore, the three described regulatory mechanisms influence each other, which makes it extremely difficult to attribute the observed results of previous studies to solely one stimulus. Although mammalian ferritin, with the exception of mitochondrial ferritin, has been considered a cytosolic protein, a recent study found it in a separate membrane-less compartment inside the cytosol [93]. In that study, the authors defined a new role of the canonical ferritinophagy receptor nuclear receptor coactivator 4 (NCOA4). The interaction of NCOA4 and H-ferritin results in liquid-like ferritin-NCOA4 condensates, which are separated from the cytosol due to liquid–liquid phase separation. However, the finding of membrane-less ferritin aggregates has been described much earlier [94,95,96]. This condensate formation is necessary for subsequent utilization of ferritin and vesicular trafficking of the protein via the binding of Tax1-binding protein 1 (TAX1BP1) to NCOA4 [93,97]. Thereby, TAX1BP1 targets ferritin to lysosomes via classical Microtubule-associated protein 1A/1B-light chain 3 (LC3)-dependent [93] and alternative pathways, the latter being independent of Autophagy-related protein (ATG) 8 but dependent on FAK family kinase-interacting protein of 200 kDa (FIP200), TANK-binding kinase 1 (TBK1) and Phosphatidylinositol 3-kinase VPS34 (VPS34) [97]. Furthermore, the alternative pathway seems not to be restricted to NCOA4 as a substrate. Rather, the proteins involved are also important for the turnover of another TAX1BP1 substrate, namely Next to BRCA1 gene 1 protein (NBR1) [98]. This mechanism of lysosomal ferritin degradation is also regulated by iron via NCOA4 [99]. Under iron-rich conditions, NCOA4 binds iron and interacts with the E3 protein ligase HECT domain and RCC1-like domain-containing protein 2 (HERC2), which leads to the subsequent degradation of NCOA4 via the proteasome [99]. Consequently, ferritin shuttling to the lysosome decreases. The trafficking of ferritin to the lysosome and its subsequent degradation is termed ferritinophagy. This process appears to be the most important way to release ferritin-bound iron, which has been shown during infection [99,100,101]. However, it is speculated, that other mechanisms, e.g., reductive iron release, may play a role in the cellular environment as well [102,103]. Hitherto, the proposed mechanisms have only been shown in cell-free systems due to difficulties in creating appropriate experimental setups in a living system. Nevertheless, ferritin has also been shown to be degraded via the proteasome and that iron is released prior to degradation [104,105]. In conclusion, there may be several mechanisms for utilization of ferritin-bound iron. However, ferritinophagy is not only the best characterized but presumably also the most important one. In the lysosome, the ferritin core dissolves due to the acidic environment (pH ~ 4.5–5.0) [106], while the protein is degraded by lysosomal proteases [107]. Thereby, the acidification is necessary for iron release of ferritin, while the proteolytic degradation is not [107]. After the dissolving/dissolution of the ferritin core, lysosomal ferrireductases six-transmembrane epithelial antigen of prostate 3 (STEAP3) and Cyb561a3 (AKA lysosomal cytochrome B, LcytB) reduce Fe3+ to Fe2+, which is then transferred to the cytosol via Natural resistance-associated macrophage protein 1 (NRAMP1), Divalent metal transporter 1 (DMT1), also known as SLC11A2 or NRAMP2, and Transient receptor potential channel mucolipin 1 (TRPML1) [108,109,110,111,112]. However, the trafficking of ferritin to the lysosome is not only important for cellular iron utilization, but also for the secretion of ferritin [21,113]. In the lysosome, ferritin is processed resulting in truncated FTL-subunits, which are called serum-subunits (S-subunit), as they are predominantly found in serum ferritin [21]. Hence, the presence of the S-subunit in serum indicates that ferritin is subsequently released via non-classical lysosomal secretion [21]. It has also been proposed that FTL, found in serum, is secreted via the classical Golgi-dependent pathway [114]. However, this finding could not be reproduced by another study [113]. Furthermore, cells secrete ferritin via the multivesicular body (MVB)–exosome pathway, whereby this process is likely being regulated via IRE/IRP-dependent translation of CD63 [113,115,116]. In addition to that, ferritin has also been shown to exit the cell via secretory autophagy upon endomembranous damage in a Tripartite motif-containing protein 16 (TRIM16), Vesicle-trafficking protein SEC22b (Sec22b) and galectin-8 dependent manner, but seemingly independent of NCOA4 [117]. Taken together, several mechanisms exist for the secretion of ferritin. However, it remains unknown whether these mechanisms are relevant in infections and for nutritional immunity. In humans, it has been shown that cells can take up extracellular ferritin directly via T-cell immunoglobulin and mucin domain (TIM) 1, transferrin receptor 1 (TFR1) and SCARA5 [118,119,120,121]. A recent study demonstrated that other members of the SCARA family, namely SCARA1 and SCARA2, are also able to bind human ferritin, albeit to a lesser degree than SCARA5, with SCARA2 only showing very weak binding [121]. Furthermore, it has also been shown in mice that cells can acquire ferritin via TIM2 and SCARA5, which has first been identified as a ferritin receptor in mice [122,123]. Thereby, TIM1, TIM2 and TFR1 act as FTH receptors [118,119,122], while SCARA5 supposedly binds FTL [120,123]. However, a recent study proposed that SCARA1, 2 and 5 are able to bind both FTL and FTH [121]. Additionally, ferritin can enter cells by using extracellular vesicles as a vehicle [116]. Hitherto, the mechanism behind the uptake of ferritin-containing exosomes has not been investigated, but might be facilitated by receptors, e.g., TIM-4 recognizes phosphatidylserines, which are usually enriched in exosomes [124,125,126]. This binding may result in internalization of the exosome or the fusion with the plasma membrane [127]. A graphic depiction of the described mechanisms is provided in Figure 2. In conclusion, numerous pathways for the uptake, intracellular trafficking and release of ferritin have been described. Therefore, it may be feasible to acknowledge ferritin as a cellular iron import and export protein. However, the biological relevance of ferritin as a systemic iron transport protein is under discussion. For example, under physiologic conditions, only a small amount of ferritin is found in serum and this ferritin is less iron loaded in comparison with intracellular ferritin [21]. Nevertheless, the saturation of serum ferritin with iron in healthy human subjects has been estimated by different investigators to be roughly between 24% [128] and 50% [129]. Furthermore, we calculated the ferritin saturation of human subjects with a normal iron status from a third study [130] by using a hypothetical molecular weight of 450 kDa and a maximum loading capacity of 4500 iron atoms per ferritin, which would apply to 100% saturation. This resulted in roughly 27% saturation. In other words, human serum ferritin has been found to contain on average roughly between 1000–2000 iron atoms per ferritin, which contrasts the general sentiment of serum ferritin containing only small amounts of iron. In addition to that, a study investigating the development of Tfr1 knockout mice embryos suggests that ferritin functions as a cell type-specific iron transport protein during organogenesis [123]. This finding is in accordance with an essential role of FTH in embryonic development [131]. However, ferritin’s function in systemic iron metabolism in adult mammals may be less important in homeostatic conditions [132]. The biological relevance of the trace metal iron in infectious diseases has been investigated in numerous clinical and animal studies. As in humans, iron is also essential for nearly all microorganisms, including bacteria, fungi, protozoa and helminths, with only a few exceptions [133]. In many bacteria, proliferation capacity and virulence is dictated by the amount of iron in their environment [134]. During infection, thus confined to the space of the host, bacteria must acquire iron from the host to sustain proliferation and accomplish efficient infection. Appropriately, systemic iron overload is associated with an increased risk of infection with various pathogens [135]. The human host has evolved several immune strategies to take advantage of this bacterial iron demand by sequestering iron from the specific localization in which a pathogen resides. The withdrawal of essential nutrients from pathogens, especially iron, is regarded as an efficient innate host defense strategy in line with the concept of innate nutritional immunity [6,136]. In systemic infection, the host adapts its iron metabolism to limit iron availability to pathogens, as well as attacking bacterial iron acquisition on multiple levels. Initiated by the production of pro-inflammatory cytokines during the acute-phase-response, several effector molecules are produced by the liver which affect systemic iron metabolism [135]. One prototypical mechanism leading to iron sequestration is the secretion of the hormone and master regulator of systemic iron metabolism hepcidin antimicrobial peptide (HAMP). HAMP binds to the only known ferrous iron exporter ferroportin-1 (FPN), leading to its internalization, degradation and thus, a decrease in iron export [137]. It is likely that most tissues are affected by this mechanism, with FPN degradation in hepatocytes, macrophages as well as duodenal enterocytes most likely contributing pivotally to hypoferremia and intracellular iron sequestration [138]. Transcriptional and post-transcriptional regulation of ferritin (as elaborated above) further increase intracellular iron storage capacity during systemic infection. This shift of iron into intracellular space is generally thought to increase host resistance against infection. Some bacteria though, accommodated to intracellular growth, may benefit from higher iron concentrations inside host cells [139]. Various studies provide evidence that in the light of specific (sub-) cellular localization of a pathogen, a differential response in terms of cellular iron metabolism is elicited in host cells [91,139,140,141]. This response depends on the primary intra- or extracellular localization of a pathogen and aims at starving the pathogen of iron, thus benefitting host defense [140,142]. In the case of infection with predominantly extracellular bacterial pathogens, the primary host strategy is to induce hypoferremia by upregulating cellular iron import and in parallel downregulating export [143]. In contrast, iron sequestration can be detrimental in the case of infection with intracellular pathogens, as the activation of the host response HAMP-FPN axis, which results in increased cellular iron sequestration, leads to enhanced intracellular pathogen growth [144]. Indeed, higher availability of iron in the pathogens’ cellular compartment is associated with increased growth in various models [145,146,147,148]. On this account, numerous studies have revealed differential cellular iron handling in the case of infection with intracellular pathogens. Specifically, the increase in iron export, mainly achieved by FPN induction, starves the pathogen and reduces intracellular bacterial proliferation [91,141,149,150,151]. This response is facilitated by at least two independent mechanisms: IFN-γ, primarily produced by activated natural killer cells and T-helper cells type 1, stimulates FPN expression and reduces TFR1 expression in infected macrophages [92,151]. During infection, nitric oxide species activate the transcription factor Nrf-2, which further promotes FPN induction [152]. Apart from FPN, NRAMP1 and DMT1 facilitate iron egress directly from the phagosome, making the metal less accessible for phagocytosed bacteria. Loss of these transporters alters cellular iron content and leads to higher iron availability to intracellular pathogens [153,154,155]. In the same line of reason, treatment with iron chelators has been shown to reduce intracellular bacterial growth, which may be therapeutically exploitable [144]. In addition to changes in systemic or cellular iron metabolism, the mammalian host produces effector molecules that directly compete with invading bacteria for iron, or inhibit bacterial iron uptake. Lactoferrin is one such example, binding iron with high affinity [156]. Exerting its effects mainly at mucosa, its bacteriostatic effects have also been evinced in an animal septicemia model [157]. Another compound at the center of iron-related host defense is the siderophore scavenger neutrophil gelatinase-associated lipocalin (lipocalin-2, NGAL). Produced by not only innate immune cells, but also epithelial cells, renal cells and hepatocytes, NGAL specifically attacks siderophore-dependent iron uptake, a major bacterial iron acquisition mechanism [158,159]. Siderophores (e.g., enterobactin) are secreted predominantly by gram-negative bacteria, bind iron in their environment with high affinity, and subsequently facilitate iron delivery to the microbe. Host-derived NGAL in turn binds and inactivates siderophores, thus disrupting bacterial iron acquisition and consequently stunting the pathogens’ growth [160,161]. Due to the key role of siderophores in a pathogen’s success, coevolution led to an immune evading mechanism of some bacterial species by producing alternative siderophores, which are not targeted by NGAL. Exemplary for this arms race, Klebsiella pneumoniae is capable of producing not only enterobactin, but also the alternative siderophores yersiniabactin and salmochelin. When this pathogen is challenged with host NGAL, expression of these alternative siderophores is an important virulence factor, enabling scavenging of iron despite the presence of NGAL and thus promoting infection [162]. Given the decisive impact of iron availability on bacterial infections, and the fundamental role ferritin provides in iron metabolism, its presence, regulation and distribution critically affect both the host’s and the pathogen’s success. In the main part of this review that follows, we will shine light on these factors and their implications for bacterial infection. Although the effect of iron on the course of infection has been investigated intensively [136], the fate of ferritin, as the main intracellular iron storage protein, during infection is less well understood. Ferritin has been determined to be utilizable as an iron source by many different types of bacteria (Table 1), including Yersinia pestis [163], Escherichia coli [164,165], Salmonella enterica serovar Typhimurium [165], Listeria monocytogenes [166,167], Burkholderia cenocepacia [168], Pseudomonas aeruginosa [169], Bacillus cereus [170], Streptococcus pyogenes [171] Vibrio vulnificus [172], Vibrio parahaemolyticus [173] and Mycobacterium tuberculosis [174]. In these studies, chelation [164,165,169,170,174] as well as reduction of the iron core [165,166,169] have been proposed as the most common mechanisms for the acquisition of ferritin-bound iron by bacteria. Furthermore, bacterial proteases play a role in the mobilization of iron in Pseudomonas aeruginosa and Burkholderia cenocepacia [168,169]. Proteolytic degradation might also be important in other bacteria [175], but its effect on iron acquisition has either not been tested or is difficult to assess due to unexpected effects of protease inhibitors on bacterial iron metabolism [165]. Additionally, Bacillus cereus binds ferritin to its surface, which facilitates the acquisition of ferritin-bound iron [170]. If such a binding of ferritin is also present in other bacteria, has yet to be determined, but might also be relevant for bacteria like Listeria monocytogenes, which acquires iron from ferritin via surface-associated ferrireductases [166]. While ferritin is a sufficient iron source for many pathogens, it may still constitute a relevant obstacle for bacterial iron acquisition [165]. These studies demonstrate that bacterial pathogens from at least three phyla are able to utilize mammalian ferritin as sole iron source in vitro. There are also some studies available, which assessed the interaction between ferritin and pathogens [176,177,178,179,180,181] (Table 1). Thereby, Neisseria menigitidis (Nm), Mycobacterium bovis, Chlamydia trachomatis, Chlamydia pneumoniae and Helicobacter pylori have been shown to colocalize with ferritin during intracellular infection [176,177,179,180]. Except for Nm, these findings are indicative of a direct extraction of ferritin-bound iron. Nevertheless, the exact mechanism of bacterial iron acquisition from ferritin has not been investigated in these studies. However, it is tempting to assume that mycobacteria may acquire ferritin-bound iron directly through such an association, as Mycobacterium tuberculosis has been shown to utilize ferritin as an iron source and to utilize extracellular as well as intracellular iron [174,182]. Nevertheless, there are studies which have investigated the role of ferritin as an iron source during infection with Nm, Ehrlichia chaffeensis (Ech), and uropathogenic Escherichia coli (UPEC) [178,180,181]. The study investigating UPEC showed that bacterial persistence in urothelial cells inside autophagosomes is facilitated by ferritinophagy and subsequent iron access to bacteria [178]. However, the authors also propose that UPEC is unable to sequester iron from ferritin. In contrast, a recent study demonstrated that another UPEC strain can use ferritin as a sole iron source in vitro [165]. This indicates that direct acquisition of ferritin-bound iron might also work for UPEC during infection. In the case of Ech, the pathogen secretes an effector protein, namely Ehrlichia translocated factor-3 (ETF-3), into the cytoplasm, which then binds to FTL and subsequently targets host iron stores to ferritinophagy [181]. Interestingly, Nm is not able to use ferritin as an iron source in vitro [183,184]. Still, Nm uses ferritin-derived iron as its main iron source during infection [180]. Thereby, it is speculated by the authors that Nm may trigger an iron starvation response and subsequently enhanced ferritinophagy, which enables Nm to acquire iron from degraded ferritin [180]. In conclusion, there is increasing evidence that ferritin may serve as an important bacterial iron source during infection, although hitherto only a small number of mechanisms have been identified. Unfortunately, most of the studies only focused on specific snippets of the whole picture, e.g., investigating whether a pathogen can use ferritin as its sole iron source or if a pathogen colocalizes with ferritin intracellularly, and were not followed up afterwards. Therefore, the role of ferritin at the host–pathogen interface remains largely unresolved for most of the investigated pathogens, emphasizing the need for further research. Salmonella enterica serovar Typhimurium is a typical model microorganism for infection with an iron-dependent intracellular pathogen. Although ferritin has not been directly investigated as an in vivo iron source yet [185], the pathogen’s mechanisms of invasion, persistence and replication have been thoroughly investigated [186]. Furthermore, a recent study found that S.Tm is able to utilize ferritin-bound iron via its diverse iron uptake pathways [165]. Therefore, we herein use this infection model as a ground to discuss the implications on ferritin metabolism for infection with intracellular bacteria and try to draw parallels to the diverse investigations with other model pathogens. In particular, we will focus on the Salmonella pathogenicity island (SPI)-1 mediated infection, because it is the most commonly investigated mode of infection. However, it is necessary to mention that there is a difference in the expression of virulence genes encoded on SPI-1 and SPI-2, depending on whether S.Tm enters the cell actively via SPI-1 or becomes phagocytosed, which can be facilitated by opsonization [187]. An extensive review on the intracellular processes during infection with S.Tm is provided by Knuff et al. However, we will go through the relevant steps below [186]. SPI-1 and SPI-2 encode syringe-like type 3 secretion system (T3SS), which S.Tm uses to transport effector proteins across membranes of host cells [186]. Prior to infection, S.Tm injects a cocktail of effector proteins via the SPI-1 encoded T3SS into the cytoplasm, which results in membrane ruffling and subsequent invasion of the pathogen into an intracellular membranous compartment termed the Salmonella-containing vacuole (SCV) [188,189]. Just after invasion, the early SCV is characterized by markers of the early endosome such as early endosome antigen-1 (EEA1) and Ras-related proteins Rab4, Rab5, Rab11 as well as TFR1 [190,191,192]. When S.Tm enters the cell using SPI-1, the SCV is damaged by the T3SS [193]. This damage results in recruitment of galectin-8 to the SCV [194]. The damaged SCV can then be repaired by S.Tm by utilizing the host autophagy machinery [195]. This repair is necessary for the activation of SPI-2 [195]. Upon maturation to the intermediate SCV, the vacuole loses the markers of the early endosome and acquires markers of the late endosome such as Lysosomal-associated membrane protein (Lamp)-1, Lamp-2, Lysosome integral membrane protein 1 (Limp-1, CD63), vATPase and Rab7 [190,196,197]. The effector proteins of SPI-2 then induce the final maturation step to the late SCV, which is associated with an extensive tubular system including the Salmonella-induced filaments (SIF) [198,199]. The formation of the SIF represents the completed establishment of the intracellular replication niche of S.Tm and coincides with enhanced metabolic activity and bacterial replication [198,199]. During infection with S.Tm, several host or pathogen-driven mechanisms may affect ferritin metabolism. These are depicted in Figure 3. Starting just after invasion, the SCV associates with the known ferritin receptor TFR1, which indicates that S.Tm may have access to ferritin from the onset of infection [119]. However, the damaged early SCV also recruits galectin-8, which may trigger secretory autophagy, in an effort of the host cell to prevent utilization of ferritin via a compartment shift [117]. Furthermore, this mechanism might be a more general one, because T3SS, which is responsible for the membrane damage, as well as other syringe-like secretion systems are employed by a large variety of bacterial pathogens [200]. Additionally, failure to repair such damage or to sustain the SCV results in cytosolic hyper-replication in permissive cells, e.g., epithelial cells. This might be facilitated by direct contact with cytoplasmic ferritin, which has been shown to significantly enhance bacterial growth of S.Tm [165,195,201]. In this context, cytoplasmic ferritin might also be a rich iron source for pathogens escaping their vacuolar compartment, such as Listeria monocytogenes, which has been shown to release ferritin-bound iron via surface-associated reductases in vitro [166,202]. The SCV enables S.Tm to acquire endosomal cargo from endocytosis-derived as well as intracellular vesicles [199]. Whether this is specific for S.Tm or might also be the case for other intracellular pathogens, which also reside in an endosomal/lysosomal-like compartment, has yet to be determined [203]. Given that some studies of such pathogens found a colocalization of bacteria with ferritin, this might be a more general mechanism in intracellular infections [176,177,179,180]. The uptake of endosomal cargo is enhanced by SPI-2 and even further with SIF, and is thought to provide nutrients for the replication of S.Tm [199]. Furthermore, this finding indicates that intracellular ferritin, which is trafficked via vesicles to the lysosome, might be delivered directly to S.Tm. Additionally, extracellular ferritin, which enters the cell via receptor-mediated endocytosis, might also be directed to the SCV. Moreover, the delivery of ferritin to the SCV might be enhanced depending on the efficiency of the uptake of extracellular iron via this mechanism, as the prevention of iron uptake from extracellular sources would result in induction of ferritinophagy by reducing the labile iron pool (LIP) in a similar manner as is proposed during infection with Nm [180]. A possible strategy of the host to counter this mechanism might be the utilization of DMT1. DMT1 has been shown to be expressed on the plasma membrane of macrophages and to transport iron directly form the extracellular space to the cytoplasm without the need for it to pass through an endosomal compartment [204]. This can be facilitated by local hypoxia, which increases DMT1 expression and local tissue acidosis, which improves the iron transport capacity of DMT1 [205,206,207,208]. Thereby, the LIP might be maintained just high enough to prevent ferritinophagy, but low enough to avoid enhanced bacterial growth via a concomitant upregulation of FPN [209]. The upregulation of FPN might then also trigger FPN-dependent mobilization of ferritin-bound iron and target ferritin for proteasomal degradation [104], which might represent a host adaptation against intracellular vacuolar pathogens. Furthermore, this might be an additional reason why nifedipine, which has been shown to increase DMT1-dependent iron uptake and subsequently promotes FPN expression and cellular iron egress, acts beneficially for the host in the case of infection with S.Tm [207,209]. Noteworthily, S.Tm aims to reduce Fpn1 transcription via its SPI-2 effector protein SpvB, which induces the proteasomal degradation of Nrf-2 [210]. Another possibility by which the host might utilize a compartment shift of ferritin is by secretion of ferritin via CD63-positive exosomes [115]. In line, a recent study found that macrophages secrete CD63-positive exosomes upon S.Tm-induced endoplasmic reticulum (ER) stress and subsequent lysosomal dysfunction [211]. Furthermore, these extracellular vesicles (EV) are enriched with TFR1, CD91 and CD163 to scavenge iron from the circulation [211]. However, it is hitherto not known if M1-derived EVs contain ferritin. Nevertheless, the fact that ferritin secretion via exosomes is CD63-dependent and CD63 expression is also regulated via the IRE/IRP system indicates that this might be the case [115,212]. In summary, there are many possibilities of how S.Tm might modulate ferritin metabolism to its advantage, but also numerous ways by which the host might counteract these efforts. Thereby, some of the mechanisms may be of a more general, intrinsic nature of intracellular bacterial infections, while others are Salmonella specific. The recent advances in our understanding of ferritin metabolism and the ever-expanding knowledge surrounding the pathomechanisms of bacterial infection open up many possible ways to investigate the role of ferritin at the host–pathogen interface. Although the proposed mechanisms, based on an infection with S.Tm, are hitherto in the realm of speculation, they are exemplarily for the branches future research may follow. Thereby, an important part of the whole picture would be to investigate the different modes of release of ferritin-bound iron. As explained above, cytoplasmic iron release and subsequent degradation via the proteasome, hitherto scarcely investigated, might be an important mechanism during infection. In this context, a knockout of TAX1BP1 could bring valuable insights, because it would supposedly abolish vesicular ferritin-trafficking and, as a consequence, ferritinophagy, while preserving the subcellular location of ferritin inside a liquid-phase condensate [93]. However, such a knockout would result in a different problem, as TAX1BP1 is also involved in the clearance of pathogens via xenophagy [213]. Another important aspect to investigate would be the role of CD63, as it is also regulated via the IRE/IRP system and is majorly involved in secretion via the MVB-exosome system. Thus, it might bring valuable insights into the route vesicular ferritin takes, be it secretion or degradation. A recent study found an increase of CD63-positive exosomes in serum during infection with S.Tm and Staphylococcus aureus in mice [211]. Furthermore, these exosomes possess TFR1, CD163 and CD91 on their surface and sequester iron from serum [211]. Moreover, this secretion is induced by ER stress and subsequent lysosomal dysfunction, which may be an important signal for secretion rather than degradation [211]. This is of interest because ER stress is a common feature found during many bacterial infections and has also been found in lipopolysaccharide (LPS)-induced inflammation, and thereby it might represent a more general host defense mechanism [214,215]. However, it has not been investigated if those EV also contain ferritin. Nevertheless, other proteins which may impede iron acquisition from ferritin, such as NGAL and superoxide dismutase, have also been found in extracellular vesicles [165,216,217,218]. Hence, it would be interesting to see if such proteins are also found in ferritin-containing exosomes. Further research should also investigate the role of galectin-8 and endo/lysosomal-like bacteria-containing compartments, because they represent mechanisms common during many intracellular infections [194,203]. Although the vesicular compartments differ from pathogen to pathogen, many associate with markers of the endo/lysosomal system, which might indicate that such vacuolar compartments have the intrinsic ability to acquire endosomal cargo via vesicle fusion, which is supported by the colocalization of ferritin with a variety of different pathogens [176,177,179,180]. Recent years have brought much insight into the mechanistic details of ferritin regulation, metabolism, secretion and uptake. This enables a more systematic approach for further research, whereby it will be easier to investigate and target specific mechanisms of ferritin metabolism in different situations. However, there is still much to learn, as specific branches of ferritin metabolism have not been followed up very much. For example, the diverse functions of ferritin at the crossroads of intracellular iron sequestration and immune metabolism in the context of infection have mostly been investigated secondarily. Nevertheless, a few studies have dared to directly investigate ferritin at the host–pathogen interface and could soundly demonstrate that ferritin is an important iron source for some bacteria. We are confident that advances in the knowledge of ferritin metabolism will facilitate future research and as a consequence provide a more holistic picture of nutritional immunity and the role of ferritin in infection and inflammation.

PMC10003480

Monika Karczewska,Patryk Strzelecki,Agnieszka Szalewska-Pałasz,Dariusz Nowicki

How to Tackle Bacteriophages: The Review of Approaches with Mechanistic Insight

23-02-2023

bacteriophages,contamination,eradication,phage decontamination,T4,phi6,phiX174,MS2,Lactococcus,lactic acid bacteria,Escherichia coli

Bacteriophage-based applications have a renaissance today, increasingly marking their use in industry, medicine, food processing, biotechnology, and more. However, phages are considered resistant to various harsh environmental conditions; besides, they are characterized by high intra-group variability. Phage-related contaminations may therefore pose new challenges in the future due to the wider use of phages in industry and health care. Therefore, in this review, we summarize the current knowledge of bacteriophage disinfection methods, as well as highlight new technologies and approaches. We discuss the need for systematic solutions to improve bacteriophage control, taking into account their structural and environmental diversity.

How to Tackle Bacteriophages: The Review of Approaches with Mechanistic Insight Bacteriophage-based applications have a renaissance today, increasingly marking their use in industry, medicine, food processing, biotechnology, and more. However, phages are considered resistant to various harsh environmental conditions; besides, they are characterized by high intra-group variability. Phage-related contaminations may therefore pose new challenges in the future due to the wider use of phages in industry and health care. Therefore, in this review, we summarize the current knowledge of bacteriophage disinfection methods, as well as highlight new technologies and approaches. We discuss the need for systematic solutions to improve bacteriophage control, taking into account their structural and environmental diversity. Bacteriophages (so-called phages) are considered the most diverse and abundant biological entities in the biosphere [1]. The estimated number of bacteriophage particles in nature is around 1031. Thereby, the relevant role of these viruses, which infect bacterial cells, cannot be neglected in several processes: (i) global ecology by controlling microbial population sizes; (ii) microbial evolution by promoting diversification and genetic transfer; (iii) scientific research, serving as models in molecular biology and providing experimental tools for analysis and manipulation of host cells at the molecular level; (iv) health system, as tools to control of microbial infections [2,3,4,5]. On the other hand, they are of great concern to the industry due to their negative impact on biofermentation processes, e.g., protein synthesis or the dairy industry [2,4,6,7]. Their role in microbial pathogenesis, as carriers of virulence genes transmission, is an ongoing challenge for the health care system. Phages can be classified based on their shape, genetic material, and mode of infection [8]. They can also be grouped into families based on shared genetic and structural features (Table 1). They are composed of a protein capsid that surrounds their genetic material, which can be either DNA or RNA. The capsid is often spherical or elongated in shape and can vary in size depending on the species of bacteriophage. Some bacteriophages also have additional structures, such as tail or tail fibers, that help them attach to and enter bacterial cells. Like all viruses, bacteriophages are very species-specific with regard to their hosts and usually only infect a single bacterial species or even specific strains within a species. Furthermore, when a phage attacks its prey, it can carry out either only a lytic or both lytic and lysogenic life cycle, whereby lytic phages kill host cells and lysogenic phages incorporate their genetic material into the host-cell’s genome [9,10]. The genetic material of bacteriophages is highly variable and can be replicated within the host cell, allowing the virus to reproduce and infect other bacteria. Once phage infects the host cell, it hijacks the bacteria’s metabolic pathways in order to propagate its particles. Bacteriophages have been used in medicine and biotechnology, including the development of bio-sensors, vaccines, antibiotics, and as a potential alternative to drugs in the treatment of bacterial infections and biofilms [11,12,13,14,15]. However, the knowledge of phage biology, especially for the model viruses, is well established and assumes their relevant contribution to antimicrobial resistance spreading among microbes [16,17,18]. Transduction by bacteriophages is one of many horizontal gene transfer mechanisms that promote genetic variation. While transmission of chromosomal DNA as a result of generalized transduction remains a rare phenomenon (approximately once in every 107–109 phage infections), the sheer abundance of existing phages and bacteria renders this process extremely frequent [19]. Even more importantly, this process relates to the spread of virulence genes and antimicrobial resistance [20,21,22,23]. According to the current knowledge, phage-related virulence of pathogenic bacteria involves classical type I membrane-acting superantigens, type II pore-forming lysins, and type III exotoxins, such as diphtheria and botulinum toxins as well as Shiga toxin. The uncontrolled and inappropriate use of bacteriophages capable of gene transduction can pose a threat to human life and health, and international initiatives have therefore established guidelines for the use of phages in therapy [24,25]. To date, disinfection methods and standards focused on the eradication of bacterial pathogens, but not bacteriophages whose distribution in medical and industrial environments is not sufficiently controlled. This review discusses various methods that so far have been developed to eradicate phages, from physical decontamination to controlling viral development within the host cell, with respect to their molecular basis. Some of these methods are universally employed in sterilization and sanitation processes to eradicate a broad spectrum of microorganisms. Typically, these approaches are tested on the model bacteria and viruses, which cannot be adequate for all pathogens. Moreover, we note that while phages have been traditionally seen as natural means of controlling bacterial populations, their ability to mutate and adapt to new environments has raised concerns about their potential to spread in environments where their presence is considered undesirable. Therefore, we state that a more systematic approach is needed to develop effective solutions to control phage spreading. The risk of bacteriophage infection can be reduced by several techniques, including sterilization by physical agents. We examined existing databases for physical factors affecting the stability of bacteriophages (Table 2), and in this chapter, we present the main methods used to inactivate them. We focus on the use of conventional techniques such as disinfection by heat, pressure, humidity, and UV light. The last method has become a rapidly developing chemical-free technology in recent decades. We pay particular attention to the use of filtration and to newly developed technologies with two important ones: non-thermal plasma processes and laser technologies. Temperature regulation is a well-known method that has been used for decades or even centuries as the main method of environmental microorganism inactivation; also, it is widely used in the food industry [26]. Most bacteriophage inactivation research is focused on the application of thermal disinfection [27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44]. Additionally, when using microwave radiation, it is the thermal effect that is associated with the inactivation of bacteriophages, compared to the application of radiation under non-thermal conditions [45]. Such conclusions were reached by Bryant et al. in an attempt to explain the mechanism of inactivation by microwave radiation of bacteriophage T4 that occurs within 20 s when compared to control samples treated on ice [45]. The mechanism of inactivation is most likely related to damage of the capsid, but before reaching the melting point, DNA is released [39,40]. The most studied application of this disinfection method is the control of bacteriophages infecting lactic acid bacteria (LAB) [46]. Among these bacteriophages, there are some that can survive pasteurization due to their high heat resistance, e.g., P680, P1532, and P008 [31,33,47]. Another interesting finding from these studies is the importance of the culture medium and its composition for bacteriophage inactivation efficiency. In the presence of fat, phage survival increases which is related to its protective effect by keeping the particles moist [27,28,29]. Such conclusions were reached, among others, by Muller-Merbach et al., who inactivated the model phage P008 in selective M17 broth and milk. In the case of M17 broth, the higher the temperature used, the faster the inactivation progressed. Exposure to 55 °C led to a 1-log reduction within 3 h. Under short-term pasteurization conditions (i.e., 30 s at 75 °C), about 1 log of the phage population was inactivated, with a 7-log decrease after 6 min at this temperature. In comparison, inactivation in milk proceeded more slowly. At 55 °C, the phage titer hardly dropped even after 24 h, and short pasteurization conditions reduced the P008 titer by less than 1 log [27,28,29]. UV radiation has been a validated technology for disinfecting surfaces as well as in air and water. It can eradicate a wide range of microorganisms. UV radiation is becoming an increasingly affordable method that yields reproducible significant reductions of infection [48,49]. Factors that may be involved in phage susceptibility to UV wavelengths are the type of nucleic acids (DNA or RNA), genome structure (single- or double-stranded), guanine and cytosine content, lipid envelope, the size of the viral particle, as well as other features of molecular structure. Therefore, in general, bacteriophages containing single-stranded RNA or DNA are more sensitive to UV radiation than phages containing double-stranded RNA or DNA. Tseng et al. determined in their study that the UV dose causing 99% inactivation was twice as high for phages containing ssRNA/DNA (MS2 and ΦX-174, respectively) than for dsRNA/DNA (Φ6 and T7, respectively) [50]. For all four virus types, the survival fraction decreased exponentially with increasing dose, by either increasing the UV intensity or exposure time. Toxic UV photoproducts are usually thymine dimers, so RNA viruses are more resistant to UV damage than DNA viruses [51], with the UV dose causing 99.9% (4 log) reduction in bacteriophages for MS2 (RNA) versus PRD1 (DNA) was 65.2 and 31.6 mW/cm2, respectively. Similar results were observed [51,52,53,54,55,56] when MS2 or Qβ phage (RNA) was compared with ΦX-174 (DNA), obtaining results with higher UV sensitivity for DNA bacteriophage. Therefore, each bacteriophage may have different susceptibility to UV dose, and this affects the effectiveness of the UV disinfection [57,58,59]. Ultraviolet waves spectra are not exclusive for inactivation of bacteriophages. Several reports demonstrating phage sensitivity to visible light (VL) at 405 and 455 nm have been published [60,61,62]. Inactivation of microorganisms under visible light can be associated with photodynamic inactivation (PDI) where a photosensitizer is excited by specific wavelengths of visible light in the presence of oxygen that leads to the production of reactive oxygen species (ROS), ultimately resulting in structural damage. Tomb and colleagues studied the effect of violet-blue light on the reduction of phage ΦC31 (genetic material on form of dsDNA) [61]. For the 103 PFU/mL, they achieved a 2.7 log reduction after exposure to 0.3 kJ/cm2, while ΦC31 titer of 105 and 107 PFU/mL were successfully decreased by ~5- and 7 log after exposure to doses of 0.5 and 1.4 kJ/cm2, respectively, by 405 nm light. It should be noted here that the inactivation was effective if the phage was suspended in liquids or substrates containing appropriate light-sensitive components (photosensitive porphyrin molecules), while no reduction in phage titer was observed when suspended in PBS. However, the study by Vatter et al. demonstrated inactivation of the enveloped virus Φ6 at 7.2 kJ/cm2 [60]. The phage titer was reduced by more than three folds within 40 h without the addition of photosensitizers [60]. However, Φ6 phage differs in genetic material structure (dsRNA) and the presence of an envelope, which is in line with previous reports that the structure of a bacteriophage affects the conditions of the observed inactivation efficiency. Phage-inactivating agents can also be used in combination with other technologies to increase disinfection efficiency, so the use of UV or visible light with ultrasound (US) shows synergistic effects. This has been proven by the study in which the simultaneous application of US and VL was more effective than US alone for MS2 inactivation [63]. Moreover, along with UV light, synergy has been shown in combination with US (bacteriophage from Klip river) [64], ozone (MS2 bacteriophage) [65], or silver ions (MS2 bacteriophage) [66]. The effect of pressure on bacteriophages appears to be effective at values greater than 300 MPa [67,68]; this has been particularly studied for lactic acid bacterial phages, which were resistant to pressure ≤100 MPa [69,70,71,72]. Electron microscope images showed shrunken phage heads containing or lacking DNA after applying pressure on T4 phage [73]. The least effective appears to be the impact of humidity, since many additional factors affect its efficiency, such as the structure of the bacteriophage. The survival rate of the non-sheath phage MS2 turns out to be better than that of the enveloped phage Φ6 [74]. The pH, presence of proteins and environmental factors also have an impact of phage sensitivity. Bacteriophages survive in the range of low and high values of relative humidity, which in addition is often correlated with temperature, and only the intermediate value of humidity is effective in virus eradication, which is also dependent on the phage type. While salt, pH and surfactant reduced survival under wide range of humidity conditions, proteins provided some protection against phage particles degradation [74,75,76,77,78,79,80,81]. Thus, the effect of chemical composition has a significant impact on relative humidity effectiveness, highlighting the importance of simultaneous investigation of different factors in bacteriophage survival. Filtration technology is not a new invention; however, due to a rapid development through modifications of membrane elements, it has been continuously improved in terms of performance over past 50 years. New materials with improved chemical and thermo-mechanical properties and better permeability and selectivity are increasingly applied. The development of membranes significantly increases the range of applications of filtration, hence in the literature one can find many studies on the use of the technique in industry, which includes purification of water and dairy products as well as wastewater and air. It is also being used in the production processes, the environment, and public health applications [82,83]. The rapid development of nanotechnology has sparked great interest in nanomaterials, which are excellent adsorbents, catalysts and sensors due to their large specific surface area and high reactivity. Several natural nanomaterials have been shown to have strong antimicrobial properties. These include, for example, carbon nanotubes (CNTs), which can enhance membrane filtration [84,85]. CNTs are graphene sheets, either single-walled (SWNT—single tube) or multi-walled (MWNT—several packed tubes) [86]. Research by Brady-Estevez et al. has shown that bacteriophages are removed by the CNT filter matrix through a deep filtration mechanism, that is, captured by bundles of nanotubes inside the SWNT layer [87]. The filter was developed using a microporous poly(vinylidene fluoride) (PVDF)-based membrane coated with a thin layer of SWNTs. A model virus particle, bacteriophage MS2, with a diameter of 27 nm, was employed and the results indicated complete removal of bacteriophage particles. This thickness of the SWNT layer removes 107 virus particles per mL (5–7 log) [87]. However, the removal of MS2 bacteriophages by the MWNT filter was 1.5 to 3 log higher than that observed in SWNTs [88]. Brady-Estevez et al. also determined the efficiency of the SWNT-MWNT hybrid layer on different bacteriophages, i.e., MS2, PRD1 and T4, which have different structures, ribonucleic acids, diameters, and isoelectric points [89]. The hybrid filter was expected to be more similar to the performance of the MWNT filter, since the nanotubes were made of 83% MWNT and only 17% SWNT, and SWNT alone had a much lower efficiency. However, the SWNT–MWNT dual filter performed better than the 100% MWNT filter, and is effective against a wide range of bacteriophages [89]. Nevertheless, the complex chemical compositions of solutions and the presence of impurities can affect filter performance. Phage removal increased at higher ionic strengths (NaCl) due to suppression of repulsive electrostatic interactions between viruses and nanotubes. The addition of divalent salts, on the other hand, had opposite effects. While CaCl2 increased the removal, probably due to the complexation of calcium ions with the phage surface, the addition of MgCl2 decreased the phage eradication [90]. This effect was also observed in other cases, and it was determined that SJC3 phage filtration was strongly dependent on the concentration and valence of the dominant cation in the pore fluid. While using a filtration system consisting of quartz sand-filled columns, column retention increased from 0% to 99.99% when the electrolyte composition was changed from NaCl to CaCl2 [91]. Another modern technique is femtosecond laser irradiation. These are ultra-short laser pulses that show great potential for disinfection. Work by Tsen et al. has shown that femtosecond infrared and visible lasers can inactivate phages, and they attribute this to a mechanism called pulsed stimulated Raman scattering (ISRS) [92,93,94,95,96,97,98,99]. It appears that during ISRS, vibrational excitation of the capsid and disruption of the protein coat occur. The sample’s exposure time to laser radiation in the study by Tsen et al. was about 1 h or longer and resulted in a 5-log reduction of M13 phage titer [95]. Gel electrophoresis results indicated that laser irradiation does not change the structure of single-stranded DNA but leads to the breaking of hydrogen/hydrophobic bonds or the separation of weak protein linkages in the envelope [95,98]. More recently, Berchtikou et al. used millijoule laser pulses (40 fs) with different exposure times (1–15 min) and different wavelengths (800, 400 nm separately of combined), pulse energy ~20 mJ, and repetition rate of 10 Hz [96]. According to data presented, the 4-log reduction of phage titer took 31 min with 800 nm wavelength of laser used. Further evaluation showed that longer exposure times and shorter excitation wavelengths result in greater reduction of viral counts. The maximum observed inactivation about 6 log was obtained using a femtosecond laser with a wavelength of 400 nm, energy of 20 mJ, and pulse width of 40 fs, after 15 min of exposure. The authors deduced that virus inactivation increases with increasing irradiation energy density and shortening wavelength [100]. A promising approach to sterilization and disinfection is the use of atmospheric pressure non-thermal plasma (APNTP). APNTP has potential advantages over standard chemical disinfectants and sanitizers. First of all, it uses non-toxic gases and is known for the absence of toxic products during its process. The effectiveness of disinfection is related to the generation of a large number of different active agents, including chemically reactive forms (oxygen and nitrogen), UV or electromagnetic fields [101]. There are several reports on the effectiveness of APNTPs in inactivating bacteriophages. Venezia et al. obtained a reduction in the PFU/mL of λ C-17 and lytic bacteriophage (Rambo; Microphage) by at least 4–6 logs after 10 min of exposure [102]. On the other hand, Yasuda et al. observed inactivation of λ phage by 6 logs after 20 s using stable plasma generated by dielectric barrier discharge (DBD) [103]. Both of these studies detected nucleic acid damage, as well as changes in coat proteins. During the investigation what factors could improve the efficiency of inactivation by plasma, it was found that the percentage concentration of oxygen in the carrier gas was positively correlated with the rate of phage inactivation (MS2). Namely, oxygen concentration (0.75%) and 3 min of exposure to a plasma source operating in a helium/oxygen gas mixture (99.25%:0.75%) resulted in 99.9% reduction of MS2, additionally, increasing the time to 9 min resulted in >7 log inactivation. Moreover, interesting results of pre-activation of water with plasma were also presented. Water was pre-treated with plasma (for 120 s for T4 or 80 s for Φ174 and MS2) and then mixed with suspensions of tested bacteriophages. After incubation for 4 and 8 h with such prepared water, the titer of bacteriophage T4 was reduced by about 7.2 and 8.8 orders of magnitude, respectively, indicating that the process was time-dependent. The titers of active bacteriophages Φ174 and MS2 decreased close to the detection limit. Moreover, the action of plasma alone for 100 s completely abolished the infectivity of bacteriophage T4 suspension, and a similar effect for the other two phages was obtained after 60 s [104]. Inorganic compounds have been known for their antiviral properties for centuries. Gases such as ozone [161] or carbon dioxide [162,163] and metals were studied for their ability to combat bacteriophages. Most common metals used in these processes are silver [164,165,166], copper [165,166,167], and iron [168,169,170,171,172]. Many of them and their oxides and salts have been extensively studied for their ability to inactivate series of different bacteriophages such as MS2, Φ6, Φ8, PP7, ΦX174, PM2, T4, T7, and Qβ. Those and other prominent agents used to inactivate bacteriophages are summarized in Table 3. With new emerging technologies and manufacturing techniques there are possibilities to create various combinations and modifications of metals that can provide new effective ways to combat viruses. One of the most promising fields is nanotechnology that allows to create nanoscale particles of metals that with unique properties differ from the input material that has been used to synthesize them. The most recent and innovative methods are described in the next sections. Nanotechnology is an emerging field that gained significant attention in recent years. A series of nanoparticles (NPs) have been already developed with a variety of potential applications [173]. The most common group of nanoparticles are based on metal such as silver, copper and gold. The properties (size, shape, and coating) of NPs strongly determine their potential application. Currently, nanotechnology is being used in a range of areas such as the manufacturing of materials, electronics, energy harvesting, the mechanical industry as well as drugs and medications [174,175]. As their precursor metal NPs have the ability to inactivate pathogens so a series of works provided data on their ability to inactivate bacteriophage lysates. AgNPs are of the most promising class because of several properties such as electric conductivity, antimicrobial activity, high surface to volume ratio, swelling, and contraction flexibility [176]. Their ability to combat viruses is highly dependent on their size with smaller NP being the most effective [177]. One of the works by Gilcrease et al. from 2020 demonstrated that silver nanoparticles negatively affected phage lytic growth cycle [178]. In the experiments involving a series of bacteriophages RG2014, KL, Det7, P22, SP6, and 9NA, uncoated bare silver nanoparticles reduced infection yields of phage RG2014 by 89% and phage KL by 92.4% after 70 min of infection. Polyvinylpyrrolidone-coated (PVP) silver nanoparticles reduced the post infection PFU/mL of RG2014 by 74%. Interestingly, PVP-coated AgNPs increased the yield of phage KL by 92%. However, phages P22, 9NA, SP6, and SF6 were less sensitive to NPs action. It was then suggested that the exposed regions of the viral coat proteins of RG2014, KL, and Det7 may share nanoparticle binding features (strong enough to overcome the weaker repelling forces between the negatively charged surfaces of phage and nanoparticles) that other phages do not possess. Further studies showed that the difference between affected and unaffected phages lay in their structure, namely the presence of overhanging positively charged capsids’ protein C-terminus., which facilitated the binding of nanoparticles [178]. Moreover, according to presented data, AgNPs and their ions also significantly affected phages at concentrations and incubation times in culture low enough to not affect their host growth. This definitely increases the chances of exploiting NPs in, e.g., biofermentation processes. The effectiveness of smaller nanoparticles has been confirmed in another work by Gokulan et al. from 2018 focused on MS2, PP7, and ΦX174 bacteriophages [179]. Effectiveness was dependent on the size and dose of NPs as well as on the temperature. All bacteriophages were more susceptible to the AgNP-mediated killing at 37 °C as compared to 4 °C. Exposure of MS2 phages to high dosage of AgNP at 37 °C resulted in the absence of PFU after 14 days, whereas at 4 °C, there was no difference in the PFU formation by MS2 during the treatment of any dose of AgNP; however, there was a clear difference between the control and AgNP-treated MS2 phages after day 2 (reduction of around 2–3 logs after 28 days). The PP7 phages appear to be more susceptible to AgNP at high and medium doses–these phages were completely inactivated at 37 °C after 14 days. At 4 °C, only 1–2-log decrease in the PFU/mL was observed [179]. All these data show that inactivation differs not only between bacteriophages but also depends on the time and temperature. There are several reports that show potential of combining AgNPs with different materials to give them new unique properties. For example, glycoprotein, curcumin, and stabilizers can be added to AgNPs to improve their antimicrobial potential [180,181,182]. In the work from 2018 Park et al. designed a silica hybrid composite decorated with AgNPs [183]. The antiviral effect has been studied with the use of MS2 bacteriophage. After 24 h of exposure, phage titer was reduced more than a 3 log. Released Ag+ ions, originating in nanoparticles, can contribute to strong antiviral capabilities. AgNP could be easily recovered in water conditions via sedimentation or centrifugation, and in addition, these particles can be reused, which means that AgNP-SiO2 particles could be more effective and environmentally friendly tool to control waterborne viruses [183]. The effectiveness of NP-Ag-CuO was tested by Shimabuku et al. in the works published in 2017 and 2018 [184,185]. The antiviral activity has been checked with the use of the granular activated carbon (GAC) modified with silver and/or copper oxide nanoparticles. The porous media containing silver and copper oxide nanoparticles showed inactivation reaching reductions higher than 3 logs [185]. GAC filter itself has only a potential for a reduction of 0.32 log [186]. The presence of copper oxide nanoparticles did not improve the efficiency of virus particles inactivation. The use of 1% AgNP increased inactivation by 0.64 log. However, values higher than 3.02 log in PFU/mL reduction was showed for the combination of both silver and copper oxide mixtures. The most efficient combination (1% Ag and 1% Cu) reached a reduction value of 5.56 log. This effect is most likely caused by the released ions, ROS, or both [184,185]. A series of works focus on gold-based nanoparticles. One of them by Richter et al. from 2021 presents nanoparticles that deactivate bacteriophages and at the same time are safe for host bacteria [187]. It has been shown that AuNPs coated with a mixture of negatively charged 11-mercapto 1-undecanesulfonic acid (MUS) and hydrophobic 1-octanethiol (OT) ligands are effective in deactivating various types of Escherichia coli selective phages: T1, T4, and T7. The titer of phages can be lowered even to 2 logs in 6 h and 5 logs in 24 h. The most effective combination MUS:OT (85:15) required just a step of 1 h preincubation at 50 °C to fully deactivate T1 phages. MUS:OT nanoparticles were not effective against MS2 bacteriophages that lack the complex head-tail structure. The mechanisms of deactivation were based on initial electrostatic attraction followed by hydrophobic interactions causing local irreversible distortions in the phage heads [187]. Nanoscale zero-valent iron (nZVI) due to its size, surface effect and quantum size effect has a various applications including inactivation effect on bacteriophages [162,188,189,190,191]. In the study from 2018 by Cheng et al., the Fe/Ni nanoparticles (Fe/Ni NPs) and (nZVI) were assessed for their antiviral ability on f2 bacteriophages [190]. Fe/Ni NPs had higher deactivation efficiency and after 30 min of their action, bacteriophage was removed. It took 1 h for nZVI to reach the same point, while NiNPs showed no effect. Further studies showed that Ni0 in the Fe/Ni NPs facilitated the removal of phage f2 by induced production of ROS as a catalyst. To better understand the basis of this interaction, the influence of pH and oxygen was assessed. Efficiency was higher under aerobic conditions than that in the anaerobic system which can be connected to the fact that ROS generated from the oxidation of Fe0 and the catalysis of Ni0 are responsible for the inactivation mechanism. The changes in pH did not have an influence on effectiveness. As for changes in the temperature, it improves the reaction rate at the initial stage but decreases the removal efficiency due to the accelerated corrosion of iron. The inactivation mechanism of bacteriophage f2 by Fe/Ni NPs was related to the ROS generated from the oxidation of Fe0 and the catalysis of Ni0 [188,189,190]. Another work by Kim et al. from 2011 proved the effectiveness of nZVI on MS2 coliphage [172]. The inactivation of MS2 was much greater under air-saturated conditions (5.3 log) than under deaerated conditions (2.6 log). This is consistent with damage by reactive species formed via oxidation of nZVI. Unlike f2 phage, the inactivation of MS2 increased as pH decreased. The addition of 1,10-phenanthroline completely blocks oxidant formation. The reduction still occurred after the addition of this compound which proves that the mechanism of action must be also connected to the direct interaction and physical disruption caused by the nanoparticles [172]. Most recent study by Cheng et al. compared the influence of nZVI on MS2 and ΦX174 containing RNA and DNA, respectively [191]. It has been found that an initial concentration of 106 PFU/mL of MS2 could be completely inactivated within 240 min, but the complete inactivation of ΦX174 could not be achieved by extending the reaction time, increasing the concentration, or changing the dosing means. Three-dimensional fluorescence spectrum and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) have been used to examine the mechanism of nZVI action. The nucleic acid analysis demonstrated that the genome of MS2, but not ΦX174, was destroyed. It indicated that bacteriophage inactivation was mainly attributed to the damage of their genetic material [191]. Work from Raza et al. showed that the activity of zero-valent iron varies strongly against different phages and that different forms of ZVI, namely pristine (reduced) ZVI, PO ZVI (ZVI nanoparticles that were exposed to air and oxidized while incubated with phages), and O ZVI (oxidized ZVI, which was completely oxidized before the addition of phages) are also impacting bacteriophages in different ways [192]. M13 is very vulnerable to all studied forms of ZVI, whereas T7 appears almost completely resistant. T4 and T7 belong to the same class (Caudoviricetes), yet significant inactivation of T4 is observed. Pristine ZVI is active against M13 and T4, but not T7 and MS2. In the case of T4, PO ZVI shows much lower activity compared to ZVI and O ZVI. All of these findings show that when using nanoscale zero-valent iron to inactivate bacteriophages a series of factors need to be considered which limits the spectrum of these methods. With the development of new techniques, materials processing has been significantly upgraded in recent years [193]. The use of, for instance, selective laser melting (SLM), aimed at using a high-power density laser to melt and fuse metallic powders, or plasma sintering (SPS), a synthesis technique that uses low voltage and direct current, has had a significant impact on producing a new range of materials and bringing them into wider use [194]. Materials with improved and more effective antiviral properties are intensively studied [195,196]. Rahmani and coworkers presented a method of phage inactivation based on the use of SLM and SPS to fabricate new materials, so-called metal matrix composites (MMC) [196]. Silver-doped titanium dioxide (TiO2 + 2.5–10% Ag), copper-doped titanium dioxide (TiO2 + 2.5–10% Cu), Cu2NiSiCr, Cu15Ni8Sn as well as pure copper spark plasma sintered discs were tested for their virucidal abilities on Φ6 bacteriophage. Phage inactivation on MMC surfaces corresponded to 99.99% and above was observed, and its effectiveness was related to the composition of the material used. Initial virus titer 1010 PFU/mL on the TiO2 + 10% Ag ceramic and CuNi2SiCr metal discs decreased by 4 logs after 15 min. Another work from the same team tested two different materials created with the use to the same technique to evaluate the effectiveness of 45% TiO2 + 5% Ag + 45% ZrO2 + 5% Cu and Co28Cr6Mo [195]. The two disks adsorbed all of the added virus suspensions during the 15-minute incubation. The surface infiltration time by the virus suspension was particularly short (3–5 s) on used Co28Cr6Mo metal disks. A total number of viruses attached to the disk, was still significantly higher than that in control steel disks, proving virucidal properties of studied material. When 108 PFU were added to the 45% TiO2 + 5% Ag + 45% ZrO2 + 5% Cu disk surface, most viruses infiltrated the disk. The authors suggest that 99.99% of viruses, placed on the surface, were either irreversibly attached or inactivated, therefore possessing no threat to potential host cells. TiO2 photocatalyst has been proven to be effective in water disinfection [197]. In particular, this technique leads to generation of reactive oxygen species as a virucidal factor. Pure TiO2 can only be activated by light in the near UV range. To overcome this problem, researchers found that metal doping (e.g., V, Cr, Cu, Co, Ag, and Au.) is an effective method to extend the spectral response of TiO2 to the visible region, as well as decrease the electron-hole recombination rate [197,198,199,200,201]. Ditta et al. studied the photocatalytic activity of TiO2-, CuO and hybrid CuO/ TiO2 prepared by atmospheric Chemical Vapor Deposition (Ap-CVD) coated surfaces and TiO2 prepared by a sol–gel process against T4 bacteriophage [201]. Employed the sol–gel coated glass deactivation of virus particles by 6 logs was observed after 2–4 h. Moreover, they showed the improved results using CVD CuO coated samples. Efficiency of phage particle reduction by over 6 logs was obtained in shorter time (80 min). Furthermore, combination of TiO2 and CuO provided higher inactivation of >9 log after 80 min. The combination of photocatalysis and toxicity of copper acted synergistically to inactivate T4 bacteriophage [201]. In their work, Zheng et al. investigated the activity of prepared Cu-TiO2 nanofibers under visible light against bacteriophage f2 [202]. All viruses were inactivated within 240 min when the initial concentration was 105 PFU/mL. The removal efficiency reached 2.5 log in 240 min with the initial concentration being 107 PFU/mL. The results indicated that the initial pH did not impact the disinfection performance significantly. In the certain range, the removal efficiency increased with the increase in catalyst dosage, light intensity and temperature, but decreased with the increase in initial virus concentration. Free oxygen radicals have been shown to play a crucial role in phage f2 inactivation as well [202]. Materials with antiviral properties have a wide range of application. The ability to implement them into frequently touched surfaces may be a powerful tool in prevention of unwanted bacteriophages propagation and/or distribution. Disinfectants based on organic compounds (Table 4) are commonly used to eradicate viruses and microorganisms from a variety of surfaces [211,212]. Among them, the best-known group are alcohols such as ethanol and isopropanol, characterized by relatively low toxicity and broad commercial distribution. With respect to the mechanism of action of ethanol, a study conducted by Maillard et al. showed capsid alterations on F116, a phage infecting Pseudomonas aeruginosa [213]. However, Halfhide [214] reported that 75% ethanol inactivated Myoviridae to levels below the detection limit, but did not cause more than a log reduction in Siphoviridae, highlighting the variability in ethanol’s efficacy against phages (taxa of this family no longer exist in phage nomenclature; species now belong to class Caudoviricetes). These observations clearly illustrate that it is imprudent to predict the efficacy of ethanol as a disinfectant against a specific phage. Quaternary Ammonium Compounds (QACs) are popular sanitizers that can be used on certain food contact surfaces at home and industry due to their low toxicity. Cetyltrimethylammonium bromide (CTAB) is a class of aliphatic quaternary ammonium compounds which have a strong antimicrobial activity [215,216]. Study by Sands [216] showed a virucidal potency of CTAB against several bacteriophages (PM2, φ6, T4, PR4). The 3-log reduction of 106 PFU/mL lysates was obtained after 15-minute incubation in 37°, but was dependent on both the compound concentration and phage type. The PM2 and φ6 phages were more sensitive to treatment than T4 and PR4. The more recent evaluation of CTAB activity was conducted by Ly-Chatain and colleagues targeting Lactococcus phage P001 (c2) associated with contaminations in the dairy industry [215]. After 1 min of contact with 0.125 mM CTAB, the c2 population was reduced from 6 to 1.5 log PFU/mL, and at 1 mM, concentration of CTAB phages were undetectable. However, the potency of CTAB was impaired in acidic pH and with an increased ionic strength of the medium. The authors explained this observation by the electrostatic interactions between cationic compounds and negatively charged particles such as bacteriophages or other compounds in a matrix. Activity of benzalkonium chloride-based QAC against 8 dairy phages infecting L. lactis (CB13, AF6, P1532, P001), Lactobacillus (B1) and streptococcal strains (2972) was also studied. The sanitizer potency was determined from 3 log to 6 log reduction within 15 min [212]. Moreover, this examination was conducted in the presence of 1% milk to mimic the dairy processing conditions. Aldehydes such as glutaraldehyde or formaldehyde have been extensively used as disinfectants because of their broad spectrum of bactericidal, virucidal, fungicidal and sporicidal activity. Their biocide activity is based on the alkylation of hydroxyl, carbonyl and amino groups which affects DNA, RNA and protein synthesis. Moreover, glutaraldehyde is routinely used as a cross-linker due to its amine-binding ability. Maillard et al. [217] tested an efficiency of glutaraldehyde against MS2 and K coliphages and showed 4.1 to 5.2 log reduction of 108 PFU/mL lysates (at 20 min) treated with 1% and 0.5% mixture respectively. It was in line with Jette et al. observations which demonstrated activity of glutaraldehyde-based disinfectants against phage f2 with 4 log particles reduction after 5 min and over 8-log reduction after 40 min [218]. Phytochemicals are a diverse group of naturally occurring chemical compounds found in plants [219,220]. These compounds have a wide range of biological properties, including antimicrobial and virucidal activities. The mechanisms of action of phytoncides vary, but they have been shown to disrupt the cell membrane, inhibit protein synthesis, modulate gene expression, and disrupt DNA replication, ultimately leading to the death of the microorganism. Overall, phytochemicals have significant potential as natural alternatives to synthetic disinfectants and antimicrobial agents [219,221]. The diversity of mechanisms of their action is presented in Table 4. Virucidal disinfectants based on phenolic compounds present variable impact on phage development [222,223]. Phenol and its derivatives have antifungal and antiviral properties. The breakdown of the plasma membrane, which allows the leakage of intracellular substances, is thought to be responsible for their antimicrobial effects. It was showed in study by Morita [223] that various phages were inactivated by polyphenols in the presence of cupric ion. The sensitivity of each phage to polyphenols was different. The T-odd series of phages were rapidly and efficiently inactivated by pyrocatechol at 37 °C. Phages fd and φX174 were less sensitive to pyrocatechol than the T-odd series. The results implicated that that free radicals of polyphenols and hydrogen peroxide are involved in phage inactivation. On the other hand, Maillard and colleagues showed that phenol has a moderate effect on the transduction of P. aeruginosa PAO by bacteriophage F116, has no effect on phage DNA within the capsid and no effect on various phage strand proteins unless the treatment lasts 20 min or longer [222]. A different perspective on the antiviral activity of polyphenols is presented by studies where plant secondary metabolites were employed. In a cross-study, Philippe and colleagues evaluated natural polyphenols activity (namely, quercetin, myricetin, p-coumaric acid, cinnamic acid, and kaempferol) against Vinitor162 and OE33PA bacteriophages of lactic acid bacterium Oenococcus oeni [224]. Seven polyphenols identified in their study inhibited the lytic propagation of OE33PA by an interference with its adsorption to the host cell. In contrast, any of the compounds showed activity in the presence of the distinct phage Vinitor162. In untreated cultures, Vinitor162 could lyse O. oeni after 20 h of incubation. Thus, the authors hypothesized that activity of polyphenolics is most likely related to phage OE33PA membrane receptor p2 block by the tested compounds [224]. This was further supported by a molecular docking analysis. Silva-Beltrán et al. in their study elucidated effects of tomato byproducts rich in polyphenolic agents (gallic, caffeic acids and quercetin) against E. coli bacteriophages MS2 and Av-5 [225]. Extracts showed an ability to reduce phage titer down to 6 logs [225]. Polyphenols exhibit activity to bind proteins, thereby forming protein-phenol aggregates [226]. More importantly, some agents were shown to impair the phage’s life cycle within its host. Such examples of specific activity have been demonstrated for representatives of flavones (e.g., quercetin, myricetin, and epigallocatechin) where arrest of DNA polymerase activity was observed [227]. Moreover, Yang and colleagues in their recent work showed epigallocatechin gallate impact on SOS response repression in E. coli resulting in the arrest of the development of phage 933W [228]. Catechins, also flavone compounds, were considered as antiviral agents in manufacturing cleaning wipes and filters as they showed biocide activity against T4 and T7 phage [229]. It was in line with mentioned above study by Morita of pyrocatechol virucidal potential [223]. Polyphenolic compounds showed wide range of antiviral activity [230,231] among them flavonoids emerge as the most promising agents for modulating bacteriophage development within its host. However, the full nature of the interactions of polyphenols with regard to their structure is still not fully evaluated. In particular, the basis of interaction with the virion particles or the effect on the stages of bacteriophage development remains to be elucidated. As presented above, catechins were able to affect phages in both ways depending on the particular strain. Isothiocyanates (ITCs) are a most prominent group of bio-active compounds synthesized as a breakdown product of glucosinolates—sulfur rich phytochemicals originated from Brassicaceae plant family. ITCs are recently a subject of extensive studies due to their broad health benefits such as anticancer, anti-inflammatory, neuroprotective as well as antiviral and antibacterial potential [232,233,234,235,236,237]. The evaluation carried by our group revealed a potent activity of ITCs to impair the development of lambdoid E. coli phages [238,239]. This phenomenon is related to ability of ITCs to trigger a bacterial stress response (called a stringent response) mediated by small nucleotide alarmones (p)ppGpp [240]. (p)ppGpp molecules affect bacterial mechanisms of metabolism adaptation in response to environmental stresses such as nutrients deprivation. We showed that in the presence of ITCs (namely, sulforaphane, phenethyl-, allyl-, and benzyl-isothiocyanate), E. coli cells behave like under amino acid starvation conditions responding with elevated level of alarmone synthesis [238,239]. In general, the host cell starvation is an effective method to disrupt coliphages lytic development as demonstrated in comparative study by Los and colleagues [241]. However, Potrykus et al. precisely showed that induction of stringent response affects the expression from phage λ promoters which has consequences in virus progeny [242]. It was in line with our study describing (p)ppGpp negative impact on development of other lambdoid phages 933W and φ24B [243]. Moreover, the activity of ITCs not only results in inhibition of virus propagation but in that particular case also impairs the virulence of Shiga-toxigenic E. coli, which pathogenicity is related to bacteriophage development. Fruit extracts have been shown to be effective disinfectant agents against bacteriophages due to their natural origin and high concentration of phytochemicals. These phytochemicals, such as phenolic compounds and tannins, have been demonstrated to exhibit antimicrobial activity against a wide range of bacteria and viruses. In addition, the combination of these phytochemicals within an extract can often exhibit a synergistic effect, resulting in an even greater antimicrobial activity. One of the main advantages of using fruit extracts as disinfectants is their broad-spectrum activity, meaning they are effective against a wide range of microorganisms. This is particularly useful in the control of bacteriophages, which are difficult to eliminate due to their ability to infect and multiply within host cells. Furthermore, the use of fruit extracts as disinfectants is environmentally friendly, as they are derived from natural sources and do not produce harmful byproducts during the disinfection process, thus making them a good alternative to chemical agents. Pomegranate extracts are known for their antimicrobial potential [244,245]. These effects are attributed to its high content of polyphenols, including mainly hydrolysable tannins (ellagitannins), such as punicalagin isomers, with small amounts of ellagic acid and anthocyanins (delphinidin, cyanidins, and pelargonidin) and their glycosides. Su et al. demonstrated a virucidal activity of pomegranate juice and pomegranate polyphenolic (PP) on MS2 phage [221,246,247]. Their activity was dependent on initial phage titer as well as concentration of PP. Thus, MS2 at low initial titers (105) was reduced by 0.41, 0.45, and 0.93 log PFU/mL and at high initial titers (108) by 0.32, 0.41, and 0.72 log PFU/mL after 4, 8, and 16 mg/mL of PP treatment, respectively. Moreover, Stewart and colleagues employed the pomegranate extract to inactivate bacteriophages in assay aimed to detection of specific bacterial pathogens [248]. A crucial step for this assay was deactivation of viruses inside a bacterium using pomegranate rind extract (PRE) with no harm to bacterial culture. In combination with ferrous sulphate, PRE can provide about an 11-log reduction in phage titer within 3 min, and it activity has been shown for a range of bacterial hosts including P. aeruginosa, Salmonella typhimurium, and S. aureus (NCIMB 10116, Felix O-1, and NCIMB 9563, respectively) [248]. The mode of action of high PP concentration in extracts are considered to be a capsid denaturation as demonstrated in other study, according to TEM visualization [249]. Overall, the obtained results showed that grape seeds and pomegranate extracts are significant inhibitory agents for phages. There are a number of publications identifying the inhibitory activity of these components on bacteriophages. In one of these studies, it was reported that cranberry juice, grape juice and orange juice had an inhibitory effect on bacteriophage T2 [250]. Study by Su et al. from 2010, demonstrated that different concentrations of cranberry juice and cranberry proanthocyanidins were found to reduce titers of MS2 and ΦX174 bacteriophages [251]. Similarly, it was found that potato peel extract had an inhibitory effect on Av-05 and MS2 bacteriophages [252]. The antimicrobial agents serve for decades to control bacterial and fungal infections. In fact, most of drugs were found to be produced by microorganisms as secondary metabolites. In the natural environment, they play an important role in the mechanism of microbes’ self-protection, as well as competition for habitats. Some of these small molecules can also act as potent inhibitors of phage replication and represent a widespread anti-phage defense system [253,254,255]. Although the antibiotic treatment of bacterial cultures can affect their development, the concentrations of drugs used in presented below studies did not affect the host development or in some cases the resistant strains were used. Among antibiotics, in particular, a group of compounds produced by Streptomyces, the aminoglycosides, have proven to be highly effective in controlling bacteriophages [256]. Aminoglycosides have bactericidal potential, and their mode of action is related to a binding affinity for nucleic acids. In bacteria, their target is the 30S subunit of the ribosomes, resulting in disruption of protein biosynthesis due to translation blockage or mistranslation events. In early 1960s, Brock and colleagues [257,258] showed the streptomycin can inhibit development of E. coli MS2 phage and certain streptococcal bacteriophages. According to their findings all of the DNA viruses tested were resistant, but the RNA virus was sensitive to the drug. At the time, it was claimed that streptomycin inhibited both the adsorption/injection phase and replication of viral genetic material. Recently, study by Jiang shed new light to aminoglycoside anti-phage action [259]. The authors showed that presence of kanamycin, hygromycin, or streptomycin leads to inhibition of the DNA replication of mycobacteriophages. They employed natural phage D29 and engineered phAE159 to comprehensive evaluation of aminoglycosides action. However, Jiang and colleagues also tested these drugs’ activity using E. coli DNA phages T7 and λ, and showed no effect to these phages. Thus, the authors hypothesized that amino sugar group of aminoglycosides might selectively inhibit mycobacteriophage DNA replication. These findings are in line with another elegant work by Kever et al. [260] where, using bacterial hosts expressing aminoglycoside resistance plasmid cassettes, aminoglycosides are demonstrated to present wide anti-phage properties. Activity of aminoglycosides was proved by employing viruses of Gram-negative E. coli, as well as Gram-positive bacteria such as Corynebacterium glutamicum and Streptomyces venezuelae. The study revealed that phage DNA was detected inside cells in the presence of aminoglycosides. Together with the observation that amplification of phage DNA was strongly impaired, these results suggest that the blockage exerted by aminoglycosides occurs mostly after DNA injection but before genome replication. Peptide antibiotics is a group of antimicrobial and cytostatic substances with a highly diverse structure and mechanisms of action. Nonetheless, some glycopeptide drugs, namely, phleomycin and bleomycin were shown to effectively affect virus propagation through genetic material alteration. Watanabe and August observed activity of phleomycin against both DNA and RNA phages of E. coli [261]. This drug shows specific affinity to single and double strand RNA resulting in impairment of T2 and R23 phages development according to the study. Moreover, inhibition by phleomycin of viral RNA polymerase and DNA-dependent RNA polymerase was proved by in vitro evaluation. Similarly, Post and Price revealed that phleomycin acts also as an effective inhibitor of the replication of Bacillus subtilis bacteriophage PBS2 [262]. In their study, phage DNA synthesis was severely inhibited by drug presence, thereby blocking the synthesis of late virion proteins. Another drug, bleomycin, is considered as a DNA binding agent and thus affects viruses’ activity. Cloos and colleagues showed the drug potential to damage PM2 phage genome [263]. Bleomycin mediates inner cross-links in phage PM2 DNA. The cross-links are observed only when the reactant covalently closed circular duplex DNA contains either positive or negative superhelical turns. However, due to its abilities to cause alterations in DNA structure bleomycin is also a potent prophage inducer via SOS response activation [264]. One of the other examples of polypeptide drug that shows abilities to bind to DNA is quinomycin A. Quinomycin A is a compound with circular structure with potent antibacterial, anticancer and antiviral activities. The drug was shown to inhibit the T2 phage development without measurable interference with the synthesis of the phage DNA, RNA, or protein [265]. Therefore, the authors assumed that quinomycin A inhibits phage development at a step during maturation, possibly in association of DNA and head protein. To our best knowledge, to date, there is no systematic approach to study the bacteriophages disinfection methods and spread monitoring. Therefore, we recognize the urgent need to develop common standard methods to reduce future risks related to the widespread use of phages. Our remarks under perspective of standardization procedures and good practice in phage usage are as follows: The relevant methods of phage eradication should take into account the differences in the structure and virus type. The research aimed at developing new methods of phage infection prevention should include not only establishing of novel compounds but also their utilization. The standards of disinfection effectiveness should be increased from typically 3-log decrease in the phage titer to 6 log (due to the need to reduce a higher relative titer of viral particles vs. bacterial cells). The phage usage in medicine and biotechnology should be under strict monitoring to prevent from uncontrolled spreading in the environment, which is especially important for phages imported from distant ecosystems. It should be taken into consideration to establish the rules of monitoring bacteriophage genetic variations and diversity to maintain the safety of phage use, especially in clinical practice. The potential of bacterial viruses, bacteriophages, nowadays gains a wide attention due to their role as useful tools in many fields. However, their uncontrolled distribution by their use in medicine, food production, and preservation as well as in bio-technology poses a potential serious risk, which should not be underestimated. As the main vector of horizontal gene transfer and driver of microbial variability, bacteriophages can become a trigger for threats to humans. Especially, the use of bioengineered strains of phages implicates potential risks. The ubiquity of bacteriophages and their persistence in the environment raise concern about their involvement in antimicrobial resistance genes and/or virulence factors transmission among different biomes and the generation of multi-resistant pathogenic bacteria. Thus, the more common use of bacteriophages in medicine and biotechnology should be preceded by research aimed in clear understanding of phage–phage and phage–bacterium dynamics as well. Thus, efforts aimed at establishing instruments to control the development and monitor the spread of bacteriophages should go simultaneously with their widespread use. The development of relevant antiviral agents and methods of phage eradication is an indispensable and necessary element of modern biotechnology and clinical practice. Moreover, the vast part of methods for bacteriophage infection prevention could be either the same or at least combined with already known and used methods for disinfection and bacterial pathogens eradication. Thus, the better understanding of the mechanisms of disinfectant actions and effects is a key step in establishing the trustful methods for microorganism control.

PMC10003510

Issam Rimawi,Gadi Turgeman,Nataly Avital-Cohen,Israel Rozenboim,Joseph Yanai

Parental Preconception and Pre-Hatch Exposure to a Developmental Insult Alters Offspring’s Gene Expression and Epigenetic Regulations: An Avian Model

06-03-2023

chlorpyrifos,avian model,epigenetic regulation,gene expression,neurogenesis and neurotransmission,parental preconception exposure

Parental exposure to insults was initially considered safe if stopped before conception. In the present investigation, paternal or maternal preconception exposure to the neuroteratogen chlorpyrifos was investigated in a well-controlled avian model (Fayoumi) and compared to pre-hatch exposure focusing on molecular alterations. The investigation included the analysis of several neurogenesis, neurotransmission, epigenetic and microRNA genes. A significant decrease in the vesicular acetylcholine transporter (SLC18A3) expression was detected in the female offspring in the three investigated models: paternal (57.7%, p < 0.05), maternal (36%, p < 0.05) and pre-hatch (35.6%, p < 0.05). Paternal exposure to chlorpyrifos also led to a significant increase in brain-derived neurotrophic factor (BDNF) gene expression mainly in the female offspring (27.6%, p < 0.005), while its targeting microRNA, miR-10a, was similarly decreased in both female (50.5%, p < 0.05) and male (56%, p < 0.05) offspring. Doublecortin’s (DCX) targeting microRNA, miR-29a, was decreased in the offspring after maternal preconception exposure to chlorpyrifos (39.8%, p < 0.05). Finally, pre-hatch exposure to chlorpyrifos led to a significant increase in protein kinase C beta (PKCß; 44.1%, p < 0.05), methyl-CpG-binding domain protein 2 (MBD2; 44%, p < 0.01) and 3 (MBD3; 33%, p < 0.05) genes expression in the offspring. Although extensive studies are required to establish a mechanism–phenotype relationship, it should be noted that the current investigation does not include phenotype assessment in the offspring.

Parental Preconception and Pre-Hatch Exposure to a Developmental Insult Alters Offspring’s Gene Expression and Epigenetic Regulations: An Avian Model Parental exposure to insults was initially considered safe if stopped before conception. In the present investigation, paternal or maternal preconception exposure to the neuroteratogen chlorpyrifos was investigated in a well-controlled avian model (Fayoumi) and compared to pre-hatch exposure focusing on molecular alterations. The investigation included the analysis of several neurogenesis, neurotransmission, epigenetic and microRNA genes. A significant decrease in the vesicular acetylcholine transporter (SLC18A3) expression was detected in the female offspring in the three investigated models: paternal (57.7%, p < 0.05), maternal (36%, p < 0.05) and pre-hatch (35.6%, p < 0.05). Paternal exposure to chlorpyrifos also led to a significant increase in brain-derived neurotrophic factor (BDNF) gene expression mainly in the female offspring (27.6%, p < 0.005), while its targeting microRNA, miR-10a, was similarly decreased in both female (50.5%, p < 0.05) and male (56%, p < 0.05) offspring. Doublecortin’s (DCX) targeting microRNA, miR-29a, was decreased in the offspring after maternal preconception exposure to chlorpyrifos (39.8%, p < 0.05). Finally, pre-hatch exposure to chlorpyrifos led to a significant increase in protein kinase C beta (PKCß; 44.1%, p < 0.05), methyl-CpG-binding domain protein 2 (MBD2; 44%, p < 0.01) and 3 (MBD3; 33%, p < 0.05) genes expression in the offspring. Although extensive studies are required to establish a mechanism–phenotype relationship, it should be noted that the current investigation does not include phenotype assessment in the offspring. It has been well established that prenatal/pre-hatch exposure to insults such as drugs, chemicals and pesticides induces behavioral deficits and molecular alterations in the offspring [1,2,3,4]. Understanding the molecular mechanisms by which teratogens exert their deleterious action enabled the reversal of neurobehavioral deficits by various means [5,6,7]. It appears, as a natural subsequent step, to establish a similar model of neurobehavioral teratogenicity for parental preconception exposure. Although first investigated in the early nineteen hundreds [8], consequences of parental preconception insult exposure on the offspring received, until recent years, limited attention. The recent increased interest in maternal and paternal preconception insult exposure effects on the offspring is probably due to a better understanding of the epigenetic mechanisms involved in such exposures (for review, see [9]). DNA methylation, histone modification and non-coding RNA transmission are the main proposed epigenetic mechanisms mediating the transfer of deficits to the offspring after paternal insult exposure (for review, see [10]). Previous studies on parental preconception exposure to insults (mainly performed on rodents) showed that maternal and/or paternal preconception insult exposure could have detrimental effects (demonstrated molecularly, biochemically and/or behaviorally) on the offspring (for review, see [9]). Many insults were investigated in such studies, including chemicals, substances of abuse, therapeutic agents and even lifestyle factors (for review, see [9]). Organophosphates, including chlorpyrifos, are among the most widely used insecticides worldwide. Chlorpyrifos is a widely studied archetypal neuroteratogen, and extensive information is available on its deleterious action on neurodevelopment [11,12]. Chlorpyrifos works by inhibiting the activity of the enzyme acetylcholinesterase (AChE) [13]. Cholinesterase inhibition following chlorpyrifos exposure can persist for weeks [14]; consequently, frequent exposure to small amounts of chlorpyrifos might cause acetylcholine accumulation and sudden-onset acute toxicity [14]. Metabolic activation of chlorpyrifos is mediated by cytochrome P450 (CYP450) oxidative desulfurization of the P=S moiety to P=O moiety, resulting in the toxic metabolite chlorpyrifos oxon [15,16,17,18]. Chlorpyrifos possesses different stabilities at different pH values, obtaining a half-life of 16 days (pH 9) up to 73 days (pH 5) [19]. The half-life of chlorpyrifos ranges from 2 weeks to 1 year in soil, and it is dependent on many factors, including soil type, pH, climate and other conditions [14]. Although the environmental exposure to chlorpyrifos could occur through different administration routes and at different levels than those applied in the current research (chronic exposure to 12.2 mg/kg in chicken feed throughout chickens’ lives [20]), the environmental effects of chlorpyrifos on chickens is not relevant to the current investigation, and chlorpyrifos was used here as a model developmental insult to study the neuroteratogenic effects of parental preconception exposure on the offspring. Neurobehavioral alterations in the offspring after prenatal exposure to neuroteratogens such as alcohol, heroin and chlorpyrifos is usually accompanied with gene expression changes. Alterations in normal control of gene expression and reprogramming during embryonic development typically occur following prenatal alcohol exposure, ultimately leading to fetal alcohol syndrome-accompanied behavioral alterations [21]. Neurobehavioral alterations after prenatal heroin exposure are well documented [22], and these alterations can be accompanied by several gene expression changes, as shown in mouse models [23]. Fetal exposure to chlorpyrifos in mice and humans causes neurobehavioral alterations that could also be accompanied by gene expression alterations [24,25]. In the avian model, neuroteratogens can be administered in defined doses with little consideration for the pregnancy stage-related pharmacokinetic changes, maternal–fetal interactions or maternal toxicities that are not directly related to the neuroteratogen exposure, since the egg is situated outside of the neuroteratogen-exposed mother from an early developmental stage [26]. Most studies on avian models for neurobehavioral teratology apply broilers or layer strains (for review, see [27]). For preconception exposure studies, it is advantageous to use robust strains that could survive severe teratogen exposure at maturity, during mating and egg laying. The strain used in the current investigation, Fayoumi, is usually exposed to harsh conditions (for review, see [28]) while being classified as a relatively resistant strain to most severe poultry diseases [29]. Our preliminary studies suggest that this strain survives preconception exposure to chlorpyrifos much better than the highly sensitive broiler strains and even better than the commercial layer strains, especially in situations where chickens are exposed to the neuroteratogen for extended periods (unpublished data). Our previous studies demonstrated neurogenesis and neurotransmission genes expression alterations in the offspring following pre-hatch exposure to chlorpyrifos [3,30]. Additional studies investigating the effects of prenatal/pre-hatch exposure to chlorpyrifos observed several signaling cascades deficits, epigenetic alterations and/or genes expression modifications in the offspring in animal [31,32,33,34] and human models [24]. In addition to their direct toxic effects, prenatal exposure to neuroteratogens could inflict deleterious actions on the offspring’s neurobehavioral development indirectly, for example, leading to cell death [35,36] and perturbing neural circuitries [37,38]. Several studies performed on rodents confirmed that parental preconception exposure to neuroteratogens could also affect signaling cascades [39,40], epigenetic regulations [41] and gene expression [42,43]. Our recent review of parental preconception exposure to insults [9] indicates that the effects of preconception exposure (especially paternal) to insults on the offspring seem to be directly related to changes in gene expression mediated by epigenetic regulation mechanisms. This observation, along with our previous observations that chlorpyrifos affects neurogenesis and neurotransmission genes expression [3,30], provided the rationale to our hypothesis that parental preconception exposure to chlorpyrifos alters neurogenesis and neurotransmission genes expression in the offspring via epigenetic mechanisms. Chlorpyrifos was selected here due to its value for neurobehavioral teratology research (as a neuroteratogen) and not due to its environmental effects on chickens. We considered neuronal deficits in the offspring after parental preconception exposure to chlorpyrifos as preconception neuroteratology. In the present study, female or male Fayoumi chickens were subjected to chlorpyrifos preconceptionally, beginning three weeks prior to eggs collection. The pertinent genes were analyzed in the embryo right before hatching (incubation day 20). To control for possible direct chlorpyrifos exposure of the early embryo, chlorpyrifos was analyzed in the maternally exposed eggs. The gene analysis results in the preconception model were compared to those obtained from the pre-hatch model, where embryos were exposed to chlorpyrifos on incubation days 0 and 5. The developed chromodomain helicase DNA-binding Z and W (CHDZ and CHDW) primers accurately differentiated between genders in 75 out of 76 samples. RT-PCR analysis using SYBR green dye demonstrated undetected CHDW expression in male samples (Ct > 35), while it was distinctly detected in female samples (Ct < 25; Supp. S1, Figure S1). CHDZ was used as a housekeeping gene, and its expression was detected in both sexes. Alterations in the offspring’s gene expression after paternal exposure to chlorpyrifos are shown in Figure 1. Neurogenesis-related genes: Paternal exposure to chlorpyrifos resulted in significant increase in brain-derived neurotrophic factor (BDNF) gene expression (22.3%, p < 0.0005). Treatment by sex analysis suggested that female offspring were the main contributors to this significance (27.6%, p < 0.005). BDNF expression in the male offspring was less impacted (non-significant increase) but still contributed to the overall significance, since the treatment by sex interaction did not exist (p > 0.38). No additional significant alterations were observed in the expression of doublecortin (DCX) or C-Fos (FOS) in the paternally exposed offspring. Neurotransmission-related genes: Paternal exposure to chlorpyrifos led to a significant decrease in the vesicular acetylcholine transporter (solute carrier family 18 member A3; SLC18A3) expression only in the female offspring (57.7%, p < 0.05). Gene expression of protein kinase C beta (PKCß), the cholinergic muscarinic receptors 2 and 3 (CHRM2 and CHRM3), and of the serotonergic transporter (solute carrier family 6 member 4; SLC6A4) was not affected significantly in the offspring after paternal exposure to chlorpyrifos. Epigenetic regulation-related genes: No significant alteration was observed in the epigenetic regulations-related genes (methyl-CpG-binding domain proteins 2 and 3 (MBD2 and MBD3), methyl CpG binding protein 2 (MeCP2), SET domain bifurcated histone lysine methyltransferase 1 and 2 (SETDB1 and SETDB2), cAMP-response element binding protein (CREB) and RE1 silencing transcription factor (REST)) expression following paternal exposure to chlorpyrifos. microRNA genes: BDNF’s targeting microRNA, microRNA 10a (miR-10a) [44], was decreased in the paternally exposed offspring (54.5%, p < 0.005). microRNA 6612 (miR-6612), which targets PKCß’s mRNA [45], was also reduced in the exposed offspring (30.9%, p < 0.05). microRNA 221 (miR-221) and microRNA 29a (miR-29a) gene expression was not significantly altered in the offspring after paternal exposure to chlorpyrifos. Alterations in the offspring’s gene expression after maternal preconception exposure to chlorpyrifos are shown in Figure 2. Neurogenesis-related genes: No significant alterations were observed in the offspring’s neurogenesis-related genes expression after maternal preconception exposure to chlorpyrifos. Neurotransmission-related genes: Similar to the results obtained after paternal exposure, maternal preconception exposure to chlorpyrifos caused a significant decrease in the cholinergic transporter (SLC18A3) gene expression only in the female offspring (36%, p < 0.05). No additional significant alterations were observed in PKCß, the cholinergic muscarinic receptors 2 and 3 or in the serotonergic transporter (SLC6A4) genes expression. Epigenetic regulation-related genes: No significant alteration was observed in the epigenetic regulation-related genes (MeCP2, MBD2, MBD3, SETDB1, SETDB2, CREB and REST) expression after maternal preconception exposure to chlorpyrifos. microRNA genes: DCX’s targeting microRNA, miR-29a [46], was decreased in the offspring after maternal preconception exposure to chlorpyrifos (39.8%, p < 0.05). miR-221, miR-10a and miR-6612 genes expression was not altered significantly in the exposed offspring. Residues of chlorpyrifos were undetected in the control eggs (n = 2), while, in the maternal preconception-exposed eggs, chlorpyrifos residues were detected (2.792–3.253 mg/kg; n = 2). Residues of chlorpyrifos methyl and chlorpyrifos’s active metabolite, chlorpyrifos oxon, were undetected in all samples. Alterations in the offspring’s gene expression after pre-hatch exposure to chlorpyrifos are shown in Figure 3. Neurogenesis-related genes: DCX and FOS gene expression was not altered significantly in the offspring exposed to pre-hatch chlorpyrifos. Neurotransmission-related genes: Pre-hatch exposure to chlorpyrifos led to a significant increase in PKCß expression in the offspring (44.1%, p < 0.05). This alteration was mainly contributed by the male offspring (females showed nonspecific increase), and treatment by sex interaction analysis was not significant (p > 0.35). Female offspring showed a significant decrease in the cholinergic transporter (SLC18A3) gene expression (35.6%, p < 0.05). Gene expression of the cholinergic muscarinic receptors 2 and 3 and of the serotonergic transporter, SLC6A4,was not affected significantly in the offspring after pre-hatch exposure to chlorpyrifos. Epigenetic regulation-related genes: Offspring exposed to pre-hatch chlorpyrifos showed a significant increase in the DNA methylation readers MBD2 (44%, p < 0.01) and MBD3 (33%, p < 0.05; mainly contributed by the female offspring) gene expression. The rest of the epigenetic regulation-related genes (MeCP2, SETDB1, SETDB2, CREB and REST) were not affected significantly in the offspring after pre-hatch exposure to chlorpyrifos. microRNA genes: miR-221 and miR-29a gene expression was not altered significantly in the offspring after pre-hatch exposure to chlorpyrifos. To better understand the chlorpyrifos exposure effects on possible interaction mechanisms between the investigated genes, we performed a correlation matrix analysis. Statistically significant correlations (Spearman’s p < 0.05) were considered. The control offspring displayed 32 correlations between the tested genes (Supp. S2). Paternal chlorpyrifos exposure offspring shared with the control offspring nine of these correlations, while maternal and pre-hatch offspring shared six and five, respectively (Figure 4). Only two correlations were shared among all offspring, namely positive correlations between REST and CREB and between SETDB1 and SETDB2 (Supp. S2–S5). Correlation matrices were used to generate unweighted gene co-expression correlation networks. The control offspring presented a 19-node correlation network with a main node module composed of eight genes, including three microRNAs (miR-6612, miR-221 and miR-29a); the chromatin modifier (SETDB1); two methylated DNA readers (MECP2 and MDB2); the neurogenesis-related gene (DCX) and the neurotransmission-related gene (PKCß). The hub genes in this module were miR-6612 and PKCß, which interacted with six of the seven remaining nodes (Figure 5a). Interestingly, chlorpyrifos-exposed chickens presented less complex networks and modules, with a reduced number of edges compared to the controls. All chlorpyrifos-exposed animals showed a reduced involvement of microRNAs and, in particular, that of miR-6612. In paternally exposed offspring, two central six-node modules were detected. Module 3 corresponded to the main module in the controls (module 5) and shared four nodes with it (DCX, PKCß, miR-221 and MeCP2), with MDB3 replacing MDB2. Module 4 connected all neurotransmitter-related genes with the chromatin modifiers (SETDB1 and SETDB2) (Figure 5b). Among all correlations found in paternally exposed offspring, only 5 out of 24 involved microRNAs, a rate significantly lower (X2, p < 0.05) than that observed in the controls (15 of 32). In maternally exposed offspring, module 3 was the dominant module, with seven nodes and 11 edges. Module 3 resembled module 4 in parentally exposed offspring containing the neurotransmitter-associated genes together with the chromatin modifiers (SETDB1 and SETDB2), in addition to MeCP2 and FOS (Figure 5c). Module 1, having seven nodes, shared four nodes (miR-6610, miR-29a, DCX and MDB2) with the main module of the control offspring network (module 5). However, the number of edges and connectivity in this module were tremendously altered. Six of the nine correlations in this module were negative correlations. miR-6612 presented three correlations, two of which were negative correlations with CREB and REST and only one positive correlation with MDB2 (the only correlation in this module resembling control correlations). In the offspring exposed to pre-hatch chlorpyrifos, a further reduced complexity of the network was observed (Figure 5d). The largest module had only five nodes and five edges and included the chromatin modifiers SETDB1 and SETDB2 and the methylated DNA readers MDB3 and MeCP2, together with the serotonergic gene SLC6A4. Module 4 shared three of its four nodes (DCX, MDB2 and MeCP2) with the main module of the control network but shred none of the edges connecting the nodes. Egg weights and offspring’s body weights of pre-hatch, maternal and paternal exposures are presented in Table 1. Significant weight alterations were observed only after maternal exposure to chlorpyrifos with an increase in egg weights (11.9%; p < 0.005) and in the offspring’s body weights (5.1%; p < 0.05). The current investigation indicated that exposure to chlorpyrifos, a significant neuroteratogen, could have deleterious effects on the offspring, even if the exposure occurred prior to pregnancy. In the current study, parental preconception exposure to chlorpyrifos in an avian model altered the expression of neurogenesis and neurotransmission-related genes, as well as the regulating epigenetic genes. The results were compared to alterations in gene expression induced by pre-hatch exposure to chlorpyrifos, and they did not necessarily correspond. Our previous work extensively studied the effects of early (prenatal (mice)/pre-hatch (chick)) exposure to several cholinergic and cholinergic-related teratogens (chlorpyrifos, heroin and nicotine) on the offspring’s behavior and the mechanistically related changes in neurotransmission and neurogenesis converging into the abolishment of cholinergic receptor-induced activation/translocation of PKC isoforms [3,47,48,49,50]. In the present research, we extend the study to another form of early exposure, parental exposure, and investigated the alterations in neurogenesis and neurotransmission gene expression as related to the previously observed behavioral deficits. It has been previously established that prenatal (mice)/pre-hatch (chicks) exposure to neuroteratogens, including chlorpyrifos, induces significant deficits in learning-related behaviors in the offspring (seen as imprinting behavior deficits in our previous pre-hatch model [3]) and that these deficits are the outcome of alterations in neurogenesis and neurotransmission-related genes, particularly the cholinergic receptor-mediated abolishment of activation/translocation of PKC isoforms [3,51]. Activation/translocation of PKC isoforms was abolished after introducing IMM tissues (extracted from offspring after pre-hatch exposure to chlorpyrifos) to the cholinergic agonist, carbachol, which was correlated with the imprinting behavior deficits seen in the same offspring [3]. We hypothesized that parental preconception exposure to the neuroteratogen chlorpyrifos would affect the offspring’s neurogenesis and neurotransmission genes expression and that those effects would be mediated by epigenetic regulation mechanisms. Consequently, we analyzed the expression of neurogenesis (BDNF, PKCß, DCX and FOS) and neurotransmission (CHRM2, CHRM3, SLC6A4 and SLC18A3) genes and microRNA genes (miR-221, miR-29a, miR-6612 and miR-10a), along with several epigenetic genes (MeCP2, MDB2, MBD3, SETDB1, SETDB2, REST and CREB), most of which were previously linked to neuronal functions. The neurogenesis-related genes included BDNF (a crucial neurotrophin involved in plastic alterations related to learning and memory [52]), DCX (serves as an efficient marker for neurogenesis [53,54,55]), PKCß (phosphorylation of PKC substrates may be involved in neuronal plasticity and growth [56]) and FOS (can be used as marker for neuronal activity following deleterious stimulation and tissue injury [57,58,59,60]). These genes’ expression was previously shown to be affected by prenatal/pre-hatch or direct exposure to chlorpyrifos in several studies, including our own [3,30,31,32,33], suggesting that the same genes might be affected in the offspring after paternal/maternal preconception exposure to chlorpyrifos. Indeed, in the current study, paternal preconception exposure to chlorpyrifos altered the expression of BDNF, suggesting neurogenesis as a mechanism mediating functional deficits in the offspring after paternal exposure to insults. Our previous studies indicate that both serotonergic and cholinergic innervations are affected in the offspring following pre-hatch exposure to chlorpyrifos [3,30]. The investigated cholinergic and serotonergic genes included SLC6A4 (the principal regulator of serotonergic neurotransmission [61,62]), SLC18A3 (mediates the transfer of acetylcholine from the cytoplasm into synaptic vesicles [63]), the muscarinic receptors 2 and 3 (CHRM2 and CHRM3) and PKCß (a key enzyme for signal transduction [64]). In the current study, pre-hatch and preconception exposure to chlorpyrifos significantly affected the expression of the cholinergic transporter, SLC18A3, in the offspring. These results, along with our previous finding that pre-hatch chlorpyrifos exposure abolishes the cholinergic activation/translocation of PKC isoforms in the offspring [3], probably indicate that the cholinergic innervation is a key mechanism involved in chlorpyrifos’s neuroteratogenic effects in both pre-hatch and preconception exposure models. microRNA was investigated as a possible mechanism that might mediate gene expression alterations in the offspring after parental/pre-hatch exposure to chlorpyrifos. The investigated microRNAs included miR-10a (targets BDNF’s mRNA [44]), miR-221 (targets FOS’s mRNA [65]), miR-29a (targets DCX’s mRNA [46]) and miR-6612 (targets PKCß’s mRNA). The selection of the current microRNAs was based on a peer-reviewed online database (TargetScan database), which identifies the targeting microRNAs based on the inserted gene and species [45]. In addition, most of these microRNAs were validated in previous investigations [44,46,65]. The microRNA investigation after parental preconception exposure to insults received limited attention, and only a few studies [66] considered investigating such exposure effects on the offspring’s microRNAs, making our study a pioneering study in this field. microRNA involvement in mediating gene expression alterations in the offspring was mainly observed in the paternal group, where miR-10a was downregulated in the offspring while its target mRNA (BDNF) was upregulated. On the other hand, the gene expression of paternal miR-6612 and maternal miR-29a was altered in the offspring, while their target mRNA (PKCß and DCX, respectively) gene expression was not affected. This is probably due to the fact that microRNAs can bind several target mRNAs, and a single mRNA can be targeted by more than one microRNA [67,68]. Other epigenetic genes that might have mediated chlorpyrifos exposure effects to the offspring were investigated. Those genes included MBD genes (MeCP2, MBD2 and MBD3) and histone modification genes (SETDB1 and SETDB2), which were previously linked to neuronal functions [69,70]. In addition, REST and CREB gene expression was investigated. REST binds the neuron-restrictive silencer element that represses neuronal gene transcription in nonneuronal cells [71,72] and is linked to neuronal inflammation [73]). CREB binds to DNA sequences called cAMP response elements, thereby increasing or decreasing the transcription of downstream genes [74], and its activity in neurons is correlated with various intracellular processes, including proliferation, differentiation, survival, long-term synaptic potentiation, neurogenesis and neuronal plasticity [75,76,77]. Although some of the epigenetic genes did not show differential expression in chlorpyrifos-exposed offspring, we estimated their potential regulatory role by performing a co-expression analysis with the other genes. Correlation matrices and the co-expression network showed complex interactions and co-expressions between several microRNAs (miR-6612, miR-221 and miR-29a); the chromatin modifier (SETDB1); methylated DNA readers (MDB2 and MeCP2) and the neurogenesis-related genes (DCX and PKCß) (Figure 5). The involvement of miR-6612 was mainly noticed in the control offspring network. On the other hand, chlorpyrifos-exposed offspring presented disrupted networks, especially regarding the involvement of microRNAs (Figure 5). miR-6612 involvement in gene expression correlations was absent in paternally exposed offspring and was altered in maternally exposed offspring. In addition, miR-6612 and miR-29a were downregulated in the paternally and maternally exposed offspring, respectively, suggesting that alterations in microRNA expression may be the key mechanism mediating the disruption of offspring neurogenesis and neurodevelopment by parental preconception exposure to chlorpyrifos. Indeed, microRNAs are the leading candidates for parental and, especially, paternal epigenetic inheritance via the gametes. Most cytoplasm and RNA contents are ejected from the spermatozoa during the final stages of spermatogenesis. However, several small non-coding RNAs (sncRNAs) and a few mRNAs have been shown to remain in sperm and may enter the oocyte upon fertilization [78,79,80,81,82,83,84,85]. Those sncRNAs were shown to be transferred to the spermatozoa in the epididymis via lipid-rich exosomes called epididymosomes [86,87], and they include microRNAs, endogenous short interfering RNAs and PIWI-interacting RNAs [79,88,89]. This study is one of only a few [41,90] that has considered investigating alterations in the offspring’s epigenetic genes after parental preconception exposure to insults. In the current investigation, MBD2 and MBD3 seemed to play a role in gene expression alterations observed in the offspring following pre-hatch exposure to chlorpyrifos. On the other hand, microRNA seemed to be the primary epigenetic regulator (among those investigated) that mediates gene expression alterations in the offspring after paternal exposure to chlorpyrifos. Further studies are required to investigate the possibility of microRNA transmission to the offspring through sperm cells. The duration of paternal exposure to chlorpyrifos was selected based on previous studies, which indicates that the spermatogenesis duration is approximately 14 days in most avian models, including the chicken model [91,92,93,94], and, consequently, was intended to affect sperm cells. Accordingly, we exposed the males to chlorpyrifos for two weeks before mating with females. The methodological obstacles that may arise upon developing a preconception maternal model might have led to the scarcity in the studies investigating this model (for review, see [9]). One of those obstacles in rodents is the possible accumulation of the exposed material/s (e.g., heavy metals from cigarette smoke) in the endometrium [95], which might affect the embryo prenatally, even if the insult was stopped prior to conception. On the other hand, chick embryos mostly develop outside their mothers’ bodies and only the very early stages of their development are spent in the uterus [26]. This implies that the possibility of the early embryos being directly exposed to an insult following maternal preconception exposure can be mostly controlled. In order to validate the integrity of the maternal preconception exposure model and inspect the possibility of chlorpyrifos being carried over to the embryos following this exposure, we performed a quantitative analysis of chlorpyrifos and its active metabolite, chlorpyrifos oxon, in maternal preconception-exposed eggs and compared them to the control eggs. The results were intended to verify whether the effects obtained in the offspring following maternal preconception exposure were obtained due to direct exposure to chlorpyrifos. This is the first study, performed in an avian model, which evaluates possible effects of neuroteratogen transfer to the egg on the offspring’s gene expression after maternal preconception exposure. The current study showed that only a small portion of chlorpyrifos was carried over to the egg after maternal preconception exposure. Based on our preliminary (unpublished) dose–response evaluations, this portion (≈3 mg/kg) is not enough to induce neurobehavioral alterations in the offspring. The fact that chlorpyrifos has long elimination half-lives in humans (≈27 h [96]) and mice (≈21 h [97]) suggests that it possesses a similar pharmacokinetic profile in chickens. That being said, the detected amount of chlorpyrifos residues (≈3 mg/kg) is far less than the overall amount that probably accumulated in the mothers’ systems after receiving 10 mg/kg/day chlorpyrifos for three weeks. In addition, gene expression alterations in the offspring differ between pre-hatch and maternal preconception exposures, since MBD2, MBD3 and PKCß genes expression was altered only in the pre-hatch-exposed offspring, while miR-29a gene expression was altered only in the maternally exposed offspring. These findings indicate that the alterations in gene expression observed in the offspring after maternal preconception exposure to chlorpyrifos were mainly mediated by an epigenetic inheritance mechanism and are less related to direct embryo exposure to chlorpyrifos. Accordingly, the possibility of chlorpyrifos being transferred to the embryos through the uterus after maternal exposure was greatly minimized in the currently used avian model compared to the rodent model. It should be reemphasized that the current study is not an environmental toxicology research; rather, it is a basic neurodevelopmental study designed to understand the effects of parental preconception exposure to neuroteratogens on the offspring and compare that to the effects obtained in the offspring after pre-hatch exposure. In the current research, we considered gender as a factor that might affect the results obtained in the parentally/pre-hatch-exposed offspring. Indeed, female offspring seemed to be more affected by exposure to chlorpyrifos than male offspring. This was mainly seen in gene expression of the cholinergic transporters SLC18A3 (pre-hatch, maternal and paternal exposures) and BDNF (paternal exposure). Although the gene expression of BDNF’s targeting microRNA, miR-10a, was similarly altered in both genders, the consequence of this alteration on BDNF’s gene expression was less prominent in male offspring, which requires further elaboration. Variations in the sex chromosomes, with the males being homogametic (ZZ) and the females being heterogametic (ZW), have been utilized to develop PCR-based methods intended to differentiate between genders [98]. Chromodomain helicase DNA-binding Z and W (CHDZ and CHDW) genes were previously proven to be effective in sex differentiation in chickens and are considered one of the most commonly used genes for this purpose [99,100,101]. In the current study, we developed CHDZ and CHDW primers that accurately differentiated between genders. This method was used to verify the results obtained after determining the sex by visual examination of the gonads. Analogous in many ways to the hippocampus and its role in cognitive behaviors in mammals, avian species possess the left IMM, which is mechanistically related to learning and memory [102,103]. Since exposure to chlorpyrifos causes significant deficits in imprinting behavior (learning and memory) [3], the left IMM was used for mRNA extraction and analysis in the current investigation. Chick embryos were sacrificed on incubation day 20, which might decrease the possible confounding factors that could affect each offspring differently (food intake, hatching day and time spent in incubator after hatching). We wished to study the effects of parental chlorpyrifos exposure on developing offspring that were all raised in a similar and well-controlled environment (with minimum environmental bias). Parental exposure did not cause a reduction in egg weights or in the offspring’s body weights, which, if occurred, could have suggested an indirect effect on the offspring. In fact, maternal preconception exposure to chlorpyrifos caused a slight increase in body weights, which does not seem to be biologically significant. Further experiments including high-throughput analysis, protein expression, immunofluorescence, Western blot and the regulation of signaling pathways are pertinent to the current research and should be considered in future research. Although adding a group in which both parents are exposed to chlorpyrifos may complicate the identification of the mechanisms through which each parent mediates the deficits, this may be considered in future research. The biological relevance of using a non-physiological route of administration and of the lack of phenotype studies remains an open question that should be fulfilled in future experiments. The present research represents a study in “preconception neuroteratology”, which strongly suggests that preconception exposure to chlorpyrifos in a well-controlled avian model affects the offspring’s neurotransmission and neurogenesis genes expression, mainly through regulating epigenetic mechanisms. The next step might include using techniques such as mRNA and small RNA sequencing to further investigate the effects of preconception exposure to chlorpyrifos on the offspring. Future studies are required to investigate whether the molecular alterations observed in the present study after preconception exposure to chlorpyrifos can be linked to the expected neurobehavioral deficits in the offspring, particularly learning and memory. Understanding the mechanisms of parentally induced deficits may provide the means for the reversal of these deficits towards future clinical application. Female and male Fayoumi chickens were maintained in our animal facilities under standard laboratory conditions, as specified by the Office of Laboratory Animal Welfare (OLAW) of the National Institutes of Health (NIH) [104]. Chickens were 7–10 months old and were divided into separate groups, where group members were replaced frequently to increase genetic variability. To enable the replacement, parents were taken from a flock of the relevant group (pre-hatch, paternal or maternal). There were always 2 males and 5 females in each cage for each replication. Male and female Fayoumi chickens (Gallus gallus domesticus) were employed as parents in all experiments. Sixteen females and nine males were separated into groups (as described in the Chicken Housing section) and were used to generate the eggs used in the pre-hatch model. Eggs were collected three times daily for 10 days and stored at 14 °C. Within three days from collection, the eggs were placed in an incubator for 20 days according to the manufacturer’s instructions (50% humidity on incubation days (ID) 0–18 and 60% humidity on ID 18–20, 37.5 °C). Chlorpyrifos was generously supplied by Adama Ltd. and was injected into the chorioallantois end (pointed end) of the eggs, as previously described [3,30]. Briefly, 10 mg chlorpyrifos/kg of egg was dissolved in dimethyl sulfoxide (DMSO, Merck, vehicle volume: 510 μL/kg of eggs) and injected on incubation days 0 (prior to incubation) and 5, the period during which most of the brain structures develop [105,106]. The injection site was covered with correction fluid (white out). Control eggs received equivalent volumes of DMSO. The chlorpyrifos dosage was based on previous studies that involved dose–response evaluations [3] and on our preliminary studies showing that the parameters described here, including dose and injection schedule, are right below the level of embryotoxicity and gross malformations. To illustrate this, we observed congenital malformations in 25% of the exposed offspring (mainly seen as cervical scoliosis and torticollis or as macrocephaly) after administering three doses of chlorpyrifos (10 mg/kg on incubation days 0, 5 and 13) to 8 eggs. Paternal exposure: Eight male chicken received daily subcutaneous injections of chlorpyrifos (10 mg/kg body weight, dissolved in 300 µL DMSO) at the nape of the neck for 21 days, then received maintenance injections every two days until all eggs were collected (Figure 6). Fourteen days following initial treatment, the exposed males were introduced to 10 untreated females and were separated into groups, as described in the Chicken Housing section. Eggs were collected for 10 days (maintenance exposure period), stored at 14 °C and placed in an incubator within 3 days of collection. The respective control groups received equivalent volumes of DMSO and were formed with 8 males and 10 females. Maternal exposure: The protocol was similar to that of the paternal exposure. Thirteen female chicken received daily subcutaneous injections of chlorpyrifos (10 mg/kg body weight, dissolved in 300 μL DMSO) for 21 days, then received maintenance injections every two days until all eggs were collected. Fourteen days following treatment initiation, 5 untreated males were introduced to the exposed females and were separated into groups, as described in the Chicken Housing section. Eggs were collected for 10 days (maintenance exposure period), stored at 14 °C and placed in an incubator within 3 days of collection. The respective control groups received equivalent volumes of DMSO and were formed of 5 males and 13 females. Chick embryo brains of all groups were removed on ID 20 right before hatching. Laterally extended left intermediate medial hyperstriatum ventrale (IMHV) or intermediate medial mesopallium (IMM), corresponding to the newer nomenclature [107], was extracted according to our modification [3,30] of a previously described procedure [108]. The extracted IMM tissues were stored at −80 °C. Total RNA was extracted separately from the left IMM using an ISOLATE II RNA Mini Kit (Bioline, Memphis, TN, USA). RNA was quantified, and its purity was assessed at an absorbance wavelength of 260 nm using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Extracted RNA was stored at −80 °C. Real-time qPCR analysis was carried out as previously described [109]. Complementary DNA (cDNA) was transcribed from mRNA and microRNA using the qScript cDNA Synthesis Kit (QuantaBio, Beverly, MA, USA) and qScript® microRNA cDNA Synthesis Kit (QuantaBio, MA, USA), respectively. Expression analysis of cDNA samples was performed on the housekeeping genes: glyceraldehyde 3-phosphate dehydrogenase (GAPDH; mRNA analysis) and U6 spliceosomal RNA (RNU6; microRNA analysis); neurotransmission genes: PKCß, CHRM2, CHRM3, SLC18A3 and SLC6A4; neurogenesis genes: BDNF, FOS and DCX; epigenetic related genes: MeCP2, MBD2, MBD3, SETDB1, SETDB2, CREB and REST; sex-determining genes: CHDZ and CHDW; and microRNA genes: miR-221, miR-29a, miR-6612 and miR-10a. microRNAs were selected based on a peer-reviewed online database (TargetScan database), which identifies the targeting microRNAs based on the inserted gene and species (Agarwal et al. 2015). Real-time PCR was carried out using the StepOnePlus and QuantStudio 5 real-time PCR systems (Thermo Fisher Scientific, MA, USA). Genes’ availability in chickens was confirmed using the Gallus gallus genome data viewer (NCBI). Primers were selected, and their specificity was verified using the Primer-BLAST tool (NCBI). The primers were then synthesized commercially (Merck, Rehovot, Israel). A universal reverse microRNA primer was provided in the qScript® microRNA cDNA Synthesis Kit (QuantaBio, MA, USA). Primers used and their sequences are listed in Table 2. Amplification for microRNA genes was performed using PerfeCTa SYBR Green SuperMix (QuantaBio, MA, USA) under the following conditions: preincubation at 95 °C for 2 min, followed by 40 cycles of denaturation at 95 °C for 5 s and annealing at 60 °C for 30 s. Amplification for the rest of the genes was performed using PerfeCTa SYBR Green FastMix ROX (QuantaBio, MA, USA) under the following conditions: preincubation at 95 °C for 20 s, followed by 40 cycles of denaturation at 95 °C for 3 s and annealing at 60 °C for 30 s. microRNA primers’ selectivity was confirmed in multiple minus Poly-A qPCR plate wells that contained treated (with chlorpyrifos) or control samples prepared by the same procedure, excluding the addition of Poly-A tails. Relative quantifications of the target genes were normalized to GAPDH levels in the mRNA analysis and to RNU6 levels in the microRNA analysis and calculated with the 2−ΔΔCt method, as previously described [110]. RT-PCR product specificity was confirmed using a melt curve analysis. In the current study, CHDZ and CHDW primers were developed using the Primer BLAST tool (NCBI) to differentiate between chick embryos genders. This method was used to confirm the results obtained after determining the sex by visual examination of the gonads. Two control and two maternally exposed eggs (preconception) were collected and homogenized on the same day (eggs were not incubated). Residues of chlorpyrifos, chlorpyrifos methyl and chlorpyrifos oxon in the exposed and control eggs were analyzed using the liquid chromatography-mass spectrometry (LC-MS) technique by the Kimron Veterinary Institute (Beit Dagan, Central District, Israel), as previously described [111]. The detection limit for all tested ingredients was 0.005 mg/kg. The possible effect of chlorpyrifos exposure on the offspring’s weights was investigated. Egg and body weights of the embryos were measured on incubation day 20 prior to their brain extraction. The weight means of chlorpyrifos exposed and control samples were calculated and compared for each exposure group (paternal, maternal or pre-hatch) as separate. Multiple-level analysis of variance (ANOVA) was employed for comparing groups. Data were expressed as the mean ± SEM. Genes expression in the offspring exposed to chlorpyrifos (paternal, maternal or pre-hatch model) was compared to the control offspring (not exposed to chlorpyrifos nor were their parents) of the same model. One-way ANOVA was used to test the effects of treatment on chlorpyrifos exposed and control groups where the dependent variable was the gene expression score. Two-way ANOVA included treatment and gender factors (independent variables) in the analysis (since a possible gender effect on the offspring’s genes’ expression was considered) and showed no significant interaction between gender and treatment in any of the tested models (paternal, maternal or pre-hatch). Consequently, after analyzing gene expression alterations in the female and male offspring separately, the results of both offspring were pooled. Post-hoc Tukey’s test was used when appropriate. A correlation analysis was performed using Spearman’s correlation, since part of the data did not show normal distribution, as indicated by the Shapiro–Wilk test. The significance level for all employed tests was considered at p < 0.05. Spearman’s correlations between expressed genes were calculated using Prizm GraphPad 9 software. Correlation networks (unsupervised and unweighted) were visualized using Cytoscape software [112], with the Cyfinder application applied for the detection of node communities (modules) according to the edge-betweenness criteria. Correlation matrices were visualized using R packages “ggplot2” and “ggcorrplot”. Venn diagrams were prepared in a designated webtool (https://bioinformatics.psb.ugent.be/webtools/Venn/ (accessed on 3 October 2022)).

PMC10003511

Jiawen Ren,Heyue Jin,Yumin Zhu

The Role of Placental Non-Coding RNAs in Adverse Pregnancy Outcomes

06-03-2023

placenta,miRNA,lncRNA,circRNA,adverse pregnancy outcomes

Non-coding RNAs (ncRNAs) are transcribed from the genome and do not encode proteins. In recent years, ncRNAs have attracted increasing attention as critical participants in gene regulation and disease pathogenesis. Different categories of ncRNAs, which mainly include microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are involved in the progression of pregnancy, while abnormal expression of placental ncRNAs impacts the onset and development of adverse pregnancy outcomes (APOs). Therefore, we reviewed the current status of research on placental ncRNAs and APOs to further understand the regulatory mechanisms of placental ncRNAs, which provides a new perspective for treating and preventing related diseases.

The Role of Placental Non-Coding RNAs in Adverse Pregnancy Outcomes Non-coding RNAs (ncRNAs) are transcribed from the genome and do not encode proteins. In recent years, ncRNAs have attracted increasing attention as critical participants in gene regulation and disease pathogenesis. Different categories of ncRNAs, which mainly include microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are involved in the progression of pregnancy, while abnormal expression of placental ncRNAs impacts the onset and development of adverse pregnancy outcomes (APOs). Therefore, we reviewed the current status of research on placental ncRNAs and APOs to further understand the regulatory mechanisms of placental ncRNAs, which provides a new perspective for treating and preventing related diseases. Adverse pregnancy outcomes (APOs) is a broadly defined term that includes various clinical outcomes such as preterm birth (PTB), miscarriage, macrosomia, low birth weight (LBW), birth defects, and others [1,2,3]. APOs are defined as the failure to give birth to offspring with a healthy appearance and function after pregnancy. Approximately 85% of women give birth at least once during their lifetime, whereas up to 30% of women may suffer from an APO [4,5,6]. At present, APOs are serious public health problems that have a significant impact on individuals, society, and finances worldwide [1,7,8]. The placenta plays an essential role in maintaining a healthy pregnancy, as well as aiding the growth and development of the fetus by providing a connection and barrier between mother and fetus, while abnormal alterations in the development and function of the placenta can cause a variety of pathological pregnancy conditions [9,10,11]. Placental formation and development involve complex networks of molecular regulation, and pregnancy-related diseases of placental origin are the result of a multifactorial combination of genetic and environmental influences. Therefore, we focused on the human placenta in this review. For many years, non-coding RNAs (ncRNAs) have been considered non-functional, while in recent years, the role of ncRNAs in post-transcriptional regulation has been discovered [12,13,14]. In addition, abnormal expression of ncRNAs is correlated with a variety of diseases, in which dysregulation of ncRNAs in the placenta is involved in various APOs (Figure 1). Therefore, this review provides a summary of recent studies concerning placental ncRNAs associated with APOs, which mainly include miRNAs, lncRNAs, and circRNAs. Understanding their functions and regulatory mechanisms provides new insights into the prevention and treatment of related diseases. ncRNAs represent approximately 60% of the transcriptional production of the human genome [15,16], and there is a close association between many diseases and ncRNA mutations or abnormal expression [17,18]. ncRNAs can be divided into two categories based on their length: small ncRNAs and lncRNAs [19,20,21]. In addition, circRNAs represent a new class of ncRNAs that are derived from a process of “back-splicing” of pre-mRNAs with covalent binding between the downstream splice donor site and upstream splice acceptor site [22,23,24] (Figure 2). miRNAs are a class of small ncRNAs (18–25 nt) that are endogenous, short, and highly conserved and are involved in a wide range of pathophysiological processes, including cell proliferation, growth, development, differentiation, and apoptosis [25,26,27]. The presence of miRNAs takes various forms: initially, miRNA exists as priRNA, which is processed into the precursor miRNA, called pre-miRNA. Then, pre-miRNA is cleaved by the Dicer enzyme and converted into mature miRNA [28,29,30]. miRNAs can bind to the target mRNAs, affecting the transcription and stability of the target mRNAs. In 1993, the identification of the first miRNA (lin-4) created the opportunity for miRNA research [31,32,33]. To date, more than 1000 different miRNAs have been identified in the human body, representing a powerful class of gene regulators [34]. Different from the short sequences of miRNAs, lncRNAs are usually longer than 200 nt, while some can be more than 100,000 nt and do not encode protein RNA transcripts [35,36]. The lncRNA primary transcripts were transcribed similarly to mRNA, including 5′ cap addition, 3′ poly (A), and splicing features. They are classified into five types according to their location in the genome: bidirectional lncRNA, intergenic lncRNA, sense lncRNA, antisense lncRNA, and intronic lncRNA [37,38,39]. There are increasing studies that have identified lncRNAs as a new class of regulatory molecules with the functions of scaffold, signal, and guide, and they are also involved in transcriptional interference [40,41,42]. circRNAs are a special type of endogenous ncRNAs [43,44]. Regarding circRNA formation, there are three main categories: exonic circRNA (ecircRNA), intronic circRNA (ciRNA), and exon-intron circRNA (EIcircRNA) [45]. circRNAs have various biological functions: (1) regulating the function of miRNAs by serving as a sponge for miRNAs; (2) acting as transcriptional regulators; (3) acting as protein translation vectors; and (4) regulating gene expression by interacting with proteins [46,47,48,49,50]. Moreover, it is obvious that circRNAs possess stable molecule properties, making them candidate markers for APOs [51,52]. Preterm births, referring to births at less than 37 weeks of gestation, of which 80% are spontaneous PTBs (sPTBs), are a worldwide health problem and one of the causes of infant morbidity and mortality [53,54,55]. The majority of PTBs are idiopathic and spontaneous and not directly related to the medical causes of the event, such as pre-eclampsia [56,57]. Although several traditional risk factors for PTB were confirmed previously, including smoking, stress, infection, and family history, an understanding of the critical biological mechanisms and perturbed networks of PTB remains lacking [58,59,60]. Recently, there were several studies indicating that placental ncRNAs may play roles in the pathogenesis of PTB, mainly miRNAs and lncRNAs (Table 1). Placenta insufficiency is an important cause of PTB, and abnormal regulation of placental miRNAs can cause the onset of PTB. A lot of miRNAs can be detected in the trophoblast cells of the placenta. For instance, according to the study of Morales-Prieto et al. [73], 762 miRNAs were detected in trophoblast cells isolated from the placenta in the first and third trimesters of pregnancy. In addition, the majority of miRNAs were expressed as clusters in trophoblast cells, with the chromosome 14 miRNA cluster (C14MC) and chromosome 19 miRNA cluster (C19MC) being the most prominent, and these clusters appeared almost exclusively in trophoblast cells. C19MC is mainly derived from trophoblast cells in late pregnancy and consists of at least 46 miRNAs [74]. According to recent studies, C19MC was discovered only in primates, with specific expression in the placental tissue [75,76,77]. Hromadnikova et al. [78] concluded that a characteristic phenomenon of PTB is having an upregulation of C19MC miRNAs by comparing the gene expression of C19MC miRNA in placental tissue between the following groups: full-term delivery, sPTB, and preterm premature rupture of membranes (PPROM). Tiozzo et al. [61] explored the expression of miRNA-519c, which is one of the types of C19MC, in placental tissue from PTB women and found that the level of miRNA-519c was significantly reduced in a preterm placenta with PPROM or chorioamnionitis than in a placenta delivered from spontaneous preterm delivery without PPROM or chorioamnionitis. Therefore, they speculated that the downregulation of miRNA-519c in the placentas may be linked to inflammation-associated PTB. The above studies reveal the importance of miRNAs in PTB and provide new opportunities for discovering candidate biomarkers in the field of PTB, and future studies may consider validating these findings with larger sample sizes in different populations. lncRNAs can regulate gene expression and are associated with PTB. Jiang et al. [62] found the overexpression of SNHG29 in PTB placentas compared to full-term placentas, which activated P53/P21 signaling and triggered cellular senescence, causing PTB. Premature rupture of membranes (PROM) and PTB are also inseparable. PPROM accounts for approximately one-third of all PTBs [79]. LUO et al. [80] used microarray analysis to identify 1954, 776, and 1050 differentially expressed lncRNAs in PPROM placentas in comparison with full-term birth (FTB), PTB, and PROM. Meanwhile, there were 449 and 3024 differentially expressed lncRNAs in PTB when compared with FTB and PROM groups, respectively. In addition, the study analyzed the metabolic pathways leading to PPROM and concluded that pathways of infection and inflammatory response, ECM-receptor interactions, apoptosis, actin cytoskeleton, and smooth muscle contraction are the major pathogenic mechanisms of PPROM. Additionally, the decreased expression of lncRNAs in the smooth muscle contraction pathway may increase placental smooth muscle contraction and induce PTB. They further investigated the connection of the differentially expressed lncRNAs between sPTB and PPROM placentas and found an overlap at a coding locus, associated with the differential expression of transcribed mRNAs at the same locus [81]. Based on the finding that lncRNAs overlap with coding sites, this leads to the conclusion that differentially expressed lncRNAs in sPTB and PPROM human placentas probably regulate related mRNAs according to different mechanisms, but detailed mechanisms are yet to be clarified. Overall, these studies have opened a new avenue of exploration to understand the mechanism and function of lncRNAs in PTB. However, there are few reports on the relationship between the lncRNAs and PTB, which needs to be further studied. Miscarriages consist of spontaneous abortion (SA) and recurrent miscarriage (RM). SA, affecting approximately 10–15% of all pregnancies, is clinically defined as pregnancy loss before 28 weeks of gestation without any external intervention [82,83]. More than 80% of SAs are early SAs (within 12 weeks of gestation), and approximately 50–60% of early SAs are associated with chromosomal abnormalities of the embryo [84,85,86]. RM is characterized by two or more consecutive miscarriages with the same sexual partner before 28 weeks of gestation, with an incidence of 1% to 5%, and the risk of recurrence increases with the number of miscarriages [87,88,89]. Several recent studies have shown that ncRNAs participate in the regulation of miscarriage by affecting trophoblast cell proliferation, invasion, migration, and apoptosis (Table 1). Placental implantation and embryonic development are important aspects of pregnancy, and placental dysfunction is related to various complications during pregnancy, including miscarriage [90,91]. The trophectoderm constitutes the most important cellular component for placental implantation and maturation. There are numerous transcription factors, extracellular matrix factors, and certain adhesion molecules that strictly regulate human trophoblast cells. Recently, large miRNAs were detected in the human placenta, some of which may trigger miscarriage by regulating trophoblast function. Tang et al. [92] performed a genome-wide screening of miRNAs to identify several miRNAs that were significantly differentially expressed in the chorionic villi tissue of patients with RM, with miRNA-4497 showing nearly 30-fold upregulated expression. They also investigated the potential targets of miRNA-4497 through software and databases to confirm the regulatory mechanism of miRNA-4497, finding that miRNA-4497 could target SP1 mRNA directly; therefore, the overexpression of miRNA-4497 in the placenta of RM could downregulate the expression of SP1, which, in turn, induces trophoblast apoptosis and leads to RM [63]. A similar result was found in another study that increasing the expression of miR-27a-3p in the placental villus tissue of patients with RM downregulated ubiquitin-specific protease 25 (USP25), which contributes to the epithelial-to-mesenchymal transition (EMT) process, thus, suppressing the migration and invasion of trophoblast cells [65]. miRNAs also have a regulatory role in SA. For instance, Lu et al. [64] collected placental villi tissue from healthy pregnancies and unexplained SA cases for assay analysis, and miR-135a-5p was found to be significantly upregulated in the unexplained SA group. Next, the interaction of miR-135a-5p with Protein Tyrosine Phosphatase Non-Receptor Type 1 (PTPN1) was explored, concluding that miR-135a-5p likely promotes unexplained SA by targeting PTPN1 to inhibit the proliferation, invasion, and migration of trophoblast cells. These studies suggest that understanding the mechanisms of miRNAs that affect the trophoblast cells of the placenta contributes to elucidating the pathogenesis of miscarriage, as well as developing new strategies to diagnose and treat miscarriage early. Additionally, the presence of SNPs in miRNA genes alters the expression or maturation of miRNAs and is involved in the occurrence of miscarriage [93,94]. However, current studies have mainly focused on the exploration of miRNA SNPs in blood, whereas studies on placental miRNA SNPs are still lacking, which is pending future research in this area. Researchers have identified several lncRNAs that were differentially expressed in the placental tissue of patients with miscarriage compared to people without miscarriage. Xiang et al. [67] found that lncRNA SNHG7-1 was downregulated in RSA placental villi compared to healthy pregnancy. In addition, SNHG7-1 targets miR-34a through the Wnt/β-catenin signaling pathway to regulate the proliferation and invasion of trophoblast cells, thereby being involved in RSA. Imprinted lncRNAs also have an important regulatory function during placental development. lncRNA H19 is an imprinted gene that is paternally imprinted and maternally expressed and has a function of limiting embryonic development and slowing the growth rate of the offspring [95,96,97]. He et al. [66] found that lncRNA H19 expression was significantly downregulated in the placental villi of patients with SA compared to women without SA but who terminated the pregnancy. They also found that H19 inhibits the function of miRNA let-7 to prevent mRNA degradation and thereby upregulates integrin β3 (ITGB3) expression, which indicates that it is involved in SA through the H19/let-7/ITGB3 axis. Sheng et al. [68] analyzed differentially expressed lncRNAs during mouse placental development through performing a microarray lncRNA screen and observed that the homologous sequence of imprinted lncRNA Rian, lncRNA MEG8, was found to be significantly upregulated in human SA villi, which inhibits the proliferation and invasion of trophoblast cells and is further involved in the development of unexplained SA. In summary, lncRNAs can induce the onset of miscarriage by regulating trophoblast function. circRNAs are likely to play a critical role in trophoblast cell invasion, EMT, apoptosis, and migration [98,99]. Recently, several researchers have begun to focus on the connection between circRNAs and SA. Zhu et al. [70] demonstrated that circPUM1 may promote the processes and anti-inflammatory effects of trophoblast cells through the miR-30a-5p/JunB axis, which prevents the formation and development of SA. Additionally, Li et al. [69] demonstrated that circ-ZUFSP regulates trophoblast cell migration and invasion by the CIRC-ZUFSP/miR-203/STOX1 pathway in RSA. Another study showed that circFOXP1 regulates trophoblast cell function through the miR-143-3p/S100A11 axis in placental tissue from patients with RSA [71]. Tang et al. [72] elucidated the expression of deregulated circRNAs and distinct competing endogenous RNA (ceRNA) networks by comparing unexplained recurrent spontaneous abortion (URSA) placental villi with those from healthy pregnancy by microarrays. They identified a unique circRNA, circRNA-0050703 (named circRNA-DURSA), that is downregulated in the placental villus of URSA. Furthermore, they found through the miR-760-HIST1H2BE axis that circRNA-DURSA could regulate apoptosis of trophoblast cells in URSA. There are few studies on circRNAs in miscarriage, and the specific mechanisms remain to be further explored. Hypertensive disorders of pregnancy (HDP) are pregnancy-specific disorders characterized by increased blood pressure during pregnancy, including gestational hypertension, pre-eclampsia, eclampsia, chronic hypertension with pre-eclampsia, and chronic hypertension [100,101,102]. The development of high-throughput sequencing techniques presents new ideas and methods for HDP research, and how placental ncRNAs participate in the pathological process of HDP has gained increasing attention, with PE being the most concerned. Placental ncRNAs can regulate placental development and the biological functions of trophoblast cells through their differential expression levels, which, in turn, affect the onset and progression of PE [103,104,105] (Table 2). Compared with placental tissue from healthy pregnancies, a population of differentially expressed miRNAs is present in the placenta with PE [126]. Using microarray methods, Brancaccio et al. [127] identified 298 differentially expressed miRNAs that are unique to the placenta of PE. Low-density lipoprotein receptor-associated protein 6 (LRP6) is a receptor for the Wnt/β-catenin signaling pathway, and its downregulation contributes to the development of PE. Zhou et al. [106] initially downloaded datasets from the Gene Expression Omnibus Database to evaluate miRNA candidates that regulate LRP6 with validation in PE and healthy maternal placental villi tissue using RT-qPCR. They found that miR-513c-5p was upregulated in PE, which promoted trophoblast cell apoptosis and inhibited cell proliferation, invasion, and migration by directly targeting LRP6 and downregulating its expression. The expression of miR-21 was found to be upregulated in PE placental tissues and could directly bind to the 3’-UTR of forkhead box M1 (FOXM1) to downregulate the expression of FOXM1, thereby inhibiting trophoblast cell proliferation and participating in the development of PE [107]. Gunel et al. [108] demonstrated that the expression level of miR-195 was decreased in the placental tissues of PE patients and may participate in PE by regulating trophoblast cell proliferation, apoptosis, and angiogenesis. Another study found that the expression level of miR-145-5p was reduced in PE placental tissue and negatively regulated fms-related receptor tyrosine kinase 1 (FLT1), thereby inhibiting trophoblast cell proliferation and invasion [109]. Aberrant expression of insulin-like growth factor-1 (IGF-1) is present in placental tissues of PE patients. Niu et al. [110] found that miR-30a-3p has overexpressed in PE placental tissues with downregulated IGF-1 expression, thereby affecting trophoblast apoptosis and invasion in order to participate in PE. Another study found that miR-548c-5p expression was significantly downregulated in the placental exosomes of PE patients and negatively regulated the expression of Recombinant Protein Tyrosine Phosphatase Receptor Type O (PTPRO) [111]. miR-210 was demonstrated to be expressed abnormally in the placental tissue of PE [128]. Placental hypoxia acts as a regulator for the occurrence and development of PE, and hypoxic culture can upregulate the expression of miRNA-210 in trophoblast cells, so miR-210 is closely related to PE [129]. Numerous other miRNAs are aberrantly expressed in PE placental tissue, such as miR-431, miR-518a-5p, and miR-124 being upregulated in PE placenta, while miR-3942, miR-532-5p, miR-423-5p, miR-127-3p, and miR-544 are downregulated [130,131]. To investigate the relationship between placental miRNAs and PE pathogenesis, the mechanisms of the placental miRNAs in the pathogenesis of PE will be further elucidated. Recently, lncRNAs were revealed to be involved in the development of PE by altering the biological functions of trophoblast cells. In the mechanism of lncRNA-miRNA interaction, lncRNAs act as ceRNAs for specific miRNAs, acting as miRNA sponge adsorbers and inhibiting the regulatory function of miRNAs, thereby regulating the expression of miRNA-targeted genes [132]. The expression of lncRNA DLX6-AS1 is upregulated in PE placentas. lncRNA DLX6-AS1 regulates the proliferation, invasion, and angiogenesis of trophoblast cells by acting as a sponge for miR-149-5p and influences the development of PE by affecting the expression of endoplasmic reticulum protein 44 (ERP44) [112]. The expression of lncRNA XIST is upregulated in the PE placenta, and XIST acts as a molecular sponge with miR-340-5p, which regulates the expression of potassium by inwardly rectifying channel subfamily J member 16 (KCNJ16), thereby inhibiting trophoblast cell proliferation and invasion and inducing cell apoptosis [113]. Yu et al. [114] demonstrated that the expression of lncRNA SNHG16 was decreased in the placental tissues of PE patients, whereas low expression of lncRNA SNHG16 inhibited trophoblast cell proliferation, migration, and invasion and induced apoptosis. The lncRNA SNHG16 functions as a ceRNA for miR-218-5p and is involved in the development and progression of PE by promoting the expression of LIM and SH3 protein 1 (LASP1) to regulate the biological function of trophoblast cells. Another study showed that the expression of lncRNA SNHG22 was significantly downregulated in PE placentas, with possible regulation of trophoblast cell migration and invasion by lncRNA SNHG22 through binding to miR-128-3p and regulation of Protocadherin 11 X-Linked (PCDH11X) expression [115]. A critical lncRNA involved in PE progression is the lncRNA TUG1. The expression of lncRNA TUG1 is downregulated in the PE placenta [116,117]. Li et al. [117] showed that lncRNA TUG1 may promote trophoblast cell proliferation, invasion, and angiogenesis by targeting miR-29b to participate in the development of PE. Liu et al. [116] further demonstrated that lncRNA TUG1 regulates the expression of vascular endothelial growth factor A (VEGFA) through binding to miR-29a-3p and activates the Ang2/Tie2 pathway, which promotes trophoblast cell proliferation, invasion, migration, and angiogenesis. Moreover, the expression of lncRNAs LINC00534 is upregulated in PE placental tissue [118], while the expression of lncRNAs BCYRN1 is downregulated [119]. Expression changes in lncRNAs in the placenta affect the biological function of trophoblast cells through multiple pathways, which, in turn, affects placental function and is closely related to the occurrence and development of PE. Consequently, investigating PE-associated lncRNA expression can contribute to further elucidating the pathogenesis of PE. Research has demonstrated that circRNAs are involved in the occurrence and development of PE. Ma et al. [133] identified 361 differentially expressed circRNAs in PE placentas, of which 252 were upregulated and 109 were downregulated. Differential expression of circRNAs in PE placental tissues can influence trophoblast cells’ biological functions by indirectly regulating target genes and signaling pathways as miRNA sponges. Zhang et al. [120] identified that the expression level of circSFXN was increased in PE placentas and was involved in the development of PE by inhibiting trophoblast cell invasion and angiogenesis. The expression of circZDHHC20 is upregulated in the PE placenta and circZDHHC20 has a molecular sponge role with miR-144. It is involved in the development and progression of PE by promoting the expression of grainy head-like 2 (GRHL2) and, thus, regulating the biological functions of trophoblast cells [121]. Zhou et al. [123] reported that the expression level of circPAPPA was decreased in PE placental tissues. circPAPPA influences the development of PE by being a sponge of miR-384 to regulate trophoblast cell proliferation and invasion, together with the regulation of signal transducer and activator of transcription 3 (STAT3) expression. Another study by Li et al. [122] showed that circPAPPA can also regulate trophoblast cells via the miR-3127-5p/HOXA7 axis, causing PE. The expression level of hsa_circ_0008726 was found to be elevated in PE placental tissue [124,125]. Shu et al. [124] demonstrated that hsa_circ_0008726 may act as a sponge for miR-345-3p and regulate the expression of RING1 and YY1 binding protein (RYBP), which, in turn, inhibits trophoblast cell migration, invasion, and EMT. Zhang et al. [125] revealed that hsa_circ_0008726 could be involved in PE by regulating the miR-1290-LHX6 pathway and inhibiting the proliferation, migration, and invasion of trophoblast cells. Numerous circRNAs were identified to be aberrantly expressed in PE placentas, but the potential functions and underlying mechanisms of these circRNAs in PE development have not been fully elucidated and need to be further investigated in the future. Gestational diabetes mellitus refers to healthy glucose metabolism before pregnancy but varying degrees of abnormal glucose metabolism during pregnancy, which is a public health problem related to metabolic disorders that affect approximately 9–15% of pregnancies worldwide [134,135,136]. Despite the fact that risk factors for GDM are known to include being overweight or obese before pregnancy, advanced age, race, previous history of GDM, and family history of diabetes, the specific pathogenesis of GDM is not clear [137,138,139]. Increasing evidence suggest that several ncRNAs are dysregulated in the placenta of GDM patients and are associated with abnormalities in placental structure, metabolism, and function [23,140] (Table 3). Research on ncRNAs in the placenta of GDM patients will contribute to elucidating the pathogenesis of GDM, screening for GDM-related biomarkers, and identifying high-risk women with GDM as early as possible. Recent studies have revealed that an increasing number of miRNAs play an essential role in the pathogenesis of GDM, yet how placenta-specific miRNAs and corresponding target genes are involved in the pathological process of GDM remains to be elucidated. Based on integrated miRNA and mRNA transcriptional profiling, Ding et al. identified 32 miRNAs and 281 mRNAs aberrantly expressed in the placenta of GDM patients, of which miR-138-5p is a critical gene [141]. Bioinformatics analysis showed that miR-138-5p was found to target the 3’-UTR of transducin β–like protein 1 (TBL1X), thereby inhibiting the proliferation and migration of trophoblast cells from participating in the development of GDM. Guan et al. [142] detected miR-21 expression levels in the placenta of 137 GDM patients and 158 healthy pregnant people by RT-qPCR, which showed that the expression of miR-21 was significantly downregulated in the GDM group. Further studies revealed that miR-21 can target peroxisome proliferator-activated receptor α (PPAR-α), which has a mutated binding site in the 3’-UTR that binds specifically to miR-21, thereby promoting trophoblast cell proliferation and migration. Similarly, miR-29b was found to be downregulated in the placenta of GDM patients and to target hypoxia-inducible factor 3A (HIF3A), which has two specific binding sites for miR-29b in the 3’-UTR, resulting in increased HIF3A expression, promoting trophoblast cell migration, and participating in GDM development [143]. Controlling inflammation and apoptosis in trophoblast cells is one of the critical aspects of the treatment of GDM. It was found that baicalein could achieve therapeutic effects in GDM by inhibiting the inflammation and apoptosis of trophoblast cells, which was mediated by miR-17-5p [150]. Meanwhile, they found that the expression of miR-17-5p was upregulated in the plasma and placenta of GDM patients. Zhang et al. [144] examined the expression levels of miR-30d-5p in the placentas of GDM patients and healthy control pregnant people, which showed that the expression levels of miR-30d-5p were significantly downregulated in the GDM group. Further studies revealed that miR-30d-5p promoted apoptosis and inhibited the proliferation, migration, invasion, and glucose uptake ability of trophoblast cells by negatively regulating the expression of Ras-related protein (RAB8A). A link exists between the level of placental exosomes and placental dysfunction; therefore, exosomes play a key role in the study of the pathological process and treatment of GDM and represent an area of great interest [151,152]. The level of placenta-derived exosomes (PdE) was found to be higher in patients with GDM than in control pregnant people [153]. In addition, PdE levels were positively correlated with maternal body mass index (BMI), glucose concentration, and fetal weight, which means that PdE may be involved in maternal metabolic adaptation to pregnancy [153,154]. Zhang et al. [155] conducted a cross-sectional study to identify the expression levels of miRNAs in the placenta and circulating exosomes composed primarily of PdE in GDM patients, and 157 differentially expressed miRNAs were identified in GDM placental tissue, among which miR-125b was significantly downregulated and miR-144 was significantly upregulated in both the placenta and circulating exosomes. Further research revealed that these two miRNAs are mainly involved in the occurrence of GDM by affecting glucose metabolism [155]. Similarly, another study revealed that the placenta-derived exosomes miR-140-3p and miR-574-3p are significantly downregulated in patients with GDM and target VEGF, thereby promoting the proliferation, migration, and tube formation of umbilical vein endothelial cells [145]. The investigation of exosomal miRNAs will provide a better comprehension and exploration of the pathogenesis and development of GDM, enabling more effective diagnosis and new treatments. lncRNAs are extensively involved in cell proliferation, migration, and apoptosis and are intimately related to the pathogenesis of GDM. Zhang et al. [146] identified the lncRNA maternally expressed gene 3 (MEG3) levels in the blood and placental villi tissue of GDM patients and control pregnant people by RT-qPCR; they found that MEG3 expression levels were significantly upregulated in the GDM group, and MEG3 overexpression may target miR-345-3p and reduce its level, thereby inhibiting trophoblast cell migration and invasion and inducing apoptosis. According to another study, lncRNA-MALAT1 expression levels were increased in the placentas of GDM patients, while siRNA intervention could inhibit inflammation development and trophoblast cell proliferation, invasion, and migration by downregulating lncRNA-MALAT1 expression, which may be achieved by regulating the TGF-β/ NF-κB signaling pathway [147]. Wang et al. [148] revealed that the expression level of LncRNA plasmacytoma variant translocation 1 (PVT1) in the placenta of GDM and PE patients was significantly lower than that of healthy placenta, which could significantly inhibit the invasion and proliferation of trophoblast cells. Further studies have indicated that PVT1 positively regulates AKT phosphorylation and the expression of GDPD3, ITGAV, and ITGB8, thus, participating in GDM. Altered DNA methylation of H19 and insulin-like growth factor 2 (IGF2)-imprinted genes is closely associated with fetal and placental development [156]. Su et al. [157] demonstrated that the expression levels of IGF2 were significantly higher in cord blood and placental tissues of GDM patients, while the expression levels of H19 were significantly lower. Further studies confirmed a strong association between IGF2/H19 methylation and intrauterine hyperglycemia-induced macrosomia. Although the research on the molecular mechanisms and signaling pathways of lncRNAs involved in GDM has achieved some success, further research is needed to support the development of lncRNAs as clinically effective biomolecular markers for the treatment of GDM in the future. Until now, few studies have been conducted on the relationship between placental circRNAs and GDM. Yan et al. [158] used next-generation sequencing (NGS) to identify 482 aberrantly expressed circRNAs in placental villus tissue from GDM patients, of which 227 were upregulated and 255 were downregulated. The GO and KEGG pathway revealed that these differentially expressed circRNAs were significantly enriched in pathways related to gluconeogenesis and lipid metabolism. Another study identified 46 differentially expressed circRNAs in GDM patients that were significantly enriched in the advanced glycation end-products receptor for the advanced glycation end-products (AGE-RAGE) signaling pathway, playing an important role in diabetic complications such as diabetic nephropathy and diabetic retinopathy [159,160]. Another study found that circMAP3K4 was highly expressed in the placenta of GDM patients, and additionally, circMAP3K4 could inhibit the insulin-PI3K/Akt signaling pathway via the miR-6795-5p/PTPN1 axis, which may be associated with GDM-associated insulin resistance [149]. The insulin-PI3K/Akt pathway promotes cellular glucose uptake and regulates cell growth, which is critical for insulin signaling [161]. In spite of these studies demonstrating the possible involvement of circRNAs in GDM, the specific mechanism of circRNA involvement in GDM has not been fully elucidated, and extensive experimental studies are needed to determine whether they can be used as potential biomarkers. The defining characteristic of macrosomia is a birth weight of over 4000 g, and the incidence of macrosomia has been increasing in recent decades [162,163,164]. The occurrence of macrosomia is an increased risk factor for maternal postpartum infections, and it is associated with several adverse perinatal outcomes, including prolonged labor and increased rates of cesarean delivery [165]. Compared to otherwise healthy infants, macrosomia leads to higher risks for childhood obesity, adult obesity, hypertension, diabetes, and other age-related diseases [166,167]. Existing research recognizes the critical role of regulating fetal growth played by placental ncRNAs (Table 4). The exploration of the correlation between placental ncRNAs and the birth outcome of macrosomia is beneficial to further understand the mechanism of macrosomia and to provide interventions and treatments. It is known that gestational diabetes (GDM) increases the risk of macrosomia [163,176,177,178]. Li et al. [168] compared miRNA profiles from the placentas of healthy and GDM pregnant women through microarray analysis and found that miR-508-3p was significantly upregulated in the GDM group and directly downregulated PIKfyve accordingly. PIKfyve is a phosphoinositide 3-phosphate-5-kinase that negatively regulates the epidermal growth factor receptor (EGFR). Therefore, increased expression of miR-508-3p in women with GDM is associated with inhibition of PIKfyve and abnormal activation of EGFR/PI3K/AKT signals, resulting in fetal overgrowth. At present, the prevention and control of the occurrence of macrosomia can be effectively achieved by strengthening the screening and management of GDM, but the cause of non-diabetic fetal macrosomia (NDFMS) remains to be studied. Several studies have proven that the abnormal expression of miRNAs in the placenta is correlated with macrosomia. Guo et al. [169] identified miR-141-3p, a key miRNA with abnormal expression in the placenta of NDFMS, through preliminary screening of miRNA microarrays and further verification via quantitative RT-PCR (qRT-PCR). It was further proven that increased expression of miR-141-3p may regulate the proliferation of trophoblast cells in later pregnancy to participate in the onset and progression of NDFMS through an in vitro cellular model and a mouse pregnancy model. Meanwhile, dysregulation of the miR-17-92 cluster in the placenta may cause various diseases, and previous studies have shown that miRNAs in the miR-17-92 cluster play an essential role in cell cycle migration, invasion, apoptosis, and proliferation. Li et al. [170] analyzed the expression levels of miRNAs in the miR-17-92 cluster between the placentas of healthy neonatal and macrosomia births, which found that miR-18a, miR-19a, miR-20a, miR-19b, and miR-92a were significantly increased in the macrosomia group compared to the healthy group, which may be due to the upregulation of miRNA-processing enzymes Drosha and Dicer. Additionally, they demonstrated that the miR-17-92 cluster targets SMAD4 and RB1 in trophoblast cells to attenuate cell apoptosis, promote cell proliferation, and accelerate cell entry into the S phase, which contributes to macrosomia development. According to another study, IGF2-derived miR-483-3p was found to be overexpressed in the placentas of macrosomia births and promoted trophoblast cell proliferation by downregulating its target gene RB1 inducible coiled-coil 1 (RB1CC1) [171]. Song et al. [172] investigated the expression of lncRNAs in the placentas of average-birth-weight newborns and GDM macrosomia newborns, which showed that 2962 lncRNAs were upregulated and 1921 lncRNAs were downregulated in the placentas of macrosomia births compared to the healthy group. According to qRT-PCR, LncRNA SNX17 showed a significant upregulation trend in the placentas of macrosomia births. Additionally, this lncRNA may promote the proliferation of trophoblast cells via the miR-517a/IGF-1 pathway and serve a function in the placental regulation of macrosomia. Another study identified 2929 upregulated lncRNAs and 2127 downregulated lncRNAs in the placentas of macrosomia compared to average-birth-weight babies. It also demonstrated that lncRNAs have a significant differential expression in the placentas of macrosomia, which was probably associated with the development of NDFMS [179]. Lu et al. [173] identified 892 differentially expressed lncRNAs (763 upregulated and 129 downregulated) based on microarray analysis of lncRNAs in 48 NDFMS and 48 control placentas, which were further validated by selecting lncRNA USP2-AS1 as a candidate lncRNA for subsequent experiments, and the downregulation of lncRNA USP2-AS1 was found to possibly participate in NDFMS development by promoting trophoblast cell viability. Su et al. [157] found that lncRNA H19 showed high methylation and low expression in the placental tissues of macrosomia with intrauterine hyperglycemia, and the methylation and ex-pression levels of lncRNA H19 were significantly correlated with the birth weight of fetuses with intrauterine hyperglycemia. Until now, there have been several related studies on the association of lncRNAs with macrosomia, but the specific mechanism remains to be further investigated. Although fewer studies have been conducted on how circRNAs are involved in macrosomia, an association between the two was demonstrated. Wang et al. [174] demonstrated that circ-SETD2 was significantly expressed in the placentas of macrosomia births compared with healthy donors via microarray assay. Additionally, bioinformatics analyses revealed that the expression of circ-SETD2 was upregulated to strengthen the trophoblast cell proliferation and invasion, while miR-519a existed at the binding sites for both circ-SETD2 and phosphate, and the tensin homolog was deleted on chromosome 10 (PTEN). Therefore, the circ-SETD2/miR-519a/PTEN axis regulates fetal weight by controlling trophoblast cell proliferation and invasion. These discoveries enhance our comprehension of the mechanisms of macrosomia, which can be explored in the future by focusing on the circ-SETD2/miR-519a/PTEN axis to facilitate the development of therapeutic strategies for this disease. Low birth weight refers to full-term newborns with a birth weight lower than 2500 g, and it affects 15% to 20% of all newborns worldwide [180,181,182]. Fetal growth is influenced by the function of the placenta, which further affects the health of the newborn and increases the risk of disease in later life [183]. The human placenta expresses more than 600 miRNAs and has a specific miRNAs profile [184]. Thus, it is worth investigating the contribution of placental miRNAs and their crucial role in LBW, which is significant to understand the potential molecular mechanisms of LBW. Song et al. [175] identified a significant increase in placental miR-517a expression with LBW when compared to those with an average birth weight. Furthermore, it was found that overexpression of miR-517a significantly inhibited trophoblast cell invasion, suggesting that miR-517a may contribute to LBW through inhibition of trophoblast invasion. To date, there are few studies investigating the involvement of placental ncRNAs to regulate LBW, which leaves a need for further research in the future. Trisomy 21 (T21) was reported in recent studies as the main birth defect associated with abnormal expression of placental ncRNAs. T21 is the most common chromosomal aneuploidy, referred to as Down syndrome (DS), with an incidence of approximately 1:700 live births [185,186,187]. Individuals with T21 are at increased risk of developing a variety of diseases, including congenital heart defects, gastrointestinal abnormalities, leukemia, and neurodegenerative diseases [185,188,189]. To date, differential expression miRNAs in T21 are characterized as mainly originating from human chromosome 21, while a genome-wide comprehensive study of human genes and miRNAs may be critical for understanding the mechanisms underlying T21-related abnormalities. Lim et al. [190] investigated the expression levels of genes and miRNAs in placental villus tissue of normal and T21 human fetuses and found significantly differential expression of 110 mRNAs (77 upregulated and 33 downregulated) and 34 miRNAs (16 upregulated and 18 downregulated). By predicting the functions and interactions between mRNAs and miRNAs using bioinformatics tools, they observed that there was a negative correlation between the expression levels of 8 miRNAs and 17 mRNAs in the T21 group, which includes 4 mRNAs with increased expression located on chromosome 21. In this study, they also identified the interaction network of three upregulated genes (U2AF1, DYRK1A, and KSR1), and four downregulated genes (MRPL43, F2RL1, TICAM2, and MAP3K5) in the placentas of T21, concluding that miRNA expression alteration may induce alterations in the levels of target genes (DYRK1A, MAP3K5) in T21, thus, playing a critical role in the pathogenesis of T21. Another study identified 12 differentially expressed miRNAs in T21 placenta, with a total of seven miRNAs confirmed to be upregulated (miR-99a, miR-542-5p, miR-10b, miR-125b, miR-615, let-7c, and miR-654), three of which (miR-99a, miR-125b, and let-7c) were located on chromosome 21 [191]. Modi et al. [192] investigated three miRNAs, miR-99a, miR-125b, and let-7c, for their expression patterns in chorionic tissue collected from full-term pregnancies with spontaneous rupture, and they demonstrated a potential role for these Chr-21 derived miRNAs in T21-related fetal membrane rupture and fetal membrane defects. Lim et al. [193] used microarray technology to analyze 1349 expression levels of miRNAs in whole blood and placenta samples from pregnant women with euploid or T21 fetuses and whole blood from non-pregnant women that identified 299 miRNAs that can be reasonably separated between the whole blood and placenta. Among the identified miRNAs, 150 miRNAs were upregulated and 149 were downregulated in the placentas, and most of the upregulated miRNAs were members of miR-498, miR-379, and miR-127 clusters. In addition, it was found that two miRNAs, miR-1973 and miR-3196, may regulate a total of 203 target genes participating in the brain, central nervous system, and neurological development and may be potential biomarkers for non-invasive testing for T21 in fetuses. There is also a series of congenital diseases that were reported in recent years to be correlated closely with miRNAs in the placenta. For example, Radhakrishna et al. [194] investigated the levels of miRNAs in the placentas of ventricular septal defect (VSD) births, which revealed that miR-191, miR-548F1, miR-148A, miR-423, miR-92B, miR-611, miR-2110, and miR-548H4 showed significant changes and that these eight miRNAs could be used as potential biomarkers for the detection of VSD. Although such similar research is just beginning, it is worth waiting for a clearer recognition of the relationship between placental ncRNAs and congenital anomalies. Recently, numerous studies have emerged offering broad discussions about placental ncRNAs and APOs. Most of the studies mainly evaluated the specific miRNAs and lncRNAs associated with APOs, while the field of circRNAs is still lacking. Notably, miRNAs, lncRNAs, and circRNAs may be involved in gene regulation by two or three of them together in the development of disease. Accordingly, we expected more comprehensive studies on circRNAs and APOs that could also be conducted to bridge the current gaps in the research. Current studies mainly analyze the relationship between the differential expression of ncRNAs and APOs by high-throughput sequencing, while future work is needed to fully understand the implications of the specific mechanisms related to disease occurrence and development. In summary, the study of ncRNAs and gene regulatory networks related to APOs is beneficial for further understanding the pathogenesis of APOs, and this may also provide new ideas for early diagnosis, prevention, and treatment.

PMC10003512

Lin Ma,Hualin Chen,Wenjie Yang,Zhigang Ji

Crosstalk between Mesenchymal Stem Cells and Cancer Stem Cells Reveals a Novel Stemness-Related Signature to Predict Prognosis and Immunotherapy Responses for Bladder Cancer Patients

01-03-2023

bladder cancer,cancer stem cell,immunotherapeutic response,mesenchymal stem cell,stemness,intercellular communication,SLC2A3,tumor microenvironment

Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management.

Crosstalk between Mesenchymal Stem Cells and Cancer Stem Cells Reveals a Novel Stemness-Related Signature to Predict Prognosis and Immunotherapy Responses for Bladder Cancer Patients Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management. Bladder cancer represents one of the most common urological malignancies, with over 500,000 newly diagnosed cases and 200,000 deaths each year worldwide [1]. Bladder cancer can be classified into non-muscle invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) based on the depth of invasion. Although MIBC only accounts for approximately 30% of the newly diagnosed, it is characterized by aggressiveness, metastasis, drug resistance, and recurrence, which are responsible for the decreased cancer-specific survival after R0 resection [2]. Cancer stemness, defined as the stem-cell-like phenotype of cancer cells, including self-renewal and differentiation, plays a critical role in the progression, metastasis, resistance to drugs, and recurrence of several cancers, including colorectal cancer (CRC) [3], hepatocellular carcinoma [4], and BCa [5]. Cancer stem cells (CSCs) and mesenchymal stem cells (MSCs) have been recognized as the main contributors to stemness maintenance [6]. Considering the important roles of CSCs in tumor initiation, conventional drug resistance, and the origin of metastasis, they have been considered the targets in cancer treatment [7]. MSCs infiltrate into the tumor microenvironment (TME) and promote tumor development through the secretion of pro-survival factors. In TME, MSCs support the cancer stemness by protecting tumor cells from physiological stress and therapies [6]. Furthermore, the exosome secretion or extracellular vesicles facilitate the intercellular crosstalk and promote angiogenesis, progression, resistance, and quiescent cancer cell activation [8]. Therefore, decoding the communication networks may shed light on the cancer stemness and identify potential therapeutic targets enhancing effective cancer treatment. Compared to conventional bulk RNA-seq technology, single-cell RNA-seq (scRNA-seq) facilitates decoding the intricate communication networks and uncovering molecular mechanisms at the single-cell level. In the study, we first integrated two BCa scRNA-seq datasets and built the intercellular communication network between CSCs and MSCs. Then, the gene regulatory network (GRN) analysis was performed to identify activated regulons (the transcription factors and their target genes) within the communication network. A stemness-related signature (Stem. Sig) was subsequently constructed, and it showed predictive values for prognosis and immunotherapy response. Ultimately, we identified the hub gene SLC2A3 of the Stem. Sig and validated its biological features in BCa cells by wet-lab experiments. Based on cell markers reported in the literature, we first identified CSCs and MSCs populations from the integrated BCa scRNA-seq datasets [6,9,10,11] (Figure S1). Following the Seurat pipeline, we re-clustered CSCs into three subpopulations and presented the top 10 markers of each subpopulation in Figure 1a. Cluster 0 highly expressed collagen gene family including COL4A1, COL3A1, COL4A2, COL1A1, COL1A2, and COL6A2. Thus, we named Cluster 0 “ECM-related CSCs.” Enrichment analysis revealed that collagen fibril organization, extracellular matrix/structure organization, and ECM-receptor interaction pathway were enriched (Figure 1b). Marker genes of Cluster 1 were enriched in tissue/organ development; thus, Cluster 1 was defined as “quiescent CSCs” (Figure 1c). As for Cluster 2, IL-6, CCL2, and CCL21 were upregulated. And Cluster 2 markers were enriched in immune-related biological progress and pathways, such as interferon-gamma, TNF signaling pathway, and complement and coagulation cascades. So, we named Cluster 2 “immune-related CSCs” (Figure 1d,e). Pseudotime analysis demonstrated that quiescent CSCs were projected onto the root of the developmental trajectory, and ECM-related CSCs and immune-related CSCs were projected onto two branches (Figure 1f). BEAM analysis demonstrated that branch-dependent genes were collagen gene family and immune-related genes. They were responsible for quiescent CSCs’ developmental direction (Figure 1g). MSCs were also clustered into three subpopulations (Figure S2a). Markers of Cluster 0 were mainly enriched in leukocyte recruitment-related biological progress, including leukocyte adhesion to vascular endothelial cells, regulation of leukocyte cell-cell adhesion, and regulation of cellular extravasation. Thus, Cluster 0 was defined as “innate immune-related MSCs” (Figure S2b). In the top 10 markers of Cluster 1, COL4A1 was identified. In combination with enrichment analysis, we defined Cluster 1 as “ECM-related MSCs” (Figure S2c). According to the upregulated genes and enriched terms, we named Cluster 2 “adaptive immune-related MSCs” (Figure S2d and Figure 1h). Pseudotime analysis revealed that immune-related MSCs were projected on the root and developed into ECM-related MSCs with the developmental trajectory (Figure 1i). BEAM demonstrated the expression status of the collagen gene family and immune-related genes changed from the early developmental stage to the top right of the tree through branch point 1 (Figure 1j). In the MSCs-CSCs communication network, ECM-related MSCs served as the main sender cells. VMF, COL4A1, CTGF, and SERPING1 were highly activated in the top 20 ligands. It has been well-documented that the four ligands were involved in tumor cell proliferation, invasion, and migration of several malignancies, including hepatocellular carcinoma, gastric adenocarcinoma, and BCa [12,13,14] (Figure 2a). Based on the 20 top ligands, we further constructed a ligand-target network predicting corresponding targets (Figure 2b). In combination with SCENIC, we obtained the highly activated regulons in the ligand-target network and compiled these genes to a communication signature named Stem. Sig (Figure 2c,d, Table S1). Based on Stem. Sig., we clustered the TME of TCGA-BLCA into two molecular subclusters via unsupervised consensus clustering. Both the CDF curves and PAC scores indicated the optimal clustering number was 2 (Figure 3a–c). Patients in cluster 1 had more unfavorable prognoses compared to those in cluster 2 (Figure 3d). Besides, cluster 1 had a significantly higher proportion of high-grade and late-stage BCa patients compared to cluster 2, indicating the association between cluster 1 and the clinical progression of BCa (Figure 3e). To verify the distinct stemness features, we compared the mRNAsi index and activities of stemness-related signatures between two clusters. Results showed that cluster 1 was characterized by a high mRNAsi index and highly activated signatures, suggesting the higher cancer stemness of tumors in cluster 1 (Figure 3f,g). Robertson et al. [15] reported three main molecular subtypes of TCGA-BLCA, namely luminal subtypes (further divided into Luminal-papillary, Luminal-Infiltrated, and Luminal), one “Basal/Squamous” subtype, and one “Neuronal” subtype. In our study, cluster 1 had a higher proportion of Basal/Squamous BCa compared to cluster 2 (Figure 3h). Functional enrichment analysis revealed that most hallmark gene sets were also upregulated in cluster 1, including EMT, IL-6/JAK/STAT3 signaling, and INFA signaling (Figure 3i). Considering the profound mechanisms between stemness and immunity, we next analyzed the immune cell infiltration abundances between two clusters. Results showed that the infiltration levels of 28 immune cell subsets were all higher in cluster 1 than those in cluster 2 (Figure 4a). To verify the robustness, we employed six other TME decoding algorithms, including CIBERSORT, EPIC, MCP-counter, quanTIseq, TIMER, and xCell. Similar results were found (Figure S3). Furthermore, most immunity-related factors, including chemokines, MHC molecules, immunostimulators, and immunoinhibitors, were highly expressed in cluster 1 (Figure S3). These findings indicated that the BCa of cluster 1 was characterized by an inflamed TME. The enrichment scores of a seven-step anticancer immunity cycle (Figure 4b) and immunotherapy-predicted pathways (Figure 4c) were also higher in cluster 1 compared to those in cluster 2. Besides, both TCR and BCR evenness were higher in cluster 1 (Figure 4d). Pathway enrichment analysis uncovered that cluster 1 was linked to immunity-related pathways, including antigen processing and presentation, natural killer cell-mediated cytotoxicity, and PD-L1 expression and PD-1 checkpoint pathway in cancer, and other common pathways, including JAK-STAT, NK-kappa B, and PI3K-Akt signaling. Given the inflamed TME and potently effective immunity in cluster 1, we hypothesized the effective responses to immunotherapy of BCa patients in this cluster. Thus, we analyzed the expression patterns of four immunotherapeutic predictors, including IFNG, CYT, GEP, and TMB, between two clusters. Figure 4f showed that all four factors were significantly highly expressed in cluster 1. Taken together, BCa of cluster 1 had an inflamed TME, and patients in this cluster may benefit from ICIs therapy compared to those in cluster 2. To further unravel the value of the Stem. Sig. in predicting immunotherapeutic responses, we analyzed two ICIs-treated BCa cohorts, IMvigor 210 and Rose2021UC. In the IMvigor 210 cohort, two molecular subclusters were identified based on the Stem. Sig. via consensus clustering (Figure S4a). Cluster 1 was related to a more favorable prognosis (Figure 5a), a higher proportion of responders (CR/PR, Figure 5b), and a higher proportion of inflamed TME phenotypes (Figure 5c) compared to cluster 2. Similarly, in the two molecular subclusters of Rose2021UC (Figure S4b), cluster 1 was linked to better survival (Figure 5d) and a higher proportion of responders (Figure 5e). Besides, the TMB, a positive predictor of immunotherapy response, was higher in cluster 1 (Figure 5f). Consistent with these two ICI-treated cohorts, cluster 1 in TCGA-BLCA was supposed to have more responders to both PD-1 and CTLA-4 inhibitors, as predicted by TIDE and SubMap analyses (Figure 5g,h). To facilitate translational medicine, we decided to develop a consensus model based on the Stem. Sig. that may be friendly used in clinical settings. First, we selected prognosis-related genes from the Stem. Sig. by univariate cox regression analysis. Then, we developed an integrated machine-learning framework of 101 combinations to select the optimal model with the highest C-index. Finally, the optimal prognostic model was constructed by both-direction StepCox and RSF (Figure 6a). The relative importance of each model gene is illustrated in Figure 6b. Besides, the model demonstrated robust prognostic prediction performance in TCGA-BLCA (Figure 6c), GSE31684 (Figure 6d), GSE13507 (Figure 6e), GSE32548 (Figure 6f), and GSE32894 (Figure 6g). As the most significant gene in the prognostic model, SLC2A3 was exclusively upregulated in ECM-related CSCs (Figure 7A) and correlated with the stemness score determined by the enrichment score of the Stem. Sig. (Figure 7B). Survival analysis demonstrated the prognostic value of the gene (Figure 7C). Cancer-immunity cycle represented the biological processes of tumor cell elimination [16]. Figure 7D demonstrated that the overexpression of SLC2A3 was associated with an impaired cancer-immunity cycle. Further investigation uncovered that M2 macrophage polarization factors were also upregulated (Figure 7E). All these findings suggested the critical roles of SLC2A3 in the stemness of BCa. We further analyzed the stemness traits of SLC2A3 by tumorsphere formation assay. As shown in Figure 8a, the number and sizes of spheres were promoted in SLC2A3 upregulated cells, which was markedly attenuated by SLC2A3 inhibition. Besides, the expression levels of stem cell markers were evaluated (Figure 8b). Results showed that SLC2A3 affected the CSC traits of BCa cells. Cancer stemness plays a crucial role in tumor initiation, progression, drug resistance, and metastasis. The reciprocal cell communications between CSCs and other cells, especially MSCs, maintain the stemness. Therefore, deciphering the communication networks can shed light on the molecular mechanisms of stemness and facilitate novel biomarker identification. CSCs have been well studied in BCa and are thought to be responsible for the BCa initiation and maintenance of tumor growth [17]. They also regulate the angiogenesis and metastasis of BCa and are associated with a higher risk of recurrence. At the single-cell level, Wang et al. generated a comprehensive BCa cancer-cell atlas consisting of 54,971 single cells and highlighted the critical roles of the CSC population in recurrent BCa [10]. Similarly, a subpopulation with overexpressed cancer stem cell markers SOX9 was discovered in the single cells derived from one T3-stage MIBC [11]. Further SCENIC analysis of the critical TF regulatory network revealed the preferential upregulation of SOX9 and SOX2 in this subpopulation. And the key roles of SOX2 and SOX9 in the regulation of cancer stemness and tumor metastasis have been well-documented in previous studies [18,19]. For MSCs, the biological roles of exosomes in BCa cells have been reported [20,21]. However, the understanding of MSCs at the single-cell level is limited in BCa. In the study, we first identified subpopulations of CSCs and MSCs in the integrated scRNA-seq dataset. Based on the communication network and GRN, the Stem. Sig was developed and showed satisfactory performance in the prediction of prognosis and response to immunotherapy. Finally, a prognostic model involving SLC2A3 was constructed and demonstrated robust performance in prognostic prediction. According to the enrichment analysis, the MSCs and CSCs can be categorized into two functional properties: ECM-related and immune-related. ECM serves as a major structural component of the TME and constantly undergoes remodeling progress with tumor development. As an essential role in the stem cell niche, ECM participates in stemness maintenance, stem cell proliferation, and self-renewal [22]. Compared to normal ECM, tumor ECM is characterized by stiffness due to overexpressed collagens. Stiffed ECM comprises a physical barrier that hinders the transport of drugs to the stem cell niche and survives the cancer stem cell. Furthermore, ECM influences the infiltration of immune cells into the TME. ECM promotes the recruitment of M2 macrophages and Tregs, whereas it inhibits the infiltration of CD8+ T cells. For example, the PI3K-AKT signaling pathway was upregulated in our ECM-related MSCs, which facilitates the immune escape of CSCs [23]. Besides, driven by immunomodulatory genes, CSCs reduce the infiltration density of anti-tumor immune cells and sculpt an immunosuppressive TME with a high abundance of pro-tumor immune cells like M2 macrophages. Targeting the cancer stemness will facilitate the chemotherapeutic drug delivery to the stem cell niche and reshape the immunological feature of TME. In the communication pattern, ECM-related MSCs functioned as the main sender cells in the ligand-receptor network, with upregulated VEGFC, ADAM17, VWF, and EDN1. As a key regulator of angiogenesis in cancer, VEGFC can be activated by oncogenes, growth factors, and stress, such as hypoxia. Apart from effects on vascular functions, including vascular constriction and normalization, VEGF can promote tumor growth and metastasis by binding receptors on tumor cells and inhibiting the maturation of immune cells. Moreover, VEGF-mediated signaling contributes to the function of CSCs and promotes tumor initiation. The crucial role of VEGF in the tumor niche makes it a promising target for anti-cancer therapy. Previous studies have reported that patients with advanced-stage cancers benefit from VEGF-targeted therapy with or without chemotherapy [24]. The pro-tumoral properties of ADAM17, VWF, and EDN1 have been well-studied in the literature, and targeted therapy has demonstrated the effects of tumor-inhibiting [24,25]. CTGF, COL4A1, and TFGB1 were overexpressed in ECM-related CSCs/MSCs according to the communication pattern. The three genes drive tumorigenesis, invasiveness, and chemotherapeutic resistance in various cancers. Except for COL4A1, the crucial roles of CTGF and TFGB1 in stemness regulation have been previously reported [26,27]. Regulons EGR1, MEF2C, and KFL9 were activated in ECM-/immune-related CSCs. For quiescent CSCs, three regulons (GATA3, KLF5, and E2F3) were upregulated, and GATA3 demonstrated exclusively activated status. Chen et al. uncovered the important function of GATA3 in quiescent cellular status. Upregulated GATA3 suggested a dormant status, and GATA3 knockdown induced a proliferative status shift [28]. These activated regulons formed a novel Stem. Sig that divided the bulk tumor samples into two molecular subtypes. Two molecular subtypes with distinct stemness properties were characterized by different immunological phenotypes: high stemness features indicated inflamed TME. Our results were consistent with the previous findings that CSC with high stemness demonstrated unfavorable prognosis, inflamed TME, and high response rate to immunotherapy [3]. Based on the Stem. Sig, we developed a prognostic model. Patients in the high-risk score group suffered from unfavorable prognoses. Within the risk model, the hub gene SLC2A3 harbored the highest hazard risk and demonstrated a positive correlation with the Stem. Sig enrichment score. In our study, upregulated SLC2A3 contributed to the unfavorable prognosis of BCa. Similarly, Yang et al. developed a prognostic signature including SLC2A3 for BCa patients and found that overexpressed SLC2A3 was related to high-risk score (poor prognosis) [29]. The correlation between upregulated SLC2A3 and decreased OS has been widely reported in other solid tumors, including CRC and breast cancer [30,31]. Decoding the molecular mechanisms unraveled that SLC2A3 promoted invasion, EMT progress, and stemness [32]. In BCa, SLC2A3 suppression inhibited tumor cell glucose uptake and proliferation and promoted cell apoptosis [33]. In our study, SLC2A3 was involved in the infiltration of M2 macrophages in BCa and contributed to the impaired anti-tumor immunity cycle, consistent with the findings of a gastric cancer study [34]. Intriguingly, SLC2A3 was found exclusively upregulated in ECM-related CSCs that facilitated ECM stiffness. In addition to the role of SLC2A3 in stem traits of BCa, targeting SLC2A3 may enhance effective cancer treatment. Interestingly, Xu and colleagues 2015 reported the striking findings of targeting SLC2A3 by siRNA-based nanomedicine in glioma therapy [35]. Collectively, targeting SLC2A3 therapy is promising for BCa patients. Two BCa scRNA-seq datasets were downloaded from the Gene Expression Omnibus (GEO) database by accession number: GSE130001 [36] and GSE146137 (mice data was discarded) [37]. We performed the quality control progress as previously described [38]. The normalization, integration, dimension reduction, and clustering were conducted stepwise according to the Seurat manual [39]. Subsequently, we identified the MSCs and CSCs populations by previously reported cell markers. BCa bulk RNA-seq datasets were procured from GEO and TCGA databases with the following accession number: TCGA-BLCA, GSE31684, GSE13507, GSE32548, and GSE32894. Two PD-(L)1 treatment datasets, IMvigor210 [40] and Rose2021UC [41], were also obtained. MSCs and CSCs populations were first extracted from the integrated scRNA-seq dataset and further clustered into subpopulations. We then used the FindAllMarkers function in Seurat to identify positive markers of each subpopulation. By clusterProfiler, enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were performed to facilitate subpopulation annotation [42]. We further performed pseudotime analysis and built the single-cell developmental trajectory by Monocle [43]. Once the branch point has been selected, the BEAM function in Monocle was used to identify genes that differ between branches or change expression status with the developmental trajectory. To decipher the intricate communication networks, we used the NicheNet to identify putative ligands and binding targets [44]. Top ligands and targets in the communication network were regarded as the communication pattern. SCENIC was subsequently used to identify activated regulons within the pattern [45]. Finally, the Stem. Sig was constructed. After removing normal samples, we identified molecular subtypes of TCGA-BLCA based on the Stem. Sig. by ConsensusClusterPlus package [46]. CDF curves and PAC scores were employed to determine the optimal clustering number. To validate the stemness between subtypes, we obtained 26 stemness-related gene sets from a web-based tool: StemChecker (http://stemchecker.sysbiolab.eu/, accessed on 9 January 2023) [47], and calculated the stemness enrichment scores of each TCGA-BLCA via GSVA [48]. Besides, messenger RNA expression-based stemness index (mRNAsi) was procured from the study by Malta et al. and used to explore the differences between clusters [49]. GSEA enrichment analysis with hallmark gene sets downloaded from Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/, accessed on 9 January 2023) was performed to investigate the biological features. Additionally, immune cell infiltration levels were evaluated by CIBERSORT, EPIC, MCP-counter, quanTIseq, TIMER, and xCell, which were implemented in the IOBR R package [50]. We used the Tumor Immune Dysfunction and Exclusion (TIDE) [51] and SubMap analysis [52] to assess the response to immunotherapy. Two anti-PD-(L)1 treated cohorts were analyzed to further evaluate the performance of the Stem. Sig. in predicting immunotherapy response. We first performed a univariate Cox regression analysis to identify prognosis-related genes (p < 0.05) based on the Stem. Sig. Then, an integrated machine-learning framework was developed to establish a consensus prognostic model based on several BCa RNA-seq cohorts, including TCGA-BLCA, GSE31684, GSE13507, GSE32548, and GSE32894. To be specific, the framework was developed from 101 combinations of 10 machine-learning algorithms via 10-fold cross-validation, including survival support vector machine (survival-SVM), random survival forest (RSF), elastic network (Enet), generalized boosted regression modeling (GBM), supervised principal components (SuperPC), partial least squares regression for Cox (plsRcox), CoxBoost, stepwise Cox, Ridge, and Lasso. TCGA-BLCA was utilized for training the model, and other cohorts were used to test the performance. We obtained human bladder cancer cell lines T24 and 5637 from the Cancer Institute of the Chinese Academy of Medical Sciences. The cell line was cultured in Dulbecco’s modified Eagle’s medium (DMEM), supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin (Gibco; Thermo Fisher Scientific, Inc., Shanghai, China). Cell lines were grown at 37 °C in a humidified atmosphere of 95% air and 5% CO2. We purchased pcDNA3.1/SLC2A3 (negative control: pcDNA3.1) and small interfering RNA (siRNA) targeting SLC2A3 (si-SLC2A3; negative control: si-NC) from RiboBio (Guangzhou, China). Following the manufacturer’s guidelines, cells were transfected using Lipofectamine 3000 (Invitrogen, Waltham, MA, USA). The bladder cancer cells were lysed in RIPA lysis buffer. Protein concentration was measured by a BCA assay kit (Beyotime, Shanghai, China). Protein lysates were separated using 10% SDS-PAGE and transferred onto PVDF membranes. The membranes were blocked with 5% skimmed milk for 1 h at room temperature and then incubated with primary antibody overnight at 4 °C. Following this, the membranes were incubated with the secondary antibody at RT for 1 h. Each blot was detected by an ECL kit. Primary antibodies used: anti-SLC2A3, anti-SOX2, anti-YAP1, and anti-GAPDH. All antibodies were purchased from Sigma-Aldrich (St. Louis, MO, USA). Bladder cancer cells were seeded into an ultralow-attachment 6-well plate at a density of 5000 cells per well containing DMEM/F12 medium with bFGF (20 ng/mL), EGF (20 ng/mL), insulin (5 µg/mL) and 2% B27 (Gibco; Thermo Fisher Scientific, Inc.). After being cultured with 5% CO2 at 37 °C for 7 days, tumorspheres were observed under the inverted microscope. R software (v 4.1.1) and GraphPad Prism (v 8.0.2) were used to perform all statistical analyses. The Wilcoxon test was used to analyze the differences between the 2 groups. Chi-squared test was used to examine the differences between categorical variables. Pearson correlation coefficient was used for correlation analysis. Kaplan–Meier curves with the log-rank test were performed for survival analysis. A 2-tailed p-value < 0.05 was regarded as statistically significant. Deciphering crosstalk between MSCs and CSCs identified a Stem. Sig. that predicted prognosis and the response to immunotherapy for BCa. SLC2A3 was exclusively upregulated in ECM-related CSCs and contributed to the stem traits of BCa. Targeting SLC2A3 may facilitate effective cancer management.

PMC10003513

Hui Liu,Songbo Song,Mengyao Liu,Yangwei Mu,Ying Li,Yuxin Xuan,Liangjie Niu,Hui Zhang,Wei Wang

Transcription Factor ZmNAC20 Improves Drought Resistance by Promoting Stomatal Closure and Activating Expression of Stress-Responsive Genes in Maize

01-03-2023

drought resistance,ZmNAC20,transcription factor,stomatal closure,ABA

Drought is a major environmental threat that limits crop growth, development, and productivity worldwide. Improving drought resistance with genetic engineering methods is necessary to tackle global climate change. It is well known that NAC (NAM, ATAF and CUC) transcription factors play a critical role in coping with drought stress in plants. In this study, we identified an NAC transcription factor ZmNAC20, which regulates drought stress response in maize. ZmNAC20 expression was rapidly upregulated by drought and abscisic acid (ABA). Under drought conditions, the ZmNAC20-overexpressing plants had higher relative water content and survival rate than the wild-type maize inbred B104, suggesting that overexpression of ZmNAC20 improved drought resistance in maize. The detached leaves of ZmNAC20-overexpressing plants lost less water than those of wild-type B104 after dehydration. Overexpression of ZmNAC20 promoted stomatal closure in response to ABA. ZmNAC20 was localized in the nucleus and regulated the expression of many genes involved in drought stress response using RNA-Seq analysis. The study indicated that ZmNAC20 improved drought resistance by promoting stomatal closure and activating the expression of stress-responsible genes in maize. Our findings provide a valuable gene and new clues on improving crop drought resistance.

Transcription Factor ZmNAC20 Improves Drought Resistance by Promoting Stomatal Closure and Activating Expression of Stress-Responsive Genes in Maize Drought is a major environmental threat that limits crop growth, development, and productivity worldwide. Improving drought resistance with genetic engineering methods is necessary to tackle global climate change. It is well known that NAC (NAM, ATAF and CUC) transcription factors play a critical role in coping with drought stress in plants. In this study, we identified an NAC transcription factor ZmNAC20, which regulates drought stress response in maize. ZmNAC20 expression was rapidly upregulated by drought and abscisic acid (ABA). Under drought conditions, the ZmNAC20-overexpressing plants had higher relative water content and survival rate than the wild-type maize inbred B104, suggesting that overexpression of ZmNAC20 improved drought resistance in maize. The detached leaves of ZmNAC20-overexpressing plants lost less water than those of wild-type B104 after dehydration. Overexpression of ZmNAC20 promoted stomatal closure in response to ABA. ZmNAC20 was localized in the nucleus and regulated the expression of many genes involved in drought stress response using RNA-Seq analysis. The study indicated that ZmNAC20 improved drought resistance by promoting stomatal closure and activating the expression of stress-responsible genes in maize. Our findings provide a valuable gene and new clues on improving crop drought resistance. Drought limits plant growth and reduces crop production worldwide. With global warming, improving drought resistance is of great importance for crop breeding [1,2]. A variety of strategies have evolved to survive under drought conditions. Plants improve drought resistance mainly by promoting stomatal closure, altering root architecture, adjusting the contents of osmotic substances, and increasing the activities of the antioxidant enzymes [3]. When facing drought stress, plant cells sense the stimuli and activate stress response genes to cope with the stress [4]. It has been demonstrated in numerous studies that transcription factors, such as NAC, WRKY, basic leucine zipper (bZIP), homeodomain-leucine zipper (HD-Zip), drought-response elements binding proteins/C-repeat binding factor (DREB/CBF), and MYB, play crucial roles in enhancing drought resistance in plants [5,6,7]. Many stress-responsive genes are activated by transcription factors [6,7]. NAC transcription factors are one of the largest transcription factor families in the plant, with a highly conserved NAC domain at the N-terminal [8]. The name NAC is derived from three transcription factors: NAM (no apical meristem) in Petunia hybrida, ATAF1/2 (Arabidopsis thaliana activating factor), and CUC2 (cup-shaped cotyledon) in Arabidopsis thaliana [9,10,11]. NAC transcription factors are key targets for crop improvement due to their diverse functions in abiotic stress responses [12]. It is found that NAC transcription factors play an important role in regulating plant response to drought [13,14,15,16,17]. NAC can improve plant drought resistance by activating the expression of stress-responsive genes, promoting stomatal closure, increasing osmotic substance content, and so on [8,18]. In maize, previous studies have identified 116 ZmNACs genes, and the function of most of them remains unknown [19]. To date, not many ZmNACs genes have been characterized as improving drought resistance in maize. Overexpression of ZmNAC111 can significantly improve the drought resistance of maize, and the natural variation of the ZmNAC111 promoter is closely related to drought resistance [13]. ZmNAC33 is upregulated under drought conditions and can be induced by abscisic acid (ABA). Overexpression of ZmNAC33 in Arabidopsis can enhance drought resistance [20]. Natural Antisense Transcripts (NATs) are long-chain noncoding RNAs whose sequences can complement other transcripts. ZmNAC48 contains one cis NAT and two significant SNPs associated with plant survival rate under drought conditions. Overexpression of ZmNAC48 improves plant drought resistance, promotes stomatal closure, reduces plant water loss rate, and increases plant survival rate. However, maize with overexpression of cis NAT of ZmNAC48 shows a higher water loss rate and larger stomatal aperture. Both ZmNAC48 and its cis NAT are involved in drought stress response. ZmNAC48 promotes stomatal closure, while the cis NAT of ZmNAC48 negatively regulates stomatal closure by regulating ZmNAC48 [16]. ZmNAC55 is localized in the nucleus and upregulated under drought stress, salt stress, cold stress, and ABA induction. Overexpression of ZmNAC55 in Arabidopsis significantly improves drought resistance [14]. ZmNAC49 can be rapidly induced and upregulated by drought stress. Overexpression of ZmNAC49 in maize results in the decline of stomatal conductance and stomatal density. Further research shows that ZmNAC49 can directly bind to the ZmMUTE promoter to inhibit its expression, thereby reducing stomatal density. ZmNAC49 enhances drought resistance mainly by affecting stomatal density [17]. Overexpression of the NAC transcription factor gene ZmNST3 (NAC secondary wall thickening promoting factor3) can significantly increase the drought resistance of maize. ChIP-seq analysis shows that ZmNST3 can directly bind to CESA5 and Dynamin-Related Proteins2A (DRP2A) promoters to activate their expression. ZmNST3 could increase the expression level of genes related to cellulose synthesis in the secondary cell wall [15]. The NAC transcription factor gene ZmNUT1 (necrotic upper tips1) is mainly expressed in the xylem of roots, stems, and leaves. The mutation of ZmNUT1 leads to abnormal water transportation. One study finds that ZmNUT1 regulates xylem development by directly regulating the expression of the cellulose synthase gene and cysteine proteolytic enzyme gene, thereby affecting water transportation [21]. The natural variation of the noncoding region in ZmNAC080308 is associated with drought resistance. Overexpression of ZmNAC080308 in Arabidopsis significantly enhances drought resistance [22]. ZmSNAC13 can improve drought resistance by promoting the expression of PYL9 and DREB3 [23]. ZmNAC84 improves drought tolerance by directly regulating the expression of ZmSOD2 [24]. ABA is a key factor that controls drought stress response. Drought stress rapidly induces the synthesis and accumulation of ABA [25]. In the absence of ABA, Serine/threonine protein phosphatase 2C (PP2C) will interact with SnRK2 (SNF1-related protein kinase) and inhibit its activity. When ABA combines with its receptor pyrabactin resistance (PYR)/PYR1-like (PYL)/regulatory components of ABA receptor (RCAR), it can release the inhibition of PP2C on SnRK2. SnRK2 activates transcription factors to control the expression of stress-responsive genes or regulates the activity of the plasma membrane proteins in guard cells to control the cell turgor and stomatal closure [25,26]. In maize, the ABA receptors ZmPYL8, ZmPYL9, and ZmPYL12 facilitate drought resistance in plants [27]. ZmPP2C26 negatively regulates drought resistance by dephosphorylating ZmMAPK3 and ZmMAPK7. The maize zmpp2c26 mutant shows enhancement of drought resistance with higher root length, root weight, chlorophyll content, and photosynthetic rate compared with the wild type. The ZmPP2C26 gene generates ZmPP2C26L and ZmPP2C26S isoforms by alternative splicing. Overexpression of ZmPP2C26L and ZmPP2C26S significantly decreases drought resistance in Arabidopsis and rice [28]. ZmPP2C-A10 functions as a negative regulator of drought resistance. Deletion of an endoplasmic reticulum stress response element (ERSE) in ZmPP2C-A10 increases drought resistance [29]. ABA signaling is critical for plants to cope with drought stress [25,30]. There are many transcription factors involved in ABA signaling to regulate drought resistance in maize. The BRI1-EMS suppressor 1 (BES1)/brassinazole-resistant 1 (BZR1) transcription factor positively regulates drought resistance by binding to E-box to induce the expression of downstream stress-related genes. Heterologous expression of ZmBES1/BZR1-5 in transgenic Arabidopsis thaliana results in decreased ABA sensitivity, facilitates shoot growth and root development, and enhances drought resistance with lower malondialdehyde (MDA) content and relative electrolyte leakage (REL) under osmotic stress [31]. The expression of ZmbZIP33 is strongly upregulated by drought and ABA. Overexpression of ZmbZIP33 causes an accumulation of ABA content and improves drought resistance in Arabidopsis [32]. Lateral organ boundaries domain (LBD) proteins are plant-specific transcription factors. ZmLBD5 negatively regulates drought resistance by impairing ABA synthesis [33]. Stomata are essential structures for plants to control gas exchange and water status. Under drought conditions, plants can reduce water loss by adjusting the size of the stomatal aperture. Stomatal closure is regulated by various signaling molecules, such as ABA, ROS, and Ca2+ [34]. Several critical factors that regulate stomatal closure in response to drought stress have been characterized in maize. ZmCPK35 (Ca2+-dependent protein kinases) and ZmCPK37 (calcium-dependent protein kinases) regulate the drought resistance of maize by regulating the activity of ZmSLAC1 (the S-type anion channel protein) in the guard cells of maize [35]. ZmSLAC1 is specifically expressed in maize guard cells and participates in regulating stomatal closure under drought conditions. zmslac1 mutant exhibits drought-sensitive phenotype. ZmCPK35 and ZmCPK37 are expressed in maize guard cells. ZmCPK35 and ZmCPK37 can interact with ZmSLAC1 on the cytoplasmic membrane and regulate ion channel activity. In the guard cells of zmslac1 and zmcpk37 mutants, S-type anion channel currents activated by ABA are significantly inhibited, while overexpression of ZmCPK35 and ZmCPK37 could significantly enhance ABA-activating S-type anion channel currents in guard cells [35]. The gene knockout mutant of zmmpkl1 (mitogen-activated protein kinase) is less sensitive to severe drought. The stomatal aperture of ZmMPKL1-overexpressing plants is higher than those of control plants, which leads to faster water loss. The stomatal aperture of the zmmpkl1 mutant is smaller than that of the control plant. ZmMPKL1 affects the response of plants to drought by regulating ABA homeostasis in plants [36]. In this study, we identified a NAC transcription factor gene ZmNAC20 in maize. ZmNAC20 was induced and upregulated by drought stress and ABA. ZmNAC20 was localized in the nucleus and enhanced drought resistance in maize. ZmNAC20 promoted stomatal closure in response to ABA. Our results suggest that ZmNAC20 plays an important role in drought stress response and stomatal movement in maize. ZmNAC20 (Zm00001eb288360 in the version of Zm-B73-REFERENCE-NAM-5.0, Zm00001d038221 in version of Zm-B73-REFERENCE-GRAMENE-4.0, GRMZM2G180328 in version of B73 RefGen_v3), which has been named in the previous study [37], encodes a NAC-type transcription factor. ZmNAC20 belongs to a large number of members of the family in maize [37]. A previous study performed phylogenetic analysis using the amino acid sequences and indicated that the closest two identified homologous genes of ZmNAC20 (GRMZM2G180328) were Sb09g020750 in Sorghum bicolor and LOC_Os05g34830 in rice [13]. In the maizeGDB database (www.maizegdb.org, accessed on 7 February 2023), the GO annotations indicated that ZmNAC20 (Zm00001eb288360) was involved in multiple processes, including positive regulation of response to water deprivation, positive regulation of response to salt stress, regulation of defense response to fungus, and response to cold (Figure S1). A previous study indicated that ZmNAC20 was upregulated by treatment with PEG, which could mimic drought stress [37]. We assumed that ZmNAC20 was likely involved in drought stress response. We performed quantitative reverse-transcription PCR (qRT-PCR) to confirm whether ZmNAC20 expression was regulated by drought stress. When the maize seedlings developed three leaves, the aerial parts were cut and subjected to dehydration stress. The results showed that the expression of ZmNAC20 was significantly upregulated after dehydration stress (Figure 1A), indicating that drought stress promoted ZmNAC20 expression. ABA is a critical hormone that regulates drought stress response in plants [25]. The leaves of maize growing for about 12 days were excised and treated with different concentrations of ABA for 1 h. By using qRT-PCR, we found that treatment with ABA elevated the expression level of ZmNAC20 (Figure 1B). We also examined the expression of ZmNAC20 treated with 1 μM ABA for 0 h, 1 h, 2 h, and 3 h. ZmNAC20 was upregulated by ABA at different times (Figure 1C). These results suggested that ZmNAC20 expression was regulated by both drought stress and ABA. To understand whether increased transcript levels of ZmNAC20 enhanced drought resistance, we generated two transgenic maize which overexpressed ZmNAC20 under the constitutive promoter ZmUbiquitin1 (Ubi). The two transgenic maize lines were named ZmNAC20-OE1 and ZmNAC20-OE2. Using qRT-PCR assay, we found that the transcript levels of ZmNAC20 in the two transgenic maize lines were significantly higher than that in the wild type (WT, B104) (Figure 1D). After drought treatment, it was found that the leaves of ZmNAC20-overexpression plants were slightly yellow and curly, whereas the leaves of WT plants were severely wilted or even began to die (Figure 2A). After 3 days of rewatering, the leaves of ZmNAC20-overexpressing plants gradually expanded and turned green, and the survival rate reached about 80%, much higher than the WT plants (Figure 2A,B). Furthermore, both the relative water content, the fresh weight, and the dry weight of ZmNAC20-overexpressing plants were significantly higher than those of WT plants (Figure 2C,D and Figure S2). These results demonstrated that overexpression of ZmNAC20 improved drought resistance in maize. Stomata are key structures to cope with drought in plants [3,38]. Plants regulated water loss mainly through modulation of the opening and closure of stomata [25]. Rapid stomatal closure is an effective way to reduce water loss and improve the drought resistance of plants [3,25]. The detached leaves of ZmNAC20-overexpressing plants showed a slower water loss rate than those of WT plants (Figure 3A). After 180 min of dehydration stress treatment, the leaves of WT had severely curved, whereas the leaves of ZmNAC20-overexpressing plants displayed a slightly curled phenotype (Figure 3B). These results suggest that overexpression of ZmNAC20 could retain more water in leaves and enhance drought resistance in maize. Next, we wondered if ZmNAC20 regulates water loss by modulation of stomatal closure. ABA plays a pivotal role in stomatal closure in response to drought stress, and ZmNAC20 was upregulated by ABA (Figure 1B,C). We performed the experiment to test whether ZmNAC20 affected the stomatal closure in response to ABA. The stomatal aperture was determined by the ratio of stomatal width to length. It was shown that overexpression of ZmNAC20 reduced the size of the stomatal aperture under 1 μM and 10 μM ABA treatment (Figure 3C,D). The stomata in ZmNAC20-overexpressing plants closed more rapidly than those of WT plants after ABA treatment. Stomatal closure in ZmNAC20-overexpressing plants was more sensitive to ABA compared with that of WT plants. These results indicated that ZmNAC20 promoted stomatal closure and impaired water loss, resulting in enhanced drought resistance in maize. Because ZmNAC20 was a NAC transcription factor, we assumed that ZmNAC20 might localize in the nucleus. To test the hypothesis, p35S:ZmNAC20-GFP and the nucleus localized construct 35S:H2B-mCherry were together transformed into leaves of Nicotiana benthamiana by agrobacterium-mediated infiltration. The ZmNAC20-GFP signal was colocalized with the H2B-mCherry signal; a strong yellow fluorescence signal was only detected in the nucleus, whereas the signals of the control construct 35S:GFP were detected throughout the cell (Figure 4). These results indicated that ZmNAC20 was localized in the nucleus. To uncover the molecular pathways regulated by ZmNAC20 under drought stress, we performed RNA-seq analysis using the detached leaves of ZmNAC20-OE1 and WT treated with dehydration stress for 3 h. Three biological repeats of the WT (WT-A, WT-B, WT-C) and ZmNAC20-OE1 (OE1-A, OE1-B, OE1-C) were used for RNA-seq analyses. Twofold gene transcript levels with the adjusted p-value (q value) cutoff of 0.05 between ZmNAC20-OE1 and WT was used as the criterion for differential expression. Compared with WT, 1361 genes were upregulated and 913 genes were downregulated in ZmNAC20-OE1 (Figure 5A, Tables S1 and S2). To reveal ZmNAC20-mediated pathways, we performed Gene Ontology (GO) enrichment analysis and KEGG pathway enrichment analysis. GO analysis showed that the 1361 upregulated genes were mainly involved in multiple biological processes, including responses to abiotic stimulus, photosynthesis, hormone, cold, water deprivation, salt stress, and osmotic stress (Figure 5B). The 913 downregulated genes were mainly involved in the processes of RNA modification, ribosome biogenesis, ribosome assembly, rRNA processing, protein import into the nucleus, and translation (Figure S3). KEGG enrichment analysis indicated that the upregulated genes participated in the pathways of photosynthesis, biosynthesis of secondary metabolites, carbon fixation in photosynthetic organisms, benzoxazinoid biosynthesis, carotenoid biosynthesis, carbon metabolism, and flavonoid biosynthesis (Figure 5C). The downregulated genes were involved in the pathways of ribosome biogenesis in eukaryotes monoterpenoid biosynthesis, tryptophan metabolism, and linoleic acid metabolism (Figure S4). These results suggested that ZmNAC20 regulated multiple biological pathways under drought stress in maize. RNA-seq analysis revealed that overexpression of ZmNAC20 affected the expression of many genes. We selected 9 upregulated genes involved in drought stress response for detailed analysis. The gene symbol name used in this study referred to the maizeGDB database (www.maizegdb.org, accessed on 7 February 2023). It is well known that the transcription factors, such as APETALA2/Ethylene Responsive Element Binding Protein (AP2/EREBP), WRKY, and bZIP, play key roles in drought stress response [7,39,40,41]. Zm00001eb168040 (ZmEREB106), Zm00001eb276700 (ZmEREB145), and Zm00001eb021440 (ZmEREB188) are putative AP2/EREBP transcription factor genes. Zm00001eb344160 (ZmWRKY106) is a transcription factor that includes a WRKY DNA-binding domain. Zm00001eb366900 (ZmbZIP75) is a putative bZIP transcription factor. Overexpression of ZmNAC20 promoted the expression of the four genes by qRT-PCR (Figure 6). After treatment with ABA, ZmEREB106, ZmEREB145, ZmEREB188, and ZmbZIP75 were upregulated by ABA, whereas ZmWRKY106 was downregulated by ABA (Figure 7). Dehydrin is a well-known protein which accumulates massively under drought stress and helps plants improve resistance to stresses [42]. Previous studies have demonstrated many dehydrins involved in drought resistance improvement [43]. For example, Medicago truncatula MtCAS31 (cold acclimation-specific 31) encodes a dehydrin which acts as a positive regulator of drought response [43,44]. In the ZmNAC20-overexpressing lines, Zm00001eb376710 (ZmDHN2), encoding a dehydrin protein showed increased transcript level compared with the wild-type B104, suggesting that ZmNAC20 promoted ZmDHN2 expression (Figure 6). Moreover, we found that ZmDHN2 was upregulated by ABA (Figure 7). Zm00001eb283860 (ZmGA2OX6) encodes a gibberellin 2-beta-dioxygenase that may deactivate gibberellin (GA). A previous study showed that low GA activity promoted stomatal closure and enhanced drought resistance [45]. Overexpression of ZmNAC20 increased the transcript level of ZmGA2OX6, suggesting that ZmNAC20 might regulate drought resistance through modulation of GA signaling via ZmGA2OX6 (Figure 6). In addition, ZmGA2OX6 was also upregulated by ABA, indicating that ABA participated in the expression of ZmGA2OX6 (Figure 7). Zm00001eb130550 (ZmSWEET17A) encodes a sugar transporter. SUGAR WILL EVENTUALLY BE EXPORTED TRANSPORTER (SWEET) proteins promote the transport of different sugars over cellular membranes and control both inter and intracellular distribution of sugars [46]. In Arabidopsis thaliana, knockout of SWEET17 resulted in impaired drought resistance [46], and mutation of SWEET11 and SWEET12 also exhibited reduced drought resistance [47]. ZmSWEET17A was regulated by ZmNAC20 and ABA (Figure 6D and Figure 7D), suggesting that ZmNAC20 might regulate drought resistance by modulating the ZmSWEET17A-mediated sugar transporter. Zm00001eb076200 (ZmPx15) encodes a peroxidase. The water-deficit condition caused the excessive production and accumulation of reactive oxygen species (ROS), which damaged the plant cells. Peroxidase acted as an antioxidant to scavenge ROS [48]. Overexpression of ZmNAC20 enhanced the transcript level of ZmPx15, implying that ZmNAC20 might improve drought resistance by modulation of ZmPx15 (Figure 6). ABA also promoted the expression of ZmPx15, suggesting that ABA regulated the expression of ZmPx15 (Figure 7). These results suggested that ZmNAC20 regulated expressions of various genes involved in drought stress response. ZmNAC20 improved drought resistance by modulation of multiple genes, which constituted a complex network. Drought is among the major environmental factors that affect plant growth and crop yield [3]. To obtain stress resistance, many transcription factor genes are activated under drought conditions. The transcription factors receive the upstream drought stress signal and activate expressions of many stress-responsive genes [49]. These molecular responses help plants rapidly adapt to the water-deficit stress environment [25]. The transcription factors-mediated networks are critical and necessary for plants to survive under drought conditions [5]. It has been demonstrated that NAC transcription factors play crucial roles in drought stress response [8,13,14,17,20]. In this study, we reported a NAC transcription factor gene ZmNAC20, which was upregulated by drought stress (Figure 1A,B). Overexpression of ZmNAC20 resulted in an increased survival rate and a higher level of relative water content (Figure 2B,C), suggesting that ZmNAC20 functioned as a positive factor in improving drought resistance. Previous studies have reported that several maize ZmNACs genes, including ZmNAC111 [13], ZmNAC33 [20], ZmNAC55 [14], ZmNAC49 [17], ZmNST3 [15], ZmNUT1 [21], ZmNAC080308 [22], ZmSNAC13 [23], ZmNAC84 [24], and ZmNAC48 [16], contributed to improving drought resistance. In maize, a large number of ZmNACs genes have been identified, but the function of most of them has remained elusive until now. Considering the important function of NACs in drought stress response, more efforts on revealing the function of ZmNACs genes in maize should be made in future studies. Stomata are important structures to control water loss and gas exchange [38,50]. Under drought conditions, stomatal closure is regulated by multiple signals, such as ABA, ROS, Ca2+, and H2S, [34,38,51]. Among these signals, ABA is the center molecule to control stomatal closure in response to drought stress [25,26]. ZmNAC20 was upregulated by drought stress and ABA (Figure 1A,B). Overexpression of ZmNAC20 accelerated the closure of stomata in response to ABA. The ZmNAC20-overexpressing transgenic maize showed a smaller stomatal aperture and lost less water than the wild-type B104 (Figure 3A,C). These results suggested that ZmNAC20 contributed to promoting ABA-mediated stomatal closure in response to drought stress. ZmNAC20 partially improved drought resistance by promoting stomatal closure. In maize, ZmNAC48 contributes to improving drought resistance by promoting stomatal closure, whereas ZmNAC49 enhances drought resistance by the decline of stomatal conductance and stomatal density [16,17]. ZmNST3 increases drought resistance by activating the expression of genes related to cellulose synthesis in the secondary cell wall [15]. ZmNUT1 improves drought resistance by affecting water transportation via regulating the expression of the cellulose synthase gene and cysteine proteolytic enzyme gene [21]. These findings indicated that ZmNACs transcription factors improved drought resistance by modulation of various pathways, suggesting that the function of NACs has diversity and complexity. Using RNA-seq analysis, we obtained a list of genes regulated by ZmNAC20 (Tables S1 and S2). GO enrichment analyses indicated that ZmNAC20 regulated multiple pathways that are mainly involved in abiotic stimulus, response to water deprivation, and response to hormones (Figure 5B). RNA-seq analysis indicated that ZmNAC20 regulated the expression of various stress-responsive genes, such as the transcription factor genes ZmEREB106, ZmEREB145, ZmEREB188, ZmWRKY106, and ZmbZIP75, the dehydrin gene ZmDHN2, the GA dioxygenase gene ZmGA2OX6, the sugar transporter gene ZmSWEET17A, and antioxidant enzyme gene ZmPx15 (Figure 6 and Figure 7). These results suggested that ZmNAC20 improved drought resistance by modulation of multiple pathways. ZmNAC20 formed a network to cope with drought stress. The molecular response induced by ZmNAC20 promoted plants to adapt to the water-deficit environment. There are many limitations when using transcription factors to improve drought resistance in crops. We should consider the fact that many transcription factors inhibit plant growth and development, while improving drought resistance. Stomatal closure prevents water loss and enhances drought resistance but also limits CO2 intake and photosynthesis [3]. For example, overexpression of ZmNAC49 enhances drought resistance in maize, but also significantly decreases stomatal conductance and stomatal density. ZmNAC49 overexpression affects the expression of genes related to stomatal development [17]. Overexpression of ZmNAC48 improves drought resistance by enhancing stomatal closure [16]. Less studies focus on revealing the mechanism of plants maintaining growth under drought conditions. It is necessary to identify the genes that increase drought resistance but do not limit plant growth and development. Previously, a study reported that overexpression of a wheat ABA receptor gene TaPYL4 improves drought resistance by reducing stomatal conductance but does not affect wheat growth and development. This is because overexpression of TaPYL4 increases water use efficiency and enhances photosynthesis [52]. Future studies should pay more attention to those transcription factors that can improve drought resistance without penalizing plant growth. In this study, we did not detect whether ZmNAC20 affected water use efficiency and photosynthesis. Further research will be focused on revealing the function of ZmNAC20 to maintain growth under drought conditions. Taken together, our work revealed the function of ZmNAC20 in drought stress response in maize. The study provides valuable insights into the role of ZmNAC20 in promoting drought resistance and shed light on the molecular mechanisms underlying plant adaptation to water-deficit stress. The overexpression transgenic plants in this study were derived from the maize (Zea mays L.) inbred line B104, which is a public, transformable maize inbred line and has been widely used in recent studies [15,53,54,55]. To analyze the function of ZmNAC20 in drought stress response, the coding sequence of ZmNAC20 was cloned and inserted into a modified pCambia3300 vector. ZmUbiquitin1 (ZmUbi) was used as the promoter to drive ZmNAC20 expression. The ZmNAC20-OE construct was transformed into the maize inbred B104. Seeds of the maize inbred line B104 and ZmNAC20-overexpressing transgenic lines (ZmNAC20-OE1 and ZmNAC20-OE2) with the same size were selected, and immersed in 75% ethanol solution for disinfection for 1 min. After disinfection, the maize seeds were washed with distilled water 5–6 times. Then, the seeds were immersed in the distilled water and cultivated in the dark at 26 °C for 24 h. The soaked seeds with embryo sides faced upward were placed evenly in the seedling tray with filter paper, adding a proper amount of distilled water (the seeds just touched the water surface). After that, the seedling tray was sealed with plastic wrap, and placed in darkness at 28 °C for 3 days. The germinated seeds were transplanted into the mixed nutrient soil (vermiculite: nutrient soil = 1:1) and cultivated in the 28 °C plant light incubator under a photoperiod of 16 h/8 h (day/night), 60% relative humidity, and 16,800 Lux light intensity. After three true leaves grew from the maize seedlings, the seedlings were subjected to the follow-up experiment. When maize seedlings of B104, ZmNAC20-OE1, and ZmNAC20-OE2 developed three true leaves, water was withheld for drought stress treatment. After about 15 days of drought treatment, watering was resumed to allow the plants to recover. The survival rate was recorded after three days of rewatering. Seedlings with green leaves and hard stems were recorded as survivors. In each test, at least 20 plants for each line were involved. Phenotype and data analysis was based on three independent experiments. After about 7 days of drought treatment, the middle segments of fresh leaves were cut about 5 cm long. The weight of the middle segments of fresh leaves was measured immediately and recorded as the fresh weight. Then the above leaves were immersed in distilled water at room temperature for 12 h. After that, the saturated fresh weight was recorded. At last, the leaves were placed in a 70 °C oven for 12 h, and the dry weight was measured. We used the formula [relative water content= (fresh weight − dry weight)/(saturated fresh weight − dry weight) × 100%] to calculate the relative water content of leaves. Statistical analysis was based on three independent experiments. The above-ground parts of B104 and ZmNAC20-OE1 maize seedlings with three true leaves were cut and spread in the plant light incubator, with a temperature of 28 °C, relative humidity of 30%, and light intensity of 16,800 Lux. The dry weight (DW) of detached leaves was measured at 15 min, 45 min, 60 min, 100 min, 120 min, 160 min, 180 min, 200 min, 300 min, and 400 min after dehydration stress treatment. The weight of detached leaves was measured as fresh weight (FW) at 0 min of dehydration stress treatment. We used the formula [relative water loss rate = (FW − DW)/FW × 100%] to calculate the relative water loss rate. Statistical analysis was based on three independent experiments. After drought stress treatment for about 7 days, the aerial parts of maize seedlings were cut off and immediately weighed. The weight was recorded as fresh weight. The aerial parts of maize seedlings were then put into a 70 °C oven for continuous drying for 24 hours. After that, the weight of the above materials was measured as the dry weight. Biomass (g) = dry weight or fresh weight. There were three biological replicates in total, with every replicate containing four maize seedlings. The aerial parts of B104 and ZmNAC20-OE1 maize seedlings with three true leaves were cut off and immersed in the stomatal opening buffer (10 mM KCl, 50 mM CaCl2, and 10 mM MES/Tris, pH 5.6), and then incubated in dark for 2 hours and in light for 3 hours. After incubation in the stomatal opening buffer, the leaves were taken out and immediately put into the 0, 1, and 10 μM ABA solution (taking stomatal opening buffer as a solution and ABA as solute) prepared in advance respectively. At 1 h of ABA treatment, transparent nail polish was coated on the upper epidermis of maize leaves. When nail polish was completely dried, the upper epidermis was torn off with tweezers and made into a temporary slide. Ten stomata were randomly selected in the view of the microscope, and the length and width were measured with Image. Three biological replicated assays were performed. To determine the subcellular localization of ZmNAC20, the coding sequence without the stop code of ZmNAC20 was cloned and inserted into a 35S:GFP vector, obtaining 35S:NAC20-GFP. 35S:H2B-mCherry is a nuclear localization marker. The constructs of 35S:ZmNAC20-GFP and 35S:H2B-mCherry were transformed into the Agrobacterium tumefaciens strain GV3101, then used for transient expression in leaves of tobacco (Nicotiana benthamiana). The constructs 35S:GFP and 35S:H2B-mCherry were used to act as the control. The A. tumefaciens GV3101 harboring 35S:ZmNAC20-GFP and 35S:H2B-mCherry or 35S:GFP and 35S:H2B-mCherry, were cultured overnight at 28 °C and centrifuged for 10 min at 5000 rpm. The cultures were resuspended using the buffer solution with 10 mM MES (pH 5.5), and 10 mM MgCl2·6H2O. The cultures were then infiltrated into the leaves of about one-month tobacco seedlings. After being cultured for 3 days, the infiltrated leaves were imaged using a Nikon A1 HD25 confocal microscope. The merged signals of GFP and RFP showed a yellow color. Total RNA from leaves was extracted using RNA-Solv® Reagent of Omega Bio-tek (No. R6830). The RNA was reverse-transcribed to synthesize cDNA by TIANGEN’s FastKing RT Kit (With gDNase) (No. KR116). The resultant cDNA was used as a template for the detection of relative gene expression, with the mazie ZmUbiquitin gene as the reference gene. qRT-PCR was performed with Hieff®qPCR SYBR®Green Master Mix of YEASEN (11201ES08). Each gene had three technical repeats and three biological repeats. Sequences of qRT-PCR primers were given in Table S3. Three biological repeats of the wild type (WT-R1, WT-R2, and WT-R3) and the ZmNAC20-overexpressing transgenic plants ZmNAC20-OE1 (OE-R1, OE-R2, and OE-R3) were used for RNA sequencing (RNA-seq). Total RNAs were isolated from the detached leaves which were treated with dehydration for 3 h using TRI reagent (Sigma; catalog no. T9424, Sigma-Aldrich, Burlington, MA, USA). RNA was sequenced using Illumina 2500 instrument in Berry Genomics, Beijing, China. The clean reads were aligned to the genome sequences of maize (Zm-B73-REFERENCE-NAM-5.0) that was downloaded from the website (plants.ensembl.org); HISAT2 software (version 2.0.5) was used for the clean reads [56]. The gene expression levels were measured using StringTie software (version 1.3.6) [56]. Differential gene expression (DEG) analysis was conducted using DESeq2 software (version 1.34.0) [57]. DEG was screened by using the cutoff of the log2 |fold change| ≥ 1 and q-value (adjusted p-value) ≤ 0.05 between the ZmNAC20-OE1 and the wild-type B104. The analysis of Gene Ontology (GO) enrichment was performed using AgriGO v2.0, a web-based tool, and a database for GO analyses [58]. The pathway KEGG enrichment for the DEG was performed using the OmicShare tools, a free online platform for data analysis (www.omicshare.com/tools, accessed on 7 February 2023). The RNA-seq data have been deposited into the sequence read archive (SRA) database of NCBI under accession number PRJNA893876. In this study, we found a nucleus-localized NAC transcription factor ZmNAC20 that improved drought resistance in maize. ZmNAC20 was rapidly induced by drought and ABA. Overexpression of ZmNAC20 promoted stomatal closure and prevented water loss. ZmNAC20 regulated multiple pathways by modulation of many stress-responsive genes expression. Our results indicated that ZmNAC20 functioned as a positive regulator to improve drought resistance in maize. ZmNAC20 contributed to improving drought resistance by modulation of stomatal closure and activation expression of stress-responsive genes.

PMC10003517

Muhammad Ammar Zahid,Shahenda Salaheldin Abdelsalam,Hicham Raïq,Aijaz Parray,Hesham Mohamed Korashy,Asad Zeidan,Mohamed A. Elrayess,Abdelali Agouni

Sestrin2 as a Protective Shield against Cardiovascular Disease

02-03-2023

Sestrin2,cardiovascular disease,cellular stress,cardioprotective,oxidative stress,antioxidant

A timely and adequate response to stress is inherently present in each cell and is important for maintaining the proper functioning of the cell in changing intracellular and extracellular environments. Disruptions in the functioning or coordination of defense mechanisms against cellular stress can reduce the tolerance of cells to stress and lead to the development of various pathologies. Aging also reduces the effectiveness of these defense mechanisms and results in the accumulation of cellular lesions leading to senescence or death of the cells. Endothelial cells and cardiomyocytes are particularly exposed to changing environments. Pathologies related to metabolism and dynamics of caloric intake, hemodynamics, and oxygenation, such as diabetes, hypertension, and atherosclerosis, can overwhelm endothelial cells and cardiomyocytes with cellular stress to produce cardiovascular disease. The ability to cope with stress depends on the expression of endogenous stress-inducible molecules. Sestrin2 (SESN2) is an evolutionary conserved stress-inducible cytoprotective protein whose expression is increased in response to and defend against different types of cellular stress. SESN2 fights back the stress by increasing the supply of antioxidants, temporarily holding the stressful anabolic reactions, and increasing autophagy while maintaining the growth factor and insulin signaling. If the stress and the damage are beyond repair, SESN2 can serve as a safety valve to signal apoptosis. The expression of SESN2 decreases with age and its levels are associated with cardiovascular disease and many age-related pathologies. Maintaining sufficient levels or activity of SESN2 can in principle prevent the cardiovascular system from aging and disease.

Sestrin2 as a Protective Shield against Cardiovascular Disease A timely and adequate response to stress is inherently present in each cell and is important for maintaining the proper functioning of the cell in changing intracellular and extracellular environments. Disruptions in the functioning or coordination of defense mechanisms against cellular stress can reduce the tolerance of cells to stress and lead to the development of various pathologies. Aging also reduces the effectiveness of these defense mechanisms and results in the accumulation of cellular lesions leading to senescence or death of the cells. Endothelial cells and cardiomyocytes are particularly exposed to changing environments. Pathologies related to metabolism and dynamics of caloric intake, hemodynamics, and oxygenation, such as diabetes, hypertension, and atherosclerosis, can overwhelm endothelial cells and cardiomyocytes with cellular stress to produce cardiovascular disease. The ability to cope with stress depends on the expression of endogenous stress-inducible molecules. Sestrin2 (SESN2) is an evolutionary conserved stress-inducible cytoprotective protein whose expression is increased in response to and defend against different types of cellular stress. SESN2 fights back the stress by increasing the supply of antioxidants, temporarily holding the stressful anabolic reactions, and increasing autophagy while maintaining the growth factor and insulin signaling. If the stress and the damage are beyond repair, SESN2 can serve as a safety valve to signal apoptosis. The expression of SESN2 decreases with age and its levels are associated with cardiovascular disease and many age-related pathologies. Maintaining sufficient levels or activity of SESN2 can in principle prevent the cardiovascular system from aging and disease. An adequate and timely response to stress is a necessity for all cells to remain viable and functioning. Cellular mechanisms that are activated in response to stress depend on the type of stress, although common effects are often observed. For example, DNA damage, ischemia/hypoxia, and endoplasmic reticulum (ER) stress all lead to increased oxidative stress with the accumulation of reactive oxygen species (ROS). Mitochondrial dysfunction due to structural lesions plays an important role in the accumulation of ROS as electrons from the oxidative phosphorylation chain leak into the cytoplasm and generate highly reactive free radicals which, in turn, can react with other macromolecules and cellular structures. The conservation of energy at this stage is of prime importance to keep driving the essential cellular machinery. A shift in the metabolism from adenosine triphosphate (ATP) consuming anabolic reactions to ATP-producing catabolic reactions takes place. The shift of metabolism from anabolism to energy-producing catabolism serves two purposes; the production of energy to keep diving the cellular machinery in the stressed state and the degradation of macromolecules and organelles that are damaged. When the stress is beyond control, programmed cell death or apoptosis is another consequence that removes the severely damaged cells without collateral damage to the surrounding tissues. If necrosis occurs instead of apoptosis, an inflammatory response could initiate contributing, thus, to further tissue damage. Death and removal of damaged cells also prevent the malignant transformation of these cells. The immune system also plays an important role in programmed cell death. The disruption in functioning and coordination of the stress response has pathological consequences, such as cardiovascular disease (CVD), cancer, diabetes, and neurodegenerative diseases. Aging comes with a natural decline of cellular stress responses which contributes to the accumulation of cellular lesions, pathologies, and death. Understanding the molecular pathways involved in the stress response and the role of different proteins can lead to new drug targets to augment the stress response, slow down the onset of age-related pathologies, or enhance the degradation of damaged cells to prevent cancerous transformation. Many proteins which play a role in stress are multi-functional and Sestrin2 (SESN2) has recently attracted interest as one of those important proteins. Genomic instability, disruptions in protein balance, changes in how cells respond to nutrients, mitochondrial dysfunction, cellular senescence, depletion of stem cells, and altered communication between cells are all hallmarks of aging and contributes to aging in one way or another [1]. Activation of AMP-activated protein kinase (AMPK), inhibition of the mammalian target of rapamycin complex 1 (mTORC1) activation, and activation of the autophagic signaling have been shown to increase the life and health span of model organisms [2,3,4,5]. SESN2 has been shown to activate AMPK, inhibit mTORC1, activate autophagy, and regulate energy and metabolic homeostasis [6,7,8]. Thus it seems plausible that SESN2 also contributes to suppression of age-associated diseases. In fact, increased levels of DrosophilaSestrin (dSesn) were observed in chronic TOR activation due to accumulation of ROS [9]. Loss of dSesn resulted in age-related pathologies, such as muscle degeneration, cardiac malfunction, triglyceride accumulation, and mitochondrial dysfunction, which were prevented by activating AMPK or inhibiting TOR. dSesn acted as a negative feedback regulator of TOR, integrating metabolic and stress inputs to prevent pathologies caused by chronic TOR activation [9]. Sestrins also protect the cells from physiological day-to-day stress resulted from metabolic activities, such as oxidative respiration and DNA replication, as dSesn mutants showed an accelerated aging phenotype even in the absence of any environmental stress. The deregulation in the metabolic homeostasis as evident by the increased lipids and sugar levels in the blood were also observed in dSesn null Drosophila and SESN2-knockout mice [9,10]. SESN2 levels in aging cardiac muscles have been shown to decrease with age and contribute to the decreased stress tolerance [11,12,13]. Taken together, reduced cardiac stress tolerance and metabolic deregulation contribute greatly to the development of CVD. CVD is a leading cause of death worldwide [14]. Stress on endothelial cells and cardiomyocytes, which make up the bulk of the cardiac tissue and vessels, due to changing metabolism, hemodynamics, or oxygenation status is at the core of these diseases [15,16,17]. The ability to cope with stress depends on the expression of endogenous stress-inducible molecules. One of such stress-inducible protein-coding genes, SESN2, initially known as hypoxia-induced genes 95 (HI95), was discovered in an attempt to identify genes that control the viability and fate of cells during prolonged hypoxia [18]. SESN2 belongs to the family of highly conserved proteins inducible by many different types of stress conditions, including oxidative stress, genotoxic stress, ER stress, hypoxia, and energetic and metabolic stress. Once induced, SESN2 fights back through an intrinsic antioxidant enzymatic activity [19], the activation of AMPK [6], the inhibition of mTORC1 [20,21], the activation of nuclear factor erythroid 2-related factor 2 (NRF2) [22], the activation of AKT [23] and autophagy [24]. Genetic deletion of SESN2 has been shown to worsen age-related pathologies and cardiac function in a variety of model organisms [9,10,25,26]. In cardiomyocytes, SESN2 deletion worsens oxidative and ER stress and contributes to cardiac dysfunction [25,26]. SESN2 also prevents intolerance to ischemia/reperfusion injury which occurs in aging [11]. A decline in SESN2 levels with age is well known but a recent association study of SESN2 polymorphism with the risk of congenital heart defects has shown a genetic predisposition to reduced levels of SESN2 which contributes to low cardiomyocyte viability under hypoxic stress [27]. Further research is needed in this regard to ascertain how genetic or epigenetic changes can alter endogenous SESN2 levels and if the increase in endogenous SESN2 levels or activity can be a therapeutic option to prevent the cardiovascular system from stressful conditions. In this article, we have reviewed the upstream regulators of SESN2 in response to different types of cellular stress and the downstream pathways affected by SESN2. The current evidence of the protective role of SESN2 in CVD and the possibility of SESN2 as a drug target is also presented. The family of Sestrins consists of three homologous members: SESN1, SESN2, and SESN3. All three Sestrins are encoded by genes located on different chromosomes. The SESN1 gene located on chromosome 6q21 also referred to as PA26, is a transcriptional target for the tumor suppressor P53 and is induced in response to genotoxic stress, such as UV radiations [28]. The SESN2 gene located on chromosome 1p35.3 was discovered in an attempt to identify genes induced by prolonged hypoxia and is also referred to as HI95 [18]. Database mining and bioinformatic analysis revealed another PA26-related gene which was named after Sestrins as SESN3 and is present at locus 11p21 [29]. The SESN2 gene encodes for a single monomeric protein of 480 amino acids and a mass of 55 kDa. SESN2 is a globular protein comprising only -helices and no -sheets (Figure 1). The X-ray crystallographic structures (PDB ID: 5DJ4) contains an N-terminal domain (NTD) comprising of residues 66–220, a C-terminal domain (CTD) comprising of residues 339–480, connected by a hinge-like linker domain (LD) comprising of residues 221–338 [30]. NTD, LD, and CTD correspond well to SESN-A, SESN-B, and SESN-C identified previously by the primary sequence and phylogenetic analysis. NTD and STD have a low primary sequence similarity but superimpose well on one another and resemble AphD monomer. The leucine binding pocket is present in the CTD at the intersection of three helices and an LD helix packs against the pocket. Amino acid residues GLU451 in the CTD and LEU261 in the LD are critical for the binding of leucine to SESN2 [30]. The amino acid residues important for the interaction of GATOR2 with SESN2 are SER190 in the NTD and ASP406 and ASP407 in the CTD [31]. The proximity of ASP406 and ASP407 to the leucine binding pocket can explain the changes in the interaction of SESN2 with GATOR2 in the presence of leucine. A detailed representation of the structural details for the interaction of SESN2 with other proteins, such as AMPK and LKB1, in coordinating the stress response and effect of leucine binding on these interactions is still elusive. This structural information will help to discover and design small molecules capable of stabilizing these interactions to augment the activity of SESN2. SESN2 is a stress-inducible protein and is expressed in response to different types of stresses. In return, the increase in expression of SESN2 tends to normalize the stress and fight for the survival of the cell, directly by using its antioxidant enzymatic activity and indirectly by regulating several signaling pathways. In this section, the regulation of SESN2 expression by different stresses is reviewed. It is worth mentioning that although for the sake of understanding, regulation of SESN2 expression in response to the different types of stress has been discussed separately, this regulation is interlinked, not so simple, and straightforward as one type of stress may progress into another type very often and rapidly. For example, an initial episode of hypoxia can progress into energetic stress. Oxidative stress can alter nucleic acids and proteins leading to genotoxic and ER stress. Thus, these regulatory mechanisms work in close coordination with one another and not simply in isolation. Loss of blood supply to a tissue leads to the decreased partial pressure of oxygen in cells and can lead to pathological tissue damage if not corrected. It is well-known that hypoxia triggers a defense mechanism by signaling through the hypoxia-inducible factor 1-alpha (HIF-1) [32]. HIFs are transcription factors that are constantly degraded in normoxia but are stabilized by hypoxia and increase the expression of different stress-related genes including SESN2 [33]. SESN2 was originally identified as a protein that is inducible by hypoxia independent of the involvement of p53 [18]. Budanov et al. used deferoxamine to model prolonged hypoxia in cells, which is a stabilizer for HIF-1. Many other studies have shown that SESN2 induction in response to hypoxia is HIF-1-dependent [34,35]. A schematic representation of the induction of SESN2 by HIF-1 stabilization in hypoxic conditions is shown in Figure 2. P53 is one of the important molecules which decide the fate of the cell in response to damage in the DNA [36]. In resting cells without genotoxic stress, p53 levels remain low due to continuous ubiquitination and proteasomal degradation by mouse double minute 2 homolog (MDM2) ubiquitin ligase [37]. The activation of p53 in response to DNA damage is a complex process and involves stabilization and activation by post-translational modifications of p53 and MDM2 [38]. Once stabilized and activated, p53 moves to the nucleus and causes the transactivation of genes involved in the arrest of the cell cycle, apoptosis, and senescence including SESN2 (Figure 3). The arrest of the cell cycle gives enough time for the DNA damage to repair and to prevent the damage to propagate in the progeny cells. However, if the damage is beyond repair, p53 can signal apoptosis of the cell. In the initial experiments by Budanov et al., SESN2 was identified as a p53-target gene and it was shown that the induction of SESN2 in response to DNA-damaging treatments, such as gamma and UV radiations or doxorubicin, is dependent on a functional p53. Cell lines containing a mutated form of p53 do not show an increase in SESN2 expression in response to these stresses. Further experiments by the same group confirmed that p53 is what connects genotoxic stress to increased expression of SESN2 and mTORC1 inhibition because the silencing of SESN2 attenuates the inhibitory effect of p53 over mTORC1 [20]. Since then, many groups have provided additional evidence of the regulation of SESN2 expression by p53 in response to different types of stresses causing actual or potential damage to DNA [24,39]. The endoplasmic reticulum (ER) is an important place for the post-translational modifications and proper folding of the transmembrane and secretory proteins, lipid biosynthesis, and calcium homeostasis. The folding capacity of the ER is closely monitored by three transmembrane proteins in the ER membrane inositol-requiring enzyme (IRE)-1, protein kinase RNA-like endoplasmic reticulum kinase (PERK), and activating transcription factor 6 (ATF-6). When the ER is overwhelmed with unfolded or misfolded proteins due to physiological or pathological changes, these proteins signal unfolded protein response (UPR) (Figure 4). The UPR on one hand temporarily holds the translation of proteins to decrease the load on the already stressed ER, and on the other hand, it tries to increase the capacity of folding by signaling increased expression of components of the ER folding machinery, including chaperones. The UPR also increases the expression of stress-fighting molecules to maintain cellular homeostasis. If the stress response in the ER is beyond control, the UPR also serves as a safety valve to initiate apoptosis of the cell. As SESN2 is one of the stress-inducible proteins, there is a growing interest in studying the regulation of SESN2 by the UPR. Jegal et al. showed that the ER stress, induced by tunicamycin, can increase the mRNA and protein expression, as well as SESN2 promoter-driven luciferase activity in a hepatocyte cell line HepG2. Among the canonical transcription factors of the UPR, ATF-6 was the most potent in the transcriptional activation of SESN2. The ectopic expression of ATF-6 increased the reporter gene activity while knockdown or silencing of ATF-6α blunted the SESN2 induction in response to tunicamycin. The induction of SESN2 protected the HepG2 cells from ER stress [40]. Although chemical inhibition of IRE-1 or PERK did not show any effect on SESN2 induction in this study, other studies also reported a role for these two ER effectors in the induction of SESN2 [41,42,43]. Park et al. previously showed that the chronic ER stress on the HepG2 cells in vitro and on mouse livers in vivo can increase the expression of SESN2 by CCAAT/enhancer-binding protein beta (CEBPB), a transcription factor downstream of PERK. The increased expression of SESN2 reduces ER stress and prevents mice from steatohepatitis and liver damage due to high-fat diet-induced (HFD) obesity. The other transcription factors downstream of PERK are ATF-4 and C/EBP homologous protein (CHOP). The expression of SESN2 was found to be associated with the expression of ATF-4 and CHOP in cancer cells undergoing treatment with Nelfinavir, an ER stress-inducing chemotherapeutic agent [42]. The ectopic expression of ATF-4 upregulated SESN2, indicating that ATF-4 is an upstream regulator of SESN2. Triple-negative breast cancer cells with ATF-4 depletion also exhibited an attenuated SESN2 induction in response to peptidyl arginine deiminases inhibitors [43]. Saveljeva et al. also reported that the expression of SESN2 in response to ER stress is independent of p53 and depends on PERK and IRE-1/XBP-1 arms of the UPR. While the pharmacological inhibition of PERK or IRE-1, in combination or alone, reduced the expression of SESN2, the knockdown of ATF-6 did not affect the increased expression of SESN2 in response to ER stress induced by thapsigargin [44]. Consistent with these findings the knockdown of PERK and XBP-1 in mouse embryonic fibroblasts reduced the expression of SESN2 and made cells sensitive to death by ER stress. From the reviewed work, it seems that the three arms of the UPR i.e., PERK, IRE-1, and ATF-6, contribute to the regulation of SESN2 in response to ER stress. However, the most effective arm may depend on the type of ER stress-inducing agent, the duration of ER stress (acute or chronic), and/or the type of cell used to model the pathology. Oxidative stress, defined as an imbalance between oxidation and anti-oxidation systems, in addition to damaging nucleic acids can also damage other macromolecules, such as proteins, and lipids and, thus, greatly affect the aging and life span of the organism [45]. Oxidative stress is another trigger for the induction of SESN2. The observations from the initial experiments of Budanov et al. showed that the induction of SESN2 in response to hydrogen peroxide is independent of p53 because the presence of functional p53 is not required. Later, researchers showed that the induction of SESN2 in response to oxidative stress is dependent on the activation of NRF2. Chemical activators of NRF2 increase the expression of SESN2 only in the presence of a working NRF2 [46]. NRF2 is a transcription factor that mediates the antioxidant effects during stress by increasing the expression of antioxidant genes. Under normal conditions of oxidative balance, NRF2 remains bound to its negative repressor, Kelch-like ECH-associated protein 1 (KEAP-1), within the cytoplasm. The binding of the KEAP-1 homodimer with NRF2 facilitates proteolysis through its ubiquitination [47]. Oxidative stress and electrophiles cause the unbinding of the KEAP-1 from NRF2. The latter translocates to the nucleus for interaction with antioxidant response elements (ARE) for the transactivation of target genes (Figure 5). The SESN2 promoter region contains ARE and NRF2 binds to this response element to increase the expression of SESN2 [46]. SESN2 is also shown to positively regulate the NRF2 signaling by P62-dependent autophagosomal degradation of KEAP-1 which sets NRF2 free for its nuclear translocation [10]. In turn, NRF2 increases the expression of SESN2 in a positive feedback manner [46]. The downstream effects of SESN2 induction are mediated either by the intrinsic antioxidant activity of SESN2 or by increasing AMPK and NRF2 activation and mTORC1 inhibition. SESN2 also signals autophagy as a downstream effect. A review of the downstream effector pathways of SESN2 is presented here. The NTD domain of SESN2 contains five alpha-helical conserved regions with sequence similarity to the C-terminal alpha-helical domains of AhpD [19]. AhpD is a prokaryotic protein with organic alkyl hydroperoxide reductase activity and is also required for the regeneration of AhPC, a peroxiredoxin family protein (Prx) oxidized during the reduction of peroxides and reactive nitrogen species (Figure 6) [48,49]. Based on sequence and structural similarity and the role of SESN2 as an antioxidant, it was natural to think of SESN2 as functionally similar to AhpD. Unlike AphD, which contains two cysteine residues required for the regeneration of AhPC, SESN2 contains only one proximal Cys125 and the mutation of this cysteine residue to serine abolished the activity of SESN2 to protect from oxidative stress [19]. In eukaryotes, the Prx pathway has evolutionary benefits to allow the functioning of peroxide as a signaling molecule. In eukaryotes, during the correction of the basal level of oxidants, the peroxidatic cysteine of Prx is oxidized to Cys-SOH which then forms a disulfide bridge with the resolving cysteine of the other dimer. Thioredoxin (Trx) reduces this disulfide bridge to reproduce Prx. However, in cases of high oxidative stress, the Cys-SOH form of Prx can over-oxidize to Cys-SO2H. Although the initial experiments by Budanov et al. showed the reductase activity of SESN2 on Prx, later studies could not confirm this observation [50]. The alkyl hydroperoxide reductase activity of SESN2 was confirmed by the reduction of cumene hydroperoxide, but cumene hydroperoxide is not an endogenous peroxide [51]. It is now well-agreed that SESN2 is not the stand-alone reductase for Prx but helps in the reduction of the overoxidized form of Prx indirectly by increasing the expression of sulfiredoxin (Srx) and other antioxidant mechanisms [50]. SESN2 affects the mTORC1 pathway in two different ways [8,20,30,31]. SESN2 facilitates the activation of AMPK which, in turn, activates kinase for tuberous sclerosis 2 protein (TSC2) and thus prevents the activation of mTORC1. SESN2 is shown to directly interact with GATOR2 and free GATOR1 from the inhibitory control of GATOR2. GATOR1, in turn, keeps mTORC1 inactive. Both pathways are reviewed here separately. The induction of SESN2 in response to different stimuli provides defense against the initiating stress by modulating the activity of two important downstream targets, mTORC1 and NRF2. Budanov and Karin showed that SESN2 connects p53 to mTORC1 in response to DNA-damaging stress. SESN2 activates AMPK by its phosphorylation at the Thr172 residue. TSC2 is a GTPase activating protein (GAP) for the mTORC1 regulatory protein RAS homolog enriched in the brain (RHEB). The activation of the GTPase activity of RHEB by TSC2 hydrolyzes RHEB-bound GTP to GDP and, thus, inactivates RHEB preventing, therefore, the activation of mTORC1. The inhibition of mTORC1 activation prevents the cell from the stress that results from the synthetic activity necessary for growth and proliferation of the cell. Even in the absence of TSC2, cells remain sensitive to AMPK. This is because AMPK can directly phosphorylate two well-conserved serine residues of the regulatory associated protein of mTOR complex 1 (RAPTOR) and, thus, inhibits mTORC1 [52]. The precise mechanism of AMPK’s activation by SESN2 was revealed later when immunoprecipitation studies showed the association of SESN2, AMPK, and LKB1, an upstream regulator of AMPK during ischemia. SESN2 worked as a scaffolding protein to increase the interaction between LKB1 and AMPK [6]. Almost six years later, three independent research groups showed that the SESN2-AMPK-TSC2-RHEB-mTORC1 axis is not the only pathway for the control of SESN2 over mTORC1. SESN2 can also regulate the activity of mTORC1 through another GTPase belonging to the RAAG family which exists as an RRAG-A/B or RAAG-C/D heterodimer. The activation of RRAGs is dependent on the binding of GTP to RRAG-A/B and GDP to RRAG-B/C. The active heterodimers can bind with mTORC1 directly by RAPTOR and upon appropriate stimulation favoring cell growth and proliferation, stimulates the translocation of mTORC1 from the cytoplasm to the lysosomal membrane. RHEB then can activate mTORC1 at the lysosomal membrane. The binding of GTP to RRAG-A/B and the lysosomal translocation of the mTORC1 is increased by the guanine nucleotide exchange factor (GEF) activity of the regulator complex [53]. Conversely, the GAP activates the GTPase activity of the RRAG-A/B, and guanidine nucleotide dissociation inhibitors (GDIs) bind to the GDP-bound state of the complex to prevent the exchange of GDP to GTP, thus keeping the complex in an inactive form. GATOR1 is a GAP for RAAG-A/B and itself is under the inhibitory control of GATOR2 in the super complex of GATOR. Parmigiani et al. [21] and Chantranupong et al. [54] showed that SESN2 can interact with GATOR2, thus, removing the inhibitory control of GATOR2 over GATOR1. Peng et al. [55] showed a different mechanism of RRAG-A/B inactivation and reported that SESN2 is a GDI for RAG GTPases. The interaction between SESN2 and GATOR2 is sensitive to leucine levels. In case of leucine sufficiency, SESN2 can bind with leucine, and the interaction between SESN2 and GATOR2 is disrupted, leaving GATOR2 to inhibit GATOR1, activating the RRAG-A/B and mTORC1 complex. Thus, SESN2 is a leucine sensor for the mTORC1 pathway [31]. The possibility that the inhibition of mTORC1 through the inhibition of RHEB by TSC2 and RAAG-A/B by GATOR1 are closely related cannot be ruled out. It has been shown previously that the GDP-bound inactive form of RRAG-A/B interacts with the TSC complex and brings the complex to the lysosomal membrane to interact with RHEB [56,57]. Thus, it is possible that inactive RRAG-A/B plays a role in the inactivation of RHEB as well and integrates the SESN2 signals from the AMPK–TSC2–RHEB and GATOR2–GATOR1–RRAG-A/B axes. The interplay between SESN2 and mTORC2 is less studied as compared to mTORC1. By using a SESN2 knock-down mouse model, Lee et al. showed that the presence of SESN2 is required for the activation of AKT in response to insulin. In carefully designed experiments, they showed that the activation of AKT by SESN2 is dependent on the presence of RPTOR independent companion of mTOR complex 2 (RICTOR), a core component of mTORC2. The interaction of SESN2 and GATOR2 was not only important for the inhibition of mTORC1 but was also required for the increase in the catalytic activity of mTORC2. The deletion or silencing of the GATOR2 domains which interact with either SESN2 or mTORC2 blunted the activation of AKT [10]. SESN2 was also found to bind to the pleckstrin homology (Ph) domain of AKT, favoring the recruitment of AKT to the plasma membrane [23]. In our own experience, we have observed a blunted activation of AKT by silencing SESN2 in endothelial cells [58]. The inhibition of mTORC1 at one end and the activation of mTORC2 and AKT at the other shows that SESN2 integrates pro-survival signals from the AKT pathway while keeping the mTORC1 on a short leash to prevent the overdue stress that accumulates due to translational activity within the cell. A schematic representation of the effects of SESN2 on mTORC1 and mTORC2 is presented in Figure 7. The antioxidant properties of SESN2 were initially credited to the peroxiredoxin reductase activity of SESN2 [19], but later studies could not confirm this finding [50]. However, SESN2 increases the expression of sulfiredoxin, a reductase for hyperoxidized peroxiredoxin under the transcription control of NRF2 [22,59]. Bae et al. studied the missing link between SESN2 and NRF2 and showed that the degradation of KEAP-1 by autophagy is promoted by SESN2. KEAP-1 is a negative regulator of NRF2 in the cytoplasm and acts as a substrate adapter for the ubiquitination of NRF2 by the ubiquitin ligase complex. The proteasomal degradation keeps NRF2 levels low in case of non-stress states. Oxidants and electrophiles disrupt the correct conformational binding between NRF2 and KEAP-1 necessary for the ubiquitination and degradation of NRF2 and facilitate nuclear translocation and induction of transcription of antioxidant genes (Figure 5). The induction of KEAP-1 degradation by forced induction of SESN2 is dependent on P62 [22]. P62 or sequestosome 1 (SQSTM1) is an autophagy adapter with a KIR domain capable of binding with and tagging KEAP-1 for autophagic degradation. KIR domain resembles the ETGF motif of NRF2 and thus P62 competes with NRF2 for binding with KEAP-1. The interaction between KEAP-1 and P62 is not strong enough for the degradation of KEAP-1 with the autophagy substrate unless the concentration of KEAP-1 is enough to drive the equilibrium in the bound state. Thus, SESN2 appears to be a scaffolding protein to strengthen the interaction between KEAP-1 and P62. Autophagy is a protective mechanism by which the cells degrade damaged cytoplasmic organelles, proteins, and lipids to protect cells from stress and maladaptive cellular signals, as well as allow the generation of energy, especially during nutrient depletion [7]. In this process, the cytoplasmic content is encapsulated within the autophagosomes, double-membraned vesicles, which then fuse with lysosomes for degradation of their cargo content. Mitophagy is the autophagic elimination of malfunctioning mitochondria protecting the cell against aberrant ROS production. Autophagy-activating kinase (ULK1) is an important kinase in the formation of autophagosomes and regulates the formation of autophagophores [54]. SESN2 is a positive regulator of autophagy through the activation of AMPK and the inhibition of mTORC1 [24]. AMPK phosphorylates Ser317 and Ser777 of ULK1 activating it and inducing autophagy [60]. In contrast to AMPK, mTORC1 has an important role in negatively regulating autophagy as it inhibits ULK1 by its phosphorylation at Ser757 and disrupts the interaction between AMPK and ULK1 [60]. SESN2 also facilitates the phosphorylation of P62 by ULK1 and acts as a scaffolding protein [61]. P62 is an autophagy substrate and phosphorylation of P62 increases its binding affinity to targets, including KEAP-1, increasing their autophagic degradation [61]. Hypertension, dyslipidemia, and diabetes are among the leading and preventable risk factors for cardiovascular diseases. Essential hypertension is the most common type of hypertension and accounts for more than 95% of hypertension cases. The increase in oxidative stress and inflammation with growing age leads to endothelial dysfunction, making pressure-regulating vessels unresponsive to dilating stimuli. Moreover, the blood pressure regulatory function of the kidneys is disrupted by increased ROS and is associated with the chronic activation of the adrenergic nervous system and the renin–angiotensin–aldosterone system (RAAS), and increased reabsorption of sodium and water from the renal tubules, leading to volume and pressure overload. SESN2 has been shown to mediate the inhibitory effects of dopamine D2 receptors on ROS accumulation. The silencing of SESN2 in the mouse kidney increased ROS production and blood pressure in SESN2-deficient mice [62]. Angiotensin-II (Ang-II) is an effector of RAAS that not only increases blood pressure but also increases oxidative stress in the endothelial cells, making them hypertrophic and contributing thus to endothelial dysfunction. SESN2 has been shown to prevent the deleterious effects of Ang-II on the endothelium [63]. Ang-II increased the expression of SESN2 in human umbilical vein endothelial cells (HUVEC) in a time- and dose-dependent manner. Knockdown of SESN2 by siRNA increased oxidative stress and reduced the viability of endothelial cells in response to Ang-II. The increase in SESN2 was dependent on JNK/c-Jun pathway as overexpression of c-Jun increased the luciferase activity under the SESN2 promoter [63]. Increased circulating levels of SESN2 have been reported in hypertension patients [64]. The compensatory increase in SESN2 expression in response to Ang-II may serve as a protective mechanism to keep blood pressure within physiological limits. Atherosclerotic plaque formation is a complex process with the involvement of endothelial cells, vascular smooth muscle cells (VSMC), and the immune system. Hyperglycemia, dyslipidemia, hypertension, immune dysregulation, and endothelial dysfunction have been implicated in the development and progression of atherosclerotic plaques. SESN2 protects against the development and progression of plaque formation and higher levels of SESN2 plasma levels have been found in patients with carotid plaques and are associated with the severity of carotid stenosis [65]. Endothelial dysfunction is a well-established response to cardiovascular risk factors, such as hypertension, hyperglycemia, and dyslipidemia, and precedes the development of atherosclerosis. SESN2 has been shown to protect against endothelial dysfunction caused by different types of cellular stresses. Fatima et al. showed that SESN2 silencing can aggravate the effects of ER stress induced by thapsigargin. Silencing of SESN2 increased oxidative stress, reduced viability of endothelial cells, and dysregulated NRF2, AMPK, and mTORC1 signaling pathways [58]. Macrophages play an important role in the formation and development of atherosclerotic plaques. Macrophages are derived from circulating monocytes and the expression of adhesion molecules on endothelial cells facilitates the capture, activation, transport, and polarization of these monocytes into the subendothelial tissue to become tissue macrophages. SESN2 has been shown to reduce the expression of adhesion molecules on the surface of HUVECs, and monocyte (THP-1) activation and polarization in vitro [66,67]. Knockdown of SESN2 increased ROS, ER stress, and the secretion of proinflammatory cytokines from endothelial cells and monocytes in response to lipopolysaccharides (LPS) exposure [66]. The expression of adhesion molecules on the endothelial cells and the adhesion of monocytes to endothelial cells were increased. At the molecular level, the decreased activation of AMPK and increased phosphorylation of nuclear factor kappa B (NFB) was observed. The activation of AMPK by AICAR (5-aminoimidazole-4-carboxamide-1--D-ribofuranoside) abrogated the effects of SESN2 silencing and LPS treatment on these cells. Similar results were obtained from aorta samples of mice. Hyperglycemia and dyslipidemia increase the risk of atherogenesis and SESN2 has been shown to decrease the activation of monocytes (THP-1) and the expression of pro-inflammatory markers in these states [67]. Hyperglycemic or dyslipidemia conditions increased the adhesion of monocytes to endothelial cells, the polarization of monocytes to M1 macrophages, and the formation of foam cells. The silencing of SESN2 and AMPK inhibition by compound C worsened the situation by increasing the phosphorylation of mTOR. The accumulation of lipids and the formation of foam cells were increased by the inhibition of autophagy. Hu et al. observed an increased expression of SESN2 in the macrophage cell line Raw264.7 upon exposure to oxidized low-density lipoproteins (OxLDL) in a time- and dose-dependent manner. The silencing of SESN2 by siRNA increased ROS production and apoptosis of the cells. Death of macrophages is characteristic of advanced plaques and contributes to the formation of necrotic core and destabilization of the plaque. Mechanistically, an increase in SESN2 expression in response to OxLDL was dependent on JNK/c-Jun pathway, as inhibiting the activity of the pathway abolished the effects of OxLDL on the expression of SESN2 [68]. Precise control of the proliferation and apoptosis of VSMCs is required for healthy vessels. The excessive proliferation of VSMCs can lead to atherosclerosis while their apoptosis may cause destabilization and rupture of atherosclerotic plaque. The induction of SESN2 by melatonin has been shown to reduce the proliferation of VSMCs by inhibiting mTORC1 and reducing ROS [69]. Melatonin increased the expression of SESN2 through C/EBP by inducing mitochondrial energetic stress. The increased oxygen demand of the myocardium or limited supply due to plaque build-up in the coronary arteries leads to myocardial ischemia which may progress to infarction if reperfusion is not achieved. Reperfusion should, in principle, restore the dysfunction of the myocardium, but paradoxical damage to the tissue after the restoration of the blood flow is a well-known phenomenon, known as ischemia-reperfusion (I/R) injury [70]. Generation of oxygen-free radicals upon the resupply of oxygen, endothelial dysfunction and microvascular injury, alterations in calcium handling, and myocardial metabolism are mediators of I/R injury. There is increasing evidence that SESN2 is important in preventing the heart from ischemia/reperfusion injury. Higher SESN2 levels and increased oxidative stress were observed in response to I/R as compared to the normoxic hearts [71]. Knockdown of SESN2 worsened oxidative stress and increased the infarct size and cardiac dysfunction in I/R. The re-introduction of SESN2 in the knockout hearts by the adenoviral expression system rescued the hearts from I/R injury by increasing the expression of SESN2 and reducing oxidative stress. During ischemia, SESN2 protein expression was found to be increased in the adult cardiomyocytes just after 5 minutes, indicating decreased degradation of the protein instead of increased de novo synthesis [6]. In SESN2-deficient mouse hearts, I/R greatly enhanced the infarct size. Ischemic AMPK activation was found to be impaired in the SESN2-deficient hearts. Mechanistically, SESN2 served as a scaffolding protein to facilitate the interaction of AMPK with its upstream kinase LKB1. The cardioprotective effects of AMPK during and after ischemia are well-established and ischemia-induced AMPK activation decreases with age which makes the aging hearts more susceptible to ischemic injury. Quan et al. studied the role of SESN2 in decreased activation of AMPK and showed changes in downstream substrate metabolism in response to ischemia. The expression of SESN2 decreased with age in mouse hearts and corresponded with the decreased activation of AMPK in response to ischemia [11,12]. The uptake of glucose and the rate of glucose oxidation was significantly impaired in the aged wild-type hearts and young SESN2-deficient hearts. The phenotype observed in SESN2-deficient hearts was similar to wild-type aged hearts. An aging-like phenotype of mouse hearts in response to SESN2 deficiency was also reported in other more recent studies [72,73]. Transcriptomic changes in the SESN2-deficient hearts were also like aged wild-type hearts when challenged with I/R indicating an age-related decline in SESN2 levels and a decreased tolerance of the myocardium to I/R. SESN2 deficiency in the hearts increased oxidative stress, provoked an immune response, and resulted in structural changes similar to those observed in aged hearts under physiological conditions [73]. The overexpression of SESN2 in the hearts with the coronary delivery of an overexpression plasmid DNA improved the tolerance of the hearts to I/R via enhanced activation of AMPK, improved uptake of glucose by increasing the translocation of GLUT4 to the plasma membrane and increased rate of glucose oxidation [11]. Regional myocardial ischemia in the hearts of aged mice and SESN2-deficient young mice decreased the activation of AMPK and downregulated PGC-1 [12]. PGC-1 is a mediator of mitochondrial biogenesis. The downstream effectors of PGC-1, TFAM, and UCP2, were impaired and apoptotic flux markers, AIF and Bax/Bcl-2, were upregulated in the aged and SESN2-deficient hearts making them more susceptible to ischemic injury. A similar protective effect of SESN2 via the AMPK/ PGC-1 pathway has also been described in the cerebral I/R [74]. SESN2 silencing by SESN2-specific siRNA duplexes exacerbated neuronal damage and increased infarct volume in response to ischemia modeled by the occlusion and reperfusion of the middle cerebral artery. A significant increase in oxidative stress with a corresponding decrease in mitochondrial biogenesis was also observed. The antioxidant effects of SESN2 on the heart in response to I/R were also attributed to a significant reduction in the activation of p38 mitogen-activated protein kinase (MAPK), extracellular signal-regulated kinase (ERK), and JNK which was observed following the overexpression of SESN2 in isolated cardiomyocytes [71]. In patients with coronary artery disease (CAD), plasma levels of SESN2 were found to be high and associated with the severity of CAD [75,76]. Higher circulating levels of SESN2 were also observed in diabetic patients [77]. However, diabetic patients with concurrent CAD had lower serum SESN2 as compared to diabetic patients without CAD. Cardiac hypertrophy is an adaptive response to pressure or volume stress and can lead to heart failure. Increasing evidence suggests that SESN2 prevents hypertrophy and cardiac remodeling. Overexpression of SESN2 salvaged the neonatal heart cardiomyocytes from the hypertrophic effects of phenylephrine by decreasing the phosphorylation of MAP-kinases and mTOR [78]. Silencing of SESN2 increased the hypertrophic marker, anti-natriuretic peptide (ANP), and cell surface area, indicating the protective role of SESN2 in phenylephrine-induced hypertrophy. The heart requires precise control of mTORC1. Hyperactivation of mTORC1 can increase the chance of postpartum cardiac hypertrophy [79]. As a regulator of mTORC1 activity, SESN2 is necessary to keep mTORC1 levels within control to prevent hypertrophy after birth. An RNA-binding protein (RBP), Zinc finger protein 36 like 2 (ZFP36L2) was found to inhibit mTORC1 to prevent hypertrophy in a p53-dependent manner by increasing the decay of MDM2 mRNA and increasing the expression of SESN2 [79]. The stabilization of p53 by chemical stabilizers could be used as a therapeutic strategy to prevent the hyperactivity of mTORC1 [80]. Nutlin-3, a chemical that destabilizes the interaction between p53 and MDM2 increased SESN2 levels and baseline expression of ZFP36L2 to rescue the heart from hypertrophic changes [79]. SESN2 also showed a protective role against oxidative stress and atrial fibrosis in a cell model of atrial fibrillation [81]. Collagen volume fraction was increased in patients and a positive association between SESN2 concentrations and oxidative stress in atrial fibrillation patients was found [81]. Overexpression of SESN2 increased the survival of HL-1 cells and prevented fibrosis by decreasing the proliferation of fibroblasts in response to Ang-II [63]. Cardioprotective effects of pentamethyl quercetin (PMQ) by increasing the concentration of SESN2 in a transverse aorta constriction-induced pressure-overload cardiac-remodeling model in mice, and an isoproterenol-induced neonatal rat cardiomyocyte hypertrophy model, have been reported [82]. Similar protective effects of PMQ on cardiac remodeling were also observed in monosodium glutamate-induced obese mice through SESN2/KEAP-1/NRF2 pathway [83]. The increased expression of SESN2 by PMQ not only prevented cardiac remodeling but also improved metabolic disorders in the mice. Obese patients are at higher risk of developing diabetes and cardiovascular complications. In a recent study, diastolic function was studied in obese mice and cardiospecific SESN2 knockout exacerbated the impairment of the diastolic function which was preserved by overexpression of SESN2 [26]. SESN2 deletion increased fibrosis, cellular damage, inflammation, and ROS levels. Increased NRF2 and SESN2 expression were observed in the human cardiac tissues of obese individuals. Such an increase could be a compensatory response to an increased ROS. Empagliflozin has been shown to reduce hypertrophy, fibrosis, and cardiac dysfunction in a SESN2-dependent manner in an obese mouse model [84]. However, the dependency of Empagliflozin on SESN2 for the cardioprotective effects was partial, indicating the involvement of other pathways as well. In the fatty liver of mice, Empagliflozin has been shown to activate the AMPK/mTOR pathway and decrease lipid accumulation in hepatocytes in a SESN2 dependent manner [85]. A functioning ER is of particular importance for the contractile function of the cardiomyocytes as it maintains calcium homeostasis within the cell. ER stress can alter this homeostasis resulting in cardiac dysfunction which is at the core of many heart diseases including hypertrophy, ischemic heart disease, and heart failure. ER stress in the mouse heart induced by tunicamycin increased the myocardial volume and reduce the ejection fraction of the heart [25]. The defects in contractile function were due to alterations in calcium homeostasis as the decay rate of calcium intracellular was greatly reduced. The dysfunction of the heart was more pronounced in the SESN2-deficient mice. The genetic deletion of SESN2 worsened the ER stress by decreasing the activation of AMPK, increasing the activation of mTORC1, and decreasing autophagy process [25]. Further studies are, however, required to examine the role of SESN2 overexpression on autophagy induction and protection from ER stress and cardiac hypertrophy. Inflammation also plays an important role in inflammation-mediated cardiomyopathy and cardiac remodeling. The inflammatory condition induced by LPS in H9c2 cardiomyocytes required functional levels of SESN2 for AMPK activation, antioxidant gene SOD2, and catalase expression and protection against increased ROS levels [86]. MMP2 and MMP9 expression and cell death were also increased by SESN2 knockdown. AICAR, an AMPK activator, prevented these disturbances. Consistent results were obtained in vivo in a mouse model where SESN2 deletion increased the expression of cardiac fibrotic factors, collagen I and III, in addition to MMP2 and MMP9. High serum levels of SESN2 clearly could distinguish septic shock patients from healthy controls, whereas low circulating levels of SESN2 are related to cardiac dysfunction to some extent but are not an independent influence factor for septic cardiomyopathy [87]. Low circulating levels of SESN2 were shown to be useful in predicting clinical outcomes in patients with septic cardiomyopathy [88]. The ability of the body to respond to stress in an adequate and timely manner is important for the viability and functioning of the cells and to prevent the accumulation of cellular lesions. Cellular proteins and molecular pathways induced in response to stress either protect the cell from the damaging effects or help the cell to die in peace to prevent chronic inflammation. The response of these inducible proteins to stress is known to decline with age, but other epigenetic and genetic factors cannot be ruled out. The declined response to stress results in age-related pathologies, such as CVD, and modulating the expression or activity of stress-inducible proteins presents an interesting opportunity to prevent or treat these pathologies. SESN2 is a stress-inducible protein that acts as a protective shield against CVD directly or by modulating the activity of different cellular pathways. The expression of SESN2 has been shown to increase by some natural products, e.g., resveratrol, eupatilin, luteolin, quercetin, and pentamethyl quercetin [82,89,90,91,92]. Empagliflozin also modulates the activity of downstream pathways in SESN2 dependent manner [84,85]. The modulation of the activity of SESN2 is possible by small molecules which bind in the leucine binding site of SESN2. NV-5138, a leucine analog for SESN2 which selectively activates mTORC1 in the brain is under development by Navitor Pharmaceuticals [93]. An antagonist of leucine effects on SESN2 in principle can inhibit mTORC1 even in the presence of leucine sufficiency. The structural basis for the interaction of SESN2 with other proteins, such as AMPK and LKB1, needs further research to find small molecules capable of stabilizing such interactions. Such molecules will open a novel avenue in the discovery of drugs against CVD and age-related pathologies.

PMC10003524

Kinjal Shah,Lina Al Ashiri,Ahmad Nasimian,Mehreen Ahmed,Julhash U. Kazi

Venetoclax-Resistant T-ALL Cells Display Distinct Cancer Stem Cell Signatures and Enrichment of Cytokine Signaling

05-03-2023

apoptosis resistance,targeted therapy,leukemia,BCL2 inhibition,navitoclax

Therapy resistance remains one of the major challenges for cancer treatment that largely limits treatment benefits and patient survival. The underlying mechanisms that lead to therapy resistance are highly complicated because of the specificity to the cancer subtype and therapy. The expression of the anti-apoptotic protein BCL2 has been shown to be deregulated in T-cell acute lymphoblastic leukemia (T-ALL), where different T-ALL cells display a differential response to the BCL2-specific inhibitor venetoclax. In this study, we observed that the expression of anti-apoptotic BCL2 family genes, such as BCL2, BCL2L1, and MCL1, is highly varied in T-ALL patients, and inhibitors targeting proteins coded by these genes display differential responses in T-ALL cell lines. Three T-ALL cell lines (ALL-SIL, MOLT-16, and LOUCY) were highly sensitive to BCL2 inhibition within a panel of cell lines tested. These cell lines displayed differential BCL2 and BCL2L1 expression. Prolonged exposure to venetoclax led to the development of resistance to it in all three sensitive cell lines. To understand how cells developed venetoclax resistance, we monitored the expression of BCL2, BCL2L1, and MCL1 over the treatment period and compared gene expression between resistant cells and parental sensitive cells. We observed a different trend of regulation in terms of BCL2 family gene expression and global gene expression profile including genes reported to be expressed in cancer stem cells. Gene set enrichment analysis (GSEA) showed enrichment of cytokine signaling in all three cell lines which was supported by the phospho-kinase array where STAT5 phosphorylation was found to be elevated in resistant cells. Collectively, our data suggest that venetoclax resistance can be mediated through the enrichment of distinct gene signatures and cytokine signaling pathways.

Venetoclax-Resistant T-ALL Cells Display Distinct Cancer Stem Cell Signatures and Enrichment of Cytokine Signaling Therapy resistance remains one of the major challenges for cancer treatment that largely limits treatment benefits and patient survival. The underlying mechanisms that lead to therapy resistance are highly complicated because of the specificity to the cancer subtype and therapy. The expression of the anti-apoptotic protein BCL2 has been shown to be deregulated in T-cell acute lymphoblastic leukemia (T-ALL), where different T-ALL cells display a differential response to the BCL2-specific inhibitor venetoclax. In this study, we observed that the expression of anti-apoptotic BCL2 family genes, such as BCL2, BCL2L1, and MCL1, is highly varied in T-ALL patients, and inhibitors targeting proteins coded by these genes display differential responses in T-ALL cell lines. Three T-ALL cell lines (ALL-SIL, MOLT-16, and LOUCY) were highly sensitive to BCL2 inhibition within a panel of cell lines tested. These cell lines displayed differential BCL2 and BCL2L1 expression. Prolonged exposure to venetoclax led to the development of resistance to it in all three sensitive cell lines. To understand how cells developed venetoclax resistance, we monitored the expression of BCL2, BCL2L1, and MCL1 over the treatment period and compared gene expression between resistant cells and parental sensitive cells. We observed a different trend of regulation in terms of BCL2 family gene expression and global gene expression profile including genes reported to be expressed in cancer stem cells. Gene set enrichment analysis (GSEA) showed enrichment of cytokine signaling in all three cell lines which was supported by the phospho-kinase array where STAT5 phosphorylation was found to be elevated in resistant cells. Collectively, our data suggest that venetoclax resistance can be mediated through the enrichment of distinct gene signatures and cytokine signaling pathways. T-cell acute lymphoblastic leukemia (T-ALL) is a type of acute leukemia that develops from immature white blood cells [1]. It is considered to be one of the most aggressive forms of leukemia, and it occurs in both children and adults representing around 15% and 25% of the patients, respectively [2]. T-ALL is characterized by several unique genetic features that disrupt key signaling pathways, including the abnormal activation of NOTCH signaling, deregulated expression of transcription factors and tumor suppressors, abnormal activation of kinase and cytokine signaling, and disruption of cell cycle regulation [1,3,4,5]. At present, a majority of T-ALL patients are treated with chemotherapy [6]. Despite the fact that survival rates have improved in children with T-ALL, as a result of better risk assessment and chemotherapy regimens, the disease is still very hard to treat upon relapse, and there are few treatment options available [7]. This highlights the need for new therapies to better treat this patient population. The normal development of T-cells is a tightly controlled process [8]. Among the various regulators, the expression of B-cell lymphoma 2 (BCL2) family proteins plays an important role in this process. For example, BCL2 expression is upregulated in double-negative thymocytes, then downregulated in a majority of double-positive thymocytes, and finally upregulated in mature single-positive thymocytes [9,10]. Expression of this family of proteins also varies in T-ALL. A group of T-ALL patients display a higher level of BCL2 expression and therefore show sensitivity to the BCL2-specific inhibitor venetoclax [11,12,13,14]. The BCL2 family proteins are characterized by the presence of a highly conserved BH3 domain. These family proteins are subdivided into three groups: multidomain proapoptotic (BAK [BCL2L7], BAX [BCL2L4], BOK [BCL2L9]), multidomain antiapoptotic (BCL2, BCL-B [BCL2L10], BCL-W [BCL2L2], BCL-XL [BCL2L1], BFL-1 [BCL2A1 or BCL2L5], MCL-1 [BCL2L3]), and BH3-only proteins, including the BH3-only activators (BID [BCL2L11], BIM [BCL2L11], PUMA [BBC3]) and BH3-only sensitizers (BAD [BCL2L8], BCL-G [BCL2L14], BCL-RAMBO [BCL2L13], BIK, BMF, HRK, NOXA [PMAIP1], SPIKE) [15,16]. In response to cellular stress, such as DNA damage, energy stress, growth factor withdrawal, hypoxia, etc., the expression of BH3-only members is elevated, and, therefore, proapoptotic members are activated through the release of antiapoptotic members or by the binding of activators. These facilitate the oligomerization of proapoptotic members, thereby creating channels in the mitochondrial outer membrane to release Cytochrome c. Thus, the expression levels of BCL2 family proteins determine whether the cell will go into apoptosis or not upon stress [16]. Since the BH3 domain plays an important role in the regulation of BCL2 family proteins, an initial attempt was taken to inhibit BCL2 by BH3 mimetics. Several BH3 mimetics (obatoclax, ABT737, sabutoclax, and navitoclax) were reported to be non-specific, and displayed higher toxicity [17,18,19,20,21,22,23]. The BCL2-specific inhibitor venetoclax was shown to be highly specific and well-tolerated and received FDA approval for the treatment of certain indications of chronic lymphoblastic leukemia and acute myeloid leukemia [21]. Venetoclax binds to BCL2 and interrupts association with BH3-only activators such as BIM, leading to the activation of the proapoptotic protein BAX [21]. Although venetoclax specifically inhibits BCL2, sensitivity varies from patient to patient and cannot always be explained by the level of BCL2 expression [14,24,25]. The expression of several other BCL2 family members, such as BCL-XL and MCL1, can play a role in venetoclax sensitivity, and inhibitors targeting multiple proteins displayed better efficacy with a cost of higher toxicity [25,26,27]. Elevated expression of those genes was reported to be maintained by secreted proteins such as IL10 and CD154, activation of toll-like receptor 9 (TLR9), and NFκB signaling [21,28]. Furthermore, copy number alterations in TP53, SF3B1, RB1, NOTCH1, VD274, and BRAF, mutations in BCL2, and ERK1/2-mediated phosphorylation of BIM contributes to venetoclax resistance [21,28,29,30,31] Although substantial progress has been made, a deeper understanding of resistance to BCL2 inhibitors is required in order to create more effective and safer treatments. In this study, we generated venetoclax-resistant cell lines via prolonged exposure to increasing concentrations of venetoclax, to study the underlying mechanisms of its resistance. We used RNAseq to determine the deregulated gene signatures in resistant cells. The expression level of BCL2 varies during T-cell development, which is maintained in different subgroups of T-ALL. To explore the expression pattern of pro-survival BCL2 family proteins, we analyzed the mRNA expression of BCL2, BCL2L1 (BCL-XL), BCL2L2 (BCL-W), and MCL-1 from seven T-ALL patient cohorts in which a wide range of variations in terms of their expression was demonstrated (Supplementary Figure S1A,B). MCL-1 displayed consistently higher expression, with a moderate variation in expression (variance between 0.7 and 1.75), except in the GSE28703 cohort. BCL2L2 expression was comparatively low, with lower expression variation (variance between 0.05 and 0.93). Expression of BCL2L1 and BCL2 was different in different cohorts, and the variance of BCL2 was consistently high (variance between 1.69 and 3.44) in all cohorts except for a pediatric T-ALL cohort, GSE26713 (variance 0.61). However, we did not see any correlation between the expression of these four genes. Because higher variation in BCL2 expression could be explained by the presence of early T-cell precursor (ETP)-ALL, we analyzed three patient cohorts (in which patients were labeled as ETP- or non-ETP-ALL) with the ETP-ALL samples removed. Although the variance was reduced slightly, it remained higher for BCL2 compared to the other three genes (Supplementary Figure S1C,D), suggesting that BCL2 expression could be increased in non-ETP ALL patients. Next, we used a panel of cell lines (Supplementary Table S1) to further assess the expression of antiapoptotic BCL2 family members. The expression of BCL2, BCL2L1, and MCL1 was detected at the mRNA (Figure 1A) and protein levels (Figure 1B) in all cell lines. BCL2L2 expression was relatively low-to-undetectable and the expression of MCL1 was higher in all cell lines (Figure 1A). BCL2 expression was lower in RPMI-8402, MOLT-4, and JURKAT cell lines, while other cell lines displayed almost equal levels of expression. BCL2L1 expression was lower in LOUCY and MOLT-16 cells but higher in all other cell lines. Because the BCL2/BCL2L1 ratio can influence the sensitivity of BCL2-specific inhibitors [25], we next determined the ratio between BCL2/BCL2L1, as well as BCL2/MCL1 and BCL2L1/MCL1. While the BCL2L1/MCL1 ratio was high in several cell lines, the BCL2/BCL2L1 ratio was only higher in the LOUCY and MOLT-16 cell lines, and the BCL2/MCL1 ratio was almost the same in all cell lines (Figure 1C). Similar to the mRNA ratio, the BCL2/BCL2L1 protein ratio was higher in LOUCY and MOLT-16 cells (Figure 1D). Collectively, our data suggest that the expression of BCL2 family proteins varies among T-ALL patients as well as among T-ALL cell lines. Because we observed a higher ratio of BCL2/BCL2L1 in LOUCY and MOLT-16 cells, we hypothesized that LOUCY and MOLT-16 would display higher sensitivity to a BCL2-specific inhibitor, while others would display resistance. As anticipated, LOUCY and MOLT-16 cells were highly sensitive to venetoclax and several other cell lines did not respond (Figure 2A,B). Although ALL-SIL displayed a low BCL2/BCL2L1 ratio (Supplementary Figure S2A), as opposed to LOUCY and MOLT-16, it was also highly sensitive (Figure 2A,B). Therefore, it is likely that the BCL2/BCL2L1 ratio cannot reliably predict venetoclax sensitivity. As we observed a higher expression of BCL2L1 in several cell lines, we used navitoclax, which inhibits BCL2, BCL2L1, and BCL2L2. The majority of cell lines were sensitive to navitoclax (Figure 2C,D), and the response was largely but not completely dependent on the BCL2L1/MCL-1 ratio. Similarly, inhibitor data from the Genomics of Drug Sensitivity in Cancer (GDSC) cell line project also displayed wide variation in the response in T-ALL cell lines (Supplementary Figure S2B–E). Taken together, our data suggest that the BCL2/BCL2L1 and BCL2L1/MCL-1 ratios have limited applications in the prediction of venetoclax and navitoclax sensitivity, respectively. To understand how cells develop venetoclax resistance, we treated all three sensitive cell lines with increasing concentrations of venetoclax until cells developed resistance to at least 5 µM venetoclax (Figure 3A). We measured BCL2, BCL2L1, and MCL-1 expression by sampling at different venetoclax concentrations and observed differential regulation during treatment (Figure 3B). While the MOLT-16 and LOUCY cell lines displayed a similar expression pattern of all three genes, BCL2L1 expression was consistently high in venetoclax-treated ALL-SIL cells. The BCL2/BCL2L1 ratio was increased in MOLT-16 cells but decreased in ALL-SIL and LOUCY cell lines (Figure 3C). In ALL-SIL, the ratio was decreased in cells at the beginning of the treatment and stayed low during the treatment period. Upon withdrawal of venetoclax for two weeks, expression of both BCL2 and BCL2L1 was decreased in MOLT-16 and ALL-SIL cells, while BCL2 expression was increased in LOUCY cells (Figure 3D and Supplementary Figure S3). The BCL2/BCL2L1 ratio was restored to the initial value in MOLT-16 and LOUCY cells but reduced in ALL-SIL (Figure 3E), further demonstrating that the BCL2/BCL2L1 ratio has limited applicability for venetoclax response prediction. Next, we isolated total mRNA from venetoclax-sensitive and venetoclax-resistant cells and analyzed them via RNA-seq. Samples were collected after being cultured in the absence of venetoclax for two weeks or longer. We observed that venetoclax-resistant ALL-SIL and MOLT-16 cells formed different clusters, while venetoclax-resistant LOUCY cells clustered with sensitive cell lines (Figure 4A). BCL2 family genes were also differentially regulated in different cells. For example, expression of BAD, BIK, and BCL2 was downregulated more than two-fold in MOLT-16 (Supplementary Figure S4A), while expression of those genes remained unchanged or changed slightly in LOUCY (Supplementary Figure S4B) and ALL-SIL (Supplementary Figure S4C). The expression of BMF, BCL2L11, and BCL2L1 was upregulated 2-fold or more, but BAX expression was downregulated 1.8-fold in ALL-SIL (Supplementary Figure S4C). While comparing sensitive and resistant cells, we observed cell line-specific transcriptional regulation (Figure 4B,C). Pathway enrichment analysis also showed differential enrichment in the pathways in different resistant cell lines (Figure 4D and Supplementary Figure S5). Furthermore, we observed the enrichment of different sets of cancer stem cell (CSC) markers in different cell lines (Figure 4E). Similarly, using the Proteome Profiler Human Phospho-Kinase Array Kit, we detected cell line-specific regulation of kinase activation (Figure 4F). However, we observed enrichment in cytokine signaling pathways in all three resistant cell lines (Figure 4D), which were also present in the phospho-kinase array, as we detected strong STAT5 phosphorylation in resistant cells (Figure 4F). In this study, we generated venetoclax-resistant cell lines from the highly sensitive T-ALL cell lines ALL-SIL, LOUCY, and MOLT-16. We compared gene expression and protein kinase activation between sensitive and resistant cell lines using RNA sequencing and Proteome Profiler Human Phospho-Kinase Array. We observed the activation of cytokine signaling and cell line-specific enrichment of cancer stem cell markers. The expression level of BCL2 varies during T-cell development, which is maintained in different subgroups of T-ALL. The expression level is relatively higher for ETP-ALL in comparison to non-ETP T-ALL patients. However, we observed higher levels of variation in BCL2 expression within non-ETP -TALL. T-ALL cell lines derived from patients of different ages (Supplementary Table S1) also showed different levels of BCL2 expression at the gene and protein levels and responded differentially to the BCL2 inhibitors. These observations suggest that the response to the BCL2 inhibitor is not limited to the BCL2 expression level. Expression of several other members including BCL-XL and MCL1 can modulate the efficacy of BCL2 inhibitors [21]. Expression of BCL2 and other anti-apoptotic BCL2 family proteins is tightly regulated by several signaling mediators. For example, T-ALL cells dependent on the JAK-family kinase TYK2 display elevated BCL2 levels, which can be suppressed by TYK2 depletion [32]. In mature T-ALL, TYK2-STAT1 signaling promotes survival through BCL2, which has also been linked to cytokine signaling [33]. Genetic abnormalities such as chromosomal rearrangement via translocation or deletion can drive elevated BCL2 expression in other diseases [34,35,36]. Thus, there are different mechanisms that contribute to elevated BCL2 expression, thereby aiding in cell proliferation and evading apoptosis. The identification of such genetic abnormalities in any of our venetoclax-resistant cells is another area to explore. However, we observed that T-ALL cells displaying venetoclax resistance exhibit differential expression of BCL2 family members, which does not always follow the classical BCL2/BCL2L1 expression ratio [25]. Furthermore, acquired resistance to venetoclax is probably achieved through the activation of several different pathways, including cytokine signaling, as we observed in GSEA, which is in line with the previous observation [33]. The signal transducer and activator of transcription (STAT) proteins are key transcription factors that play important roles in cytokine signaling [37]. We observed the enrichment of IL3, IL12, and IL23 signaling pathways and elevated phosphorylation of STAT5 and STAT3 in venetoclax-resistant cells. All three cytokines, IL3, IL12, and IL23, are known to activate STAT3 and STAT5 [38,39,40], further suggesting the link between venetoclax resistance and cytokine signaling in T-ALL. The role of STAT5 in venetoclax resistance has not been studied well. One study suggests that the inactivation of STAT5 enhances venetoclax efficacy [41]. Furthermore, the oncogenic mutant of type III receptor tyrosine kinase FLT3 (FLT3-ITD) activates STAT5 signaling and regulates BCL-XL and MCL1 expression [42,43,44]. Therefore, it is likely that venetoclax resistance through cytokine/STAT5 signaling is partially mediated through the transcriptional regulation of BCL2 family proteins. We observed enhanced expression of CSC markers in the venetoclax-resistant cells. CSCs are well known for their roles in therapy resistance [45,46,47,48]. For instance, the type I transmembrane protein CD44, which was upregulated in venetoclax-resistant MOLT-16 and ALL-SIL cells, was involved in the regulation of venetoclax sensitivity in acute myeloid leukemia [49]. Expression of CD44 was reported to be regulated by STAT5 activation in mastocytosis [50], possibly linking cytokine signaling to the expression of CSCs through STAT5 activation. Several other CSC markers which are upregulated in venetoclax resistance cells including NOTCH1 and IL7R have been reported to be involved in therapy resistance in different settings [51,52]. Taken together, our data suggest that venetoclax resistance in T-ALL can be mediated through the activation of cytokine signaling, which might eventually regulate the expression of cancer stem cell markers. The human leukemia cell lines (CCRF-CEM, CML-T1, DND-41, JURKAT, KE-37, MOLT-16, PF-382, P12-ICHIKAWA, and RPMI-8402) were grown in RPMI 1640 medium containing 10% heat-inactivated fetal bovine serum (FBS) from ThermoFisher Scientific, Waltham, MA, USA, 100 U/mL penicillin, and 100 µg/mL streptomycin from Corning, USA. The ALL-SIL, CTV-1, LOUCY, MOLT-4, and TALL-1 cell lines, on the other hand, were cultured in RPMI 1640 supplemented with 20% heat-inactivated FBS from ThermoFisher Scientific, Waltham, MA, USA, 100 U/mL penicillin and 100 µg/mL streptomycin from Corning, USA. All the cell lines were obtained from Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ, Braunschweig, Germany) and maintained in a ThermoFisher Scientific (Waltham, MA, USA) Heraeus BBD 6220 Incubator at 37 °C with 5% CO2. The cell lines were routinely screened for the presence of mycoplasma. The viability of T-ALL cell lines was evaluated against different concentrations of BCL-2 inhibitors, navitoclax, and venetoclax, in 96-well plates by seeding the cells at a density of 20,000 cells per well. To determine the effective concentration 50 (EC50) for venetoclax, venetoclax-resistant cell lines (MOLT-16, LOUCY, and ALL-SIL) were seeded in the same way. After a 48-h incubation period, 10 µL of PrestoBlue was added to each well and incubated for 2 h. Fluorescence was then measured using a plate reader, and EC50 values were calculated using GraphPad Prism 5.0 software. All cell lines were lysed in a RIPA buffer supplemented with protease/phosphatase inhibitors (PMSF, Trasylol, and Na3VO4). The bicinchoninic acid (BCA) assay method (ThermoFisher Scientific, Waltham, MA, USA) was used to determine the protein concentration of the total cell lysates. Around 10 µg of lysates were separated on SDS-PAGE gels; this was followed by their transfer to polyvinylidene difluoride (PVDF) membranes. The membranes were incubated with a panel of different primary antibodies. The anti-BCL2 (sc-509, 1:1000 dilution) and anti-β-actin-HRP (sc-47778, 1:2000 dilution) were obtained from Santa Cruz Biotechnology, Dallas, TX, USA. Anti-BCLXL (BCL2L1, 10783-1-AP, 1:4000) and anti-MCL1 (16225-1-AP, 1:2000) antibodies were from ProteinTech, Rosemont, IL, USA. For immunodetection, all the blots were incubated with the respective horseradish peroxidase-conjugated secondary antibodies, developed with the Luminata Forte Western HRP substrate (Millipore), and imaged with the Amersham Imager 600 (GE Healthcare, Danderyd, Sweden). ImageJ (NIH, Bethesda, MD, USA) was used to perform a densitometric analysis of the protein bands. Total RNA was extracted from T-ALL cell lines and even venetoclax-resistant T-ALL cells, using the RNeasy mini kit (Qiagen) following the manufacturer’s instructions. The High-Capacity cDNA Reverse Transcription Kit (ThermoFisher Scientific, Waltham, MA, USA) was used to synthesize cDNA according to the manufacturer’s instructions. RT-qPCR was run to assess gene expression using gene-specific qPCR primer assays (ThermoFisher Scientific, Waltham, MA, USA) and an Applied Biosystems QuantStudio 7 Flex detection system. Each sample was analyzed in quadruplicate, and gene expression was normalized to the endogenous controls such as GAPDH and β-Actin. Relative changes in gene expression were calculated with the help of the comparative Ct method. Different probes used for qPCR included BCL2, BCL2L1, BCL2L2, MCL1, GAPDH, and β-Actin. These probes were ordered from ThermoFisher Scientific, Waltham, MA, USA. Target gene expression levels were normalized against GAPDH and β—actin, and relative expression was determined using the ΔΔCt method. Total RNA was extracted from venetoclax-resistant cells using the RNeasy mini kit (Qiagen N.V. Venlo, The Netherlands) following the manufacturer’s instructions. The quality of total RNA was checked by Bioanalyzer (Agilent, Santa Clara, CA, USA), and the samples with an RNA integrity greater than 8 were further analyzed following the previously described method [53] with the help of the Center for Translational Genomics (CTG) at Lund University. The Proteome Profiler Human Phospho-Kinase Array Kit (ARY003C) was obtained from R&D Systems (Minneapolis, MN, USA). Venetoclax-sensitive and venetoclax-resistant cells were lysed, and the lysates were processed according to the manufacturer’s protocol and also described previously [5,54]. Gene expression data corresponding to seven different datasets were downloaded from the NCBI Gene Expression Omnibus. The expression of some BCL-2 family genes in T-ALL patients was assessed in all the datasets, which also showed bifurcation into ETP and non-ETP groups. Moreover, IC50 data for a variety of BCL-2 family inhibitors impacting various T-ALL cell lines were downloaded from the Genomics of Drug Sensitivity in Cancer (GDSC). Venetoclax-resistant T-ALL cell lines (MOLT-16, ALL-SIL, and LOUCY) were generated from their parental cells via the multistep exposure of cells to increasing concentrations of venetoclax, starting from 10 nM. The concentrations were doubled when the treated cells showed proliferation at an equal rate to the untreated parental cells. Venetoclax concentrations were increased at regular intervals until a 10 µM concentration was reached for MOLT-16 and ALL-SIL and a 5 µM concentration was reached for LOUCY cells. They were then checked for venetoclax resistance. These cells were further grown for two weeks in the absence of venetoclax. All the cells were retested for drug resistance before any further studies. Gene expression data of venetoclax-resistant and venetoclax-sensitive T-ALL cell lines were used to run Gene Set Enrichment Analysis (GSEA) using the GSEA 4.0.2 software (Broad Institute, Cambridge, MA, USA) with the Molecular Signatures database MSigDB to identify pathways enriched in venetoclax-resistant cells. Statistical analysis was performed using the GraphPad Prism 5.0 (La Jolla, CA, USA) software, where data were expressed as mean ± SE. Unpaired Student’s t-test and one-way ANOVA with Bonferroni’s post-test were used where applicable. p ≤ 0.05 was considered significant.

PMC10003525

Jianmei Wang,Xin Li,Wuqie Qubi,Yanyan Li,Yong Wang,Youli Wang,Yaqiu Lin

The Important Role of m6A-Modified circRNAs in the Differentiation of Intramuscular Adipocytes in Goats Based on MeRIP Sequencing Analysis

02-03-2023

MeRIP-seq (m6A-seq),intramuscular adipocyte,goat,m6A-circRNAs

Intramuscular fat contributes to the improvement of goat meat quality. N6-Methyladenosine (m6A)-modified circular RNAs play important roles in adipocyte differentiation and metabolism. However, the mechanisms by which m6A modifies circRNA before and after differentiation of goat intramuscular adipocytes remain poorly understood. Here, we performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) and circRNA sequencing (circRNA-seq) to determine the distinctions in m6A-methylated circRNAs during goat adipocyte differentiation. The profile of m6A-circRNA showed a total of 427 m6A peaks within 403 circRNAs in the intramuscular preadipocytes group, and 428 peaks within 401 circRNAs in the mature adipocytes group. Compared with the intramuscular preadipocytes group, 75 peaks within 75 circRNAs were significantly different in the mature adipocytes group. Furthermore, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of intramuscular preadipocytes and mature adipocytes showed that the differentially m6A-modified circRNAs were enriched in the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption, lysine degradation, etc. m6A-circRNA–miRNA–mRNA interaction networks predicted the potential m6A-circRNA regulation mechanism in different goat adipocytes. Our results indicate that there is a complicated regulatory relationship between the 12 upregulated and 7 downregulated m6A-circRNAs through 14 and 11 miRNA mediated pathways, respectively. In addition, co-analysis revealed a positive association between m6A abundance and levels of circRNA expression, such as expression levels of circRNA_0873 and circRNA_1161, which showed that m6A may play a vital role in modulating circRNA expression during goat adipocyte differentiation. These results would provide novel information for elucidating the biological functions and regulatory characteristics of m6A-circRNAs in intramuscular adipocyte differentiation and could be helpful for further molecular breeding to improve meat quality in goats.

The Important Role of m6A-Modified circRNAs in the Differentiation of Intramuscular Adipocytes in Goats Based on MeRIP Sequencing Analysis Intramuscular fat contributes to the improvement of goat meat quality. N6-Methyladenosine (m6A)-modified circular RNAs play important roles in adipocyte differentiation and metabolism. However, the mechanisms by which m6A modifies circRNA before and after differentiation of goat intramuscular adipocytes remain poorly understood. Here, we performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) and circRNA sequencing (circRNA-seq) to determine the distinctions in m6A-methylated circRNAs during goat adipocyte differentiation. The profile of m6A-circRNA showed a total of 427 m6A peaks within 403 circRNAs in the intramuscular preadipocytes group, and 428 peaks within 401 circRNAs in the mature adipocytes group. Compared with the intramuscular preadipocytes group, 75 peaks within 75 circRNAs were significantly different in the mature adipocytes group. Furthermore, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of intramuscular preadipocytes and mature adipocytes showed that the differentially m6A-modified circRNAs were enriched in the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption, lysine degradation, etc. m6A-circRNA–miRNA–mRNA interaction networks predicted the potential m6A-circRNA regulation mechanism in different goat adipocytes. Our results indicate that there is a complicated regulatory relationship between the 12 upregulated and 7 downregulated m6A-circRNAs through 14 and 11 miRNA mediated pathways, respectively. In addition, co-analysis revealed a positive association between m6A abundance and levels of circRNA expression, such as expression levels of circRNA_0873 and circRNA_1161, which showed that m6A may play a vital role in modulating circRNA expression during goat adipocyte differentiation. These results would provide novel information for elucidating the biological functions and regulatory characteristics of m6A-circRNAs in intramuscular adipocyte differentiation and could be helpful for further molecular breeding to improve meat quality in goats. Goat is one of the most widely consumed meats in the world. Compared with beef or pork, goat meat is an important source of high-quality protein, healthy fats, low-calorie intramuscular fats and saturated fats [1], and plays a crucial role in human nutrition. Meanwhile, studies have reported that increased intramuscular fat (IMF) content can improve meat quality significantly in pigs [2]. Therefore, IMF, as a main form of fat deposition, is an important factor affecting meat quality traits, such as its tenderness, juiciness and taste, making it an economically important factor in goat breeding. For meat, the content of IMF is an important trait influencing meat quality, and the differentiation of preadipocytes is a key factor affecting IMF deposition [3,4]. Thus, there are intensive efforts for exploring the molecular mechanisms underlying IMF deposition, which is of great significance for improving the quality of goat meat. In recent years, increasing evidence has suggested a potential role for non-coding RNAs (ncRNAs) in IMF deposition at the post-transcriptional level [5]. Circular RNAs (circRNAs), a novel class of endogenous ncRNAs that form covalently closed-loop structures and lack a 5′ cap or 3′ poly-A tail [6], have been widely detected in eukaryotes [7]. Previous studies have reported that circRNAs can participate in various physiopathologic processes by mediating protein–RNA interactions [8,9], such as miRNA or protein sponges [10], or modulating protein translation [11], mostly by acting as competing endogenous RNA (ceRNA) to relieve suppression. With the continuous exploration of its diverse functions, circRNAs have been shown to regulate various biological processes extensively, including fat deposition. However, studies on how circRNAs are regulated before exerting specific biological functions are still limited. m6A is a common epitranscriptomic modification of RNA, which has been found to affect the metabolism of messenger RNAs (mRNAs), including splicing, export, translation, and decay, and plays vital roles in the functions of various ncRNAs, such as long noncoding RNAs (lncRNAs), microRNAs, circRNAs, small nuclear RNAs (snRNAs), and ribosomal RNAs (rRNAs) [12,13]. Interestingly, circRNA can be regulated by m6A modification, showing a different m6A pattern from that of mRNA [14]. Recent studies have shown that m6A-modified circRNAs have been associated with diseases [15,16]. Meanwhile, Hui et al. [17] believed that m6A-modified circRNAs were involved in secondary hair follicle (SHF) development and cashmere growth in goats. Unfortunately, there are currently no reports on circRNA m6A modification in the intramuscular adipocyte differentiation of meat goats. Therefore, to further identify the potential function of m6A modification in regulating circRNA, our objective was to explore the regulatory differences in m6A methylation that mediate circRNA translation in the intramuscular adipocytes of meat goats before and after differentiation using MeRIP-seq (m6A-seq) sequencing technology. The findings provide new knowledge to understand the regulatory mechanisms of adipocyte differentiation and fat deposition in meat goats. In order to examine the fat deposition and lipid droplet morphology in the cultured intramuscular adipocytes, we performed Oil Red O and BODIPY staining. After 3 days of induction, lipid droplets could be observed with Oil Red O and BODIPY staining (nuclei were counterstained with DAPI) (Figure 1), which could indicate that intramuscular preadipocytes (IMPA) and adipocytes (IMA) models were successfully established. To investigate the circRNA profile in goat intramuscular adipocytes before and after differentiation, purified cellular RNA was subjected to circRNA-seq (m6A-seq input library) and MeRIP-seq. The sequencing raw reads were generated from the IMPA group and the IMA group. With three biological replicates, the circRNA-seq and MeRIP-seq sequencing of 12 libraries generated a total of 289.49 Gb of data, with each library averaging from 12.98 Gb to 14.22 Gb of data. The Q30 results in each library were >93.82%, and the GC percentage was less than 59%, as listed in Table 1. Subsequently, more than 95.30% of the clean reads were perfectly mapped to the goat reference genome (assembly ARS1, https://www.ncbi.nlm.nih.gov/genome/?term=goat (accessed on 11 November 2021)), and 83.78~91.49% uniquely mapped reads were obtained from the total mapped reads from the 12 samples (Table 2). The goat genome and circRNA-seq and MeRIP-seq data information are provided in Figure S1. The experimental strategy is shown in Figure 2. We used circRNA-seq to compare the differences in circRNAs between intramuscular preadipocytes (IMPA) and adipocytes (IMA) in goats. We found that most circRNAs were between 200–700 bp and derived from sense-overlapping RNAs (Figure S2A,B). Moreover, circRNAs were mainly distributed on chromosome 7 (Figure S2C). The MeRIP-seq data for m6A in the IMPA and IMA groups were compared and analyzed; there were 427 m6A methylation peaks within 403 circRNAs in the IMPA group, and 428 peaks within 401 circRNAs in the IMA group. According to the differences and overlaps in m6A-modified circRNA transcripts, 64 methylation peaks and 63 circRNAs were uniquely modified in the IMPA group, and 65 methylation peaks and 61 circRNAs were uniquely modified in the IMA group. In addition, 363 peaks were consistently observed in the two groups, and 340 circRNAs within both groups were modified by m6A (Figure 3A,B). Further analysis was performed to assess the features of m6A-modified circRNAs. The number of m6A methylation peaks in each circRNA was highly similar in the IMPA and IMA groups (Figure 3C). We found that almost 61.94% of methylated circRNAs hold only one m6A peak, and most circRNAs contain one to three m6A peaks, which indicates that m6A modification sites are not unique in circRNAs. Moreover, the length results of m6A-modified circRNAs in each group showed that the length of most m6A-modified circRNAs were less than 2000 bp, and the length characteristics of the two groups were similar (Figure 3D). The sources of m6A-circRNAs were most correlated with sense-overlapping RNAs (Figure 3E). Finally, chromosome distribution also revealed that m6A-methylated circRNA is more likely to be present on chromosome 7 (Figure 3F). Based on a p value < 0.05 and |Log2 (fold change)| > 1.5, 75 m6A methylation peaks within 75 circRNAs were screened out between the IMPA and IMA group. Among them, 44 hypermethylated peaks were within 44 circRNAs (e.g., circRNA_NUCB1), and 31 hypomethylated peaks were within 31 circRNAs (e.g., circRNA_ZMYND8), as seen from Table S1. Data visualization analysis was performed using IGV to show the differential m6A peaks between the IMPA and IMA groups (Figure 4A). The top 10 differentially methylated circRNAs with hypermethylation or hypomethylation in the IMA group compared to the IMPA group are shown in Table 3. Meanwhile, the expression profiling was identified by hierarchical clustering analysis, confirming that undifferentiated and differentiated cells exhibited dramatically differentially expressed methylation circRNAs profiles (Figure 4B). GO and KEGG pathway enrichment analyses for the differentially m6A-modified circRNA source genes were performed (p-value < 0.05). GO annotation of m6A-modified circRNAs illustrated that they were mainly enriched in cytoplasm, nucleus and metal ion binding (Figure 4C). KEGG analysis indicated that they were enriched in the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption and lysine degradation (Figure 4D). In recent years, studies have found that circRNAs are able to regulate the expression of target genes as sponges for miRNAs based on complementary base pairing. By predicting the target miRNA for both the circRNA and mRNA, we constructed a m6A-circRNA–miRNA–mRNA ceRNA interaction network. In this study, according to a max-score > 150 and max-energy < −30, a total of 12 hypermethylated circRNAs, 14 miRNAs and 55 mRNAs (Figure 5A), and 7 hypomethylated circRNAs, 11 miRNAs, and 22 mRNAs were identified in IMA and IMPA groups (Figure 5B). These associations of m6A-circRNA–miRNA–mRNA interactions are shown in detail in Table S2. In the interaction network of the two groups, many fats deposition and lipid metabolism miRNAs were predicted, such as miR-103-5p, miR-423-5p and miR-423-3p. In addition, we also found that m6A-modified circRNAs exhibited several m6A-circRNA –miRNA–mRNA regulatory pathways. For instance, m6A-circRNA _1659 may sponge two miRNAs (miR-33b-3p and miR-18a-3p) to further individually or cooperatively regulate the expression of their target genes through a ceRNA network mechanism (Figure 5B). To further explore the potential function of circRNAs with m6A modification in the IMPA and IMA groups, a conjoint analysis of circRNA-seq and MeRIP-seq was performed. Based on a p value < 0.05 and |Log2 (fold change)| > 1.5, 450 differentially expressed circRNAs were detected in the two groups, including 263 upregulated circRNAs and 187 downregulated circRNAs (Figure 6A). Simultaneously, we constructed a clustered heat map to further explore the potential roles of the circRNAs (Figure 6B). Moreover, GO ontology and KEGG pathway analyses were performed to analyze the differentially expressed circRNAs. The GO analysis of the differentially expressed circRNAs illustrated that the meaningful terms (p < 0.05) may be related to lung development, protein autophosphorylation, striated muscle myosin thick filament, etc. (Figure S3A). The KEGG enrichment showed that the top 10 significantly enriched signaling pathways were enriched based on the significantly differentially expressed circRNAs in these two groups (p < 0.05). These pathways included the MAPK signaling pathway, tight junction, lysine degradation, FoxO signaling pathway, cGMP-PKG signaling pathway, etc. (Figure S3B). Furthermore, the correlation between the differentially m6A-modified circRNAs and the corresponding circRNA expression levels was analyzed by combining MeRIP-seq and circRNA-seq. There are 20 significantly upregulated circRNAs with hypermethylation (2 annotated genes and 18 unannotated genes), 2 downregulated circRNAs with hypomethylation (1 annotated gene and 1 unannotated gene) and 1 upregulated circRNA with hypomethylation that were found in the preadipocyte and adipocyte groups (Figure 6C). To verify the reliability of circRNA-seq results, four candidate circRNAs were randomly selected from the differentially methylated circRNAs obtained from the screening, and UXT was used as an internal reference for qRT-PCR analysis. The results showed that circRNA_PAPD7 and circRNA_LMO7 were significantly upregulated during the differentiation of intramuscular adipose cells. On the other hand, circRNA_SP3 and circRNA_CHD9 were significantly downregulated during the differentiation of intramuscular adipose cells. These results were consistent with the circRNA-seq trend, indicating the credibility of the circRNA-seq results (Figure 7). Fat deposition is a very important economic trait that determines goat production, feed efficiency and meat quality, including flavor and tenderness. Studies have shown that the differentiation of intramuscular lipid deposition is a complex biological process regulated by multiple genes, signal pathways and transcription factors [18,19,20,21]. Thus, elucidation of the molecular mechanism underlying meat quality traits in goats will have both biological and economic consequences. Over the past few years, increasing lines of evidence indicate that m6A modification in circRNA molecules plays significant roles in various cells [22,23,24]. Nevertheless, the potential roles of m6A-modified circRNA in most livestock, and especially in the differentiation of goat intramuscular preadipocytes, has remained largely unclear. To the best of our knowledge, our study is the first to screen for m6A-modified circRNA in goat preadipocytes and adipocytes using MeRIP-seq technology. CircRNAs were generated by back splicing of pre-mRNAs through different pathways. It has been confirmed that the major source of circRNAs is derived from exons and exists in a large number of eukaryotic cells [25,26,27]. Some scholars have shown that circRNAs are generated by contranscription and competition with conventional splicing [28]. However, our results indicated that the characteristics of m6A-modified circRNAs changed before and after differentiation of intramuscular adipocytes. Most of the differential m6A-modified circRNAs are longer and come from sense-overlapping regions, which means that these differential and long m6A-modified circRNAs derived from sense-overlapping regions play a more important function, providing new insights into the regulatory mechanism of m6A-modified circRNAs of different adipocytes. In the present study, approximately 75 differentially m6A-modified circRNAs were identified before and after the differentiation of goat intramuscular adipocytes. GO subcategory analysis revealed that they were mainly enriched in the cytoplasm, nucleus and metal ion binding. The KEGG enrichment analysis based on the differentially m6A-modified circRNAs demonstrated that the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption and lysine degradation play a vital role in the adipose differentiation. Maimaitiyiming et al. [29] suggested that increased PKG signaling stimulates brown adipocyte differentiation, promotes healthy expansion and browning of white adipose tissue, and stimulates white adipose tissue lipolysis. Endocrine and other factor-regulated calcium reabsorption is related to the immune system, and it has a critical role in adipose differentiation [30]. In addition, it has been shown that the dietary lysine to energy ratio mainly determines the rate of protein and fat deposition [31]. Yang et al. [32] demonstrated that lysine degradation plays a promoting role in the process of fat differentiation, which is conducive to fat deposition. These are consistent with our results. Therefore, we conclude that the different m6A-modified circRNAs might be involved in the differentiation of intramuscular preadipocytes. In recent years, a growing number of studies have found that circRNA can be used as a molecular sponge to interact with miRNA to regulate mRNA [33,34]. By integrating the data from the analyses of circRNAs, miRNAs, and mRNAs, hub ceRNAs networks were constructed for goat adipogenic differentiation. In our ceRNA network, we found that 11 downstream genes in the ceRNA pathways were strongly related to candidate m6A-modified circRNAs in the present study, suggesting that these circRNAs might play functional roles during adipogenesis. It is worth noting that fibronectin type III domain-containing protein 3B (FNDC3B) regulates white fat browning and adipogenesis [35]. Moreover, TTN (Titin) has been related to changes in intramuscular fat deposition, possibly by exerting effects on adipocyte lineage cells or on the milieux surrounding them [36]. In our study, we found that miR-103-5p was able to regulate TTN, ZNF536 and WDR76 in three ceRNA networks, and multiple circRNAs had binding sites with miR-2305. Thus, we speculated that circRNA_1944 (circFNDC3B) and circRNA_0582 (circTTN) potentially regulate goat adipogenesis. However, in-depth studies on the functions of goat circFNDC3B, circTTN, circRNA_0582 (circZNF536) and circRNA_0582 (circWDR76) on adipogenic differentiation are essential. Previous research reported that LAMA5, HDAC11, CCND2, EBF3 were associated with adipogenesis and fat deposition [37,38,39]. We found that circRNA_1689 might influence adipogenic differentiation by regulating downstream genes (LAMA5 and EBF3) through two miRNAs (miR-874-3p and miR-874-3p), and that circRNA_0873 might influence adipogenic differentiation by regulating downstream genes (HDAC11 and CCND2) through one miRNA (miR-1343). Based on the above results, we believe that the m6A-circRNAs, as a “molecular sponge” of these miRNAs, may play essential roles in establishing an optimal expression balance of their target genes during goat adipocyte differentiation, in which m6A modifications may be required, as the m6A-circRNA plays an important role in regulating the proliferation and differentiation of adipocytes and myocytes. To further reveal the relationship between circRNA and m6A modification, we performed an analysis of circRNA-seq. We found a total of 450 circRNAs with expression differences. In the conjoint analysis of MeRIP-seq, we found that a total of 23 circRNAs showed a significant association between expression and m6A modification; of these, 3 were annotated genes and 20 were unannotated genes. Earlier studies have indicated that m6A modification is closely related to circRNA expression [40]. For instance, Zhang et al. suggested that circRNA accumulation is associated with enhanced splicing at the m6A site and m6A modification may interfere with sperm motility by influencing circRNA expression levels [41]. In the present study, we showed that the expression of two m6A-circRNAs, including circRNA_0873 (circRNA_SLC8A3) and circRNA_1161 (circRNA_DEPTOR), were dramatically upregulated in adipocytes as compared to preadipocytes, and the majority of m6A-circRNAs were expressed at a medium level with a positive relationship between circRNA expression and m6A methylation modification. Thus, it can be suggested that these two m6A-circRNAs (circRNA_0873 and circRNA_1161) may be implicated in the physiological process of goat adipocyte differentiation by constituting coordinated regulatory pairs. In this process, the m6A modifications within the circRNAs might play an important role in promoting the differentiation of goat adipocytes. Additionally, the four circRNAs in the comparison of IMF before and after differentiation were verified by qPCR, and the results were basically consistent with those of RNA-seq. This shows that our RNA-seq discovery is reliable. Based on sequencing data, we considered that these circRNAs play a role in the intramuscular adipocytes of goats before and after differentiation. Although these newly identified circRNAs have not been reported in studies of intramuscular adipocyte differentiation, they can provide some preliminary data for further study. Goat intramuscular preadipocytes were collected from the longissimus dorsal muscle of 7-day-old Jianzhou Daer goats (n = 3) (Sichuan Jianyang Dageda Animal Husbandry Co., Ltd., Sichuan, China). The intramuscular preadipocytes were isolated and cultured as described by Xu et al. [42]. DMEM/F12 (Hyclone, Logan, UT, USA) containing 10% FBS (Hyclone, Logan, UT, USA) and 50 μmol·L−1 oleic acid (Sigma, St. Louis, MO, USA) induced differentiation of goat intramuscular adipocytes, and cells were collected at 0 and 3 days [4,43]. The Oil Red O staining and BODIPY staining were used to distinguish mature adipocytes from preadipocytes during the process of culture. The Oil Red signal was quantified by measuring the absorbance at 490 nm (OD 490) as a semi-quantitative assessment method to determine the extent of differentiation. The fluorescence intensity of the BODIPY signal (arbitrary units, in %) was analyzed using the ImageJ tool (NIH, Bethesda, MD, USA). Total RNA from 6 samples was extracted. We have generally utilized 100 ng of RNA for library construction for MeRIP-circRNA sequencing. Briefly, the mRNA with polyA in the total RNA was enriched by Oligo-dT magnetic beads. The intact mRNA was then fragmented using an ultrasound machine. The segmented RNA was divided into two parts. One part was added to an m6A-capturing antibody to enrich the mRNA fragments containing m6A methylation (MeRIP-seq), and the other part was used as an Input to directly construct a conventional transcriptome sequencing library (circRNA-seq). The m6A antibody was enriched by magnetic beads, and the mRNA fragments containing m6A were recovered. The conventional sequencing library was constructed according to the transcriptome library construction process. Illumina Hiseq X Ten was used for high-throughput sequencing of the library. After paired-end sequencing, raw data were first filtered according to Q30 and GC content; fastp software (v0.20.0) was used to obtain high-quality reads. Hisat2 software (v2.1.0) was used to align high-quality reads to the goat reference genome, CIRI2 software (v2) was used for circRNA detection and identification, and the MeTDiff software was used for methylation peak calling and differential peak identification. The circBase database and Circ2Traits were used to annotate the identified circRNA. Then, DESeq2 software (v1.14.1) was used for data standardization and differentially expressed circRNA screening (log2FC ≥ 1.5, p-value ≤ 0.05). The DAVID database was used to conduct GO enrichment analysis [44]. KOBAS software (http://kobas.cbi.pku.edu.cn (accessed on 14 February 2023)) [45] was used to test the statistical enrichment of differentially expressed circRNA source genes in KEGG pathways. A p value < 0.05 was considered significant. The R language (v1.42.0) and related packages were used to visualize the results. The m6A-circRNAs/miRNA interactions were predicted using miRanda (http://www.microrna.org/ (accessed on 16 September 2022)) [46]. miRanda was used to predict the downstream mRNA targets of the predicted miRNA. The R language (v1.42.0) and related packages were used to visualize the results. Additionally, statistical analysis was conducted with the SPSS 17.0 program (SPSS Inc., Chicago, IL, USA). Results are shown as the mean ± SEM and the data are representative of three biological and two technical replicates. * p < 0.05, ** p < 0.01. Primers were designed using Primer-BLAST on the NCBI website (Table 4). First-strand cDNA was synthesized using a reverse transcription system (Takara, Shiga, Japan) according to the manufacturer’s instructions, and the cDNA was used for quantitative real-time PCR, which was carried out with the SYBR Prime Script RT-PCR Kit (Takara, Shiga, Japan). UXT was used as the housekeeping gene for normalization of the gene expressions in all samples [47]. Quantification of selected gene expression was performed using the comparative threshold cycle (2−ΔΔCT) method [48]. The experiment was repeated three times. In conclusion, our present study generated transcriptome-wide maps of the m6A profiles and distribution patterns of goat intramuscular adipocytes before and after differentiation based on the MeRIP-seq technique. We found that the different m6A-circRNAs might be involved in the differentiation of intramuscular preadipocytes. Meanwhile, the m6A-circRNAs work as molecular sponges for miRNAs and may play essential roles in regulating miRNA target gene expression during goat adipocyte differentiation. Additionally, this study also explores the correlation between m6A methylation and the level of circRNA expression, indicating the m6A-circRNAs may act through a potential regulatory mechanism in promoting the differentiation of goat adipocytes.

PMC10003534

Elsa Wilma Böhm,Bernhard Stoffelns,Adrian Gericke

β-Adrenoreceptors as Therapeutic Targets for Ocular Tumors and Other Eye Diseases—Historical Aspects and Nowadays Understanding

28-02-2023

β-adrenoreceptors,catecholamines,glaucoma,ocular hemangioma,uveal melanoma

β-adrenoreceptors (ARs) are members of the superfamily of G-protein-coupled receptors (GPCRs), and are activated by catecholamines, such as epinephrine and norepinephrine. Three subtypes of β-ARs (β1, β2, and β3) have been identified with different distributions among ocular tissues. Importantly, β-ARs are an established target in the treatment of glaucoma. Moreover, β-adrenergic signaling has been associated with the development and progression of various tumor types. Hence, β-ARs are a potential therapeutic target for ocular neoplasms, such as ocular hemangioma and uveal melanoma. This review aims to discuss the expression and function of individual β-AR subtypes in ocular structures, as well as their role in the treatment of ocular diseases, including ocular tumors.

β-Adrenoreceptors as Therapeutic Targets for Ocular Tumors and Other Eye Diseases—Historical Aspects and Nowadays Understanding β-adrenoreceptors (ARs) are members of the superfamily of G-protein-coupled receptors (GPCRs), and are activated by catecholamines, such as epinephrine and norepinephrine. Three subtypes of β-ARs (β1, β2, and β3) have been identified with different distributions among ocular tissues. Importantly, β-ARs are an established target in the treatment of glaucoma. Moreover, β-adrenergic signaling has been associated with the development and progression of various tumor types. Hence, β-ARs are a potential therapeutic target for ocular neoplasms, such as ocular hemangioma and uveal melanoma. This review aims to discuss the expression and function of individual β-AR subtypes in ocular structures, as well as their role in the treatment of ocular diseases, including ocular tumors. Catecholamines, such as adrenaline and noradrenaline, act via α- and β-adrenoceptors (ARs) to regulate central physiological functions, such as blood pressure, heart rate, and contractility, as well as metabolic and central nervous system functions [1]. ARs are members of the superfamily of guanosine triphosphate-binding protein (G-protein)-coupled receptors (GPCRs) [1]. Based on their pharmacological properties, amino acid sequences, and signaling mechanisms, ARs can be divided into three subfamilies: the α1-, α2-, and the β-AR subfamily [2,3]. The purpose of this review was to give an overview on the expression and function of β-Ars in ocular structures and tumors including those of the periocular region. Moreover, treatment approaches for ocular diseases and tumors targeting β-ARs are presented. The literature was identified via a search on PubMed. The PubMed database search included the following keywords: (“β-adrenoreceptors” OR “β-adrenoreceptor subtypes” OR “β1-adrenoreceptors” OR “β2-adrenoreceptors” OR “β3-adrenoreceptors” OR “β-adrenoreceptor antagonist” OR “β-blocker” OR “catecholamines”), AND (“cornea” OR “conjunctiva” OR “lacrimal gland” OR “trabecular meshwork” OR “uvea” OR “retina” OR “ocular tumors” OR “ocular hemangioma” OR “periocular infantile hemangioma” OR “choroidal hemangioma” OR “retinal hemangioblastoma” OR “conjunctival hemangioma” OR “uveal melanoma”). The research was performed from 13 November 2022 to 23 January 2023 with the following inclusion criteria: all studies, written in English, and published after 1948. Studies reporting on the role of β-adrenoceptors in non-(peri)ocular tissues were excluded. The reference list of all selected articles was reviewed for further identification of potentially relevant studies. The theory on the existence of specific receptors binding drugs or intracellular molecules for regulation of cellular mechanisms was first introduced by John Newport Langley in the early 1900s [4]. The hypothesis, that these receptors are specific and selective, was proposed by Paul Ehrlich at the same time [5]. The first description of α- and β-adrenoceptors activated by epinephrine was published in 1948 by Raymond P. Ahlquist [1]. In 1958, the first β-blocker was synthesized by Eli Lilly Laboratories [4]. A few years later, Sir James W. Black introduced the first clinical application of β-blockers treating angina pectoris with propranolol, receiving the Nobel Prize for this crucial success in clinical medicine [4]. Over time, several clinical trials, especially in cardiovascular research, were performed, and β-Ars and their antagonists became a central tool in the treatment of cardiovascular diseases, such as angina pectoris, hypertension, arrhythmias, and post myocardial infarct [4]. Binding of an agonist to a β-adrenoceptor causes a dissociation of Gα-GTP and Gβγ subunits with consequent activation of adenylate cyclase, and production of the second messenger cyclic adenosine monophosphate (cAMP). This leads to activation of downstream effectors, such as cAMP-dependent protein kinase (PKA) and cAMP-dependent phosphorylation of gated ion channels [6,7]. Among the β-AR family, three different subtypes (β1-, β2-, and β3-ARs) can be distinguished based on pharmacological studies [8]. The previously postulated β4-AR turned out to be a specific affinity state of the β1-AR [9]. The β1-AR has high affinity to adrenaline and noradrenaline, and is expressed predominantly in the heart, brain, and adipose tissue. A lower affinity to noradrenaline is found in the β2-AR subtype, which is more involved in relaxation of vascular and other smooth muscle cells, and further metabolic mechanisms of catecholamines [10]. The β3-AR is abundantly expressed in adipose tissue, but is also expressed in the eye [11,12]. β-ARs are found in the central and peripheral nervous systems, and are essential for a variety of functions, such as regulation of heart rate and contractility, vasorelaxation, bronchodilation, and neurotransmitter release [13]. In this review, we focus on the expression and function of β-ARs in ocular structures. Furthermore, we describe the role of these receptors in ocular diseases, including ocular tumors, such as hemangioma and uveal melanoma. The role of β-blockers, such as propranolol, as possible therapeutic tools will also be discussed. A scheme of β-adrenergic the signaling pathways is shown in Figure 1. Adrenergic nerve fibers originating from the superior cervical ganglion innervate the surface of the cornea. In adult human corneas, these nerve fibers could be identified by sodium-potassium-glyoxylic acid-induced fluorescence [14,15]. Both α-ARs and β-ARs have been detected in corneas, and the mediating neurotransmitter, norepinephrine, has been identified in the corneal epithelium [15,16,17,18,19]. Furthermore, high levels of β2-ARs have been detected in corneal epithelial cells [20,21,22]. There is an ongoing discussion on the role of β2-ARs in corneal re-epithelialization [23,24,25]. Some researchers suggested that, through antagonism of β2-ARs, and consequent increase in extracellular signal-regulated kinase (ERK) phosphorylation, corneal epithelial cell migration and corneal wound healing was enhanced [22,26]. Recently, a study was published revealing attenuated corneal wound healing after treatment with β2-AR antagonists by modulating the expression of Ki67, and phosphorylation of ERK1/2 in the limbal and regenerated corneal epithelium [27]. These contrary results point toward a role of the β2-AR in homeostasis of the corneal epithelium. However, the definite role of β-AR signaling in corneal wound healing remains to be examined in further studies. Conjunctival functions, such as secretion of mucous substances from goblet cells, and mobilization and attraction of conjunctival eosinophils, seem to be controlled by sympathetic nerves. These functions might be involved in the pathophysiology of common conjunctival diseases, such as allergic conjunctivitis and dry eye disease [28,29,30,31]. In cell culture experiments with primary human conjunctival epithelial cells, the presence of β2-ARs was also demonstrated [32]. Using fluorescence microscopy, β1- and β2-ARs could be detected in conjunctival goblet cells in developing rats [33]. The β3-AR subtype was only seen on epithelial and goblet cells of the human conjunctiva, but not in conjunctival cells of the mouse [28]. In the human conjunctival epithelial cell line, IOBA-NHC, all individual AR subtypes could be detected by western blot analysis. In the same study, analysis by flow cytometry revealed constitutive expression of β1- and β3-ARs on cell membranes and in intracellular compartments. The β2-AR was detected only intracellularly under normal culturing conditions. Furthermore, immunofluorescence microscopy was performed, and β1- and β2-AR subtypes, but not β3-ARs, were detected in IOBA-NHC cells [34]. In biopsies of the human conjunctiva, all β-AR subtypes could be detected [34]. Notably, β-AR subtypes seem to play a role in the pathogenesis of certain conjunctival diseases. For example, irregular expression of the β1-AR was observed in all epithelial cell layers of human conjunctival biopsy specimens of patients with vernal keratoconjunctivits, suggesting an involvement of the autonomic nervous system in pathogenesis of the disease [35]. Furthermore, β2-AR agonists, such as salbutamol and terbutaline, reduced microvascular permeability, and exerted anti-inflammatory effects in allergic conjunctivitis [29,36]. These findings reveal that β-ARs might be a promising therapeutic target for inflammatory ocular surface diseases, such as allergic conjunctivitis. The lacrimal gland is composed of acinar cells, myoepithelial cells, and ductal cells [37]. With pharmacological tools, detection of β-ARs in the lacrimal gland of various species was possible [38]. By using RT-PCR, mRNA for all AR subtypes except for α2C-, β1-, and β3-ARs was detected in acinar cells of the rat lacrimal gland [39]. However, protein secretion in the lacrimal gland of rats and mice was reported to be regulated by stimulation of β-ARs [40,41,42,43]. Moreover, in rabbits, contribution of β1- and β2-ARs to secretion in the lacrimal gland was suggested [42,44]. Nevertheless, the physiological and pathophysiological roles of ARs in accessory lacrimal glands need to be discussed. Immunohistochemical studies in human specimens indicated that β1-ARs were the predominant AR subtype in the glands of Wolfring [45]. In epithelial cells of the human meibomian gland, activation of β2-ARs was suggested to stimulate lipid synthesis [46]. These findings indicate that β-ARs are participating in regulation of tear secretion. They may also play a crucial role in the pathophysiology of dry eye disease, including Sjögren’s syndrome, by an altered neuronal control of lacrimal gland fluid regulation [37,39]. Based on these findings, activation of adrenergic pathways may be a potential therapeutic approach to treat dry eye disease. In sections of the trabecular meshwork, predominant expression of β2-ARs has been shown [47]. Moreover, high expression and functional relevance of β2-ARs was detected in pharmacological and radioligand binding studies in cultured human trabecular cells and in trabecular meshwork from human eyes [48,49,50]. An augmentation of outflow facility through the trabecular meshwork mediated via ß-AR signaling with a particular role of the β2-AR after adrenaline and noradrenaline stimulation was demonstrated in studies on monkey and human eyes [51]. Further functional studies on isolated trabecular meshwork strips revealed that β-adrenergic agonist stimulation induced relaxation, whereas contraction was induced by α-adrenergic agonists [52]. In summary, there is some evidence that activation of β2-ARs increases outflow facility in the trabecular meshwork. The uvea consists of three parts: the iris, the ciliary body, and the choroid. In the human ciliary body, abundant expression of β1- and β2-ARs was reported [53,54,55,56,57]. Furthermore, autoradiographic and ligand binding studies in rabbit eyes revealed expression of β-ARs in the ciliary process epithelium, indicating that they may participate in aqueous humor formation [58,59]. β2-ARs coupled to adenylate cyclase were detected in the ciliary process epithelium in various species, including humans [60,61,62]. Adrenergic agonists, such as adrenaline, are suggested to induce a desensitization of the β-AR-adenylate cyclase complex, which may be a reason for the delayed intraocular pressure decrease after topical application of adrenergic agonists, and for the paradoxical fact that both β-AR agonists and antagonists lower intraocular pressure [63]. Vasoconstriction of the uveal vasculature with consequent decrease in aqueous humor production could be another possible mechanism of the intraocular pressure-lowering effect of β-AR blockers [64]. Due to potent binding of the non-subtype-selective β-AR antagonist, timolol, and some β2-AR antagonists to β-ARs on ciliary processes in radioligand binding studies, and potent lowering of intraocular pressure in various species, β2-ARs are a pharmacological target in glaucoma treatment [65,66,67,68]. Abundant expression of β-ARs has also been detected in the choroid [58]. In humans, the presence of β-ARs in the choroid was found by showing an increased choroidal vascular tone following systemic administration of the nonselective β-AR blocker, timolol [69]. Sympathetic nerves and signaling via β-ARs may be important for maintaining normal choroidal vascular architecture [70]. Experiments with the specific β3-AR agonist, BRL37344, revealed that the β3-AR may be involved in choroidal endothelial cell invasion and elongation [12]. Moreover, the β2-AR may participate in the regulatory process of VEGF and IL-6 expression in cells of the choroidal endothelium and other cells, indicating that blockade of these receptors may attenuate formation of choroidal neovascularization [71,72]. The retina is a complex neuronal multilayer processing visual information to the brain [73]. Six major types of neuronal cells are found in the neuronal lamination of the retina: retinal ganglion cells (RGCs), amacrine cells, bipolar cells, horizontal cells, and the cone and rod photoreceptors [74]. These retinal neurons use same types of neurotransmitters (noradrenaline, dopamine, and acetylcholine) as those of the central nervous system [75]. Due to the complex neuronal structure of the retina, it is vulnerable to various detrimental factors, such as ischemia and oxidative stress, that may lead to deterioration of retinal cell function, and consequently cause retinal pathologies [76]. The supply of the retina with oxygen and other nutrients is ensured by two different vascular beds, both originating from the ophthalmic artery, the retinal circulation, and the choroidal circulation [77]. Choroidal blood vessels are innervated and modulated by autonomic nerve fibers. In contrast, such nerve fiber terminals were not found in or on the wall of human retinal blood vessels [78]. Vascular tone of retinal blood vessels is controlled by local chemical factors, including oxygen (O2), carbon dioxide (CO2), nitric oxide (NO), and hydrogen sulfide (H2S) [79,80,81]. Although there is no evidence for sympathetic nerve fibers in the retina, catecholamines including noradrenaline, adrenaline, and dopamine have been detected in retinal tissue [82]. A potential source of noradrenaline in the mammalian retina could be sympathetic nerve terminals located in the choroid, reaching ARs of the retina by paracrine diffusion [83,84]. In support of this concept, decreased retinal noradrenaline concentrations have been reported after removal of the superior cervical ganglion, that provides sympathetic input to the choroid [82]. The predominant catecholamine in the retina is dopamine, synthetized and released by dopaminergic amacrine (DA) cells [85,86]. A potential source of noradrenaline could be metabolization of dopamine to noradrenaline in retinal tissue [87]. Apart from noradrenaline, dopamine may also activate α1-, α2-, and β-ARs [88]. It is important to recognize that members of all three adrenoceptor subfamilies, α1-, α2-, and β-ARs, have been detected in retinal tissue, including endothelial cells of retinal blood vessels [89,90,91,92,93,94]. Sympathetic neurotransmission presents a possible mechanism to regulate expression of inducible nitric oxide synthase, angiogenic growth factors, and the number of pericytes in the retina, as described below [95,96,97]. β-ARs were detected in the outer nuclear layer, the outer plexiform layer, the inner nuclear layer, and the inner plexiform layer of the rat retina [98]. In the human retina, β-ARs were visualized in vitro by autoradiography [21]. In bovine retinal vessels and in the neural retina, β1-AR and β2-AR binding sites have been detected [99]. Functional β3-ARs have also been found in rat retinal blood vessels [100]. Immunohistochemical studies revealed localization of β3-ARs in the inner capillary plexus of the mouse mid-peripheral retina [101,102]. Intriguingly, pharmacological activation of β3-ARs induced cell migration and proliferation of retinal vascular endothelial cells [93]. Furthermore, expression of β1- and β3-ARs has been reported in human retinal endothelial cells [103]. Due to the broad distribution of β-ARs in retinal blood vessels and in the neural retina, β-ARs are believed to play an important role in the regulation of vascular and neuronal functions of the retina. During stress conditions, such as hypoxia, catecholaminergic responses from the cardiovascular system are enhanced leading to activation of β-ARs [104]. Under hypoxic conditions, increased levels of noradrenaline by approximately 90% were detected in the mouse retina compared to normoxic conditions [102]. Activation of β-ARs induces an upregulation of hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF). These factors maintain a crucial role in the formation of pathogenic blood vessels in various retinal diseases, such as ROP and diabetic retinopathy [102,105,106]. By application of propranolol, a non-subtype-selective β-AR antagonist, this hypoxia-mediated increase in VEGF expression, which is involved in neovascularization of the retina, could be prevented [84]. Likewise, in a mouse model of oxygen-induced retinopathy (OIR), subcutaneous administration of propranolol resulted in a decrease in VEGF and HIF-1α levels, indicating that blockade of β1- and β2-ARs is protective against retinal angiogenesis, and can enhance blood-retinal barrier function [101]. Another study that used a mouse model of OIR also revealed reduced retinal VEGF receptor-2 expression, and less vascular abnormalities in the superficial plexus of the retina after deletion of the β1- and β2-ARs [107]. Selective blockade of β2-AR by ICI 118,551 in a mouse OIR model also resulted in decreased retinal levels of proangiogenic factors, and reduced pathogenic neovascularization, suggesting that β2-AR blockade may be a potential way to block retinal angiogenesis [108]. However, there are also contradictory findings that need to be mentioned. While most studies reported inhibitory effects of pharmacological β-AR blockade on VEGF levels, some other studies observed a blockade of VEGF formation by exposure to β-AR agonists [84,101,102,104,105,106]. For example, decreased VEGF levels in the diabetic rat retina were reported after administration of a novel β-AR agonist, compound 49b [109]. Modulation of eNOS and PKC pathways with an increase in insulin-like growth factor binding protein 3 (IGFBP-3) may be the reason for reduced VEGF levels in the diabetic retina [109]. These contradictory findings lead to the suggestion that the effects may be mediated through diverse regulatory mechanisms depending on the retinal disease and the experimental setting. Previous studies reported that the nonselective β-ARs agonist, isoproterenol, can cause agonist-induced β2-AR desensitization that downregulates expression of β2-ARs in the retina, which in turn exerts an inhibitory effect on VEGF expression in OIR [102]. β3-ARs were shown to have an impact on neovascularization processes of various retinal vascular diseases [101]. For example, in an OIR mouse model with dense β3-AR immunoreactivity in engorged retinal tufts, upregulation of β3-ARs in response to hypoxia indicated that activation of β3-ARs also plays an important role in pathologic angiogenesis [101]. Furthermore, hypoxia-inducible factor-1α (HIF-1α) could increase the expression of the β3-AR gene in the hypoxic retina, supporting the hypothesis that β3-ARs may participate in the angiogenic response in hypoxia [110]. Due to severe side effects, such as thromboembolism or hyperkalemia, systemic administration of HIF-1α inhibitors is not recommended [111,112]. Downregulation of retinal VEGF release via modulation of the nitric NO signaling pathway could be induced by the β3-AR antagonists, L-748,337, and SR59230A [113]. Furthermore, retinal damage after intravitreal injection of N-methyl-D-aspartate (NMDA) in rats could be prevented by the β3-AR agonist, CL316243 [114]. In addition, β3-ARs, which are not coupled to a G protein receptor kinase are resistant to agonist-induced desensitization [115,116]. Therefore, the β3-AR may represent an attractive therapeutic target for the treatment of ischemic retinal diseases. β-AR stimulation was also shown to increase human and mouse pericyte survival under diabetic conditions [117]. In support of this concept, surgical removal of the right superior cervical ganglion, which supplies the eye with sympathetic nerve fibers, induced a significant decrease in the number of retinal pericytes in a rat model [97]. These findings indicate that β-AR signaling is important for pericyte survival. Moreover, β-ARs are involved in regulation of inducible nitric oxide synthase (iNOS) expression [118]. Activation of β-ARs reduced levels of iNOS and other inflammatory molecules, such as interleukin (IL)-1β, tumor necrosis factor-α (TNF-α), and prostaglandin E2 (PGE2) in human retinal endothelial cells, and rat Müller cells in an in vitro model of hyperglycemia [95]. In line with these findings, iNOS expression in human retinal endothelial cells grown in high glucose medium could be reduced by the partial β1-AR agonist xamoterol [95]. An overview on the expression and function of β-ARs in ocular structures is presented in Table 1. Infantile hemangioma is a benign vascular tumor, which typically occurs as a cutaneous lesion in early childhood with a high incidence of approximately 4–5% of infants [119,120]. It is characterized by nonlinear growth during its proliferative stage, reaching its final size by the age of about 3 months [121]. Periocular infantile hemangioma can present as a small isolated lesion or as a large mass with visual impairment through ocular occlusion [120]. A major part of the tumors is characterized by a predictable course with spontaneous regression. However, persisting lesions can lead to serious ocular or systemic complications, such as amblyopia or cardiac failure [120]. There are different growth patterns in infantile hemangioma. Superficial lesions present as red lesions with a flat or rough surface. Deep hemangiomas grow later and longer than superficial hemangiomas, and appear as blue to purple discolorations or changes of thickness of the skin. They can also only cause anatomical distortions without discoloration [120,121]. Infantile hemangioma is frequently located unilaterally at the upper eyelid [122]. Twenty to 40% of large facial segmental hemangiomas are associated with the PHACE (posterior fossa anomalies, arterial, cardiac, eye, and endocrine anomalies) syndrome related to typical malformations, such as hemangioma, posterior fossa abnormalities present at birth, arterial lesions, cardiac anomalies, eye abnormalities, and sternal clefting [123,124]. These clinical manifestations can lead to systemic, cutaneous, and ocular complications. Periocular manifestation of infantile hemangioma can cause severe ocular complications, such as ptosis, strabismus, telangiectasia, ulceration, scarring, or facial disfigurement [120]. Secondary vision loss due to amblyopia occurs in 60% and represents the most common ocular complication in patients with periorbital hemangioma [125]. Systemic complications include airway obstructions or high cardiac output problems [120]. Following clinical examination, imaging techniques such as ultrasonography, color Doppler ultrasonography [126], computer tomography scans, and magnetic resonance imaging and angiography play a central role in the diagnosis of hemangiomas [120,127,128]. The main therapeutic target in the treatment of infantile periocular hemangioma is the prevention of systemic and ocular complications, such as amblyopia. Due to a high spontaneous remission rate, small lesions without risk of clinical complications have to be observed in first line [120]. There are medical and surgical treatment modalities described in infantile hemangiomas. Medical treatment strategies next to beta blockers include systemic or intralesional corticosteroids, imiquimod, vincristine, bleomycin A5, cyclophosphamide, interferon-α, or angiotensin-converting enzyme (ACE) inhibitors, such as captopril [120,129]. Less common modalities are laser therapy or surgery [129]. The therapeutic effect of β-blockers on infantile hemangioma was found by chance, when patients were treated with β-blockers for cardiopulmonary indications, and regression of hemangioma was observed [130]. Since then, several studies on the application of the nonselective β-blocker, propranolol, in infantile hemangioma have been published. Hermans et al. performed a prospective study in 174 patients with complicated hemangioma, and reported treatment success in 99.4%. Treatment success was defined as immediate cessation of growth, softening, fading of the erythema, and rapid induction of regression [131]. With a fixed dose of 2 mg/kg bodyweight oral propranolol, complete regression of hemangioma occurred in 60% of the treated patients. Among the patients, 17.4% showed evidence of rebound growth after termination of therapy, but they responded well to re-treatment [132]. The respective study of Schneider et al. included 207 patients and also found high effectivity of systemic application of propranolol [133]. Potential side effects were arterial hypotension (3.4%), wheezing (9.2%), nocturnal restlessness (22.4%), and cold extremities (36.2%) [131]. Others reported severe hypoglycemia during treatment with propranolol [134]. This side effect was not observed when propranolol was strictly applicated after feeding [133,135]. Furthermore, side effects, such as bronchial hyperreactivity or constipation, have been observed [136]. However, it is reasonable to start therapy with propranolol under severe surveillance. A multicenter retrospective analysis demonstrated superiority of oral propranolol against oral corticosteroids, with respect to clinical and cost efficacy. Furthermore, fewer surgical interventions and fewer adverse effects were found in the propranolol treated group [137]. To minimalize adverse effects, topical application of β-blockers, such as timolol, can also be performed to treat infantile periocular hemangioma. Especially in localized and superficial hemangiomas, successful treatment with topical timolol maleate 0.5% gel has been reported [138,139,140,141,142]. Chambers et al. also demonstrated good results of topical timolol in a retrospective study [143]. Likewise, studies showing good response of deep hemangiomas to topical timolol application have been published [144,145]. The timolol maleate 0.5% solution or gel should be applied twice daily on the surface of the lesion, and therapeutic responses can be seen after 4–8 weeks [120]. On the other hand, a randomized clinical study found limited benefit of topical timolol in lesion resolution when given during the early proliferative stage compared to a placebo treated group [146]. A randomized controlled trial found that combination of systemic and topical β-blockers in the early proliferative stage is significantly more effective than systemic treatment only [147]. There are also few investigations analyzing intralesional β-blocker application. For example, Awadein et al. showed a reduction in hemangioma lesion size, asigmatic error, and degree of ptosis after intralesional propranolol injection. There were no adverse effects reported. The rate of rebound growth was 25%, but with good response to reinjection [148]. Others reported interruption of hemangioma growth without changes in size or color after intralesional propranolol injection [149]. Another study compared intralesional and oral propranolol application, and found comparable results in efficacy and side effects [150]. In summary, β-blockers represent an effective and safe possibility to treat infantile periorbital hemangioma. Choroidal hemangioma is a benign vascular tumor located at the ocular posterior pole. It can be distinguished between circumscribed choroidal hemangioma (CCH) and diffuse choroidal hemangioma. Circumscribed choroidal hemangioma emerge sporadically and are not associated to local or systemic abnormalities. CCHs are solitary, well-demarcated lesions located posterior to the equator [151]. They are mostly detected in the second to fourth decade of life when visual restrictions occur. Diffuse choroidal hemangiomas are usually part of neuro-oculo-cutaneous hemangiomatosis (Sturge-Weber syndrome) and manifest at birth [152]. Visual symptoms occur due to subretinal fluid, cystoid macular edema, changes in retinal pigment epithelium, subretinal fibrosis, retinoschisis, or exsudative retinal detachment [151]. Common symptoms are decreased visual acuity (81%), visual field defects (7%), metamorphopsia (3%), floaters (2%), progressive hypermetropia (1%), photopsia (1%), pain (1%), and no symptoms (6%) [153]. At the ocular fundus, a circumscribed orange-red tumor can be seen, that is found to be unilateral and located most frequently in the superotemporal quadrant close to the macula [154]. Few cases of bilateral CCH have also been reported [155,156,157]. Diagnostic tools next to fundus examination are ultrasound, fluorescent angiography, indocyanin green (ICG) angiography, enhanced-depth imaging (EDI) optical coherence tomography (OCT), and OCT-angiography (OCT-A) [151]. Representative pictures of a patient with circumscribed hemangioma are shown in Figure 2. Treatment of CCH is indicated when clinical symptoms occur. The primary goal of therapeutic strategies is reduction in subretinal fluid and macular edema, which causes a decrease in visual acuity. Reduction in tumor size is only an additional outcome [151]. Therapeutic strategies are laser photocoagulation [158], photodynamic therapy (PDT) [159], transpupillary thermotherapy (TTT) [160], and radiation therapy, such as external beam radiotherapy (EBRT) or episcleral brachytherapy [161,162]. These therapies have often been combined with intravitreal anti-VEGF injections [163,164]. The pathophysiology of choroidal hemangioma Is not fully understood. Choroidal hemangioma is supposed to be a congenital vascular hamartoma that is composed of choroidal vessels. Histological studies revealed that choroidal hemangiomas are nonproliferative tumors with tumor growth by venous congestion rather than cell proliferation [165,166]. In cutaneous capillary hemangioma, activation of endothelial cells and β-ARs are supposed to be involved in the pathogenesis [167,168] However, some studies using nonselective β-blockers as therapeutic strategy in choroidal hemangioma have also been described so far. Sanz-Marco et al. treated a patient with CCH, who was resistant to treatment with laser photocoagulation, by oral administration of propranolol, and reported improvement of visual acuity, and resolved serous macular detachment without complications through systemic or local adverse effects [169]. Likewise, there have been several case reports demonstrating successful treatment of choroidal hemangioma by oral application of propranolol [170,171,172,173,174]. Reported adverse effects are decreased exercise tolerance, an increase in fatigability, and weakness. A prospective, longitudinal, interventional study treating patients with CCH with oral propranolol at a dosage of 1.5 mg/kg/day found a reduction in sub- and intraretinal fluid without full regression in the first four months of treatment. Afterwards, stagnation in the therapeutic response followed by worsening despite continued therapy occurred, indicating that a saturation point exists [175]. Furthermore, in a case report on oral propranolol treatment in two patients with Sturge-Weber syndrome, no therapeutic effect could be found [176]. Histopathologically, cavernous and capillary components have been found [165]. In patients with Sturge-Weber syndrome, the predominant hemangioma type is the cavernous type, followed by mixed cavernous and capillary types [177]. This could be an explanation for the different therapeutic responses to propranolol in patients with Sturge-Weber syndrome compared to capillary hemangioma [165]. Recently, intravitreal β-blocker application has also been studied. Jorge et al. reported on a single case with CCH and consequent extensive subretinal fluid resistant to intravitreal anti-VEGF therapy. After two following intravitreal injections of metoprolol, a decrease in subretinal fluid, and improvement of visual acuity could be recognized [178]. In a phase I clinical trial, safety and early outcome of intravitreal metoprolol injection was analyzed, and no signs of acute intraocular toxicity were found. Furthermore, the authors also found a decrease in intra- or subretinal fluid [179]. Application of β-blockers intravitreally was also found to be safe in patients with central serous chorioretinopathy, and in rabbits [180,181]. However, further investigations addressing long-term effects and different drug concentrations are mandatory in this field. Retinal hemangioblastoma (RH) is a main component of ocular manifestation of Von-Hippel Lindau (VHL) disease. A national study with 64 genetically tested participants with RH revealed VHL as the underlying cause in 84% of the cases [182]. VHL disease is an autosomal dominantly inherited mutation in the VHL tumor suppressor gene that is related to characteristic benign and malignant neoplasms, such as central nervous system hemangioblastoma, RH, pheochromocytoma, or clear cell renal carcinoma [183]. First manifestation of RH mostly occurs at young age between 25 and 37 years [182,184]. Unilateral location was found in 42.1%, and bilateral location in 57.9% of patients [185]. The main part of RHs is located in the peripheral retina, and is less common in the juxtapapillary area [185]. Clinical manifestations can be vision loss due to retinal exudation, fibrosis, vitreous and subretinal hemorrhage, or exsudative retinal detachment [183]. To confirm the diagnosis of RH, fundus examination, fluorescein angiography, and optical coherence tomography play a central role. Furthermore, genetic testing is important to secure the diagnosis of VHL disease [183]. When RH is detected, fast intervention or close follow-up is needed. There are different established methods for ablative treatment, such as laser photocoagulation, cryotherapy, radiotherapy (brachytherapy, external beam radiotherapy, and proton beam radiotherapy), photodynamic therapy, or transpupillary thermotherapy [183]. Tumor-associated exudation can be reduced by intravitreal injection of VEGF blockers [183,186]. Histological studies revealed that RH are composed of abnormal capillary-like fenestrated channels surrounded by vacuolated stromal cells, and tumorlet-like cells expressing stem cell markers [187]. A loss of heterozygosity within the VHL tumor suppressor gene was mostly found in cells from the hematopoetic/vascular lineage, and was associated with an increase in VEGF, hypoxia induced factor (HIF), or ubiquitin [188]. By the absence of VHL protein, HIF accumulates because it is not ubiquitinated for degradation, and activates the expression of its targeted genes, such as VEGF [189]. Cell culture experiments could show that propranolol induced apoptosis in hemangioblastoma cells from VHL patients by downregulating HIF-dependent transcription [189]. Cuesta et al. could also demonstrate a reduction in activation of HIF-target genes by the β2-AR antagonist, ICI-118,551, in hemangioblastomas in VHL disease [190]. Hence, propranolol could be a therapeutic tool to control hemangioblastoma growth in patients with VHL. In a study with oral application of 120 mg propranolol once daily in VHL patients with RH, tumor size remained stable, and retinal exudation decreased without any adverse events. Furthermore, biomarkers, such as VEGF and miRNA, decreased in the first month of treatment [191]. Moreover, other authors reported that hemangioblastomas remained stable during 12 months under therapy with propranolol [192]. These studies indicate that systemic β-blockers are a feasible possibility for treatment of retinal hemangioblastomas, especially when juxtapapillary location complicates ablative treatment. Conjunctival hemangiomas are benign vascular tumors located at the bulbar conjunctiva that can grow sessile or pedunculated [193]. Congenitall hemangiomas have already reached their full size at birth. Infantile hemangiomas manifest at birth, but can increase in size followed by involution. In adults, acquired hemangiomas are described, also with increasing size [193,194]. Clinically, they can become apparent by elevated red lesions on the bulbar conjunctiva [195] and possible conjunctival bleeding [193]. For clinical management, regular observation is necessary. Especially in elderly patients, malignancy needs to be excluded. Therefore, biopsy and histopathological examination are mandatory [193]. Conjunctival hemangiomas consist of vascular channels lined by endothelial cells with positive immunostaining signals for CD31 and CD34, but with negative signals for the smooth muscle marker desmin [196]. There are several studies that show promising results for the therapy of conjunctival hemangioma by topical application of non-subtype-selective β-blockers, such as timolol. Lubahn et al. reported that an acquired sessile hemangioma resolved following topical application of timolol for 6 months [197]. In addition, infantile conjunctival hemangiomas were successfully treated by topical timolol administration [198,199]. As described above, non-subtype-selective β-blockers represent an effective method to treat different types of ocular hemangioma, and these effects have been discovered by chance. Expression of all three subtypes of β-ARs in hemangiomas has been demonstrated [200]. However, the specific role of each subtype is still not fully understood. Recently, it has been shown, that overexpression of the β3-AR is associated with a lack of response to propranolol [201]. Early effects of propranolol may be due to intralesional vasoconstriction caused by decreased release of nitric oxide [202]. Catecholamines activate endothelial β2-ARs, and induce vasodilatation via endothelial vasorelaxing factors, such as nitric oxide [203]. Through non-subtype-selective blockade of β-ARs, vasoconstriction and consequent reduction in intralesional blood flow can be induced [204,205]. Clinically, these effects cause reduction in the surface redness, brightening, and softening in infantile hemangioma [120,205]. However, longtime effects of propranolol treatment may not be caused by intralesional vasoconstriction. Intermediate effects of propranolol treatment could be explained by a reduction in proangiogenic factors, such as vascular endothelial growth factor (VEGF), matrix metalloproteinases (MMPs) or proangiogenic cytokines, such as interleukin-6 (IL-6) [205]. Catecholamines upregulate VEGF and HIF alpha-protein through β-ARs by induction of protein kinase A (PKA) and cyclic adenosine monophosphate (cAMP) [206]. It has been reported that chronic behavioral stress increased tumor angiogenesis and growth in ovarian carcinoma cells by β-AR-mediated activation of the cAMP-PKA signaling pathway with consecutive upregulation of VEGF, MMP2, and MMP9 [207]. Prevention of catecholamine stimulation by propranolol was shown to reduce expression of VEGF-A, which is known to play a crucial role in hemangioma growth [205]. By suppression of VEGF-A and VEGF-C, inhibitory effects on the development of experimental hemangioma have been shown [208]. In addition, other proangiogenic factors are downregulated by propranolol. By AR blockade through propranolol in vitro, a reduced tubulogenesis in human brain endothelial cells, and a decreased MMP-9 secretion was observed [209]. For angiogenesis, apart from formation of new blood vessels, different other events are necessary [205]. To enable migration of endothelial cells, proteolysis of components of the extracellular matrix is essential [205]. In this process of carcinogenesis, MMPs play a central role [210]. It has been shown that inhibition of MMPs reduced in vivo hemangioma growth [211]. Moreover, it has been observed that norepinephrine promoted the invasiveness of pancreatic cancer cells, which was associated with an increased expression of MMP-2, MMP-9, and VEGF. Intriguingly, these effects were blocked by propranolol [212]. Another proangiogenic cytokine, whose expression can be induced by catecholamines, is IL-6 [213]. High levels of IL-6 have also been found in infantile hemangioma, and inhibition of IL-6 was shown to reduce hemangioma growth [214]. Propranolol was also found to reduce IL-6 levels by blocking its upregulation [205]. These mechanisms may be responsible for interruption of hemangioma growth during propranolol application. Long-term effects of β-blockers in hemangiomas may be explained by induction of apoptosis in endothelial cells during the proliferative stage [202,215,216]. Possible mechanisms are activation of pro-apoptotic genes, such as caspase-9, caspase-3, p53, and Bax, and down-regulation of anti-apoptotic genes, such as Bcl-xL [217,218]. Furthermore, propranolol may reduce differentiation of hemangioma progenitor cells into endothelial cells or pericytes [205]. Conversion from a proliferating to an involuting tumor stage could be caused by differentiation of progenitor cells to adipocytes, induced by propranolol [205]. A scheme of the early, intermediate and longtime effects of β-blockers on hemangiomas is shown in Figure 3. Uveal melanoma is the most common primary intraocular malignant tumor in adults. In Europe, standardized incidence rates of 1.3–8.6 cases per million per year were reported [219]. However, uveal melanoma is a relatively rare cancer, occurring commonly in older age groups [220]. In Europe and in the United States, the median age of uveal melanoma diagnosis is 59 to 62 years [221]. Epidemiological studies revealed a higher incidence of uveal melanoma in males than in females [222]. The majority of uveal melanomas is located in the choroid (90%). A minor part was found to be located in the iris (4%) and in the ciliary body (6%) [223]. Predisposing factors are presence of choroidal nevus, oculodermal melanocytosis, fair skin, blond hair, light eye color, inability to tan, and mutation of BRCA1-associated protein 1 [220,224]. Furthermore, environmental factors, such as exposure to sunlight or artificial ultraviolet light may play a role in the development of uveal melanoma [220]. Iris melanoma is commonly detected by changes in iris color or pupil distortion. Additionally, it can cause secondary glaucoma by compression of the anterior chamber angle, angle seeding, ectropion uveae, hyphema, and extraocular extension [225]. Ciliary body and choroidal melanoma are characterized by painless vision loss or metamorphopsia due to serous retinal detachment in larger tumors. Other clinical manifestations are blurred vision, photopsia, floaters, visual field loss, visible tumor, or pain [220]. Thirty percent of uveal melanomas remain asymptomatic [220]. About 50% of patients with uveal melanoma develop metastatic disease, most frequently located in the liver, which has a high impact on the patient’s prognosis [226]. It has been shown that micrometastases can already develop 5 years before treatment of the primary tumor [227]. Therefore, early detection of uveal melanoma is mandatory. For diagnosis, fundus examination is necessary. Suspicious choroidal lesions with documented growth, presence of subretinal fluid, and orange pigment are suggestive for uveal melanoma [224]. Further diagnostic features are ultrasonography, where a mushroom-like configuration and low internal reflectivity are typical, fluorescein angiography, indocyanine green angiography to visualize intrinsic tumor vasculature, computed tomography, and magnetic resonance imaging [220,224]. Established therapeutic options are transpupillary thermotherapy, focal radiation therapy, local resection, enucleation, or orbital exenteration [220,224]. Figure 4 shows representative pictures of patients with uveal melanoma. A variety of clinical trials on targeting β-ARs to treat ocular hemangiomas/hemangioblastomas has been conducted. The trials are listed in Table 2. In cutaneous melanoma, β-ARs were found to be a new target for inhibition of tumor growth and dissemination [228]. In different cell lines of cutaneous melanoma, a pro-tumorgenic effect with increased MMP-dependent motility, and increased levels of IL-6, IL-8, and VEGF by catecholamines was shown. These effects could be reversed by the non-subtype-selective β-AR antagonist propranolol [229,230]. In a retrospective study on patients with cutaneous melanoma receiving regularly β-blockers, a lower disease progression and mortality rate was found [228,231]. Immunohistochemical studies demonstrated expression of β1- and β2-ARs in all patients with uveal melanoma, and a higher expression was found in more aggressive epitheloid cells [232]. The epitheloid cell type is associated with a poorer prognosis due to a higher mitotic activity, a higher microvascular density, and more tumor-infiltrating macrophages than in the spindle cell type [233]. A possible role of the β3-AR in melanoma growth and vascularization was identified in cutaneous melanoma cells of mice [113]. However, the role of β3-ARs in uveal melanoma remains unclear. In cutaneous and uveal melanoma cell lines, potent anti-proliferative effects of propranolol have been shown in a dose-dependent manner [232]. Decreased levels of VEGF in human uveal melanoma cells were reported by propranolol treatment [232]. Expression of VEGF-A has been shown to stimulate proliferation in uveal melanoma cells [234]. Furthermore, VEGF levels are significantly higher in patients with metastatic uveal melanoma disease than in patients without metastases [235]. This proliferative effect could be inhibited by blocking VEGF-A [234]. Other authors revealed limited effects of VEGF-blockers, such as bevacizumab, on cell proliferation in uveal melanoma [236]. Likewise, cytotoxic effects of propranolol via induction of apoptosis and cell cycle arrest could be demonstrated [232]. It is known that norepinephrine activates the raf-1 kinase/MAP kinase cascade through stimulation of β-ARs [237]. Activation of the MAP kinase cascade is also involved in the development of uveal melanoma, but without involvement of the protooncogenes NRAS and BRAF, which are part of cutaneous melanomagenesis [238]. Via the MAP kinase pathway and IP3 signaling with consecutive increase in intracellular calcium, PKC is activated. PKC stimulates the RAF/MEK/ERK pathway that is associated with increased proliferation, migration, and survival in cutaneous and uveal melanoma [232,239]. By blockade of these signaling pathways, β-blockers may be beneficial in the treatment of cutaneous and uveal melanoma. Janik et al. analyzed expression of β2-ARs in primary cutaneous (FM-55-P), primary uveal (92-1, Mel202), and metastatic cutaneous (A375) melanoma cells, and found cell line-dependent differences in β2-AR expression with higher expression levels in primary uveal melanoma cells. Furthermore, the authors could show that, through adrenaline treatment, a stimulation of melanoma cell proliferation and activation of MMPs was induced. Especially, uveal melanoma cells showed higher migration rates in comparison to cutaneous melanoma cells [240]. Patients with uveal melanoma positive for MMP-2 and MMP-9 had a significantly higher incidence of metastatic disease and lower survival rate, indicating that proteolytic enzymes, such as MMPs, may play a central role in tumor spread [241,242]. These findings indicate that blockade of β-ARs could be a potential therapeutic tool to treat uveal melanoma. However, further experimental and clinical examinations are necessary in this field. A scheme of potential effects of propranolol treatment on uveal melanoma growth is demonstrated in Figure 5. To expedite the clinical use of β-blockers in ocular diseases and tumor treatment, the intracellular signaling pathways, such as inflammatory, redox, and cell death signaling routes, modulated by activation or blockade of individual β-AR subtypes, remain to be characterized in more detail. Since different ocular tissues are equipped with various β-AR expression patterns, as well as with different intracellular signaling molecules, conclusions regarding individual β-AR functions cannot be generalized, but need to be confined to a specific cell type [3]. Since the immunologic system contributes to most ocular diseases, and because β-ARs are involved in various immune cell actions, expression and function of β-AR subtypes in individual immune cell types deserves further in-depth analysis [243,244,245]. Genetically modified cell cultures or animals may be useful to determine the role of individual β-AR subtypes in the pathophysiology and treatment of specific ocular diseases [107,246,247]. Since the specificity of AR antibodies is still limited, better specification of antibodies directed against-individual β-AR subtypes is needed to draw reliable conclusions regarding their expression pattern and modulation of expression by pharmacological or genetic tools [248,249,250,251]. Furthermore, more specific pharmacological agonists and antagonists for individual β-AR subtypes are desirable [252,253,254]. The use of highly selective β-AR ligands may pave the way for more specific therapeutic applications with limited side effects. Disturbed β-AR signaling is discussed in the pathophysiology of some ocular surface diseases, such as dry eye disease or disturbed corneal wound healing. Moreover, β-ARs are involved in the regulation of outflow facility of the trabecular meshwork, and in the regulation of aqueous humor formation in the ciliary body. Therefore, antagonism of the β2-AR by timolol plays a central role in glaucoma therapy. β-ARs are also involved in new blood vessel formation and tumor growth. In different ocular types of hemangioma, such as periorbital infantile hemangioma, choroidal hemangioma, retinal hemangioblastoma, and conjunctival hemangioma, different studies on therapeutic administration of β-blockers have been introduced, reporting promising results. Furthermore, expression of β-ARs and inhibitory effects of β-blockers in uveal melanoma cells have been reported. From a clinical point of view, the specific role of each β-AR subtype in tumor growth and treatment needs to be pursued further to tailor specific therapeutic approaches.

PMC10003538

Mengmeng Zhao,Gege Zheng,Xiuyun Kang,Xiaoyan Zhang,Junming Guo,Shaomei Wang,Yiping Chen,Lingui Xue

Aquatic Bacteria Rheinheimera tangshanensis New Ability for Mercury Pollution Removal

05-03-2023

Hg-tolerant bacteria,extracellular polymeric substances,mer operon,dead bacterial biomass,environmental pollution remediation

To explore the strong tolerance of bacteria to Hg pollution, aquatic Rheinheimera tangshanensis (RTS-4) was separated from industrial sewage, with a maximum Hg(II) tolerant concentration of 120 mg/L and a maximum Hg(II) removal rate of 86.72 ± 2.11%, in 48 h under optimum culture conditions. The Hg(II) bioremediation mechanisms of RTS-4 bacteria are as follows: (1) the reduction of Hg(II) through Hg reductase encoded by the mer operon; (2) the adsorption of Hg(II) through the production of extracellular polymeric substances (EPSs); and (3) the adsorption of Hg(II) using dead bacterial biomass (DBB). At low concentrations [Hg(II) ≤ 10 mg/L], RTS-4 bacteria employed Hg(II) reduction and DBB adsorption to remove Hg(II), and the removal percentages were 54.57 ± 0.36% and 45.43 ± 0.19% of the total removal efficiency, respectively. At moderate concentrations [10 mg/L < Hg(II) ≤ 50 mg/L], all three mechanisms listed above coexisted, with the percentages being 0.26 ± 0.01%, 81.70 ± 2.31%, and 18.04 ± 0.62% of the total removal rate, respectively. At high concentrations [Hg(II) > 50 mg/L], the bacteria primary employed EPS and DBB adsorption to remove Hg(II), where the percentages were 19.09 ± 0.04% and 80.91 ± 2.41% of the total removal rate, respectively. When all three mechanisms coexisted, the reduction of Hg(II) occurred within 8 h, the adsorption of Hg(II) by EPSs and DBB occurred within 8–20 h and after 20 h, respectively. This study provides an efficient and unused bacterium for the biological treatment of Hg pollution.

Aquatic Bacteria Rheinheimera tangshanensis New Ability for Mercury Pollution Removal To explore the strong tolerance of bacteria to Hg pollution, aquatic Rheinheimera tangshanensis (RTS-4) was separated from industrial sewage, with a maximum Hg(II) tolerant concentration of 120 mg/L and a maximum Hg(II) removal rate of 86.72 ± 2.11%, in 48 h under optimum culture conditions. The Hg(II) bioremediation mechanisms of RTS-4 bacteria are as follows: (1) the reduction of Hg(II) through Hg reductase encoded by the mer operon; (2) the adsorption of Hg(II) through the production of extracellular polymeric substances (EPSs); and (3) the adsorption of Hg(II) using dead bacterial biomass (DBB). At low concentrations [Hg(II) ≤ 10 mg/L], RTS-4 bacteria employed Hg(II) reduction and DBB adsorption to remove Hg(II), and the removal percentages were 54.57 ± 0.36% and 45.43 ± 0.19% of the total removal efficiency, respectively. At moderate concentrations [10 mg/L < Hg(II) ≤ 50 mg/L], all three mechanisms listed above coexisted, with the percentages being 0.26 ± 0.01%, 81.70 ± 2.31%, and 18.04 ± 0.62% of the total removal rate, respectively. At high concentrations [Hg(II) > 50 mg/L], the bacteria primary employed EPS and DBB adsorption to remove Hg(II), where the percentages were 19.09 ± 0.04% and 80.91 ± 2.41% of the total removal rate, respectively. When all three mechanisms coexisted, the reduction of Hg(II) occurred within 8 h, the adsorption of Hg(II) by EPSs and DBB occurred within 8–20 h and after 20 h, respectively. This study provides an efficient and unused bacterium for the biological treatment of Hg pollution. Mercury (Hg) is a common, naturally occurring, toxic heavy metal. It is easy to volatilize, spread, and stay in the atmosphere in the form of a gas, and redeposit in water or soil in the form of rain or dry gas. In this way, Hg already widely exists in the global environment and threatens the global biosphere [1]. Hg is extremely harmful to the environment because of its high toxicity, strong accumulation, and biological amplification. Various industrial wastewater discharges always contain Hg(II), such as from batteries, mining and smelting operations, industrial production and use, metallurgy, and electronics [2]. Hg(II) could accumulate in the kidney and cause acute renal failure, exposure to Hg(II) has become the main reason for autoimmune diseases and antinuclear antibodies. Hg(II) is also the pathogen of Alzheimer’s disease and Parkinson’s disease. Therefore, Hg(II) has a strong toxic effect on the central nervous system and digestive system [3]. Establishing efficient and green mercury remediation strategies has become an important issue in the field of environmental governance [4]. Many methods have been developed to remediate the pollution caused by Hg, such as the transference of Hg pollutants to remote areas, and removal through solidification and stabilization, cations, precipitation adsorption, and membrane filtration [5,6]. However, these approaches are usually costly, inefficient, and can easily produce by-products that cause secondary environmental pollution, unable to achieve the purpose of in situ remediation [7,8]. Microbial remediation is a safer, economical, and more effective alternative to traditional methods [9]. Sulfate-reducing bacteria were found to be very important in controlling both Hg methylation and MeHg degradation [10]. In 2022, it was found that the extracellular polymer of Bacillus could adsorb Hg, and its adsorption amount was 123.40 mg/g [11]; a strain of Acinetobacter indicus yy-1 was found to have a removal effect on both Cr and Hg [12]; Pseudomonas shows resistance to Hg and is able to transform Hg(II) to Hg(0), and shows great potential for the remediation of heavy metal-contaminated soil [13,14]. Many studies have showed that indigenous microorganisms found in the environment have a positive effect on the removal of Hg pollution, through reduction or adsorption [15,16,17], and current research mainly focuses on the isolation of microorganisms from soils. However, water is the main natural environment that accepts, degrades, and transforms various forms of Hg [5,18], so a water environment should also be a key focus for further research [19]. To explore the strong tolerance of bacteria for the bioremediation of Hg sewage, this study selected a bacterial strain of Rheinheimera tangshanensis (RTS-4), which has never demonstrated the ability to remediate Hg pollution from industrial wastewater, to explore its ability to tolerate and remove Hg(II). Then, the maximum Hg(II) tolerance concentration of the bacteria in solid and liquid media, optimal growth conditions, and Hg(II) removal efficiency were determined, and the mechanisms of Hg(II) removal by the RTS-4 bacteria were explored. Finally, the growth experiment of the indicator organism Chlorella vulgaris, verified the Hg(II) removal effect of the RTS-4 bacteria. The study found that RTS-4 bacteria can tolerate up to 120 and 60 mg/L of Hg(II), in solid and liquid media, respectively, and the removal rate of Hg can reach 86.72 ± 1.38%, at 48 h. RTS-4 bacteria also have the following capabilities: Hg(II) can be reduced by the mer operon during the 0–8 h period of bacterial growth; can be adsorbed by extracellular polymeric substances (EPSs) during the 8–20 h period, and can be adsorbed by dead bacterial biomass (DBB) after 20 h, until the treatment process is completed. This study provides valuable strain resources for the microbial remediation of Hg pollution, and suggests that the bacterium has broad application prospects in Hg pollution remediation. Ten bacterial strains with Hg-tolerant ability were isolated from a solid medium containing 120 mg/L Hg(II). One bacterial strain had 100% similarity to the Rheinheimera tangshanensis strain JA3-B52 (Figure 1A), and was identified as Rheinheimera tangshanensis (NCBI login number MT683260). This bacterial strain was termed RTS-4. Reports showed that bacteria in the genus of Rheinoniae generally play a role in plant growth and development, as rhizosphere microorganisms or endophytes [20,21]. The pectin removal property of Rheinheimera tangshanensis has substantial scope for its exploitation in wastewater treatment, and biopulping applications in the paper industry [22]. They can also produce DNA enzymes to mitigate the potential pleiotropic effects of new crop protection technologies, such as RNA interference [23]. However, few studies have demonstrated their strong Hg tolerance and conversion capacity, and it is rare for them to be used in the treatment of heavy metal wastewater. The colony of RTS-4 was round and yellowish, with a neat edge and smooth surface, and the diameter of the colony was about 2–3 mm (Figure S1A). Microscopic examination showed that it was comprised of rod-shaped Gram-negative bacteria (Figure 1B and Figure S1B). The optimal growth conditions of RTS-4 were 30 °C, pH 7, 150 rpm, and 5% inoculation amount (Figure S2). Although these results are consistent with previous reports [17,24,25,26], our studies also found that the RTS-4 bacteria had good temperature and pH adaptability. They can grow well in the temperature range of 20–30 °C (Figure S2A), exhibit high activity under neutral and acidic conditions (pH 6–7), and can grow normally under alkaline conditions (pH 8–9), which lays the foundation for the bacteria to demonstrate its bioremediation ability under various environmental conditions (Figure S2B). Its maximum Hg tolerant concentrations in solid and liquid medium were 120 mg/L and 60 mg/L, respectively. Under optimal growth conditions, the Hg(II) removal rates of RTS-4 after 24, 48, and 60 h were 55.80 ± 1.30%, 86.72 ± 1.38%, and 86.98 ± 2.01%, respectively (Figure 1C). After 24 h, the Hg(II) removal rates of Enterobacter helveticus and Brevundimonas HgP1 were 28.80% and 63.60%, respectively, at a 5.5 mg/L initial Hg(II) concentration [27,28]. The Hg(II) removal rates of FG11 75B (Enterococcus durans), FG11 85F (Enterococcus durans), and AG0352A (Enterococcus faecium) were about 70% at a 5 mg/L initial Hg(II) concentration, after 48 h [29]. Compared with previous research, the RTS-4 bacteria still had good Hg(II) removal ability at higher concentrations of Hg(II) (10 mg/L), indicating its great potential for sewage treatment. After RTS-4 was activated by 10 mg/L Hg(II), the merT gene showed expression after 2 h, reaching a maximum expression quantity after 6 h, and then downregulating from 8–24 h with negligible change (Figure 2B). After 2 h, the expression of merT was about 428, 62, and 26 times higher than that of merR, merC, and merA, respectively. After 6 h, it was about 17, 6, and 6 times higher than that of merR, merC, and merA, respectively. The expression of merR, merC, and merA genes showed similar trends, being significantly upregulated at 2 h, reaching a maximum expression after 6 h (Figure 2A,C,D), and showing downregulation after 8 h. The mer operon mainly includes merR, merT, merC, and merA genes [15,29,30]. merR is the promoter that initiates the expression of the entire operon. The merT and merC genes help Hg(II) transport from the outer membrane to the inner membrane and then deliver it to the Hg reductase binding site, which is encoded by merA. Finally, Hg(II) is reduced to Hg(0) by Hg reductase [15,31]. In the genome of RTS-4, the merR gene was upregulated at 2 h, but the expression level was downregulated due to the feedback inhibition of its own expression products after 8 h [15]. The merT and merC genes were significantly upregulated at 2 h, but became downregulated after 8 h, indicating that the bacteria began to regulate the transport of Hg(II) from outside to inside the membrane at 2 h but this ended after 8 h. The merA gene changed from being significantly upregulated at 2 h, to downregulated after 8 h, indicating that Hg reductase began to synthesize and reduce Hg(II) to Hg(0) between 2 and 8 h, but its function ended after 8 h (the evolutionary trees of the four genes are shown in Figure S4). From the removal rate of Hg(II) by RTS-4 bacteria between 0 and 12 h, the reduction rate of Hg(II) after 2 h in the control group (without RTS-4 bacteria and adding 10 mg/L Hg(II)) and the experimental group (with RTS-4 bacteria and 10 mg/L Hg(II)) were 0.56 ± 0.01% and 0.54 ± 0.01%, respectively, indicating that the reduction of Hg(II) in the experimental group was caused by the volatilization of Hg; between 2 h and 8 h, compared with the control group, the removal rate of Hg(II) increased to 23.41 ± 0.93%, indicating that the bacteria had begun to remove Hg(II); this period is also when the mer operon plays its role. After 8 h, the bacteria still maintained a high Hg(II) removal rate from the adsorption of extracellular polymeric substances (EPSs) produced by the bacteria. Therefore, the removal rate of Hg(II) by the RTS-4 bacteria, at different times, can also confirm the role of the mer operon. In the reported literature, the mer operon in Staphylococcus was significantly upregulated between 23 and 25 h. During this time, the expression of the merT gene increased by about 9 times, compared to the control, and the merR, merC, and merA genes could be activated by Hg(II) [15]. The mer operon in Pseudomonas cremoricolorata was significantly upregulated after 4 h, the expression of the merT gene was much higher than that of the merR, merC, or merA genes, and the Hg ion reduction process ended after 12 h [17]. The mer operon in Pseudomonas caricapapayae was expressed from 8 to 12 h, with the expression of the merT and merA genes being multiple times higher than that of the merR and merC genes [17]. Compared with the above bacteria, the expression times of the RTS-4 bacteria were early and short, showing that, as a newly discovered bacteria with Hg removal ability, the Hg removal mechanism of RTS-4 differed from that of the discovered bacterial strains. In addition, the expression level of the merT gene was higher than that of the other genes, especially the merC gene, which is also an encoded transporter. Therefore, the transporter encoded by merT was mainly responsible for the transport of Hg(II) in RTS-4, similar to the findings of other reported results [17]. Comparing the action time of the mer operon with the point when RTS-4 reached the highest Hg removal rate, we believed that RTS-4 bacteria also contained other mechanisms for removing Hg pollution, to achieve the observed results. The content of the EPS polymer was 1025.46 ± 12.98 mg/L, indicating that RTS-4 could produce a large amount of the EPS polymer. Scanning electron microscopy (SEM) analysis showed that the cells were similar to the original bacterial strain in morphology (Figure S3A), and did not produce mucus or filamentous substances after 10 mg/L Hg(II) treatment (Figure S3B). However, when the concentration of Hg(II) was raised to 20 mg/L and 30 mg/L, the cell morphology remained intact but the number of deposits on the cell surface gradually increased (Figure S3C,D). When the concentration of Hg(II) was raised to 40 mg/L, a large number of sediments appeared and some cells were sunken (Figure S3E). We speculate that a large number of extracellular polymeric substances (EPS) began to be produced. At a Hg(II) concentration of 50 mg/L, the cell morphology was damaged, the surface was covered with mucus or filaments, and severe adhesion was observed. In addition to a large amount of EPSs on the surface of bacterial cells, dead bacterial biomass began to be produced (Figure S3F). This indicated that the RTS-4 bacteria cells could grow very well in lower concentrations (10 mg/L) of Hg(II), gradually produced EPSs to adsorb Hg(II) at the concentrations of 20, 30, and 40 mg/L (medium concentrations), became damaged with the mass production of EPSs in high concentrations (50 mg/L) of Hg(II), and stopped growing and produced dead bacterial biomass in 60 mg/L Hg(II) (the maximum tolerance concentration of RTS-4 in liquid medium). Therefore, we believe that the concentrations of 10 and 50 mg/L are the thresholds for different mechanisms of bacterial Hg removal. The adsorption rate of Hg(II) by EPSs reached 23.50 ± 0.98% after 120 h (Figure 3C). The adsorption rate of EPSs increased rapidly in the first 20 h and slowed afterwards (Figure 3C). Song et al., studied the effect of cyanobacteria extracellular polymer on Hg adsorption by goethite [32], while Dash and Das, isolated Bacillus thuringiensis and produced EPSs to adsorb Hg [29]. RTS-4 has a stronger ability to produce EPSs than the studied bacteria, under high concentrations of Hg(II) (50 mg/L) (Figure S3) [32,33,34]. After eliminating the influence of Hg(II) volatilization (Figure 3A), the adsorption rate of Hg(II) by EPSs between 0 and 20 h was found to account for 81.70 ± 1.33% of the total removal rate (Figure 3C). After 60 h, the adsorption rate gradually decreased (Figure 3B), indicating that the EPS removal of Hg(II) reached completion within 20 h. Precipitation elemental analysis confirmed that there were five elements (carbon, nitrogen, oxygen, phosphorus, and Hg) on the surface of the cells (Figure 3E,F), and in the EPS solution (Figure 3G,H) containing 50 mg/L Hg(II). The proportions of C, N, O, P, and Hg were, respectively, 13.05 ± 0.84%, 15.49 ± 0.48%, 1.80 ± 0.07%, 6.80 ± 0.11%, and 49.13 ± 1.06% on the surface of the cells and 33.76 ± 0.98%, 14.19 ± 0.35%, 19.18 ± 0.12%, 8.38 ± 0.09%, and 24.10 ± 0.76% in the EPS solution. The SEM analysis, combined with the precipitation element analysis, showed that the EPSs produced by RTS-4 could embed Hg as spherical or amorphous sediments to achieve Hg removal. Francois et al. [33] isolated seven Hg-resistant strains, namely Bacillus cereus, Lysinibacillus sp., Bacillus sp., Kocuria rosea, Microbacterium oxydans, Serratia marcescens, and Ochrobactrum sp., that all produced EPSs. Inductively coupled plasma–optical emission spectroscopy (ICP–OES), and transmission electron microscopy (TEM) in conjunction with X-ray energy dispersive spectrometry, revealed that the bacteria incubated in the presence of HgCl2, sequestered Hg extracellularly, as spherical or amorphous deposits. However, no quantitative determination of the adsorption rate of EPSs for Hg(II) was found. The atomic percentage ratio of Hg in the precipitation formed by RTS-4 and EPSs was 2:1 (Figure 3F,H), indicating that, besides the EPSs reduction pathway, there is also a third Hg removal mechanism [34]. A series of changes in the functional groups of the EPSs before and after Hg(II) adsorption were characterized by FTIR, to further verify the adsorption characteristics of EPSs for Hg(II) (Figure 3D). The results indicated that Hg(II) adsorption by EPSs can be attributed to functional groups associated with proteins, lipids, and polysaccharides. Among them, the absorption peak at 3413 cm−1 shifted, indicating that the hydroxyl (–OH) group was involved in the adsorption of Hg(II) [35,36]. The C–H stretching vibration region shifted from 2938 cm−1 to 2936 cm−1, indicating that –CH2 was involved in the adsorption of Hg(II) [37]. The displacement from 1616 cm−1 to 1615 cm−1 indicated the stretching vibration of the double bond and the involvement of the C=O double bond, in Hg(II) adsorption [38]. The displacement at 1450 cm−1 signified the involvement of COO− in Hg(II) adsorption [39], while the peak at 614 cm−1 was assigned to the symmetrical stretching vibration of the pyranose backbone [40]. The changes in the IR spectra observed in the 4000 and 500 cm−1 regions suggested changes in the –OH, –CH2, and –COO groups, which indicated that hydroxyl complexation and ion exchange occurred in EPSs during the adsorption of Hg(II). When an amount of 10, 20, 30, 40, 50, 60, 70, or 80 mg/L Hg(II) was added to the liquid medium, the adsorption rates of Hg(II) by DBB were respectively 41.80 ± 0.82%, 35.25 ± 1.24%, 23.17 ± 0.58%, 11.71 ± 0.26%, 12.98 ± 0.38%, 14.96 ± 0.51%, 14.59 ± 0.41%, and 13.17 ± 0.88% (Figure 4B). The correlation between the adsorption rate of Hg(II) by DBB and the concentration of Hg(II) in the solution, was determined by comparing the Hg(II) removal rates of the blank control and RTS-4 bacterial cells (Figure 4A) at different concentrations. The adsorption rate of DBB increased and then decreased (Figure 4B) with increasing Hg(II) concentration. At lower concentrations of Hg(II) (≤10 mg/L), RTS-4 bacteria rarely produce EPSs, and only reduce Hg(II) through mer operon and adsorption Hg(II) by DBB, which led to a higher adsorption rate of DBB [5]. When the concentration of Hg(II) increased to 40 mg/L, the EPS complex was produced in large quantities, and its adsorption was dominant, causing the adsorption rate of DBB to decrease. Through calculation, the contribution rates of Hg(II) by DBB adsorption to the total treatment process were found to be 45.43 ± 1.02%, 38.47 ± 0.87%, 27.46 ± 0.74%, 17.25 ± 0.63%, 24.67 ± 0.82%, 27.63 ± 1.15%, 48.26 ± 1.31%, and 53.80 ± 1.47%, at the respective concentrations of Hg(II) (Figure 4C). The rate tended to increase, decrease, and increase again (Figure 4C). This trend is closely related to the production of DBB at different Hg(II) concentrations, and the mechanism of Hg removal by RTS-4. RTS-4 removes Hg(II) through Hg reduction by the mer operon, and Hg adsorption by DBB in the presence of Hg(II) concentrations equal to or lower than 10 mg/L; therefore, Hg adsorption by DBB accounted for a large proportion of the Hg removal process. When the Hg(II) concentration was between 10 and 50 mg/L (this concentration did not reach the maximum tolerance limit of RTS-4 bacteria), bacteria rarely produced DBB at this stage, and the three processes of Hg removal (i.e., mer operon reduction, EPS adsorption, and DBB adsorption) coexisted. Thus, the proportion of Hg(II) adsorption by DBB in the whole Hg removal process was lower. When the concentration of Hg(II) was above 50 mg/L, RTS-4 bacteria died in large numbers, and the adsorption process of DBB was dominant. This caused the proportion of DBB-adsorbed Hg(II) in the overall Hg removal process, to again increase [33]. Adsorption kinetics were mainly used to analyze the relationship between the adsorption rate and adsorption time. This is an important parameter used to study the adsorption performance. The quasi-second-order kinetic model is based on the assumption that the adsorption rate is controlled by the chemical adsorption process [41,42]. In this experiment, we use the quasi-second-order kinetic model to describe the relationship between the amount of Hg(II) absorbed by the bacteria and time. The results showed that, when the initial concentration of Hg(II) was 10 mg/L, the adsorption of Hg(II) by RTS-4 was divided into two stages (Figure 4D): 0–2 h was a fast adsorption stage, during which the adsorption amount of Hg(II) reached 99.30 ± 2.58% of the total adsorption amount; the adsorption capacity of RTS-4 toward Hg(II) was 48.88 ± 2.83 mg/g. According to the parameters shown in Figure 4D, the fitting effect of the quasi-second-order kinetic equation was better, as the R2 was higher. The equilibrium adsorption quantity, qe, obtained from the quasi-second-order kinetic model was close to the equilibrium adsorption quantity measured after the experiment was completed; the pseudo-second-order kinetic model could more accurately describe the adsorption process of Hg(II) by RTS-4 bacteria. According to the mechanism of the quasi-second-order kinetic equation, it is inferred that the adsorption of Hg(II) by RTS-4 bacteria was a combination of physical and chemical adsorption. The chemical adsorption is dominant [43], which might be the result of the interaction between the functional groups on the cell surface and heavy metal ions [44]. When the initial concentration of Hg(II) was 10 mg/L, Kumar et al., showed that chlorella rapidly adsorbed Hg in the first hour, and reached the equilibrium adsorption capacity of 75.41 mg/g after 1 h [45]. Patiño-Ruiz et al., modified sodium alginate (Mat) microspheres with thiourea and magnetite nanoparticles, to adsorb Hg(II) ions in aqueous solution [36]. In the first 20 min, the adsorption rate of Hg(II) increased rapidly, accounting for 98% of the total adsorption amount, and reached equilibrium after 100 min (equilibrium adsorption capacity, 2.60 mg/g). A strain of arsenic-resistant bacteria, Yersinia sp., was also tested. The adsorption of SOM-12D on arsenic reached equilibrium at 60 min, and the equilibrium adsorption amount was 36.28 mg/g [46]. When the initial concentration of Cr(VI) was 50 mg/L, the adsorption capacity of the spores of Aspergillus niger, pretreated by freeze-thawing, increased rapidly in the first 25 min and reached the equilibrium adsorption state after 100 min, with an equilibrium adsorption amount of 40.63 mg/g [41]. Compared with the reported equilibrium adsorption amount, the equilibrium adsorption amount in this experiment was lower, which may be due to the self-metabolism of the bacteria used for adsorption and the different adsorption sites, or different bacteria having different repair mechanisms for Hg(II). In summary, Hg(II) removal by RTS-4 bacteria occurs through three mechanisms: (1) the reduction of Hg(II) by mer operon; (2) the adsorption of Hg(II) by EPSs; and (3) the adsorption of Hg(II) by DBB. When the environment contained lower concentrations of Hg(II) (≤10 mg/L), the RTS-4 bacteria mainly used the mer operon to reduce Hg(II), accompanied by the adsorption process of DBB, with contribution rates of 54.57 ± 1.41 and 45.43 ± 1.41%, respectively (Figure 5A). For moderate Hg(II) concentrations (10 mg/L < Hg(II) ≤ 50 mg/L), the RTS-4 bacteria first used the mer operon to reduce Hg(II), then focused on the production of EPSs to adsorb Hg(II), and finally formed DBB to adsorb any remaining Hg(II); the contribution rates of the three processes were 0.26 ± 0.01, 81.7 ± 0.74, and 18.04 ± 0.73%, respectively (Figure 5B). When the concentration of Hg(II) was >50 mg/L, the bacteria removed Hg mainly by producing a small amount of EPSs and a large amount of DBB to adsorb Hg(II), with the contribution rates of the two processes being 19.09 ± 0.44% and 80.91 ± 0.64%, respectively (Figure 5C). In chronological order, the mer operon reduction process was dominant between 0 and 8 h, the EPS adsorption process was dominant from 8 to 20 h, and the DBB adsorption process was dominant after 20 h (Figure 5D). Some scholars have used Chlorella vulgaris (CV) as an indicator organism, to verify Hg(II) toxicity. Wang et al., evaluated the toxicity of Hg, Cu, Zn, Pb, and Cd toward CV, and found that Hg is most toxic to CV [5]. Duan et al., used a chlorophyll fluorescence analysis technique to study the combined toxic effects of Hg(II) on CV and to analyze the stress effect of Hg(II), using the chlorophyll content of CV [47]. Thus, we used Chlorella vulgaris (CV) and its chlorophyll content as an indicator to verify the Hg removal effect by the RTS-4 bacterial strain. The chlorophyll contents were 4.56 ± 0.08, 0.78 ± 0.02, 0.65 ± 0.03, 4.45 ± 0.12, 0.75 ± 0.03, and 4.13 ± 0.14 mg/L in CK, C1, C2, CK′, C1′, and C2′, respectively (Figure 6A). The chlorophyll contents changed little in CK, CK’, and C2′. However, the culture mediums in C1, C1′, and C2 turned yellow and precipitated, indicating low concentrations of chlorophyll and CV cell death (Figure 6B). After culturing for 36 h, the remaining concentrations of Hg(II) in the C1, C1′, C2, and C2′ solutions were, respectively, 9.47 ± 0.24, 9.35 ± 0.21, 9.23 ± 0.28, and 3.99 ± 0.07 mg/L. The removal rates of Hg(II) were 5.30 ± 0.11% (C1), 6.50 ± 0.09% (C1′), 7.70 ± 0.15% (C2), and 60.10 ± 2.12% (C2′). In the experimental group (C1), where CV was added immediately after Hg(II) was added, a large amount of CV died within 12 h, due to Hg(II) poisoning. The culture solution had turned yellow and precipitated, indicating that the chlorophyll content was significantly reduced. Hg(II) volatilized for 24 h followed by the addition of CV (C1′), led to CV that was also poisoned by Hg(II), and a large number of deaths occurred within 12 h. This indicated the volatilization of Hg(II) could not alleviate its damage to CV. In the C2 group, where Hg(II), the RTS-4 bacterial strain, and CV were added at the same time, the CV still died within 12 h, causing the culture solution to turn yellow and precipitate, and the chlorophyll content to decrease. As the bacterial strain was unable to deal with the Hg(II) in time, CV still died in large numbers. Adding Hg(II) and RTS-4 bacterial strains 24 h prior to the addition of CV to the solution (C2′), caused most of the Hg(II) to be reduced or adsorbed by the bacterial strains. This allowed for the growth of CV to not be significantly affected, creating a solution that was green and clear (Figure 6). The higher chlorophyll content, lower residual Hg concentration, and higher Hg removal rate of the C2′ experimental group, fully demonstrated the superior removal effect of the RTS-4 bacterial strain on Hg(II). The composition of industrial wastewater is complex and may contain many kinds of heavy metals. In this experiment, we found the tolerance and adsorption capacity of RTS-4 bacteria toward other heavy metals, and will discuss this more deeply in a followup report. In the future, we believe that immobilization technology can be used to study the process and control conditions of the immobilized bacteria for Hg-containing wastewater, to address the difficult reuse and poor stability of microbial remediation technology, and further improve its remediation efficiency. This research aims to provide a high-efficiency, environmentally friendly, and reusable approach for the biological treatment of Hg-containing wastewater. Wastewater was collected from the industrial sewage outfall in Xigu District, Lanzhou City, Gansu Province, China [48]. The enrichment, culture, separation and purification of bacteria were all performed as the methods described in Zhao et al.; the obtained bacterial suspension was stored in a refrigerator at −80 °C, for subsequent experiments [17]. To identify Hg-tolerant bacteria, 16S rRNA gene amplification was used. Using the common primers 27F and 1492R for the bacterial V3–V4 region [49], the amplification conditions and results detected were all performed as the methods described in Zhao et al. [17]. The sequencing results were submitted to the NCBI (www.ncbi.nlm.nih.gov/blast (accessed on 7 July 2020)) gene database to obtain the strain accession number MT683260. After BLAST comparison, we inferred the evolutionary history using the neighbor-joining method, and conducted evolutionary analyses in MEGA5 [50]. The single-factor analysis method was used to analyze the biomass of the Hg-tolerant strains under different Hg(II) concentrations, pH, temperatures, rotation speeds, and inoculation amounts, to determine the optimal growth conditions of the bacteria. For the preliminary experiment, we selected Hg concentrations of 0, 30, 60, 90, and 120 mg/L; pH values of 6, 7, 8, and 9; temperatures of 20 °C, 25 °C, 30 °C, 37 °C, and 42 °C; rotation speeds of 0, 50, 100, 150, 180, and 200 r/min; and inoculation amounts of 5%, 10%, 15%, and 20%. First, 1 mL of bacterial liquid was inoculated into 50 mL of LB liquid medium containing different Hg(II) concentrations, and cultured at 30 °C and pH 8 [33]. This was repeated in triplicate for each group. Culture medium (3 mL) was collected at regular intervals, and the absorbance (OD600) was measured with an ultraviolet–visible light spectrophotometer (UV-2100, Shanghai Unico Instrument Co., Ltd., Shanghai, China) to draw a growth curve. When selecting the optimal culture pH, temperature, rotation speed, and inoculum amount, 10 mg/L Hg(II) was added to the medium to measure bacterial growth, because the concentration of Hg(II) in general industrial wastewater did not exceed 10 mg/L [51,52,53]. One milliliter of logarithmic growth phase bacterial culture medium was added to 50 mL of LB liquid medium containing 10 mg/L Hg(II), and cultivated at 30 °C and 150 rpm, using the LB liquid medium containing 10 mg/L Hg(II), without bacteria, as a control. An atomic fluorescence Hg meter Mercur® (AFS, Jena Analytical Instruments Co., Ltd., Jena, Germany) was used to detect the remaining concentration of Hg(II) after treatment at different times (24, 48, and 60 h), and the removal rates of Hg(II) were calculated by the following equation: where C is the Hg(II) removal rate, C0 is the initial Hg(II) concentration in the samples, and C1 is the remaining Hg(II) concentration in the samples after bacterial treatment. Fresh bacterial liquid was inoculated into 50 mL of LB liquid medium, according to the optimal inoculation amount selected in the previous experiments, under the conditions of 0 and 10 mg/L Hg(II). The biomass (OD600) of the bacterial solution was measured initially, and sampling every 2 h until 12 h. After 12 h, the biomass (OD600) of the bacterial solution was measured every 12 h. The growth curves of the strains were plotted, and changes in the growth curves of the strains with and without Hg(II) were compared. To activate the bacteria, 10 mg/L of Hg(II) was added to the LB liquid medium, and the liquid medium without Hg(II) was used as a control. To study the real-time changes in gene expression in the mer operon, according to the results of preliminary experiments, measurements taken at 2, 6, 8, 12, and 24 h were selected for the determination of gene expression. The RT-qPCR experiment detected four main genes in the mer operon, merA, merR, merC, and merT, and the whole process was conducted on ice. The specific genes and 16S rRNA housekeeping gene primers used were designed and synthesized by Lanzhou Ruizhen Biotechnology Co., Ltd., Lanzhou, China (the primers of the merA, merR, merC, merT genes, and the housekeeping gene, are provided in Table S1). The 16S rRNA house-keeping genes were used as the internal reference gene, and the Ct value method was used to calculate the expression level of each gene: where ∆∆Ct = (the Ct value of the target gene in the experimental group − the Ct value of the internal reference gene in the experimental group) − (the Ct value of the target gene in the control group − the Ct value of the internal reference gene in the control group). Therefore, 2−∆∆Ct represents the fold change in the target gene expression in the experimental group relative to the control group. The bacterial strains were collected by centrifugation in a culture medium containing 50 mg/L Hg(II), and observed under a scanning electron microscope (TESCAN MIRA3, Brno, Czech Republic), at a magnification of 15.0 KX and a voltage of 8.0 kV. The experimental process of obtaining EPSs was referred to Francois et al. [33], the EPSs produced by RTS-4 were extracted by high-speed centrifugation and were identified using a TOC instrument. The precipitation of EPSs and Hg(II) in the dialysis bag was vacuum freeze-dried; one portion was directly used for scanning electron microscopy, and the other was used for scanning energy dispersive spectroscopy (EDS) analysis. The extracellular polymeric EPS purified sample was freeze-dried (FreeZone 6, Labconco Corporation, Kansas City, MO, USA), the dried sample was ground into a powder, and the slices were made via a KBr Fourier transform method and analyzed by infrared spectroscopy (Vertex 70, Bruker Spectroscopy, Ettlingen, Germany). Preparation of dead bacteria was according to a previous study [54]. The dead bacterial cells were placed in media containing 10, 20, 40, 60, and 80 mg/L Hg(II), respectively, with the blank medium and medium with live bacteria used as controls. The contribution rate at different concentrations of dead bacteria, toward the adsorption of Hg during heavy metal removal, was analyzed. An AFS was used to detect the remaining concentration of Hg(II) in the culture medium after 0 h and 120 h treatment, and the Hg(II) adsorption rate was calculated using Equation (1). The suspension of RTS-4 bacteria from the logarithmic stage was cultured to 2 mL. After centrifugation, 0.1 g of bacteria was added to 50 mL of distilled water containing 10 mg/L Hg(II), and was oscillated and adsorbed at 30 °C in a constant-temperature shaking bed, at 150 rpm. The residual Hg(II) concentrations were determined by AFS at 0.5, 1, 2, 4, 6, 8, 12, and 24 h, and the adsorption kinetic curve was drawn. The pseudo-second-order kinetic equation can be written as where qt is the adsorption capacity at time t (mg/g), qe is the equilibrium adsorption capacity (mg/g), t is the adsorption time (h), and K2 is the pseudo-second-order adsorption rate constant. The growth status of Chlorella vulgaris (CV) was used to determine the Hg(II) reduction abilities of Hg-tolerant bacterial strains. CV was originally cultured in a BG11 medium [55]. The specific experimental procedures was referred to Zhao et al. [17]. In this study, the SPSS 20.0 software (IBM SPSS Statistics for Windows, version 22.0, IBM Corp., Armonk, NY, USA) was used for the analysis of all data, the Origin 9.0 software (version 9.0, OriginLab, Northampton, MA, USA) was used for chart processing, and the phylogenetic tree was constructed using the MEGA5 bioinformatics software [50]. In this study, a bacterial strain of RTS-4, with strong tolerance to Hg(II), isolated from industrial wastewater, was used to analyze the Hg pollution repair ability and mechanism. It was found that the bacteria can reduce Hg(II) to Hg(0) by Hg ion reductase, to alleviate the toxicity of Hg(II), and adsorb Hg(II) by producing extracellular polymers and dead biomass to reduce the concentration of Hg(II) in the environment. When different concentrations of Hg(II) are found in the environment, these three mechanisms work alone or in synergy, to remediate Hg pollution in the environment. The effect of Hg(II) remediation by RTS-4 was verified through a chlorella growth experiment. Because this kind of microorganism (Rheinheimera tangshanensis) has high tolerance, and a strong biotransformation ability and adsorption ability towards Hg, and has never before been found to have the ability to repair Hg(II) pollution, this study broadens the source of bacterial strains for Hg pollution bioremediation, provides valuable bacterial strain resources, and introduces a theoretical basis for the application of this bacterial strain in Hg pollution treatment in water.

PMC10003541

Xue Bai,Kai Xu,Le Xie,Yue Qiu,Sen Chen,Yu Sun

The Dual Roles of Triiodothyronine in Regulating the Morphology of Hair Cells and Supporting Cells during Critical Periods of Mouse Cochlear Development

25-02-2023

triiodothyronine,hearing loss,cochlear remodeling,organ of corti

Clinically, thyroid-related diseases such as endemic iodine deficiency and congenital hypothyroidism are associated with hearing loss, suggesting that thyroid hormones are essential for the development of normal hearing. Triiodothyronine (T3) is the main active form of thyroid hormone and its effect on the remodeling of the organ of Corti remain unclear. This study aims to explore the effect and mechanism of T3 on the remodeling of the organ of Corti and supporting cells development during early development. In this study, mice treated with T3 at postnatal (P) day 0 or P1 showed severe hearing loss with disordered stereocilia of the outer hair cells (OHCs) and impaired function of mechanoelectrical transduction of OHCs. In addition, we found that treatment with T3 at P0 or P1 resulted in the overproduction of Deiter-like cells. Compared with the control group, the transcription levels of Sox2 and notch pathway-related genes in the cochlea of the T3 group were significantly downregulated. Furthermore, Sox2-haploinsufficient mice treated with T3 not only showed excess numbers of Deiter-like cells but also a large number of ectopic outer pillar cells (OPCs). Our study provides new evidence for the dual roles of T3 in regulating both hair cells and supporting cell development, suggesting that it is possible to increase the reserve of supporting cells.

The Dual Roles of Triiodothyronine in Regulating the Morphology of Hair Cells and Supporting Cells during Critical Periods of Mouse Cochlear Development Clinically, thyroid-related diseases such as endemic iodine deficiency and congenital hypothyroidism are associated with hearing loss, suggesting that thyroid hormones are essential for the development of normal hearing. Triiodothyronine (T3) is the main active form of thyroid hormone and its effect on the remodeling of the organ of Corti remain unclear. This study aims to explore the effect and mechanism of T3 on the remodeling of the organ of Corti and supporting cells development during early development. In this study, mice treated with T3 at postnatal (P) day 0 or P1 showed severe hearing loss with disordered stereocilia of the outer hair cells (OHCs) and impaired function of mechanoelectrical transduction of OHCs. In addition, we found that treatment with T3 at P0 or P1 resulted in the overproduction of Deiter-like cells. Compared with the control group, the transcription levels of Sox2 and notch pathway-related genes in the cochlea of the T3 group were significantly downregulated. Furthermore, Sox2-haploinsufficient mice treated with T3 not only showed excess numbers of Deiter-like cells but also a large number of ectopic outer pillar cells (OPCs). Our study provides new evidence for the dual roles of T3 in regulating both hair cells and supporting cell development, suggesting that it is possible to increase the reserve of supporting cells. The organ of Corti (OC), the auditory sensor by which sounds are converted into nerve impulses, is one of the most complex organ structures in mammals. The structure includes one row of inner hair cells (IHCs) and three rows of outer hair cells (OHCs) interdigitated among different types of supporting cells (SCs). The morphology of different SCs is distinct and few studies have focused on their biology and function [1]. Abnormal development of SCs induced by gene mutations, congenital cytomegalovirus infection, or thyroid disease can lead to severe hearing loss [2,3,4]. In addition, growing evidence suggests that well-formed SCs act as mediators of hair cell development, function, and survival. Therefore, further research on the proliferation, maturation, and development of SCs may increase our understanding of inner ear development and regeneration. In rodents, the overall structure of the auditory epithelium is formed by the time of birth and continues to mature structurally until hearing begins on postnatal day (P)14. During this period, HCs form V-shape stereocilia that accommodate the mechanoelectrical transduction (MET) channels. Deiter cells (DCs), a type of SCs coupled with OHCs, extend phalangeal processes to provide structural support for OHCs. Inner and outer pillar cells (IPCs and OPCs) form triangular tunnels of Corti which support the whole OC. More different types of SCs, such as Hensen’s cells, Claudius cells, or inner sulcus cells, lie lateral to OHCs or IHCs. Many previous studies have focused on the molecules that regulate the proliferation and differentiation of hair cells (HCs) in order to achieve the purpose of restoring impaired hearing through HC regeneration strategies [5,6,7]. Although ectopic HCs can be induced in the cochleae of newborn or adult mice, due to the lack of corresponding SCs and fine OC structure, these efforts still failed to restore hearing and maintain it in the long term [8,9,10]. For the treatment of deafness, reconstruction of the entire OC may be a better but more difficult choice. It is particularly important to explore the development and regeneration of SCs. Interestingly, SC development is regulated by both local molecular pathways and systemic hormones. The thyroid hormone regulates OC formation and the development of normal hearing [11,12]. Triiodothyronine (T3) is the main active form of thyroid hormone and acts on thyroid hormone receptors (TRs) to induce a series of physiological changes in target tissues [13,14]. In particular, animals with developmental hypothyroidism exhibit delayed opening of the tunnel of Corti [15,16]. Conversely, excess T3 can lead to the death of SCs in the greater epithelial ridge (GER) and early opening of the tunnel of Corti with premature PCs [17,18]. These findings suggest that T3 regulates the development of some types of SCs in the cochlea. In humans, thyroid-related diseases such as endemic iodine deficiency, congenital hypothyroidism, and resistance to T3 caused by mutations in TRs are associated with hearing loss [19,20,21]. In mice, secondary hypothyroidism caused by mutations in TRs results in permanent potassium channel dysfunction and impaired HC function [22,23,24]. Knockout of T3 transporters can lead to OHC death and developmental arrest of SCs in mice [25]. These findings suggest that T3 plays multiple roles in the function of HCs and the development of SCs, especially in the fine structure formation of the OC. To explore the effect of T3 on the remodeling of the OC and the development of SCs during early development, we administered T3 to neonatal mice at different time points after birth. Our results show that excess T3 given at an early stage (P0 or P1) leads to severe hearing loss with abnormal stereocilia alignment and HC mechanosensory dysfunction. Moreover, mice in the P0 or P1 group showed an overproduction of Deiter-like cells. These extra cells expressed the functional marker acetylated α-tubulin and are linked to adjacent DCs through gap junctions. A series of genes related to the development of cochlear sensory epithelium were significantly downregulated in the T3 group. When Sox2 haploinsufficient mice were treated with T3 at P0, the number of DCs and OPCs increased significantly and resulted in a great change in the structure of the OC. Our finding suggests that excess T3 may lead to deafness by interfering with the normal stereocilia formation and amplification function of HCs. Excessive T3 or T3 combined with Sox2 downregulation can alter the fine structure of the OC by regulating the development of SCs. Hormone action combined with key signaling pathways in the inner ear may be a potential research focus for regulating OC development and regeneration. To evaluate the effect of T3 treatments at different postnatal periods on auditory function in mice, ABR testing was performed on mice in the control group and T3 treatment group (n = 4 mice in each group) at P18. Compared with the control group, the ABR-click thresholds increased significantly in the P0 or P1 group, while mice in the P3 group showed normal hearing (Figure 1A). Mice in the P0 group showed severe deafness with mean thresholds above 80 dB SPL at 8–40 kHz, while mice in the P1 group displayed moderate to severe deafness with hearing thresholds at 8, 16, 24, 32, and 40 kHz of 61.3 ± 6.3, 51.3 ± 2.5, 57.5 ± 9.6, 73.8 ± 7.5, and 90.0 ± 0 dB SPL, respectively (Figure 1B). Mice treated with T3 at P3 showed normal hearing at P18 (Figure 1B). HC loss is a major cause of hearing loss. Thus, we analyzed the survival patterns of HCs in T3-treated mice. No substantial HC loss was observed in the different T3-treated groups at P18 (Figure 2B–M). Although scattered losses of OHCs were occasionally observed in the basal turn of the P0 group (white arrows, Figure 2G), statistical analysis showed that the number of OHCs was not significantly changed (n = 4/group, p > 0.05) (Figure 2N). In neonatal mice, the cochlea continues to develop structurally and functionally before hearing onset, and regression of the GER is a prominent event. During natural development, cells in the GER promote the development and maturation of sensory epithelium through programmed cell death. We performed activated caspase-3 staining to determine the apoptosis pattern of the GER in T3 P0 treated mice. At P6, no activated caspase-3-positive (caspase-3+) cells were detected in the GER of control mice, while a large number of caspase-3+ cells were observed in the GER of the T3 P0 treated group (Figure 2P,Q). In contrast, caspase-3+ cells were evident in the GER of control cochleae and were not detected in the T3 P0 treated group at P11 (Figure 2R,S). Statistical analysis showed that the number of caspase-3+ cells differed significantly between the two groups at P6 and P11 (n = 4, p < 0.01) (Figure 2O). In mammals, stereocilia are located in the cuticular plate of HCs and are responsible for converting mechanical vibrations generated by sound stimulation into electrical signals. Structural or functional defects of the stereocilia are one of the main causes of congenital or progressive deafness. We performed SEM to characterize the morphology of stereocilia in different T3-treated groups. In the control group, three rows of stereocilia formed V-shaped bundles in all turns (Figure 3a–c,a’–c’). However, stereocilia bundles of OHCs in the apical and middle turns of the P0 or P1 group were disordered and lost their V-shaped structure. Interestingly, there were no obvious changes in the morphology of the stereocilia bundles in the basal turn of the P0 or P1 groups (Figure 3d–i,d’–i’). In contrast, the morphology and arrangement of the OHC stereocilia bundles were almost unaffected when T3 was given at P3 (Figure 3j–l,j’–l’). These results suggest that the abnormal arrangement of the OHC stereocilia bundle may be strongly associated with hearing loss caused by excess T3. In addition, FM1-43 loading of OHCs was used to assess the function of the MET channel. Compared with the control group, the uptake of FM1-43 by OHCs in the T3 treatment group was reduced (Figure 4A). Quantitative results showed that the relative fluorescence density of FM1-43 in OHCs of T3-treated mice decreased by 23.9 ± 13.9% (Figure 3B). These results indicated that abnormalities of the HC stereocilia bundles and dysfunctions of the MET channel might be responsible for the hearing loss induced by excess T3. At both 10 and 16 kHz, the DPOAE input/output plots measured from the P0 group decreased significantly compared with the control group (Figure 3C,D). The level of DPOAE in the P0 group was significantly lower than that in the control group at all input levels (p < 0.001, n = 5 in each group). To investigate the effect of T3 on OC remodeling, mice were sacrificed at P18 and the SCs were labeled with Sox2 (white). Furthermore, phalloidin (red) was used to label the bases of the DCs and PCs. In the control group, the DCs were neatly arranged in three rows and the PCs were arranged in a single row in all turns (Figure 5A–F). However, in the P0 group, we observed four rows of DCs in the apical turns, and sporadic extra DCs in middle turns, indicating the production of extra Deiter-like cells. In addition, the arrangement of Sox2-labeled SCs was disordered and the OPCs were disordered compared to the control group (Figure 5G–J). The arrangement of DCs in the basal turn was almost unaffected in the P0 group (Figure 5K,L). Statistical analysis showed that the number of DCs (including Deiter-like cells) was significantly increased in the apical and middle turns (n = 4, p < 0.001) (Figure 5M). Next, we explored the effects of excess T3 administration at different time points after birth on the development of the OC. We labeled DCs with Cx30, a protein subunit that constitutes gap junctions, which serves as a functional marker of DCs. In the control group, Cx30 signals (green) were evenly distributed along the boundaries of all DCs (Figure 6A–C). In contrast in the P0 group, we observed that the Deiter-like cells also expressed Cx30, which suggested that these cells might have some of the functions of DCs (Figure 6D,d,E,e). When T3 was given at P1, we also observed four rows of Cx30-expressing DCs in the apical and middle turns (Figure 6G,g,H,h). However, T3 given at P3 did not significantly affect the number of DCs (Figure 6J–L,j–l). Quantitative results showed that the number of DCs was significantly increased in apical and middle turns from the P0 and P1 groups (n = 4, p < 0.01) (Figure 6M). The distance between the feet of the IPCs and OPCs was also reduced in the apical and middle turns of the P0 and P1 groups (Figure 6N). These parameters did not change significantly in the P3 group. Our results reveal that excess T3 regulates the development of the OC, especially for DCs, in a narrow postnatal time window. Radial sections of the cochlea revealed the nuclei of three rows of DCs in the control group (Figure 7A,B). However, in the apical turn of the P0 group, we observed nuclei of four rows of DCs (Figure 7C,D). In addition, ultrastructural examination showed the presence of three rows of DC cell bodies in the control group and bundles of microtubules and normal mitochondria in DCs (Figure 7E–G). In the P0 group, we observed four rows of DC cell bodies (Figure 7H). The phalangeal processes of extra DCs showed normal architecture of the bundles of microtubules and mitochondria (Figure 7I,J), which indicated that the overproduced Deiter-like cells have a similar structure to normal DCs and could potentially function similarly. To investigate the mechanism involved in the T3-induced remodeling of the OC, we performed qPCR to analyze the expression levels of a series of genes regulating the development of the inner ear. Neonatal mice were injected with T3 at P0 andP1 and then sacrificed at P4 for qPCR to analyze. Mice without T3 treatment save as control group, the mRNA expression of Atoh1 and Sox2, two transcription factors that regulate the development of HCs and SCs, was significantly downregulated (Figure 8A). However, the other important factors Pou4f3, Neurog1, and Gfi1 did not change significantly. In addition, we analyzed the Notch, Wnt, TGFβ, and FGF signaling pathways as well as cell cycle signaling pathways and found that the transcription levels of Notch pathway-related genes, such as Notch1, Notch2, Notch2, Notch3, Jag1, Jag2, Hey1, Hey2, Hes1, Hes5, and Dll1 were significantly downregulated (Figure 8B). In contrast, expression of FGF and most TGFβ signaling pathway genes did not change significantly, while only Smad4, Bmpr1b, and Ltbp1 were downregulated (Figure 8C,D). In the Wnt pathway, the mRNA expression levels of Lgr5 and Wnt2b were significantly downregulated and other related genes were not significantly changed (Figure 8E). In addition, we found that the cell cycle-dependent kinases Cdk2 and Cdk4, and cell division cyclin Cdc25c, were downregulated in cochleae of T3-treated mice (Figure 8F). All these results suggest that T3 may lead to the overproduction of DCs mainly through downregulation of the Notch signaling pathway in early cochlear development. Recent studies have shown that Sox2CreER/+ mice exhibit Sox2 haploid insufficiency due to one of the alleles being replaced by CreER [26]. Using this characteristic, Sox2CreER/+ mice were injected with T3 to explore the effect of T3 combined with Sox2 downregulation on the development of SCs in the inner ear (Figure 9A). In Sox2 haploinsufficient (Sox2 haplo) mice, three rows of DCs were neatly arranged, and Cx30 was observed at the edge of all DCs—same as in the control group (Figure 9B–G,b–g). In the T3 and the Sox2 haplo + T3 groups, four rows of DCs were observed in the apical and middle turns (Figure 9H,I,K,L), and the quantified results showed no significant difference in the number of DCs between the T3 and the Sox2 haplo + T3 groups (Figure 9N). However, ectopic OPCs were observed in the apical and middle turns of the Sox2 haplo + T3 group (Figure 9K,k,L,l). Statistical analysis showed that the number of OPCs was significantly increased in the apical and middle turns of the Sox2 haplo + T3 group (n = 4, p < 0.01) (Figure 9O). These results suggest that T3 combined with Sox2 downregulation did not aggravate the overproduction of DCs induced by T3, but did induce the overproduction of OPCs (white arrows, Figure 10G). Moreover, extra OPCs in the Sox2 haplo + T3 group appeared to form new tunnels of Corti that affected the structure of the OC (white arrowhead, Figure 10G,H). The yellow lines show the boundaries of the tunnel of Corti (Figure 10B,E,H). Over recent decades, a series of studies have focused on the role of thyroid hormones in fetal tissue differentiation and development [27]. Fetal nervous system development is highly sensitive to thyroid hormones, and maternal thyroid hormone disorder can cause fetal central nervous system symptoms including hearing, speech, and color vision impairments, and squint [28,29]. A previous study showed that injections of T3 resulted in expected increases in serum T3 concentrations, with daily injections of 0.01, 0.1, and 2.0 µg T3 up to P5 resulting in serum T3 levels that were increased approximately 12-, 80-, and 280-fold, respectively [30]. T3-induced hearing loss in mice was concentration-dependent, with a dose of 0.1 µg T3/d resulting in a threshold of approximately 70 dB SPL, whereas 1.5 or 2.0 µg T3/d resulted in thresholds of more than or equal to 90 dB SPL [30]. A single injection of T3 at P0 resulted in significant hearing loss, whereas T3 given at P3 or later did not significantly change thresholds compared to saline-treated groups [18]. In this study, our results indicated that administration of excess T3 in the early postnatal period (P0 or P1) induced severe hearing loss in mice (Figure 1). However, we did not observe significant degeneration of HCs, suggesting that the cause of hearing loss is not simply HC death. When T3 was given at P3 (the P3 group), mice exhibited normal hearing at P18. Observations by us and others have proven that P0–P2 is the critical period when deafness is caused by excess T3 [18]. In addition, caspase-3+ cells were detected in the GER of the P0 group at P6, while apoptosis of the GER in the control group was not triggered at this time. However, a recent study by Borse et al. reported that macrophages were recruited into the GER region after initiation of GER regression during cochlear remodeling [17]. In this study, apoptotic signals in the GER region were detected at P5. This difference in timing may be due to differences in experimental technique and mouse strain used. Excess T3 advances the overall program of apoptosis, with regression of the GER initiated at P3 and creating a large cavity known as the inner spiral sulcus at P5 in the T3 treatment group, whereas in normal mice this process occurs at P7 [18]. Premature degeneration of the GER triggered by T3 resulted in the advanced opening of the tunnel of Corti. However, it remains unclear whether pre-maturation of the OC is directly related to hearing loss. Stereocilia are mechanical sensors located in the cochlear sensory cells that convert sound stimuli into electrical signals, and normal auditory function depends on the organization and morphology of the stereocilia, thus they are thought to be critical for mammalian hearing and balance [31,32]. Disorders of the stereocilia hair bundle structure are involved in various forms of congenital or progressive hearing loss [33,34,35]. We observed that administration of excess T3 in the early postnatal period (P0 or P1) caused a disturbance in the arrangement of the stereocilia of HCs, while the stereocilia showed normal structure in the P3 group. As shown in the picture (Figure 3), the stereocilia hair bundles were disordered and varied in length in the T3-treated group. Similar to the effect on hearing, only P0–P2 administration of excess T3 resulted in abnormal stereocilia development. In addition, we observed the reduced function of MET channels located at the apical junction of hair cell stereocilia in the P0 group (Figure 4A,B). Additionally, lower DPOAE levels were also found in the P0 group (Figure 4C,D). This evidence indicated that the OHC abilities of mechanoelectrical transduction and amplification were both significantly impaired. Combined with analysis of the audiological phenotype and pathological phenotype, the results suggested that the disturbance of HC stereocilia and impaired function of OHCs were the main causes of hearing loss caused in the P0 and P1 groups. Based on the above results, excess T3 during the very early stage after birth does not affect HC survival but does cause dysfunction of HCs with abnormal development of stereocilia, which would be a novel mechanism of thyroid hormone-induced hearing loss. TRs, deiodinase, and thyroid hormone transporter are widely expressed in the cochlea [30,36], which suggests that cochleae are the targets of thyroid hormone regulation of inner ear development. Forrest et al. reported that T3 regulates cochlear remodeling, which involves premature regression of the GER [18]. However, the effect of T3 on the remodeling of the OC during early development has not been further explored. Here, we observed that treatment with T3 in the early development stage (P0 or P1) resulted in the overproduction of DCs. Immunostaining results showed that these cells were connected with adjacent DCs by gap junctions. Microtubules, labeled by acetylated α-tubulin, were found in the body and phalangeal processes of the cells. This indicated that these Deiter-like cells may be functioning normally and can communicate intercellularly with adjacent SCs. We further speculate that they may be used as the reserve of DCs which can support new regenerated OHCs. Previous studies mainly focused on regulating SC proliferation by regulating proliferation-related genes. Our study showed that endocrine signals also contribute to the regulation of SC proliferation and development. In addition, T3 administration at P3 did not affect the number of DCs, suggesting that there was a narrow time window during which T3 regulated the proliferation of SCs. In adult mammals, damage to sensory cells in the inner ear causes permanent hearing loss because degeneration of HCs is irreversible, whereas HCs can spontaneously regenerate from supporting cells (SCs) after injury in birds and fish [37]. Recent studies have shown that HCs can also be regenerated from SCs in newborn mice [38,39,40], however this spontaneous regenerative ability rapidly diminishes with age. Current research suggests that there are two mechanisms for HC regeneration in mammals, one of which is the direct trans-differentiation of SCs into new HCs [41]. The second mechanism involves the SCs or progenitor cells of the inner ear proliferating and then differentiating into new HCs [42,43,44]. The common feature of both pathways is that the new HCs are derived from SCs, which suggests that SCs in the inner ear are the key factor necessary for HC regeneration. Therefore, increasing the number of SCs is an important step in achieving HC regeneration. Multiple signaling pathways (Wnt, Notch, FGF, IGF, and Shh) are involved in the development and proliferation of SCs, and regulation of related genes leads to an increase in the number of SCs in the inner ear [45,46,47]. Our results reveal that endocrine signals regulate the proliferation of inner ear SCs during critical periods of cochlear development, providing a reference to coordinate the multi-factor regulation of SC proliferation and HC regeneration. Recent studies have shown that multiple signaling pathways are involved in regulating the development of HCs and SCs, among which the Notch signaling pathway plays an important role in this process [48]. In the sensory epithelium of the inner ear, HCs express the Notch ligands Dll1, Dll3, Dll4, Jag1, and Jag2, while SCs express Notch downstream genes including Hes1, Hes5, Hey1, Hey2, and Heyl. Notch-mediated lateral inhibition maintains SCs in a quiescent state, and suppression of Notch signaling by drugs or genetic ablation of Notch effector genes leads to excessive formation of HCs or overproduction of SCs [49,50]. Hes1, Hes5, and Hey1 are three of the important Notch downstream transcription factors, and knock-out of Hes1, Hes5, and Hey1 in the inner ear results in extra HCs accompanied by overproduction of SCs [46,51,52]. In our study, real-time quantitative PCR results showed that the expression of genes related to the Notch signaling pathway including Hes1, Hes5, and Hey1 was significantly downregulated. Therefore, the T3-induced overproduction of SCs may be directly related to notch downregulation. We did not find any expression changes of FGF signaling pathways, which suggests that the phenotype of overproduction of SCs induced by T3 might not involve FGF pathways. In addition, the expression of individual genes in some classical pathways that regulate DC proliferation was significantly altered, such as Smad4, Bmpr1b, Ltbp1 Lgr5, and Wnt2b which were significantly downregulated, but the significance of these gene changes remains unclear. In the future, the effects of T3 on more pathways related to inner ear development remain to be explored. Expression of the transcription factor Sox2 was significantly downregulated in the T3 group. Based on the characteristics of Sox2CreER/+ mice with Sox2 haploinsufficiency [26], we constructed a mouse model of T3 combined with downregulation of Sox2 by giving T3 to Sox2CreER/+ mice. The results showed that excess T3 treatment combined with downregulation of Sox2 not only resulted in overproduction of DCs but also led to a large number of OPCs. In cochlear development, the formation of the tunnel of Corti is a milestone in OC maturation. These ectopic OPCs resulted in a great change in the morphology of the normal OC. This phenomenon indicates that T3 combined with local transcription factors (such as Sox2) may regulate and even induce the formation of the complex spatial structure of the OC. The key signaling pathway mediating SC proliferation and remodeling of the fine structure of the OC induced by T3 still needs further study. The idea that endocrine signaling may combine with gene programming to regulate cochlear development and SC proliferation is a novel proposal that will open up new aspects of the field of study and potentially lead to the development of new therapies. In general, our results show that excess T3 given at an early stage (P0 or P1) leads to severe hearing loss with abnormal stereocilia alignment and HC mechanosensory dysfunction. However, the molecular mechanism by which T3 induces the abnormal development of the stereocilia of OHCs remains unclear. The key molecules of T3 leading to abnormal stereocilia of OHCs need to be further explored. Moreover, overproduction of Deiter-like cells and a series of genes related to the development of cochlear sensory epithelium were significantly downregulated in the T3 group, but the significance of these gene changes remains unclear. C57BL/6J mice were approved by the Committee of Tongji Medical College, Huazhong University of Science and Technology. Neonatal mouse pups were subcutaneously injected with 2.0 µg of T3 (T2877, Merck KGaA, Darmstadt, Germany) in a volume of 10 µL, or the equivalent volume of saline, at P0 (the P0 group), P1 (the P1 group), or P3 (the P3 group). The concentration and total dose of T3 were based on previous studies and combined with data from our preliminary experiment; mice at this dose show an obvious audiological phenotype without causing gross developmental abnormalities [30]. Both female and male neonatal mouse were included in the experiment and randomly grouped. Mice without T3 treatment were saved as a control group (n = 4 in each group). The preparation of T3 was performed strictly in accordance with the manufacturer’s instructions. Operators wore masks and gloves for self-protection, and waste disposal was standardized. All mice were raised in the specific-pathogen free (SPF) Experimental Animal Center and housed at 22 ± 1 °C under a standard 12 h light/dark cycle and were allowed free access to water and a regular mouse diet. The Sox2 haploinsufficient mice were a gift from Prof. Zhang at Southeast University in China. This line (Sox2CreER/+) was generated as an inserted targeted mutation in the single exon of the Sox2 gene, resulting in Sox2 haploinsufficiency [26,53]. Details of this line are given in the study by Zhang et al. [41]. Sox2 haploinsufficient mice treated with T3 at P0 (the Sox2 haplo+T3 group) were used to investigate their combined effects on cochlear development. The genotyping primers for Sox2CreER/+mice were as follows: wild type (F) 5′-CTAGGCCACAGAATTGAAAGATCT-3′; wild type (R) 5′-GTAGGTGGAAATTCTAGCATCATCC-3′; mutant (F) 5′-GCG GTCTGGCAGTAAAAACTATC-3′; mutant (R) 5′-GTGAAACAGCAT TGCTGTCACTT-3′. The auditory thresholds of different groups were determined by ABR detection at P18 (n = 4 mice in each group). The details of the ABR test were as described in our previous study [54]. Briefly, the mice were deeply anesthetized and three subcutaneous electrodes were placed at the vertex of the skull, the tested ear, and the contralateral ear. Click and tone burst stimuli at frequencies of 8, 16, 24, 32, and 40 kHz were generated. The responses were recorded and determined by decreasing sound intensities from 90 dB in 10 dB steps, which narrowed to 5 dB steps when near the threshold. The lowest sound intensity that could be recognized was determined to be the auditory threshold. DPOAE was measured at P20 (n = 5 mice in each group). The details of the DPOAE test were as described in our previous study [55]. For activated caspase-3 immunostaining, mice were anesthetized and sacrificed at P6 or P11. For counting cochlear HCs and DCs, mice (n = 4 in each group) were sacrificed at P18. The cochleae were carefully dissected in 0.01 M PBS and then fixed in 4% paraformaldehyde. For flattened cochlear preparations, the samples were rinsed three times with PBS and decalcified with 10% disodium EDTA at 4 °C for two days. Each stretched cochlear preparation was carefully dissected and incubated in blocking solution at room temperature for 1 h, then incubated with polyclonal rabbit anti-myosin 7a antibody (1:500 dilution, 25–6790, Proteus Bio-Sciences, Ramona, CA, USA), polyclonal goat anti-Sox2 antibodies (1:100 dilution, sc-17320, Santa Cruz Biotechnology, Santa Cruz, CA, USA), monoclonal rabbit anti-α-tubulin antibody (1:200 dilution, ab179484, Abcam, Cambridge, UK), or polyclonal rabbit anti-Cx30 antibodies (1:200 dilution, 40–7400, Invitrogen, Carlsbad, CA, USA). After washing with PBST three times, the samples were incubated with fluorescent secondary antibodies (1:200 dilution, ANT032, Antgene, Wuhan, China) for 2 h in the dark. Phalloidin (P5282, Sigma, St. Louis, MO, USA) was used for fluorescent visualization of HC F-actin, and nuclei were labeled with DAPI (C1005, Beyotime Biotechnology, Shanghai, China). All images were scanned with a laser scanning confocal microscope (Nikon, Tokyo, Japan). The distance between OPCs and IPCs was measured using Image J software (Version 1.48, National Institutes of Health, Bethesda, MD, USA). For outer hair cell and DCs counting, cells were counted from 60 X images taken from the apex, middle, and base of the basilar membrane. The detailed methods for TEM have been described previously [55]. Briefly, mice were anesthetized and sacrificed at P18 (n = 4 mice in each group). After decalcification with 10% disodium EDTA for 48 h, each sample was then immersed in 1% osmium tetroxide to post-fix for 1 h. Samples were dehydrated through a graded ethanol series, before embedding in resin. Sections (1.5 μm in thickness) were stained with toluidine blue (89640-5G, Sigma-Aldrich, St. Louis, MO, USA) for observation, and ultrathin sections were stained with uranyl acetate and lead citrate and examined by TEM. The morphology of HC stereocilia was observed by SEM at P18 (n = 4 mice in each group). As previously described [54], after fixation and decalcification, the cochleae were carefully dissected to expose the basilar membrane. Then, the samples were dehydrated in increasing ethanol concentrations, dried (HCP-2, Critical Point Dryer, HITACHI, Tokyo, Japan), and sputter-coated with a layer of gold (Eiko Engineering, Tokyo, Japan). Stereocilia bundles were observed in the three turns of the cochlea. Images were captured using a scanning electron microscope (VEGA 3 LMU, Tescan, Brno, Czech Republic). FM1-43 loading of HCs was used to assess the function of mechano-transduction channels. Mice (n = 4 in each group) were sacrificed at P18, and cochleae were quickly dissected from the temporal bones. The samples were incubated in a culture loaded with 4 µM FM1-43 (T35356, Invitrogen) for 30 s, and then fixed in 4% paraformaldehyde for 1 h. Samples were washed with 0.01 M PBS three times before imaging with a confocal microscope; all operations were performed at room temperature. DAPI was used for nuclear staining. Next, 40 OHCs were selected from four mice in each group for fluorescence quantification. The intake of FM1-43 was determined by mean fluorescence intensity. Neonatal mice were injected with T3 at P0 and P1, then sacrificed at P4. The cochleae were removed and dissected in cold Hanks’ balanced salt solution (H1045, Solarbio, beijing, China). The membranous cochlear duct sourced from one cochlea was used to generate one sample. The detailed methods for the RNA extraction and reverse transcription were as described previously [56]. Total RNA was extracted from the collected tissues using an RNAprep Pure Tissue Kit (Tiangen Biotech Co., Ltd., Beijing, China) and was reverse transcribed using a PrimeScript RT Reagent Kit with gDNA eraser (Takara Bio Inc. Shiga, Japan). RT-qPCR was performed in a Roche LightCycler 480 instrument (Roche Diagnostics Ltd., Basel, Switzerland). Real-time qPCR conditions were an initial denaturing step of 15 s at 95 °C followed by 40 cycles of 15 s denaturation at 95 °C, 60 s annealing at 60 °C, and 20 s extension at 72 °C. The transcriptional expression was normalized to the expression of GAPDH and the relative expression level between the control and T3 group was calculated using the 2−∆∆CT method [41]. The real-time qPCR primers are shown in Supplementary Table S1. Data are presented as means ± SD, statistical analyses were conducted using GraphPad Prism (Version 8.0, GraphPad Software Inc., La Jolla, CA, USA) and SPSS software (version 19, IBM SPSS Statistics, IBM Corp., Armonk, NY, USA). One-way ANOVA followed by a Dunnett multiple comparisons test was used when there was only one factor. Two-way-ANOVA multiple comparisons test was used when two factors were involved. p < 0.05 was considered to be statistically significant. Our results suggest that (I) T3 is an exogenous factor involved in mouse stereocilia formation and HC functions; (II) T3 regulates the production of mouse SCs during critical periods of cochlear development; and (III) the combination of T3 and Sox2 haploinsufficiency regulates not only the number of SCs but also the structure of the OC. Our findings provide new evidence for the role of endocrine signaling in regulating the development of mouse cochlear sensory epithelium.

PMC10003543

Anthony Cannavicci,Qiuwang Zhang,Michael J. B. Kutryk

The Potential Role of MiRs-139-5p and -454-3p in Endoglin-Knockdown-Induced Angiogenic Dysfunction in HUVECs

03-03-2023

hereditary hemorrhagic telangiectasia,endoglin,microRNA,endothelial cell,angiogenesis

Hereditary hemorrhagic telangiectasia (HHT) is a rare genetic disease characterized by aberrant angiogenesis and vascular malformations. Mutations in the transforming growth factor beta co-receptor, endoglin (ENG), account for approximately half of known HHT cases and cause abnormal angiogenic activity in endothelial cells (ECs). To date, how ENG deficiency contributes to EC dysfunction remains to be fully understood. MicroRNAs (miRNAs) regulate virtually every cellular process. We hypothesized that ENG depletion results in miRNA dysregulation that plays an important role in mediating EC dysfunction. Our goal was to test the hypothesis by identifying dysregulated miRNAs in ENG-knockdown human umbilical vein endothelial cells (HUVECs) and characterizing their potential role in EC function. We identified 32 potentially downregulated miRNAs in ENG-knockdown HUVECs with a TaqMan miRNA microarray. MiRs-139-5p and -454-3p were found to be significantly downregulated after RT-qPCR validation. While the inhibition of miR-139-5p or miR-454-3p had no effect on HUVEC viability, proliferation or apoptosis, angiogenic capacity was significantly compromised as determined by a tube formation assay. Most notably, the overexpression of miRs-139-5p and -454-3p rescued impaired tube formation in HUVECs with ENG knockdown. To our knowledge, we are the first to demonstrate miRNA alterations after the knockdown of ENG in HUVECs. Our results indicate a potential role of miRs-139-5p and -454-3p in ENG-deficiency-induced angiogenic dysfunction in ECs. Further study to examine the involvement of miRs-139-5p and -454-3p in HHT pathogenesis is warranted.

The Potential Role of MiRs-139-5p and -454-3p in Endoglin-Knockdown-Induced Angiogenic Dysfunction in HUVECs Hereditary hemorrhagic telangiectasia (HHT) is a rare genetic disease characterized by aberrant angiogenesis and vascular malformations. Mutations in the transforming growth factor beta co-receptor, endoglin (ENG), account for approximately half of known HHT cases and cause abnormal angiogenic activity in endothelial cells (ECs). To date, how ENG deficiency contributes to EC dysfunction remains to be fully understood. MicroRNAs (miRNAs) regulate virtually every cellular process. We hypothesized that ENG depletion results in miRNA dysregulation that plays an important role in mediating EC dysfunction. Our goal was to test the hypothesis by identifying dysregulated miRNAs in ENG-knockdown human umbilical vein endothelial cells (HUVECs) and characterizing their potential role in EC function. We identified 32 potentially downregulated miRNAs in ENG-knockdown HUVECs with a TaqMan miRNA microarray. MiRs-139-5p and -454-3p were found to be significantly downregulated after RT-qPCR validation. While the inhibition of miR-139-5p or miR-454-3p had no effect on HUVEC viability, proliferation or apoptosis, angiogenic capacity was significantly compromised as determined by a tube formation assay. Most notably, the overexpression of miRs-139-5p and -454-3p rescued impaired tube formation in HUVECs with ENG knockdown. To our knowledge, we are the first to demonstrate miRNA alterations after the knockdown of ENG in HUVECs. Our results indicate a potential role of miRs-139-5p and -454-3p in ENG-deficiency-induced angiogenic dysfunction in ECs. Further study to examine the involvement of miRs-139-5p and -454-3p in HHT pathogenesis is warranted. Hereditary hemorrhagic telangiectasia (HHT) is a rare genetic disease inherited in an autosomal dominant fashion that can lead to life-threatening vascular dysplasia. Approximately 1 in 5000 to 8000 people are affected globally [1]. HHT patients can develop vascular malformations that form a direct connection between arteries and veins absent of capillaries, called telangiectasias and arteriovenous malformations (AVMs) [2,3]. Telangiectasias are superficial dilated blood vessels that form on the skin and mucocutaneous tissue [4]. Approximately 95% of patients with HHT develop epistaxis due to nasal telangiectasias [5]. AVMs are greater in size and can develop in various locations, including the lungs, brain, liver and spine [6]. Severe complications can arise from untreated AVMs, including hypoxia, brain abscess, high-output cardiac heart failure, hypertension and ischemic and hemorrhagic stroke [6]. There is no cure for HHT, and effective pharmacological therapies are limited. It was found that mutations in three genes cause HHT, including endoglin (ENG, chromosomal locus 9q34) [7], activin-receptor like kinase 1 (ACVRL1, also known as ALK1, chromosomal locus 12q1) [8] and mothers against decapentaplegic homolog 4 (SMAD4, chromosomal locus 18q21) [9]. Additionally, mutations in growth/differentiation factor 2 (GDF2, chromosomal locus 10q11) [10] and Ras p21 protein activator 1 (RASA1, chromosomal locus 5q14) [10] create HHT-like syndromes. ENG and ACVRL1 mutations are responsible for approximately 70–90% of confirmed HHT cases and lead to HHT Type 1 and 2, respectively [11,12,13]. SMAD4 mutations are responsible for approximately 1–2% of HHT cases and can result in a combined juvenile polyposis-HHT syndrome (JP-HHT) [14]. There are over 850 known disease-causing mutations in ENG, ACVRL1 and SMAD4 (https://arup.utah.edu/database/HHT/, https://arup.utah.edu/database/SMAD4/SMAD4_welcome.php, access date: 3 November 2021) that most commonly include missense mutations, although single base pair changes, large deletions, duplications, frameshifts and substitutions have also been documented [15]. ENG, ACVRL1, SMAD4 and GDF2 are all involved in the transforming growth factor beta/bone morphogenetic protein (TGFβ/BMP) signaling pathway, while RASA1 predominately regulates PI3K/Akt signaling [16]. These pathways are integral in the regulation of various cellular processes, including growth, differentiation, apoptosis and, importantly, endothelial cell (EC) function and angiogenesis. The pathogenic role of these mutations has been confirmed in mouse models, where the loss of ENG, ACVRL1 or SMAD4 results in various vascular defects [17,18]. ACVRL1 encodes for a TGFβ receptor I that is mostly expressed on endothelial, lung and placental cells. SMAD4 is a downstream effector of the TGFβ/BMP signaling pathway that upon activation translocates to the nucleus to regulate gene expression. ENG, predominantly expressed in the endothelium, activated monocytes and macrophages, is a co-receptor that ensures a high-affinity bond between ligands and TGFβ receptors I/II. MicroRNAs (miRNAs) are short non-coding RNA molecules, approximately 21–25 nucleotides long, that regulate gene expression in a post-transcriptional manner [19]. Since their discovery in 1993 by the Ambros and Ruvkin groups, over 2000 miRNAs have been identified [20,21]. MiRNAs have been shown to be involved in a vast array of cellular processes regulating approximately 30% of known genes [22,23,24]. Processed in the nucleus and cytoplasm by endoribonucleases, such as RNAase III, they exert their effects through the interaction with the 3′ untranslated region (UTR) of messenger RNA (mRNA) [25]. Typically, human miRNAs bind imperfectly and silence mRNAs through the blockage of translational machinery [22]. These low-fidelity molecules have been shown to target tens to hundreds of genes, while groups of miRNAs expressed from the same transcript, known as clusters or families, share similar target homology [22,26]. MiRNAs are involved in almost every cellular process and have been implicated in the pathogenesis of human diseases [27]. They have been shown to be reliable biomarkers, especially in oncology, and are being investigated as novel therapeutic targets [28,29]. Endoglin (ENG) is primarily expressed in endothelial cells (ECs), and loss of ENG has been shown in numerous studies to result in abnormal angiogenic function in ECs [30]. However, how ENG deficiency contributes to EC dysfunction remains to be fully understood. We hypothesized that ENG depletion results in miRNA dysregulation that contributes to EC dysfunction. To test this hypothesis, we performed a miRNA microarray analysis and RT-qPCR to identify dysregulated miRNAs in ENG-knockdown human umbilical vein endothelial cells (HUVECs) and further characterize their potential role in EC function. The N shown in all figures is the number of independent experiments. ENG-siRNA transfection significantly depleted ENG protein in HUVECs compared with that in non-transfected and control siRNA-transfected HUVECs as shown by Western blot analysis (Figure 1). A TaqMan miRNA microarray with 377 human miRNA targets was employed to identify potentially dysregulated miRNAs in ENG-knockdown HUVECs compared with negative control siRNA HUVECs. MiRNAs that had less than a 1.5-fold change and a cycle threshold (Ct) value ≥ 30 were systematically excluded (Figure 2). Three independent miRNA microarray analyses were performed for ENG-knockdown and control HUVECs, that identified a total of 32 miRNAs as potentially downregulated (Table 1) and none as upregulated in ENG-knockdown HUVECs. The MicroRNA Microarray Card A v2.0 used in this study detects both non-angiogenic and angiogenic miRNAs. Of the 32 potentially dysregulated miRNAs identified by the array analysis, those with unknown EC angiogenic activity, i.e., miR-99a-5p, miR-99b-5p and miR-574-3p, were not chosen for further study. MiRNAs, whose downregulation has been documented in the literature to promote tube formation in ECs, which is discordant with angiogenic dysfunction seen in ENG-deficient ECs, were not characterized further either, such as miR-191-5p, miR-125b-5p, miR-31-5p, etc. [31,32,33]. MiR-126-3p, one of the best-characterized angiogenic miRNAs in ECs [34], was not investigated further, as a previous study showed that ENG depletion does not affect the target genes of miR-126-3p in HUVECs [35]. Eventually, miRs-let-7b, -16-5p, -21-5p, -139-5p and -454-3p were selected for RT-qPCR validation. As shown in Figure 3, miRs-139-5p and -454-3p were significantly reduced (p = 0.0048 and p = 0.0062, respectively) in ENG-knockdown HUVECs, while the levels of miRs-let-7b, -16-5p and -21-5p were not significantly different as compared with those in controls. MiR-139-5p demonstrated a 4.4-fold decrease, and miR-454-3p demonstrated a 2-fold decrease in ENG-knockdown HUVECs, respectively. In the context of HHT, the literature demonstrates that HHT Type 1 (ENG-deficient) ECs have increased rates of proliferation and viability [30]. To understand the role miRs-139-5p and -454-3p may play in HUVEC function, we inhibited these miRNAs individually and assessed HUVEC viability and proliferation with a CCK8 assay. MiRs-139-5p and -454-3p were both successfully downregulated after miRNA inhibition as shown in Supplementary Figure S2. The CCK8 assay demonstrated that the inhibition of miR-139-5p or miR-454-3p had no effect on either HUVEC viability or proliferation (Figure 4A,B, respectively). For viability, the inhibition of miRs-139-5p or -454-3p returned an OD of 0.53 ± 0.12 and 0.51 ± 0.11, respectively, compared to the negative control’s OD of 0.48 ± 0.14. In terms of proliferation, the inhibition of miRs-139-5p or -454-3p returned an OD of 0.41 ± 0.16 and 0.40 ± 0.17, respectively, compared to the negative control’s OD of 0.40 ± 0.16. Apoptotic events, determined by the flow cytometric detection of AV, were unchanged when miR-139-5p or miR-454-3p were inhibited in HUVECs compared with those in negative controls (Figure 5). The percentages of double-stained (+/+) or AV+/PI+ events or late apoptotic/necrotic cells were 16.8 ± 4.22, 18.45 ± 3.20 and 16.97 ± 3.325 for negative controls, miR-139-5p inhibition and miR-454-3p inhibition, respectively (Figure 5). The percentages of AV-stained (−/+) or PI−/AV+ events or early apoptotic cells were 29.95 ± 11.54, 30.92 ± 13.00 and 27.47 ± 9.99 for negative controls, miR-139-5p inhibition and miR-454-3p inhibition, respectively (Figure 5). Necrotic cells or only PI-stained events were barely detectable. It has been well established in both in vitro and in vivo models that the loss of ENG results in perturbed EC migration [36,37,38]. To further understand the role miR-139-5p or miR-454-3p plays in EC function, we assessed cell migration with an Ibidi wound healing assay. The inhibition of miR-454-3p in HUVECs had no effect on migration rates compared with that in negative controls shown in Figure 6A. Interestingly, the inhibition of miR-139-5p resulted in significantly increased rates of migration (Figure 6B), as determined by the percentage (%) of open wound area, at 3, 6, 9 and 12 h compared with that in negative controls (Figure 6C). No significant differences in the percentage of open wound area were found at the start of the assay (0 h) between the miRNA inhibitor- and control-transfected HUVECs (Figure 6A,B). Images of cell migration among groups at 3, 6, 9 and 12 h are shown in Figure 6D. The role of ENG in angiogenesis has been well established in the general literature [30] as well as in the context of HHT, especially in mouse models [17]. However, to our knowledge, only Fernandez-L et al. have demonstrated deficient in vitro tube formation of HHT Type 1 and 2 blood outgrowth ECs (BOECs) [39]. Interestingly, they determined that the reduced ability of tube formation is correlated with reduced ENG expression in both HHT Type 1 and 2 BOECs [39]. Whether miRs-139-5p and -454-3p contribute to EC dysfunction in this regard remains to be clarified. We investigated how the inhibition of miR-139-5p or miR-454-3p affected the angiogenic capacity of HUVECs with an in vitro tube-formation assay. A significant reduction of tube formation was observed for the inhibition of miR-139-5p or miR-454-3p compared with that in negative controls based on four parameters: segments, nodes, junctions and meshes (Figure 7A). A detailed description of these parameters can be found in Supplementary Figure S3. In brief, segments refer to connected tubes, nodes are central connecting points, junctions are points with three or more connecting segments and meshes are complete ring structures. The number of segments was 90 ± 32 (p < 0.01), 103 ± 30 (p < 0.05) and 141 ± 33 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7B). The number of nodes was 237 ± 83 (p < 0.05), 254 ± 73 (p < 0.05) and 344 ± 80 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7C). The number of junctions was 67 ± 22 (p < 0.01), 75 ± 20 and 99 ± 23 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7D). Lastly, the number of meshes was 27 ± 11 (p < 0.01), 32 ± 11 (p < 0.05) and 46 ± 12 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7E). Next, we sought to explore if the overexpression of miRs-139-5p and -454-3p could rescue ENG-knockdown-induced HUVEC dysfunction. Firstly, we confirmed that HUVECs with ENG-knockdown had a significant reduction in tube formation compared with that in HUVECs transfected with control siRNA (wild type, WT), shown in Figure 8. Segments, nodes, junctions and meshes were all significantly decreased (p < 0.05) in ENGsi HUVECs (Figure 8B). For the functional rescue assay, miRs-139-5p and -454-3p were introduced into ENGsi HUVECs by transfection with miR mimics (Supplementary Figure S4). Most notably, the simultaneous overexpression of miR-139-5p and miR-454-3p in ENG-knockdown HUVECs rescued HUVEC dysfunction, shown in Figure 9. Segments, nodes, junctions and meshes were all significantly increased in ENG-knockdown HUVECs with miR-139-5p/-454-3p mimics compared with those in negative control mimics (Figure 9B). ENG mutations cause EC dysfunction, leading to HHT Type 1. Animal studies have identified ECs as the main pathological cell in HHT [36,40]. Inducible EC-specific ENG knockout in mice results in retinal AVMs and enlarged veins [36]. Garrido-Martin et al. demonstrated the formation of skin AVMs in EC-specific ENG-knockout mice following wounding [40]. The importance of ENG in EC function has also been highlighted in various EC models, including HUVECs and HHT-patient-derived BOECs, where loss of ENG resulted in enlarged or elongated morphology, dysregulated cellular proliferation, perturbed migration and polarity, and reduced tube formation [30,37,38,39,41,42]. Fernandez-L et al. showed that BOECs derived from HHT Type 1 patients demonstrate decreased tube formation and a disorganized actin cytoskeleton [39]. These researchers also demonstrated that the reduced ability of tube formation is correlated with reduced ENG expression in both HHT Type 1 and 2 BOECs [39]. The aim of this study was to explore the role of miRNAs in EC dysfunction caused by ENG depletion, which has rarely been documented. We performed a microarray assay to identify potentially dysregulated miRNAs for further analysis. Of the five miRNAs measured by RT-qPCR, miR-139-5p and miR-454-3p were found to be significantly downregulated in ENG-knockdown HUVECs, in line with the microarray data. The inhibition of miRs-139-5p or -454-3p reduced the angiogenic capacity of HUVECs as shown by a tube formation assay. Most notably, the overexpression of miRs-139-5p and -454-3p rescued ENG-knockdown-induced angiogenic dysfunction in HUVECs. These novel findings underscore the critical role miRs-139-5p and -454-3p may play in EC function and HHT pathogenesis. A plethora of miRNAs have been identified as key regulators of EC function and ultimately, the angiogenic process. The EC-specific knockdown of Dicer, an endoribonuclease involved in miRNA biogenesis, resulted in the dysregulation of various EC-specific genes, including vascular endothelial growth factor (VEGF) receptor 2 and endothelial nitric oxide synthase [43]. The TGFβ/BMP signaling pathway has also been shown to both be regulated by and regulate various miRNAs in a multitude of cell types and disease states [44,45]. MiR-132 has been demonstrated to be upregulated during the inflammatory phase of wound healing in direct response to TGFβ1/2 and enhance the activation of TGFβ signaling by targeting Smad7 [46]. Previous work from our laboratory has demonstrated that circulating miR-210 may be a potential biomarker for the detection of untreated pulmonary AVMs [47]. We have also shown that miR-361-3p and -28-5p were significantly decreased in peripheral blood mononuclear cells (PBMCs), and miR-132-3p was downregulated in myeloid angiogenic cells from HHT patients [48,49]. Tabruyn et al. have shown that circulating miR-205 is significantly decreased and -27a significantly increased in HHT patients [50]. Recently, Ruiz-Llorente et al. identified circulating miR-370 and -10a as candidate biomarkers for the differentiation of HHT Type 1 and 2, respectively [51]. These data and the findings in the present study suggest that, apart from their widely studied role in cancer [52,53,54,55], miRNAs are involved in HHT pathogenesis and may also serve as biomarkers for HHT diagnosis. MiR-139-5p (chromosomal locus 11q13.4) has been extensively studied in the diagnosis, prognosis and tumorigenesis of various cancers, including chronic myeloid leukemia, non-small cell lung carcinoma, prostate cancer, breast cancer and glioblastoma [53]. In tumorigenesis, miR-139-5p predominately acts as a tumor suppressor and is involved in PI3K/Akt, Wnt/β-catenin, RAS/MAPK and TGFβ/BMP signaling, to name a few [53]. The role of miR-139-5p in EC function has also been explored, albeit to a lesser extent. Similarly, miR-454-3p (chromosomal locus 17q22) has also been extensively studied in oncology [54,55,56] but to an even lesser extent in EC function. Previous studies have reported that these miRNAs are critical in EC function yet have demonstrated contradicting roles. Zhang et al. demonstrated that the inhibition of miR-139-5p suppresses VEGF-induced neovascularization of human microvascular endothelial cells by targeting phosphatase and tensin homolog (PTEN) [57]. Interestingly, they also found that miR-139-5p knockdown decreases cell viability and migration [57]. In contrast, Luo et al. reported that the inhibition of miR-139-5p in HUVECs and diabetic-derived BOECs results in increased tube formation by targeting c-Jun [58]. Similar to our findings, the authors also reported that the inhibition of miR-139-5p increases HUVEC migration [58]. Papangeli et al. showed increased HUVEC migration with miR-139-5p inhibition despite demonstrating that the intravenous administration of miR-139-5p inhibitors in the retina of a mouse model results in reduced vascularized area, radial expansion and branch points, corroborating our in vitro findings [59]. Li et al. found that miR-139-5p inhibition in primary endothelial cell cultures from pancreatic tumors results in reduced tube formation and migration [60]. There are few reports on the role of miR-454-3p in EC function. Xia et al. demonstrated that miR-454-3p inhibition results in increased HUVEC tube formation [55]. However, it is difficult to determine any specific effects of miR-454-3p inhibition since tube formation was conducted in the presence of a long non-coding RNA silencer and conditioned tumor medium. Liao et al. demonstrated that the inhibition of miR-454-3p reduces human aortic endothelial cell viability and increases apoptosis [61]. The variability seen in the literature regarding the role of the miRNAs implicated in EC dysfunction can be attributed to their diverse nature. MiRNAs are extremely context-specific and promiscuous biomolecules with tens to hundreds of targets. Their role in any context is dependent on their relative expression, the relative expression of their targets and the crosstalk of multiple regulatory pathways. Different culturing protocols, EC subtypes, experimental conditions and methodologies could all contribute to variable results. Despite the complexity of miRNA function, it is clear that miRs-139-5p and -454-3p play a critical role in EC function, where their differential expression leads to EC dysfunction. Limitations of this study include: (1) only one type of EC, i.e., HUVECs, was used, and (2) targets of miRs-139-5p and -454-3p were not explored. To date, the role of any one miRNA in HHT pathogenesis has yet to be fully explored. The present study has demonstrated three novel findings: (1) ENG-knockdown HUVECs had a dysregulated miRNA profile, (2) miRs-139-5p and -454-3p were found to be significantly decreased in ENG-knockdown HUVECs, and (3) miRs-139-5p and -454-3p were critical for normal HUVEC function. Most importantly, we have shown that the inhibition of miR-139-5p or miR-454-3p resulted in angiogenic dysfunction similar to that shown in HHT Type 1 BOECs and that the overexpression of these miRNAs rescued ENG-knockdown-induced HUVEC dysfunction. The downregulation of miRs-139-5p and -454-3p in ENG-knockdown endothelial cells potentially serves as a novel mechanism in HHT pathogenesis and may be crucial in the identification of novel therapeutic targets. Further research is necessary to understand the role of miRNAs in HHT pathogenesis. HUVECs purchased from Lonza (Walkersville, MD, USA) were cultured in fibronectin-coated (10 μg/mL) T25 or T75 flasks at 37 °C and 5% CO2. HUVECs were maintained in complete Endothelial Cell Growth Medium-2 (EGM-2) (Lonza, EGM-2 BulletKit, cat# CC-3162) supplemented with 5% fetal bovine serum (FBS). Cells at 80–90% confluence and ≤ to the fifth passage were used for all experiments. HUVECs were detached with trypsin-EDTA (Multicell Trypsin/EDTA 0.05% trypsin, 0.53 mM EDTA with sodium bicarbonate). HUVECs obtained for this study were tested negative for mycoplasma, bacteria, viruses and fungi by the supplier, and used in low passage. This protocol was adapted from our previous work [35]. Six-well plates were seeded with HUVECs (1.5 × 105 cells/well) and cultured until 60–80% confluence (approx. 24 h). At this point, negative control siRNA- or ENG siRNA-Lipofectamine RNAiMAX complexes were added to each well of cells. The complexes were prepared as follows: 3 μL of 10 μM siRNA (ENG or negative control) and 5 μL of Lipofectamine RNAiMAX were diluted in 250 μL of Opti-MEM reduced serum medium, respectively. These diluted mixes were then combined and incubated for 15 min to allow for complex formation. The complexes were added to cells with 2.5 mL of fresh complete EGM-2 medium (final siRNA concentration: 10 nM). The cells were cultured in the media–complex mixture for 48 h and then used for experimentation. Lipofectamine RNAiMAX (cat# 13778075), Opti-MEM (cat# 31985062), Silencer Select Negative Control No. 2 siRNA (cat# 4390846) and ENG siRNA (cat# 4392420, siRNA ID s4679) were purchased from Thermo Fisher Scientific (Burlington, ON, Canada). Cellular protein was isolated from HUVECs in RIPA Lysis Buffer (25 mM TrisHCl pH 7.6, 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, 0.1% SDS) supplemented with a 100× Halt Protease Phosphatase Inhibitor Cocktail (1:100 dilution, Sigma, Oakville, ON, Canada). Protein concentration was measured via a Bradford assay. Protein separation (50 μg/lane) was conducted by SDS-PAGE (4 to 12% Tris-Glycine gel) and electrically transferred onto a 0.2 μm nitrocellulose membrane. The membrane was blocked in 1× TBST (50 mM TrisHCl, 150 mM NaCl, pH 7.5, 0.1% Tween-20) containing 5% skim milk for 1 h at room temperature followed by primary antibody incubation overnight at 4 °C (ENG, 1:1000 dilution; β-actin, 1:10,000 dilution). After incubation, the membrane was washed twice with 1× TBST for 5 min. The membrane was incubated with secondary antibodies (1:5000 dilution) in a blocking buffer (1× TBST containing 5% skim milk) for 1 h in the dark at room temperature. After incubation, the membranes were washed 3 times with 1× TBST for 15 min. Protein bands were visualized with the Odyssey fluorescence imaging system (LI-COR Biosciences, Lincoln, NE, USA). Densitometry analysis was performed with Image Studio Lite Quantification Software 5.0 (LI-COR Biosciences). β-actin was used as an internal loading control. Primary antibodies used: ENG, Cell Signalling Technologies (Oakville, ON, Canada), mouse, cat# 14606S, clone 3A9 and β-actin, ABclonal Technology (Woburn, MA, USA), rabbit, cat# AC026. Secondary antibodies used: Goat anti-mouse, Thermo Fisher Scientific, cat# A32742 and goat anti-rabbit, LI-COR Biosciences, cat# 926-32211. Total RNA was isolated from HUVECs with a Qiagen RNeasy Mini Kit (cat# 217004, Qiagen, Toronto, ON, Canada). Cells in a well of a 6-well plate were scraped in 700 μL of Qiazol lysis reagent and transferred to a 1.5 mL Eppendorf tube. The mixture was incubated for 5 min at room temperature. After incubation, 140 μL of chloroform was added and shaken vigorously for 15 s. The mixture was incubated at room temperature for 3 min and centrifuged at 12,000× g for 15 min at 4 °C. After centrifugation, 300 μL of the supernatant was carefully extracted without disruption of the interphase. Subsequently, 1.5 volumes or 450 μL of 100% ethanol was added and mixed thoroughly by pipetting. To capture the RNA, 700 μL of this mixture was added to an RNeasy Mini column and centrifuged at 10,000× g for 15 s at 4 °C. The column was then washed with 500 μL of Buffer RPE at 10,000× g for 15 s at 4 °C. This was repeated with a 2 min centrifugation. Then, the column was washed with 100% ethanol and centrifuged for 1 min at 10,000× g at 4 °C. Finally, RNA was eluted with 30 μL of RNase-free water at 10,000× g for 1 min at 4 °C. A NanoDrop 2000 spectrophotometer was used to assess the concentration and quality of RNA before storage at −80 °C. All components used were DNase, RNase and pyrogen-free. To profile miRNAs in HUVECs, a TaqMan Low-Density MicroRNA Microarray (Thermo Fisher Scientific, Card A v2.0, cat# 4398965) covering 377 human miRNAs was used. Total RNA samples were reverse-transcribed into cDNA with a TaqMan MicroRNA Reverse Transcription (RT) Kit (cat# 4366596) and Megaplex RT Primers. The total volume of the RT reaction was 7.5 μL and comprised 3 μL of total RNA (600 ng), 0.8 μL of Megaplex RT primers (10×), 0.2 μL of dNTPs (100 mmol/L), 1.5 μL of MultiScribe Reverse Transcriptase (50 U/μL), 0.8 μL of 10× RT buffer, 0.9 μL of MgCl2 (25 mmol/L), 0.1 μL of RNase inhibitor (20 U/μL) and 0.2 μL of nuclease-free water. The thermocycling protocol for RT was performed as follows: 40 cycles of 16 °C for 2 min, 42 °C for 1 min, and 50 °C for 1 s followed by 85 °C for 5 min and 4 °C hold. The total reaction volume for PCR was 900 μL and comprised 450 μL of 2× TaqMan Universal PCR Master Mix (no AmpErase UNG), 444 μL of nuclease-free water and 6 μL of Megaplex RT product. Then, 100 μL of diluted RT product was dispensed in each of the 8 ports of the Array Card A v2.0. The card was sealed and centrifuged twice at 1200 rpm for 1 min. PCR was performed on a ViiA 7 Real-Time PCR System (Applied Biosystems, Waltham, MA, USA) with a 384-well TaqMan Low-Density Array block. The results were analyzed using RQ Study software 1.4 (Thermo Fisher Scientific) and normalized to U6 snRNA as determined by the NormFinder Excel plugin (https://moma.dk/normfinder-software, access date: 23 February 2021). Select miRNAs of interest were determined based on a fold change of 1.5 or greater and <30 Ct value [62,63]. As RT for microarray analysis was completed in a single reaction tube using pooled primers (https://assets.fishersci.com/TFS-Assets/LSG/manuals/cms_054742.pdf, access date: 9 December 2022) that may result in mis-priming between two different primers or between a primer and an RNA template, reducing the accuracy of array results, RT-qPCR was performed to measure each select miRNA to validate the array data. The RT reaction was carried out with a total volume of 15 μL consisting of 7 μL of RT master mix, 3 μL of 5× RT primer and 5 μL of RNA sample (total RNA 20 ng). For each reaction, the RT master mix was prepared as follows: 0.15 μL of 100 mM dNTPs, 1 μL of (50 U/μL) MultiScribe Reverse Transcriptase, 1.5 μL of 10× reverse transcription buffer, 0.19 μL of (20 U/μL) RNase inhibitor and 4.16 μL of nuclease-free water. RT was performed on a Veriti 96-well thermal cycler according to the following protocol: 16 °C for 30 min, 42 °C for 30 min, 85 °C for 5 min and 4 °C hold. PCR was performed in a total volume of 10 μL consisting of 1 μL of RT product, 0.5 ul of 20× miRNA PCR primer, 5 μL of 2×TaqMan Fast Advanced Master Mix and 3.5 μL of nuclease-free water. PCR was performed on a QuantStudio 7 Flex Real-Time PCR System (Thermo Fisher Scientific) according to the following thermocycling protocol: 95 °C for 20 s and 40 cycles of 95 °C for 1 s and 60 °C for 20 s. Relative quantification of the expression of individual miRNAs against endogenous U6 snRNA was carried out. For miRNA inhibitor transfection, six-well plates were seeded with HUVECs (1.5 × 105 cells/well) and cultured until 60–80% confluence (approx. 24 h). MirVana miRNA inhibitors (Thermo Fisher Scientific, cat# 4464084; hsa-miR-139-5p, Assay ID MH11749; hsa-miR-454-3p, Assay ID MH12343) and MiRNA Negative Control #1 (Thermo Fisher Scientific, cat# 4464076) were thawed on ice and spun down before use. MiRNA inhibitor/transfection reagent complexes were generated as follows: 5 μL of Lipofectamine RNAiMAX and 5 μL of 10 μM miRNA inhibitor or negative control were diluted in 125 μL of Opti-MEM reduced serum medium, separately. The diluted reagent and inhibitor were then mixed, incubated for 5 min at room temperature and added to cells replenished with 1.75 mL of fresh complete EGM-2 medium (final miRNA inhibitor concentration: 25 nM). The cells were cultured for 24 h and then used for experimentation. For miRNA mimic transfection, HUVECs were transfected with ENG siRNA and cultured for 24 h as described above. Subsequently, 5 μL of mimics (2.5 μL of 10 μM miR-139-5p plus 2.5 μL of 10 μM miR-454-3p) or 5 μL of miRNA-negative control was used for transfection of ENG-knockdown HUVECs, which was done in the same manner as with miRNA inhibitors. The cells were cultured for another 24 h after mimic transfection for the tube formation assay. A cell-counting kit-8 (CCK8/WST-8) assay was used for the measurement of cellular viability and proliferation (Sigma, cat# 96992). Ninety-six-well plates were seeded with HUVECs (5 × 103 cells/well for viability, and 2.5 × 103 cells/well for proliferation). The cells were cultured for 24 h in complete EGM-2 medium and then transfected as described above. After transfection, the cells were either supplemented with fresh, complete EGM-2 medium (proliferation) or endothelial basal medium-2 (EBM-2) without serum (viability) and cultured for 24 h. WST-8 was then added, and the cells were incubated for 4 h at 37 °C and 5% CO2. Subsequently, the absorbance (450 nm) was measured with a microplate reader (endpoint analysis) and compared between different groups of cells. All conditions were carried out in triplicate. Apoptosis was measured via flow cytometric detection of Annexin V (AV). HUVECs were transfected with MirVana miRNA Inhibitors and Negative Control #1 as described above. Appropriate fluorescence controls were used, including unstained and double-stained (AV and propidium iodide (PI)) negative controls (healthy cells) and unstained, single-stained (AV or PI) and double-stained positive controls (Supplementary Figure S1). Positive controls were generated with hydrogen peroxide (10 mM H2O2) treatment for 1–2 h at 37 °C and 5% CO2. The cells were detached with PBS containing 1 mM EDTA for analysis. Positive controls were spiked with negative controls (approx. 50% cell viability) to ensure a background level of healthy cells for appropriate gating. The cells were resuspended at a concentration of 1 × 103 cells/μL in cold 1× Annexin V Binding Buffer (BD Pharmingen, Mississauga, ON, Canada, cat# 51-66121E). Then, 100 μL of each cell suspension was incubated with either 0.5 μL of Alexa Fluor (APC channel) AV (BioLegend, San Diego, CA, USA, cat# 640911), 1.5 μL of PI (PE-CF594-A channel) (BD Pharmingen, cat# 51-66211E) or both at room temperature for 15 min in the dark. After incubation, the cells were put on ice and supplemented with 200 μL of cold 1× Annexin V Binding Buffer (final volume of 300 μL). The cells were analyzed via flow cytometry immediately after staining on a BD LSRFortessa X-20 Cell Analyzer with BD FACSDiva Software 6.1.2. Analysis of flow cytometric data was conducted with FlowJo 10.8.1 software. Forward/side scatter scatterplots were used to exclude cellular debris and doublets of 1 × 104 recorded events. The cellular migration assay was performed with an Ibidi wound healing assay (culture-insert 2 well, Ibidi, Martinsried, Germany, cat# 81176) in a 12-well plate. HUVECs were cultured, transfected and detached as described above. Ibidi 2-well culture inserts were placed in the center of the well with slight pressure to ensure adhesion. In each well of the Ibidi 2-well culture inserts, 70 μL (28,000 cells) of cells was seeded. The cells were incubated at 37 °C and 5% CO2 for 24 h with fresh, complete EGM-2 medium until confluent. The plate was handled carefully to prevent shaking. The cells were then serum-starved (EBM-2 medium, 0.5% FBS) for 4 h, and the insert was gently removed with sterile tweezers to create an open wound area. The cells were washed with warm phosphate-buffered saline (PBS) and replenished with serum-reduced EBM-2 medium (0.5% FBS). Cell migration was carried out at 37 °C under an atmosphere of 5% CO2 and live-imaged for 12 h with a Hamamatsu Camera and a Zeiss Axio Observer microscope (10× magnification) with Zen Pro 3.6 software (Zeiss Canada Ltd., Toronto, Canada). The images were processed with Zen 3.3 Lite (Blue Edition) and analyzed with TScratch 1.0. The percent of the open wound area of 5 fields was calculated and averaged. All conditions were done in duplicate. Geltrex LDEV-free reduced growth factor basement membrane matrix (Gibco, Burlington, ON, Canada, cat# A1413201) was used. The Geltrex basement membrane matrix was thawed overnight in a 4 °C fridge. Once thawed, it was mixed well and aliquoted (80 μL/well) into a 96-well plate (on ice) with chilled pipette tips. To prevent air bubble formation, the basement membrane was dispensed without a full stop, and the plate was centrifuged at 300× g for 10 min at 4 °C. Then, the coated plate was incubated at 37 °C and 5% CO2 for 30 min. HUVECs were cultured and transfected as described above. The cells were serum-starved for 4 h and detached with trypsin-EDTA, then resuspended at 2 × 105 cells/mL in complete EGM-2 medium. Each coated well received 100 μL of cell suspension (2 × 104 cells/well). Tube formation was carried out at 37 °C under an atmosphere of 5% CO2 and live-imaged with a Hamamatsu Camera and a Zeiss Axio Observer microscope (5× magnification) with Zen Pro 3.6 software. The images were processed at the 16 h time point with Zen 3.3 Lite (Blue Edition) and analyzed with Angiogenesis Analyzer 1.0 software for ImageJ2 or Fiji. All conditions were done in duplicate. All data were normally distributed as determined by the Shapiro–Wilk test and expressed as the mean ± standard deviation (SD). Statistical analyses were performed with an unpaired two-tailed Student’s t-test with Welch’s correction using GraphPad Prism 9. For comparison between three groups, a one-way ANOVA with Tukey’s multiple comparison test was conducted. p < 0.05 was considered statistically significant.

PMC10003545

Elena Efremenko,Aysel Aslanli,Ilya Lyagin

Advanced Situation with Recombinant Toxins: Diversity, Production and Application Purposes

27-02-2023

recombinant toxin,protein,exotoxin,killer toxin,prion,antivenom,antidote,toxicity prediction,detoxification,enzyme

Today, the production and use of various samples of recombinant protein/polypeptide toxins is known and is actively developing. This review presents state-of-the-art in research and development of such toxins and their mechanisms of action and useful properties that have allowed them to be implemented into practice to treat various medical conditions (including oncology and chronic inflammation applications) and diseases, as well as to identify novel compounds and to detoxify them by diverse approaches (including enzyme antidotes). Special attention is given to the problems and possibilities of the toxicity control of the obtained recombinant proteins. The recombinant prions are discussed in the frame of their possible detoxification by enzymes. The review discusses the feasibility of obtaining recombinant variants of toxins in the form of protein molecules modified with fluorescent proteins, affine sequences and genetic mutations, allowing us to investigate the mechanisms of toxins’ bindings to their natural receptors.

Advanced Situation with Recombinant Toxins: Diversity, Production and Application Purposes Today, the production and use of various samples of recombinant protein/polypeptide toxins is known and is actively developing. This review presents state-of-the-art in research and development of such toxins and their mechanisms of action and useful properties that have allowed them to be implemented into practice to treat various medical conditions (including oncology and chronic inflammation applications) and diseases, as well as to identify novel compounds and to detoxify them by diverse approaches (including enzyme antidotes). Special attention is given to the problems and possibilities of the toxicity control of the obtained recombinant proteins. The recombinant prions are discussed in the frame of their possible detoxification by enzymes. The review discusses the feasibility of obtaining recombinant variants of toxins in the form of protein molecules modified with fluorescent proteins, affine sequences and genetic mutations, allowing us to investigate the mechanisms of toxins’ bindings to their natural receptors. To date, recombinant toxins from various biological sources (bacteria, yeast, scorpions, snakes, spiders and other living organisms) are widely used as: (i) antimicrobial agents for medical purposes, as well as antimicrobial additives for the food and biotechnological industries, (ii) groundwork for the creation of drugs with anticancer activity and the treatment of neurodegenerative diseases and (iii) the basis to develop vaccines, etc. Multiple works have been performed to study the mechanisms of action of genetically modified toxins and their applications [1,2,3,4,5,6] (Figure 1). The protein/polypeptide nature of most of these natural toxins allows them to obtain their recombinant forms. The potential for developing these biomolecules in high enough quantities is the basis for further advancements in developing vaccines and drugs with reduced cost and their widespread use, on the one hand. On the other hand, the production of recombinant toxins avoids the need to work directly with the natural sources of these biomolecules (animals and microbial pathogens). Obtaining genetic constructs encoding the synthesis of recombinant toxins expands the possibilities of their synthesis in special modified forms. Like many recombinant proteins, recombinant toxins can be obtained in high yields using different expression systems, including extracellular secretion, and further isolated and finely purified using affine carriers [7,8]. Various modifications, which in this case can be introduced into such recombinant proteins, can lead to a weakening of the toxic potency of the resulting toxins or, conversely, increase their toxicity. Thus, it is important to publicly discuss the situations and monitor the emergence of such developments. Specifically, it is possible to preliminarily assess the toxicity of the resulting proteins using bioinformatics tools and databases. The issues of the targeted production of recombinant proteins with toxic activities for a variety of uses have been raised multiple times in various reviews in recent years [9,10]. However, each of these scientific analytical publications was focused on discussing specific and rather narrow areas in ongoing research. This review is aimed at a broad analysis of a currently known variety of recombinant toxins, their systematization according to both their origins and purposes of their production and the possibility of predicting the level of toxicity of new variants of recombinant toxins based on the current level of computer science development in analysis of protein structures. Special attention in the review was focused on developments aimed at finding enzymatic solutions (i.e., antidotes) for detoxification of individual recombinant toxic proteins. It was interesting from a scientific and practical standpoint to determine new achievements and main trends during last 5 years in this field, including results obtained by researchers in Russia and worldwide. Toxins produced by various living organisms are the main pathogenic factors causing severe diseases and poisoning of humans and animals. At the same time, one organism can synthesize a number of different toxins responsible for multiple symptoms and effects of intoxication. Most of proteinaceous toxins well-studied to date are produced by various bacteria. However, toxins that are found in yeast, snake, scorpion and spider venoms and other living organisms are also actively studied by various scientific groups today. Recombinant toxins obtained from various origins and purposes of their obtaining are presented in Table 1 [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66]. Bacterial cells are capable of synthesizing endo- and exotoxins. Endotoxins, as a rule, are cell-bound lipopolysaccharides that are released after cell destruction, while exotoxins are protein toxins that are synthesized inside cells and released into the environment. Thus, the recombinant forms of these exotoxins are discussed next (Table 1). Botulinum neurotoxin (BoNT) and tetanus toxin (TeNT) produced by cells of the Clostridium botulinum and C. tetani, respectively, are among the most dangerous and therefore the most well-studied bacterial toxins. Botulism and tetanus diseases caused by these toxins are among the most severe neurological diseases that cause flaccid paralysis and spastic paralysis, respectively. In addition, BoNT is widely used to treat a number of diseases. Consequently, recombinant forms of these toxins have been actively created and researched for many years with the aim of both developing effective antidotes and obtaining drugs based on them. A double-blind, placebo-controlled study evaluated the safety, tolerability and pharmacodynamics (PD) of the recombinant botulinum toxin serotype E (rBoNT-E) compared with commercial botulinum toxin type A (ABO, Dysport ®) [11]. All doses of the recombinant toxin were well tolerated, and rBoNT-E had a faster onset of action, a greater peak effect and a shorter duration of effect at the highest tested doses compared with ABO. To solve an opposite task and neutralize BoNT and other toxins, various antibodies are usually used. Special interest is afforded to single-domain camel antibodies (sdAb, VHH or nanobody) possessing unique structure and characteristics and their chimeras with usual human immunoglobulins. As a result, such immunotherapeutic agents could have up to 1000 times increased protective activity against C. botulinum and prolonged circulation in blood [47]. Different subtypes of BoNT have a varying toxicity, and BoNT/A is more potent toward the human neuroblastoma cell line as compared to BoNT/B [53]. At the same time, genetic modification of the latter to BoNT/BY resulted in improved affinity for human synaptotagmin and BoNT/B receptor, as well as increased toxicity toward this cell line. C3 protein toxin from C. botulinum (C3bot) cells is a mono-ADP-ribosyltransferase that selectively intoxicates macrophages, osteoclasts and dendritic cells by cytosolic modification of Rho GTPases (Rho-A, Rho-B and Rho-C). Thus, C3bot and, even better, its nontoxic variant C3botE174Q have been proven as perspective transporters for selective delivery of small molecules, peptides and proteins to the cytosol of macrophages and other cells [25,26]. Proteolytically activated separate binding/transport subunit C2IIa of C2 toxin from C. botulinum has been found [27] to be a specific inhibitor of chemotaxis of polymorphonuclear neutrophils (PMN), allowing selective suppression of excessive and harmful PMN recruitment to organs as a result of trauma. The enzymatically inactive N-terminal part of the C. botulinum C2 toxin (C2IN) when fused to Rho-inhibiting C3 toxin from C. limosum (C3lim) significantly improves the toxic action of the latter [54]. In a clinically significant mouse model, the in vivo introduction of C2IN-C3lim into the lungs after a blunt chest injury prevented injury-induced recruitment of monocytes into the lungs. Thus, such combinatorial fusion chimeras can be of practical interest due to great variability of available toxin modules. Until now, vaccination has been the best way to combat diseases associated with many bacterial strains, including C. perfringens cells and α-, β- and ε-toxins of the bacteria. However, commercially available vaccines are based on inactivated toxins and have many manufacturing disadvantages that can be overcome using recombinant antigens. Recombinant α-, β- and ε-toxins were synthesized in E. coli cells to create a trivalent vaccine and evaluated on rabbits, cattle, sheep and goats. The levels of produced antibodies in all animals exceeded the minimum values recommended by international protocols [48,49], thus proving the viability of the approach. Even more, nonvirulent species of the same bacteria can be modified to bear a specific toxin or its part and safely modulate strong immune response, e.g., Vibrio cholerae cells expressing the β-subunit of cholera toxin (CTB) [50]. Another major group of proteinaceous toxins is produced by the members of the genus Bacillus. Bacillus cereus cells causing foodborne diseases secrete various pore-forming pathogenicity factors, including Hemolysin II (HlyII). As above mentioned, it can be specifically neutralized by antibodies [29], thus preventing mortality in vivo [30]. B. anthracis cells cause one of the most dangerous infectious diseases, Anthrax. The use of the Anthrax protective antigen (PA) is considered the most promising approach to the development of an Anthrax vaccine. However, the instability of the recombinant PA complicates the production of stable recombinant vaccines. Thus, a number of modification methods have been applied in recent years to design a stable recombinant Anthrax PA. For example, proteolytic-sensitive sites simultaneously with deamidation-prone amino acids can be genetically modified [58,59]. Alternatively, additional stabilizers, e.g., spherical particles (SPs) of tobacco mosaic virus, can be added [60]. Joint application of both methods gives even better results in terms of stability, immunogenicity and protectiveness of the final product, including in vivo tests with a fully virulent B. anthracis strain. B. thuringiensis cells produce δ-endotoxins (Cry), which are toxic to a wide variety of insect pests and currently used widely in agriculture. Insertion of the gene encoding Cry1Ia toxin into a bacterial strain inhibiting fungal growth results in combined fungistatic and insecticidal activity as well as ability to induce plant resistance [31]. A lot of bacterial toxins in their structures contain metal ions performing various purposes. First of all, metal ions can be located in the active sites of metalloproteases such as BFT toxin from B. fragilis leading to damage and necrosis of the intestinal epithelium [32]. In addition, such metals can contribute to toxin structural stabilization and even promote recognition of the target receptor like in the case of staphylococcal enterotoxin-like protein P (SElP) from Staphylococcus aureus binding to major histocompatibility complex class II (MHCII) [61]. It should be noted that some virulence factors secreted by bacteria may be toxic to the microorganisms themselves. To prevent collateral damage and to additionally protect active components, they can be secreted in nanovesicles, which are able to be modeled in silico [32]. The diphtheria toxin (DT) from Corynebacterium diphtheriae kills mammalian cells by inactivating the elongation factor EF-2. The translocation domain in DT plays a critical role in allowing the catalytic domain to pass to the cytosol from endosomal compartments and can be used as a functional vector for active transport of protein drugs [33]. Some mammalian species are resistant to DT. The DT receptor, proHB-EGF, in resistant and sensitive species differs by amino acid sequence and therefore by secondary structure; however, there is no consensual opinion on how the difference in the structure of primary receptors changes the process of internalization of DT by resistant cells compared to sensitive ones. According to some publications [34], there can be even very little difference of binding constants of DT subunit B (which includes receptor-binding and translocation domains) to resistant and sensitive cells, while there was huge difference of intracellular concentrations of toxin within model cells. It means that multiple mechanisms of resistance to DT may exist in mammalian cells. Several approved drugs, e.g., denileukin diftitox, which is fusion of DT with interleukin-2, are commercially available and actively used to date. However, research to improve their efficiency, producibility and safety as well as to obtain new therapeutics with DT are constantly continued [56,57]. Listeria monocytogenes cells apply internalins InlA and InlB to attach and penetrate into mammalian cells. Curiously, hepatocyte growth factor receptors (HGFR) together with other multiple variants are also affected by InlB [35]. This is important since HGF/HGFR play crucial role in liver restoration after its acute toxic damage. Thus, truncated bacterial InlB was implemented as a functional analogue of HGF to obtain novel drugs with hepatoprotective activity. Bacterial toxins can interact not only with receptors themselves but with complexes of receptor and signal molecules. One of such examples is LcrV from Yersinia pestis [36]. It is a strong virulence factor having multiple functionalities, one of which is specific activation of human receptor-bound interferon-γ (hIFN-γ), which resulted in immune cell death via apoptosis. It became possible only after hIFN-γ binding to receptor and presentation of its 138GRRA141 site, which specifically interacts with 32LEEL35 and/or 203DEEI206 sites of LcrV. Thus, inactivation of these sites by specific antibodies completely prevents any harmful effects of LcrV. Protein biosynthesis can be targeted by bacterial toxins, as well. For example, bacteria can utilize multiple enzymes from Gcn5-related N-acetyltransferase (GNAT) superfamily to acetylate and thus inactivate specific aminoacyl tRNAs, including transporters of Met, Ile, Gly, etc. [37]. Killer yeasts are able to produce proteins named “killer toxins” that are often glycosylated and bind to specific receptors on the surface of the sensitive microorganism, which is then destroyed by a target-specific mechanism of action (Table 1). They are widespread among yeasts and attract a lot of attention of researchers. To date, more than 100 types of killer yeasts have been described [67]. The most well-characterized killer toxins in terms of their genetic determinants, biochemical characteristics, molecular targets on sensitive cells and mechanisms of their destruction are toxins K1, K2 and K28 from Saccharomyces cerevisiae; zymocin from Kluyveromyces lactis; PMKT and PMKT2 from Pichia membranifaciens; PaKT from Wickerhamomyces anomalus; HM-1 from Cyberlindnera mrakii and Kpkt from Tetrapisispora phaffii. Due to their properties and spectrum of action, which is aimed at pathogenic microorganisms, recombinant killer toxins are being actively investigated in order to develop therapeutic agents based on them. However, the lack of research on their effects on humans and animals limits their use in the food and feed industry. Another drawback is that additional information about the mechanisms underlying the formation of killer toxins in yeast is required. Without solving these issues, it is not possible to successfully implement killer toxins in practice [67,68]. A study of S. paradoxus revealed a new K1-like toxin (K1L) being active against sensitive competing yeast cells [12]. It is encoded by double-stranded RNA (dsRNA) and satellite dsRNA, which may also be of virus origin. Its homologues have been identified in other six yeast species not belonging to Saccharomyces and are likely to be acquired by horizontal gene transfer via dsRNA and/or DNA with subsequent diversification of their structure and toxicity profile. Genetic fusion of toxins with fluorescent proteins allowed researchers to study the binding of the toxin to the cell envelope of affected yeast [13]. However, intracellular translocation of labeled recombinant toxin K28 was not observed then, in spite of the presence of toxicity. It means there are gaps in our understanding of the true mechanism of killer toxin action and transport even among best-investigated ones. Further research is required to visualize intracellular transfer of toxins using high-resolution imaging techniques of individual molecules. Killer toxin K1 is secreted by S. cerevisiae strains in a heterodimeric form. After binding to the primary receptor (β-1,6 glucans) in the cell wall, K1 is transported to the plasma membrane and is initially supposed to interact with its secondary receptor Kre1p, which ultimately leads to an ionophoric disruption of the membrane function. However, expression of recombinant K1α in resistant yeasts lacking Kre1p resulted in profound toxic effect [14], thus excluding role of the receptor. At the same time, co-expression of toxin precursor(s) in sensitive cells eliminated any negative effects. Thus, resistance to killer toxins is a part of adaptive (acquired) immune system. Some killer toxins, e.g., Kpkt from T. phaffii (formerly Kluyveromyces phaffii), have antimicrobial activity not only on yeast but also on bacteria [15]. Interestingly, activity of Kpkt was not detected toward all tested mycelial fungi. Meanwhile, Kpkt has a β-1,3-glucanase activity [16,38] and thus can be combined, for example, with chitinases to synergistically improve their antifungal effects. At concentrations effective again yeasts, recombinant Kpkt has no effect on immortalized human epidermal keratinocyte cell line HaCaT [38]. That makes it promising for further investigations. Venoms of snakes, scorpions and spiders are used by animals as their own defensive and offensive means by immobilizing victim and blocking the functional activity of their cardiovascular, respiratory and/or nervous systems. Proteinaceous toxins are the main components of these systems and modulate important ion channels and receptors after introduction into the body. Today, powerful databases of poisons and protein toxins with improved properties have been assembled already for more selective action, resistance to the effects of proteases, less immunogenicity and improved characteristics, in terms of pharmacokinetic properties. These characteristics can be improved by genetic modification of amino acid sequences, addition of disulfide and ion bridges, etc. After all, animal venom toxins are of great interest for applications in medicine as a basis for drug development [5] (Table 1). The β/δ agatoxin-1 of the spider Agelena orientalis was obtained in recombinant form in the entomopathogenic fungus Lecanicillium muscarium with a special secretory signal peptide [18]. Further toxin was fused with eGFP to simplify the screening procedure. Unfortunately, toxic activity of the fusion protein was not investigated in the work. Another fusion protein of GFP with agitoxin-2 from scorpion Leiurus quinquestriatus hebraeus was more useful [64]. That allowed researchers to visualize the binding of toxins to their receptor as well as to determine dissociation constants of various toxins competing for the same Kv1.3 channel. Purotoxin-1 (PT1) from the venom of the Central Asian spider Geolycosa sp. selectively inhibits the purinergic receptor P2X3 and is a potent analgetic. It can be produced in pilot scale as self-cleavable fusion protein with mini-intein DnaB [19]. However, its purification is multistage and labor-intensive with modest yield at the end. Interestingly, Tbo-IT2 toxin was identified in the spider Tibellus oblongus by cDNA analysis of the transcriptome of its venom glands [42]. Its amino acid sequence has a 41% identity match with the closest protein toxin, while its spatial structure folds into a well-known inhibitory cysteine knot (ICK). The first main difference is the formation of five disulfide bonds instead of the typical three that should result in extreme stability of the toxin. The second and the most puzzling difference is that Tbo-IT2 did not have inhibitory activity on the tested panel of available ion channels and neuroreceptors, while it is still toxic to the housefly, Musca domestica. Further research may elucidate the target(s) of the Tbo-IT2. Another attempt to apply mini-intein DnaB was a little bit more successful [23], although the target toxin, APHC3 from the anemone H. crispa, which has analgesic activity, was produced in inclusion bodies and multistage purification was still required. Fusion with His-tag and Smt3-leader peptide was shown to be a much more efficient method [24]. The resulting inhibitor of the TRPV1 ion channel (HCRG21 peptide from the sea anemone H. magnifica) was easier to purify and after cleavage was obtained at comparable yield to APHC3. As stated previously with bacterial toxins, antibodies are used almost exclusively in antivenoms [22]. Combining several recombinant toxins in simple mixture [17,51] or even in fusion protein [65] often leads to improved efficiency of antivenoms, including comparing to commercial ones. Furthermore, it was found that rationally selected toxin-specific single-stranded DNA aptamers can exhibit broad cross-reactivity in vitro and ex vivo against isoforms of toxins found in various snake venoms [52]. Computer modeling provides powerful tools to thoroughly solve even complicated issues. For example, interaction of proteinaceous toxins KTx from scorpion M. eupeus with potassium channels (KV) was simulated and explained, followed by modulation of their activity using genetic modification [40,41]. In other work [45], authors have investigated binding of TFTs with novel receptors. Secondary structures of multiple actinoporins Hct from the sea anemone Heteractis crispa were generated [69], followed by analysis and successful structure–activity hypothesis testing. Venoms contain a large number of biologically active compounds with diverse activities. Shorter peptides, e.g., azemiopsin acting on neuroreceptors [20] and bradykinin-potentiating peptides (i.e., affecting blood pressure) [21], could be prepared by a solid phase synthesis using a general Fmoc-method, while larger polypeptides are the most rational to produce using common expression systems [44,45]. A modulatory effect of some proteinaceous toxins on neuroreceptors is worth mentioning. Well-known three-finger toxins (TFTs) and their analogues [44,45] as well as azemiopsin bind mostly nicotinic acetylcholine receptors (nAChRs), but γ-aminobutyric acid receptors (GABARs) can also be affected [45]. Pore-forming toxins, e.g., Hct from the sea anemone H. crispa [46], have a wide nonspecific action and are almost equally cytotoxic to normal and malignant cells. However, fusing them with targeting partners, such as site-specific ligands, toxins or antibodies, could result in new drug platform development. Recombinant toxins can be easily genetically modified and truncated to help researchers investigate their toxic action in a more detailed way. For example, peptide Ms 9a-1 from sea anemone Metridium senile causes significant analgesic and anti-inflammatory effects by desensitization of TRPA1-expressing sensory neurons, and it was thought to be a positive modulator of TRPA1 channel. However, truncation of its unordered domains on the N- or C-terminus resulted in complete loss of analgesic and anti-inflammatory activities in vivo [66]. Thus, another target receptor(s) is likely present in neurons. Prions (Pr) are infectious agents that cause devastating and incurable disorders known as transmissible spongiform encephalopathies (TSE). With the advent of innovative technologies, such as protein misfolding cyclic amplification (PMCA) and real-time quaking-induced conversion (RT-QuIC), in vitro amplification of prions has become possible. There is evidence suggesting that prion complexes can acquire high-order assemblies in vivo, which may look structurally ordered. However, the biophysical nature of these structures and their role in amyloid biology are still unclear. Despite the fact that the amyloid collected in vitro has some biochemical similarities with the ex vivo amyloid of the same protein, it often does not reproduce the biological activity of the latter. For example, preparations of prion protein (PrP), which are resistant to proteinase K and obtained exclusively from one recombinant PrP (rPrP), may not have any detectable infectious activity both in cell cultures and in animal bioassays. However, the proteinase K-resistant PrP obtained from rPrP is infectious if it is placed in the homogenate of a diseased brain ex vivo using the PMCA assay [70]. To study the rPrP, mechanisms of the development of toxicity and pathogenicity of prion diseases as well as their role in the development of pathologies of the nervous system is an important task of the world scientific community (Table 2, [71,72,73,74,75,76,77]). Recent studies have shown that the infectivity of prions and their neurotoxicity may not be related to each other. Therefore, it is important to distinguish directly infective prions and those with a toxic effect, since the current hypothesis suggests that it is not the prions themselves that are toxic but another type of protein responsible for the toxicity of the disease. This species may be a by-product of prion formation, in a non-pathway amyloid PrP structure or even a non-protein whose formation is catalyzed by a prion [78]. Thus, using highly purified infectious prions, it was demonstrated that prions are not directly neurotoxic and that the toxicity presented in infected brain tissue may be different from infectious prions [76]. rPrP was obtained using the insect baculovirus cell expression system (Bac-rPrP) [71] to determine whether pathogenic Bac-pathogenic PrP (PrPSc) is produced spontaneously in intermittent ultrasound reactions. No spontaneous formation of Bac-rPrPSc was observed at 37 °C, but when the reaction temperature increased to 45 °C, Bac-rPrPSc was formed in all samples studied. Some variants of Bac-rPrPSc were transmitted to mice, but when the reaction was repeated for 40 cycles, transmissibility was lost. It is noteworthy that various variants of Bac-rPrPSc, including nontransmissive ones, were characterized by resistance to proteinase K and were dependent on the presence of cofactors during amplification. However, their characteristics also disappeared after 40 reaction cycles, and the variety converged on one variant. These results show that different variants of Bac-rPrPSc are generated with different transmissivity to mice and structural properties; variants of Bac-rPrPSc compete with each other and gradually converge to a variant with a slightly higher amplification rate. To understand the role of the hydrophobic region in the formation of an infectious prion at the molecular level, X-rays of crystal structures of mouse PrP (MoPrP, residues 89–230) in complex with a nanobody (Nb484) were obtained [72]. Using a rPrP reproduction system, it has been shown that binding of Nb484 to the hydrophobic region of MoPrP effectively inhibits the reproduction of proteinase-resistant PrPSc and the infectivity of prions. In addition, when added to cultured mouse brain slices in high concentrations, Nb484 did not exhibit neurotoxicity, which is sharply different from other neurotoxic antibodies against PrP. Thus, Nb484 may be a potential therapeutic agent against prion disease. Five groups of transgenic mice expressing elk PrP (TgElk) were vaccinated with either one CpG adjuvant or one of four rPrP immunogens: deer dimer (Ddi); deer monomer (Dmo); mouse dimer (Mdi) and mouse monomer (Mmo) [73]. Then mice were intraperitoneally infected with prions of chronic wasting disease (CWD). All vaccinated mice developed anti-PrP antibody titers detected by ELISA. It is important to note that all four vaccinated groups survived longer than the control group, while in the group immunized with Mmo, the average survival time increased by 60% compared to the control group (183 vs. 114 days after inoculation). Thus, the use of recombinant forms of prions allows researchers to study their immunogenicity and to develop novel vaccines. In order to establish how various cofactors modulate the formation and selection of prion strains, PMCA was used to generate a variety of infectious rPrP strains by multiplication in the presence of brain homogenate [77]. It is known that brain homogenate contains certain cofactors whose identity is only partially known and which facilitate the transformation of normal PrP (PrPC) into PrPSc. A mixture of various infectious prion strains was obtained and introduced into the brain homogenate, where various polyanionic cofactors were present. These cofactors could control the evolution of mixed prion populations toward the development of specific strains (types of conformations). As a result, it has been shown that various infectious rPrP can be obtained in vitro. Their specific conformation (strain) depends on the cofactors available during reproduction. These observations are very important for understanding the pathogenesis of prion diseases and their ability to reproduce in various tissues and hosts. The RT-QuIC method can be used to detect pathogenic PrP in various biological tissues of humans and animals. However, this method requires a continuous supply of freshly purified PrP and thus is not available in a diagnostic laboratory. To solve the issue, a method for obtaining a rPrP has been developed [74]. Lyophilized rPrP from bank vole (BV rPrP) can be stored for a long time before use, as well as be transported at certain temperatures to appropriate diagnostic laboratories, which can facilitate implementation of the RT-QuIC method as a diagnostic tool [74]. Nucleic acids have been shown in recent studies to act as potential cofactors of protein aggregation and prionogenesis. For example, RNAs, regardless of their sequence, source and size, modulate rPrP aggregation in a bimodal manner, affecting both the degree and the rate of rPrP aggregation depending on the concentration [75]. Finding ways of obtaining effective antibodies and the development of vaccines against recombinant toxins is one of the main goals today [79,80]. For maximal quality and efficiency of immunologic medications, initial toxins should be highly purified, be in sufficient quantities and stimulate selective immune response. Recombinant toxins’ production solves the first two issues, though vaccines can still have cross-specificity. Today, different recombinant vaccines against diseases caused by pathogenic Clostridium genus (botulism, tetanus, black disease, etc.) are actively developed [8,9,10]. Due to the simplicity of preparation and effectiveness of action, recombinant bacterin is one of the intensively promoted for the production of immunizers against C. perfringens [48,49]. A number of promising experimental multivalent recombinant vaccines made up of CPA, CPB, ETX, NetB, HC-BoNT/A, HC- BoNT/B and HC-BoNT/E have been reported [10]. Recently, recombinant, genetically detoxified, full-length tetanus toxin protein (8MTT) was described and found to be an immunogenic antigen and effective as a carrier protein for peptide and polysaccharide conjugates [81]. A study on fusion toxin combining recombinant CPE (C-terminal region) from C. perfringens and the subunit of the Shiga toxin (E. coli) showed that it is effective to stimulate an immune response in mice [82]. Furthermore, monovalent recombinant vaccines Iota and TpeL have been expressed separately in E. coli [83]. Bioinformatics tools were also used to design new versions of recombinant CPB [48]. Anthrax toxin from Bacillus anthracis cells is one of the most dangerous toxins, considered among other things as a potential bioterrorism agent. In this regard, there is a huge interest in the development of vaccines based on Anthrax recombinant PA (rPA). Subunit vaccines based on rPA have a good safety and protection profile; however, rPA is unstable antigen, especially with aluminum adjuvants. The development of modern vaccines based on adjuvant compositions in the dry forms of mutant PA variants resistant to proteolysis and deamidation should help solve the problem of neutralization of Anthrax toxin. An analysis of scientific databases was carried out recently [79] with an emphasis on causes of PA instability and finding solutions to this problem. New approaches to rPA expression, new formulations of rPA-based vaccines and the simultaneous use of PA with other Anthrax antigens were reviewed in this study. A number of rPA-based vaccine candidates, including DNA vaccines and vaccines based on viral and live bacterial vectors and plant expression systems, are currently under development [79]. The protective efficacy of human sera from vaccinated individuals with a new rPA vaccine (GC1109) against Anthrax challenge has been demonstrated in passive transfer studies [84]. A DPX-rPA-based vaccine generated neutralizing antibodies titers toward Anthrax PA toxin in animal models [85]. Furthermore, modified variants of the Anthrax antigen have been obtained simultaneously through deamidation-prone asparagine residues substitution and by inactivation of proteolysis sites, and stability of modified rPA has been demonstrated under various temperature conditions [59]. Recombinant lethal Anthrax toxin (LeTx) has recently been successfully used to treat breast cancer cell line MBA-MD-231 [28]. The most recombinant vaccines are developed with a narrow spectrum of effective action. It may be a significant problem, since microorganisms secrete a lot of toxins simultaneously. Meanwhile, it is possible to create multiantigenic nanotoxoids using the natural affinity of virulence factors to cell membranes [86]. The obtained polyvalent nanotoxoids are able to deliver combination of virulence factors, are safe both in vitro and in vivo and can cause functional immunity capable of fighting live bacterial infections in model animals. Today, protein toxins play a very important role in the treatment of advanced solid tumors by either directly destroying tumor cells or by changing the cellular processes occurring in them. Due to advancements in biomolecular methods, a number of nonpathogenic bacteria have been genetically modified for use in the development of bacterial anticancer drugs [2,87]. Immunotoxins, which consist of a protein derived from bacterial, fungal, plant toxins or human cytotoxic proteins and conjugated to a specific targeting molecule, have demonstrated high cytotoxicity to cancer cells. They are engineered to recognize disease-specific target receptors and kill the cell upon internalization. To date, a number of immunotoxins are under clinical trials, and some of them have been approved by U.S. Food and Drug Administration for the treatment of hematological tumors. However, there are some disadvantages, including immunogenicity, nonspecific toxicity and poor penetration, that need to be addressed [88]. Among the available cytolytic toxins, the Pseudomonas exotoxin (PE) and DT are extensively studied [89]. Their main mechanism of action is based on blocking protein synthesis via ADP-ribosylation of eukaryotic elongation factor 2. Suicide-gene therapy strategies, where controlled tumor-specific expression of DT is used for the eradication of malignant cells, are becoming increasingly important [90]. A new immunotoxin based on shortened DT389 fused to humanized scFv YP7 selective to an oncophetal marker Glypican-3 (GPC3) has recently been developed and studied against hepatocellular carcinoma (HCC) cells [55]. Recombinant immunotoxins based on PE have demonstrated significant efficacy in the treatment of tumors and autoimmune diseases. Recent strategies for structural optimization of these immunotoxins, combined with mutagenesis approaches, have reduced the side effects associated with their immunogenicity and nonspecific cytotoxicity and, as a result, led to an increase in both their safety and efficacy [91]. Recently developed immunotoxins, comprising of truncated Pseudomonas exotoxin A (PEA) and DT conjugated to trastuzumab, have demonstrated the potential to reduce the therapeutic dose of the trastuzumab [92]. An advanced modification technology was used to construct the site-specifically conjugated immunotoxin based on immunoglobulin G (IgG) and Pseudomonas exotoxin A (PE24). The constructed immunotoxin demonstrated specific toxicity toward HER2-positive cancer cell at very low concentrations [93]. The combination of two highly toxic proteins (a low immunogenic variant of PEA and ribonuclease Barnase from B. amyloliquefaciens) allowed the achievement of directed anticancer therapy toward HER2 and EpCAM [94]. The use of AgNPs as a delivery system for targeting of toxins to cancer cells was demonstrated for the first time by the investigation of the inhibitory effect of the nanotoxin comprised of truncated Pseudomonas exotoxin (PE38) loaded silver nanoparticles (AgNPs) on the viability of breast cancer cells through apoptosis [62]. The Stx toxin from Stx-producing Shigella dysenteriae and enterohaemorrhagic E. coli is another promising toxin for use as a delivery system. Engineered StxB-based drug delivery systems have the potential to deliver small or macromolecular drugs to specific intracellular organelles/cancer targets. After binding to ganglioglobotriaosylceramide (Gb3, CD77), the nontoxic subunit B (StxB) of the Shiga-holotoxin is endocytosed and delivers its payload by a unique retrograde trafficking pathway via the endoplasmic reticulum to the cytosol [95,96]. Despite the widespread use of bacterial recombinant toxins in cancer therapy, toxins from other sources are also being considered as potential anticancer agents today. Thus, a recombinant form of a new short-chain toxin isolated from the venom of the scorpion Mesobuthus eupeus MeICT was used to treat glioma [39]. Recombinant toxin MeICT-His in low concentration significantly inhibited the proliferation and migration of glioma cells. In vivo studies have not revealed the toxicity of MeICT when administered to mice in high doses. Studies of the effect of MeICT on the expression of mRNA MMP-2, annexin A2 and FOXM-2, which are key molecules in the development and invasion of glioma, have shown a significant decrease in the expression of mRNA annexin A2 and FOXM1. The effect of nicotine acetylcholine receptor (nAChR) antagonists, α-conotoxins of sea snails and α-cobratoxins of snakes on the survival and proliferation of glioma C6 cells has been studied [43] to evaluate the presence and role of nAChR in C6 cells. It was found that α-conotoxins and α-cobratoxin contribute to the proliferation of glioma C6 cells. The membranolytic activity of actinoporins, which are a pore-forming toxins produced by sea anemones, is also of great interest for the development of new antitumor drugs [97]. Although the development of vaccines and anticancer drugs are the two main areas of research in the production of recombinant toxins, there are also a number of other applications for which the production of recombinant toxins is of great interest. For example, killer toxins produced by yeast can be used in biological plant protection in order to obtain safe food products [98]. Moreover, killer toxins can also control postharvest pathogens [99]. Another example is the development of antidotes to these toxins for the treatment of poisoning caused by venomous bites of snakes, scorpions and spiders. The resulting antidotes consist of various antibodies, depending on the type of toxin against which they are created, and are injected. Poisonous bites of snakes, scorpions and spiders pose a serious threat and are the cause of high mortality rates worldwide. Despite the fact that antidotes based on polyclonal antibodies are the main means of saving people’s lives from poisonous animal bites, a wide variety of toxins in the composition of venoms of different species leads to the low effectiveness of such antidotes. It is worth nothing that such a thorough study of the properties of animal venoms (snakes, scorpions, spiders, bees, marine organisms) in the last few years made it possible to identify a number of compounds with antiviral activity in venoms. The possibility of use of their recombinant forms (e.g., recombinant peptide rEv37 from scorpion Euscorpiops validus, snake recombinant PLA2-CB isoforms) as the basis for antiviral drugs has been studied [100]. The outstanding therapeutic potential of BoNTs and TeNT made it possible to use them for the treatment of a wide range of neurological conditions related to hyperactivity in the periphery, acute and chronic muscle weakness. The potential to use the TeNT as a nanocarrier for neuron targeting and drug delivery to the central nervous system is another focus of research that is of great interest [101]. Thus, the purpose of obtaining recombinant toxins can be both the study of the properties of the toxin, the mechanisms of toxicity development in order to develop antidotes, the development of vaccines and the production of drugs based on the toxin, for example, to combat various tumor diseases and antimicrobials, which can also be used in biotechnological production. The majority of the publications of recent years emphasize the importance of using bioinformatics methods to identify new variants of toxins and clarify the mechanisms of their toxic effects. Molecular modeling facilitates the understanding of the interaction of toxins with their receptors and/or targets, especially when these compounds are bound to the membrane, and biochemical approaches to the study of these processes are complex [102]. Due to advances in synthetic biology, the cost and time required for the development and synthesis of individual recombinant products are steadily decreasing. Many research laboratories regularly create genetically modified proteins as a part of their research activities. However, manipulations of amino acid sequences in proteins can lead to the unintended production of protein toxins. Therefore, the ability to determine the toxicity of a protein before its synthesis reduces the risk of the potential danger of synthetic production of protein toxins. For this purpose, various methods based on machine learning are being developed to predict the toxicity of proteins in silico based on a number of initial data (Figure 2). ThreatSEQ, developed by Battelle Memorial Institute, identifies sequences of concern when compared with a database of known toxic proteins [103]. ToxinPred2 and other developed methods are aimed at detecting toxic bacterial proteins and peptides using machine learning methods based on information about the amino acid sequence [104,105,106]. ClanTox uses a machine learning method to classify known peptide inhibitors of ion channels [107], among which there are many well-characterized toxins. ToxClassifier is available for use as a web application or as a separate downloaded tool for the purpose of classifying toxins from nontoxic protein sequences [108]. These methods are similar in that they use information about the amino acid sequence. However, new methods for predicting toxicity, including recombinant proteins, are emerging. In this vein, a new method of NNTox (prediction of protein toxicity based on a neural network) was recently presented [109], which can assess the potential toxicity of the sequence of the requested protein based on the annotation of the gene ontology (GO) of the protein [110]. GO is a controlled dictionary of protein functions that is widely used for annotation and prediction of functions. Earlier, the authors of the method developed a number of approaches to function prediction, including PFP and Phylo-PFP [111,112,113,114]. By combining genes or part of genes of similar or dissimilar proteins of various organisms, it is possible to obtain fusion proteins in vitro when designing recombinant proteins including toxins [18,25,42,54]. However real-time laboratory experiments to automatically predict the functionality of fusion proteins are expensive and time-consuming. Today, a new method for predicting the functionality of fusion proteins based on a hybrid swarm algorithm of genetic optimization (HybGPSO) has been proposed to solve this problem [115]. The cellular component, the biological process and the molecular function of the unannotated fusion protein determined by the GO constitute the three main characteristics predicted by this algorithm. Bacterial cells of Bacillus thuringiensis produce a natural three-domain Cry (3d-Cry) protein toxin (Bt), which is very actively used in different countries of the world as a bioinsecticide. The only existing tool for finding of Cry toxins, called BtToxin_scanner [116], has significant limitations, in particular, the limited size of the search query, insufficient accuracy and an outdated database. In this regard, a fast and convenient CryProcessor tool has recently been developed, which enables productive and accurate finding of 3d-Cry toxins [117]. A unique feature of this tool is the ability to search for Cry toxin sequences directly on assembly graphs, which makes it possible to analyze raw sequencing data and overcome the problem of fragmented assemblies. Moreover, CryProcessor is able to accurately predict the location of domains in arbitrary sequences, allowing to extract sequences of specific domains beyond the limited number of toxins presented in CryGetter. Thus, modern bioinformatic and genomic methods make it possible to assess the toxicity of recombinant proteins that are not related to known toxins and to discover new protein toxins in living organisms. These methods not only expand the diversity of toxins within known families but also reveal completely new classes of toxins, including artificially synthesized ones. One of the key problems associated with bioinformatically identified toxins is that there are few clues as to where to look for a possible mechanism of action beyond the information presented in the amino acid sequence and predicted domains. Due to the wide variety of toxins known to date and differences in the mechanisms of their action, there is an urgent need to create antidotes that both have a specific effect and are active against a wide range of toxins. The main directions of antidote development today are either the creation of various inhibitors capable of blocking the sites of binding of toxins to targets or the production of proteins (usually antibodies) capable of acting as bioscavengers via binding directly to the toxins themselves, thereby limiting their interactions with targets [118]. However, the search and development of new antidotes based on other principals, namely using molecules capable of detoxifying toxins by their enzymatic transformation into less toxic or nontoxic molecules, may become a promising alternative to existing solutions. To date, several enzymes are known that can act as antitoxins against various bacterial toxic substances, as well as enzymes that exhibit hydrolytic activity against PrP (Table 3, [119,120,121,122,123,124,125,126,127]). The toxin/antitoxin (TA) systems are present in almost all strains of bacteria and archaea and consist of a toxin that slows down growth and an antitoxin, a compound that inhibits the activity of the toxin. Currently, there are six main classes of TA systems based on the nature of the antitoxin and the way in which the antitoxin inactivates the toxin [128]. It has recently been shown that there are at least three additional and different TA systems in which the antitoxin is an enzyme and the related toxin is a direct target of the antitoxin, and it has been proposed to use the type VII of TA system to designate those TA systems in which the enzyme-antitoxin can chemically modify the toxin post-translationally in order to neutralize it [129]. The Hha and TomB proteins from E. coli cells form an oxygen-dependent TA system in which the antitoxin oxidizes the Cys 18 of the toxin. It has been shown that Mob from Yersinia is an orthologue of TomB, and its only cysteine variant [C117S]Mob can replace TomB as antitoxins in E. coli cells. Unlike other TA systems, [C117S]YmoB temporarily interacts with Hha (rather than forming a stable complex) and enhances spontaneous oxidation of the conservative cysteine residue of Hha to -SOxH-containing compounds (sulfenic, sulfinic or sulfonic acid), which destabilizes the toxin [122]. In this case, oxidation of toxin molecules is used as a tool of its detoxification. Recently, a study was published [119] in which the authors structurally and functionally characterized the putative TA locus Mtb Rv1044-Rv1045, demonstrating that it is a full-fledged TA system but uses a previously unknown mechanism of antitoxicity, including toxin phosphorylation. While Rv1045 encodes guanylyltransferaseTglT, which functions as a toxin, Rv1044 encodes a new atypical serine protein kinase TakA, which specifically phosphorylates a related toxin at the S78 residue, thereby neutralizing its toxicity. The two-gene module encoding HEPN (the highest nucleotide-binding domain of eukaryotes and prokaryotes) and the related domain MNT (minimal nucleotidyltransferase) (HEPN/MNT) is considered the most common TA system in prokaryotes. However, its physiological function and the mechanism of neutralization remain unclear. Recently, it was discovered [120] that the MntA antitoxin (a protein with the MNT domain) acts as an adenylyltransferase and chemically modifies the HepT toxin (a protein with the HEPN domain) to block its toxicity as RNases. Biochemical and structural studies have shown that MntA mediates the transfer of three antimicrobial peptides (AMP) to a tyrosine residue near the HepT RNase domain in Shewanella oneidensis. In addition, in vitro enzymatic assays have shown that three AMP are transferred to HepT by MntA sequentially, with ATP serving as the substrate, and this polyadenylation is crucial for reducing the toxicity of HepT. In addition, the GSX10DXD motif, conserved among MntA proteins, is a key active motif for polyadenylation and neutralization of HepT. Thus, HepT/MntA is a new type of TA system, and the polyadenylation-dependent mechanism of TA neutralization prevails in bacteria and archaea. Another example is the enzyme which is an antitoxin of the TA type V system that does not bind directly to the toxin but is able to cleave the mRNA of the corresponding toxin. Recently, ghoST has been studied for the first time as a type V of TA system that encodes a small toxin protein GhoT, which can damage the cell membrane, and antitoxin GhoS exhibited sequence-specific endoribonuclease activity with respect to the mRNA of the toxin GhoT [121]. The TA DarT/Dart system found in various bacteria, including the well-known pathogen Mycobacterium tuberculosis, has been identified and well characterized [124]. It turns out that the system toxin (DarT) is a domain of unknown function (DUFF) 4433, and the antitoxin (Dark) is a macrodomain protein. It has been found that DarT is an enzyme that specifically modifies thymidines on single-stranded DNA in a sequence-specific manner through a nucleotide-type modification called ADP-ribosylation. The authors found that this modification can be removed by DarG antitoxin by reversible ADP-ribosylation of DNA and suggested potential therapeutic benefits of such an enzyme–enzyme system in bacterial pathogens such as M. tuberculosis. Prions can act as slow poisons, and therefore, these toxic proteins have the dangerous potential to be used as biological weapons [130]. Taking into account these facts, the search for enzymes that are capable of inactivating prions is an important current task of science. It is believed that the prion, which is the etiological agent of TSEs, consists of aggregated conformers of PrP (PrPTSE) rich in β-sheets obtained as a result of improper folding of the cellular form of the same protein. Enzymatic inactivation of prions in the absence of living microorganisms has been actively investigated in the last decade. A number of studies have reported successful enzymatic inactivation of prions, but many researchers have resorted to a combination of enzymatic treatment with high temperatures (>50 °C), high pH values (>9) [124], or both reaction conditions combined. The enzymatic inactivation of the prion under such extreme conditions limits the applicability of such treatment for use in the environment and in relation to most biological objects. Proteases catalyze the hydrolysis of peptide bonds in the main chain of polypeptides and are therefore of particular interest because of their ability to inactivate prions. Despite the resistance of prions to proteolytic inactivation, a number of enzymes have been found that can cleave PrPTSE and in some cases reduce the infectivity of prions. Most of the proteases found to date with the ability to cleave PrPTSE are serine proteases. Subtilisin and subtilisin-like serine proteases are found in bacteria, archaea and fungi and represent one of the five superfamilies of prokaryotic serine proteases. Subtilisins are well represented among enzymes capable of hydrolyzing PrPTSE [131]. The results of a study of the effectiveness of a commercially available subtilisin enzyme, Prionzyme, for the decomposition of soil-bound and unrelated PrP of CWD and hyper strain of transmissible mink encephalopathy (HY TME) depending on pH, temperature and treatment time are known [124]. The enzyme subtilisin efficiently decomposed PrP adsorbed on a wide range of soils and soil minerals below detection limits. Signal loss occurred rapidly at pH 12.5 and within 7 days under conditions typical of the natural environment (pH 7.4, 22 °C). There was no obvious difference in the efficiency of the enzyme action between bound and unbound CWD PrP. Thus, it was shown that, although adsorbed prions retain relative resistance to enzymatic cleavage compared to other brain homogenate proteins, they can be effectively decomposed when they are immobilized (in this case, when bound to soil). Topical application of a solution of the enzyme subtilisin can be an effective method of disinfection to limit the transmission of the disease through environmental “hot spots” of prion infectivity. Two serine protease enzymes, subtilisin 309 and subtilisin 309-v, were used to treat brain homogenates containing a high level of prion infectivity under slightly alkaline conditions to study methods of prion decontamination. When confirming the elimination of the infectivity of abberantly folded rPrP, only one condition of hydrolysis (subtilisin 309 at 138 mg/mL, 55 °C, 14 h, pH 7.9) was considered statistically significant (p < 0.001) compared to the control [125]. Nattokinase (NK, also known as subtilisin NAT) is one of the most important extracellular enzymes produced by Bacillus subtilisnatto cells. The main interest in this enzyme is its fibrinolytic activity. The stability of this enzyme in the gastrointestinal tract makes it a useful agent for oral thrombolytic therapy. Thus, NK is used as a valuable food additive or as a nutraceutical. In addition to these valuable benefits, there are other uses attributed to NK, including the treatment of hypertension and Alzheimer’s disease. Additionally, it was found that NK is able to reduce the amyloid structure of recombinant human PrP fibrils [126]. In this regard, in the future, probably, it is possible to consider this enzyme as a candidate for the role of an antitoxin (antidote). Keratinases are able to cleave the structure of β-keratin; thus, they can cleave PrPSc, which consists of tightly packed β-sheets. The first keratinase detected for degradation of PrPSc was KerA from B. licheniformis PWD-1 cells [127]. An interesting study of PrPTSE inactivation by lichens revealed that both aqueous and acetone extracts of three lichen species (Parmeliasulcata, Cladoniarangiferina and Lobaria pulmonaria) have the ability to decompose PrP-infected TSE hamsters, mice and deer. It has been found that PrP levels in PrPTSE-enriched preparations or infected brain homogenates also decrease after exposure to freshly harvested P. sulcata or aqueous lichen extract. Presumably, some other lichens may also have the potential to inactivate TSE infectivity in the landscape or be a source of agents for the decomposition of prions [131]; however, the active agent (biocatalyst) of this process has not yet been identified. Different methods of isolation of recombinant proteins are used, depending on the source of the original toxin and the purposes for which it must be obtained. To date, E. coli is the most widely used expression system for the biosynthesis of recombinant toxins. At the same time, the very production of recombinant toxins occupies an important place in the study of the toxicity of various proteins/peptides, the mechanisms of their action and the disclosure of trends in the development of toxicity in vivo and helps researchers to look for new possible methods of their application in medicine and other fields of human activity. The main advantage of genes’ expression of recombinant forms of toxins is the possibility of producing these proteins/peptides in quantities sufficient to conduct experiments with them at the molecular and cellular levels. Moreover, modern methods of molecular biology and bioinformatics make it possible to carry out various genetic modifications of recombinant proteins and predict their toxicity and the most effective substitutions in their amino acid sequence.

PMC10003546

Yuxuan Liang,Xiaoyi Wei,Rui Ren,Xuebin Zhang,Xiyao Tang,Jinglan Yang,Xiaoqun Wei,Riming Huang,Gary Hardiman,Yuanming Sun,Hong Wang

Study on Anti-Constipation Effects of Hemerocallis citrina Baroni through a Novel Strategy of Network Pharmacology Screening

02-03-2023

daylily,constipation,16S rRNA,transcriptomes,network pharmacology

Daylily (Hemerocallis citrina Baroni) is an edible plant widely distributed worldwide, especially in Asia. It has traditionally been considered a potential anti-constipation vegetable. This study aimed to investigate the anti-constipation effects of daylily from the perspective of gastro-intestinal transit, defecation parameters, short-chain organic acids, gut microbiome, transcriptomes and network pharmacology. The results show that dried daylily (DHC) intake accelerated the defecation frequency of mice, while it did not significantly alter the levels of short-chain organic acids in the cecum. The 16S rRNA sequencing showed that DHC elevated the abundance of Akkermansia, Bifidobacterium and Flavonifractor, while it reduced the level of pathogens (such as Helicobacter and Vibrio). Furthermore, a transcriptomics analysis revealed 736 differentially expressed genes (DEGs) after DHC treatment, which are mainly enriched in the olfactory transduction pathway. The integration of transcriptomes and network pharmacology revealed seven overlapping targets (Alb, Drd2, Igf2, Pon1, Tshr, Mc2r and Nalcn). A qPCR analysis further showed that DHC reduced the expression of Alb, Pon1 and Cnr1 in the colon of constipated mice. Our findings provide a novel insight into the anti-constipation effects of DHC.

Study on Anti-Constipation Effects of Hemerocallis citrina Baroni through a Novel Strategy of Network Pharmacology Screening Daylily (Hemerocallis citrina Baroni) is an edible plant widely distributed worldwide, especially in Asia. It has traditionally been considered a potential anti-constipation vegetable. This study aimed to investigate the anti-constipation effects of daylily from the perspective of gastro-intestinal transit, defecation parameters, short-chain organic acids, gut microbiome, transcriptomes and network pharmacology. The results show that dried daylily (DHC) intake accelerated the defecation frequency of mice, while it did not significantly alter the levels of short-chain organic acids in the cecum. The 16S rRNA sequencing showed that DHC elevated the abundance of Akkermansia, Bifidobacterium and Flavonifractor, while it reduced the level of pathogens (such as Helicobacter and Vibrio). Furthermore, a transcriptomics analysis revealed 736 differentially expressed genes (DEGs) after DHC treatment, which are mainly enriched in the olfactory transduction pathway. The integration of transcriptomes and network pharmacology revealed seven overlapping targets (Alb, Drd2, Igf2, Pon1, Tshr, Mc2r and Nalcn). A qPCR analysis further showed that DHC reduced the expression of Alb, Pon1 and Cnr1 in the colon of constipated mice. Our findings provide a novel insight into the anti-constipation effects of DHC. Constipation is one of the common gastrointestinal symptoms, and different definitions of constipation lead to a range of reported incidences (from 1% to 80%) [1,2,3]. The occurrence of constipation is considered to be multifactorial [4], and it can lead to decreased quality of life and increased medical costs for people [5]. In particular, elderly people and women are more likely to be affected by constipation. Only approximately 25% of constipated people use medical treatments because of the adverse effects of some drugs [5,6,7], indicating safe and effective natural products for constipation relief are attractive. Daylily (Hemerocallis citrina Baroni, HC) is an Asphodelaceae plant widely distributed around the world. It is cultivated as an ornamental species in Europe and North and South America [8], and thousands of cultivars have been registered [9]. The flowers of various Hemerocallis species have been used as an important vegetable in Asia, especially for Hemerocallis citrina and Hemerocallis fulva [10,11]. Among them, dried daylily (DHC) is a popular vegetable because of its delicious taste and various physiological activities. Some ancient medicine books, such as the Compendium of Materia Medica (Ben Cao Gang Mu), recorded that daylily can be used for anti-depression, promoting lactation, etc. These physiological activities of daylily have been reported in recent years [12,13,14]. Ben Cao Fen Jing (an ancient medicine book) also recorded the beneficial effects of daylily on the gut and stomach. In our previous research, we found more than 728 phytochemicals in daylily using UPLC-MS/MS, mainly including flavonoids, lipids, phenolic acids, amino acids and derivatives and organic acids [12,15]. Among them, flavonoids are one of the most abundant classes of compounds in daylily. The physiological activity of daylily polysaccharides was also reported recently [16]. It is well known that the benefits of flavonoids and polysaccharides on intestinal function have been widely reported [17,18,19,20]. However, the anti-constipation role of DHC is still unclear. In this study, we investigated the anti-constipation effects of DHC using the defecation test and gastrointestinal transit test. Secondly, we aimed to evaluate the potential mechanism by measuring the content of short-chain organic acids (SCOAs) and the composition of gut microbiota in cecal contents. Then, we further evaluated the potential mechanism by integrating the network pharmacology and RNA sequencing. Lastly, we measured the expression of the related genes (Alb, Pon1, Cnr1, Nos, Ache and Grp). Compared with the Normal group (distilled water), the gastrointestinal transit rate and defecation number of the loperamide (Lop) group were significantly regulated (p < 0.05), which indicated that the constipated model was built successfully (Figure 1). For the gastrointestinal transit test, DHC did not significantly accelerate the gastrointestinal transit rate in constipated mice (Figure 1a). However, for the defecation test, compared with the Lop group, DHC treatment significantly promoted the defecation number of constipated mice (Figure 1b,c, p < 0.05). These results suggest that the acceleration of large intestinal peristalsis can be responsible for the increased defecation frequency in constipated mice. The SCOAs of the cecal contents were further evaluated to test the impact of daylily on the intestinal environment in mice (Figure 2). There were no significant differences in the levels of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid and isovaleric acid between the DHC group and the Lop group. However, compared with the Lop group, the administration of DHC elevated the contents of acetic acid (increased by 64.0%) and valeric acid (increased by 23.5%). The 16S rRNA sequencing of the cecal contents was performed to characterize the effect of DHC on the intestinal flora. The results show that the administration of DHC did not significantly promote the alpha diversity of the intestinal flora (Figure 3a), whereas it affected the structure of the gut microbiota (Figure 3b). In addition, the relative abundance of the top 30 genera was further visualized with a heatmap (Figure 4a). To further reveal the difference in the community of gut microbiota, the relative abundance of the genus was analyzed. As shown in Figure 4b, the levels of [Eubacterium]_xylanophilum_group, Monoglobus, Family_XIII_AD3011_group, HT002 and Anaerostipes were significantly reduced in the Lop group compared with those of the Normal group (p < 0.05). Conversely, the levels of Robinsoniella, Roseburia, Eisenbergiella, Robinsoniella, Ruminococcaceae_unclassified, Odoribacter and Negativibacillus were significantly increased in the Lop group than in those of the Normal group (p < 0.05). Compared with the Lop group, DHC promoted the levels of Akkermansia, Bifidobacterium, Bacteroidetes_unclassified and Flavonifractor while decreasing the levels of Peptococcaceae_unclassified, Helicobacter, RF39_unclassified, Christensenellaceae_unclassified, Vibrio, Candidatus_Stoquefichus and Negativibacillus in comparison with the Lop group (Figure 4c, p < 0.05). According to the target data of the current drug and disease database on constipation indications, a total of 309 constipation-related targets (Homo sapiens) were screened from the GeneCards, DrugBank and DisGeNET databases. After the conversion of species targets in the STRING database, a total of 278 constipation-related targets (Mus musculus) were obtained. Transcriptome profiling of colon tissue was further used to investigate gene expression regulated by DHC. There are 772 differentially expressed genes (DEGs) found between the Lop group and the Normal group (Figure 5a,b and Table S2). Compared with the Normal group, a total of 634 genes were up-regulated in the Lop group, while 138 genes were down-regulated in the Lop group. In addition, a total of 736 DEGs were observed between the DHC group and the Lop group (Figure 5a,c and Table S3). Compared with the Lop group, a total of 92 genes were up-regulated, whereas 644 genes were down-regulated in the Lop group. DEGs between groups were further used to perform KEGG functional enrichment. As a result, the top 10 KEGG pathways between the Lop group and the Normal group were Olfactory transduction, Phototransduction, Maturity onset diabetes of the young, ErbB signaling pathway, Complement and coagulation cascades, Steroid hormone biosynthesis, Neuroactive ligand–receptor interaction, Tight junction, Intestinal immune network for IgA production and Cytokine–cytokine receptor interaction (Figure 5d, p < 0.05). In addition, the top 10 KEGG pathways between the DHC group and the Lop group were Olfactory transduction, Phototransduction, Cholesterol metabolism, Regulation of lipolysis in adipocytes, PPAR signaling pathway, Neuroactive ligand–receptor interaction, Adipocytokine signaling pathway, Bile secretion, Thyroid hormone synthesis and Starch and sucrose metabolism (Figure 5e, p < 0.05). To further investigate the relationship between DEGs and constipation targets, a Venn diagram was used to illustrate the overlapping targets between the DEGs (DHC vs. Lop) and constipation targets. The results show that seven overlapping targets were found (Figure 6a). To further understand the relationship among these seven targets (Alb, Drd2, Igf2, Pon1, Tshr, Mc2r and Nalcn), the PPI relationships of these seven targets were further displayed using the PPI networks (Figure 6b and Table 1). The results show that Alb and Pon1 were the most closely associated targets in the PPI network. The relative mRNA expression of the core targets (Alb and Pon1) from the PPI network and other constipation-related targets (Cnr1, Nos, Ache and Grp) were further analyzed by qPCR. As a result, compared with the Lop group, DHC treatment significantly reduced the relative expression of Alb, Cnr1 and Pon1 in constipated mice (Figure 7, p < 0.05). Daylily is a food resource that has a long history of consumption in Asia given its delicious taste and various physiological activities. Previous studies have shown that daylily contains many potential anti-constipation components, such as flavonoids and polysaccharides. In this study, the defecation frequency and gastrointestinal transit were firstly adopted to investigate the anti-constipation effect of DHC. Then, the SCOAs and 16s rRNA sequencing of cecal contents were further performed to investigate the anti-constipation effects of DHC. Lastly, the perspective of the transcriptomes and network pharmacology was adopted to elucidate the underlying mechanisms of DHC. Constipation is a common symptom affecting people of all ages, and it results in an expensive burden on the economy [21]. Although laxative drugs are used to treat constipation and have good effects, side effects have been reported with using these drugs [22]. Recently, dietary supplements (such as natural products, prebiotics and probiotics) with anti-constipation effects have drawn the attention of researchers due to their good effectiveness, high safety and low costs [23,24,25]. In this study, DHC treatment did not promote the gastrointestinal transit but significantly accelerated the defecation frequency of constipated mice. The gut metabolites (SCOAs) are closely related to the development of constipation [26,27]. To investigate the anti-constipation role of DHC, the contents of SCOAs in the cecal contents were further measured by GC. As a result, although increasing trends of acetic acid and valeric acid were found, the contents of SCOAs (acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid and isovaleric acid) were not significantly regulated by DHC. These results suggest that the constipation-relieving effects of DHC may not involve the regulation of SCOAs in the cecum. Accumulating evidence reported that alterations in the intestinal microbiota of the host are closely associated with the regulation of constipation. In this study, 16S rRNA sequencing was performed to characterize the regulation of DHC on the intestinal flora in constipated mice. The results show that 11 genera were significantly regulated (p < 0.05). Bifidobacterium is a well-known intestinal probiotic, and accumulating evidence suggested that increased Bifidobacterium was beneficial for constipation relief [28,29]. Our results show that DHC significantly promoted the levels of Bifidobacterium (p < 0.05). Akkermansia reportedly plays a positive role in metabolic modulation and gut health protection [30,31,32,33]. For example, Akkermansia can decrease the pro-inflammatory factor expression to relieve ulcerative colitis [34]. Previous studies reported that some probiotics (Bifidobacterium longum and Lactobacillus plantarum KFY02) and symbiotics can alleviate constipation, and they all promoted the relative abundance of Akkermansia [32,35,36]. In this study, DHC elevated the levels of Akkermansia (p < 0.05). Flavonifractor is a flavonoid-degrading bacterium [37], and our results show that DHC promoted the level of increased Flavonifractor, suggesting gut microbiota can utilize flavonoids of DHC to exert a physiological effect. Taken together, these results reveal the anti-constipation effects of DHC involving the proliferation of beneficial bacteria and flavonoid-utilizing bacteria and the inhibition of harmful bacteria. Furthermore, the KEGG pathway enrichment was performed to further reveal the underlying mechanism of DHC in constipation relief. In this study, the KEGG pathway enrichment of DEGs (Lop vs. Normal; DHC vs. Lop) showed that olfactory transduction was the most significantly enriched pathway. In this pathway, LOP up-regulated the expression of 40 genes compared with Normal, whereas DHC down-regulated the expression of 38 genes compared with Lop (Figure 5d,e). It is well known that SCOAs, indoles and ammonia are known to be odorous compounds in feces. SCOAs are considered beneficial to health, while indole and ammonia are the opposite. Feces odor is associated with constipation [38]. Protein catabolism in the gut may produce compounds that are toxic to the host, such as amines and indoles, which can potentially affect intestinal motility [39,40,41]. A previous study reported that lactosucrose treatment significantly reduced the concentrations of p-cresol, indole, skatole and ammonia in feces in the elderly with constipation [42]. We speculate that some harmful odorous compounds are produced in the gut of constipated mice, while DHC treatment reduces the level of these odorous compounds. These results indicate that olfactory transduction is closely related to the anti-constipation role of DHC. However, the role of olfactory transduction in the anti-constipation of DHC still needs further study. In recent years, the network pharmacology method has emerged as an effective strategy for establishing relationships between genes and diseases [43,44]. Herein, we adopted the network pharmacology strategy to systematically collect constipation-related targets through GeneCards, DrugBank and DisGeNET. According to the list of overlapping targets, the indirect relationship between DEGs (DHC vs. Lop) and constipation targets was established. As a result, we found that DEGs (DHC vs. Lop) and constipation targets shared seven overlapping targets, and the PPI network of overlapping targets further revealed that Alb and Pon1 were the two main targets in the PPI network. Alb encodes serum albumin, and the constipation scoring system was significantly and negatively correlated with the serum albumin level [45,46]. Furthermore, Alb was regarded as a core anti-constipation target of raffino-oligosaccharide [47]. Pon1 was found to have been significantly related to chronic constipation in a cross-sectional study [48]. In this study, the administration of DHC significantly down-regulated the expression of Alb and Pon1 in constipated mice (p < 0.05). Grp codes a gastrin-releasing peptide, which is associated with bowel motility [49,50]. Ache and Nos are important regulators of gut peristalsis, and they are also common genes of interest in gastrointestinal motility studies [51,52,53]. However, in this study, the expression of these genes was not significantly regulated by DHC intervention. A previous study reported that the activation of Cnr1 receptors slowed down the peristalsis of the colon [54], while a Cnr1 inverse agonist relieved the slow gastrointestinal motility [55]. Herein, DHC treatment significantly down-regulated the expression of Cnr1 (Figure 7, p < 0.05). In a word, the qPCR analysis suggested that the anti-constipation effect of DHC involved the regulation of Alb, Pon1 and Cnr1. The dried daylily (flower bud) was obtained from Yunxing Lake Modern Agricultural Center (Qidong, China), and it was subjected to superfine grinding according to the research of Hu et al. [56]. The loperamide hydrochloride was purchased from Dashenlin Pharmacy, which was produced in Janssen Pharmaceutical Ltd. (Xi’an, China). The active charcoal and gum Arabic were bought from Hengxing (Tianjin, China). A total of 30 male BALB/c mice (7 weeks old and weighing 20 g ± 2 g) were purchased from Guangdong Medical Laboratory Animal Centre (Guangzhou, China). All mice were fed under standard conditions, and the Ethics Committee of South China Agricultural University (SYXK 2019-0136) approved this experiment. For defecation test, 30 mice were randomly divided into three groups (n = 10) after 7 days of adaptive feeding: normal control group (Normal, distilled water), constipation model group (Lop, distilled water) and dried daylily group (DHC, DHC suspension). Three groups were administered with 0.5 mL/mouse/day in the corresponding sample by vialing gavage once a day for 14 days. On this basis, 30 min after completing the original gavage, the Lop group and the DHC group were treated with loperamide (5 mg/kg body weight; 0.5 mL) via gavage from Day 12 to Day 14 to induce constipation [29,57]. Correspondingly, the Normal group was given an additional 0.5mL distilled water from Day 12 to Day 14. Then, the defecation status (fecal numbers in six hours) of each mouse in a separate cage was observed. DHC powder and Lop powder were distributed in distilled water as a suspension. A 10 g/day dosage of dried daylily for an adult (70 kg) was considered, which is equivalent to 0.14 g/kg per day. Referring to the technical standards for testing and assessment of functional food formulated by China Food and Drug Administration and our previous research [57], mice were administered with DHC at a dose of 1.4 g/kg body weight/day. All groups fasted for 16 h (water was available) before measurement of the gastro-intestinal transit. At the end of the experiment, after giving Lop for 30 min, each group was intragastrically given activated carbon suspension (containing 5% activated carbon and 10% gum Arabic) containing corresponding samples (Normal group: water; Lop group: Lop; DHC group: DHC). After 25 min, the mice were anesthetized with pentobarbital and euthanized. The gastrointestinal transit rate was calculated using our previous method [57]. The cecal content and colon tissue were collected and stored at −80 °C. The cecal contents of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid and isovaleric acid in mice were detected by gas chromatography (GC, 7890B, Agilent, Santa Clara, CA, USA), and the corresponding standard samples were obtained from Macklin (Shanghai, China). For GC detection, FFAP elastic quartz capillary column (30 m × 0.25 mm × 0.25 μm) was used, and the initial temperature was 70 °C, then increased at 5 °C/min to 150 °C (maintained 2 min). Nitrogen was used as the carrier gas (flow rate 2 mL/min). The detector temperature was 280 °C, and the injection volume was 2 μL. The cecal contents of mice were used to perform 16S rRNA sequencing. Cetyltrimethylammonium bromide was used to extract DNA from the cecal content. The primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′) were used to amplify the V3–V4 variable region of 16S rRNA gene by PCR. The paired-end sequenced (2 × 250) was performed on the NovaSeq PE250 platform. Detailed information on the sequencing procedures was shown in the previous study [57]. The constipation-related therapeutic targets were screened by GeneCards (four times the score of all the targets, the score > 3.79) [58], DrugBank [59] and DisGeNET 7.0 (the score > 0.1) [60]. To reveal the relationship between daylily and constipation, a Venn diagram was used to illustrate the overlapping targets between DHC targets and constipation targets. Protein–protein interaction (PPI) networks of the overlapping targets were constructed by STRING. The proximal colons of the mice were cleaned with saline and stored in a −80 °C freezer until transcriptomic sequencing. The total RNA of these tissues was isolated and purified with the TRIzon kit (CWBIO, Beijing, China) and the RNA was reverse transcribed according to the manufacturer’s instructions. (Invitrogen, Carlsbad, CA, USA). Quantity and purity of total RNA were evaluated by NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA), and the integrity of RNA was detected by Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). RNA libraries were created using the TruSeq RNA sample preparation kit (Illumina, San Diego, CA, USA). Illumina NovaseqTM 6000 was used for the RNA sequencing, and the read length of PE150 was adopted. The details of the transcriptomic analysis were consistent with the previous study [61]. For analysis of differential expression, the screening criteria of DEGs were set as FC ≥ 2 or FC ≤ 0.5 and p-value < 0.05. The RNA samples for qPCR analysis were selected from the same colon tissues used for RNA sequencing. qPCR analysis was performed using a TB Green® Premix Ex Taq™ II kit (Takara, Shanghai, China) and Bio-Rad C1000 Thermal Cycler Real-Time PCR System (Bio-Rad, Hercules, CA, USA). The reverse transcription reaction system is a final volume of 10 μL, including 1 μg RNA, 1 μL PrimeScript RT Enzyme MixⅠ, 1 μL RT Primer Mix, 4 μL 5 × PrimeScript Buffer and RNase-free water (37 °C for 15 min and then 85 °C for 5 s). Amplification volume was 20 μL containing 2 μL cDNA, 0.8 μL forward primer (10 μM), 0.8 μL reverse primer (10 μM), 0.4 μL ROX Reference Dye (50×), 10 μL SYBR Premix Ex Taq Ⅱ and 6 μL RNase free water. The amplification conditions were a pre-denaturation program (95 °C for 30 s), and the amplification program (95 °C for 5 s, and 60 °C for 34 s) was for 40 cycles. The expression level of Gapdh was normalized [12]. Table S1 provides detailed information on the primers used. The relative expression levels of gene expression were calculated by the ΔΔCt method. The Least Significant Difference Test and Kruskal–Wallis Test (SPSS version 20.0) were used to analyze the differences between groups according to whether the variances were consistent between groups [57,62]. All data were expressed with the mean ± SD, and a p < 0.05 was considered statistically significant. Our findings reveal that the administration of DHC accelerated the defecation frequency of mice. It elevated the abundance of Akkermansia, Bifidobacterium and Flavonifractor in cecal contents while reducing the levels of pathogens (such as Helicobacter and Vibrio) in cecal contents. A transcriptomic analysis further found 736 DEGs in the colon after DHC intervention, which mainly involved the olfactory transduction pathway. Furthermore, the integration of transcriptomes and network pharmacology revealed seven overlapping targets (Alb, Drd2, Igf2, Pon1, Tshr, Mc2r and Nalcn). A qPCR analysis further showed that DHC effectively down-regulated the expression of Alb, Pon1 and Cnr1 in the colon. These results improve the understanding of the anti-constipation effect of daylily and provide a novel integrated perspective of transcriptomes and network pharmacology.

PMC10003547

Michał Bereza,Mateusz Dembiński,Agnieszka E. Zając,Jakub Piątkowski,Monika Dudzisz-Śledź,Piotr Rutkowski,Anna M. Czarnecka

Epigenetic Abnormalities in Chondrosarcoma

25-02-2023

chondrosarcoma,epigenetic mechanisms,targeted therapy

In recent years, our understanding of the epigenetic mechanisms involved in tumor pathology has improved greatly. DNA and histone modifications, such as methylation, demethylation, acetylation, and deacetylation, can lead to the up-regulation of oncogenic genes, as well as the suppression of tumor suppressor genes. Gene expression can also be modified on a post-transcriptional level by microRNAs that contribute to carcinogenesis. The role of these modifications has been already described in many tumors, e.g., colorectal, breast, and prostate cancers. These mechanisms have also begun to be investigated in less common tumors, such as sarcomas. Chondrosarcoma (CS) is a rare type of tumor that belongs to sarcomas and is the second most common malignant bone tumor after osteosarcoma. Due to unknown pathogenesis and resistance to chemo- and radiotherapies of these tumors, there is a need to develop new potential therapies against CS. In this review, we summarize current knowledge on the influence of epigenetic alterations in the pathogenesis of CS by discussing potential candidates for future therapies. We also emphasize ongoing clinical trials that use drugs targeting epigenetic modifications in CS treatment.

Epigenetic Abnormalities in Chondrosarcoma In recent years, our understanding of the epigenetic mechanisms involved in tumor pathology has improved greatly. DNA and histone modifications, such as methylation, demethylation, acetylation, and deacetylation, can lead to the up-regulation of oncogenic genes, as well as the suppression of tumor suppressor genes. Gene expression can also be modified on a post-transcriptional level by microRNAs that contribute to carcinogenesis. The role of these modifications has been already described in many tumors, e.g., colorectal, breast, and prostate cancers. These mechanisms have also begun to be investigated in less common tumors, such as sarcomas. Chondrosarcoma (CS) is a rare type of tumor that belongs to sarcomas and is the second most common malignant bone tumor after osteosarcoma. Due to unknown pathogenesis and resistance to chemo- and radiotherapies of these tumors, there is a need to develop new potential therapies against CS. In this review, we summarize current knowledge on the influence of epigenetic alterations in the pathogenesis of CS by discussing potential candidates for future therapies. We also emphasize ongoing clinical trials that use drugs targeting epigenetic modifications in CS treatment. Chondrosarcoma (CS) is a heterogeneous type of primary bone tumor that presents different morphologic features and responses to treatment. CS constitutes the second most common primary solid bone tumor following osteosarcoma [1]. According to the most recent WHO classification [2], CS can be classified into primary central CS, secondary central CS, and secondary peripheral CS (grade 1, and grade 2 and 3), which had previously been described as conventional CS, periosteal, dedifferentiated, and mesenchymal CS. The most common type of this tumor is primary central CS (75% of cases). The risk of metastases depends on the grade of CS. Low-grade CS (grade 1) has about a 10% risk of metastases, whereas in high-grade CS (grades 2 and 3) the risk is 50–70% [3]. The long bones and pelvic bones are the most commonly affected [4]. Patients usually complain of long-lasting pain and swelling close to the altered bone [5]. Tissue biopsies and imaging studies are essential to diagnose and differentiate CS from other tumors [5]. The most efficient method of treating these tumors is surgical excision. Other therapeutic options, such as chemotherapy/radiation therapies, are not effective in the treatment of CS (except for the use of chemotherapy in dedifferentiated CS containing high-grade spindle cell components and mesenchymal CS, and for the use of radiation therapy after incomplete resection or local recurrence in intermediate CS and high-risk CS) [5,6]. Due to the limited therapeutic options in CS treatment, it is essential to look for new methods of treatment. Therefore, focusing on epigenetic mechanisms may be promising in the development of new therapeutic methods. These mechanisms include e.g., DNA methylation and demethylation, histone modifications, and microRNA-regulated epigenetic changes [7,8]. Epigenetic modifications might be considered as potential targets for specific drugs, as well as diagnostic and prognostic factors [9]. In this review, we discuss the current state of knowledge of epigenetics in CS, describe novel potential therapeutic targets, and summarize ongoing epigenetics-based clinical trials. DNA methylation is a process of adding a methyl group to a nucleotide base of the DNA, catalyzed by the action of DNA methyltransferase enzymes (DNMTs) [10,11]. DNA hypomethylation, in contrast to DNA methylation, refers to the loss of the methyl group(CH3) in the 5-methylcytosine nucleotide [12]. Two DNMT inhibitors, 5-azacytidine (azacytidine) and 5-aza-2′-Deoxycytidine (decitabine, DAC), have been already approved by the FDA for the treatment of some hematological diseases e.g., acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) [13]. Hypomethylation can be divided into two classes: global hypomethylation and hypomethylation of a single gene [10]. Among global hypomethylation, we can distinguish repetitive DNA sequences, such as Satellite 1 and long interspersed nuclear elements 1 (LINE-1; L1). Satellite 1, a member of the satellite DNA family (mentioned in Table 1), has been associated with a variety of important cell functions, from correct segregation of chromosomes and genome stability to its association with regulatory functions through satellite transcripts [14]. L1 (Table 1) plays a role in genome instability in tumors and, via its retrotransposition activity, participates in tumor progression [15]. Therefore, both Satellite 1 and L1 may become promising biomarkers and/or therapeutic targets. In the study by Hamm et al. [16], performed on Swarm rat CS (SRC) cells treated with DAC, both repetitive DNA sequences (Satellite 1 and L1) were hypomethylated after treatment with DAC. In the same study, SRY-related HMG-box transcription factor 2 (Sox-2) and neurite outgrowth-promoting factor 2 (midkine, MDK) were found to be overexpressed and there was a decrease in the methylation level in the promoter of both genes (SOX2 and MDK) after DAC treatment (Table 1) [16]. After DAC administration, the tumor became more invasive, grew faster, and was larger, both in in vitro and in vivo models [16]. However, the effect of DAC is different among various CS cell lines. The research mentioned above was carried out on the SRC-MSCV3-LTC cell line, while Bui et al. [17] have shown in the H-EMC-SS cell line that DAC can restrict CS cell growth and invasiveness through increased expression of the Heparin-Glucosamine 3-O-Sulfotransferase (3-OST-2) gene (Table 1). Research conducted on SRC cells revealed that Sox-2 and MDK may have a significant impact on the pathogenesis of CS [16]. In general DAC is effective in the treatment of hematopoietic malignancies; however, it can also promote tumorigenesis through the hypomethylation of specific genes, as shown in this research. Further research is needed in these field in CS models [16,18]. In CS, decreased methylation was also observed in cytosine–guanosine dinucleotide (CpG) sites. It was associated with increased expression of the epithelial-specific markers Mammary serine protease inhibitor (Maspin), encoded by the serine protease inhibitor b5 (SERPINB5), and 14-3-3σ, encoded by Stratifin (SFN), during the development and progression of CS cells after DAC treatment with DAC (Table 1) [19]. Maspin is a regulatory protein that cooperates with a variety of intracellular and extracellular proteins and regulates cell adhesion, motility, apoptosis, and angiogenesis [20]. The tissue-specific expression of Maspin is epigenetically controlled and aberrant methylation of the Maspin promoter is closely associated with Maspin gene silencing [20]. 14-3-3σ expression is regulated by a p53-dependent pathway and by epigenetic deregulation. Moreover, 14-3-3σ is a significant G2/M cell cycle checkpoint regulator and inhibits nuclear localization of the CDC2/cyclin B complex, which is essential for mitosis progression through mitosis [21,22]. 14-3-3σ was also revealed to be epigenetically silenced in many tumors by methylation of CpG and can cause tumor development and progression through impaired cell cycle control [22,23]. In the same study by Fitzgerald et al. [19], the treatment of chondrocyte cells with DAC led to the downregulation of the transcription factor snail, the mediator of epithelial–mesenchymal transitions (EMT), [16]. These results showed an epigenetic switch associated with the mesenchymal to epithelial transition (MET) in CS [16]. Furthermore, the microenvironment may play a role in global hypomethylation processes in CS. The study by Hamm et al. investigated the impact of the microenvironment on the methylation status of SRC cells [24]. In their study, the researchers transplanted SRC cells into different positions in Sprague-Dawley rats, e.g., subcutaneous and tibia, and performed pyrosequencing to distinguish the methylation status of these locations compared with normal cartilage tissue [24]. The study revealed differences in gene expression profiles in SRC and normal cells. The researchers indicated that thymosin-β4, FBJ Murine Osteosarcoma Viral Oncogene Homolog (c-fos), and connective tissue growth factor (CTGF) may play a role in CS development and metastatic spread [24]. Furthermore, different sites of transplantation had a significant impact on the epigenetic profile of SRC cells. The subcutaneous tumors were larger compared to tibial tumors, but the tibial tumors were more invasive. However, in both tumor types, the genome was hypomethylated compared with normal cartilage tissue. In conclusion, the microenvironment can affect DNA methylation in CS cells; however, there are still limited data in this area and further research is needed [24]. DNA methylation is an epigenetic process that leads to the addition of a methyl (CH3) group to a CpG in the DNA chain. This mechanism alters the silencing of DNA activity and gene expression [25]. DNA hypermethylation has been confirmed to play an important role in the pathogenesis of multiple tumor types, including lung, breast, liver, and colon cancer, as well as melanoma, and glioma [26,27]. Multiple genes are involved in this process, including the isocitrate dehydrogenase 1 (IDH1)/isocitrate dehydrogenase 2 (IDH2) genes, which encode cytosolic (IDH1, NADP+) and mitochondrial (IDH2, NADP) enzymes. These genes are found to be altered in acute myeloid leukemia [28], glioma [29], cholangiocarcinoma [30] and CS [31]. IDH1 mutations are commonly found in CS—in approximately 50% of all CSs [31]—and have major impacts on cell metabolism and proliferation. In normal cells, IDH1/IDH2 plays an important role in the tricarboxylic acid cycle by isocitrate to α-ketoglutarate conversion [32]. The mutated IDH—with a gain of novel catalytic activity—promotes the accumulation of δ-2-hydroxyglutarate (D2HG), an oncometabolite, which causes inhibition of α-KG-dependent dioxygenases and, consequently, hypermethylation of DNA and histones [33]. Consequently, many important biological functions are blocked, e.g., regulation of DNA hydroxymethylation, RNA and histone demethylation, and prolyl hydroxylation of collagen and hypoxia-inducible factors [34]. Disturbances in these mechanisms can lead to overexpression of oncogenic genes or underexpression of tumor suppressor genes and, consequently, progress to malignancy [34]. The study conducted by Guilhamon et al. [35] has demonstrated independent activation of the retinoic acid receptor (RAR) signaling pathway in primary CS with the IDH mutation-correlated hypermethylation phenotype. The authors suggested that inhibition of ten-eleven-translocation methylcytosine dioxygenase (TET) enzymes could be a mechanism of DNA hypermethylation in CS with IDH mutations. TET enzymes are inhibited by the increased production of D2HG. This process affects the methylation of DNA at CpG islands, which then enrich for genes associated with stem cell maintenance, differentiation, and lineage specification [36,37]. On the other hand, the rare occurrence of TET mutations simultaneously with IDH mutations suggests another mechanism of this event [35,38]. The TET enzymes work through the oxidation of 5-methylcytosines (5-mC), which results in a decrease in DNA methylation [39]. The study by Lu et al. [37] showed that IDH mutations were also related to DNA hypermethylation at CpG islands in CS. Another study demonstrated that levels of 5-mC and 5-hydroxymethylcytosine (5-hmC) in central CS were variable, but not associated with IDH mutations and not directly dependent on TET inhibition by 2HG [40]. In addition to this, studies on human CS cells with the inhibitor of IDH1—N-[2-(cyclohexylamino)-1-(2-methylphenyl)-2-oxoethyl]-N-(3-fluorophenyl)-2-methyl-1H-imidazole-1-acetamide (AGI-5198) decreased D2HG levels in two cell lines and inhibited cell formation and migration, with interruption of cell cycling and apoptosis induction [41]. However, the study by Suijker et al. [42] with the AGI-5198 agent—the first highly potent and selective inhibitor of IDH1 R132H/R132C mutants—showed that the use of mutated IDH inhibitors may not always be efficient for the treatment of operable or metastasized CS patients [42]. In another study, almost all primary cartilage tumors with a mutation in IDH presented the CpG island methylator phenotype (CIMP). The tumors were clustered into two groups: benign/low-grade tumors and high-grade tumors [43]. The analysis performed in this study demonstrated that grade 3 CSs were more strongly methylated than grade 2 CSs. Furthermore, due to promoter methylation, both signal transduction and inflammation-related genes were affected [43]. In the same study, an epigenetic compound screen was performed to indicate potential novel targets for the therapeutic strategy. The results showed that inhibitors of several proteins, i.e., Aurora kinase inhibitors, bromodomain and extra-terminal motif (BET), Fms related receptor tyrosine kinase 3 (FLT3), histone deacetylase (HDAC) inhibitors, and Janus kinase (JAK), reduced the growth of all CS cell lines (independent of the IDH mutations status) [43]. Hypermethylation of CpG islands was also observed in dedifferentiated CS. In this study, the low-grade chondroid compartment presented hypermethylation of p16INK4 and E-cadherin (CDH1) promoters (Table 1) [44]. The osteosarcomatous compartment of dedifferentiated CS has the same aberrations in p16INK4, fragile histidine triad diadenosine triphosphatase (FHIT) (Table 1) and CDH1 promoters. No methylation in p14ARF and p21WAF1 promoters was detected [44]. Other genes involved in the hypermethylation of the CpG islands in CS are nicotinamide phosphoribosyl transferase (NAMPT) and nicotinic acid phosphoribosyl transferase (NAPRT)—intracellular enzymes that catalyze the first step in the biosynthesis of NAD from nicotinamide and nicotinic acid [45]. Hypermethylation in the promoters of these genes led to decreased cell viability. However, the pro-apoptotic effect on CS cell lines was not related to the status of the IDH mutation. Moreover, an increased level of methylation of the NAPRT promoter was observed in high-grade, compared with low-grade, CS. It suggests that NAMPT and NAPRT inhibitors may be potentially useful in the treatment of high-grade CS [45]. Diminished expression of the RUNX family transcription factor 3 (RUNX3) tumor suppressor gene is found in many cancers, for example, breast cancer [46] or hepatocellular carcinoma [47]. Jin et al. [48] confirmed that this gene is also underexpressed in CS. The molecular analysis of tumor specimens acquired from patients who did not undergo chemotherapy or radiotherapy revealed that RUNX3 protein and RUNX3 transcript levels were reduced compared with normal tissue. Immunostaining of tissue samples also showed loss of RUNX3 expression relative to normal tissue [48]. The methylation status of CS cells assessed by methylation-specific PCR (MSP) confirmed excessive methylation of the RUNX3 promoter region. RUNX3 expression was strongly associated with a positive prognosis in patients with CS. The same research showed that a poor prognosis was correlated with a negative expression of RUNX3. To verify the results, the CS cell line SW135 was transfected with pcDNA3.1-RUNX3. The results similarly revealed that RUNX3 expression inhibits proliferation and promotes apoptosis in CS cells [48]. Another study demonstrated that Apolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3B (APOBEC3B) caused a reduction in the antitumor activity of RUNX3. APOBEC3B protects the immune system from retrovirus infection and protects the cell from endogenic mobile retroelements [49,50]. Cells without APOBEC3B knockdown had a lower apoptotic ratio than RUNX3-positive SW1353 cells with APOBEC3B knockdown, so it could be deduced that APOBEC3B obstructs RUNX3 transcription. Potential therapy to improve apoptosis in CS may involve the suppression of APOBEC3B knockdown [50]. There is an association between the expression of the p73 protein and aberrant methylation patterns in CS [51]. p73 is a protein which is part of the p53 tumor suppressor family. Due to their similar structures, both p53 and p73 are regarded as anti–oncogenic factors [52,53]. p73 shows the ability to influence the transcription of genes controlled by p53; for example, p21WAF1, mouse double minute 2 homolog (MDM2), B cell CLL/lymphoma2 (Bcl-2) Associated X-protein (BAX), 14-3-3s, and phorbol-12-myristate-13-acetate-induced protein 1 (PMAIP1, NOXA) [51,54]. As a result, the cell undergoes apoptosis or cell cycle arrest [55,56]. According to Liu et al. [51], in CS cell lines, the expression of p73 was significantly decreased as a result of hypermethylation of the p73 promoter region. Furthermore, the level of methylation correlated with the histological grade of the tumor. Grade 2 and 3 CS cells had a markedly higher level of methylation compared to grade 1 CS. Therefore, the analysis of methylation could be used as a prognostic tool and p73 could be a target for the treatment of CS. The research conducted by Tan et al. [57] revealed that pigment epithelium-derived factor (PEDF) induced apoptosis in the CS cell line. The molecular analysis has shown changes in the expression of multiple factors that participate in the cell cycle and apoptosis. Importantly, p73 expression was significantly elevated. PEDF works through multiple mechanisms as it affects molecules involved in apoptosis, cell adhesion, and invasion of cells. Therefore, it should be investigated as a candidate for the targeted treatment of CS [57]. MicroRNAs (miRNAs) are small noncoding RNAs involved in the post-transcriptional regulation of gene expression and, as epigenetic modulators, affect the protein levels of the target mRNAs without modifying the gene sequences [17,69]. They are mainly endogenous and transcribed from genomic DNA. By binding to 3′UTRs and inducing transcript degradation or translational repression, miRNAs can induce the downregulation of their target mRNAs. However, miRNAs can also bind to other regions within the mRNAs, which, in certain situations, induces gene expression upregulation [70,71]. MicroRNAs are involved in chondrogenesis and cartilage diseases [72], and they may also act as tumor suppressors or as oncogenes [73]. There are several thousand miRNAs in humans [74]. MicroRNA can control angiogenesis by inhibiting vascular endothelial growth factor A (VEGF-A) signaling and CS cell proliferation [75]. Two important main studies, which revealed down-regulation of let-7a, hsa-miR-100, hsa-miR-136, hsa-miR-222, hsa-miR-335, and hsa-miR-376a, and up-regulation of hsa-miR-96 and 183 in CS cell lines and tissue samples, were published by Yoshitaka et al. [76] and Nugent et al. [77]. The most important miRNAs in CS are, among others, hsa-miR-30a, which inhibits proliferation; hsa-miR-218 and hsa-miR-524-5p, which increase proliferation; hsa-miR-125b and hsa-miR-192, which enhance chemosensitivity; hsa-miR-16-5p, which promotes angiogenesis; hsa-miR-519d and hsa-miR-145, which inhibit metastases; and hsa-miR-26a and hsa-miR-199a, which inhibit angiogenesis [78]. Liang et al. [79] have shown that hsa-miR518b overexpression decreases the expression of Bcl-2 in human CS cell lines, which induces apoptosis and inhibits cell migration. On the other hand, hypoxia regulates hsa-miR-181 in CS, which up-regulates the expression of VEGF and matrix metalloproteinases (MMPs) [80]. Overexpression of hsa-miR-181a was observed in high-grade CS, promoting tumor progression. In 2019, Sun et al. [80] published results of the systemic and local intratumoral use of anti-miRNA oligonucleotides directed against hsa-miR-181a, the regulator of G-protein signaling 16 (RGS16) [80,81]. In general, the removal of hsa-miR-181a restored RGS16 expression and inhibited tumor progression [80]. Hameetman et al. [82] also found that miRNAs are involved in the malignant transformation of osteochondroma to CS. Galoian et al. [83] have found up-regulation of tumor suppressors hsa-miR-20a, hsa-miR-125b, hsa-miR-192, and down-regulation of onco-miRNAs, hsa-miR-490-3p, hsa-miR-509-3p, hsa-miR-589, and hsa-miR-550 in the human JJ012 CS cell line treated with the mammalian target of the rapamycin complex 1 inhibitor (mTORC1). In another study carried out in CS cells and in vivo in mice, overexpression of breast cancer anti-estrogen resistance 4 (BCAR4), a long noncoding RNA (lncRNA) that participates in the formation of multiple cancers [84], resulted in hyperacetylation of histone H3 in the mammalian target of rapamycin (MTOR) promoter. Activation of the mTOR signaling pathway led to the progression of CS cells through the proliferation and migration of CS cells [73]. In vivo experiments confirmed that increased tumor growth was associated with BCAR4 overexpression. On the other hand, blocking this pathway nullified the outcome of BCAR4 expression [73]. Nicolle et al. analyzed a series of 102 cartilage tumors, mostly CSs (89%), from 8 clinical sites in France treated between 1997 and 2013 [85]. Among many parameters evaluated, CS microRNA profiling was performed using RNAseq. The most differentially expressed microRNAs were frequently found at the 14q32 locus, defining the level of malignancy. Therefore, assessment of miRNA could be used as a prognostic tool in CS. MiRNAs may also be involved in mechanisms responsible for CS resistance to chemotherapy. Tang et al. [86] discovered that hsa-miRNA-125b causes sensitization of CS cell to treatment with doxorubicin via inhibition of erb-b2 receptor tyrosine kinase 2 (ErbB2) and glucose metabolism. ErbB2 is known to be overexpressed in cancer cells and promote glycolysis and further proliferation of cells [87]. These findings show a new possible approach to treatment of CS with a combination of epigenetic drugs and chemotherapy. Acetylation of histones is a process that leads to the addition of an acetyl group to lysine residues present in the core histones. As a result, the ionic charge of histone changes from positive to neutral. DNA, which has a negative charge, becomes separated from histones and, consequently, transcription factors gain access to DNA. Therefore, hyperacetylation is associated with the active expression of genes. HDAC are enzymes that decrease histone acetylation, resulting in chromatin remodeling and decreased expression of particular genes. [88] In tumors, down-regulated expression is related to proteins involved in the cell cycle and proliferation. Several experiments revealed that HDAC inhibitors can restore abnormal gene silencing and stop tumor progression [88,89]. Therefore, they can be a potential target for the treatment of CS. One of the candidates in CS treatment, targeting HDAC, may be resveratrol, which activates the expression of Sirtuin1 (SIRT1). Abnormal SIRT1 expression increases the metastatic potential of CS cells by induction of the EMT [90]. Additionally, SIRT1 expression was correlated with tumor progression and prognosis in patients with CS [90]. Resveratrol acts as an nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) deactivator through deacetylation of the p65 subunit, which forms NF-κB. It also promotes apoptosis through the activation of caspase 3 [91]. The antiapoptotic ability of resveratrol was confirmed in vivo by using a CS cell xenograft in mice. Tumor growth after resveratrol treatment was significantly inhibited. After tumor excision, SIRT1 and caspase 3 levels in tumor cells increased [91]. Another HDAC inhibitor, depsipeptide, a protein that promotes the expression of the p21 protein and regulates the cell cycle [92], was observed to induce apoptosis and cell cycle arrest in CS cells [93]. Furthermore, the expression of the collagen alpha-1(II) chain (COL2A1) gene was also increased as a consequence of histone H3 acetylation in the promoter and enhancer of COL2A1. The depsipeptide also has an impact on the composition of the extracellular space due to higher levels of aggrecan expression and a2 chain of type XI collagen [93]. HDAC inhibitors can also regulate CS cell differentiation. Histological analysis has shown that CS cells treated with depsipeptide differentiate into the hypertrophic phenotype [93]. These antitumor effects were also confirmed in vivo by decreased tumor growth and markedly more differentiated cells. Inhibitors of deacetylases can also regulate CS cell proliferation by a mechanism that is not related to epigenetics. Histone deacetylase 6 (HDAC6) can regulate the structure of the cytoskeleton and cilia [94,95]. CS lacks the proper sensor of primary cilia due to the increased activity of HDAC6. Inhibition of HDAC6 with tubastatin A caused inhibition of CS cell proliferation. Increased expression of acetylated a-tubulin, a protein present in the cilia, was also observed in the affected cells [96]. Histone methylation plays a significant role in gene expression. This process is carried out by two classes of enzymes: histone methyltransferases (HMTs) and histone demethylases (HDMs). Depending on the position of methylation, it can promote or suppress the transcription of genes [97]. For example, methylation of histone H3 lysine K4 (H3K4), histone H3 lysine K36 (H3K36), and histone H3 lysine K79 (H3K79) promotes transcription, while methylation of histone H3 lysine K9 (H3K9), histone H3 lysine K27 (H3K27), and histone H4 lysine K20 (H4K20) leads to repression of transcription by chromatin remodeling [97]. H3K4, H3K9, and H3K27 are believed to control the promoter region of SRY-Box transcription factor 9 (SOX9) and COL2A1 genes [98,99]. HDM inhibitors have already been shown to decrease cell proliferation in gliomas and acute lymphoblastic leukemia [100,101]. Due to the positive results of research conducted on different tumors, HDMs have begun to be investigated in CS [102]. One of the HDM inhibitors studied in CS cells is GSK-J4, which has shown an antiproliferative effect on CS cells [103]. GSK-J4 is an inhibitor of histone demethylases of Lysine specific demethylase 6A (KDM6A, UTX) and Lysine demethylase 6B (KDM6B, JMJD3). Both UTX and JMJD3 regulate the methylation of H3K27. GSK-J4 has been proven to reduce proliferation in CS without affecting normal chondrocytes. Moreover, it induces apoptosis and senescence in CS cells. The combination of GSK-J4 and cisplatin showed a decreased proliferation of CS cells compared with treatment with cisplatin or GSK-J4 alone, but not all CS cell lines were treated with both drugs. Due to the insufficient amount of data, more molecular tests should be performed before moving to pharmacological treatment [103]. Another HDM described in CS is lysine-specific demethylase 1 (LSD1). This enzyme participates in stem cell proliferation and differentiation, as well as in the regulation of EMT via repression of CDH1 [104]. LSD1 demethylates H3K4 mono-/dimethylation (H3K4me1/2), leading to the repression of gene expression. At the same time, it induces H3K9me1/2 demethylation, which activates the expression of genes [105,106]. Its influence on epigenetics suggests that it is a proto-oncogenic factor. LSD1 is overexpressed in CS, similarly to other tumors, e.g., neuroblastomas, breast carcinomas, leukemias, bladder, lung, colorectal carcinomas, and other types of sarcomas [107,108]. Therefore, it may be another promising target to investigate. A candidate drug can be Tranylcypromine, which is an inhibitor of monoamine oxidase used to treat patients with depression and anxiety [109]. On the other hand, it also has the effect of irreversibly inhibiting LSD1. Tranylcypromine has shown an antiproliferative effect in neuroblastoma, breast carcinoma, and synovial sarcoma, supporting further research on LSD1-targeting drugs in the treatment of CS [108]. One more therapeutic possibility for CS involves proline-rich polypeptide-1 (PRP-1). It is an inhibitor of H3K9 demethylase that can restore the expression of anti-inflammatory cytokines and has the potential to be used as an antiproliferative agent [110]. PRP-1 can reestablish the expression of suppressor of cytokine signaling 3 (SOCS3) and ten-eleven-translocation methylcytosine dioxygenase 1 and 2 (TET1/2) [111,112]. SOCS3 is considered to be responsible for suppressing pro-inflammatory factors [113]. The inactivation of SOCS3 and TET1/2 was caused by the demethylation of histone H3K9 in the promotor regions of these proteins [114,115]. PRP-1 restored the proper level of methylation in these promotor regions. As a consequence, the population of stem cells from CS decreased. The ability of PRP-1 to restore the normal level of expression of anti-inflammatory cytokines and reduce tumor growth makes it a potential therapeutic agent [116]. The enhancer of zeste homolog 2 (EZH2) is part of the polycomb repressive complex 2 (PRC2), which has HMT activity and is responsible for H3K27 methylation, leading to a decrease in gene transcription [117,118]. The study by Girard et al. [119] showed that the EZH2 protein was expressed in CS, whereas it was not present in enchondromas or chondrocytes, suggesting the role of this protein in the pathogenesis of CS. Furthermore, the level of EZH2 expression correlated with the grade of CS and could potentially be used as a prognostic factor [119]. The study also revealed that EZH2 expression can be reduced by 3-Deazaneplanocin (DZNep), an inhibitor of S-adenosyl homocysteine hydrolase (SAH) inhibitor [119]. Using DZNep in vitro led to a depletion of EZH2 expression and, consequently, loss of methylation of H3K27 [119,120]. In many studies, DZNep demonstrated the ability to inhibit tumor growth, e.g., in breast and hepatocellular cancer in vitro [121,122]. In vitro studies revealed that DZNep inhibited tumor growth and migration and promoted apoptosis in CS cells with the down-regulated activity of EZH2. Interestingly, DZNep slightly reduced the growth of normal chondrocytes [119]. However, its antiproliferative effect may not only be related to the inhibition of EZH2. DZNep is not selective and inhibits methylation globally, so its effect on CS cells is more complicated and requires further examination [119]. The next study conducted by Lhuissier et al. [123] showed that the combination of DZNep and cisplatin was more effective in reducing CS cell growth in comparison to the use of each of these drugs alone. This study presents a potentially new way of treating CS with epigenetic drugs and standard chemotherapy. In CS, the methylation of H3K4, H3K9, and H3K27 appears to be independent of the mutation of the IDH1/2 gene, contrary to what is observed in other tumors such as gliomas [40,42]. In the study by Suijker et al. [42], both the DNA methylation pattern and the methylation of H3K4, H3K9, and H3K27 were not altered after treatment of CS cells with the AGI-5198 [40,42]. However, these histone modifications seem to be relevant only in the formation of enchondromas; therefore, in CSs, it is necessary to search for other processes causing modifications of histones [98,99]. However, other studies indicate that loss of methylation in H3K27 can affect the clinical and histopathological features of CS [124]. This was already described in dedifferentiated CS, which is considered to be related to mutations in the Embryonic Ectoderm Development (EED) and the suppressor of the Zeste 12 Protein Homolog (SUZ12) genes, belonging to PRC2. On the other hand, these genes were not mutated in well-differentiated CS [124]. Therefore, changes in the activity of PRC2 may play a significant role in the dedifferentiation process of CS. The histological characteristics presented by dedifferentiated CS with histone modification resemble the malignant peripheral nerve sheath tumor (MPNST) with spindle cells [125]. These two tumors can be distinguished by analysis of the Neurofibromatosis type 1 (NF1) mutation, which typically occurs in nerve sheath tumors, and by the presence of IDH2, COL2A1, SUZ12 or EED mutations, related to CS [124]. To summarize, the analysis of histone modifications could be useful for the diagnosis of CS and the introduction of specific drugs; however, further studies are needed to explain the precise mechanism of these changes. A summary of histone modifications and potential therapeutic drug candidates already found in CS is presented in Figure 1. Small ubiquitin-like modifier (SUMO) proteins constitute a group of proteins which participate in post-translational modifications of molecules [126]. The study conducted by Kroonen et al. [127] revealed that expression of SUMO in CS is elevated. Moreover, increased expression of SUMO 1 and SUMO 2/3 corresponded with higher histological grade and a higher level of SUMO 2/3 resulted in worse overall survival. Therefore SUMO 2/3 has the potential to become a prognostic marker. In vitro studies performed in the same research showed that inhibition of SUMO E1 reduced CS cell proliferation and viability. Dedifferentiated CS cell lines, which are known for aggressiveness, were exceptionally susceptible to inhibition of SUMO E1. To summarize, introduction of drugs targeting SUMO may lead to more effective treatment of CS [127]. Epigenetic modifications, based on promising preclinical data, should be the area of extended research and development in CS. Most potential drugs are currently being evaluated for safety and dosage in phase 1 clinical trials in solid tumors and hematological malignancies. Some limited studies are specifically enrolling patients with CS, but most of the studies enrolled only participants with solid tumors to assess doses, safety and preliminary efficacy signals. Examples of studies conducted in CS as well as in the general population of solid tumors have been summarized in Table 2. Studies concerning IDH inhibitors have also included patients with CS. Currently, there are three ongoing clinical trials which use drugs targeting the mutant IDH1. The drugs that are being tested are LY3410738 (NCT04521686) and Ivosidenib (AG-120) (NCT04278781, NCT02073994). As mentioned above, IDH1 mutations are common in CS and these substances have the potential to inhibit CS growth. The results of the research using AG-120, administered orally in advanced CSs, showed that the level of plasma D2HG decreased in all patients, and in half of the patients (52%, 11 out of 21), most tumors stopped growing [128]. Currently, another phase II trial study (NCT04340843) has been started on patients with unresectable and metastatic CSs treated with the HDAC inhibitor belinostat in combination with hypomethylating agents (SGI-110 (guadecitabine) or ASTX727 (cedazuridine)). However, this has been suspended due to the pending completion of the safety lead-in [129]. Besides IDH inhibitors, other drugs have been tested, such as LSD1 and BET inhibitors (NCT03895684, NCT02419417). Dose and safety studies with these two drugs on solid tumors have been completed. Preliminary efficacy data of a phase 1/2a, open-label study with BMS-986158 monotherapy (NCT02419417) revealed stable disease (SD) in 26.1% to 37.5% of patients, depending on dosing schedules. BMS-986158 was well tolerated in patients with schedule A dosing (5 days on, 2 days off) and its antitumor activity was noted by 30.4% of these patients [130]. Currently, one more phase 1b/2 study, including patients with advanced or metastatic solid tumors treated with TAK-981 (SUMO inhibitor) in combination with pembrolizumab, is ongoing (NCT04381650). During the last decade, our knowledge about epigenetic alterations and their influence on the pathogenesis of cancers has changed significantly. Due to the poor effectiveness of chemotherapy and radiotherapy in the treatment of CS, there is a constant need for the development of new therapies. In the future, epigenetic changes may be used as a potential prognostic and predictive factor as well as a therapeutic target in CS treatment. It is known that modification of DNA and histones, such as methylation or acetylation, as well as miRNAs, can play an important role in the pathogenesis of CS. Examining these modifications gives us valuable insight into the pathogenesis of tumors. However, this is particularly challenging, since the exact mechanisms of the processes involved in epigenetic alterations are still not fully understood. MicroRNAs and SUMO have the potential to be used as prognostic factors. Abnormalities in the expression of these molecules can indicate sensitivity to chemotherapy in CS as well as be an indicator of prognosis and overall survival. Analysis of the methylation level of genes related to the pathogenesis of CS could be used to diagnose and assess its histological and clinical characteristics. So far, none of the drugs that influence epigenetic changes have been widely accepted in treatment and there are only a few potential candidates to implement. However, epigenetic alterations in CS should be the subject of intensive research in upcoming years.

PMC10003548

Anna P. Loboda,Leonid S. Adonin,Svetlana D. Zvereva,Dmitri Y. Guschin,Tatyana V. Korneenko,Alexandra V. Telegina,Olga K. Kondratieva,Sofia E. Frolova,Nikolay B. Pestov,Nick A. Barlev

BRCA Mutations—The Achilles Heel of Breast, Ovarian and Other Epithelial Cancers

05-03-2023

breast cancer,ovarian cancer,PARP inhibitors,Alu repeats,protein-protein interactions

Two related tumor suppressor genes, BRCA1 and BRCA2, attract a lot of attention from both fundamental and clinical points of view. Oncogenic hereditary mutations in these genes are firmly linked to the early onset of breast and ovarian cancers. However, the molecular mechanisms that drive extensive mutagenesis in these genes are not known. In this review, we hypothesize that one of the potential mechanisms behind this phenomenon can be mediated by Alu mobile genomic elements. Linking mutations in the BRCA1 and BRCA2 genes to the general mechanisms of genome stability and DNA repair is critical to ensure the rationalized choice of anti-cancer therapy. Accordingly, we review the literature available on the mechanisms of DNA damage repair where these proteins are involved, and how the inactivating mutations in these genes (BRCAness) can be exploited in anti-cancer therapy. We also discuss a hypothesis explaining why breast and ovarian epithelial tissues are preferentially susceptible to mutations in BRCA genes. Finally, we discuss prospective novel therapeutic approaches for treating BRCAness cancers.

BRCA Mutations—The Achilles Heel of Breast, Ovarian and Other Epithelial Cancers Two related tumor suppressor genes, BRCA1 and BRCA2, attract a lot of attention from both fundamental and clinical points of view. Oncogenic hereditary mutations in these genes are firmly linked to the early onset of breast and ovarian cancers. However, the molecular mechanisms that drive extensive mutagenesis in these genes are not known. In this review, we hypothesize that one of the potential mechanisms behind this phenomenon can be mediated by Alu mobile genomic elements. Linking mutations in the BRCA1 and BRCA2 genes to the general mechanisms of genome stability and DNA repair is critical to ensure the rationalized choice of anti-cancer therapy. Accordingly, we review the literature available on the mechanisms of DNA damage repair where these proteins are involved, and how the inactivating mutations in these genes (BRCAness) can be exploited in anti-cancer therapy. We also discuss a hypothesis explaining why breast and ovarian epithelial tissues are preferentially susceptible to mutations in BRCA genes. Finally, we discuss prospective novel therapeutic approaches for treating BRCAness cancers. The first case of hereditary cancer was described in 1866 by Pierre Paul Broca, when he documented the development of breast and ovarian cancers within his wife’s family. It took almost 130 years to decipher the genetic mechanism behind this hereditary cancer syndrome. This was completed by Mary Claire-King and her colleagues, who published a linkage analysis of families with an early onset of breast cancer (BC) and identified the gene locus of BRCA1 (BReast CAncer 1) at 17q21 [1]. The gene responsible for this phenotype was cloned in 1994. Shortly thereafter, the BRCA2 gene was linked to chromosome 13, and cloned [2]. The products of these genes are functionally classified as tumor suppressors, meaning that inactivation of both copies of either gene is strongly associated with carcinogenesis. BRCA1 and BRCA2 proteins lack obvious structural homology, whereas a segment of BRCA1 is homologous to its partner, the BARD1 protein. In contrast to the canonical tumor suppressor inactivation mechanism, whereby one allele of a tumor suppressor gene is mutated and the other is either deleted or epigenetically inactivated (“loss of heterozygosity” principle, LOH), the BRCA-mutated cancerous cells frequently bear the remaining alleles in the wild-type state [3]. In this case, mutations in the BRCA1 or BRCA2 genes are often preceded by mutations in other critical tumor suppressor genes, PTEN and/or TP53 [4]. Reversion of germline BRCA mutations in growing cancers is also common [5]. This indicates that haploinsufficiency may be the major basis for early development of BC in BRCA1/2 pathogenic mutation carriers. Importantly, since the products of these genes are involved in the DNA damage response, the BRCA mutation status has profound significance for the selection of appropriate therapeutic interventions. Despite their close functional connection, BRCA1 and BRCA2 have somewhat different effects on cancer development and progression. For example, BRCA1 and BRCA2 each correlate with different subtypes of BC. BRCA1 mutations are linked preferentially to the triple negative form of BC (estrogen receptor negative, progesterone receptor negative, and HER2 negative, TNBC), whereas BRCA2-associated breast cancers are generally estrogen receptor-positive [6], and phenotypically different (mostly luminal-like BC) [7]. Furthermore, mutations in BRCA2 are more often associated with other types of epithelial cancer, including male BC, pancreatic cancer, and prostate cancer, than BRCA1 mutations [8]. The expectancy for OC to occur in either of these genes in various tumors is also different. For example, for BRCA1 mutations, the risk of OC is 40 to 45%, compared to 10–20% for BRCA2, as well as an earlier onset of OC for BRCA1 cases [9]. Mutations in the BRCA1 gene are mostly associated with hereditary cancers and are rarely found in sporadic cancers (compare more than 300 germline mutations for familial BC and/or OC, with only a few somatic ones in sporadic BC [10]). However, these rare cases are quite interesting, since they may result either from functional inactivation of BRCA1 due to low gene expression, or from incorrect subcellular localization of the encoded protein [11]. Since BRCA1 is a tumor suppressor, and is directly involved in the double-strand break (DSB) repair process, it is not surprising that the mutation status of this gene serves as a prediction marker for a high risk of carcinogenesis. Carriers of germline mutations in the BRCA1 gene are prone to developing mostly BC and/or OC [12]. Although BRCA mutations are also found in many other types of tumors, they apparently do not have any detectable effect on cancer incidence in the brain, colon, bladder, kidneys, cervix, or lungs, nor an increased risk of melanoma [13,14]. However, BRCA mutation status often correlates with the severity of the disease and a shorter overall survival [15]. In total, 90% of ovarian cancers (OCs) are identified as epithelial OC (EOC), which is further subdivided according to histological characteristics into: low-grade serous; clear cell; endometrioid and mucinous [16]; and the most common, high-grade serous (HGSOC). The latter accounts for about 70% of all cases of EOC [17]. Importantly, approximately 15–20% of patients with HGSOC have germline mutations in BRCA1 or BRCA2 [18,19]. The presence of such BRCA mutations has also been reported in other histological subtypes of EOC [19,20]. Hereditary ovarian cancers are characteristic of three autosomal dominant familial syndromes: BC and/or OC, site-specific OC, and Lynch (hereditary non-polyposis colorectal cancer) syndrome [21]. Meanwhile, a familial history of OC, especially when associated with BRCA1 mutations, poses a significant lifetime risk of developing the disease. Thus, 39–44% of women who inherit a BRCA1 oncogenic-driving mutation develop OC by age 70–80 [22], and diagnosis at a later stage significantly worsens prognosis [23]. However, there is evidence that mutations in the BRCA1 gene are associated with an increase in progression-free survival (PFS) [18,24,25,26]. This may be due to an increased sensitivity of such patients to treatment with platinum-containing drugs [12] or poly(ADP-ribose) polymerase (PARP) inhibitors. Oncogenic mutations in BRCA1 can be germline or somatic. According to the results of several independent studies, somatic mutations make up a significant part of all observed mutations in this gene among patients with OC [27,28,29,30]. Overall, somatic BRCA mutations occur in approximately 5–7% of OC cases [31]. The existence of somatic mutations fits into the concept of “BRCAness”, in which germline mutations of BRCA1 or BRCA2 are not detected, but the DNA repair defect occurs due to problems in the process of homologous recombination [32]. Studies have not revealed a significant difference in the course and aggressiveness of OC in patients with somatic or germline BRCA1 mutations. Similarly to patients with congenital BRCA1 mutations, patients with somatic BRCA1 mutations showed an increased sensitivity to platinum-containing drugs and olaparib, a PARP inhibitor [29,33]. BC is one of the most common types of cancer diagnosed in women. This disease can also occur in men, although much less frequently. Molecular subtypes of BC include luminal A, luminal B, HER2-positive, triple negative, claudin-low, and normal-like, with other molecular markers important for classification being ERα+, PR, EGFR, CK5/6, VEGF, KI67, TNBC, MES, IM, and LAR [34]. Tumors associated with a BRCA1 mutation are more likely to be triple-negative BC (TNBC), which is more aggressive and difficult to treat than other types [7,35]. BC caused by a mutation in the BRCA1 gene has a higher rate of mitosis and greater lymphatic permeability than sporadic BC, as well as a higher frequency of somatic mutations in the p53 gene [34]. Women who inherit pathogenic BRCA1 mutations face a very high lifetime risk of developing BC: 60% to 80% by the age of 80 years [34,36]. Two-thirds of the BRCA1 mutations found in BC are germline, and the remaining third relates to somatic mutations [37,38,39]. Germline and somatic BRCA1 mutations are currently assumed to be biologically equivalent [40]. There is evidence that tumors carrying BRCA1 germline mutations have biological signatures similar to tumors with somatic BRCA1 mutations [41,42]. However, there is also data showing that somatic mutations of the BRCA1 gene have not been identified in BC without concurrent germline mutations [43], which may explain the small difference between tumors with somatic and germline BRCA1 mutations. Pancreatic cancer is reported to be the third most common cancer associated with BRCA mutations [44]. A family history of pancreatic cancer is found in 5–10% of patients with pancreatic cancer. Pancreatic ductal adenocarcinoma (PDAC) occurs especially frequently in families with OC or BC [45]. Pathogenic mutations in BRCA2 occur in 2% of patients with pancreatic cancer, and mutations in BRCA1 in 1% of patients. Approximately 7% of patients with pancreatic cancer may carry germline mutations in BRCA1/2. In patients with hereditary pancreatic cancer, the prevalence of BRCA1/2 mutation carriers is estimated at 4.9–26%. Mutations in BRCA2 appear to be more common in pancreatic cancer. Furthermore, these mutations are considered to be more dangerous and increase the risk of developing pancreatic cancer severalfold [46]. Mutations in the BRCA1 and BRCA2 genes increase the risk of developing prostate cancer. Some results indicate significantly lower survival rates and a more aggressive course of the disease [47,48]. Male carriers of a BRCA2 gene mutation have a significantly increased risk of developing prostate cancer [49]. Pathogenic mutations in BRCA1/2 have been found throughout the coding region of this gene and at splicing sites (Figure 1). Most mutations in both genes are small insertions or deletions resulting in frameshifts, nonsense mutations, or splice-site changes that cause the stop codon to occur prematurely [21]. Therefore, it is quite difficult to isolate the regions that are most susceptible to the deleterious mutations common among various types of cancer. In respect to BC, there are studies highlighting exon 10 (usually termed exon 11 for historical reasons) of BRCA1 as the most mutated in BC patients [34,50]. According to The Breast Cancer Information Core (BIC), a catalog of BRCA1 and BRCA2 mutations identified worldwide, the most commonly identified BRCA1 mutations are 185delAG (16.5%), 5382insC (8.8%), and the C61G missense mutation (1.8%). However, exon 10 is longer than all other exons combined, thus physically providing more opportunities for mutations to occur. Additionally of note, there is a remarkable variation in the distribution of BRCA1 mutations around the world; for example, some BRCA1 variants are limited to geographically isolated regions or specific populations. This phenomenon is described as the “founder effect”. It has a profound influence on fundamental studies, diagnoses, and treatment approaches of BRCA1-associated cancers [51]. In some countries and ethnic communities, the spectrum of BRCA1 mutations is strictly limited to a few founder mutations. For example, the founder effect in the population of Ashkenazi Jews is well described: three mutations in the BRCA1 gene (BRCA1 c.68_69delAG, c.5266dupC and BRCA2 c.5946delT) account for 98–99% of the identified mutations, and are found in approximately 2.6% of the Ashkenazi Jewish population [52]. In Russia, the most common BRCA1 mutation is c.5266dupC, accounting for about 90% of all BRCA1 mutations. Other less common mutations found in Western Russia are c.4035delA, c.181T > G and c.68_69delAG [53,54,55]. Evolutionarily, both BRCA1 and BRCA2 are ancient genes that are indispensable for high-fidelity DSB DNA repair in most of Eukaryota. However, it should be mentioned that BRCA1 seems to be absent from all fungi, and BRCA2 was not found in yeast. However, the carboxyl-terminal BRCT domain (Figure 1) homologs were identified in several yeast proteins (e.g., Rad4 and Rad9), indicating that the function of BRCA1 and BRCA2 can be distributed between several yeast proteins involved in the process of DNA repair [56,57]. Since the harmful effects of mutations in the BRCA genes are developed only later in life, these mutations are likely to be passed on to future generations. Because these mutations do not affect reproductive fitness, the purging force of natural selection will be weak and insufficient for consistently eliminating these mutations [58]. Therefore, mutations in BRCA1 and BRCA2, especially because they are inherited in a dominant manner, may be considered as good illustrations of the mutation accumulation theory. In this situation, the dominant nature of BRCA1/2 mutations may decrease the fertility of female carriers through an accelerated depletion of ovarian reserve, as described in several independent reports (for example, [59,60]). Although the onset of menopause is largely unaffected [60], and hence the magnitude of this effect may be overestimated [61], it is worth mentioning that even a small decrease in age-associated fertility may have drastic consequences on the evolutionary scale. It is assumed that BRCA1 or BRCA2 mutations promote carcinogenesis predominantly in breast and ovarian epithelia because, since menstrual cycles periodically create a hormone-dependent enrichment in the female hormone-responsive tissues of reactive oxygen species (ROS), there would be a demand for an augmented expression of the genes responsible for antioxidant defense and DNA repair machinery against genotoxic metabolites including, for example, endogenous quinones derived from 2- and 4-hydroxyestradiols [62]. This may be a plausible explanation for the fact that mostly female hormone-responsive tissues are exquisitely sensitive to germline mutations in the BRCA1 and BRCA2 genes [63]. It should be noted, however, that this highly tempting hypothesis of tissue-specific carcinogenesis cannot account for the increase in pancreatic and prostate cancer incidences (albeit to much lower levels compared to breast and ovarian tissues). Indeed, the problem of tissue-specificity of oncogenic effects exerted by ubiquitously expressed genes is rather multifactorial and requires additional studies [64]. Here, we attempt to highlight the importance of the intrinsic genetic mechanisms that control genomic instability in humans, specifically Alu repeat elements. They occupy almost 11% of the human genome and exert wide-ranging influences on gene expression. Alu elements are ~300 base pair retrotransposon sequences that are normally silenced by DNA methylation and heterochromatin formation. However, in the germline, Alu elements are more active and may significantly contribute to genetic diseases and population diversity. In particular, we argue that Alu repeats may significantly contribute to the mutagenesis of BRCA1/2 genes through several mechanisms: direct insertional mutagenesis and/or as an abundant source of repetitive sequences that, in turn, contribute to non-allelic homologous recombination, which would result in genetic deletions and duplications [65]. Over the last 20 years, research has expanded to improve the understanding of BRCA-related BC and OC, specifically in how they respond to treatment, as well as the expected clinical course. Better characterization of alterations in these genes may enable the development of new, targeted therapies, or broaden the clinical application of current therapies [12]. BRCA1/BRCA2 genes harbor a very high density of repetitive DNA elements that contribute to genetic instability [66]; the BRCA1 gene contains 138 individual Alu elements [67], which occupy about 42% of intronic sequences (Figure 2). In addition, this gene includes 5% of various other repeats [68,69]. BRCA2 contains almost 47% repetitive DNA elements, but only 17–20% of them are Alu repeats. These genes show a high probability of mutations that are associated primarily with Alu-mediated genomic rearrangements [70,71]. These rearrangements are more frequent in BRCA1 than in BRCA2, probably due to the large number of Alu repeats in the gene sequence [72,73,74]. Although most genomic rearrangements were proven experimentally to be pathogenic by causing frameshifts and premature termination codons, some rearrangements have more ambiguous effects. In particular, this concerns in-frame deletions of redundant exons [75] or, conversely, some duplications, where additional copies of exons might be well tolerated by the organism without deleterious effects [76]. Almost 10% of BC cases are related to defects in the BRCA1 or BRCA2 genes [77]. Women with a familial history of confirmed BRCA1 or BRCA2 defects have been shown to possess a remarkably high lifetime risk of developing BC (80% and 60%, respectively) [78,79]. It was also shown that large rearrangements in BRCA1, but not BRCA2, play a notable role in the predisposition to breast and ovarian cancers in high-risk families of German origin [80]. Researchers analyzed 226 patients with a high-risk of hereditary BC and OC and described six large genomic alterations in the BRCA1 locus. BRCA1 mutations include a deletion of exon 5, a deletion comprising exons 5–7, a deletion of exons 1A, 1B, and 2, two duplications of exon 13, and a deletion of exon 17. However, nothing similar was found in the BRCA2 gene. In another study, two families with a high risk of hereditary BC and OC were found to carry a 7.1 kb germline deletion, which includes exons 8 and 9. This deletion leads to a frameshift at the mRNA level [81]. Only a few other studies have investigated BRCA2 rearrangements [82]. To date, about 16 cases of BRCA2 germline rearrangements have been reported. It was shown that large genomic BRCA2 rearrangements are observed in males in affected hereditary BC families, predominantly [83]. Genomic rearrangements of the BRCA2 gene were present in 25 families, among which there was at least one man with BC. However, no BRCA2 gene rearrangements were found in 114 families among women with BC [84]. These results raise the question of the possible existence of sex-related mechanisms of the gene rearrangements in the BRCA2 gene. The Alu-indirect insertion in exon 3 of BRCA2-c.156_157insAlu- is quite common in families with an inherited predisposition to BC and/or OC. Researchers found this mutation in 14 families (out of 208 tested) and it accounts for about a quarter of all mutations in the BRCA1/2 loci [85]. Thus, Alu-mediated rearrangements in the BRCA1 and BRCA2 genes, including deletions and insertions that lead to global genomic rearrangements of these genes, are closely associated with the predisposition to BC and OC. The BRCA1 protein is involved in vital processes in the nucleus, namely transcription, DNA repair (including the repair of transcription-related DNA damage), and cell cycle control. Accordingly, BRCA1 is localized to discrete sub-nuclear structures associated with DNA replication or repair. DNA damage induces BRCA1 phosphorylation and recruitment to specific foci containing DNA repair proteins, where BRCA1 is deemed to act as a scaffold for the assembly of various multiprotein complexes. Despite the large molecular weight of BRCA1 (1863 amino acid residues [86]), only two conserved domains can be distinguished in its structure: the N-terminal RING domain (exons 2–6) [87] that encompasses 100 amino acid residues; and two tandem C-terminal BRCT domains, with 90 amino acid residues each [88], encoded by the end of exon 16, and exons 21–24, respectively (Figure 3). The region of the protein located between these two terminal domains is structurally variable between mammalian BRCA1 homologues. It is believed to be intrinsically disordered, yet it is critical for the proper functioning of BRCA1, along with the other two conserved domains (Figure 3). The DNA-binding RING (Really Interesting New Gene) domain has an E3 ubiquitin ligase activity, being a scaffold for the interaction with the corresponding E2 ubiquitin ligases such as UbcH5, UbcH6, UbcH7, Ube2e2, UbcM2, Ube2w, and Ubc13 (Figure 4) [89]). The ubiquitin ligase activity of BRCA1 is stimulated by the formation of a heterodimer with the BARD1 protein [90]. The latter also contains a RING domain and tandem BRCT domains, and shares some structural similarity to BRCA1 [91]. Like BRCA1, BARD1 tends to form specific foci in the nucleus in S-phase of the cell cycle that overlap with the ones formed by BRCA1, suggesting that the formation of the BRCA1/BARD1 complex is cell-cycle-dependent [92]. The formation of a complex with BARD1 is necessary for the stabilization of BRCA1 at the protein level. Furthermore, this interaction is apparently important for the nuclear localization of BRCA1. The BRCA1/BARD1 heterodimers are involved in the DNA repair of double-strand breaks, and hence the preservation of DNA integrity, including the process of resolving impaired replication forks (for more details, see [89]). Mechanistically, the BRCA1/BARD1 complex is recruited by the RAP80 protein to sites of DNA damage [93], where the BRCA1/BARD1 ubiquitin ligase is employed to modulate the activity of DNA damage response factors (Figure 5). Additionally, the proteolytic activity of 26S proteasomes is also modulated by DNA damage stimuli, thereby adding another level of complexity to the regulatory mechanisms of DNA repair [94]. Importantly, the BRCA1/BARD1 heterodimers also interact with the RNA polymerase II holoenzyme. However, BRCA1 does not show an increased affinity for specific DNA sequences, except for some abnormal structures (branched DNA formations) [95]. This does not allow BRCA1 to be considered a bona fide transcription factor. Considering the fact that in the central unstructured and C-terminal regions of BRCA1, there are many binding sites for various transcription factors, chromatin remodeling factors, and DNA-damage response factors, it would be fair to say that BRCA1, in complex with BARD1, forms a scaffold for the surveillance of genome integrity control during transcription [96]. However, there are also cases when BRCA1 acts as a corepressor; for example, the transcription factor ZBRK1 suppresses the transcription of its target genes in a BRCA1/CtIP-dependent manner [97]. ZBRK1 acts as a metastatic suppressor by directly regulating MMP9 in cervical cancer. The C-terminal region of BRCA1 (1650–1863) is occupied by two BRCT (BRCA1-C-Terminal) tandem-repeat domains connected by a 22-amino-acid linker [98]. The BRCT domains are protein-binding modules that recognize the phosphorylated motif pSer-x-x-Phe [99]. Due to this, BRCA1 is included in the signaling cascades triggered by DNA damage as a scaffolding platform for the interactions of various kinases and other proteins involved in the regulation of the cell cycle [100]. Additionally, BRCA1 itself undergoes reversible phosphorylation upon DNA damage [101] by key regulators of the DNA damage response: PIKK kinases (ATM, ATR, and DNA-PK) [102] and checkpoint effector kinases (Chk1, Chk2 and MK2) [103]. Phosphorylation of BRCA1 also creates new sites for complex protein–protein interactions affecting various aspects of DNA damage and repair (Figure 5). The BRCA1/BARD1 complex senses the ubiquitination status of histone H2A and works as a ubiquitin ligase of this histone. These activities play important roles in the choice between HR or NHEJ during DNA damage repair: BRCA1 acts as a mediator for HR, antagonizing the 53BP1-mediated NHEJ pathway [104,105,106] (Figure 6A). BRCA2, complexed with SEM1/DSS1 and ssDNA [107] (Figure 6B), functionally interacts with recombinase RAD51, PALB2, ssDNA-specific endonuclease XPG/ERCC5, and BRCA1 [108]. TP53 (p53) is arguably one of the most significant tumor suppressor genes in humans. It is frequently mutated and several point mutations in its DNA-binding domain convert the p53 protein into an oncogene. That TP53 mutations occur in tumors bearing BRCA1 mutations suggests that the two genes may function in different signaling pathways to suppress tumorigenesis [109]. However, results from experiments in mice have shown that tumorigenesis occurs much more efficiently when both BRCA1 and TP53 are deleted, compared to BRCA1 deletion alone [110], indicating that p53 is located downstream of BRCA1 in the same signaling pathway. Accordingly, mutations in BRCA1 preceding mutations in the TP53 gene, as seen in cases of familial BC, are not sufficient for tumor progression. Since BRCA1-null cells display genomic instability, it is likely that persistent intrinsic DNA damage in the presence of wild-type p53 leads to the extermination of such cells via p53-dependent cell cycle arrest and apoptosis. There is another important fact that functionally links p53 and BRCA1: in response to various types of DNA damage, both p53 and BRCA1 become phosphorylated by DDR-dependent kinases, ATM and Chek1. Upon DNA damage, BRCA1 also interacts with another kinase, c-Abl [111]. The C-terminus of BRCA1 is phosphorylated by c-Abl in vitro. In vivo, BRCA1 is phosphorylated at tyrosine residues depending on ATM and irradiation. However, the tyrosine phosphorylation of BRCA1 does not disrupt the interaction between BRCA1 and c-Abl. Notably, cells with BRCA1 mutations exhibit constitutively high c-Abl kinase activity, which does not increase when cells are exposed to gamma radiation. Probably, BRCA1 mutations, due to defects in DNA repair, induce the kinase activity of c-Abl towards p53, which culminates in p53-dependent cell cycle arrest and cell death. In addition to phosphorylation and the subsequent activation of p53 transcriptional activity, c-Abl also stabilizes p53 on the protein level by inactivating its major inhibitor, E3 ligase Mdm2 [112]. Curiously, c-Abl also phosphorylates another tyrosine kinase, BTK [113]. In this respect, we have recently shown that BTK can phosphorylate p53, leading to its stabilization and transcriptional activation [114], suggesting a novel role for BTK as a potential tumor suppressor [115]. It is also known that BRCA1 and p53 are able to interact physically. Deletion analysis in the BRCA1 gene allowed for the identification of p53-interacting domains in the coiled–coiled region and in the second BRCT domain. On the other end, p53 interacts with BRCA1 at the C-terminus. BRCA1-mediated stabilization of the wild-type p53 protein occurs through upregulation of the p14ARF gene product, which in turn upregulates mouse p53 phosphorylation at serine 18 (equivalent to human serine 15). Exon 10 (historically exon 11) of BRCA1 appears to be responsible for this, since cells with deletions of exon 10 in BRCA1 are defective in p53 stabilization after DNA damage [116]. Functionally, this interaction converts BRCA1 into a p53 coactivator [117]. Perhaps not surprisingly, both proteins, p53 and BRCA1, transcriptionally regulate the expression of the GADD45 gene, which induces growth arrest and DNA damage repair. Both BRCA1-deficient and GADD45-deficient cells displayed a G2/M cell cycle checkpoint defect and increased genome instability [118]. Collectively, these results suggest that the phenotypic manifestation of BRCA1 tumorigenic mutations heavily relies on the spectrum of inactivation in other critical tumor suppressors, e.g., p53. Both BRCA1 and BRCA2 are ubiquitously expressed in human tissues and serve as important parts of the complex machinery that guards DNA integrity. Especially as demonstrated by gene knockout mice (reviewed in [119]), the complete absence of these genes is incompatible with normal development. However, many questions remain to be answered, such as the mutational rates in the germline on the evolutionary scale in different populations and species, especially with respect to the relatively fast evolution of BRCA1 and BRCA2 themselves, and especially in their unusually long central exons. One may wonder why the tumorigenic role of BRCA1/2 mutations is exemplified preferentially in BC cells, and not so much in other epithelial tissues. In this respect, it should be noted that mutated BC cells are largely derived from luminal progenitor cells. Although germline BRCA1/2 mutations occur stochastically in many tissues [120], the breast tissues of patients with oncogenic germline BRCA1/2 mutations have distinct histological features [121]. Premalignant lesions in this tissue also have certain molecular hallmarks, such as upregulated expression of progesterone receptor A [122]. The survival of early malignant cells in the surrounding normal tissue is dependent on many factors, including escape from immune surveillance by natural killers. Indeed, it is physiological for the breast ductal epithelium to invade into adipose tissue and partially displace it during lactation [123]. Thus, breast adipocytes may sense the invasion of micro-metastatic or circulating breast tumor cells as a normal process, which would prevent inflammatory signaling in these niches. In general, the role of adipocytes in cancer progression was highlighted in several excellent reviews [124,125,126,127,128]. It was suggested that adipocytes enhance cancer growth through the secretion of exosomes that contain tumor-promoting factors, e.g., TSP5 [129]. In this respect, BC-associated adipocytes may stimulate the onset of epithelial-mesenchymal transition (EMT) in BC cells by expressing exosomal TSP5 [124,130]. Mechanistically, breast adipocytes protect early breast tumor cells from ferroptosis and other ROS-mediated forms of cell death through the secretion of fatty acids [131], and the cross-talk between adipocytes and malignant cells may occur via secretion of leukemia inhibitory factor (LIF) and C-X-C subfamily chemokines in a positive feedback mode [132]. Also, these cancer-associated adipocytes undergo “browning”: the process of increasing the number of mitochondria [133]. This occurs concomitantly with inflammation-like signaling [134], and the stimulation of vascularization [135]. Collectively, breast adipocytes may create a unique natural tumor niche for BC cells with germline mutations in BRCA1/2 genes. Furthermore, BC cells readily invade multiple tissues, such as the lungs, liver, bones, etc. Again, adipocytes may play an important role in allowing invading cells to colonize and proliferate [136]. However aggressive the BRCA mutant cancers may be, these mutations also give fast-growing cells certain features that may result in paradoxically better sensitivity to some cytostatic and targeted therapies. Indeed, patients with TNBC now have better prognoses if they bear the pathogenic BRCA mutations [6]. Both platinum-containing drugs and PARP inhibitors (PARPi) are used to treat homologous recombination-deficient (HRD) cancers that have mutations in genes involved in double-strand DNA repair [137]. Platinum salts create DNA interstrand crosslinks that are extremely difficult to cleave in the absence of homologous recombination (HR), which leads to the death of HRD cancer cells [138]. Enhanced sensitivity of BRCA1/2-mutated cancers to platinum salts has been well documented in numerous studies, for instance, those on OC [139], pancreatic cancer [140], and BC [141]. If the normal copy of BRCA1 or BRCA2 is retained, the efficacy of platinum-based therapies is decreased [142]. Additionally, platinum resistance may develop upon reverse mutations in BRCA1 [143]. The exact mechanism of action for PARP inhibitors (Figure 7) has not yet been fully understood. Initially, they were developed as dissipaters of DNA repair and potent sensitizers of cancer cells to chemotherapy, but they also showed a significant independent effect on patients with mutations in the HR genes, primarily BRCA1. The effect of synthetic lethality for PARP inhibitors was shown in cells with the loss-of-function mutations in BRCA1 [144]. There are several hypotheses about the mechanism of their combined action [137]. The main model posits that inhibitors bind to the PARP catalytic site, preventing its autoPARylation and further dissociation from the DNA. The latter ultimately leads to the collapse of the replication fork and DNA double-strand breaks that cannot be repaired by HR in cancer cells [145]. The increased sensitivity to these drugs in tumor cells with either somatic or germline BRCA1 mutations suggests that the mechanism of HRD does not depend on whether the BRCA1 mutation was inherited, or arose during the life of the patient. Significant disturbances in the mechanism of DSB DNA repair in the absence of fully functional BRCA1 or BRCA2 make cancer cells particularly sensitive to PARP inhibitors, especially in the case of LOH. In this case, the same molecular features that make these cancers more aggressive also give them vulnerabilities that may be therapeutically exploited. There have been reports on the rather encouraging success of PARP inhibitors, even against relapsed BRCA-mutated cancers [146]. However, in the treatment of certain types of tumors, such as BRCA1/2-mutated and HER2-positive BC, the efficacy of talazoparib, a potent PARP1/2 inhibitor, did not surpass conventional chemotherapy [147]. This indicates that further personalization of anti-cancer therapy may improve the effectiveness of PARP inhibitors, as well as reduce their unwarranted use. Currently, there is a number of ongoing clinical trials with patients recruited based on their BRCA1/2 status (Table 1 has been excerpted from Supplementary Table S1 to give a snapshot of the modern approaches being utilized to employ co-targeting beyond standard cytostatic regimens). However, future possibilities for specific new therapies are much wider. For example, the ubiquitination activity of BRCA1 may become a prospective target for new synthetic lethality drugs [148]. PARP inhibition may be synergistically accompanied by blocking the RAD52 pathway of HR [149]. PARP inhibitors may be converted to more complex molecules with a double-specificity mechanism of action [150]. The action of olaparib and other PARP inhibitors may sometimes be enhanced by some unexpected supplements, such as antioxidants [151]. Combining the inhibition of PARP with the blocking of ATR by ceralesertib may potentially augment the anti-cancer effect of already-existing PARPi [152]. Further, DNA G-quadruplex binders such as pidnarulex may act in a similar manner, thus increasing the arsenal of drugs for BRCA-mutated cancers [153]. Over the past few decades, the clinical significance of BRCA mutations for the rational choice of anti-cancer therapy has been firmly established. In this respect, the synthetic lethal interaction between PARPi and BRCA mutations gives a remarkably successful example of how a fundamental discovery in molecular medicine can be translated into clinical cancer therapy. However, the next step of the problem is the multifariousness of PARPi resistance mechanisms (recently reviewed in depth by Jackson and Moldavan [154]) that eventually arise in patients with BRCA mutations in response to this therapy. In particular, Alu mobile elements regulate the expression of many genes, including the ones that mediate DNA repair [155]. This observation poses an interesting question of whether Alu repeats can be involved in the DNA damage repair process and serve as a potential mechanism for PARPi resistance in BRCA mutant cells [156]. Furthermore, the recently published data of the clinical trial of RITA suggest that patients treated with a PARPi, niraparib, displayed significantly longer PFS, compared to the placebo cohort, regardless of the presence or absence of intact HR repair [157]. This result indicates that PARPi might kill cancer cells in ways other than by affecting DNA repair, although the most feasible explanation is the inhibited PARylation of HR-participating proteins, including BRCA1 [158,159]. Theoretically, it can be hypothesized that a loss of BRCA by cancer cells should increase their susceptibility to various novel regimens of anti-cancer therapies due to the attenuated DNA repair. For example, therapeutic viral intervention seems to be a plausible therapeutic approach to treating BRCAness cancers, especially in combination with PARPi drugs [160]. However, it should be noted that PARP inhibition may activate genes linked to the normal interferon response in BRCA1,2-deficient cells [161] and this may explain the molecular basis of interference between the treatment with oncolytic viruses and PARPi. Therefore, one should pay attention to the BRCA mutational status when implementing new oncolytic viruses against BC and/or OC. Managing BRCA1 and BRCA2 pathogenic mutations may include many options other than extensive testing and preventive surgery for such patients. The idea of long-term therapeutic interventions, such as hormone replacement, has long been discussed, but poses serious risks of adverse effects [162]. This concept is now re-emerging (discussed in [163]), due to the implementation of drug repurposing (Denosumab, Metformin, Letrozole, etc.; see Supplementary Table S1), as well as principally new approaches, such as adiponectin receptor-targeting molecules [164]. The p53 tumor suppressor plays an important role in inhibiting cancer progression, especially in response to chemotherapy or targeted therapy. Genomic inactivation of TP53 by missense or nonsense mutations often leads to drug resistance in cancer cells. It was previously thought that, since wild-type p53 transcriptionally induces the expression of genes involved in DNA repair [165], then TP53-mutant cells with attenuated DNA repair would be more sensitive to PARP inhibitors which block homologous DNA repair. Accordingly, a deficiency of or mutations in the TP53 gene have been shown to enhance the cytotoxicity of PARP inhibition in various tumors with mutations in BRCA1/2 [166]. However, recent studies in colorectal cancer have shown that, contrary to previous findings, wild-type p53 activity appears to be important for a full cytotoxic response to PARP inhibition [167], as PARP inhibitors have been found to activate the p53 pathway [168]. One of the explanations for this phenomenon may be the fact that it is wild-type, and not mutant, p53 that promotes the export of BRCA1 from the nucleus, increasing the cellular deficiency of homologous repair [169]. Another explanation could be that TP53 encodes a large number of microRNAs that target genes responsible for the repair of double- and single-stranded DNA breaks [170,171], thereby increasing the sensitivity of cancer cells to PARP inhibitors. In this regard, the question arises of whether the combination of PARP and activators of p53 may have a synergistic effect. Since Mdm2 is the principal p53-specific E3 ligase that degrades p53 [172], it will be interesting to see whether inhibitors of the p53–Mdm2 interaction can be combined with PARP inhibitors. A number of new Mdm2 inhibitors are currently undergoing clinical trials [173]. Notably, we and our colleagues have also discovered several new inhibitors of p53 interaction with Mdm2, and these molecules exhibited strong apoptotic effects [174,175,176]. Future experiments will show whether the combination of p53 activators and PARP inhibitors is a viable therapeutic approach to treating BRCAness cancers. Complex combinations, as expected, should be more effective, although more difficult and time-consuming to develop and adjust to practical regimens. For example, a combination of cisplatin, mitomycin C, and doxorubicin was reported to be more efficient than the respective double combinations [177]. Finally, there are multiple ways to boost standard neoadjuvant regimens, such as the addition of bevacizumab to anthracycline and taxane for patients with BRCA1,2 mutations [178]. Further progress in fundamental studies on DNA repair, and the development of even more potent and specific drugs, may wield power over the intrinsic weaknesses of many cancers. Even relatively simple improvements in molecular diagnostics, such as the detection of cases with loss-of-function BRCA1,2 mutations, may yield a highly positive impact on the therapeutic treatments for many oncological patients worldwide.

PMC10003549

Yanfang Zhao,Yujin Gu,Qili Zhang,Hongliang Liu,Yingying Liu

The Potential Roles of Exosomes Carrying APP and Tau Cleavage Products in Alzheimer’s Disease

27-02-2023

Alzheimer’s disease,APP,Aβ,p-Tau,endosomal–lysosomal pathway

Alzheimer’s disease (AD) is the leading cause of dementia throughout the world. It is characterized by major amyloid plaques and neurofibrillary tangles (NFTs), which are composed of amyloid-β (Aβ) peptide and hyperphosphorylated Tau (p-Tau), respectively. Exosomes, which are secreted by cells, are single-membrane lipid bilayer vesicles found in bodily fluids and they have a diameter of 30–150 nm. Recently, they have been considered as critical carriers and biomarkers in AD, as they facilitate communication between cells and tissues by delivering proteins, lipids, and nucleic acids. This review demonstrates that exosomes are natural nanocontainers that carry APP as well as Tau cleavage products secreted by neuronal cells and that their formation is associated with the endosomal–lysosomal pathway. Moreover, these exosomes can transfer AD pathological molecules and participate in the pathophysiological process of AD; therefore, they have potential diagnostic and therapeutic value for AD and might also provide novel insights for screening and prevention of the disease.

The Potential Roles of Exosomes Carrying APP and Tau Cleavage Products in Alzheimer’s Disease Alzheimer’s disease (AD) is the leading cause of dementia throughout the world. It is characterized by major amyloid plaques and neurofibrillary tangles (NFTs), which are composed of amyloid-β (Aβ) peptide and hyperphosphorylated Tau (p-Tau), respectively. Exosomes, which are secreted by cells, are single-membrane lipid bilayer vesicles found in bodily fluids and they have a diameter of 30–150 nm. Recently, they have been considered as critical carriers and biomarkers in AD, as they facilitate communication between cells and tissues by delivering proteins, lipids, and nucleic acids. This review demonstrates that exosomes are natural nanocontainers that carry APP as well as Tau cleavage products secreted by neuronal cells and that their formation is associated with the endosomal–lysosomal pathway. Moreover, these exosomes can transfer AD pathological molecules and participate in the pathophysiological process of AD; therefore, they have potential diagnostic and therapeutic value for AD and might also provide novel insights for screening and prevention of the disease. Alzheimer’s disease (AD) is the most common cause of dementia. It was first defined as ‘presenile dementia’ in 1901 by the German psychiatrist Alois Alzheimer. More than a century later, there are still no treatments that can cure or slow the progression of the disease. Current estimates suggest that 50 million people live with dementia worldwide at present. Globally, one new case of dementia is diagnosed every three seconds. The number of cases is expected to reach approximately 152 million by 2050 as the population ages. Approximately 50–60% of all diagnosed dementia cases are caused by AD. Moreover, the current annual cost of dementia is about USD 1 trillion per year, and this figure is forecasted to double by 2030, generating both a global health concern and a heavy economic burden [1]. AD is considered as a neurodegenerative disorder that is linked to aging, with the main characteristic being irreversible damage to neurons in the cortex, cerebellum, hippocampus, and basal cholinergic nuclei, which leads to the deterioration of memory as well as cognitive, mood, and behavioral functions [2,3]. However, no hypothesis has yet attempted to account for all symptoms and pathogenic mechanisms of AD. The senile plaques composed of amyloid β (Aβ) peptide and neurofibrillary tangles consisting of hyper-phosphorylated Tau (p-Tau) are commonly considered to be two key pathological features of AD [4]. The main component of senile plaques is the Aβ peptide, which is derived from the breakdown of amyloid precursor protein (APP). APP is a highly conserved, single-pass transmembrane protein with large extracellular domains, the expression of which is mainly localized on the cell membrane or in intracellular vesicles [5]. The APP gene is located on chromosome 21 and spans approximately 170 kb containing 18 exons. Alternative splicing of APP transcripts creates different mRNA isoforms ranging from 695 to 770 amino acids, of which the most 3 common isoforms are APP695, APP751, and APP770, all of which contain Aβ regions [6]. Aβ is a 36–43 amino acids peptide that usually originates from the proteolytic processing of APP. Under physiological conditions, the level of Aβ in the brain maintains a balance in its production and clearance [7]. Under pathological conditions, APP is usually processed by the amyloidogenic pathway and releases neurotoxic Aβ fragments [7,8] (Figure 1). APP is first cleaved by the protease β-secretase 1 (beta-site APP-cleaving enzymes, BACE1, a membrane-spanning aspartyl protease with its active site located in lumen) at the β-site, thus releasing the majority of the extracellular portion of the protein at its N-terminus (soluble APPβ, sAPPβ) and a 99 amino acids long C-terminal fragment (C99, also called CTFβ). The CTFβ fragment is sequentially cut by the γ-secretase/presenilin complex at the γ-sites, resulting in formation of Aβ peptides, including those that have lengths of 40 (Aβ1–40 or Aβ40) and 42 (Aβ1–42 or Aβ42) amino acids [7,8]. The Aβ40 and Aβ42 fragment monomers generated from the cleavage of APP assemble to form a quantity of soluble oligomeric products [9]. These oligomeric species further self-organize and accumulate into sheet-like structures, called beta-sheets (β-sheets), then, each strand of β-sheet is assembled in parallel and polymerized with an alternate monomer. This ultimately leads to the formation of structurally distinct forms, including fibrils, protofibers, and polymorphic oligomers, referred to as β-plaques [10]. These become resistant to proteolytic cleavage and cause deterioration in neuronal health, leading to calcium homeostasis disequilibrium, oxidative stress, weakened energy metabolism and glucose regulation, cytokine release, inflammatory responses, and, eventually, neuronal cell death [8]. Moreover, Aβ and soluble Aβ oligomers can also affect normal learning and memory and impair cognition functions [11]. Intracellular neurofibrillary tangles (NFTs), which are mainly composed of hyperphosphorylated Tau, are considered one of the hallmarks of AD. Human Tau is encoded by the MAPT gene, which is located on chromosome 17q21.3 and composed of 16 exons [12,13]. In human CNS, the alternative splicing of exons 2, 3, and 10 yields 6 isoforms of Tau. These six isoforms vary from 352 to 441 amino acid residues and differ from each other according to the presence of 3 (3R) or 4 repeats (4R) situated at the C-terminal region and the 2 (58 amino acids, 2N), 1 (29 amino acids,1N) or no inserts (0N) in the N-terminal region of the Tau protein [14]. The N-terminal insert is known to modulate the interaction of Tau with neuronal membranes, and the repeat areas are responsible for binding microtubules [14]. The alternative splicing exclusion or inclusion of exon 10 generates Tau isoforms with 3R or 4R regions [14]. Normally, 3R-Tau and 4R-Tau are expressed in equivalent amounts in normal adult humans, with 3R-Tau isoforms mainly being generated in the developmental stage and 4R-Tau isoforms being generated in adulthood [13], whereas a changed ratio of 3R/4R-Tau occurs in most of the neurodegenerative Tauopathies [15] (Figure 2). Studies have found that the main role of Tau in promoting microtubule assembly and stability is closely related to its post-translational modification phosphorylation. There are 85 potential phosphorylation sites located on the amino acid chain, and its phosphorylation state is linked to the biological activity of Tau proteins [12]. Under pathological conditions, the balance between phosphorylation and dephosphorylation of Tau is disrupted due to deregulation of the balance between kinases and phosphatases, which could result in the hyperphosphorylation of Tau [16]. The process whereby natively unfolded Tau becomes hyperphosphorylated is considered as a critical event in the progression of AD. The hyperphosphorylated Tau loses its affinity and dissociates from microtubules, becomes insoluble, and has increased expression in the cytoplasm; it is then prone to self-aggregation into PHFs, eventually forming NFTs [17]. The hyperphosphorylated Tau oligomers and NFTs exert various pathological effects, including axonal transport impairment, synapse loss, neuronal cytoskeletons, and mitochondrial dysfunction, as well as memory loss and cognitive lesions [17,18]. Extracellular vesicles (EVs) are natural nanoparticles that are secreted from unhealthy or dying cells in the body. EVs are categorized into three subtypes according to their diameter and biogenesis process, including exosomes (30–150 nm), microvesicles (MVs; 100–1000 nm), and apoptotic bodies (500 nm–2 μm) [19]. Exosomes are single-membrane lipid bilayer vesicles that have the same topology as a cell and are generated from the endosomal pathway either by vesicle budding into endosomes that mature into multivesicular bodies (MVBs) or by direct vesicle budding from the plasma membrane [20]. Exosome biogenesis is controlled by precise biological modulation and is usually initiated by the activation of cell-specific receptors and their downstream signaling pathways [21]. Exosomes are generated when invagination of the plasma membrane with cell-surface proteins and soluble proteins forms an early endosome (EE), which then matures into a late endosome (LE). The inward budding of the LE membrane forms numerous intraluminal vesicles (ILVs) within MVBs (also termed multivesicular endosomes) through the presence of the endosomal-sorting complex necessary for transport (ESCRT) machinery [22]; alternatively, ILVs are sometimes formed through the absence of ESCRT (Figure 3). The main ESCRT apparatus major includes four complexes (ESCRT-0, -I, -II, and -III), the associated AAA ATPase vacuolar protein sorting 34 (Vps34) complex, and Alix. ESCRT-0 is responsible for recognizing the location of ubiquitylated proteins in the endosomal membrane and initiates the pathway. The combination of ESCRT-0, -I, and -II associated with ESCRT-III assemble to form a de-ubiquitination machinery, which packages cargo into maturing vesicles and advances vesicle budding into the luminal surface. This process is activated by phosphatidylinositol 3-phosphate (PIP3), hepatocyte-growth-factor-regulated tyrosine kinase substrate (HRS), the ubiquitination of the cytosolic tails of endocytic proteins, or curved membrane topology, and with the participation of Alix and TSG101 [23]. Subsequently, the transportation of MVB towards the membrane in the cytoskeleton and its fusion with the plasma membrane are mainly executed by Rab GTPases and the sensitive factor attachment protein receptor (SNARE) complex, ultimately releasing intraluminal vesicles such as exosomes [24]. Additionally, MVBs can be transported to the trans-Golgi network for endosomal circulation, finally combining with lysosomes or autophagosomes to be degraded [25]. The evidence suggests that MVB biogenesis can occur in an ESCRT-independent pathway, and the transportation of ILVs to MVBs can be triggered by lipid raft microdomains formed by ceramide and a tetraspanin such as CD63 [23]. After release into the extracellular environment, exosomes can target adjacent tissues and organs or be present in bodily fluids, including blood, cerebrospinal fluid, saliva, semen, urine, and breast milk, in order to transmit biological signals between parental or distant cells [26]. The cellular or organ targeting of exosomes is influenced by many materials, including receptors, transcription factors, enzymes, extracellular matrix proteins, lipids, and nucleic acids (mRNA and noncoding RNAs) inside and on the surface of the exosomes that constitute their content. Analysis of exosome contents reflects that some proteins specifically arise from parental cells and tissue and some are commonly found in exosomes [21]. The lipid bilayer membranes contain proteins such as tetraspanins (e.g., CD9, CD63, CD81, and CD82), which are a family of proteins characterized by the presence of four hydrophobic transmembrane domains, and conserved intracellular loops have been identified as relatively specific exosomal markers [27]. Moreover, TGS101, Alix, flotillin1, integrins, and cell adhesion molecules (CAM) are also considered as exosomal markers [28]. On the other hand, exosomes also contain a range of cytoskeletal proteins, such as actin, myosin, tubulin, fusion and transferring proteins, such as Rab2, Rab7, and annexin, and heat shock proteins, such as HSP70 and HSP90 [29]. Based on their size and protein and lipid content, exosomes can be analyzed using various techniques, including western blotting, flow cytometry, nanoparticle tracking analysis, mass spectrometry, and microscopy techniques [30]. In addition to lipids and proteins, various other genetic compositions, including mRNA, ribosomal RNA, microRNA (miRNA), long non-coding RNA (lncRNA), piwi-interacting RNA (piRNA), transfer RNA (tRNA), circular RNA (circRNA), and small Cajal body-specific RNA (scaRNA), have also been identified as existing in exosomes to execute cell-to-cell communication in different organs and tissues in the body [31]. The genetic materials and proteins in exosomes participate in normal physiological processes and diseases, and they are also regarded as biomarkers of various diseases [32]. The toxic Aβ and hyperphosphorylated Tau can be transmitted between cells and a substantial fraction of exosomes enter into second cells through an internalized dependent pathway [33], subsequently exerting toxic effects on the recipient cells and contributing to neuronal impairment in Alzheimer’s disease (AD). EVs have been proven to be the location for the production and accumulation of APP-derived neurotoxic peptides. Meanwhile, EVs may also be useful for removing the neurotoxic peptides [34]. Exosomes have been presented as transporters for misfolded proteins; for instance, they feed more exogenous Aβ42, resulting in exosomes containing more Aβ42 from cultured cells [35]. Neuronal exosomes serve as transmitters to diffuse amyloidogenic peptides throughout the brain during the pathologic progression of AD. Exosomes extracted from peripheral plasma were injected into the mouse hippocampus and then observed to diffuse to other regions of the hippocampus and the cortex [36]. The increased level of Aβ oligomers in AD patients’ brains can be packaged into exosomes, which are subsequently internalized in cultured neurons and then their toxic content is transmitted to recipient cells. Furthermore, exosomes containing APP can spread to normal neurons in a dose-dependent manner [37], inhibiting the formation, secretion, or uptake of exosomes that could decrease the spread of toxic oligomers [38]. Neuroblastoma cells that express high levels of APP or APP Swedish mutation type (APPswe) were able to secrete exosomes containing APP and APP-derived products (CTFs or Aβ); these types of exosomes can be internalized, leading to the accumulation of pathogenic AD proteins in the receiving neuronal cells [39]. Several studies have considered the underlying mechanism whereby exosomes containing APP and APP-derived products spread to receiving cells (Figure 4) (Table 1). Treatment of exosomes derived from astrocytes with U18666, which can induce cholesterol sequestration, reduced exosomal release but enhanced levels of APP and its cleaved products in exosomes. Moreover, these exosomes could be internalized by cultured neurons in a phosphoinositide 3-kinase (PI3K)-dependent pathway and lead to neurotoxicity, contributing to the pathogenic progression of AD [40]. The deficiency of neutral sphingomyelinase 2 (nSMase2) can decrease the release of brain exosomes, the production of Aβ42, plaque deposition, and the overall brain amyloid load, resulting in enhanced cognition in 5XFAD mice [41,42]. The cellular prion protein (PrPC), which is highly abundant in exosomes and associated with oligomeric Aβ42, was found to drive Aβ fibrillization and prevent the neurotoxicity mediated by oligomeric Aβ42 in neuronal cells [43]. Moreover, Qin et al. found that PrPC could promote Aβ plaque deposition by enhancing the expression levels of APP [44]. These results prompted us to consider how PrPC maintains a balance between neurotoxic and neuroprotective pathophysiology in AD and may also indicate a new approach for treating AD with respect to protein balancing. In summary, exosomes act as transporters for diffusing toxic Aβ and APP to recipient cells, and they are associated with the PI3K pathway, nSMase2, and PrPC. In this context, the toxic influence of Aβ on neurons has been elaborated. However, the function of Aβ on glial cells also requires further exploration. Exposure to Aβ was able to decrease the secretion of exosomes derived from astrocytes, which was mainly caused by activation of the c-Jun N-terminal kinase (JNK) signaling pathway [47]. Aβ treatment can induce the selective release of small heat-shock protein HspB1 from astrocytes via a non-classical method of secretion. HspB1 was detected free in the medium or bound-to exosomes and was found to bind and sequester extracellular Aβ [48]. In addition, exosomes derived from astrocytes accelerate the development of AD under pathological conditions. The Aβ-related astrocyte-derived exosomes (ADEs) from the brain tissue and serum of a transgenic mouse model of familial AD (5 × FAD) or AD patients were rich in the sphingolipid ceramide, which promotes the binding of Aβ to voltage-dependent anion channel 1 (VDAC1) to form an oligomeric proapoptotic pore. This ultimately triggered downstream apoptosis, neuronal cell fragmentation, and death, which suggested that the neurotoxicity of Aβ was strengthened by exosomes [49]. Interestingly, ADEs under physiological conditions alleviate the progression of AD. ADEs contributed to a reduction in oligomeric Aβ-induced neurotoxicity in vitro and enhanced the clearance of Aβ in vivo. The production of exosomes secreted from astrocytes (ADEs) was strengthened by ultrasound, could be internalized by SH-5Y5Y cells, and reduced the uptake of Aβ42. ADEs can also be delivered into the brain and clear amyloid-β plaques across the BBB in APP/PS1 mice [50]. The astrocytes demonstrated a protective function on neurons by decreasing Aβ binding to oligomers and synaptopathy through the release of insulin and insulin-like growth factor-1 (IGF1) in an exosome trafficking pathway [51]. Moreover, microglia participate in the process of regulating the release of exosomes containing Aβ (Table 1). Microglia are major phagocytes in the brain and they participate in eliminating Aβ via the secretion of exosomes. The CHME3 microglia showed an early phagocytic influence on extracellular APP and Aβ aggregation and, later, release of inflammatory factors when co-cultured with SH-5Y5Y cells that overexpressed APP695swe. They could also internalize exosomes secreted from neuroblastoma cells and showed sustained sensitization to the overexpression of pro-inflammatory gene markers, implying that the dysregulation of the neuron-microglia signaling pathway participates in AD pathology [52]. The activation of microglia and the AD pathogenic process are linked to glutaminase C (GAC), which is upregulated in mouse brains with early AD. The enhanced expression levels of GAC promote the release of microglial exosomes and make functional alterations to exosomes and inclusions containing microglia-activated pro-inflammatory miRNAs in the early stage of AD pathogenesis [45]. The microglial transmembrane receptor TREM2 (a triggering receptor expressed on myeloid cells-2), which is located on the membrane of microglial exosomes, governs the release of exosomes, altering the inflammatory circumstances around Aβ and promoting the clearance of Aβ by microglia [53]. Thus, ADE promotes AD progression under pathological conditions while decreasing AD progression under physiological conditions. Moreover, microglia are involved in removing Aβ by releasing exosomes regulated by GAC and TREM2. A large body of evidence implies that the abnormal accumulation of APP-related products, such as CTF and Aβ, initiate intraneuronal communication in AD within vesicles of the endosomal–lysosomal (endolysosomal) pathway, which mediates both the generation and degradation of APP-derived products. Amyloid formation was proven to originate intracellularly, breaking the integrity of the intracellular membrane and resulting in lysosomal leakage [54]. The formation process of exosomes is associated with the endosomal–lysosomal pathway. These findings suggest that the metabolic process of APP and exosome production is involved in the process of sorting the endosomal–lysosomal pathway. Several studies have explored the underlying molecular mechanism of endolysosomal system dysfunction for the formation of exosomes containing APP and its products. The post-translational modification ubiquitination of APP cytodomain lysines plays a critical function in APP endosomal sorting. Blocking the ubiquitination of APP by all of its mutant C-terminal lysines causes redistribution of APP from the endosomal intraluminal vesicles (ILVs) to the endosomal membranes; this is accompanied by a reduction in CTF levels but an enhancement of Aβ40 levels in secreted exosomes, mediated by presenilin 2 (PSEN2) cleavage [55]. The accumulation of CTFβ (C99) is closely associated with early lysosomal dysfunction [56]; treatment with γ-secretase inhibitor D6 caused further enhancement of endolysosomal-related APP-CTFs and aggravated the dysregulation of lysosomal-autophagic function [56]. Further studies revealed that D6 can facilitate APP-CTF oligomerization and induce oligomeric APP-CTFs to be mislocated in compartments of the endolysosomal network, including exosomes, by preventing C99 proteolysis that is dependent on the blockage of γ-secretase in APPswe-expressing cell media and the mouse brain. This suggests that D6 can be considered as a potential therapeutic strategy in AD pathology [57]. The components of the ESCRT apparatus are considered as critical regulators in the formation process of exosomes containing APP and its products. The secretion of CTFβ into small vesicles and the subcellular localization of APP are mediated by vesicle-related proteins Alix and Syntenin-1, the functions of which are important in the budding of the endosomal membrane. Meanwhile, the depletion of Alix and Syntenin-1 was able to change the subcellular localization of APP and attenuate the neurotoxicity induced by EVs containing APP [58]. The class III PI3K (PI3K-III)/Vps34 signaling pathway participates in the regulation of endolysosomal function and autophagy. Vps34 depletion can lead to endolysosomal membrane injury and advance the secretion of atypical exosomes that are rich in undigested lysosomal compounds, especially CTFs [59]. The accumulation and aggregation of Aβ have been observed in MVBs and can lead to the enlargement of MVBs in late endosomes, these events can be mimicked by the dysfunction of ESCRT-III as well as dominant negative VPS4A (dnVPS4A), suggesting that a deteriorating cycle of ESCRT-dependent late endosomal dysfunction is associated with Aβ accumulation [54]. Aβ accumulation can be induced by the interaction between APP and CD147, a subunit of γ-secretase, when its accessory protein Hook1 targets Rab22 in neuronal cells overexpressing APPswe695 under hypoxic conditions [60]. This evidence suggests that the endosomal–lysosomal system is dysregulated in AD pathology, and the substances that accumulate in neuronal cells are released into the extracellular space via EVs. As well as Aβ being viewed as an endosomal–lysosomal route, the degradation of Aβ has also been linked with the exosome formation process. Intraneuronal Aβ can be degraded by metalloproteases, including endothelin-converting enzyme (ECE)-1 and -2. The activities of these enzyme were also detected in exosomes, implying that MVBs are intracellular sites of Aβ degradation. Moreover, prohibiting the activities of ECE proteins enhanced intracellular and extracellular Aβ aggregation and the intracellular generation of Aβ oligomers both in vitro and in vivo [61]. Moreover, Tetraspanin-6 (TSPAN6) is highly expressed in AD brains and acts as a crucial regulator in balancing lysosomal-dependent degradation and the secretion of exosomes enriched in APP-CTF. The overexpression of TSPAN6 can increase Aβ accumulation and shift the balance towards the generation of ILVs, eventually forming exosomes, while reducing the degradation of APP-CTF by impairing the autolysosomal pathway [62]. In brief, the main reason that the formation of APP-related products such as CTF and Aβ is toxic to the cell or causes Aβ degradation is closely linked to the formation process of exosomes in the endolysosomal pathway. The propagation of pathological Tau proteins is a crucial characteristic of AD, and extracellular vesicles, especially exosomes, can spread this Tau pathology. For instance, exosomes can act as transporters for the spread of p-Tau pathology (Figure 4). Mice injected with plasma NDEs from ADC patients displayed increased p-Tau (PHF-1 antibody)-positive cells in the CA1 region of the hippocampus compared to plasma NDEs from patients with CNC and stable MCI patients [63]. Indeed, the exosomes extracted from the brains of Tau transgenic rTg4510 mice had high levels of Tau proteins, accelerated Tau phosphorylation, NFT production, and oligomeric aggregation, and could transfer the accumulation and misfolding of endogenous cellular Tau to recipient cells in a threshold-dependent way [64,65]. Tau in neuron-derived exosomes has different species, including monomers, oligomers, and aggregates, and the secretion of exosomes is raised by neuronal activity. These exosomes containing propagated Tau advance Tau accumulation and are associated with the trans-synaptic transmission of Tau between neurons [66]. Exosomes, taken from human induced pluripotent stem cell (iPSC)-derived neuron (iN)-conditioned media, cerebrospinal fluid (CSF), and plasma major, contained more mid-region-positive Tau than full-length (FL) Tau [67]. Although FL Tau has a greater tendency to propagate, the iN-derived exosomes containing Tau that were injected into wild mice possessed the ability to cause Tau aggregation and neurodegeneration, and they enhanced the dendritic blebbing of hippocampal neurons that were both ipsilateral and contralateral to the injection site in naïve mouse brains [68]. Moreover, mutant Tau expression in iNs caused the dysregulation of cargo proteins containing iN-derived exosomes, resulting in the aggregation of pathologic p-Tau after injection into the mouse brain [69]. Glial-derived exosomes enriched in Tau also contribute to Tau diffusion in the brain. The astrocytes were able to release Tau- and p-Tau-containing exosomes, which spread pathogenic Tau through the brain when exposed to Aβ25–35 but could be inhibited by the calcium-sensing receptor (CaSR) antagonist (calcilytic) NPS2143 [46]. The release of exosomes from the microglia transferred Tau and decreased Tau aggregation by restraining the synthesis of these exosomes both in vivo and in vitro [70]. The accumulation of Tau in exosomes was associated with microglia in Tau transgenic mice and could attenuate the accumulation of Tau by decreasing the release of exosomes [70]. In this context, we elucidated the interaction between Aβ aggregation and the endolysosomal pathway, which is also associated with Tau aggregation. The exosomal Tau escapes the endosome and propagation only occurs when the endosomal membranes present permeabilization, which is enhanced by the overexpression RAB7. This indicates the critical role played by the integrity of the endosomal membranes in transferring the aggregated protein to escape lysosomal degradation to recipient cells [71]. In summary, exosomes derived from neurons or astrocytes under AD pathological conditions can transfer and promote the accumulation of p-Tau, while exosomes from microglia can decrease aggregation. Moreover, the biogenesis of exosomes containing Tau is also modulated by the endosomal–lysosomal pathway. Currently, numerous clinical evaluations, including cognitive tests and functional brain imaging (MRI, PET, and SPECT scans), are employed to evaluate AD [72]. Moreover, detecting markers, including Aβ42 (Aβ1–42), total-Tau (tTau), and p-Tau-181, in CSF is paving the way for AD diagnosis based on biomarkers [73]. A growing body of evidence suggests that the crucial functions of exosomes that contain certain aggregation-prone proteins, including Aβ, APP C-terminal fragments, Tau, and the prion protein, are involved in the pathophysiology of AD [74]. The aggregation-prone proteins transfer from cell to cell and spread across the brain via transportation by vehicles, leading to onset and propagation of the disease [75]. Furthermore, the pathogenic proteins in exosomes derived from brains containing AD were proven to be able to freely cross the blood–brain barrier (BBB), thus suggesting that brain-derived exosomes could be potential biomarker carriers for AD in the blood [76]. Determination of the pattern of several AD-related proteins in plasma exosomes has value for exploring blood-based biomarkers at different stages of AD. Plasma exosomes were demonstrated to be ring-shaped in both AD patients and healthy controls; however, compared to plasma exosomes in healthy people, the exosome distribution in individuals with AD was more concentrated and the exosome diameter was relatively smaller [77]. To be protected from degradation by the bilayer membrane in exosomes, AD pathogenic proteins were more enriched in plasma exosomes than in plasma [76]. Tau in central-nervous system (CNS)-derived exosomes, which are labeled by a putative CNS-specific marker-L1 cell adhesion molecule (L1CAM), have been found to be readily transported from the brain to the peripheral blood in AD mice [78]. The concentrations of tTau and APP were reduced while the p-Tau-181/tTau ratio, Aβ42 level, Aβ42/Aβ40 ratio, and tTau/Aβ42 ratio were increased in plasma EVs, including exosomes, in the mild and moderate stages of AD [79]. Furthermore, the raised levels of p-Tau-181 and the tTau/Aβ42 ratio in plasma EVs were both negatively correlated with cognitive scores [74,76]. Moreover, older participants with cognitive decline less severe than MCI or dementia also presented higher levels of total Tau, p-Tau-181, and p-Tau-231 in neuronal extracellular vesicles (nEVs) than cognitively stable participants [80]. Plasma neuron-derived exosomal levels of p-Tau-181 and Aβ42 changed markedly with increasing age in AD patients compared to controls, while there was no alternation in p-Tau-S396 levels [63,81]. The difference between Aβ42, tTau, p-Tau-181, and p-Tau-S396 levels in plasma neuron-derived exosomes in control, aMCI, and AD individuals was strongly related to CSF levels, and the diagnostic powers of these combined markers in exosomes were similar to those of CSF. Moreover, the AUC (area under the curve) values of these combined markers in exosomes and CSF were both higher than those of individual markers, suggesting that this combination of exosomal biomarkers had higher diagnostic efficiency than each single biomarker, and the exosomal biomarkers had the same diagnostic power as the CSF biomarkers [77,82]. The combination of Aβ42 in plasma NDEs and Sniffin’ stick (SS-16) scores exhibited better prediction of the conversion of MCI to AD dementia at two- and three-year return visits [83]. In summary, AD is a disease that progresses from an asymptomatic phase, to a minor cognitive (MCI) phase, to AD with mild, moderate, and severe dementia phases with biomarker evidence [84], including higher levels of exosomal Tau, p-Tau-181, and p-Tau-231. This is followed by the MCI phase, which is characterized by Aβ42 and enhanced levels of tTau and p-Tau-181; meanwhile, high levels or ratios of p-Tau-181/tTau, Aβ42, Aβ42/Aβ40, and tTau/Aβ42 are seen in the mild and moderate AD phases. Moreover, these complex pathogenic AD proteins found in plasma neuronal exosomes have been proven to be more dependable biomarkers for AD than single markers alone [74] (Figure 5). In addition, other Aβ-peptide-related biomarkers involved in the progression of AD pathology were also identified in exosomes. For instance, levels of two Aβ-binding proteins, including alpha-1-antichymotrypsin (AACT), were increased and the level of C4b-binding protein alpha chain (C4BPα) was decreased in plasma exosomes in a case of AD; these proteins were therefore identified as potential exosomal biomarker candidates for AD diagnosis [85]. The levels of gelsolin, which is related to restraining Aβ fibril formation, were lower in serum exosomes in patients with dementia than in controls [86]. The level of BACE1-antisense transcript (BACE1-AS) was notably increased in plasma exosomes in AD patients compared with the normal controls [87]. However, Fotuhi et al. found no notable differences between levels of BACE1-AS in the plasma exosomes of AD and control participants. The evidence suggests that more samples need to be evaluated to verify the different data. Interestingly, the composition of the Aβ42-generating system was detected in two separate, independent sets of astrocyte-derived exosomes (ADEs) and NDEs in the plasma of AD patients and controls. The levels of β-site amyloid precursor protein-cleaving enzyme-1(BACE-1), γ-secretase, soluble Aβ42, soluble sAPPβ and sAPPα, p-Tau-181, and p-Tau-S396 were dramatically higher (3- to 20-fold) in ADEs than in NDEs in both AD patients and matched normal subjects, which suggests that ADE cargo proteins may facilitate an investigation of the mechanisms of cellular interactions and biomarkers in AD [88]. Moreover, Tau levels were found to be enhanced in the microglia-derived EVs of AD patients compared with controls [89]. Animal experimental data also confirmed that the levels of Aβ and Tau in plasma NEVs and AEVs were consistent with their levels in the brain [90]. These data demonstrate the potential role of microglia-derived EVs in the spread of Tau in the human brain and the progression of AD pathology. As well as exosomes that contain pathogenic proteins as markers extracted from CSF and plasma, several studies have demonstrated the novel detection of vehicle-based urinary or salivary exosomes in the early stages of AD. The levels of AD pathological proteins in urinary exosomes of AD patients were significantly higher than those found in matched healthy controls. The quantity of urinary exosomes in AD patients was also higher than that in healthy subjects assessed by NTA [91]. The expression levels of Aβ oligomer/fibril, Aβ, and phosphorylated Tau contained in salivary exosomes were markedly higher in AD and cognitively impaired patients compared with healthy subjects, a finding that contributes to research into the pathological progression of AD [92]. Exosomes originate from various cells under specific physiological or pathological conditions. However, to date, the exact functions of exosomes have still not been sufficiently explained. This review demonstrated that exosomes act as major natural nanocontainers containing APP cleavage products as well as hyperphosphorylated Tau, which is secreted by neurons and microglial cells. The formation process of these exosomes are involved in the endosomal–lysosomal pathway; furthermore, they can transfer AD pathological molecules and are closely associated with the pathological processes of advanced AD. Exosomes originate from the body’s cells, meaning that their contents are tightly associated with the functional state of the donor cell. Moreover, exosomes are characterized by their smaller size, more extensive sources, and lower immunogenicity compared with donor cells. This suggests that exosomes can be considered a potential and promising noninvasive biomarker in the diagnosis of a variety of diseases, including AD. The cause of most AD cases remains unknown, except for genetic mutation, but several important mechanisms have been explored as potential causes of AD, including Aβ plaque, neurofibrillary tangles, synaptic dysfunction, neurotransmitter imbalance, neuroinflammation, gut microbiome disruption, oxidative stress, and autophagy. This range of causes reflects the heterogeneity of AD patients [93], which increases the difficulty of exploring identical biomarkers for different AD cases. Exosomes released by cells into circulation, as well as bodily fluids, show various protein and RNA contents in healthy subjects and patients, which can be measured as potential diagnostic markers [94]. In this review, we introduced the alteration of plasma exosomal APP and Tau cleavage products as a potential biomarker for different AD stages; however, more specific and precise biomarkers of the different causes of AD cases still require further exploration. This review also described how the exosomes extracted from bodily fluids, including CSF, plasma, urinary, or salivary exosomes, carry various diagnostic molecules, such as Aβ40, Aβ42, tTau, and p-Tau, which are also considered as biomarkers of CSF in AD diagnosis. Exosomes may provide more exact data to identify early markers of AD based on their precisely regulated biogenetic processes and structural features. However, a lack of standard and efficient isolation and characterization techniques places significant constraints on the use of exosomes as a tool in AD diagnosis. Currently, differential ultracentrifugation is considered the gold standard for separating exosomes; however, this method is time-consuming. Other methods, such as immunoprecipitation and size filtration, have been developed to avoid the need for ultracentrifugation. However, these methods typically lead to high levels of polluted proteins and a mixture of extracellular vesicles. Thus, extraction technology, identification standardization, and database construction of exosomes need to be the further developed, as this will provide a new basis for the early detection of exosomal APP cleavage products or p-Tau in AD.

PMC10003551

Xiaofeng Qin,Yujie Ning,Liming Zhou,Youming Zhu

Oral Submucous Fibrosis: Etiological Mechanism, Malignant Transformation, Therapeutic Approaches and Targets

05-03-2023

oral submucous fibrosis,oral squamous cell carcinoma,myofibroblast,malignant transformation,epithelial–mesenchymal transition,natural compounds,miRNAs,lncRNAs

Oral submucosal fibrosis (OSF) is a chronic, progressive and potentially malignant oral disorder with a high regional incidence and malignant rate. With the development of the disease, the normal oral function and social life of patients are seriously affected. This review mainly introduces the various pathogenic factors and mechanisms of OSF, the mechanism of malignant transformation into oral squamous cell carcinoma (OSCC), and the existing treatment methods and new therapeutic targets and drugs. This paper summarizes the key molecules in the pathogenic and malignant mechanism of OSF, the miRNAs and lncRNAs with abnormal changes, and the natural compounds with therapeutic effects, which provides new molecular targets and further research directions for the prevention and treatment of OSF.

Oral Submucous Fibrosis: Etiological Mechanism, Malignant Transformation, Therapeutic Approaches and Targets Oral submucosal fibrosis (OSF) is a chronic, progressive and potentially malignant oral disorder with a high regional incidence and malignant rate. With the development of the disease, the normal oral function and social life of patients are seriously affected. This review mainly introduces the various pathogenic factors and mechanisms of OSF, the mechanism of malignant transformation into oral squamous cell carcinoma (OSCC), and the existing treatment methods and new therapeutic targets and drugs. This paper summarizes the key molecules in the pathogenic and malignant mechanism of OSF, the miRNAs and lncRNAs with abnormal changes, and the natural compounds with therapeutic effects, which provides new molecular targets and further research directions for the prevention and treatment of OSF. OSF is a chronic and insidious oral disease involving multiple parts of the oral cavity and is generally considered to be a disease related to collagen metabolism disorder. Increased collagen formation and decreased collagen degradation lead to the deposition of collagen fibers in oral tissues, which in turn leads to the development of OSF. Patients often go to the doctor because of burning pain of the oral mucosa, accompanied by ulcers, blisters, a diminished sense of taste, a dry mouth, lip and tongue numbness and other symptoms, such as a serious mouth opening restriction, dysphagia and tongue movement disorder. The disease has a certain malignant potential, which belongs to oral potentially malignant disorders (OPMD). At the same time, OSF is closely related to the occurrence of OSCC [1]. The data published by the World Health Organization (WHO) in 2022 reported that the global prevalence of OSF was 4.96%, with a 95% confidence interval of 2.28–8.62 [2]. At present, OSF is mainly found in the Indian Peninsula, including Southeast Asian countries and regions such as India and Pakistan [2], and in China, it is mainly found in Hunan, Hainan and Taiwan [3]. The disease can occur at any age, but is most common in adolescents and adults under the age of 35. Most of the literature mentioned the high incidence of OSF in women, but some literature suggested that the high incidence of OSF was in men aged 20–40 years [4]. Researchers conducted a 10-year follow-up survey and found a significant increase in the number of cases of OSF in eastern India, especially in men [3]. Stimulating factors such as eating pepper, smoking and drinking can aggravate the progression of OSF [5]. A study in Taiwan found that alcohol consumption was associated with a higher risk of OSF, increasing the overall risk of malignant transformation of OPMD by 23% [6]. Studies have shown that there are more than 5000 chemicals in tobacco smoke, among which N-nitrosamine is the main cause of its genotoxic effect [7]. N-nitrosamine can directly produce cytotoxic effects on keratinocytes and fibroblasts [8], trigger oxidative stress and inflammation, and activate immune cells, such as macrophages, lymphocytes and B cells [7]. A large number of reactive oxygen species (ROS) are released while smoking and act on intracellular lipid, protein, polypeptide, nucleic acid and other biological macromolecules, resulting in structural and functional changes of proteins and nucleic acid damage [9]. In turn, the accumulation of oxidative damage can cause cell senescence and further accelerate the production of ROS, forming a vicious cycle. The senescence-associated secretory phenotype (SASP) components like interleukin-1 (IL-1), interleukin-6 (IL-6), and growth regulated oncogene α (GRO-α), induce double-strand DNA breaks in keratinocytes and drive genetic instability [10]. Continuous mechanical stimulation to the oral mucosa, causing trauma to the mucosa, and the inflammatory reaction, is initiated locally and a variety of inflammatory mediators are secreted, such as interleukin-1β (IL-1β), IL-6, interleukin-8 (IL-8), tumor necrosis factor-α (TNF-α) and transforming growth factor β (TGF-β); the injured mucosa further atrophy and cause ulcer development due to long-term inflammation [3]. Mucosal ulceration stimulates fibroblast proliferation and activates the coagulation system. Thrombin can induce the activation of TGF-β1 mediated by alphavbeta1 (αvβ1), alphavbeta3 (αvβ3) and alphavbeta5 (αvβ5) integrins, causing the generation of connective tissue growth factors (CTGFs) in buccal mucosal fibroblasts (BMFs) [11,12]. Individuals who are anemic and deficient in vitamins A, B, C and iron have an increased risk of OSF [13]. Studies have shown that the levels of vitamin A, C and E in the saliva of OSF patients are significantly decreased, while the activities of superoxide dismutase (SOD) and glutathione peroxidase (GPx) are significantly decreased. These changes are positively correlated with the degree of OSF, thus reflecting the increase in oxidative stress with the progression of the OSF [14]. The level of vitamin A in saliva is positively correlated with the level of serum vitamin A, which has the role of stabilizing mucosa, and a deficiency will lead to the loss of mucosecretory cells and epithelial atrophy. Vitamin C is an important free radical scavenger antioxidant, which plays a protective role by alleviating the ROS-induced response, and its level decreases with the increase of collagen synthesis [14]. The interaction between trace elements in saliva and OSF has been confirmed by some studies; the copper level and copper/zinc ratio in the saliva of OSF patients are significantly increased [15]. The levels of zinc and copper in serum were significantly increased in OSF patients [3,13]. Lysyl oxidase (LOX) has a conserved copper binding site, which is a copper-dependent enzyme [16]. High concentrations of copper can increase the activity of LOX, increase collagen synthesis, catalyze the covalent cross-linking of extracellular matrix (ECM) collagen and elastin, and has a certain anti-dissolution ability, which can enhance the hardness and mechanical properties of the ECM [16,17]. The study found that blood samples from patients with OSF were significantly deficient in zinc compared with healthy controls [3]. Matrix metalloproteinases (MMPs) are a class of zinc-dependent proteins and peptide hydrolases [18], which can specifically regulate protein degradation of the ECM, and more importantly, they are related to tumor invasion and metastasis [19]. The tissue inhibitor of matrix metalloproteinases (TIMPs) is a specific inhibitor of MMPs, which jointly maintain ECM homeostasis. The degradation process of the ECM is affected by the increase in TIMPs, which breaks the dynamic balance between TIMPs and MMPs, reduces the degradation of collagen, leads to the deposition of the ECM, and promotes the occurrence and progression of OSF [3]. Some scholars believe that mucosal fibrosis may be related to allergic reactions caused by exogenous antigen stimulation [20]. Moreover, T lymphocytes, macrophages and mast cells increased significantly in the connective tissue of OSF, and CD4 lymphocytes were dominant [13]. The levels of profibrotic cytokines such as interleukin-1α (IL-1α), IL-1β, IL-6 and TGF-β1 in OSF serum were significantly increased, while the tumor necrosis factor-γ (TNF-γ) was significantly decreased [3]. Antinuclear antibodies (ANA), smooth muscle antibodies (SMA) and gastric parietal cell autoantibodies (GPCA), which are immune-related antibodies, have tested positive in patients with OSF [21]. The expression of TGF-β in OSF tissues was significantly higher than that of normal oral mucosa, in which TGF-β1 was a major growth factor and the most obvious molecule in the process of fibrosis, and was related to the development of almost all fibrosis lesions, including OSF, in which TGF-β2 also played an important role [22,23]. The signaling pathways of TGF-β/Smad2 and Smad4 have been found to be activated in keratinocytes and myofibroblasts in OSF tissues [24]. TGF-β has also been shown to promote fibroblast–myofibroblast differentiation by inducing the contractile phenotype and upregulating α-SMA [25]. In addition, by activating αvβ6-dependent TGF-β1, tissue fibrosis-related genes were upregulated, inducing oral fibroblasts to differentiate into myofibroblasts [23]. Myofibroblasts are α-SMA expressing contractile cells that migrate to the site of injury at the initial stage of inflammation, are responsible for wound healing, and are the major producers of ECM after injury, including fibronectin 1 (FN1) and collagen [26,27]. Myofibroblasts continued to increase from the beginning to the later stages of OSF, suggesting that myofibroblasts could be used as an indicator to evaluate the severity of the OSF [26]. The continued activation of myofibroblasts is associated with the excessive deposition of the ECM and pathological fibrosis; in addition, methods that inhibit myofibroblast activity have been proven to prevent fibrosis, such as of the lung, liver, etc. [25,28]. Studies have found that the frequency of HLA-A10, HLA-B7, HLA-DR3, haplotypes A10/DR3, B3/DR3 and A10/B8 in OSF patients increases. The increased frequency of the HLA-B76 phenotype and the increased frequency of the HLA-B51/Cw7 and HLA-B62/Cw7 haplotypes were also associated with OSF susceptibility [3]. Accumulating evidence supports the significance of inherited family history and genetic predisposition in the pathogenesis of OSF [3,24]. Some individuals are more likely to develop OSF due to their genetic polymorphisms in collagen, MMPs, TIMPs and TGF-β1 [5]. Genomic instability was found in 47% to 53% of OSF samples [29]. Studies have indicated that the genotype of type I collagen is associated with the highest risk of OSF, and the genotypes of the low exposure group associated with OSF are CC of collagen type I alpha 1 chain, AA of collagen type I alpha 2 chain, and TT of collagenase-1 [24]. Single nucleotide polymorphisms (SNPs) in the MMP-3 promoter region and the 5A genotype increase the risk of OSF [4]. The CC allele of the TGF-β1 gene on chromosome 19q was associated with OSF risk, and the AA and GG genotypes of the LOX gene on chromosome 5q were the low and high exposure alleles of OSF, respectively. Cystatin C is encoded by the CST3 gene on chromosome 20p, and its high OSF risk allele is AA in both the low and high exposure groups [24]. CST3 or Cystatin C belonging to the cystatin family and decreased production of cysteine protease inhibitors can enhance the collagen degradation of OSF [30]. Cystatin C is an effective inhibitor of lysosomal proteolytic enzymes and cysteine proteases [30]. Higher concentrations of cystatin are directly or indirectly related to the degradation of ECM and lead to the invasion and metastasis of tumor cells [30]. More importantly, it has been demonstrated that Cystatin C is a new type of TGF-β signaling antagonist [30]. Betel quid (BQ) is chewed by over 0.6 billion people globally, especially in Asia, where the BQ chews are formulated in a variety of formulas, but usually include betel nuts, betel leaves and hydrated lime, and often contain tobacco [31]. The International Agency for Research on Cancer (IARC) has reported that BQ is carcinogenic to humans. This has also been confirmed in animal studies, where BQ intake has been linked to OSF and OSCC, as well as other cancers. The chemical composition of BQ has been repeatedly studied and arecoline has been consistently detected in all products; regardless of the type of areca nut product, regional location and maturity of the BQ chewers, the arecoline has been considered a key driver of OSF and OSCC [31]. It has been reported that the relative risk of OSF increases significantly with the increase of BQ chewing frequency, and any frequency of BQ intake will increase the risk of OSF by about 50 times [5]. The crude fiber, areca alkaloids, slaked lime, ROS, copper and other components of BQ play different degrees of promoting role in the process of OSF. Long-term chewing of BQ is both a physical and chemical stimulus. Arecoline is a primary areca alkaloid, which itself induces ectopic changes in homologous chromosome alleles [24], and also leads to chromosome breakage and other cell malformations [32]. Areca alkaloids will also form N-nitrosamine metabolites after nitrosation [3]. Shajedul Islam et al. found that under the joint action of arecaidine and slaked lime, the proliferation of BMFs increased and the phenotype of cells changed, leading to the increase of collagen fiber production and the promotion of collagen synthesis [3,33]. The profibrotic effect of arecoline on BMFs may also be indirectly induced by oral keratinocytes, thereby affecting the collagen metabolism of BMFs [31]. Arecoline activated YAP by increasing the level of ROS and inducing the PERK pathway, leads to the start of the endothelial–mesenchymal transition (EMT) and then OSF [34]. The ROS is generated by the autooxidation of areca polyphenols in the mouth and the nitrification of areca alkaloids [31]. TGF-β1 activation, Smad2 phosphorylation and ROS production in BMFs are induced by arecoline [23]. Previous evidence has shown that CD147 is related to the development of multiorgan fibrosis. On this basis, Wang et al. showed that arecoline promoted the expression of CD147 in human oral keratinocytes through the TGF-β1 signaling pathway, and upregulation of CD147 may promote the development of OSF [35]. Arecoline-induced mitochondrial ROS leads to the initiation of TGF-β1 signaling in human oral mucosal fibroblasts, and subsequently, increases the composition of CTGF and Egr1, which are key TGF-β factors in fibrotic diseases [23]. Arecoline can directly stimulate BMFs to synthesize collagen and differentiate into myofibroblasts [23]. More soluble copper can be detected in the oral environment of QB chewers and can be absorbed by buccal mucosa, which will promote the process of OSF [36]. Plasminogen activator inhibitor Type-1 (PAI-1) inhibits MMPs activation to adjust the dynamic balance of the ECM, and excessive PAI-1 can aggravate fibrosis [37]. TGF-β may promote the expression of PAI-1 through ROS and Smad-dependent (ALK5/Smad2/3) and Smad-independent (Src/EGFR/MEK/ERK) pathways [24]. Hypoxia increases arecoline-induced production of PAI-1 and ECM in oral mucosal fibroblasts [24]. Hypoxia-induced factor-1α (HIF-1α) promotes epithelial–mesenchymal transition by increasing extracellular matrix modifiers and LOX, leading to OSF fiber formation [3]. ROS and HIF-1α can induce upregulation of TGF-β1 under hypoxia conditions [3]. In the past two decades, non-coding RNAs (ncRNAs), which do not encode proteins, have been found to play a key role in physiological and pathological processes by regulating gene transcription and translation through various mechanisms, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), etc. [38]. Yang et al. observed that the expression of miR-29c in fibrotic buccal mucosa fibroblasts (fBMFs) was downregulated and that transfection of miR-29c mimics reduced the fBMFs migration ability and collagen gel contractility whereas inhibition of miR-29c could induce a myofibroblast phenotype, and mir-29c also inhibited the activation of myofibroblasts by inhibiting tropomyosin-1 (TPM1) [28]. From the above results, it is not difficult to see that upregulation of miR-29c can delay the development of OSF, so miR-29c can be regarded as a promising therapeutic target for OSF. MiR-21 is a definite non-coding RNA for fibrosis. Liao et al. verified that programmed cell death factor 4 (PDCD4) is an immediate target of miR-21, and the overexpression of PDCD4 in fBMFs attenuates the activity of myofibroblasts [39]. The study by Han et al. clarified that adipose-derived stem cell-derived extracellular vesicles (ADSC-EVs) inhibited the proliferation, migration, invasion and fibrosis of fBMFs and promoted apoptosis through the miR-375/FOXF1 axis, thus inhibiting OSF progression [40]. Chattopadhyay et al. showed that the expressions of miR-31 and miR-204 were, respectively, upregulated and downregulated in OSF tissues [41]. Chickooree et al. summarized the expression profiles of miRNAs in the buccal mucosa of clinically significant OSF patients and normal volunteers and found that there existed clear differences in the expression of 11 miRNAs. Among them, the overexpressed miRNAs were hsa-miR-455-3p, hsa-miR-455-5p and hsa-miR-623, and the underexpressed miRNAs were hsa-miR-1290, hsa-miR-3180-3p, hsa-miR-4792, hsa-miR-509-3-5p, hsa-miR-5189, hsa-miR-610, hsa-miR-760 and hsa-miR-921 [42]. In the above papers, some scholars have verified the targets of miRNAs (miR-760 [42,43], miR-455 [42,44], miR-29c [28], miR-21 [39], miR-10b [45], miR-200C [46], miR-1246 [47], miR-203 [48]). However, there are still some miRNAs (miR-760 [42,43], miR-455 [42,44], miR-509-5p [42], miR-610 [42], miR-10b [45], miR-623 [42], miR-31 [41], miR-204 [41]) whose target sites are only predicted by TargetScan, miRanda and other databases. However, the exact targets of these miRNAs, the signaling pathways involved in them, and whether they have the effect of inhibiting the proliferation and migration of OSF cells, promoting the apoptosis of the OSF cells as predicted, need to be verified by subsequent experiments. Lee et al. showed that LINC00084, as a sponge of miR-204, upregulated the expression of zinc finger E-box binding homeobox 1 (ZEB1) and induced the transdifferentiation of myofibroblasts, causing an increase of ECM and fibrosis [49]. Therefore, downregulation of LINC00084 expression is considered to reduce the continuous activation of fBMFs and further prevent the malignant transformation of OSF. Yu et al. showed that the chronic stimulation of areca nut activates TGF-β signaling, leading to upregulation of the lncRNA H19 expression, thereby preventing the type I collagen inhibition of Mir-29b and reducing the activity of myofibroblasts [50]. Therefore, targeting the molecules on the H19/miR-29b axis is a possible way to alleviate OSF. Zhou et al. found that exosome-derived lncRNA ADAMTS9-AS2 inhibited the progression of OSF through the AKT signaling pathway, and also inhibited the PI3KT-Akt signaling pathway and EMT [51]. According to the above, we proposed a multi-factor pathogenic model of OSF with BQ as the main cause (Figure 1). The above key factors involved in the occurrence and development of OSF can become therapeutic targets for the disease and block the development of the disease. However, because TGF-β, HIF-1α and other molecules involve too many pathways, their regulatory effects on the human body are too extensive. Therefore, relatively small molecules, such as LOX, MMPs, TIMPs, Cystatin C, PAI-1, CTGF, Egr-1 and ncRNAs, can be considered for further research, and can improve local inflammation, the hypoxia environment and oxidative stress, so that they can be applied in clinical practice quickly. Oral cancer refers to malignant tumors of the mouth and lips, about 90% of which are diagnosed as OSCC [1]. In the GLOBOCAN 2020 report, there were 377,713 new cases of oral cancer (2% of the total 36 cancer cases) and 177,757 new deaths (1.8% of the total 36 cancer deaths) [52]. The incidence is highest in Melanesia and Central and South Asia, among which 69.1% are male, and there is a large regional difference [52]. Patients with OSF can have accompanying oral leukoplakia, oral lichen planus and other OPMD. OPMD lesions are more prone to cancer due to field cancerization. Therefore, OPMD is an important group of mucosal diseases before the diagnosis of OSCC [53]. Abnormal epithelial growth and epithelial atrophy can increase the probability of carcinogenesis, and current studies have shown a relevance between OSF epithelial dysplasia and malignant transformation [54]. Other studies have shown that the thickness of fibrosis in OSF is correlated with epithelial dysplasia [55]. The WHO reports that oral cancer is more common in areas of the world where BQ is chewed. South Asia has a large number of patients with OSF who develop oral cancer, with a cancer rate of about 4.2% (CI 2.7–5.6%) [1]. Tobacco, wine and betel nut are the main causes of oral cancer [56]. The carcinogenic component of areca nut can also induce gene mutations, such as tumor suppressor gene inactivation and activation of oncogenes, which can cause the development of cancer. Tobacco is a known carcinogen, and previous studies have shown that nitrosamines found in tobacco products are the main cause of their genotoxic effects [42]. Tobacco is metabolically activated by P450 enzymes to form N-nitronicotinoids, which can cause DNA damage and lead to potentially malignant diseases and, ultimately, oral cancer [7]. In patients with OSF, the progression to OSCC is associated with smoking and alcohol, but specific mechanisms of fibrosis are also involved [5]. Some studies have pointed out that OSCC originating from OSF tends to be younger and more aggressive [3]. BQ and its additive tobacco consumed by OSF patients are both first-level carcinogens that have been clearly defined by the IARC, which can damage cell genes, cause radiation damage, impair immune function, and further induce OSCC [57,58]. The potential carcinogenic components of BQ are mainly alkaloids and polyphenols. Although polyphenols have antioxidant effects, they may enhance the genotoxic and carcinogenic effects of alkaloids under certain environmental conditions, which is of special significance for the development of OSCC [31]. Arecoline is proved in OSCC and OSF-induced inflammation and produces ROS [31]. Slaked lime works by changing the environmental conditions, changing the pH of polyphenols, allowing them to be oxidized to produce ROS, regulating cell proliferation, cell migration and invasion, and potentially promoting cancer. And more importantly, nitrosamines interact with other macromolecules of the cell through oxidative stress, thereby promoting the occurrence of oral cancer [31,33]. The above results emphasize the importance of BQ components, including tobacco, in the malignant transformation of OSF. ROS are a group of short-lived, highly active, oxygen-containing molecules that can induce DNA damage and influence DNA damage response [59]. Numerous previous studies have shown that a small amount of ROS can adjust intracellular signal transduction and maintain a dynamic balance. However, a large number of ROS play a key role in the destruction of proteins and DNA, and even induce the development of cancer [9]. During the progression of OSF, a large number of ROS are produced, including both exogenous (BQ and tobacco) and endogenous ROS. The imbalance between ROS and the antioxidant defense system will cause oxidative stress, thus initiating the occurrence of cancer, and the ROS is joined in the adjustment of cancer cell apoptosis [60]. More importantly, studies have shown that in any normal cell, high levels of ROS can transform it into malignant cells [60]. A recent article by Nithiyanantham et al. showed that arecoline N-oxide plays an initial carcinogenic role in the oral cavity through inflammation, consumption of ROS and antioxidant enzymes [61]. ROS can regulate a lot of signaling pathways through transcription factors, such as nuclear factor-kappa-B (NF-κB), signal transducer and activator of transcription 3 (STAT3), HIF-1α, kinases, growth factors, cytokines and other proteins and enzymes, which are related to cell transformation, inflammation, tumor survival, proliferation, invasion, angiogenesis and tumor metastasis [60]. The ROS is associated with epigenetic changes in genes, which can help diagnose diseases [60]. The dual role of the ROS in tumorigenesis and progression includes ROS-dependent malignant transformation and oxidative stress-induced cell death [62], which provides us with new ideas for the prevention and treatment of OSF and OSCC. The research on ROS as a therapeutic target is worthy of further study. The use of antioxidants in the early stage can inhibit the ROS and prevent the occurrence of OSF and the activation of the OSCC tumor signaling pathway. After the disease, ROS production can be promoted, so that it can play the role of oxidative stress against the cancer cells to induce cancer cell death. Senescence is the common feature of wound healing, fibrosis and cancer [10]. Although senescence has a temporary anti-fibrosis effect, prolonging the senescence will promote fibrosis and malignant transformation [10]. Fibroblast senescence is induced by ROS production by keratinocytes in a TGF-β-dependent manner [31]. Previous studies have demonstrated that senescent fibroblasts have the same characteristics as activated fibroblasts/myofibroblasts and could promote the progression of OSCC through the production of ROS and MMPs [31]. The SASP derived from myofibroblasts induces the EMT of OSF and promotes cancer progression [10]. The senescence of oral mucosa cells plays an irreplaceable role in promoting the malignant transformation of OSF, and it also interacts with other cancer-related factors in OSCC, playing a synergistic role. EMT is a cellular process that transforms epithelial cells into a mesenchymal phenotype and is critical for tumor migration, tumor stem cell properties, chemotherapy resistance and metastatic potential [63]. During the dynamic transformation of EMT, E-cadherin, occludins, α-catenin and claudins, which maintain epithelial cell–cell junctions, are downregulated, whereas mesenchymal markers are overexpressed, such as α-SMA, snail, slug, vimentin, MMPs, insulin-like growth factors 1 (IGF-1), ferroptosis-suppressor-protein 1 (FSP-1), N-cadherin and zinc finger E-box binding homeobox (ZEB) [64,65,66]. These changes resulted in the loss of cell adhesion, increased ECM composition, enhanced migration potential and increased invasiveness [64]. Existing research also demonstrated that OSF significantly increased the cell–matrix adhesion, invasion and migration abilities and the activity of the MMP2 and IGF-1R of oral cancer, and affected the EMT by enhancing the expression of N-cadherin, fibronectin and vimentin and downregulating the expression of E-cadherin in human oral cancer cells [67]. Researchers have suggested that turning off the expression of the EMT-induced transcription factor Twist1 to reverse EMT is vital for spreading tumor cell proliferation and promoting distant colonization [68]. EMT activation plays an important role in the initial metastasis of OSCC and generates cancer stem cells (CSCs) in OSCC [69]. CSCs, also known as cancer initiating cells, have the ability to self-renew and are a risky cancer cell population associated with cancer disease recurrence, aggressiveness and resistance to chemoradiotherapy [70,71]. At this point, it has to be said that to improve the cure rate of OSCC, reduce the recurrence rate and mortality, targeting the CSCs is crucial. Several articles demonstrated that arecoline activates the TGF-β pathway [22], and the TGF-β signal transduction pathway is a key pathway to trigger OSCC [12]. The phosphatase and tensin homolog (PTEN) plays a role in immunity, fibrosis, malignancy and is inversely correlated with α-SMA [72]. The increase of TGF-β in OSF can reduce the level of the PTEN, and the inactivation of the PTEN gene leads to the upregulation of the AKT/S6K/Snail pathway by TGF-β1, resulting in the disassembly of the tight junctions of epithelial cells, the destruction of the basement membrane and the increase of epithelial-derived myofibroblasts, which play a role in EMT [72]. At the same time, AKT activity was enhanced, which prolonged the survival time of fibroblasts, and increased ECM production and fibrosis [72]. Richter et al. found that long-term combined stimulation of TGF-β1/EGF could enhance the invasive phenotype of OSCC compared with single growth factor stimulation, such as the significantly upregulated expression of MMP2 and MMP9 [73]. Increased expression of CD105, the TGF-β1 receptor, is associated with hypoxia-induced angiogenic activity in OSF and with the transformation of epithelial dysplasia [74,75,76]. One of the predictive methods for the malignant transformation of OSF is the presence of epithelial dysplasia on the initial biopsy [77]. Another factor in the malignant transformation of OSF is the HIF-1α. At this stage of OSF, collagen fiber accumulation, degeneration and vascular occlusion in the lamina propria and submucosa make oxygen supply to the diseased tissue more insufficient. HIF-1α, a tumor growth signal that is upregulated during hypoxia, is responsible for activating the vascular endothelial growth factor pro-angiogenic gene, which has an effect on tumor growth, glucose metabolism, invasion, chemoradiotherapy resistance and prognosis [78]. Studies have also confirmed that hypoxia modulates the activity of three key transcription factors (c-Myc, p53 and HIF-1α), leading to the continuous accumulation of ROS and the malignant transformation of cells [60]. Ishida et al. showed that hypoxia-induced EMT in OSCC occurs through the activation of the Notch signaling pathway [79]. Therefore, it is necessary to reduce the expression of HIF-1α in OSF and OSCC by targeting HIF-1α as a target, both in prevention and treatment. The inflammatory environment and degree of fibrosis also play a contributing role in the malignant transformation of OSF. Microtrauma in the process of OSF accelerates the diffusion of chemical components in the BQ into the submucosal tissues, and immune cells are locally recruited and secrete proinflammatory cytokines [80], resulting in inflammatory cell infiltration in submucosal tissues, which causes further atrophy and ulcers of mucosa, and continuous tissue inflammation leads to tissue fibrosis and malignant transformation. Various articles have told us that increased myofibroblasts are related to the severity and progression of OSF and OSCC [49]. Bale et al. have also demonstrated that the degree of fibrosis and levels of oxidative stress biomarkers (serum malondialdehyde (MDA) and SOD) are associated with malignant transformation [81]. The study by Reis et al. showed that the loss of PDCD4 expression was associated with tumorigenesis and invasion of OSCC, and the downregulation of PDCD4 by miR-21 was proved to increase the invasivity of oral cancer [82]. As a target gene of miR-31, the downregulation of C-X-C Motif Chemokine Ligand 12 (CXCL12) was of great significance in the development of precancerous lesions to cancer [41]. Wang et al. found that the circEPSTI1/miR-942-5p/LTBP2 axis promoted the proliferation and invasion of OSCC cells and promoted the progression of OSCC via the phosphorylation of the PI3K/Akt/mTOR signaling pathway elements [83]. Studies have shown that lncRNA ADAMTS9-AS2 inhibits PI3K-AKT signaling and EMT in OSCC. Exosomal ADAMTS9-AS2 can be transported into cells and exerts a similar tumor suppressor effect as exogenous ADAMTS9-AS2, which provides further evidence that exosomal lncRNAs can have a vital role in the occurrence and development of OSCC [51]. Chen et al. showed that IncRNA MEG3 inhibits the self-renewal and invasion ability of oral cancer stem cells by interacting with the molecular sponge miR-421, and the low expression of MEG3 can serve as a marker of poor prognosis in oral cancer [84]. Existing evidence has long been clear that OSF can go through malignant transformation into OSCC, and OSCC of OSF origin is clinically more aggressive than OSCC of non-OSF origin, with a higher rate of metastasis and recurrence [32]. OSF is an irreversible disease, even if the pathogenic factors are removed, so it is not only necessary to block the occurrence of OSCC from the malignant transformation process of OSF, but more importantly, to prevent OSCC from the occurrence of OSF. Figure 2 is our proposed OSCC model of malignant transformation based on OSF. Patients generally have a history of chewing BQ, and the clinical symptoms are white oral mucosa accompanied by leather-like texture changes. Patients will have severe burning in the oral cavity after eating spicy food [85]. With the development of this illness, patients may have dysfunctions in eating, chewing, pronunciation and even other functions in the latter course of the disease, which seriously affect patients’ nutrition intake and social communication. The main pathological changes in OSF include epithelial atrophy, collagen fiber accumulation, degeneration, vascular occlusion and reduction in the lamina propria and submucosa of the mucosa, and some patients experience epithelial dysplasia [23]. In patients with severely impaired mouth opening, numerous muscle fiber necrosis can be seen. Electron microscopic examination showed that the space between the epithelial cells was widened, a lot of free desmosomes or cell debris could be seen, the number of mitochondria was reduced, some mitochondria were swollen, and collagen fibers with hyalinosis were distributed in bundles [2]. Tissue biopsy is the gold standard, but it is invasive. So, we need to find easier, less invasive, more accurate and less expensive screening and diagnosis methods. Some biochemical parameters are changed in the process of OSF, which suggests that these biomarkers can be used as tools for disease progression and detection of malignant transformation. Shaikh et al. used attenuated total reflection–Fourier transform infrared spectroscopy (ATR-FTIR) combined with salivary total protein measurement to distinguish between OSF patients and healthy controls [86]. Analysis by Singh et al. showed that people with blood type A were more likely to develop oral cancer and OPMD, while people with blood type O were less likely to develop oral cancer [87]. Therefore, blood typing could be used to identify susceptible people for early disease prevention and surveillance. The clinical analysis of OSF patients by Bale et al. concluded that the serum MDA level increased with the increase in clinical stage, while the serum SOD level decreased with the increase in clinical stage [81]. The above two measurements can be used to evaluate the level of oxidative damage caused by this illness, and also could serve as a diagnostic method to prevent malignant transformation of OSF [81]. Other known markers of fibrosis include TGF-β [88], IL-6 [89], transglutaminase 2 (TGM2) [74], α-SMA [75], collagen type I and collagen type III, etc. Kamala et al. showed that the expression of the Ki-67 antigen increased from normal oral mucosa to OSF and OSCC. In addition, the expression of Ki-67 increased with the aggravation of dysplasia [77]. The results from Nag et al. said that the expression of p63 and E-cadherin and the number of mitotic figures could be used as molecular markers to evaluate the malignant potential of OSF [76]. Of course, not only these, but also p53 [90], cyclin D1, β-catenin, Rb protein, B-cell lymphoma-2 (Bcl-2), the Bcl-2 associated X protein (Bax), the cellular mesenchymal epithelial transition factor (c-Met) and PTEN are diagnostic markers that can be used to predict the malignant transition of OSF [91]. Monteiro et al. also used the combined biomarker to predict high-risk OSF, and proposed a combined expression level formula: 0.688 × Ki-67 + 0.888 × p16 [72]. This provides a new idea for the application of OSF biomarkers. Of course, both the current biomarkers and formulas, and the additional indicators that will emerge later, need to be tested and verified with a large number of samples before they can be used in clinical practice. OSF is an irreversible disease, even if the pathogenic factors are removed in the latter stage, so early treatment will have a better prognosis and prevent malignant transformation as much as possible. The incidence of OSF is closely related to chewing BQ. Health education should be strengthened to enhance people’s understanding of the potential harm from chewing BQ. Patients with clinical symptoms should be treated in stomatological hospitals as soon as possible. Quit the chewing BQ habit, quit smoking, quit alcohol and avoid spicy food stimulation. The therapeutic principles of OSF mainly include anti-inflammatory, anti-fibrosis, improvement of ischemic state and anti-oxidation. Commonly used OSF therapeutic drugs mainly include the following categories: (1) Glucocorticoids: glucocorticoids can inhibit the production of inflammatory factors and promote the apoptosis of inflammatory cells, thereby playing the role of anti-inflammatory and inhibiting the process of fibrosis [92,93]; (2) Antifibrotic drugs and proteolytic enzymes: exogenous antifibrotic factors and proteolytic enzymes can reverse the process of OSF fibrosis [93]. In clinical practice, hyaluronidase is often used in combination with hormones, and clinical studies have shown that dexamethasone combined with hyaluronidase is the clinical efficacy of local injection into lesions [93]; (3) Peripheral vascular dilators: improve the microcirculation and hemorheology in the lesion area to improve clinical efficacy and relieve the symptoms of patients with OSF [94,95]. Clinical studies have shown that treatment with oral isoxsuprine and combined injections of dexamethasone and hyaluronidase are more effective in relieving OSF symptoms than treatment alone [95]; (4) Antioxidants and nutritional elements: in the treatment of OSF, the use of antioxidants and nutritional elements can reduce the damage to macromolecules caused by reactive oxygen species, thereby slowing down the progression of OSF [96,97]. With the help of oral physiotherapy exercise, tissue elasticity and mouth opening can be increased [98]. There are researchers who verify the effect of mouth opening training, the control group using salvia miltiorrhiza combined with triamcinolone local injection treatment and the experimental group, on the basis of the control group, combined mouth opening training for 2 years. The oral opening of the two groups at the end of local injection treatment, 1-year and 2 years after treatment, was compared. The oral opening of the experimental group was significantly higher than that of the control group, and the effective rate of the experimental group was 97.1%, which was significantly higher than that of the control group at the return visit 2 years later [99]. The first choice is surgical treatment for advanced patients, who have limited mouth opening movement due to heavy fibrous bands in the mucosa. The operation included excision of the fibrous band and insertion of different flaps, such as a palatal flap, tongue flap, nasolabial flap, platysma myocutaneous flap, etc. [92]. Platysma musculocutaneous flaps have good flexibility and the same texture as oral mucosa. However, their high technical sensitivity and postoperative complications, such as flap necrosis, flap cracking, skin paddle loss and donor area lesions, are more common [100]. A split skin graft is widely used as a graft material, but postoperative wound contracture and scarring can lead to recurrence of submucosal fibrosis [101]. The buccal fat pad is easy to obtain and can be used to cover the defective area after the removal of the fibrous band. However, the tissue size of the flap is limited, which may not be enough to cover the defect completely, and there may be mild secondary fibrosis in the later stage [102]. The blood supply of the nasolabial flap was sufficient and the defect adaptability was good, but scar and hair growth outside the mouth could be observed [102]. Different skin flaps should be selected according to the specific conditions of the patients with the removal of the fibrous bands. Clinical combined reconstruction has been used to repair the defect, such as the joint reconstruction of the buccal fat pad and nasolabial flap [101]. Of course, postoperative mouth opening training with drug therapy is also needed to improve the prognosis. In addition to the above conventional treatment methods, in recent years, some scholars have adopted new treatment methods for the clinical manifestations and pathogenesis of OSF, such as hyperbaric oxygen therapy [103], laser therapy [104] and new functions of some natural compounds. Hyperbaric oxygen can increase blood oxygen content, improve local ischemia and hypoxia, promote neovascularization and collateral circulation in the affected area [103]. Existing clinical studies have shown that laser therapy can alleviate the difficulty in opening the mouth, the burning sensation and even increase cheek flexibility in patients with OSF [104]. Arctigenin is a lignan extracted from Arctium lappa, which has a lot of pharmacological effects, including antifibrotic effects [12]. The results of Lin et al. suggest that arctigenin could inhibit arecoline stimulated TGF-β/Smad2 signaling and reduce fBMFs activity [12]. In addition, burdockaglyin has been proven to reduce the expression of LINC00974, which could activate the TGF-β/Smad signaling pathway to promote the occurrence of oral fibrogenesis [12]. At present, previous studies have shown that salvia miltiorrhiza can improve blood supply, inhibit collagen accumulation, the proliferation of fibroblasts and EMT, and has therapeutic effects on OSF [105]. Black turmeric is commonly known Kali Haldi. Moreover, Bohra et al. found that Kali Haldi and Aloe vera have a synergistic effect on antioxidant radicals in patients with OSF, and they are even better at correcting the burning sensation than intradermal hydrocortisone, hyaluronidase and antioxidants [106]. The results by Lee et al. showed that glabridin inhibited the myofibroblast features of fBMFs through the TGF-B/Smad2 signaling pathway and that it also prevented arecoline increased fBMFs activity [80]. So, it can be used as a natural antifibrotic compound to treat OSF. Hsieh et al. found that EGCG inhibited arecoline-induced activation of TGF-β1, mitochondrial ROS and subsequent synthesis of CTGF and Egr-1 in BMFs in a dose-dependent manner [23,107]. Studies by Nerkar Rajbhoj et al. and Al-Maweri et al. have shown that curcumin is effective in improving OSF symptoms without any side effects [98,108]. Several studies have shown that the administration of Aloe vera to patients with OSF can reduce the clinical symptoms of patients and its clinical efficacy is just like that of intra-lesion injection of hydrocortisone and hyaluronidase with antioxidant supplementation [98,106,109,110]. Honokiol is a polyphenolic component derived from Magnolia officinalis. Chen et al. showed that the expression of the TGF-β/Smad2 pathway was downregulated and the expression of α-SMA and type I collagen was downregulated when treated with honokiol, and honokiol could inhibit arecoline-induced fBMFS activity [111,112]. It could prevent the oral squamous cell epithelium from turning into cancer [113] and is a promising compound. The treatment methods and principles of OSF are listed in Table 1. The above studies on the mechanism of OSF and malignant transformation into OSCC make the key molecules and abnormal RNAs clear, which are of great significance for the occurrence, development, detection, diagnosis, monitoring and prognosis of the disease. The important molecules and processes involved in OSF pathogenesis and malignant transformation to OSCC are shown in Figure 3. The roles of miRNAs and the targets mentioned above for OSF and OSCC are listed in Table 2. The pathways and roles of the mentioned lncRNAs and circRNAs in OSF and OSCC are listed in Table 3. Therefore, targeted blocking of these key molecules is the trend and key for disease prevention and treatment in the future. The application of natural compounds has also shown its therapeutic potential, so it is necessary to conduct further research on natural compounds in the hope that they will become first-line drugs for OSF treatment in the future.

PMC10003558

Yaguang Zhang,Qin Zhang,Yang Zhang,Junhong Han

The Role of Histone Modification in DNA Replication-Coupled Nucleosome Assembly and Cancer

03-03-2023

histone modification,nucleosome assembly,DNA damage repair,cancer,epigenetics

Histone modification regulates replication-coupled nucleosome assembly, DNA damage repair, and gene transcription. Changes or mutations in factors involved in nucleosome assembly are closely related to the development and pathogenesis of cancer and other human diseases and are essential for maintaining genomic stability and epigenetic information transmission. In this review, we discuss the role of different types of histone posttranslational modifications in DNA replication-coupled nucleosome assembly and disease. In recent years, histone modification has been found to affect the deposition of newly synthesized histones and the repair of DNA damage, further affecting the assembly process of DNA replication-coupled nucleosomes. We summarize the role of histone modification in the nucleosome assembly process. At the same time, we review the mechanism of histone modification in cancer development and briefly describe the application of histone modification small molecule inhibitors in cancer therapy.

The Role of Histone Modification in DNA Replication-Coupled Nucleosome Assembly and Cancer Histone modification regulates replication-coupled nucleosome assembly, DNA damage repair, and gene transcription. Changes or mutations in factors involved in nucleosome assembly are closely related to the development and pathogenesis of cancer and other human diseases and are essential for maintaining genomic stability and epigenetic information transmission. In this review, we discuss the role of different types of histone posttranslational modifications in DNA replication-coupled nucleosome assembly and disease. In recent years, histone modification has been found to affect the deposition of newly synthesized histones and the repair of DNA damage, further affecting the assembly process of DNA replication-coupled nucleosomes. We summarize the role of histone modification in the nucleosome assembly process. At the same time, we review the mechanism of histone modification in cancer development and briefly describe the application of histone modification small molecule inhibitors in cancer therapy. The nucleosome is the basic unit of chromatin. It is an octamer composed of 4 core histones (H3, H4, H2A, H2B), including one H3-H4 tetramer and two H2A-H2B dimers, surrounded by 147 pairs of DNA base pairs [1]. The core histones form a spherical core particle, and their N-terminal tails are free from the core particle, which helps the modification occur. Posttranslational modifications (PTMs) are involved in a variety of cellular processes, such as transcription, DNA damage, apoptosis, and cell cycle regulation. Mass spectrometry is a powerful tool for finding and verifying histone PTMs [2]. In addition, new proteomic, genomic, and functional solid-phase chemistry tools have been developed to detect the function of PTMs [3,4]. Histone acetylation was first identified by biologist Vincent Allfrey in the 1960s and has been associated with mammalian gene activity [5,6]. Since then, histone PTMs have been discovered and well described. Currently, more than 10 different covalent modifications have been found on different amino acid residues of core histones, including acetylation of lysine, methylation of arginine and lysine, ubiquitination, ADP ribosylation, citrullination, phosphorylation of serine and tyrosine, isomerization of proline, sumoylation, carbonylation, and controversial biotinylation. Moreover, new modification sites and patterns are continuously discovered (Figure 1). Covalent modification can occur not only in the N-terminal tail protruding from the nucleosome but also in the core region. Different combinations of modification sites and forms can encode very rich information, which can be transmitted to daughter cells as epigenetic markers [7]. Therefore, the “histone code” hypothesis has been proposed by Allis et al. in the early 21st century and supposes that the functions derived from rich histone language are extremely extensive and fine, involving all aspects of cell fate determination, such as replication of genetic code, cell adaptation to internal and external environmental changes, regulation of gene expression, and others. Interpreting these messages and elucidating their functions is the main content of epigenetics [8,9,10]. Common sites of histone acetylation are K5, K9, and K13 on histone H2A [11,12]; K5, K12, K15, and K20 on H2B [13]; K9, K14, K18, K23, K27, K56, and K79 on H3 [11]; and K5, K8, K12, K16, and K91 on H4 [14]. The various acetylation sites of histones correspond to different functions. For example, H3K56 acetylation is involved in the regulation of nucleosome assembly, while H4K16 acetylation is involved in the regulation of nucleosome-mediated chromatin compaction, activation or inhibition of gene transcription, DNA damage repair, and other processes. Methylation occurs mainly at K4, K9, K27, K36, and K79 on histone H3 and at K20 of H4 [12]. Most histones are monoubiquitinated rather than polyubiquitinated, which occurs mainly on H2A and H2B [15,16]. A key feature of chromatin assembly during DNA replication is that it occurs immediately after DNA synthesis, with the first deposited nucleosome detected approximately 250 bp behind the replication fork. Histone deposition and chromatin assembly are important processes throughout S phase DNA synthesis and are indispensable for gene expression [17]. Histone chaperones, including Nap1, Vps75, NASP, FACT, CAF-1, Rtt106, Spt6, Asf1, and DAXX, play a central role in both histone deposition and chromatin assembly and are therefore involved in the regulation of cellular processes [18]. Nucleosomes can block DNA access during the S phase of the cell cycle [19]. Nucleosomes located in front of replication forks are depolymerized so that DNA replication elements can bind to DNA. During DNA replication, parental histones undergo depolymerization before replication forks, and newly synthesized histones are deposited on DNA with the help of histone chaperones to reform nucleosomes and assemble chromatin [20]. Newly synthesized and preexisting histones are randomly and sequentially deposited to assemble “new” nucleosomes; the H3-H4 tetramer and H2A-H2B dimers are deposited on DNA in a chaperone-dependent manner, and this nucleosome assembly is called replication-coupled nucleosome assembly (RCNA) (Figure 2A) [21]. The RCNA process is important for both epigenetic information transmission and genome integrity [22]. In some DNA damage reactions, parental histones must be removed. The removal of histones at DNA damage sites is considered to have many similarities with the RCNA process. In addition, nucleosome assembly during gene transcription and histone exchange can occur throughout the cell cycle and is named replication-independent nucleosome assembly (RINA) (Figure 2B) [21]. Packaging DNA into the chromatin structure is an important step in DNA replication, which not only ensures the high compaction of DNA but also the correct transmission of epigenetic information to daughter cells [23,24,25,26]. The replication of DNA to the correct packaging of chromatin structure depends on the precise modification, transportation, and assembly of newly synthesized histones. In addition to recycling parental histones, chromatin assembly on replication forks requires the deposition of newly synthesized histones. The expression of canonical histones is activated in the late G1/early S phase to ensure the rapid supply of histones during replication and is inhibited in G1, G2, and early mitosis to prevent the adverse consequences of excess histones on DNA metabolism [27,28]. Newly synthesized histones travel with molecular chaperones from the cytoplasm to the nucleus and are modified after translation to facilitate chromatin deposition. In particular, acetylation of the amino terminus tail of H3 and H4 plays an important role in chromatin assembly [29]. The histone acetyltransferase Hat1 can form the Hat1-Hat2 complex with the histone partner Hat2 to acetylate lysine 5 (H4K5) and 12 (H4K12) of histone H4 [30]. In budding yeast, lysine 9 and 27 of histone H3 are acetylated by the acetyltransferases Rtt109 and Gcn5 [31,32], and the acetylation of H4K91 by Hat1 and H3K56 by Rtt109 are both important in replication-coupled chromatin assembly [33,34,35]. H3 can also be acetylated at lysine 14 and 18 in some mammals [36]. In yeast, most newly synthesized histones H3 are acetylated at lysine 56, which is also a marker of newly synthesized histones. However, the acetylation of H3K56 in humans is less than 1.5%, and SETDB1-mediated monomethylation of H3.1K9 marks newly synthesized histones [33]. The histone chaperone Asf1 binds to newly synthesized H3-H4 dimers and presents them to Rtt109 for acetylation [37]. H3K56 acetylation increases the binding affinity of dimer H3-H4 for histone deposition factors CAF-1 and Rtt106, as well as the binding of CAF-1 to chromatin [38]. The Rtt101Mms1/Mms22 complex can facilitate this process by preferentially binding and ubiquitinating H3K56ac at lysine 121/122/125, which weakens the interaction of Asf1-H3-H4 and promotes the transfer of H3-H4 to downstream chromatin assembly factors, such as Rtt106 (Figure 3) [39]. Notably, H3K56 acetylation is not essential, in part because GCN5-mediated acetylation of the amino terminus of H3 also increases the binding affinity of the dimer H3-H4 for CAF-1 and Rtt106 [32]. CAF-1 is a highly conserved histone chaperone that plays a role in the deposition of newly synthesized histones through the interaction between its subunits and H3-H4 dimers [40,41,42]. CAF-1 is recruited to the replication fork through direct interaction with PCNA [43,44], and promotes nucleosome assembly through interaction with Asf1. The CAF-1-Asf1 histone deposition complex binds to a single H3-H4 dimer, and CAF-1’s ability to form homodimers may provide the second H3-H4 dimer required for the deposition of (H3-H4)2 tetramer [45]. In addition, in vitro interaction analysis has shown that CAF-1 can also bind (H3-H4)2 tetramers in monomer form [46]. Interestingly, the binding of H3-H4 to Asf1 stimulated the binding of Asf1 and CAF-1, while the binding of H3-H4 to CAF-1 was mutually exclusive with Asf1, indicating that the H3-H4 transfer process from Asf1 to DNA occurs through CAF-1 [45]. In yeast, the histone chaperone Rtt106 interacts with CAF-1. Rtt106 can also form homodimers, which interact with the K56 region of histone H3 via the double pleckstrin homology domain and bind directly to the newly synthesized (H3-H4)2 tetramer. After the acetylation of H3K56, the affinity between Rtt106 and H3-H4 was enhanced [47,48]. The roles of CAF-1 and Rtt106 in new histone deposition are redundant, and only the simultaneous deletion of both complexes will affect histone deposition. Additionally, FACT participates in the deposition of new histones by forming complexes with CAF-1 or Rtt106 and H3K56Ac-H4 (but not Asf1) [22,49]. Replication protein A complex (RPA) can regulate DNA metabolism [50], including three subunits of Rfa1, Rfa2, and Rfa3 in yeast, which bind single-stranded DNA to replication forks and mediate replication movement. The initial replication-coupled nucleosome assembly begins with the deposition of histones H3-H4 onto the replicated DNA, followed by the rapid incorporation of histones H2A-H2B. RPA can directly bind the unmodified H3-H4 histone complex. In vitro experiments have shown that RPA can promote the formation of single-stranded DNA-(H3-H4) complex and can quickly connect to double-stranded DNA. In this process, a series of H3-H4 chaperones are recruited (RPA subunit Rfa2 can bind the three histone chaperones CAF-1, FACT, and Rtt106) to assist in the assembly of new nucleosomes [51]. The above research shows that the main function of RPA is to provide a “platform” for the incorporation of histones into the replication fork through the coupled nucleosome accompanied by DNA replication. It provides a good model for explaining how epigenetic information is assembled and transmitted during chromatin replication. In humans, two subtypes of NASP have been identified: sNASP (somatic NASP) and tNASP (testicular NASP) [52]. HSC70 binds to the new histone H3.1, promoting its folding. The newly synthesized histone H3.1 is then presented to HSP90, which, together with the helper chaperone tNASP, promotes the formation of the H3.1-H4 dimer [44]. sNASP is a H3-H4 histone chaperone in cytoplasmic histone processing. sNASP binds the H3.1-H4 heterodimer and presents it to RbAp46 [53]. RbAp46 recruits Hat1 and catalyzes the acetylation of H4K5/12. The histone chaperone Asf1 binds to H3-H4K5/12ac and promotes new histone nuclear import with Importin-4 [54]. In the nucleus, p300/CBP binds and catalyzes acetylation of H3K56, which can further promote Cul4A/DDB1 to catalyze ubiquitination of H3K122 [55]. Acetylation and ubiquitination enable H3.1-H4 to dissociate from Asf1 and be presented to the histone chaperone CAF-1, which is eventually deposited on replicated DNA and involved in the assembly of replication-coupled nucleosomes (Figure 4). DNA replication stress poses a threat to the transmission of genetic information [56]. For example, replication stress may contribute to the development of tumors by promoting changes in histone-related epigenetic marker patterns. When the replication fork encounters obstacles, it inevitably enters a stagnant state, which is prone to collapse, leading to DNA damage or genomic instability [57]. Therefore, these obstacles must be repaired or bypassed to restore normal DNA replication [58]. This replication fork damage bypass occurs through different mechanisms, either by break-induced replication using the DNA polymerase Polδ subunit, yeast Pol32 or human POLD3, or by switching to a sister chromatid template to bypass the damage site [59,60,61]. These mechanisms all occur in the context of nucleosome assembly; thus, histone modification plays an important role in DNA damage repair (DDR) and is one of the criteria for selecting damage repair pathways. After DNA damage, the damaged site is marked by histone modification to regulate the signaling pathway in a timely manner and provide support for the assembly of effector proteins [62]. During DNA replication, the MCM2-MCM7 complex is loaded at replication initiation under the regulation of the origin recognition complex (ORC), Cdc6, and Cdt1 to form a prereplication complex (pre-RC). Then, the MCM complex is phosphorylated by DDK and CDK. Cdc45 is recruited to the MCM in a SLD3-dependent manner, and the GINS complex is recruited to the MCM complex by phosphorylated Sld2 and Sld3 together with Dbp11 to assemble the CMG (CDC45-MCM-Gins) complex [63,64]. Double-stranded DNA unwinds into single-stranded DNA (ssDNA), and RPA rapidly binds to the newly formed ssDNA, protecting it from damage and generating secondary structures. Subsequently, DNA polymerase α (Polα) initiates DNA synthesis, DNA polymerase ε (Polε) continuously synthesizes the leading strand, and DNA polymerase δ (Polδ) synthesizes the legging strand [65]. Ctf4, a yeast homolog of human AND1, links CMG helicase to Polα polymerase to form trimers involved in DNA replication [66]. The human MMS22L-TONSL complex is located in the replication fork and increases enrichment when DNA damage occurs [67]. It has a similar function to the Rtt101/Mms1/Mms22 complex in yeast. It has been found that the absence of the MMS22L-TONSL complex affects replication fork stability in the context of CPT stimulation [68]. The proportion of H3K56ac modification in human cells is less than 1.5% of the total H3 [36], and this proportion varies little throughout the cell cycle [69]. However, the unmethylated H3-H4K20 histone is methylated at the late G2/M stage [70]. In particular, MMS22L-TONSL is able to bind not only to newly synthesized histones as part of a predeposited complex with MCM2 and ASF1, but also to H4K20me0 on nascent chromatin. MMS22L and TONSL were necessary for the recruitment and homologous recombination of RAD51 [70,71] (Figure 5). Here, we describe the role of a typical histone modification in DDR. H3K56ac is one of the earliest core modifications described in yeast [72] and is deacetylated by the deacetylases Hst3 and Hst4 at the end of S/G2. During DNA damage, Hst3/Hst4 is downregulated in a checkpoint-dependent manner [73], suggesting that H3K56ac modification is crucial in the DNA damage reaction. In fact, yeast cells with defective H3K56 acetylation are highly sensitive to DNA damage agents such as MMS and CPT [74]. Genetic analysis showed that H3K56ac was upstream of the Rtt101/Mms1/Mms22 ubiquitin ligase complex signaling pathway, which is resistant to genotoxic agents [75,76]. Direct evidence for the involvement of H3K56ac in DDR is that fully acetylated H3K56 in vitro increases exposure to DNA sites [77]. This function is unlikely to be related to the role of chromatin assembly in replication fork stability, as cells lacking CAF-1 and Rtt106 are much less sensitive to MMS and CPT than H3K56 acetylated mutants [78]. Members of the Asf1/Rtt109/H3K56ac/Rtt101Mms1/Mms22 pathway are required in the process of MMS and CPT-induced DNA damage [79,80]. Deletion mutations in this pathway can disrupt checkpoint recovery after drug therapy, demonstrating that this pathway plays an important role in the mechanism of DDR template conversion. H3K56ac deposition appears to promote the ubiquitination of some unknown substrate to uncouple the replicating helicase with the polymerase as a prerequisite for blocking the recombinant bypass of the lesion (Figure 6). Consistent with this model, the interaction of Rtt101Mms1/Mms22 with Ctf4 via the amino terminal tail of Mms22 is necessary for the function of H3K56ac in tolerating replication stress. Ubiquitination of unknown factors is used for Mrc1 and Ctf4 to uncouple the helicase CMG with the polymerase and facilitate recombination repair bypass [81]. Histone chaperone FACT is ubiquitinated by Rtt101 in a manner independent of Mms1/Mms22 [82]. Histones are also potential targets for ubiquitination. Studies have found that human histones are ubiquitinated by Cul4A/DDB1 in UV-induced photodimers, and this modification weakens their interaction with DNA and promotes the recruitment of repair proteins [83,84]. FACT is mainly involved in the deposition of newly synthesized H3-H4. In yeast, Spt16 interacts with Pob3 to form FACT, which is a conserved histone chaperone that plays an important role in DNA regulation [85,86]. Deletion of FACT disrupts the chromatin structure of the gene-coding region [87]. Studies have shown that Spt16 is involved in chromatin remodeling in DDR through ubiquitination of H2B [88,89,90]. At the same time, FACT can regulate DDR mediated by homologous recombination (HR) and base excision repair (BER), which proves that FACT is essential for damage repair [91]. Asf1 is critical for histone modification, histone deposition, and DNA replication. Its function in heterochromatin silencing was first identified in yeast [92] and later found as a replication-coupled assembly factor (RCAF) in Drosophila [93]. Asf1 can bind to the histone H3-H4 dimer with Mcm2-7. Histone H3-H4 was modified with specific parental labeling (H4K16ac and H3K9me3) under hydroxyurea treatment, leading to the accumulation of replication forks [94,95]. It is suggested that Mcm2-H3-H4-Asf1 is an intermediate in parental histone assembly and may promote DNA unwinding through its ability to transfer histones during chromatin assembly. CAF-1 promotes a Rad51-dependent replication fork bypass repair pathway [96]. The interaction between CAF-1 and the RecQ helicase Bloom in human cells is conserved, and both factors accumulate in the DNA replication center through replication stress and promote cell survival [97]. Histone modification is involved in chromatin remodeling [98], thereby altering chromatin status and gene expression [99] and is very important for gene regulation and genomic stability. Abnormal histone modification can cause abnormal chromatin status or genomic instability, which is often believed to be closely related to the occurrence and development of cancer [100,101,102]. Histone methylation, including monomethylation, demethylation, and trimethylation, is regulated by methyltransferases and demethylases and occurs mainly on lysine residues of H3 and H4 [103]. H3K4me1/2/3, H3K36me1/2/3, and H3K79me1/2/3 are transcriptionally active marks, while H3K9me1/2/3 and H3K27me3 are transcriptionally repressive marks [9]. Histone methylation disorder leads to the destruction of gene expression and genomic stability, and the abnormal modification of histone methylation in tumor cells can alter cancer development (Table 1). For example, decreased H3K27me3 and increased H3K4me3 activate the Wnt/β-catenin signaling pathway to promote colorectal cancer cell development [104]. Mutations in histone methylation sites (H3K27M, H3K27I, etc.) are present in approximately 30% of children with glioblastoma [105]. NSD2 maintains genome integrity and reduces disease incidence by methylating H3K36 and DOT1-mediated H3K79 methylation in response to UV radiation-induced DDR [106]. Under normal physiological conditions, the number of H3K9me3 increases dramatically over time at the site of DNA double-strand break damage and participates in DDR. In contrast, in the environment of abnormal tumor cell metabolism, abnormal H3K9me3 inhibits DNA repair [107]. Histone methylation has been used as a promising target for cancer therapy. A large number of methyltransferase inhibitors have been developed and entered clinical trials, mainly against H3K27 and H3K79 methyltransferase, and arginine methyltransferase [108]. EZH2, a methyltransferase of H3K27, is involved in tumor occurrence, metabolism, drug resistance, and immune regulation [109]. Therefore, targeting EZH2 for cancer therapy has become a hot research topic. Strategies for EZH2 inhibitors include targeting methyltransferase activity (GSK126, GSK343, EPZ011989, et al.), breaking PRC2’s structure (SAH-EZH2, Astemizole, MAK683, et al.), or triggering EZH2 degradation (GNA022, ANCR, FBW7, et al.) [109]. For example, EZH2 inhibitor GSK343 can decrease self-renewal and increase sensitivity to chemotherapy in colorectal cancer cells [110]. Some studies have also shown that EZH2 has an antitumor effect [111,112]. For example, GSK126 can increase the number of myeloid-derived suppressor cells (MDSC) and decrease the number of IFNγ+CD8+ T cells, leading to the failure of antitumor therapy. Interestingly, when combined with neutralizing antibodies against the myeloid differentiation antigen GR-1, MDSC-mediated immunosuppression was mitigated and increased the therapeutic effect of GSK126 [113]. Developing a multi-drug combination therapy strategy may address the limitations of single drug therapy. These studies indicate that histone methylation modification plays an important role in the development and prevention of cancer. Acetylation is one of the main modifications of histones and is strictly regulated by histone acetyltransferases (HAT) and histone deacetylases (HDAC) to maintain the normal acetylation state, thus controlling the initiation and shutdown of gene transcription. HATs transfer the acetyl group from acetyl-CoA to the amino terminal of the specific lysine residue of the histone, generating an acetate bond. Acetylation is a key epigenetic mechanism in gene regulation [192] and regulates chromatin structure and function through transcriptional capacity [193,194]. Abnormal histone acetylation can disrupt cell homeostasis and affect cell metabolism and gene regulation [195]. Cumulative evidence suggests that abnormal expression of histone modification enzymes is closely related to tumor development (Table 2). The current antitumor treatment of histone acetylation as a therapeutic target is expected to be achieved through the development of HAT and HDAC inhibitors. The first HDAC inhibitor approved for clinical treatment was suberoylanilide hydroxamic acid (SAHA), and more drugs are being developed, such as YF479, which has good antitumor activity and can inhibit the recurrence and metastasis of breast cancer [196,197]. Thus, histone acetylation modification plays a significant role in the occurrence and development of cancer. Ubiquitin (Ub) exists widely in eukaryotes, and ubiquitination is also one of the main posttranscriptional modifications. Posttranslational modification of proteins is a reversible, dynamic process. Histone ubiquitination is dynamically regulated by ubiquitination enzymes and deubiquitination enzymes and can participate in most intracellular processes, including protein degradation, intracellular signaling, endocytosis, and DNA damage reactions [216,217,218]. Histone ubiquitination is the core event of DDR, and DNA damage requires a large number of ubiquitin molecules, which are crucial for preventing abnormal DNA repair and maintaining genomic stability [219]. Histone H3 ubiquitination enzymes mainly include NEDD4 and CUL4A. NEDD4 ubiquitinates histone H3 on lysine 23/36/37 residues in a glucose-dependent manner, specifically recruiting the histone acetyltransferase GCN5 for subsequent H3 acetylation. This mechanism can regulate gene transcription and tumorigenesis in cancer [220]. The RNA demethylase ALKBH5 and the USP22/RNF40 axis regulate histone H2AK119 monoubiquitination to regulate the expression of key genes involved in DNA repair, thus playing a crucial role in the development of osteosarcoma [221]. Rad6 and Bre1 form a well-characterized H2B monoubiquitin enzyme to degrade histones in DDR reactions [222]. USP11 can deubiquitinate H2AK119 and H2BK120 to separate ubiquitin molecules from histones and maintain genomic stability [223]. It is worth noting that the existing studies on histone ubiquitination mainly focus on histone H2A/H2B, and the discovery of histone H3 ubiquitination and the study of its mechanism are also gradually deepening. However, the regulation of histone H3 deubiquitination remains unclear. Histone phosphorylation occurs on serine and tyrosine residues of histones and has been shown to be involved in many cellular life activities, including DNA damage repair, gene transcription, chromatin maintenance and aging, through histone methylation [224,225]. For example, PRK-mediated H3T11 phosphorylation (H3T11ph) hastens the removal of repressive histone H3 lysine 9 (H3K9) methylation by JMJD2C, demonstrating a unique mechanism by which histone phosphorylation activates gene expression. Importantly, the level of H3T11ph correlates with prostate cancer malignancy, suggesting that inhibition of H3T11ph may be a promising therapeutic target [226]. Phosphorylated H3.3 (H3.3S31ph) enhances the binding of the methyltransferase SETD2 to histone proteins, thus promoting gene transcription and highlighting the causal role of H3.3 phosphorylation in tumor metastasis [227]. H3.3S31ph is also involved in the regulation of heterochromatin regions and reduces the demethylation of H3K9me3 to maintain chromatin integrity by downregulating the activity of KDM4B [228]. Pyk1-catalyzed H3T11ph can weaken the binding of Dot1 to chromatin and reduce Dot1-mediated H3K79me3, leading to suppression of autophagy-related gene transcription and uncovering histone modification crosstalk in response to cell metabolism [229]. Additionally, a recent study showed that phosphorylation of histone H3 at serine 10 inhibits methylation of histone H3 at adjacent arginine 8, providing a framework for understanding the effects of phosphoserine on the methylation of adjacent amino acid residues and arginine [230]. In order to function, histone phosphorylation may antagonize its methylation. Nucleosome assembly is a complex and highly regulated process in eukaryotes. Nucleosome assembly requires precise regulation by histone-modifying enzymes, histone chaperones, and histone modifications. In recent years, yeast-based experiments have provided new insights into how to regulate the assembly of novel H3-H4 through histone modification and molecular chaperones. Additionally, nucleosome reassembly maintains replication fork stability, but the mechanism remains elusive. Similarly, histone epigenetic modifications affect the complexity and correlation of newly assembled chromatin structures during DDR [231]. In fact, some aspects of the replication-dependent chromatin assembly process are not discussed here because there is still no evidence that they are associated with the progression and stability of replication forks. Finally, it is worth mentioning that although we focus on how chromatin assembly regulates DNA replication, the effects are mutual. For example, replication stress resulting from replication disorders promotes heterochromatin formation. The combination of genetic and biochemical approaches with genome-wide analysis may help reveal the dynamics of chromosomal remodeling in these different scenarios and understand the molecular mechanism of how defects in replication-coupled chromatin assembly lead to genetic diseases, cancer, and aging. Epigenetic modification of histones is closely related to disease pathogenesis and can be a molecular signature in cancer [232]. The diversity of histone modifications provides new molecular targets for the treatment of various diseases [233]. It is worth noting that many drugs targeting histone modifications have been developed and used in clinical research in the past decade, which is sufficient to show that histone modification plays a very important role in disease treatment. Therefore, understanding the basic mechanisms controlling epigenetic modification changes will bring new breakthroughs and advances in drug development and treatment of cancer and other human diseases [234]. The development of epigenetic drugs creates a new avenue for the treatment of diseases, which is a huge leap forward in the extension of basic scientific research to clinical drug development. Meanwhile, numerous studies have found that histone modification tandem is closely related to the development and pathogenesis of various diseases, indicating a new direction for the research and development of histone modification inhibitors.

PMC10003559

Jinhui Wang,Haojie Feng,Xiaoke Jia,Shengnan Ma,Chao Ma,Yue Wang,Siyang Pan,Qingshan Chen,Dawei Xin,Chunyan Liu

Identifications of QTLs and Candidate Genes Associated with Pseudomonas syringae Responses in Cultivated Soybean (Glycine max) and Wild Soybean (Glycine soja)

27-02-2023

soybean,bacterial spot disease,Pseudomonas syringae,wild soybean,QTL

Soybeans (Glycine max) are a key food crop, serving as a valuable source of both oil and plant-derived protein. Pseudomonas syringae pv. glycinea (Psg) is among the most aggressive and prevalent pathogens affecting soybean production, causing a form of bacterial spot disease that impacts soybean leaves and thereby reduces crop yields. In this study, 310 natural soybean varieties were screened for Psg resistance and susceptibility. The identified susceptible and resistant varieties were then used for linkage mapping, BSA-seq, and whole genome sequencing (WGS) analyses aimed at identifying key QTLs associated with Psg responses. Candidate Psg-related genes were further confirmed through WGS and qPCR analyses. Candidate gene haplotype analyses were used to explore the associations between haplotypes and soybean Psg resistance. In addition, landrace and wild soybean plants were found to exhibit a higher degree of Psg resistance as compared to cultivated soybean varieties. In total, 10 QTLs were identified using chromosome segment substitution lines derived from Suinong14 (cultivated soybean) and ZYD00006 (wild soybean). Glyma.10g230200 was found to be induced in response to Psg, with the Glyma.10g230200 haplotype corresponding to soybean disease resistance. The QTLs identified herein can be leveraged to guide the marker-assisted breeding of soybean cultivars that exhibit partial resistance to Psg. Moreover, further functional and molecular studies of Glyma.10g230200 have the potential to offer insight into the mechanistic basis for soybean Psg resistance.

Identifications of QTLs and Candidate Genes Associated with Pseudomonas syringae Responses in Cultivated Soybean (Glycine max) and Wild Soybean (Glycine soja) Soybeans (Glycine max) are a key food crop, serving as a valuable source of both oil and plant-derived protein. Pseudomonas syringae pv. glycinea (Psg) is among the most aggressive and prevalent pathogens affecting soybean production, causing a form of bacterial spot disease that impacts soybean leaves and thereby reduces crop yields. In this study, 310 natural soybean varieties were screened for Psg resistance and susceptibility. The identified susceptible and resistant varieties were then used for linkage mapping, BSA-seq, and whole genome sequencing (WGS) analyses aimed at identifying key QTLs associated with Psg responses. Candidate Psg-related genes were further confirmed through WGS and qPCR analyses. Candidate gene haplotype analyses were used to explore the associations between haplotypes and soybean Psg resistance. In addition, landrace and wild soybean plants were found to exhibit a higher degree of Psg resistance as compared to cultivated soybean varieties. In total, 10 QTLs were identified using chromosome segment substitution lines derived from Suinong14 (cultivated soybean) and ZYD00006 (wild soybean). Glyma.10g230200 was found to be induced in response to Psg, with the Glyma.10g230200 haplotype corresponding to soybean disease resistance. The QTLs identified herein can be leveraged to guide the marker-assisted breeding of soybean cultivars that exhibit partial resistance to Psg. Moreover, further functional and molecular studies of Glyma.10g230200 have the potential to offer insight into the mechanistic basis for soybean Psg resistance. Soybeans (Glycine max) are an important agricultural crop, serving as an important source of oil and high-quality plant protein [1,2,3]. In China, Heilongjiang is the site of over 40% of domestic soybean production [4,5]. The yield and quality of soybean crops have been seriously impacted by a series of diseases in recent years, with bacterial spot disease (BSD) caused by Pseudomonas syringae pv. glycinea (Psg) being one important cause of soybean yield losses [6,7,8]. Psg can overwinter and infect soybean plants even under low-temperature and high-humidity conditions [9]. While it can infect the pods, stems, and petioles of soybean plants, this pathogen primarily causes damage by infecting the leaves [6]. During the early stages of infection, polygonal, transparent, water-stained spots develop, with light yellow spots developing as the disease progresses [7]. These spots are often brown in the middle and are surrounded by a chlorotic halo, with affected leaves readily falling off of infected plants [10,11,12]. BSD outbreaks are primarily observed in Northeast China and in the Huang-Huai-Hai region, resulting in yield losses for soybeans grown under both field conditions and in greenhouses [4,5,13]. Efforts to breed Psg-resistant soybeans present a sustainable and effective approach to reducing BSD-related damage to soybean plants [14]. Psg resistance is a complex, quantitative trait under the control of multiple genes, and as such, marker-assisted selection can be used to help breed resistant cultivars via the integration of the known resistance locus [14,15,16,17]. However, resistance-related loci and genes identified to date are highly diverse and are dispersed among different germplasms, complicating efforts to develop Psg-resistant soybean varieties [14]. There is thus a clear need to further characterized Psg resistance and associated QTLs and genes in available soybean germplasm resources so as to guide future breeding and genome editing. Multiple Psg resistance-related genes have been identified to date. For example, Rpg-1 is a CC-NB-LRR protein that can aid in plant resistance to Psg carrying the type III effector AvrB [18,19,20], while Rpg-2 is related to soybean resistance to Psg carrying the effector AvrA [20]. The GmEDS1a/b and GmPAD4 genes are required for Rpg2-mediated resistance to Psg, with the GmEDS1 protein being capable of directly interacting with pathogen-derived AvrA1 to control its function in Psg-infected soybean plants [21,22,23]. Rpg3 and Rpg4 are additionally associated with resistance against Psg expressing AvrB2 and AvrD1, respectively [24]. GmRIN4b can be phosphorylated by AvrB, affecting direct interactions between Rpg1 and GmRIN4b and thereby contributing to Psg resistance [25]. The resistance-related protein GmNDR1 can additionally directly interact with GmRIN4 [25]. While these studies clearly demonstrate that certain Psg resistance-related genes have been functionally characterized to date, these genes primarily focus on effector-related signaling pathways, and there have been few comprehensive analyses of soybean Psg-resistance genes to date [7]. QTL mapping can be used as an effective means of identifying key loci associated with particular agronomic traits and aiding in molecular marker-assisted selective breeding [26,27,28]. While there have been few Psg-related QTL studies on soybean to date, there have been several such studies in other crop species. For example, four QTLs associated with resistance to Pseudomonas syringe pv. tomato (Pst) have been identified on three chromosomes via a composite interval mapping approach [29]. High-density genetic maps and intensive phenotyping have further led to the identification of seven QTLs in kiwifruit, with the candidate genes within these QTLs having been further validated via RNA sequencing as being related to Pseudomonas syringae pv. Actinidiae (Psa) resistance [15]. In total, 76 QTLs related to Pseudomonas syringae pv. Phaseolicola (Psp) resistance have been identified in common beans, with 26 of these QTLs being positive for resistance-associated gene clusters encoding nucleotide-binding and leucine-rich repeat proteins and some known defense genes [30]. QTL-based mapping of BSD-resistant crops thus represents an effective means of characterizing resistance mechanisms, highlighting the value of employing a comparable approach to characterize QTLs associated with soybean Psg resistance. The present study was developed to identify BSD-related QTLs and genes. To that end, the BSD-susceptible cultivated variety Suinong14 and the BSD-resistant wild soybean variety ZYD00006 were used as parents to construct a population of chromosome segment substitution lines (CSSLs). These CSSLs were then used to identify QTLs associated with soybean Psg responses through a combination of QTL mapping, BSA-seq, and analyses of the insertion of wild soybean chromosomes. Candidate genes within the QTL interval were further screened and validated through qPCR and haplotype analyses. A total of 310 soybean germplasms from Northeast China, including 229 improved cultivars, 71 landraces, and 10 wild soybean varieties, were collected to evaluate the resistance of different soybean varieties’ responses to Psgneau001 (Table S1). Phenotypic analyses of the 310 soybean germplasms revealed that the wild accessions exhibited pronounced BSD resistance and were less affected by BSD as compared to the tested landraces and improved cultivars. In contrast, improved soybean cultivar accessions exhibited the highest degree of pathogenicity, with many exhibiting clear symptoms of disease, while tested landraces exhibited intermediate disease phenotypes between those of wild soybeans and improved cultivars (Figure 1A). One possible explanation for this observed resistance pattern may be that Psg has gradually developed the ability to overcome resistance in cultivated soybean plants through the natural variation and selection of industrial bactericide. Alternatively, artificial soybean domestication and agronomic trait improvement may have reduced the genetic diversity present among cultivated soybean varieties, leading to reduced Psgneau001 resistance owing to an overall narrowing of the genetic background. Importantly, these results suggest that wild soybean accessions represent a valuable source of abundant Psg resistance-related loci. Through an analysis of the resistance and susceptibility to Psg, the wild soybean could be used to improve the resistance of soybean cultivars to Psg, especially for the improvement of soybean varieties with relatively large spread areas. ZYD00006, one of the 10 wild soybean varieties included, was highly resistant to Psg (Figure 1B,C). Suinong14, as one of the 229 improved cultivars, is a variety with a large area of popularization in Northeast China, and a large number of new soybean varieties have come from Suinong14. While Suinong14 was highly susceptible to Psgneau001 (Figure 1B,C), it had great influence on yield and quality. In order to identify important QTLs and genes affecting resistance to Psg for improving the improved cultivar, a population of one hundred and seventy chromosome segment substitution lines (CSSLs) derived from cross and continuous backcross between Suinong14 (recurrent parent) and ZYD00006 (donor parent) were constructed to identify QTL loci response to Psgneau001. From 2006, when all 170 CSSLs were inoculated with Psgneau001, the population exhibited significant variability with respect to resistance, with CFU (colony forming unit) counts ranging from 60 to 1102 across the 170 CSSLs. The phenotypes of the parent were located within these intervals (Table 1). This suggests that the genetic differences between Suinong14 and ZYD00006 may contribute to the observed differences in response to Psgneau001. In total, 10 QTLs associated with disease resistance were detected using a WinQTL Cartographer via a composite interval mapping model (CIM) [27,28,29], including qbsd-02-1, qbsd-08-1, qbsd-08-2, qbsd-08-3, qbsd-09-1, qbsd-10-1, qbsd-10-2, qbsd-11-1, qbsd-11-2, and qbsd-16-1 located on chromosomes 2, 8, 9, 10, 11, and 16 (Table 2). By comparing the sequencing data of 30 resistant varieties and 30 susceptible varieties of CSSLs, Suinong14, and ZYD00006 to the reference genome, a total of 3,739,321 SNPs of response to Psgneau001 were used for correlation analysis by the Euclidean distance method. According to the rules of this method, we excluded SNP loci containing multiple alleles (those with more than one SNP within 5 bp) and SNP loci with identical genotypes between the two pools. Finally, we obtained 3,099,344 high-quality SNPs, including 630,809 mixed-pool genotype-consistent loci and 9168 multiple-allele loci. An SNP index association algorithm was then used for candidate gene selection, with the Euclidean distance method being used to fit the ΔSNP index. Three intervals correlated with disease resistance phenotypes were thereby located based on the results of a computer simulation test including Chr03 (chromosome location: 0.67–15.37 cM, physical location: 0.38–7.39 Mb), Chr10 (chromosome location: 0–5.90 cM, physical location: 0–3.15 Mb), and Chr10 (chromosome location: 84.26–92.52 cM, physical location: 43.91–48.05 Mb) (Figure 2) (Table 3). By comparing overlapping QTL intervals from QTL mapping and BSA-seq, a candidate QTL extending from 45.3 Mb to 48.2 Mb on Chromosome 10 was identified and selected for further analyses of BSD resistance-related genes. Over the multiple years of backcrossing, DNA fragments from ZYD00006 were integrated into the Suinong14 genome such that the genomes of individual members of the constructed CSSLs primarily consisted of the Suinong14 genome containing small segments of the ZYD00006 genome. Because of the difference in Psg-resistance between Suinong14 and ZYD00006, the genomic integration led to different CSSLs exhibiting a distinct genomic composition as compared to that of Suinong14, resulting in distinct Psg-resistance phenotypes in these individual CSSLs. Via the screening of 10 extremely resistant individuals from these CSSLs, certain ZYD00006 DNA fragments were inserted into the region of Chromosome 10 that overlapped with the candidate QTL identified above. Based on analyses of the overlapping inserted DNA fragments and BSD susceptibility phenotypes, a 301.9-kb locus (45.8–46.1 Mb) between the BARC-015925-02017 and Sat_038 markers was identified as potentially being associated with Psgneau001 infection (Figure 3), indicating that one or more genes within this region may interact with Psgneau001 to control associated disease resistance. Based on the Williams82 reference genome, 40 genes were located within the 301.9-kb genomic region of the candidate QTL. To explore which of these genes were associated with Psgneau001 resistance, SNP distributions for this 301.9-kb region of Suinong14 and ZYD00006 were assessed via whole-genome resequencing, revealing 1279 SNPs within this region of Chromosome 10 (Figure S1). Of these SNPs, 127 were located within the exonic regions of 30 genes, while 88 were located within the 3000-bp promoter regions upstream of 20 genes, including 20 shared genes (Table S2). A qPCR analysis was next used to assess the expression of these 30 genes potentially associated with Psgneau001 resistance in Suinong14 and ZYD00006 (Table S3). Of these 30 genes, 15 (Glyma.10G228500, 228600, 228800, 228900, 229200, 229300, 229600, 229800, 230000, 230400, 230700, 230800, 231000, 231100, and 231400) were not expressed at detectable levels. The expression patterns of 13 of the 15 remaining genes did not differ significantly when comparing with plants that were not inoculated with Psgneau001 (Figure 4). The Glyma.10g231500 Psgneau001 infection could increase its expression level both in Suinong14 and ZYD00006. Though Glyma.10g231500 might be involved in response to Psgneau001, we could not select it as the candidate gene, because this expression pattern was similar in Suinong14 and ZYD00006. However, Glyma.10g230200 was upregulated almost two-fold following Psgneau001 inoculation in ZYD00006, whereas its expression did not change following inoculation in Suinong14 (Figure 4). According to the SNP analysis of the Glyma.10g230200 in parents, there were two SNPs in the exons and 15 SNPs in the promoter region, and the SNPs in exons do not cause a change in amino acids (Table S2). It indicated that the SNPs in the promoter region could cause different expression patterns of Glyma.10g230200 during Psgneau001 infection. Thus, we selected Glyma.10g230200 as the candidate gene response to Psgneau001 in soybean. The 894-bp Glyma.10g230200 gene encodes a 297 amino acid WRKY family protein and targets the plant nucleus (Figure 5A). Phylogenetic analyses of six plants (including Glycine max, Oryza sativa, Zea mays, Setaria italica, Arabidopsis thaliana, and Medicago truncatula) revealed Glyma.10g230200 to be closely related to Medtr8g028565 and AT5G52830(Figure 5B). Via phenotypic analysis, the incidence of leaf disease was investigated at Grade 0 to 5: Grade 0: leaf lesions are more difficult to see, and CFU is 0–100; Grade 1: leaf lesions are not obvious, CFU is 100–200; Grade 2: the lesion area is enlarged with a chlorosis halo around it, CFU is 200–400; Grade 3: the lesion area has spread, CFU is 400–600; Grade 4: lesion area encompasses more than half of the leaf area, leaf is yellow, CFU is 600–800; Grade 5: leaves turn yellow and then wilt or fall, CFU exceeds 800. Grades 0 and 1 obviously indicate disease resistance, and Grades 4 and 5 obviously indicate susceptibility. According to the CFU and the grade of leaf disease, the resistant and sensitive cultivar were evaluated. Ten representative CSSLs, including five that were extremely resistant to BSD (CSSL-F647, CSSL-F604, CSSL-F684, CSSL-F531, and CSSL-F606) and five that were extremely susceptible (CSSL-F699, CSSL-F625, CSSL-F565, CSSL-553, and CSSL-F561) were used to analyze Glyma.10g230200 expression at 24 h post Psgneau001 inoculation. There were no significant differences in Glyma.10g230200 expression in response to Psg inoculation in the five extremely susceptible CSSLs, whereas it was significantly upregulated at 24 h post inoculation in the five extremely resistant CSSLs (Figure 5C,D) This confirmed that Glyma.10g230200 could be involved in resistance to Psgneau001. Given that different soybean germplasms exhibited distinct phenotypic responses to Psgneau001, in an effort to confirm whether resistance to this pathogen is associated with the Glyma.10g230200 gene, the resequencing and Psgneau001 resistance of the 310 soybean natural varieties used in this study were assessed to analyze Glyma.10g230200 haplotypes. In total, four Glyma.10g230200 haplotypes (Haps) were identified in these 310 soybean varieties, with the two Haps containing over 10 accessions being considered to be dominant. Only one SNP and one indel were identified within the promoter regions for Hap 1 (including Suinong14) and Hap 2 (including ZYD00006) (Figure 6A,B). To explore the relationship between different Glyma.10g230200 alleles and variations in resistance to Psgneau001, a combined phenotype and haplotype analysis was conducted using these 310 soybean germplasms. This analysis revealed a marked difference in Psgneau001 resistance between Hap1 and Hap2 soybean accessions (Figure 6C). Eleven natural soybean varieties, including five extremely susceptible varieties (Hap1) and six extremely resistant varieties (Hap2), were randomly selected to analyze Glyma.10g230200 expression patterns at 24 h post Psgneau001 inoculation. As shown in Figure 6D,E, Glyma.10g230200 expression in five extremely susceptible varieties was not significantly altered following Psgneau001 inoculation, whereas it was significantly upregulated at 24 h post inoculation in six of the tested extremely resistant varieties. This haplotype analysis thus confirmed the relationship between Glyma.10g230200 and soybean resistance to Psgneau001 infection. Soybean is a critically important crop for agricultural production, with stable soybean yields being dependent on the ability to prevent disease. BSD caused by Pseudomonas syringae pv. glycinea (Psg) can have a serious adverse impact on soybean quality and crop yield. Certain genes and loci associated with Psg resistance have been identified in previous genetic and RNA-seq studies, including Rpg-1 [24], Rpg-2 [24], GmEDS1a/b [21], GmPAD4 [22,23], GmRIN4b [25], and GmNDR1 [24]. Identifying additional functional genes and loci associated with Psg resistance has the potential to offer new insight into the molecular basis for breeding improved soybean varieties that are less susceptible to BSD. Different soybean germplasms are highly genetically diverse and have the potential to aid in soybean breeding and analyses of key agronomic traits [33,34,35]. These germplasms are broadly divided into improved cultivars, landraces, and wild soybeans. Improved cultivars were originally derived from wild soybeans, with their genetic diversity having been gradually reduced over the course of domestication and selection for desirable agronomic traits [3,28,36,37,38]. Relative to improved cultivars, wild soybeans exhibit a higher degree of genotypic and phenotypic diversity [39,40,41]. When not subject to artificial selection, wild soybeans can adapt to a range of environmental conditions and abiotic stressors through natural selection, in addition to acquiring biotic stress resistance [4,39,42,43]. In this study, 10 wild soybeans, 71 landraces, and 229 improved cultivars were leveraged to identify QTLs and genes associated with Psg resistance in these different germplasm resources. Consistent with their greater genetic diversity, the tested wild accessions exhibited greater Psg resistance compared with improved cultivars, suggesting that they represent a valuable resource for efforts to breed resistant soybean varieties. The breeding of the Suinong14 (improved cultivar) and ZYD00006 (wild soybean) varieties was then conducted as a means of further probing Psg resistance-related QTLs and genes. CSSLs were generated via extensive backcrossing onto the Suinong14 background, with molecular markers and resequencing then being used to determine the location of ZYD00006 chromosome fragment insertion [44,45,46]. As such, backcrossing was continuously performed for over 10 years, the ZYD00006 DNA fragments were inserted into the Suinong14 genome, and different individuals exhibited distinct genomic compositions capable of reducing the interfering effect of the genetic background on these analyses [47,48,49,50]. Suinong14, an improved cultivar, exhibits greatly reduced genetic diversity and increased linkage disequilibrium relative to that observed for wild soybean varieties as a consequence of domestication, and these properties are poorly suited to the mapping of QTLs associated with key agronomic traits [48]. The ZYD00006 variety is found in the wild in China and was the wild variety most closely related to the improved cultivars [51]. Because of its more allelic diversity compared with cultivated soybeans [34,39,51,52], wild soybean can be used as an ideal germplasm to detect loci associated with particular traits and improve important agronomic traits, by the combination of wild and cultivated soybeans [34,43]. Here, 10 QTLs associated with Psg resistance were identified, with some of these exhibiting overlap with previously reported disease resistance-related genes or loci, including qXav-10 [4], q10.1 [31], qSCN3-11 [32], and qXav-16 [4], respectively. These data thus supported the overall accuracy of these QTL mapping and genetic analysis efforts. Bulked segregant analysis (BSA) and chromosome fragment insertion analysis approaches were then further used to screen for and analyze Psg resistance loci in an effort to further refine these results. Through gene annotation, parents’ genome information, and qPCR analyses of the overlapping QTLs, Glyma.10g230200 was found to be related to Psgneau001. Glyma.10g230200 encodes a 297 amino-acid WRKY family protein detectable in the roots and leaves of soybean plants. WRKY proteins comprise a large family of plant transcription factors that contain one or two conserved ~60 amino acid WRKY domains that bind to W-box elements [TTGAC(C/T)]. These WRKY domains contain a conserved WRKYGQK sequence followed by C2H2 or C2HC zinc-finger motifs [53]. A growing number of studies have shown WRKY transcription factors to serve as important negative or positive regulators of plant response to specific abiotic and biotic stress [54,55]. For example, several WRKY genes are rapidly induced in response to pathogen exposure, leading to the activation of stress-related gene expression that can defend plants against inducing stressors or promote stress tolerance [56]. The most recent research suggests that WRKY proteins can additionally interact with other transcription factors through complex signaling networks that can lead to the regulation of a diverse range of defense-related genes and processes to coordinate plant immunity [54,55]. For example, the OsWRKY62 protein can negatively regulate both effector-triggered immunity (ETI) and PAMP (pathogen-associated molecular patterns)-triggered immunity (PTI), inhibiting the expression of a subset of genes associated with defensive responses [57]. In the context of Xanthomonas oryzae pv. Oryzae infection, OsWRKY62 can reportedly positively regulate ETI and PTI [58,59]. AtWRKY27 expression in Arabidopsis thaliana can reportedly suppress defensive responses against Ralstonia solanacearum by modulating gene expression. Moreover, the CaWRKY40b protein expressed in pepper can control immunity-associated gene expression in the context of Ralstonia solanacearum infection [60]. The virus-induced gene silencing (VIGS) of CaWRKY40b or CaWRKY40b-SRDX (the chimeric repressor version of CaWRKY40b) overexpression respectively resulted in the up- and down-regulation of positive and negative regulatory genes, while the opposite effect was observed following the overexpression of CaWRKY40b [60]. WRKY family proteins can thus play disparate roles in response to biotic stress exposure [54,55]. In total, 174 WRKY genes have been identified in the soybean genome, several of which have been linked to biotic stress responses [53,61]. For example, GmWRKY31 and GmHDL56 interact to regulate soybean defense-associated gene expression so as to resist Phytophthora sojae [62]. Similarly, GmWRKY40 positively regulates defensive responses against P. sojae by promoting JA signaling and H2O2 accumulation [63]. Previously, 22 different soybean WRKY genes were found to be differentially expressed in response to Peronospora manshurica, with GmWRKY31 reportedly binding the GmSAGT1 promoter to drive its upregulation and thereby enhance resistance against this pathogen [56]. Here, Glyma.10g230200 was identified as a regulator of soybean response to Psgneau001 in both cultivated and wild soybean plants. Psgneau001 can induce Glyma.10g230200 expression in disease-resistant soybean cultivars, and SNPs in the promoter region of this gene were associated with differences in its expression patterns among soybean varieties. Further analyses of the phenotypes and Glyma.10g230200 haplotypes of natural soybean varieties revealed a significant correlation between the Glyma.10g230200 haplotype and BSD resistance. Through the whole genome resequencing of natural varieties and analysis of expression levels in Suinong14 and ZYD00006, we confirmed that the SNPs in the promoter region are closely associated with phenotypic differences between Suinong14 and ZYD00006 in response to Psgneau001. Though an analysis of cis-acting elements of different promoter sequences in Hap 1 and Hap 2, the Glyma.10g230200 promoter of ZYD00006 lacked one GC motif and some unnamed motives compared with Suinong14 (Tables S4 and S5). GC motifs have been found to be involved in stress and hormone response [64,65,66]. The difference between the GC motif and other motifs in the promoter of Suinong14 and ZYD00006 might result in a different expression pattern response to Psgneau001, leading to the differences in resistance to Psgneau001. These results thus support the notion that Glyma.10g230200 is a regulator of Psgneau001 resistance and provide a foundation for further studies on the mechanistic basis for such resistance. These findings will also support efforts to breed BSD-resistant soybean varieties to improve crop yield and quality. The experimental Pseudomonas strain used in this study, Psgneau001, was isolated from soybean leaves affected by BSD in the main soybean planting area of Jiamusi city, Heilongjiang province, China. Psgneau001 was isolated as follows [4]. Soybean leaves with bacterial spot disease were collected from soybean plants grown in the main producing areas of Jiamusi city after rain. The collected leaves were sterilized with 1:1000 HgCl2, after which they were immersed in alcohol and subsequently thoroughly rinsed with sterilized water to remove the HgCl2. The leaves were transferred to sterilized tubes and ground using a sterilized pestle, and after a brief centrifugation, the supernatant was coated on the NYG solid medium. Candidate single clones were underlined on new NYG solid medium, and then the new single clones were picked for subsequent verification to ensure the purity of the bacteria. New candidate single clones were isolated. More than 2 days were required for this clone to grow at 28 °C, after which the 16S rDNA from single clones were amplified and sequenced (primer sequence as shown in Table S3). The BLAST analysis of the NCBI database (https://blast.ncbi.nlm.nih.gov/, accessed on 12 December 2021) with the 16Sr DNA of candidate clones were used to determine Pseudomonas. The candidate Pseudomonas strain suspension was prepared by diluting cultured Psg 1000-fold using 10 mM sterilized MgCl2 and 0.05% Silwet-L77 when the bacteria had reached an OD600 (optical density) of 0.8 when cultured at 28 °C. Suspended bacteria were applied to the back of trifoliate in Suinong14 using an atomizer, after which plants were housed in a humidified cabinet at 100% relative humidity for 4 days. The strain could cause significant symptoms of BSD; thus, the isolated strain was named Psgneau001. In total, 310 natural soybean varieties were used for disease susceptibility analyses. These soybean germplasm resources consisted of 10 wild soybeans (G. soja Sieb. & Zucc.), 71 landraces, and 229 improved cultivars. BSD-related QTLs were verified using 170 chromosome segment substitution lines (CSSLs) derived from the crossing and continuous backcrossing of the soybean cultivar Suinong14 (which showed obvious susceptibility to Psgneau001) and the wild soybean ZYD00006 (which showed obvious resistance to Psgneau001), through single (one year) self-cross and six instances (six years) of backcross, and the CSSLs consist of 10 generations (6 BC3F5, 30 BC3F6, 51 BC3F7, 2 BC4F4, 12 BC4F5, 22 BC4F6, 13 BC5F4, 17 BC5F5, 7 BC6F5, and 10 BC6F6) [48]. The final map consisted of 5308 markers associated with 20 linkage groups and was 2655.68 cM long, with an average distance of 0.5 cM between markers [51]. Three seeds selected from each soybean variety were planted in a greenhouse at 25 °C with a photoperiod of 16 h/8 h (day/night). Plants were inoculated with a Psgneau001 suspension at the V1 stage [4]. When the Psgneau001 culture at an optical density (600 nm) of 0.8 cultured at 28 °C, it was briefly centrifuged to remove supernatant and was then diluted 1000-fold using 10 mM sterilized MgCl2. Silwet-L77 was added to the suspension so that the Silwet-L77concentration was 0.05% [67]. Psgneau001 suspension was applied to the back of trifoliate using an atomizer, after which the soybean plants were cultured for 4 days at 100% relative humidity. BSD symptoms were then assessed based on the number of lesions per unit area at 4 days post inoculation according to the following procedure. Three leaf plates were taken from one plant using a hole punch with a diameter of 2 mm and were fully ground in 1.5-mL sterilized tubes containing 400 μL 10 mM MgCl2, then added to 600 μL 10 mM MgCl2 to 1.0 mL in 1.5 mL tube, diluted 1000 times with 10 mM MgCl2. A measure of 100 μL diluted solution was extracted and evenly applied on NYG solid medium with carbenicillin and was then cultured for 2 days. The number of single colonies on the medium was counted and the average was calculated [4]. The phenotypic measurement was performed on three independent samples in each of three independent experiments, and Student’s t-test was used for statistical analyses. The cultivated Suinong14 soybean variety and the wild soybean variety ZYD00006 were used to construct chromosome segment substitution lines (CSSLs) using a previously published genetic map [34,48]. BSD-related QTLs were then identified using a WinQTL Cartographer and composite interval mapping techniques were used as follows [47]. The control marker number was 5 and window size was 10 cM. A walk speed of 0.5 cM and the forward regression method were selected. Through a composite interval mapping analysis, the proportion of the variance explained by each particular QTL and the additive effects were analyzed. When LOD score was higher than 3.0, indicating the existence of QTLs for BSD-related genes. The experimental threshold levels for linkage were calculated from 1000 permutations of each genotypic marker against the phenotype in the population. Linkage was reported as significant if the two values for a marker were greater than the critical value at p = 0.05. Through analyses of the BSD symptoms observed in CSSLs, 30 individuals that were extremely resistant to Psgneau001 and 30 that were highly susceptible to this pathogen were selected. A Hi-DNAsecure Plant Kit (Tiangen. Co., Beijing, China) was used to isolate DNA from the leaves of these plants, and gDNA concentration and purity was assessed using a Nanodrop 2000C instrument and 1.5% agarose gel electrophoresis. A pooled sequencing library was prepared based on the provided directions, after which 150-bp pair-end sequencing was performed with an Illumina HiSeq 2500 instrument (CA, USA) using standard protocols by Beijing Biomarker Technologies Corporation (http://www.biomarker.com.cn, accessed on 12 December 2021). According to the sequencing results, the association analysis between markers and phenotype was conducted by using the Euclidean distance method. The median + 3SD (median plus three standard deviations) of all locus fitting values was taken as the association threshold for analysis, to determine whether markers and phenotype were closely linked. When the specified threshold was exceeded, a marker was considered to be related to the trait. Major QTLs associated with a response to Psgneau001 were identified via the analysis of ZYD00006 chromosome insertion in combination with the phenotypic assessment of BSD in the 170 CSSLs. Major BSD-related QTLs were identified via QTL mapping, BSA-seq, and ZYD00006 chromosome fragment insertion analysis. The Williams82 reference genome was used when identifying genes within major QTL regions, with candidate genes being annotated using corresponding annotation information [48]. Patterns of candidate gene expression in Suinong14 and ZYD00006 following Psgneau001 inoculation or control treatment were assessed via qPCR. Briefly, leaves harvested at 24 h post inoculation with Psgneau001 were snap-frozen with liquid nitrogen and ground to a fine powder in a liquid nitrogen-precooled mortar, after which TRIzol was used to extract total RNA. A PrimeScript™ RT reagent Kit (Takara Biotech Co., Beijing, China) was used to synthesize cDNA, and SuperReal PreMix Color (SYBR Green) (Tiangen Co., Beijing, China) was used for qPCR analyses. Three independent experiments were conducted in soybean plants. GmUKN1 (Glyma.12g020500) served as a normalization control and the 2−ΔΔCt method was used to assess the expression patterns of candidate genes [34]. Candidate gene haplotype analyses were conducted using 310 natural soybean varieties. Genomic sequences for candidate genes, including both the coding sequence as well as the 3000-bp upstream promoter sequence, were obtained from genomic resequencing for these 310 varieties, with local BLAST analyses then being used to identify any SNPs. Analyses were conducted using Haploview 4.2 (MA, USA) with the Haps Format module, and correlations between Psgneau001 resistance and these haplotypes were analyzed using GraphPad Prism 8 [47,51].

PMC10003563

Loredana Raciti,Caterina Formica,Gianfranco Raciti,Angelo Quartarone,Rocco Salvatore Calabrò

Gender and Neurosteroids: Implications for Brain Function, Neuroplasticity and Rehabilitation

01-03-2023

neurosteroids,neuroplasticity,excitability,GABA-receptors,estrogen,gender,hippocampus,hypothalamus,rehabilitation

Neurosteroids are synthesized de novo in the nervous system; they mainly moderate neuronal excitability, and reach target cells via the extracellular pathway. The synthesis of neurosteroids occurs in peripheral tissues such as gonads tissues, liver, and skin; then, because of their high lipophilia, they cross the blood–brain barrier and are stored in the brain structure. Neurosteroidogenesis occurs in brain regions such as the cortex, hippocampus, and amygdala by enzymes necessary for the in situ synthesis of progesterone from cholesterol. Neurosteroids could be considered the main players in both sexual steroid-induced hippocampal synaptic plasticity and normal transmission in the hippocampus. Moreover, they show a double function of increasing spine density and enhancing long term potentiation, and have been related to the memory-enhancing effects of sexual steroids. Estrogen and progesterone affect neuronal plasticity differently in males and females, especially regarding changes in the structure and function of neurons in different regions of the brain. Estradiol administration in postmenopausal women allowed for improving cognitive performance, and the combination with aerobic motor exercise seems to enhance this effect. The paired association between rehabilitation and neurosteroids treatment could provide a boosting effect in order to promote neuroplasticity and therefore functional recovery in neurological patients. The aim of this review is to investigate the mechanisms of action of neurosteroids as well as their sex-dependent differences in brain function and their role in neuroplasticity and rehabilitation.

Gender and Neurosteroids: Implications for Brain Function, Neuroplasticity and Rehabilitation Neurosteroids are synthesized de novo in the nervous system; they mainly moderate neuronal excitability, and reach target cells via the extracellular pathway. The synthesis of neurosteroids occurs in peripheral tissues such as gonads tissues, liver, and skin; then, because of their high lipophilia, they cross the blood–brain barrier and are stored in the brain structure. Neurosteroidogenesis occurs in brain regions such as the cortex, hippocampus, and amygdala by enzymes necessary for the in situ synthesis of progesterone from cholesterol. Neurosteroids could be considered the main players in both sexual steroid-induced hippocampal synaptic plasticity and normal transmission in the hippocampus. Moreover, they show a double function of increasing spine density and enhancing long term potentiation, and have been related to the memory-enhancing effects of sexual steroids. Estrogen and progesterone affect neuronal plasticity differently in males and females, especially regarding changes in the structure and function of neurons in different regions of the brain. Estradiol administration in postmenopausal women allowed for improving cognitive performance, and the combination with aerobic motor exercise seems to enhance this effect. The paired association between rehabilitation and neurosteroids treatment could provide a boosting effect in order to promote neuroplasticity and therefore functional recovery in neurological patients. The aim of this review is to investigate the mechanisms of action of neurosteroids as well as their sex-dependent differences in brain function and their role in neuroplasticity and rehabilitation. Neurosteroids (NSs) were named in 1981 [1] and identified as steroids that are synthesized de novo in the nervous system, such as in the hippocampus and other brain structures, and are accumulated in the nervous system autonomously from the steroidogenic endocrine glands. Neurosteroids have been implicated in several neurological mechanisms, such as epileptogenesis, hepatic encephalopathy, neurodegeneration, neuroprotection, and psychiatric disorders. NSs’ origins from cholesterol or other steroidal precursors derive from circulating steroid hormones. They mainly moderate neuronal excitability [2,3] and reach target cells via extracellular pathways. These paracrine signals modulate neurotransmitter-gated ion channels and G-protein-coupled receptors, predominantly [4,5] γ-aminobutyric (GABA)A2 and the N-methyl-D’Aspartate (NMDA) receptors [4,5]. Excitability is carried by chemicals signals discharged from astrocytes, oligodendrocytes, Schwann cells, and neurons such as Purkinje cells, hippocampal neurons, and retinal amacrine and ganglion cells of the brain [6,7]. Following the structural characteristics, NSs can be classified as: (i) pregnane, such as allopregnanolone (5α-pregnane-3α-ol-20-one) and allotetrahydrodeoxycorticosterone (THDOC, 5α-pregnane-3α,21-diol-20-one), whose precursors are progesterone and deoxycorticosterone, respectively; (ii) androstane, such as androstanediol and etiocholanone, derived from testosterone and estradiol; (iii) sulphated, such as pregnenolone sulfate (PS) and dehydroepiandrosterone sulfate (DHEAS). The NSs cross the brain barrier and stimulate brain function. Neurons and glial cells display activity of 5α-Reductase [8,9], whereas neocortex and subcortical white matter, as well as hippocampal tissues, have 5α-reductase and 3α-HSOR enzymes activities [10,11]. Moreover, the brain astrocytes and glutamatergic principal neurons express cytochrome P450 cholesterol side-chain cleavage enzyme (CYP450scc) that transforms cholesterol to pregnenolone [12,13]. Therefore, a translocator protein (18 kD) present in the peripheral tissues and in the brain, acting as a peripheral or mitochondrial benzodiazepine receptor [14,15], supports the moving of cholesterol through to the inner mitochondrial membrane [16]. Successively, in the inner mitochondrial membrane the availability of cholesterol to the CYP450scc increases, so cholesterol is converted to pregnenolone, which is a key intermediate for NSs biosynthesis. Moreover, the presence of the 3β-hydroxysteroid dehydrogenase enzyme that converted the pregnenolone to progesterone has been shown in the brain [17] (Figure 1). Neurosteroidogenesis occurs in the brain regions such as the cortex, hippocampus, and amygdala by enzymes necessary for the in situ synthesis of progesterone from cholesterol [18,19]. NSs may act via multiple pathways, by regulating gene transcription or through a direct action on neurotransmitter-gated ion channel receptors and G-protein-coupled receptors. The most important targets are the γ-aminobutyric (GABA)A [20] and the NMDA receptors [21,22,23,24]. Nevertheless, the biosynthesis of NSs in the brain is still unclear. The aim of this review is to investigate the mechanisms of action of the NSs, their sex-dependent differences in brain function, and their role in neuroplasticity and rehabilitation. There are two chronic effects of NSs in the brain: genomic (classical intracellular steroid receptors), due to their metabolic interconversion to traditional steroids [3], and non-genomic rapid actions, mediated by ion channels and membrane receptors. The effects of NSs on the brain excitability modulation depend on the interaction between neural membrane receptors and ion channels with rapid effects (within minutes), in contrast to the slow effects of steroid hormone via intracellular steroid receptors (even though a prolonged duration has been shown) [22]. Moreover, it has been shown that NSs directly and widely control the GABA-A receptors, the ligand-gated ion channels [23], in positive or negative phase depending on the type of the steroid molecule [24]. Structurally, GABA-A receptors are heteropentamers with five protein subunits that form the chloride ion channels to moderate the bulk of synaptic inhibition in the central nervous system. NSs increase the chance of opening the GABA-A receptor chloride channel, given that the closed time increases the chloride current through the channel with a reduction of neuronal excitability. The GABA function includes the opening of chloride ion channels, and the internalization of the chloride ion to facilitate the hyperpolarization of the membrane [25,26,27]. GABA-A receptors bypass the depolarization of the excitatory neurotransmission and avoid the action potential generation by two types of inhibitory neurotransmission: synaptic (phasic) and extrasynaptic (tonic) inhibition, that are modulated and potentiated by NSs. The GABA-A receptor subunit influences the NSs action modulation of GABA-A receptors [23,24,25,26,27,28,29]. Specifically, the α-subunit influences the NSs efficacy, whereas the γ-subunit may control both the efficacy and potency [27]. The precise site of NSs binding is currently unknown, although it seems to be placed at highly conserved glutamine (position 241 in the M1 domain of the α-subunit), playing a key role in NSs modulation. Therefore, the effect of NSs is probable due to their action on both synaptic and perisynaptic/extrasynaptic GABAA receptors. The intermittent release of high levels of GABA, from presynaptic axon terminals of GABAergic interneurons, triggers the γ2-containing receptors at the synapse, inducing the phasic/synaptic inhibition. The tonic/inhibition results from the extrasynaptic continuous activation of δ-containing receptors, related to low levels of ambient GABA molecules that escape reuptake by GABA transporters [27,28,29]. The δ-subunits are located perisynaptically/extrasynaptically and they mediate the “tonic” GABA-A receptor current [20,28,29,30,31], producing a stable inhibition of neurons and decreasing their excitability. Furthermore, the location of the δ-subunit on the dendrites of hippocampal dentate gyrus granule cells supports the GABA-A receptors to work as a controller of hippocampus excitability. Allopregnanolone (ALLO), THDOC, and androstanediol are potent positive allosteric modulators of GABA-A receptors [4,5,32], binding the D ring at both C20 of the pregnane steroid side chain and C17 of the androstane of the ring A with a positive activity at GABA-A receptors [19]. ALLO has anxiolytic, sedative–hypnotic, and anticonvulsant effects. Alcohol, hydroxybutyrate, and diazepam may potentiate GABAergic inhibition directly or through the increased availability of ALLO [20]. Pregnanolone sulphate (PS) and DHEAS are sulphated at C3 (called “sulphated steroids”) and block GABA-A receptors at low micromolar concentrations, reduced the channel opening frequency [24,33,34,35,36] and inhibited actions [24,36]. They are also effective allosteric agonists at the NMDA receptor complex and negative non-competitive modulators of the GABA-A receptor [37]. High micromolar concentrations of PS and DHEAS accomplish actions on NMDA receptor-mediated currents and act on the σ1 receptors with presynaptic action, inducing glutamate release. Therefore, NSs can also modulate the NMDA type glutamate receptors [38]. The NMDA receptors exhibit two distinct sites for NSs modulation: one facilitates the effects of positive modulators, while the other pleads the effects of negative modulators. The results may have implications on mechanisms of cognition, neuroprotection, and neurotoxicity [21]. Such receptors may modulate the release of acetylcholine and dopamine, neurotransmitter systems involved in memory, motor control and behavior [39]. PS increases the fractional open time of NMDA-activated channels, by increasing the frequency and the duration of the channel opening based on the subunit ligand, and inhibits the NMDA-induced [3H] norepinephrine. The NR2A and NR2B subunits supported a potentiating effect, while NR2C and NR2D subunits sustain an inhibitor effect [40]. DHEAS and PS, as well as pregnenolone, cooperate with σ1 receptors in the brain [40]. DHEAS and PS perform an agonist action, while progesterone acts as an antagonist. On the other hand, DHEAS potentiate the NMDA-evoked excitability of hippocampus neurons, an effect that could be blocked by the σ1 antagonist haloperidol and NE-100, as well as by progesterone [40]. Therefore, whereas pregnenolone sulphate exercises excitotoxic effects on cortical and retinal cells, DHEA and DHEA-S have a neuroprotective effect against glutamate toxicity in vitro. The brain NSs vary in concentrations through time with different physiological mechanisms, depending on aging, stress, menstrual cycle, pregnancy, menopause and neurologic and psychiatric disorders [41]. Mameli et al. showed that NSs are implicated in correct brain development: some NSs may act as retrograde messengers, encouraging plasticity in immature synapses during development [42]. In fact, the administration of some positive modulators of GABAergic function such as diazepam, a benzodiazepine agonist, cause several variations in GABA-mediated functions in adulthood, with impaired locomotion and exploration as consequences [43]. Moreover, it has been shown that the enzymes necessary for neurosteroidogenesis are expressed in the immature brain and that the treatment with NSs of neuronal cells in vitro induces trophic effects, especially in the case of progesterone. The result was the boost of dendritic outgrowth in Purkinje cells. At the same time, the authors showed that ALLO helps the formation of neuronal circuitry that supported the persistence of neurons’ development. On the other hand, ALLO administered in rat pups caused an impairment of the diffusion of interneurons in the adult prefrontal cortex due to a physiological age fluctuation of ALLO in the rat brain [42]. This latter finding showed a first prenatal peak of cortical levels of ALLO and a second peak in the second week of life [44]. The administration of 10 mg/kg of ALLO on the fifth postnatal day caused an impairment of the localization and function of prefrontal and dorsal thalamic GABAergic neurons in the adult rat brain [44,45]. Moreover, perinatal NSs administration might modify the normal development of the hippocampus and the striatal and cortical dopaminergic activity [46,47]. Other research in rats by Darbra et al. showed that the administration of ALLO, during neonatal age, manipulates the behavioral affects in adolescents and adults [48]. In particular, the administration of finasteride to inhibit neonatal ALLO diminished the novelty exploratory behavior, decreased unspecific body weight and increased anxiety-related behavior during adolescence. Moreover, the neonatal administration of ALLO progressively declines the prepulse inhibition (PPI) of the acoustic startle response in adulthood, indicating an impairment of the sensorimotor gating [48,49]. The deficiency of sensorimotor gating is characteristic of various neuropsychiatric disorders, such as schizophrenia [50]. Furthermore, the effects of NSs on the dopaminergic system have also been investigated. Li et al. showed that finasteride, administrated during adolescence, inhibited the dopaminergic system in late adolescent male rats [51]. The impairment of the dopaminergic system caused the inhibition of exploratory and motor behaviors, and a drop in dopamine metabolites in the frontal cortex, hippocampus, caudate putamen, and nucleus accumbens of late adolescent male rats. The inhibition of the 5α reductase II of these areas caused a block of dihydrotestosterone production and, consequently, androgen production, with a lack of stimulation of the dopaminergic system. Moreover, a down-regulation of tyrosine hydroxylase mRNA and protein expressions in the substantia nigra and ventral tegmental area has been shown. No delayed dopaminergic effect has been demonstrated after the administration of finasteride during the first early post-natal period. This result suggested that the finasteride effect on the dopaminergic system is mediated by the inhibition of the activity of androgen. Consequently, androgen acts on central nervous system function [52,53], stimulating the activity of the dopaminergic system, and finasteride could be used as a therapeutic option for neuropsychiatric disorders such as schizophrenia or Tourette syndrome. Sex difference is one of the long-standing issues in neuroscience research concerning certain brain disorders. Testosterone is either irreversibly converted to estradiol (E2) by the activity of aromatase or metabolized to DHT by the activity of 5α-reductase. The sexual NSs (SN) DHT and E2 concentrations in the hippocampus are significantly higher than in the serum of males and females, respectively [54]. E2 and DHT are synthesized de novo from cholesterol that is transported through the mitochondrial membranes by the steroidogenic acute regulatory protein (StAR), which is expressed in the hippocampus of male and female animals [55]. Ovariectomy and gonadectomization in males reduced the hippocampal dendritic spine density [56,57]. These mechanisms of action could be blocked by letrozole, an aromatase inhibitor, in females, as well as by finasteride, a 5α-reductase inhibitor, in males [58]. E2 enhances the cellular model for learning and memory in the hippocampus, the so-called long-term potentiation at the CA3-CA1 synapses, increases the number of NMDA receptor binding sites, without effect on AMPA receptor binding sites [55], and enhances the immunofluorescence of the NMDA receptor subunit NR1 in females. Therefore, the result is a block of the NR2B NMDA receptor subunit that abolishes E2-induced enhancement of LTP. Consequently, E2 induces the magnitude of LTP at the CA3-CA1 Schaffer collaterals in the hippocampus. Fester et al. [58] showed that the receptors for Gonadotropin releasing hormone (GnRH) regulate E2 synthesis in the ovaries and, subsequently, SN synthesis in the hippocampus. Therefore, due to the estrous cycle, GnRH are released cyclically from the hypothalamus in females; thus, the brain SN levels are correlated to related to sex hormones and the reproductive state of the organism throughout life. On the other hand, after GnRH stimulation, similar effects in males were not shown [58] and it has been assumed that GnRH stimulates testosterone synthesis, which is converted to DHT in males. The double function of increasing spine density and enhancing LTP has been related to the memory-enhancing effects of sexual steroids. In ovariectomized animals, treatment with E2 and testosterone increased CA1 pyramidal spine synapse density [59]. The local release of E2 induces testosterone to the rescue of spine density [60]. On the other hand, in orchiectomized males, the only steroids that restore the orchiectomy-induced spine synapse loss are either testosterone or the non-aromatizable DHT. Therefore, as previously reported, it could be assumed that synaptic plasticity in the hippocampus is sex-dependent, with the E2 sex steroid in females and testosterone in males [61]. Moreover, Fester et al. [58] highlighted the role of SN as the principal player in SN, which induced hippocampal synaptic plasticity [61]. Additionally, these results provided evidence that the continuous synthesis of NSs is required for normal transmission in the hippocampus [55,58,61]. Treatment with E2 has led to a beneficial function of memory in women; meanwhile, androgens have shown positive results in working memory tests on male animals [61,62]. As we have seen, the mechanisms of action of NSs are different for gender. A study conducted in a healthy population showed a correlation between NSs such as DHEA, DHEA-S, and pregnenolone regarding cognitive function and psychological well-being differences between genders. In males, serum DHEA levels correlated positively with quality of life while DHEA-S and pregnenolone levels were correlated with cognitive function. On the other hand, a correlation between DHEA-S and working memory was found in females [62]. These results indicate that NSs had a relevant role in cognitive function and quality of life, with a difference between genders [63,64,65]. Neuroplasticity is considered the capacity of neural networks to modify their structure and function in response to environmental and biological inputs. It is regulated by different mechanisms, but NSs seem to play an important role. NSs are found in the brain at high concentrations, and their presence after steroidogenesis suggests that there is a local synthesis [66,67]. However, to better understand the role of NSS in modulating brain function, it is noteworthy to talk about neuroplasticity in terms of neurogenesis, structural and functional plasticity [42,61]. In fact, the earliest work on neuroplasticity was conducted by Hebb, which assumed the involvement of structural and functional changes that seem to occur in excitatory (glutamate) and inhibitory (GABAergic) networks [68,69]. Structural plasticity refers to the dimension of the neural arbor, dendritic length and number or ramifications [69], while functional plasticity is considered as an increase or decrease of electrical activity in cerebral regions, called LTP and long-term depression (LTD), respectively [70]. LTP and LTD are sustained by NMDA and AMPA receptors and modulated by GABAergic neurotransmission [71]. Various studies have demonstrated that NSs have been characterized as neuroplasticity modulators, regulating neurogenesis and structural and functional plasticity [72]. Schverer et al. [72] described the effects that specific NSs had in neuroplasticity, regarding Pregnenolone (PREG), Dehydroepiandrosterone (DHEA), their sulphate derivatives, PREGS and DHEAS, progesterone (PROG), and ALLO [54]. PREG increases the functional plasticity through NMDA receptors and stimulates NMDA receptors in newborn neurons. DHEA increases functional plasticity in terms of synaptic efficacy developed LTP via NMDA receptor signaling, and increases short-term potentiation, neurogenesis and structural plasticity through an increase in spine density. ALLO potentiates both mature excitatory synapses in vitro, possibly via presynaptic GABA-receptors modulation, and neurogenesis through GABA receptor activation in neuroprogenitor cells [23,24]. It is known that steroids may act through a genomic action mediated by a specific steroid receptor, as well as through a nongenomic action mediated by certain receptors for neurotransmitters or neuromodulatory proteins [73,74,75]. Based on these assumptions, steroids are considered neuroactive steroids, they have pharmacological effects specifically on the receptor GABAA, NMDA [76] and on the sigma-1 receptor [74]. In fact, progesterone and some of its metabolites ALLO are potent positive modulators of the GABAergic function, while DHEA, PREG, and their sulfate esters are negative modulators of the GABAA receptor and positive modulators of the NMDA and sigma-1 receptor. There is growing evidence about the interactions between neuroactive steroids and the serotonergic system. DHEA and ALLO are believed to modulate the activity of the serotonergic neurons in the dorsal raphe nucleus, either through their direct action on these neurons or in combination with some serotonin receptor inhibitors [73,77]. Sexual steroids play an important role in the development, growth, maturation and differentiation of the Central (CNS) and Peripheral Nervous System (PNS) [75]. Moreover, estrogen and progesterone affect neuronal plasticity differently in males and females regarding changes in structure and function of neurons in different regions of the brain. SNs, namely 17β-estradiol (E2) and 5α-dehydrotestosterone (DHT), are synthesized in the hippocampus and provide some sex-specific circuit modifications, i.e., a different modification in the number of excitatory spine synapses [78]. In general, hippocampal neurons synthesize sex steroids de novo from cholesterol, since the brain is equipped with all the enzymes required for the synthesis of estradiol and testosterone, the end products of sex steroidogenesis. Locally, estradiol and testosterone maintain synaptic transmission and synaptic connectivity [79]. Remarkably, the NSs estradiol is effective in females, but not in males, and vice versa DHT is effective in males, but not in females [80]. In fact, the inhibition of estradiol synthesis in females and DHT in males causes synapse loss, LTP impairment, and synaptic protein downregulation [80]. Recently, Brökling et al. [81] showed that the upregulation of the immediate hippocampus early gene Arc/Arg3.1 is related to sex steroids in a sex-dependent manner. The cytoskeleton protein Arc/Arg3.1 is involved in synaptic plasticity, and it is crucial for long-term memory function. The authors found that E2 upregulates Arc/Arg3.1 in female, but not in male hippocampal neurons. Meanwhile, testosterone upregulates Arc/Arg3.1 in male hippocampal neurons but not in female. The block of Arc/Arg3.1 protein expression in knockout mice impairs LTP without affecting short-term memory. It could be assumed that sex steroids influence hippocampal plasticity and memory by the challenging of LTP, Arc/Arg3.1 utilization and other mechanisms that lead to spine formation. A study conducted on mice found that treatment with letrozole reduced spine synapse density in female but not in male animals [82]. Lu et al. [83] also carried out a study on forebrain-specific aromatase knock-out mice and showed an upregulation of estradiol receptors (ER) ERβ and a downregulation of ERα in the hippocampus, and reduced the number of mushroom spines with impairment of LTP. Fester et al. [84] found a strong sex-dependency in estradiol-induced synaptic plasticity. In the female hippocampus, either in vivo or in hippocampal tissue which originate from female animals, locally synthesized estradiol sustains hippocampal connectivity and LTP. On the other hand, testosterone and dihydrotestosterone are responsible for the sex steroid-induced synaptic plasticity specifically in males, either for the density of mushroom spines or of spine synapses. Regarding hippocampal cultures of male animals, the authors found that the sex-dependent development of neurons took place in response to sex NSs, either directly encouraged by sex chromosomes or indirectly by fetal testosterone (T) secretion during the perinatal period. In fact, the authors showed that, in vitro, the synaptic plasticity as well as LTP and the stability of synapse density in the hippocampus is controlled by E2 in female and testosterone in male animals, respectively, in a sex-specific manner, and that sex steroids act in a paracrine manner [85]. Synapse loss in females was paralleled by the downregulation of NR1 subunits of NMDA receptors after removing the main source of estradiol in females [86]. It was demonstrated that estradiol, in females, is important for synaptogenesis, rather than estradiol from peripheral sources such as the ovaries [87]. The loss of synapses in females was found only in the hippocampus and not in other regions of the brain or cerebellum [88]. Brandt et al. showed that synapse density in the hippocampus is controlled by sex NSs in a sex-specific manner. Therefore, the preservation of synapses and mature (mushroom) spines is mediated by T and its metabolite DHT (by 5 α-reductase) in the hippocampus of males, E2 derived from the conversion by aromatase of hippocampus-derived T, in females [85]. Data on estradiol that regulated cognitive abilities come from studies of estradiol replacement therapy in pre- and postmenopausal women. NSs have been related to the physiological control of seizure susceptibility only in patients with epilepsy, in specific seizures such as catamenial epilepsy, stress and temporal lobe epilepsy or alcohol withdrawal [11] Physiologically, progesterone positively influences the seizure threshold by its conversion to ALLO that, as reported previously, strongly and positively modulates tonic GABAergic inhibition. Therefore, the pathophysiology of catamenial epilepsy (CE), a cyclical exacerbation of seizure during the menstrual cycle, has been related to the sudden decrease of hematic progesterone before menstruation in a high proportion of women with drug refractory epilepsy [89]. Antiepileptic therapy with the oral contraceptive agent medroxyprogesterone has been used effectively because of its capacity to increase the synthesis of ALLO. Trivisano et al. [90] showed a significant reduction in cortisol and PS levels in postpubertal CE girls and low levels of ALLO, and meanwhile no differences were found in prepubertal CE girls [91]. Therefore, these results encouraged trials on ganaxolone, a synthetic analogue of ALLO, for its effect on epilepsy [89,92,93]. Even the seizure incidence, severity, and antiseizure medication (ASM) efficacy are gender dependent, especially in signaling pathways that determine network excitability. It has been shown that the electroneutral cation-chloride cotransporters (CCCs) of the SLC12A gene family have a strong influence over the electrical response to the inhibitory neurotransmitter GABA. CCCs dysfunction has been linked to seizures during early postnatal development, epileptogenesis, and refractoriness to ASMs in a sex-dependent manner [94]. However, better knowledge on the pathophysiology of sex-dependent signaling in epilepsy is fundamental to reduce long-term epilepsy comorbidities, such as lower scores on neuropsychological tests and attention-deficit hyperactivity disorder symptoms in children [94]. Migrainous auras and mechanisms of nociceptive sensitization have been related to a disproportion between excitatory and inhibitory neurotransmission, and consequently to a hyperactivation of N-methyl-d-aspartate receptors [95]. Owing to their mechanisms of action, NSs impact the pathophysiology of migraines by altering the peripheral production of progesterone and other NSs precursors (e.g., the pre-menstrual period) by the changes in γ-aminobutyric acid mediated neurotransmission and abnormalities of neuronal excitability [96]. Koverech et al. [97] found that fluctuations of NSs levels are associated with chronic headache disorders. The authors demonstrated an increase in AP levels (that behave as a positive allosteric modulator) of both synaptic and extrasynaptic γ-aminobutyric acid A and reduced DHEA in chronic migraine (CM), and reduced DHEAS only in CM patients (DHEA and DHEAS behave as weak negative allosteric modulators or γ-aminobutyric acid A receptors). During migraine attacks, patients affected by CM + MO, showed reduced AP levels and AP/EAP ratio (EAP is an NS competitive antagonist at the AP site of γ-aminobutyric acid A receptors) and increased in DHEAS levels [98]. Whether the NS levels influence or are influenced by the attacks is still under debate [97]. On the other hand, in cluster headaches (CH) the AP levels were reduced as well as testosterone [98], giving the message of different and more severe symptoms with respect to EM and CM, but the same pathophysiological mechanisms of increased neuronal excitability. Whether the AP and T levels depend on the reduction of progesterone is still under investigation, because of the prevalence of CH in males. Neurosteroids have been studied in traumatic injury, cerebral ischemia, multiple sclerosis, and other neuropsychiatric disorders, This date highlighted an exertion of trophic and neuroprotective effects of progesterone, DHEA, testosterone, and estradiol, in in vitro studies. A recent case–control study on the gender differences of NS concentrations in schizophrenic patients showed DHEA-S and pregnenolone levels as significantly higher in males than in females, and a positive correlation with age of onset and negative correlation with the duration of illness in schizophrenic males, while pregnenolone serum levels demonstrated a positive correlation with the severity of anxiety, depression and cognitive impairment [99]. Reduced CSF levels of ALLO have been associated with depression. Therapy with fluoxetine and DHEA alleviates depressive symptoms. Even alcohol has been related to impaired levels of NSs mediated by modifications in GABAA receptor subunit expression, suggesting that an imbalance between excitatory and inhibitory signaling in alcohol use disorders (AUD) and therapy with ALLO have shown positive results for the treatment of alcohol dependence and withdrawal [100]. Studies on multiple sclerosis (MS) have shown that NSs exert local effects on glial and neuronal tissue. Specifically, progesterone products act as promyelinating features continuously during the extensive process of myelin preservation in the adult human brain [101]. It has been shown that two enzymes that convert progesterone to its promyelinating metabolites (DHP and ALLOPREG), the 5-alpha reductase (5-ARD)-3-alpha-hydroxy-steroid dehydrogenase (3-alpha HSD), are in the white matter, indicating a function in central myelination [102,103,104]. These two enzymes regulate the intracellular concentration of steroid hormones in the myelinating cells in the central and peripheral nervous systems. The NS concentrations were equal in men and women, with variations in the female brain during the menstrual cycle [105,106]. Leitner et al. [101] showed that a deficit of promyelinating NSs in the nervous system plays a decisive role in the pathogenesis of multiple sclerosis. They showed that a deficiency of ALLOPREG and DHP, that regulate the neuronal-glial crosstalk necessary for myelin maintenance, is related to demyelination and reduction and impaired myelin protein composition in the whole white matter. Therefore, the etiology of MS is a dysregulation of NS synthesis that causes an impairment of myelin maintenance as well as remyelination and increased vulnerability of the myelin sheath, phagocytosis of myelin debris, and processing of myelin antigen by microglia, with the subsequent formation of focal demyelinating lesions over months and years. Inadequate remyelination fails in most MS lesions and leads to a persistence of the disease. Then, the authors concluded that a new therapeutic approach based on hormonal replacement with DHP alone or in combination with ALLOPREG may be helpful in MS research [101]. NSs are believed to have an important role in cognitive function. Some studies indicated a positive function of estradiol in memory [107,108], with a reduction of the risk of dementia [109]. In males, it was shown that spatial memory is improved in response to androgen treatment [92]. In tests for cognitive impairment, the pharmacological inhibition of estradiol synthesis did not affect cognitive performance in boys. DHT reverses the alteration of synaptic transmission following gonadectomy in male mice [110]. Recently, androgens have been shown to be important in achieving optimal results in working memory tests in male animals [111]. Studies conducted on female gender showed that, after menopause, when levels of estradiol decreased, cognitive impairment could increase significantly, while those who maintained higher levels of estradiol showed better performance in executive functions than females that not received estradiol in menopause [112]. Duarte-Guterman et al. [113] highlighted that estrogen type, treatment duration, dose, and treatment timing influence the effects of estrogen on spatial memory, on cognition, and in neurogenesis. Therefore, the results of these studies showed that the beneficial effects of estradiol on cognitive function could be a method to prevent cognitive impairment and, consequently, the neurodegenerative process, as well as improving synaptic plasticity in subjects at an early stage of the disease [114]. Some studies showed that therapies based on estradiol could lead to a slower cognitive decline and may represent a protective factor for the development of Alzheimer’s Disease (AD) [115]. However, different studies found controversial results about the effect of estrogen in AD patients [116,117]. A clinical study revealed that estrogen replacement therapy for one year had no effect on the progression of AD in females [118]. Postmortem studies conducted in AD patients showed a significant reduction in estrogen level and in the maturation of adult neurons in the dentate gyrus compared to healthy subjects [119]. However, the administration of estradiol may provide gender-specific prevention and therapeutic approaches for AD [63,64,65]. In addition, several studies demonstrated the correlation between the effects of estradiol on neurogenesis in the hippocampus and its therapeutic effects to improve spatial memory in AD [63,64]. A significant increase in hippocampal neurogenesis was associated with an improvement of cognitive deficits after estrogen therapy during the early stage of AD in the Aβ1-42 mouse model of AD [83]. It is important to understand the mechanism of neurogenesis in response to estradiol to promote novel cognitive and physical treatments to improve neurogenesis in AD, and consequently increase synaptic plasticity [65]. The molecular mechanisms of the interaction between estradiol and the loss of synapses are unclear to the scientific community. More experiments focused on this mechanism could be useful to design an appropriate therapeutic intervention that may reverse or delay the progress of neurodegeneration in AD. Most of the available data are collected by studies on animal models, caused by the limitations of adult hippocampal neurogenesis in humans. NSs have also been related to Niemann–Pick type C (NP-C), characterized by impaired cholesterol trafficking and reduced levels of ALLO. The brains of mice with NP-C present widespread CNS demyelination, Purkinje cell loss, and motor impairment. Treatment with the neonatal administration of ALLO increased cell survival, delayed the appearance of neurologic symptoms, and approximately doubled the lifespan of the mice [120]. To date, the scientific community has questions about the possibility of modulating the hormonal system and how to promote well-being and improve cognitive and physical performance. The regulation of physical and mental health also depends on the maintenance of skeletal muscle mass, the physical activity being influenced by hormones such as testosterone, E2, growth hormone (GH), and insulin-like growth factor (IGF). The importance of these hormones for the regulation of skeletal muscle mass is known, but their interaction with the processes controlling muscle mass remain unclear [121]. Few studies have demonstrated the link between physical training and hormonal response, although resistance exercise elicited a significant hormonal response. It has been seen that physical activity at a certain level influenced the hormonal response. Anabolic hormones, such as testosterone and GH, are elevated during the 15 to 30 min following resistance exercise if an adequate stimulus is present. Indeed, moderate or high intensity training that stresses a large muscle mass tends to produce higher acute hormones (testosterone, GH, and the catabolic hormone cortisol) than low-intensity training [122]. Razzak et al. [123] investigated the effects of aerobic and anaerobic exercises on postmenopausal women. The study concluded that 12 weeks of anaerobic exercise programs improved women’s E2 levels better than aerobic exercise, as a protective factor not only to maintain physical well-being but consequently cognitive function, by regulating adult neurogenesis of the hippocampus and synaptic plasticity, learning skills and memory [114]. Cognitive and motor rehabilitation is itself a non-invasive neuromodulation tool that creates favorable conditions to promote changes in nerve impulse transmission for therapeutic purposes, thus supporting neuroplasticity. According to the literature, this phenomenon is most encouraging with the use of invasive neuromodulation tools (such as Transcranial Magnetic Stimulation and transcranial Direct Current Stimulation), and we could hypothesize that the combination with NS therapy enhances the neuroplasticity effect [58,113,123]. Indeed, it was found that SN, such as E2, influence spatial memory and other cognitive functions, and this depends on the type of E2 therapy, the duration of treatment and the dose. On the other hand, Mohammadi at al. [123] described the importance of using Transcranial Magnetic Stimulation to induce neuromodulation effects. In previous studies, it has been found that E2 administration in postmenopausal women allowed for improving cognitive performance [112] and that the combination with aerobic motor exercise would enhance this effect. For this reason, we could hypothesize that the paired association between neuromodulatory techniques, motor rehabilitation and NSs treatment could provide a boosting effect in order to promote neuroplasticity. NSs endogenously regulate neural excitability by the allosteric potentiation of GABA-A receptors. Although NS biosynthesis in the brain is well known, the controlling molecular mechanisms must be enhanced. Current neuroscience studies on neuroactive steroids have demonstrated their efficacy in some neurological conditions, although future investigations are required to improve information about the NSs impact on the human brain. NS research continues to provide new insights into the mechanisms of action that may influence therapeutic intervention. Further studies are needed to improve the hormonal impact on brain function, especially in females, and the specific NSs role in gender-specific brain conditions. To this end, there is renewed interest in synthetic NS analogs as promising therapeutic agents in clinical practice to manage several neurological disorders. Indeed, there are currently at least some compounds in clinical trials for epilepsy, traumatic brain injury, status epilepticus, and Fragile X syndrome, as well as unmet neuropsychiatric disorders. Moreover, NSs may be positively used to improve neurodevelopmental disorders. In fact, alterations of ALLO levels during maturation could partly explain the inter-individual differences shown by adolescents in response to novelty (exploration) and in the sensorimotor gating and prepulse/impulse inhibition in adults. These data underline that the spreading of a set of interneurons is in response to neonatal NS exposure and the importance of their mechanisms’ maturation in the brain related to emotionality and the responses to environmental stressors in adulthood. Longitudinal studies in these patients are necessary to establish whether the use of NSs may change the natural history of these disabling disorders. Finally, concerning the rehabilitation field, it could be investigated as to how and to what extent NSs integrating with virtual reality and other innovative technologies may boost neuralplasticity, and therefore the motor and cognitive outcomes of patients with neurological disorders. In conclusion, NSs are potent endogenous neuromodulators with rapid actions in the brain via non-genomic mechanisms. Indeed, they modulate different neurotransmitter pathways and act in a different way in the female and male brain. As they have a pivotal role in neurogenesis, the absence or reduced concentrations of NSs during development may be associated with various neurodevelopmental and neuropsychiatric disorders such as anxiety disorders, schizophrenia, epilepsy, or AD. The effect of NS compounds should be investigated in future studies in order to establish if and to what extent they may change the course of neuropsychiatric disorders.

PMC10003564

Sarah Fischer,Nicolas Spath,Mohamed Hamed

Data-Driven Radiogenomic Approach for Deciphering Molecular Mechanisms Underlying Imaging Phenotypes in Lung Adenocarcinoma: A Pilot Study

03-03-2023

lung cancer,radiogenomics,data integration,imaging genomics

The heterogeneity of lung tumor nodules is reflected in their phenotypic characteristics in radiological images. The radiogenomics field employs quantitative image features combined with transcriptome expression levels to understand tumor heterogeneity molecularly. Due to the different data acquisition techniques for imaging traits and genomic data, establishing meaningful connections poses a challenge. We analyzed 86 image features describing tumor characteristics (such as shape and texture) with the underlying transcriptome and post-transcriptome profiles of 22 lung cancer patients (median age 67.5 years, from 42 to 80 years) to unravel the molecular mechanisms behind tumor phenotypes. As a result, we were able to construct a radiogenomic association map (RAM) linking tumor morphology, shape, texture, and size with gene and miRNA signatures, as well as biological correlates of GO terms and pathways. These indicated possible dependencies between gene and miRNA expression and the evaluated image phenotypes. In particular, the gene ontology processes “regulation of signaling” and “cellular response to organic substance” were shown to be reflected in CT image phenotypes, exhibiting a distinct radiomic signature. Moreover, the gene regulatory networks involving the TFs TAL1, EZH2, and TGFBR2 could reflect how the texture of lung tumors is potentially formed. The combined visualization of transcriptomic and image features suggests that radiogenomic approaches could identify potential image biomarkers for underlying genetic variation, allowing a broader view of the heterogeneity of the tumors. Finally, the proposed methodology could also be adapted to other cancer types to expand our knowledge of the mechanistic interpretability of tumor phenotypes.

Data-Driven Radiogenomic Approach for Deciphering Molecular Mechanisms Underlying Imaging Phenotypes in Lung Adenocarcinoma: A Pilot Study The heterogeneity of lung tumor nodules is reflected in their phenotypic characteristics in radiological images. The radiogenomics field employs quantitative image features combined with transcriptome expression levels to understand tumor heterogeneity molecularly. Due to the different data acquisition techniques for imaging traits and genomic data, establishing meaningful connections poses a challenge. We analyzed 86 image features describing tumor characteristics (such as shape and texture) with the underlying transcriptome and post-transcriptome profiles of 22 lung cancer patients (median age 67.5 years, from 42 to 80 years) to unravel the molecular mechanisms behind tumor phenotypes. As a result, we were able to construct a radiogenomic association map (RAM) linking tumor morphology, shape, texture, and size with gene and miRNA signatures, as well as biological correlates of GO terms and pathways. These indicated possible dependencies between gene and miRNA expression and the evaluated image phenotypes. In particular, the gene ontology processes “regulation of signaling” and “cellular response to organic substance” were shown to be reflected in CT image phenotypes, exhibiting a distinct radiomic signature. Moreover, the gene regulatory networks involving the TFs TAL1, EZH2, and TGFBR2 could reflect how the texture of lung tumors is potentially formed. The combined visualization of transcriptomic and image features suggests that radiogenomic approaches could identify potential image biomarkers for underlying genetic variation, allowing a broader view of the heterogeneity of the tumors. Finally, the proposed methodology could also be adapted to other cancer types to expand our knowledge of the mechanistic interpretability of tumor phenotypes. Lung cancer is one of the most predominant cancer types that are diagnosed with a high incidence (14.3% of total male and 21.5% of female new cancer cases) and with a high mortality rate worldwide [1]. Currently, the diagnosis, prognosis, and treatment selection of lung cancer are mainly accomplished by histologic inspection of tumor tissue [2], lymph node involvement [3], radiological imaging [4], and mutational status of EGFR, KRAS, ALK, BRAF, ROS1, HER2, RET, MET, and PD-L1 expression analysis [5]. Major challenges include the genetic, temporal, and spatial heterogeneity of tumors, the invasive collection of tumor samples, and the inability to distinguish between clinically relevant subtypes [6]. Genome-wide characterization has recently been utilized in the clinical assessment of lung cancer with multiple molecular assays, including gene expression alterations [7], miRNA expression profiles [8], and epigenetic modifications [9] such as DNA methylation status. However, these genomic sequencing assays fall short of capturing the spatial and temporal heterogeneity of tumors [10]. Medical imaging modalities such as MRI and CT have great potential to provide comprehensive details about tumor shape, intensity, and texture. Using this information as a prognostic biomarker for overall survival has already been proposed by generating a risk score from CT image features in lung cancer [11]. Furthermore, radiological imaging is used as an ongoing clinical routine to monitor tumor progression, angiogenesis, and distant metastasis to other organs [6]. There are several well-performing machine learning-based radiomic signatures for predicting EGFR and KRAS mutation status [12,13]. There is an ongoing effort to describe the biological representation of radiomic features [14]. The recent technological revolutions in clinical imaging (radiology/radiomics) and genomic technologies have led to the emergence of a new research area called “molecular imaging”, “imaging genomics”, or radiogenomics. This field refers to the study of the association between the molecular properties of tumors and their imaging phenotypes. For instance, many radiogenomics studies have reported significant correlations of molecular markers and clinical variables based on CT or MRI image features of lung [15,16,17], prostate [18], and breast neoplasms [19]. These studies hypothesized that alterations in gene expression patterns could lead to specific tumor architectures captured by non-invasive imaging. Recently, the field has gradually broadened. For example, machine and deep learning approaches have predicted mutation status based on the image features of lung tumors [13,20,21]. To improve these studies, radiomic features need to be robust to changes in the setting, such as CT or MRI scanner variables and reconstruction algorithms. Recently, a major step has been taken to define and validate the robustness of the features [22]. In contrast to unconnected molecular or imaging analyses, radiogenomics specifically outlines links between different datasets across a range of spatial and temporal scales [23]. Radiogenomic association maps (RAMs) can represent the correlation of radiomic features, genomic features, and clinical data in visually appealing graphs that reveal complex patterns [24]. Thus, the construction of RAMs could contribute to a better understanding of the tumor biology underlying imaging phenotypes and provide new insights into the identification of non-invasive surrogate biomarkers that accurately predict tumor molecular characteristics and suggest potential therapeutic approaches. This could provide an extension to the currently available methods, such as machine learning-based approaches [11,13,18]. When various molecular assays (multi-omics data) are available, RAM generation could provide more comprehensive insights than just analyzing correlations between, for example, image features and gene expression. For instance, we can learn more comprehensively how biological processes and signaling pathways are reflected in image features. Our methods for constructing RAMs consist of unsupervised cluster-based feature selection, which is well understood and has been applied to other applications such as early diabetes detection [25]. We developed and applied a bioinformatics workflow to perform an integrative analysis of gene (mRNA) expression, miRNA expression, and clinical and imaging data (Figure 1). All patients with primary tumors were included. The common cohort size used for the integrative analysis is 22 patients with a median age of 67.5 years (min–max, 42–80) (Table 1). Image processing starts with the manual segmentation of the tumor region of interest (ROI) from patient CT scans (n = 69). Fiji [26] and MATLAB were used to extract and store 86 image features related to four imaging phenotypes: tumor size, texture, morphology, and shape. The expression data of all available mRNA (n = 515) and miRNA (n = 513) samples were analyzed by differential expression analysis. The resulting differentially expressed genes (DEGs) and miRNAs (DEMs) were further used to identify over-represented gene ontology (GO) functional terms using gProfiler [27]. We performed gene set enrichment analysis using GO terms and extracted image features via Piano [28]. This provides a summary statistic of the correlations of the extracted image features with the enriched GO terms. We extracted the intersection of enriched GO terms between gene and miRNA expression datasets. For these intersecting GO terms, patients were clustered into phenotypically distinct subgroups according to their gene and miRNA expression signatures using hierarchical clustering, reflecting the biological correlations of these signatures with the corresponding image features. Clinical and mutation data were added to these clusters using the ComplexHeatmap package [29] resulting in a radiogenomic association map. Finally, TFmiR2 [30] was used to construct the gene regulatory network (GRN) of these GO terms that potentially explain the phenotypic differences between patient subgroups. Differential expression analysis yielded 7214 and 147 differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs), respectively. The postulated functional roles of these dysregulated genes and miRNAs were summarized in 317 significant GO terms (biological processes) for the DEGs and 538 terms for the DEMs (Supplementary Tables S1 and S2). Gene set enrichment analysis was performed to investigate the association between the transcriptional signatures of these significant terms and the tumor radiomic phenotypes. This revealed 7634 and 1156 significant associations between any image feature and any revealed enriched GO term for the DEGs (Supplementary Figure S1, Supplementary Table S1) and the DEMs (Supplementary Figure S2, Supplementary Table S2), respectively. Biological processes highly associated with radiomic phenotypes included nuclear division, cell cycle, cytokine-mediated signaling, and interleukin-6 signaling. Only 11 GO terms overlapped between the association results of both DEGs and DEMs with the radiomic features (Figure 2A). Most of these 11 GO terms were biological processes specific to cell differentiation, such as cell population proliferation or positive regulation of developmental processes. Interestingly, the four studied tumor phenotypes (morphology, shape, texture, and size) show different association patterns with the dysregulated genes (DEGs) and miRNAs (DEMs). For instance, most image features related to tumor size and morphology are mainly associated with DEGs but not with DEMs. Additionally, several texture features calculated based on the neighborhood gray-tone difference matrix negatively correlate with DEGs. By contrast, the texture features calculated from the gray-level run-length matrix positively correlate with DEMs. The gene/miRNA expression values of these 11 GO terms were hierarchically clustered to form two patient clusters. We measured the similarity of the clusters between the DEG and DEM datasets by the intersection of common patients (Table 2). We also integrated patient clinical information such as age range, smoking status, tumor stage (T and N), and the incidence of the most common mutations in lung cancer: ALK, EGFR, KRAS, and TP53. As we were interested in basic cellular and biological processes, we narrowed our analysis to the following two GO processes: (1) regulation of signaling, which shows the highest overlap of patients (17/22 = 77%) between the two patient clusters of DEGs and DEMs, and (2) cellular response to organic substances, which has the highest number of associations between the transcriptomic and image features (see Figure 2B and Table 2). We then analyze these GO terms in more detail to unravel how they were reflected in the radiomic phenotypes. The RAMs of the remaining 11 detected GO terms are depicted in more detail in Supplementary Figures S7–S24. The regulation of the signaling process incorporates basic signaling genes and miRNAs. Previous studies have shown heterogeneous tumors exhibit different signaling mechanisms and dysregulation patterns of related genes and miRNAs [31]. Our results not only showed that regulation of signaling was significantly associated with varying tumor phenotypes but also allowed for patient clustering based on the expression signatures of the signaling genes/miRNAs (Figure 3) with significant differences in tumor morphology (tumor variance). Moreover, signaling genes and miRNAs positively correlated with tumor variance appear to have an inflammatory function, such as hsa-mir-9 (Supplementary Figures S3 and S4). Consistent with our findings, this miRNA has already been experimentally proposed as a prognostic biomarker based on its correlation with poor overall outcomes [32]. It is also noteworthy that most clinical data, such as tumor stage and mutation status, did not show significant differences between the two patient groups. Furthermore, the DRFs calculated as a differentiator for the two groups with their fold change and p-values are displayed. The assigned image phenotype refers to the group of the image feature (Supplementary Table S3). Biological processes related to response to organic substances had the highest number of significant associations between the transcriptomic and image features in lung carcinoma. This is consistent with the fact that one of the main causes of lung cancer is tobacco smoking, which contains carcinogenic substances, such as organic cyclic compounds [33], that damage lung tissue. Most of the texture features were significantly associated with the expression patterns of miRNAs and genes, with a positive correlation observed for the miRNA signature and a negative correlation for the gene signature (Figure 3). Moreover, when clustering patients based on the miRNA expression signature of the biological process “cellular response to organic substances”, patient groups tend to have significant differences in tumor texture features such as homogeneity, contrast, and coarseness (Figure 4C, Supplementary Figures S5 and S6). This highlights the critical role of miRNAs in tumor texture heterogeneity in CT images of lung cancer patients exposed to organic substances. Unexpectedly, the clustering of patients based on gene expression signatures of the BP “cellular response to organic substances” revealed only morphology (i.e., variance) as a difference between the patient subgroups. Figure 4B depicts exemplary CT images for the two patient groups. Notably and in concordance with tumor heterogeneity, inflammatory activity and previous exposure to organic cyclic compounds are positively correlated overall. Similar to the “regulation of signaling” BP, there were no clear, coherent patterns in tumor stage, mutation status, or smoking status (Figure 4A) between the patient subgroups. Furthermore, the DRFs calculated as a differentiator for the two groups are shown with their fold changes and corresponding p-values. The assigned image phenotype refers to the group of the image feature (Supplementary Table S3). In contrast to one DRF (variance) of the mRNA expression-based RAM, the two groups in the miRNA RAM can be differentiated by a set of 14 image features, all belonging to the texture phenotype. For each of the two examined biological processes, we constructed a TF–miRNA-mediated regulatory network that combines transcriptional and post-transcriptional interactions between the associated DEGs and DEMs, potentially driving the phenotypic differences between the patient subgroups (Figure 5). The constructed networks encompass three types of molecular interactions: (1) TF → target gene, (2) miRNA → target gene, and (3) TF → miRNA, describing how miRNAs are significantly involved in controlling tumor phenotypes. For the “regulation of signaling”, we identified two main hub genes: TAL1 and TGFBR2, which contribute largely to the regulation of the network (Figure 5A). By contrast, TGFBR2 was identified as the main hub gene for the “cellular response to organic substances” term (Figure 5B). Our results show that TAL1 is a lung-specific gene associated with lung carcinoma and directly regulates TGFBR2, which was previously annotated as a tumor suppressor gene [34]. TAL1 is also known to control normal myeloid differentiation and is an experimental drug target for the treatment of T-cell acute lymphoblastic leukemia [35]. Our analysis suggests a regulatory role for TAL1 in controlling tumor morphology, particularly tumor variance (Figure 3C). Many studies have reported the suppressive function of TGFBR2 in tumorigenesis [35,36], but no previous report has been able to highlight its regulatory role in governing the tumor texture and morphology (Figure 4C). Radiogenomic approaches combine radiological images with underlying molecular information to reveal possible links between these tumor phenotypes and the underlying biology [31]. Biologically plausible associations between gene expression, miRNA expression, and image features could have a clinical context, such as early prediction of appropriate treatments, and a positive impact on overall survival. The decision to utilize the whole transcriptome, in addition to high-evidence genotypes like EGFR mutations, was made to include as yet unknown dysregulated genes. In addition, we did not want to reduce the already small sample size by including only a subset of the patients. For example, EGFR mutations have an estimated prevalence of only 10–16% in Caucasians and ALK adds up to 1–10% [37]. We proposed a data-driven approach to construct radiogenomic association maps (RAMs) that link imaging phenotypes to associated molecular features. These RAMs have the potential to identify image features that reflect the transcriptomic and post-transcriptomic regulations behind tumor pathogenesis. Such candidate image features could be used as surrogate biomarkers in the absence of genomic information and as an indicator of the underlying biological processes and pathways. Yeh et al. [31] applied a similar approach in breast cancer patients and found positive and negative associations between image phenotypes, such as size and KEGG pathways. In addition to the RAM-based approach, several other methods detect relationships between the image features and genetics, for example, by using PET rather than CT images and associating image features with oncogenic signaling pathways [38]. Other approaches use different methods to associate the imaging phenotypes with genetic signatures, so-called metagenes, using a correlation-based approach [17]. In addition, our approach helped to decipher the complex regulatory interactions between associated genes and miRNAs, explaining the differences between patients in tumor imaging phenotypes. Our approach highlighted biologically plausible associations between imaging phenotypes, dysregulated genes, and miRNAs in lung tumor patients. For instance, the tumor size and morphology phenotypes were exclusively associated with gene expression profiles, whereas the texture phenotypes were associated with gene and miRNA profiles. This relationship sheds light on quantifying the regulatory role of genes and miRNAs in shaping the observed tumor phenotypes in radiological images. Missing interpretability of image features for clinical associations beyond the subcategories defined by image features such as shape or density complicates their evaluation. As gene ontology databases provide curated molecular knowledge, this direct connection to previous findings enables the detection of surrogate image features for biological processes involved in tumor phenotypes. Additionally, our approach visually represents the patient’s clinical and mutation data to the constructed RAM in a complex heatmap. Although no differences in clinical and mutational data of EGFR, ALK, TP53, and KRAS were observed, an equivalent analysis with a larger patient cohort could determine yet unknown patterns. Interestingly, the genes involved in the regulation of cell signaling were found to be positively associated with shape and size image features. This connection seems biologically plausible as upregulated signaling pathways in tumors would induce proliferation and, thus, growth. Both genes and miRNAs involved in this biological process were negatively associated with tumor variance. This might lead to the conclusion that rapidly growing tumors lose their grayscale variance. Moreover, our RAM analysis shows that this image feature can be used to distinguish the signaling activity of a patient’s tumor. For instance, the miRNAs hsa-mir-9-1, hsa-mir-9-2, and hsa-mir-9-3 are known to cause inflammation and positively correlate with tumor variance in patient group 1 (Figure 3, blue samples). Recent unpublished work analyzed the expression differences of several miRNAs (including mir-9) and showed that these miRNAs show different expression patterns in early, middle, and late tumor stages [39]. In patient group 2, the gene DEPTOR, which is known to inhibit lung tumorigenesis [40], is negatively correlated with tumor variance (Supplementary Figure S4, red samples), suggesting its potential role as a diagnostic biomarker for differentiating patients at high risk of progression. The dysregulated genes and miRNAs related to organic substances were able to distinguish patients with significant differences in tumor texture phenotype. Of particular interest is the state of the inflammatory microenvironment of the tumor. Our results demonstrated evidence that inflammatory activity due to organic cyclic compounds (smoking) correlates with tumor texture and suggests the miRNAs hsa-mir-196a, hsa-mir-187, hsa-mir-133a, and hsa-mir-1 as a potential factor for tumor heterogeneity between patient groups. When constructing the gene–miRNA regulatory networks associated with the two GO terms examined, TAL1 and TGFBR2 were identified as hotspot genes potentially regulating these two GO terms. The stimulation of TGFBR2 by TAL1, specifically in lung tissue, has not been experimentally confirmed. Lo Sardo et al. [34] described EZH2 as a suppressor of TGFBR2, resulting in tumor growth mediated by a cluster of miRNAs (miR-25, 93, and 106b). Although this mechanism was not reflected in our GRN, we discovered another cluster of miRNAs (hsa-mir-19a, 20a, and 21) that may be involved in tumor growth and progression, in addition to the findings described by Lo Sardo et al. [34]. It is also noteworthy that the transcription of ADRB2, a target gene in the constructed regulatory network, is enhanced by the visualized TAL1-EZH2 axis. It is the encoding gene for beta-adrenoreceptors. In the literature, ADRB2 has been controversially reported to be associated with proliferation, angiogenesis, tumor progression, distant metastasis, and TKI resistance [41]. Missing freely available repositories for patients’ multi-omics data was the main challenge for this study. We thus used all matched samples to create the RAM. Therefore, the results presented in this study require larger patient cohorts with various radiogenomics profiles to validate the detected RAMs. Furthermore, many radiogenomic studies can be improved by marking the specific biopsy site in the radiomic images to correlate the tissue-specific expression with the corresponding ROI in the image. Another important limitation is the technical challenges in data acquisition and processing, such as image standardization problems when using different CT scanners with varying parameters such as slice thickness, reconstruction algorithms, and radiation detector resolution. Finally, an automated ROI segmentation would compensate for the human bias introduced by manual segmentation. We must stress the obvious but often missed fact that association never implies causation when using RAM models. Nevertheless, we spotted literature-confirmed RAM examples generated from different OMICs datasets. Future research is warranted to test/assess the robustness and consistency of the proposed RAM map via receiver operator characteristic curves and cross-validation (CV) techniques—for instance, by building machine learning models to predict the radiographic features from the molecular data and vice versa. A second standard method to validate the detected RAMs is to apply our approach to independent/external patient cohorts and compare the identified association patterns. Clinical data, and gene and miRNA expression profiles for lung adenocarcinoma patients were downloaded from The Cancer Genome Atlas (TCGA) portal, namely the TCGA-LUAD project [42]. Genomic datasets were collected at level three. The matching CT studies (imaging traits) were obtained from The Cancer Imaging Archive (TCIA) [43] (Supplementary Table S4). The DICOM images were loaded as image sequences into the ImageJ2 software [44] and segmented using the segmentation manager plugin of Fiji V.8 [26] to create the regions of interest (3D ROIs) delineating the tumor in each CT slide. The resulting ROIs were saved in TIFF format. The statistical and geometric features (n = 32) of the 3D tumor were extracted using the Fiji 3D-ROI Manager plugin [45]. The texture features (n = 54 features) were computed by loading the TIFF ROIs (TIFF-stack library) into MATLAB R2018b using the texture toolbox [46,47]. Finally, the two feature sets were combined, resulting in 86 imaging traits for each LUAD patient. Gene and miRNA expression profiles were processed by normalization of raw read counts followed by differential expression analysis. We used the DESeq2 v. 1.12.4 R package [48] to identify differentially expressed genes (DEGs) and miRNAs (DEMs) between normal and tumor samples. Genes and miRNAs that exhibited at least a 2-fold change and a p-value cutoff of 0.05 were classified as DEGs and DEMs, respectively. p-values were adjusted using the Benjamini–Hochberg [49] procedure to limit the false discovery rate to 5%. To compare the functional enrichment of the DEGs versus the DEMs, we used the GOSt tool of the gProfiler2 R package [27] with the correction method gSCS to identify significantly enriched (p-value < 0.05) GO biological processes. To study the association between the transcriptomic functional level and the radiomic phenotypes, we used the gene set enrichment analysis (GSEA) implemented in the R package Piano [28]. For each combination of image features and a GO term, we performed GSEA to evaluate the Spearman rank correlation between the gene or miRNAs of the GO term and the image feature values. The p-values (<0.05) obtained from the GSEA were evaluated through 10,000 gene or miRNA set random permutations, and FDR-adjusted. The summary statistic indicates the directionality of the association between the GO term and the image feature in the up or down direction, revealing positive and negative associations between the transcriptomic expression profiles and the image feature. In our further analysis, we restricted our evaluation by considering only GO terms with more than two image features significantly associated with GSEA for both gene and miRNA-based analysis. Hierarchical clustering with Euclidean distance and the complete method (hclust R function) was used to derive a dendrogram of columns for visualization. T and N classification [4], smoking status, patient age, and mutation status of EGFR, KRAS, ALK, and TP53 were added. The heatmaps were visualized using the ComplexHeatmap R package [29]. The fold change (FC) for each image feature between two patient groups was calculated and tested for significance using the unpaired statistical t-test. p-values were adjusted using the Benjamini–Hochberg [49] procedure to limit the false discovery rate to 5%. The TFmiR2 web server [30] was utilized to construct the gene regulatory network (GRN) from the genes and miRNAs significantly associated with the examined GO terms with a p-value of less than 0.01. We contextualized the output network to lung cancer by selecting non-small cell lung carcinoma as the disease attribute. We also considered molecular interactions that were only supported by experimental evidence. The output networks were visualized by Cytoscape V.3.7.1 [50] highlighting edges/interactions that are lung-cancer and tissue-specific. All used methods and software packages are listed in Supplementary Table S5. We demonstrated a radiogenomics-based approach that deciphers the underlying regulatory machinery behind tumor imaging phenotypes by systematically correlating transcriptomic and image features in lung cancer patients. We have highlighted several biological processes significantly associated with tumor phenotypes (radiomic features) and unraveled the corresponding regulatory interactions with potential driver genes and miRNAs, providing better interpretability of radiologic phenotypes. This data-driven approach can be generalized to other cancer types and complex diseases, given the availability of related multi-omics datasets. Such an approach could be helpful in individualized medicine for detailed non-invasive diagnosis, treatment suggestions, drug susceptibility testing, and patient follow-up.

PMC10003567

Karol Mierzejewski,Aleksandra Kurzyńska,Zuzanna Gerwel,Monika Golubska,Robert Stryiński,Iwona Bogacka

PPARβ/δ Ligands Regulate Oxidative Status and Inflammatory Response in Inflamed Corpus Luteum—An In Vitro Study

05-03-2023

corpus luteum,pig,inflammation,oxidative stress,GW0724

Inflammation in the female reproductive system causes serious health problems including infertility. The aim of this study was to determine the in vitro effects of peroxisome proliferator-activated receptor-beta/delta (PPARβ/δ) ligands on the transcriptomic profile of the lipopolysaccharide (LPS)-stimulated pig corpus luteum (CL) in the mid-luteal phase of the estrous cycle using RNA-seq technology. The CL slices were incubated in the presence of LPS or in combination with LPS and the PPARβ/δ agonist—GW0724 (1 μmol/L or 10 μmol/L) or the antagonist—GSK3787 (25 μmol/L). We identified 117 differentially expressed genes after treatment with LPS; 102 and 97 differentially expressed genes after treatment, respectively, with the PPARβ/δ agonist at a concentration of 1 μmol/L or 10 μmol/L, as well as 88 after the treatment with the PPARβ/δ antagonist. In addition, biochemical analyses of oxidative status were performed (total antioxidant capacity and activity of peroxidase, catalase, superoxide dismutase, and glutathione S-transferase). This study revealed that PPARβ/δ agonists regulate genes involved in the inflammatory response in a dose-dependent manner. The results indicate that the lower dose of GW0724 showed an anti-inflammatory character, while the higher dose seems to be pro-inflammatory. We propose that GW0724 should be considered for further research to alleviate chronic inflammation (at the lower dose) or to support the natural immune response against pathogens (at the higher dose) in the inflamed corpus luteum.

PPARβ/δ Ligands Regulate Oxidative Status and Inflammatory Response in Inflamed Corpus Luteum—An In Vitro Study Inflammation in the female reproductive system causes serious health problems including infertility. The aim of this study was to determine the in vitro effects of peroxisome proliferator-activated receptor-beta/delta (PPARβ/δ) ligands on the transcriptomic profile of the lipopolysaccharide (LPS)-stimulated pig corpus luteum (CL) in the mid-luteal phase of the estrous cycle using RNA-seq technology. The CL slices were incubated in the presence of LPS or in combination with LPS and the PPARβ/δ agonist—GW0724 (1 μmol/L or 10 μmol/L) or the antagonist—GSK3787 (25 μmol/L). We identified 117 differentially expressed genes after treatment with LPS; 102 and 97 differentially expressed genes after treatment, respectively, with the PPARβ/δ agonist at a concentration of 1 μmol/L or 10 μmol/L, as well as 88 after the treatment with the PPARβ/δ antagonist. In addition, biochemical analyses of oxidative status were performed (total antioxidant capacity and activity of peroxidase, catalase, superoxide dismutase, and glutathione S-transferase). This study revealed that PPARβ/δ agonists regulate genes involved in the inflammatory response in a dose-dependent manner. The results indicate that the lower dose of GW0724 showed an anti-inflammatory character, while the higher dose seems to be pro-inflammatory. We propose that GW0724 should be considered for further research to alleviate chronic inflammation (at the lower dose) or to support the natural immune response against pathogens (at the higher dose) in the inflamed corpus luteum. Increasing infertility due to chronic inflammation has become a serious problem and a challenge for human and veterinary medicine in recent years. Inflammation is a protective response to pathological conditions such as bacterial infections. However, if the inflammatory cascade is not stopped, it transforms into chronic inflammation and leads to organ dysfunction [1]. An inflammatory response in the female reproductive system is often associated with the presence of lipopolysaccharide (LPS), the endotoxin of Gram-negative bacteria, e.g., Escherichia coli (E. coli) [2]. LPS binds to TLR and stimulates the synthesis of various pro-inflammatory cytokines such as IL-1β, IL-6, IL-8 and TNF-α [3]. There is evidence that E. coli LPS causes infertility by interfering with ovarian follicular development and the ovulation process [4]. Luttgenau et al. [5] reported that luteal TLR2 and TLR4 appear to be involved in the immune response of the corpus luteum (CL), which may be related to the production of pro-inflammatory cytokines and decreased ovarian steroidogenesis in cows. LPS has been reported to alter ovarian axis hormone secretion by affecting GnRH and LH production, CL growth and functions, the timing of ovulation and the estrous cycle [6,7]. In addition, the treatment of cows with LPS altered the structure of the CL and decreased plasma progesterone levels (P4), resulting in a temporary suppression of luteal function [8]. Despite these reports, there is a lack of data on the effect of LPS on the functions of the porcine CL. Furthermore, the great anatomical and physiological similarity of the female and porcine reproductive systems and the course of bacterial infection makes the pig a good model for studying the in vitro effects of infection on the immune response in the CL [9]. Peroxisome proliferator-activated receptors (PPARs) are ligand-dependent transcription factors belonging to the nuclear receptor superfamily. To date, three isoforms of PPARs—α, β/δ and γ—have been described [10]. PPARs have been reported to be involved in the various processes necessary for the proper functioning of the ovaries, such as the regulation of steroidogenesis, angiogenesis, tissue remodeling, cell cycle and apoptosis [11]. There is evidence that PPARγ ligands may play a luteotropic role by increasing the activity of 3β-HSD and the secretion of progesterone [12,13]. However, there is limited information on the role of PPARβ/δ ligands in CL function. The anti-inflammatory effects of PPAR ligands have been widely reported, including in our previous work, but most of this relates to the PPARγ isoform [14,15,16]. The effect of PPARβ/δ on inflammation has not been fully elucidated [17]. In some cases, PPARβ/δ agonists appear to exert anti-inflammatory effects, such as inhibiting the synthesis of pro-inflammatory cytokines TNF-α and MCP-1 in the liver, alleviating inflammation in experimental autoimmune encephalomyelitis, or inhibiting diabetic nephropathy by reducing inflammatory mediators in mice [18,19,20]. There are also reports suggesting that PPARβ/δ signaling promotes inflammation [17]. It has been reported that in mice with arthritis, mesenchymal stem cells (MSCs) had higher anti-inflammatory potential than the MSCs derived from PPARβ/δ knockout mice [21]. The present study was conducted to determine the influence of PPARβ/δ ligands on the global transcriptomic profile of the LPS-stimulated corpus luteum of pigs during the mid-luteal phase of the estrous cycle. In addition, transcriptomic changes in the CL after the treatment with LPS alone have been described. For the first time, our research has revealed the role of PPARβ/δ in the regulation of oxidative stress and genes involved in the inflammatory response. In addition, we have shown a dose-dependent effect of the tested agonists. RNA sequencing data were created for 20 cDNA libraries, including four untreated samples (controls), four with LPS, four with GW0724 at a concentration of 1 μmol/L, four with GW0724 at a concentration of 10 μmol/L and four with GSK3787. The analysis produced 968,505,414 raw paired-end reads in total, with an average 48,425,271 per sample and a Q20 value that was on average 99.94%. The short reads, low-quality sequences and ambiguous nucleotides were removed from the raw reads, leaving on average of 938,720,608 valid reads per sample, that were used for further analysis (Supplemental Table S2). The filtered reads were mapped to the Ss11.1.98 version of the pig genome with a unique mapped average rate of 94%. The analysis of the distribution of mapped reads to gene structures indicated that 94.11% of read pairs (in average per sample) mapped to coding sequences, 3.56% mapped to introns, and 2.33% mapped to intergenic regions (Figure 1). RNA-seq data have been deposited in the ArrayExpress database at EMBL-EBI under accession number E-MTAB-12027. The RNA-Seq analysis revealed 117 DEGs (63 downregulated and 54 upregulated) in porcine CL on days 10–12 after LPS treatment (Figure 2A and Figure 3A). The Gene Ontology (GO) analysis assigned these DEGs to 159 terms of biological processes, 18 terms of cellular components, and 47 terms of molecular functions (Figure 4A). The treatment of the CL tissue with LPS altered the expression of genes involved in processes such as the regulation of signaling receptor activity (INSL6, IL-6, TNFSF14, IFN-DELTA-7, PDYN, PRL), response to bacterium (C15orf48, NLRP6, ENSSSCG00000037358) or oxidoreductase activity (ALOX12B, ALDH3B2, XDH, SOD2). Moreover, KEEG enrichment analysis revealed that DEGs were involved in signaling pathways such as cytokine–cytokine receptor interaction (TNFRSF9, IL-6, TNFSF14, IL-27, PRL) or the NOD-like receptor signaling pathway (NLRP6, IL-6, ENSSSCG00000007964) (Supplemental Figure S1A). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S3–S5, respectively. The results of our study showed that the PPARβ/δ agonist GW0724 at a concentration of 1 μmol/L affected the expression of 102 protein-coding genes (74 downregulated and 28 upregulated) (Figure 2B and Figure 3B). The GO analysis assigned these DEGs to 193 terms of biological processes, 13 terms of cellular components, and 37 terms of molecular functions (Figure 4B). These DEGs were involved, for example, in oxidation–reduction processes (CYP46A1, CYP4A24, ALOX12B, ALDH3B2), immune response (IL-15, CSF3, TNFSF14, VTN) or cell population proliferation (SHH, MAB21L2, CSF3). Furthermore, KEEG analysis showed that these DEGs were engaged in pathways such as cytokine–cytokine receptor interaction (CD27, IL-15, CSF3, TNFSF14) or drug metabolism (TK1, ENSSSCG00000040980, ALDH3B2) (Supplemental Figure S1B). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S6–S8 respectively. In turn, the treatment of the CL with PPARβ/δ agonist GW0724 at a concentration of 10 μmol/L resulted in changes in the expression of 103 genes (57 downregulated and 46 upregulated) (Figure 2C and Figure 3C). The GO analysis assigned these DEGs to 275 terms of biological processes, 18 terms of cellular components, and 42 terms of molecular functions (Figure 5A). These DEGs were involved, for example, in immune and inflammatory response (LTA, CCL3L1, IL-6, TNFSF14, CCL4, ELF3), chemotaxis (PDGFRA, CCL3L1, ENSSSCG00000020934, CCL4), cellular response to lipopolysaccharide (CD180, IL-6, ZFP36) and tumor necrosis factor (CCL3L1, ZFP36, CCL4), or cytokine activity (LTA, CCL3L1, IL-6, TNFSF14, CCL4). Additionally, KEEG analysis indicated that these DEGs were engaged in pathways such as the NF-kappa B signaling pathway (LTA, TNFSF14, CCL4) or Toll-like receptor signaling pathway (LTA, CCL3L1, IL-6, CCL4) (Supplemental Figure S1C). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S9–S11, respectively. Statistical analysis identified 97 DEGs (19 downregulated and 78 upregulated) in the CL treated with GW0724 at a concentration of 10 μmol/L compared with 1 μmol/L (Supplemental Figure S2A, Supplemental Figure S2B). The GO analysis assigned these DEGs to 148 terms of biological processes, 8 terms of cellular components, and 32 terms of molecular functions (Supplemental Figure S2D). These DEGs were involved, for example, in immune and inflammatory response (ENSSSCG00000007642, CCL19, CSF3, MBL1, IL17B, CCR3), oxidation–reduction processes (CYP4A24, HSD17B3, SURF1) or response to DNA damage stimulus (MRNIP, BATF). Moreover, KEEG analysis indicated that these DEGs were engaged in pathways such as cytokine–cytokine receptor interaction (CCL19, IL17B, CSF3, CCR3, IL-27) and the IL-17 signaling pathway (IL17B, CSF3) (Supplemental Figure S2C). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S12–S14, respectively. The study demonstrated that PPARβ/δ antagonist GSK3787 affected the expression of 88 protein-coding genes (63 downregulated and 25 upregulated) (Figure 2D and Figure 3D). The GO analysis assigned these DEGs to 250 terms of biological processes, 16 terms of cellular components, and 39 terms of molecular functions (Figure 5B). These DEGs were mostly assigned to oxidation–reduction processes and oxidoreductase activity (CYP46A1, ENSSSCG00000003963, ALOX12B, ENOX1, CRYZL1, ENSSSCG00000030195) as well as angiogenesis (ANGPTL4, SHH, EPHB1, HAND1, LEP). Moreover, KEEG analysis indicated that these DEGs were engaged in pathways such as the PPAR signaling pathway (ANGPTL4, PLIN2) and cAMP signaling pathway (GRIN2B, GHRL, CACNA1S, PLN) (Supplemental Figure S1D). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S15–S17, respectively. The treatment of the CL with LPS increased PPARβ/δ mRNA abundance during the mid-luteal phase of the estrous cycle (Supplemental Figure S3). Real-time PCR expression patterns of the tested DEGs (IL-6, SOD2, CD180, ANGTPL4) were in agreement with RNA-Seq results (Supplemental Figure S4). Total antioxidant capacity was lower in the LPS-treated CL (21.66 mM Trolox/mg protein) compared with the control (33.97 mM Trolox/mg protein). Analysis of the CL, treated with PPARβ/δ agonist at a concentrations of 1 μmol/L and 10 μmol/L, showed higher TAC levels compared with the LPS-treated CL. Moreover, TAC was enhanced with increasing agonist concentration (38.1 and 43.9 mM Trolox/mg protein, respectively). The total antioxidant capacity of the CL treated with the antagonist was similar to that of the CL treated with LPS (21.63 mM Trolox/mg protein) and no statistical difference was noted (Figure 6A). The activity of peroxidase in the CL increased almost 2-fold after stimulation with LPS compared with the control (226.4 vs. 424.8 μM/mg protein). The difference in peroxidase activity in the agonist-treated CL compared with LPS-treated CL was not statistically significant. However, peroxidase activity in CL, which was treated with an antagonist (200.2 μM/mg protein), was decreased almost two-fold compared with LPS-treated CL (424.8 μM/mg protein) (Figure 6B). The activity of catalase in the CL did not change after LPS administration. Only the lower concentration of agonist compared with LPS-treated CL increased catalase activity (0.47 vs. 2.88 kat/mg protein) (Figure 6C). The trend of the activity of SOD and GST was similar. The treatment of the CL with LPS decreased the activity of SOD almost three-fold compared with the control (9.58 vs. 3.18 a.u./mg protein). In turn, PPARβ/δ agonist GW0724 at concentrations of 1 μmol/L or 10 μmol/L increased the activity of SOD compared with the LPS-treated CL (1 μmol/L–35.77 and 10 μmol/L–32.72 a.u./mg protein) (Figure 6D). A similar observation was made with respect to GST activity. The treatment of the CL with LPS decreased the activity of GST compared with the control (7.69 vs. 2.74 a.u./mg protein), while the treatment with the agonist increased the activity of GST at both low and high concentrations (16.37 and 16.16 a.u./mg protein, respectively) compared with the LPS-treated CL. The activity of SOD or GST was not significantly affected by the PPARβ/δ antagonist (Figure 6E). A growing body of evidence shows a negative impact of lipopolysaccharide from Escherichia coli on reproductive functions. There are reports indicating that LPS leads to infertility by impairing ovarian functions [4]. It has been shown that LPS accumulates in follicular fluid, decreases the production of estradiol from granulosa cells, suppresses the expression of gonadotrophin receptors and disrupts blastocyst implantation [22]. Despite this evidence, transcriptome changes in the porcine corpus luteum under the influence of LPS had never been studied. The present results demonstrate for the first time the global transcriptomic profile of the CL of gilts during the mid-luteal phase of the estrous cycle and the effect of LPS as well as PPARβ/δ ligands during LPS-induced inflammation within the structure. We demonstrated that LPS affected the expression of 118 DEGs (63 of which were downregulated, whereas 55 were upregulated). These DEGs were assigned to different biological processes, such as response to bacterium, the negative regulation of endothelial cell proliferation, or the IL-17 signaling pathway. Among the above genes with altered expression after LPS stimulation, we identified those involved in the regulation of oxidative stress and reactive oxygen species (ROS) production (XDH, ALDH3B2, SOD2, ALOX12B). It has been frequently reported that ROS play a significant and diverse role within the ovary, especially in the CL during luteal regression [23]. In addition, the abruptly increased production of ROS (e.g., by LPS during bacterial infection) decreases P4 secretion, which may contribute to functional and structural luteolysis and disturb the proper course of the estrous cycle [24]. Xanthine dehydrogenase (XDH) is the rate-limiting enzyme for purine degradation, metabolizing hypoxanthine/xanthine to uric acid [25]. During these metabolic processes, numerous ROS are produced, including superoxide anion (O2•−) and hydrogen peroxide (H2O2) [26]. In the present study, we demonstrated that XDH was upregulated in the LPS-treated CL during the mid-luteal phase of the estrous cycle. Moreover, we found that LPS downregulated the expression of ALDH3B2 in the CL. This gene belongs to the aldehyde dehydrogenase (ALDH) family of enzymes, which is critical for the detoxification of aldehydes [27]. ALDH3B1 has been reported to metabolize and protect cells from aldehydes and oxidative compounds derived from lipid peroxidation (LPO), suggesting an important role of this enzyme in cellular defense against oxidative stress and downstream aldehydes [28]. Mishra et al. [29] reported that the exposure of bovine luteal cells to LPS increased the LPO process. Based on our results, we can assume that LPS intensifies LPO and oxidative stress by increasing the expression of XDH and decreasing ALDH3B2 in the porcine CL. Our studies revealed also that LPS increased the expression of SOD2 in the CL during the mid-luteal phase of the estrous cycle. Superoxide dismutase 2 (SOD2) is known to play a crucial role as the major antioxidant defense system with increased expression under inflammatory conditions [30,31]. This enzyme efficiently converts superoxide to the less reactive hydrogen peroxide (H2O2), which can diffuse out of mitochondria and be further detoxified to water by other antioxidant enzymes [32]. It has been reported that the antioxidant system (including SOD2) plays an important role in the maintenance of CL integrity and function during the estrous/menstrual cycle [33]. The luteal expression of SOD2 appears to be dependent on the stage of the estrous cycle as well as the activity of various immune cells [24]. To confirm our transcriptomic results, we performed biochemical analyses to determine antioxidant status. We found that LPS reduced the total antioxidant capacity of the CL and decreased the activity of key antioxidant enzymes such as catalase, superoxide dismutase, and glutathione-s-transferase. It should be noted that SOD2 gene expression was upregulated after LPS treatment, whereas superoxide dismutase activity decreased. The lack of correlation between mRNA and protein expression has been frequently described and is the result of differences in mRNA and protein stability and the differential regulation of post-transcriptional and translational processes [34,35,36]. An interesting part of our present research is the identification of genes involved in the immune response, such as TNFSF14, NLRP6, IL-6 and BMX. Of particular interest seems to be TNFSF14 (TNF Superfamily Member 14), which was upregulated in the CL after the treatment with LPS. TNFSF14 is known to be a pro-inflammatory cytokine produced mainly by macrophages and T cells [37]. TNFSF14 has been shown to promote the activation and maturation of T lymphocytes [38] and increase the production of ROS [39], which subsequently leads to severe inflammation and tissue destruction. In addition, TNFSF14 has recently been proposed as one of the biomarkers for PCOS [40]. These results confirm that the use of LPS in the proposed experimental model induces an inflammatory response in porcine CL. In the present studies, we investigated the effect of PPARβ/δ ligands on the CL treated with LPS under in vitro conditions. It is worth noting that stimulation with LPS increased the expression of PPARβ/δ, suggesting its regulatory role in inflamed tissue. Our experimental model included two concentrations of PPARβ/δ selective agonist (GW0724)—1 μmol/L and 10 μmol/L. We found that 1 μmol/L of GW0724 affected the expression of 102 DEGs (63 DEGs were downregulated and 39 DEGs were upregulated), whereas 10 μmol/L of GW0724 altered the expression of 105 DEGs (58 DEGs were downregulated and 57 DEGs were upregulated). Most of these DEGs were involved in processes related to the regulation of oxidative stress and inflammation. Only the most interesting DEGs are discussed below. In this study, we demonstrated that the activation of PPARβ/δ by GW0724 affected the expression of genes related to the control of oxidative stress, such as ALDH3B2, SURF1, DUOXA2 and PDK4. The treatment of the LPS-stimulated CL with PPARβ/δ agonist at both doses decreased the expression of ALDH3B2 (described earlier in the discussion) and SURF1 (Surfeit locus protein 1), which is involved in the proper assembly of cytochrome c oxidase (COX) [41]. It is worth noting that these genes were upregulated after treatment with LPS alone, suggesting that activation of PPARβ/δ reverses the negative effect of LPS. Our study also showed the downregulation of DUOXA2 (maturation factor of DOUX2) after treatment with GW0724 at a concentration of only 1 μmol/L. DUOX2 is a membrane-localized glycoprotein composed of six transmembrane helices. In the presence of DUOXA2, these structural components regulate the transfer of electrons from NADPH to molecular oxygen to generate H2O2 [42]. DOUXA2 expression has been reported to be increased during chronic inflammation and in various cancers, which may be related to the extensive production of ROS [43,44]. DUOX2 upregulation has also been associated with a significant increase in extracellular H2O2 production and DNA damage in tissues [45]. In addition, it has been suggested that the pro-oxidant state resulting from the upregulation of DOUX2 may impede the recovery of tissue damage caused by inflammatory stress [44]. Moreover, the current study also demonstrated that blocking PPARβ/δ by an antagonist upregulated ENOX1 (Ecto-NOX disulfide thiol exchanger), a member of the ecto- NOX family involved in intracellular redox homeostasis [46]. ENOX1 has been reported to induce oxidative stress in human aortic endothelial cells [47]. Biochemical analyses determining antioxidant status confirmed the transcriptomic results. We demonstrated that the PPARβ/δ agonist reversed the LPS effect by increasing the activity of superoxide dismutase, glutathione transferase and catalase. The obtained results suggest that the use of the PPARβ/δ agonist attenuates oxidative stress and prevents tissue damage. Conversely, blocking the receptor may increase oxidative stress. The present study has revealed the regulatory role of GW0724, a PPARβ/δ agonist, in the inflammatory process in the porcine CL. Interestingly, the observed effects appear to be dependent on the dose of ligand administered. The treatment with GW0724 at a concentration of 1 μmol/L revealed six DEGs (CSF3, VTN, IL-15, C1QTNF12, DUOXA2, TNFSF14) involved in the regulation of the inflammatory response or immune processes, according to the Gene Ontology analysis. In this work, we have demonstrated the inhibitory effect of GW0724 on the expression of CSF3 (Granulocyte colony-stimulating factor 3), the major regulator of neutrophil production [48]. CSF3 has been reported to exert pro-inflammatory properties in inflammatory joint diseases. There is also evidence that a deficiency of CSF3 protects mice from acute and chronic arthritis [48]. An inhibitory effect of GW0724 on the expression of a potent proinflammatory cytokine—TNFSF14—was also observed. It is worth noting that this is the opposite effect to that observed after LPS treatment alone. The current results showed that GW0724 (1 μmol/L) decreased the expression of VTN (Vitronectin), a pro-inflammatory glycoprotein that binds to integrin receptors [49]. VNT-deficient mice were found to have lower numbers of neutrophils and lower concentrations of pro-inflammatory cytokines such as IL-1β and IL-6 in the lungs after LPS exposure than VTN-positive mice [50]. Moreover, the exposure of mice to VTN was associated with the decreased apoptosis of neutrophils [51]. In addition to its anti-apoptotic effect, VTN may also exacerbate the severity of acute lung injury by decreasing the uptake and clearance of apoptotic neutrophils by alveolar and tissue-derived macrophages, which is associated with the release of pro-inflammatory mediators [52]. The treatment with GW0724 (1 μmol/L) upregulated the expression of IL-15 in inflamed CL. Interleukin 15 is a pleiotropic cytokine involved in the inflammatory response in various infectious diseases [53]. It has been reported that IL-15 plays an important role in host defense in sepsis induced in mice by E. coli [54]. Mice overexpressing IL-15 were resistant to the septic shock induced by E. coli, which was related to the inhibition of apoptosis triggered by TNF-α. Moreover, the treatment of normal mice with exogenous IL-15 made them resistant to E. coli-induced lethal shock [54]. The treatment of inflamed CL with GW0724 at a concentration of 10 μmol/L affected the expression of eight genes involved in the regulation of inflammatory responses or immune processes (CD180, IL-6, CCL3L1, LTα, CCL4, ELF3, ZFP36, TNFSF14). In contrast to the lower dose of GW0724 (1 μmol/L), which showed an anti-inflammatory character, the higher dose (1 μmol/L) seems to be pro-inflammatory. We have shown that the expression of CD180, a specific inhibitor of TLR4-mediated inflammatory response [55], was downregulated after the treatment of inflamed CL with GW0724 at the higher dose. CD180 is an accessory TLR4 molecule expressed in various cell types, including monocytes and macrophages [30]. In addition, we detected the increased expression of IL-6, CCL3L1, CCL4, LTα and ELF3, which are genes known to possess pro-inflammatory properties, mainly expressed through the induction of chemotaxis and the activation of lymphocytes and macrophages [56,57,58,59]. Statistical analysis performed between the two PPARβ/δ agonist doses revealed 19 downregulated and 77 upregulated genes. The most interesting genes are involved in the regulation of inflammatory and immune responses. Among them are MBL1, CCL19, IL-17β, PGLYRP3 and CSF3, whose expression was higher after treatment with GW0724 at a concentration of 10 μmol/L compared with 1 μmol/L. Mannan-binding lectin (MBL) is an important factor of innate immunity that contributes to the elimination of microorganisms. MBL has been reported to bind to bacteria and then neutralize them by opsonizing and activating complement through the lectin pathway of complement activation [60]. In turn, peptidoglycan recognition protein 3 (PGLYRP3) recognizes bacterial compounds (peptidoglycan) and plays a role in antibacterial innate immunity [61]. Both factors are crucial during the first step of bacterial infection. The chemokine CCL19 triggers T cell proliferation, leading to upregulation of pro-inflammatory cytokine synthesis [62]. It has been reported that IL-17B induces monocytes to produce TNF-α and IL-1β and supports neutrophil recruitment and B cell chemotaxis [63,64]. During infection, immune cells such as granulocytes, macrophages, and lymphocytes are recruited to tissues to clear bacterial infection [6]. We propose that PPARβ/δ may not only play a key role in alleviating chronic inflammation, but may also be helpful in supporting the immune response to bacterial infection in the CL. The study was conducted on corpora lutea harvested from gilts intended for commercial slaughter and meat processing in accordance with the guidelines for animal care (the Act of 15 January 2015 on the Protection of Animals Used for Scientific or Educational Purposes and Directive 2010/63/EU of the European Parliament and the Council of 22 September 2010 on the protection of animals used for scientific purposes). Experimental material was collected from adult crossbred gilts (Large White × Polish Landrace, 7 months old, 100 kg body weight, n = 4) on days 10–12 of the estrous cycle (mid-luteal phase). On the farm, pigs were observed in two consecutive heat cycles. The first mark of estrus (the behavior of gilts observed in the presence of the boar) was defined as day 0 of the estrous cycle. The animals were transported to the local slaughterhouse where the ovaries were dissected within a few minutes. The removed tissues were transferred to the laboratory on ice in phosphate-buffered saline (PBS) with an antibiotic cocktail (100 IU/mL penicillin and 100 mg/mL streptomycin, PolfaTarchomin, Poland). The phase of the estrous cycle was proven in the laboratory from the morphological characteristics of the ovary [65]. The procedure for collection and incubation of the porcine CL was previously described [66]. In the laboratory, the CL were dissected from the ovary, connective tissue was removed, and placed on ice in a sterile Petri dish. CLs were cut into small pieces (100 ± 10 mg, in duplicate from each experimental replicate). Each tissue explant was placed in M199 medium (Sigma Aldrich, St. Louis, MO, USA) supplemented with 0.1% BSA fraction V (Roth, Germany) and antibiotics. The explants were pre-incubated for 2 h in a water bath at 37 °C in an atmosphere of 95% O2 and 5% CO2. Then, the explants were treated with LPS (100 ng/mL, from E. coli) for 24 h. Explants not treated with LPS were considered as controls. The medium was removed, and the explants were incubated for 6 h with LPS alone or in combination with the PPAR β/δ ligands: GW0724 (agonist; 1 μmol/L or 10 μmol/L, Cayman Chemical Company, Ann Arbor, MI, USA) or GSK3787 (antagonist; 25 μmol/L, Cayman Chemical Company). Controls also contained dimethyl sulfoxide (DMSO, solvent for the tested PPAR ligands). After the incubation, tissue explants were frozen at −80 °C until further analysis. Total RNA from 20 samples was isolated using the “RNeasy Mini Kit” (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. The Tecan Infinite M200 plate reader (Tecan Group Ltd., Männedorf, Switzerland) and Agilent Bioanalyzer 2100 (Agilent Technology, Santa Clara, CA, USA) were used to evaluate total RNA quantity and quality. The samples with an RNA Integrity Number (RIN) of >7 were selected for the next analyses. The poly(A) RNA-sequencing library was prepared according to the Illumina TruSeq Stranded mRNA Sample Preparation Protocol. Two rounds of purification were performed using oligo(dT) magnetic beads to purify the poly(A) tailed mRNA. Subsequently, the poly(A) RNA was fragmented at high temperature using a divalent cation buffer, and poly(dT) oligonucleotides were used to transcribe the RNA into cDNA. Subsequently, the cDNA was subjected to 3’ tail adenylation and adapter ligation. Reverse transcription during library construction was strand-specific. Finally, the libraries were pooled and then sequenced. Quality control analysis and quantification of the sequencing libraries were performed using the Agilent Technologies 2100 Bioanalyzer High Sensitivity DNA Chip. Paired-end sequencing was performed using the Illumina NovaSeq 6000 Sequencing System (LC Science, Houston, TX, USA). FastQC was used to assess sequence quality. After removing low-quality reads, the remaining 150 bp paired-end sequences were reassembled and mapped to the Sus scrofa genome using HISAT2 [67,68]. The mapped reads from each sample were assembled using StringTie [68]. All transcriptomes were then merged to reconstruct a comprehensive transcriptome using Perl scripts and GffCompare. Once the final transcriptome was constructed, StringTie and edgeR [69] were used to estimate the expression levels of all transcripts. StringTie was used to determine the expression of mRNAs by calculating fragments per kilobase of transcript per million (FPKM) [68]. Differentially expressed genes (DEGs) were selected with log2 (fold change) > 1 or log2 (fold change) < −1 and with statistical significance (p-value < 0.05) using the R package edgeR [69]. Differentially expressed genes were validated via real-time PCR using the AriaMx real-time PCR System (Agilent Technology, Santa Clara, CA, USA), as previously described [70]. Primer sequences (Supplemental Table S1) for reference and target genes (IL-6, SOD2, CD180, ANGTPL4, PPARβ/δ) were designed via Primer Express Software 3 (Applied Biosystems, Waltham, MA, USA). The abundance of the tested mRNAs was calculated using the comparative Pfaffl method [71]. The constitutively expressed ACTB and GAPDH genes were implemented as reference genes, and the geometric mean values of the expression levels were used for analysis. Real-time PCR results were analyzed using Statistica software (version 13.1; Statsoft Inc. Tulsa, OK, USA) with Student’s t test and expressed as means ± SEM. Results were considered statistically significant at p ≤ 0.05. The extract of the CL tissue after in vitro culture for biochemical analyses (in 5 technical replicates of each sample) was prepared via mechanical homogenization (Omni tissue Homogenizer, Kennesaw, GA, USA) in sterile PBS. Extracts were centrifuged (5000× g) at 4 °C for 15 min, and the supernatant was transferred to new tubes containing 500 μL. Protein concentration was determined using the bicinchoninic acid method (Pierce BCA Protein Assay Kit, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol. Total antioxidant capacity (TAC) was analyzed using the improved ABTS radical cation decolorization assay according to Re et al. [72]. The pre-formed radical monocation of 2,2’-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS*+) was generated via the oxidation of ABTS with potassium persulfate and was reduced in the presence of such hydrogen-donating antioxidants. The results were calculated as Trolox (a water-soluble analogue of vitamin E) equivalents per L per mg of protein. Preoxidase activity was determined according to the method described by Chance and Maehly [73]. The method consists of determining the content of purpurogallin, an orange crystalline compound in the incubation mixture, formed when pyrogallol is oxidized as a hydrogen donor in the presence of hydrogen peroxide. Samples were mixed with pyrogallol and hydrogen peroxide and incubated at 30 °C for 4 min. Absorbance was measured at 430 nm against air. The difference between the absorbance of the control sample (0.05 M acetate buffer at pH 5.6 was added instead of the tissue homogenate) and the tested sample (tissue homogenate) was a measure of enzyme activity. The millimolar absorbance coefficient for purpurogallin was 2.47/mM·cm. Enzyme activity was converted to mg of protein in the assay. The measurement method is based on the ability of catalase to decompose hydrogen peroxide [74]. The reaction is accompanied by a decrease in absorbance at a wavelength of 240 nm. Briefly, samples were diluted 20 times with 0.2 M phosphate buffer at pH 7. A total of 100 µL of H2O2 was then added to 200 µL of the sample. The absorbance was measured relative to the control (buffer instead of sample) for 30 s at 5 s intervals. The value of the decrease in absorbance was determined and the activity expressed in katal per mg of protein. The method for determining the activity of superoxide dismutase (SOD) uses the ability of p-iodonitrotetrazolium [2-(4-iodophenyl-3-(4-nitrophenyl)-5-phenyltetrazolium; INT] to be reduced to a water-soluble product with an absorption maximum at about 505 nm (reddish pink) by superoxide anion (O2−), which is formed during the oxidation reaction of xanthine by xanthine oxidase [74]. The rate of reduction of INT is linearly related to the activity of xanthine oxidase and is inhibited by SOD. Superoxide dismutase inhibits the reduction of INT to purple formazan by scavenging this radical. The rate of formazan formation is a measure of the activity of SOD [75]. The activity of SOD was expressed in arbitrary units [a. u.] per mg of protein. The glutathione S-transferase (GST) activity was determined using the Rice-Evans [76] method. Enzyme activity was calculated based on the millimolar absorption coefficient (9.6 mmol−1/cm−1) for the glutathione conjugate formed from 1-chloro-2,4-dinitrobenzene. The GST activity was converted to arbitrary units [a. u.] per mg of protein. Statistical analysis for the obtained results was performed using t-test in Prism 9 software (version 9.1.1 (223); GraphPad Software Inc., San Diego, CA, USA). Results were considered statistically significant at p ≤ 0.05 (*) and p ≤ 0.002 (**). In conclusion, this is the first report describing the in vitro effects of different doses of PPARβ/δ agonist (GW0742) on LPS-induced inflammation in the CL. We imply that PPARβ/δ ligands act in two ways depending on the dose. We have shown that both doses of the ligand exert a positive effect on the oxidative status during inflammation. Moreover, we postulate that lower dose of GW0724 effectively inhibits the expression of potent pro-inflammatory mediators, whereas the higher dose increases the expression of pro-inflammatory factors, which are mostly responsible for the induction of chemotaxis and the functional and proliferative activation of leukocytes. Therefore, we propose that the lower dose of GW0724 can be used to alleviate chronic inflammation, while the higher dose can be used to support the natural anti-pathogen response during the acute phase of inflammation that occurs at the onset of bacterial infection.

PMC10003568

Ikumi Yoshihara,Yutaka Kondo,Ken Okamoto,Hiroshi Tanaka

Sepsis-Associated Muscle Wasting: A Comprehensive Review from Bench to Bedside

06-03-2023

muscle wasting,post-intensive care syndrome,sepsis,ICU,critically ill

Sepsis-associated muscle wasting (SAMW) is characterized by decreased muscle mass, reduced muscle fiber size, and decreased muscle strength, resulting in persistent physical disability accompanied by sepsis. Systemic inflammatory cytokines are the main cause of SAMW, which occurs in 40–70% of patients with sepsis. The pathways associated with the ubiquitin–proteasome and autophagy systems are particularly activated in the muscle tissues during sepsis and may lead to muscle wasting. Additionally, expression of muscle atrophy-related genes Atrogin-1 and MuRF-1 are seemingly increased via the ubiquitin–proteasome pathway. In clinical settings, electrical muscular stimulation, physiotherapy, early mobilization, and nutritional support are used for patients with sepsis to prevent or treat SAMW. However, there are no pharmacological treatments for SAMW, and the underlying mechanisms are still unknown. Therefore, research is urgently required in this field.

Sepsis-Associated Muscle Wasting: A Comprehensive Review from Bench to Bedside Sepsis-associated muscle wasting (SAMW) is characterized by decreased muscle mass, reduced muscle fiber size, and decreased muscle strength, resulting in persistent physical disability accompanied by sepsis. Systemic inflammatory cytokines are the main cause of SAMW, which occurs in 40–70% of patients with sepsis. The pathways associated with the ubiquitin–proteasome and autophagy systems are particularly activated in the muscle tissues during sepsis and may lead to muscle wasting. Additionally, expression of muscle atrophy-related genes Atrogin-1 and MuRF-1 are seemingly increased via the ubiquitin–proteasome pathway. In clinical settings, electrical muscular stimulation, physiotherapy, early mobilization, and nutritional support are used for patients with sepsis to prevent or treat SAMW. However, there are no pharmacological treatments for SAMW, and the underlying mechanisms are still unknown. Therefore, research is urgently required in this field. Sepsis is a leading cause of mortality in intensive care units (ICUs) [1,2]. It is characterized by a very high mortality rate of 20–30%, which further increases to 40–50% following complications, such as respiratory and circulatory failure [3]. Furthermore, sequelae remain even after recovery, and there are many cases in which daily life becomes difficult. However, sepsis has a variety of causes and severity, with many unknown aspects of its pathology. Sepsis-associated muscle wasting (SAMW) is characterized by decreased muscle mass, reduced muscle fiber size, and muscle strength loss, resulting in persistent physical disability [4]. SAMW is associated with increased morbidity and mortality, and systemic inflammation is reported to be the main cause [5,6]. It occurs in 40% of critically ill, ICU-hospitalized patients and is associated with prolonged ventilator use, extended hospital stay, increased mortality, and long-term functional disorders [7]. In particular, muscle wasting in sepsis occurs early and rapidly during the first 10 days of ICU stay [8]. Furthermore, many critically ill patients who survive are said to have a lower quality of life after hospital discharge due to decreased physical function [9,10]. Thus, although improvement and prevention of SAMW is an important issue, there are no pharmacological therapeutic drugs for SAMW. In the present review, we outline the pathophysiology, treatment options, and future directions of SAMW. This study did not require the approval of an ethical committee because it is a review based on previously published studies. No unpublished data are included. The skeletal muscle is an important tissue that accounts for approximately 40% of the total body weight; it is the largest tissue in the human body. Furthermore, skeletal muscle is responsible for many functions in the human body, such as movement, maintaining posture, breathing, and protecting internal organs. Skeletal muscle is composed of discrete muscle fiber types defined by myosin heavy chain (MyHC) isoforms and metabolic activity: type I (slow twitch) fibers with slow oxidative ability and type II (fast-twitch) fibers with fast oxidative and glycolytic ability, with each having specific metabolisms and contraction patterns [11]. Type I fibers have a rich capillary supply, a high number of mitochondria and aerobic respiratory enzymes, and a high myoglobin concentration. In contrast, Type II fibers have a low mitochondrial number, high ATP activity, and increased strength and shortening speed on muscle. The proportion of type I and II fibers is variable according to the condition of the human body. Thus, many researchers have investigated the ability of fiber types to transition from slow to fast and vice versa. Of note, skeletal muscle serves as a protein reservoir used in life-threatening situations, such as starvation and severe diseases, including sepsis. Muscle wasting occurs systemically as a physiological response to aging and many systematic diseases, including trauma, burns, and sepsis; muscle atrophy occurs in specific muscles with inactivity or denervation [12]. In skeletal muscle, three major pathways are known to be involved in muscle wasting. The first is the ubiquitin–proteasome system, which plays a key role in muscle mass loss and is involved in the upregulation of ubiquitin-conjugating enzymes (E2) and ubiquitin–protein ligases (E3). Muscle atrophy gene-1 (Atrogin-1; also known as MAFbx) and muscle ring finger-1 (MuRF1) were the first muscle-specific ubiquitin ligases to be discovered [13], and they are now key target genes for muscle wasting. The second is the calpain system, which belongs to the calcium-dependent cysteine protease family [14]. The calpain system is involved in myofibrillar protein consumption. Furthermore, an in vivo study showed that the administration of calpain inhibitors reduced muscle atrophy by 30% [15]. The calcium-activated calpains are considered modulator proteases because their limited proteolytic activity alters the structure and function of the target substrate. The third is the autophagy system, a cell catabolic process that ensures the breakdown and restoration of cellular components. Although autophagy has been found to play an important role in maintaining muscle homeostasis and, in practice, may contribute to muscle degeneration, it is a necessary mechanism for cell survival. Nevertheless, increased autophagy activities have been reported to contribute to muscle loss under various conditions, including cancerous cachexia, chemotherapy, disuse, fasting, denervation, and even sepsis [16,17]. The mechanisms underlying muscle wasting, including these three pathways, have not been fully elucidated, warranting further research. Muscular wasting is a major complication of sepsis and occurs in 40–70% of patients with sepsis [2]. The progression of muscle wasting greatly influences clinical prognosis [18,19]. Inflammatory cytokines such as IL-6, TNF-α, IFN-γ, and IL-1β, whose expression levels increase at the onset of sepsis, cause acute muscle wasting [12,20,21,22,23]. Among inflammatory cytokines, IL-6 has also been reported to directly affect myofibrils [24]. Inflammatory cytokines activate many signaling pathways involved in muscle protein degradation or promote muscle atrophy-related gene expression. Additionally, other factors can influence muscle wasting. For instance, the use of a ventilator accelerates muscle atrophy owing to the inactivity of the strength and mass of the diaphragm, which is a crucial respiratory muscle [25]. Inflammatory cytokines suppress the activation of AMPK, which acts as an energy sensor, and activate mTOR and p70S6K, which are involved in protein synthesis located downstream. However, inflammatory cytokines simultaneously activate the JAK/STAT and PI3K/Akt pathways, which are involved in protein degradation in the ubiquitin–proteasome system, activate the expression of the muscle atrophy-related genes Atrogin-1 and MuRF1, and induce muscle atrophy. They are also known to activate the p38MAPK/NF-kB transduction pathway, which is involved in the inhibition of skeletal muscle differentiation and muscle protein degradation. Thus, inflammatory cytokines activate a number of degradative pathways, which result in protein degradation exceeding protein synthesis, leading to muscle wasting in sepsis. The pathways of the ubiquitin–proteasome system and autophagy system are reported to be particularly active during sepsis [26,27,28,29]. In particular, muscle atrophy-related genes Atrogin-1 and MuRF-1 are seemingly increased via the ubiquitin–proteasome pathway [30,31,32]. We have visually summarized the proposed mechanism of SAMW (Figure 1). Histological changes in muscles are mainly evaluated by microscopy with tissue staining, and the muscles may require an objective measure of the muscle fiber mean size, size variation, and types of fibers. Thus, muscle fiber cross-sectional area (CSA) is used as a standard technique for the evaluation of SAMW. A previous randomized control trial reported a 26% decrease in CSA seven days after the onset of sepsis, and the loss was improved by intensive physiotherapy [33]. In a previous trial, CSA was associated with muscle strength, and it was found that the amount of physiotherapy might lead to better muscle mass maintenance. Furthermore, there are several other studies on the measurement and evaluation of CSA in critically ill patients [34,35]. In contrast, the CSA method can hardly distinguish the types of skeletal muscle fibers, such as type I and type II. An enzyme histochemical staining for NADH-tetrazolium reductase, myosin ATPase, and cytochrome C oxidase is required to classify type I and type II. Only a few studies have focused on muscle fiber types in patients with sepsis [36,37,38]. An observational study revealed an average daily decrease in CSA of 4% for type II skeletal muscle fibers and 3% for type I skeletal muscle fibers in the anterior tibialis muscle of patients with sepsis [37]. Moreover, loss of the filamentous structure of myosin occurred before the degradation of actin or cytoskeletal proteins and was associated with increased expression of lysosomal enzymes and ubiquitin. In another study with muscle biopsies of the vastus lateralis, CSA was significantly reduced in type IIa and type IIb fibers in critically ill patients, including those with sepsis [38]. The changes in CSA of type II fibers are reduced already early in treatment in the ICU. In addition, significantly lower transcript levels of MyHC isoforms were observed in the muscle. Lipopolysaccharides (LPS) bind to genes present on the surface of immune cells and induce inflammatory reactions through the production of inflammatory cytokines via intracellular signal transduction; LPS are also called endotoxins. The receptor for LPS is the toll-like receptor 4 (TLR4). When bound to LPS, TLR4 is transported to CD14 on the plasma membrane, which acts as a co-receptor for TLR4, and activates the expression of MyD88, a cellular protein adapter. MyD88 activates the NF-kB signaling pathway, which promotes protein degradation via the ubiquitin–proteasome system; thus, LPS administration induces an inflammatory response. Myoblasts, particularly the C2C12 line, are often used as an in vitro model in research focusing on muscle wasting. Previous research reported that adding LPS to C2C12 myoblasts increases the mRNA levels of the inflammatory cytokines TNF and IL-6 in a dose-dependent manner [39]. IL-6 has also been shown to decrease myotube diameter in C2C12 cells, and the expression of Atrogin-1 and MuRF1 has been reported to increase with IL-6 expression [24]. Moreover, the addition of LPS to C2C12 cells promoted the production of IL-1β, suggesting that IL-1β may be directly involved in muscle fiber atrophy [40]. Sepsis models are often used in animal experiments by ligating the cecum and inducing intraperitoneal infection with its contents to induce peritonitis in mice (cecum ligation and puncture; CLP). Many studies on sepsis and muscle wasting have been reported in experiments conducted using CLP model mice (Table 1) [24,41,42,43,44,45,46,47,48,49,50,51]. Among previous studies (10/12, 83.3%) evaluated muscle wasting within a week after CLP. Morphological changes of muscle wasting were seen from 2 to 24 days after the CLP procedure. Additionally, morphological changes were mainly assessed by histological evaluation, and some studies (4/12, 33.3%) included the results of weight in the muscles. Various muscles were found to be wasting after CLP, including the tibialis anterior, gastrocnemius, soleus, extensor digitorum longus, diaphragm, and heart muscle. Many studies (7/12, 58.3%) reported that the tibialis anterior muscle was mainly wasted after CLP, indicating that the tibialis anterior muscle is the most easily influenced muscle during sepsis and underlying sepsis-related muscle wasting. Disuse muscle atrophy can be detected as early as 1 week after inactivity, whereas SAMW can be detected as early as 2 days after onset; therefore, disuse muscle atrophy and muscle atrophy resulting from sepsis may have different mechanisms [52,53,54]. Additionally, type II fibers have been found to be affected more than type I fibers in SAMW, whereas disuse of muscles more easily affects type I fibers [41,42]. Providing evidence that type II fibers are easily affected in SAMW, it has been reported that mTOR, which controls the muscle protein synthesis system, is suppressed in the skeletal muscle during the onset of sepsis. However, the signal transduction may occur only in type II fibers [50,55,56]. The FoxO genes, activated by sepsis, are located upstream of MuRF1 and Atrogin-1 and regulate downstream muscle atrophy-related genes (Table 1). It has also been reported that FoxO-related muscle atrophy is mainly prominent in type II skeletal muscle fibers [41,57]. Furthermore, recoveries from disuse muscle atrophy and SAMW differ remarkably. A previous study has reported that mTOR and its downstream muscle protein synthesis-related genes are more activated than in controls at 12 to 24 h following re-loading after disuse muscle atrophy [58]. Thus, recovery of muscle protein from disuse muscle atrophy takes place in a relatively short period of time, whereas SAMW recovery takes a long time and is less likely to return to before-sepsis conditions. This is because SAMW is not merely a reduction in muscle protein but is deeply debilitating due to sustained activation of protein degradation pathways, such as the ubiquitin–proteasome system [59]. SAMW occurs in both skeletal muscles and the diaphragm, presenting specific electrophysiologic and morphologic findings. However, the underlying mechanisms differ, and here we mention some specific characteristics of muscle wasting in the diaphragm. Mechanical ventilation is an important treatment option for a life-threatening event, and many sepsis patients require mechanical ventilation for respiratory support. However, ventilator-related diaphragm wasting is caused by excessive power of artificial breathing and may lead to worse clinical outcomes. Although most patients can be weaned from the ventilator, 30% of critically ill patients cannot avoid extended use of mechanical ventilation [60]. A prior study has reported that approximately 50% of patients have decreased diaphragm muscle thickness after intubation [61]. Both decreased and increased diaphragm thickness in the early course of mechanical ventilation predicted prolonged ventilation. Decreasing thickness of diaphragm was related to very low inspiratory effort, and increasing thickness was related to excessive effort [62]. Furthermore, a prolonged period of mechanical ventilation has been reported to be associated with an increased risk of death and worse long-term outcomes. Fewer than half of patients could not survive beyond a year, although a high proportion of patients could be discharged from the hospital [63]. In clinical settings, SAMW has been diagnosed using anatomical evaluations and functional tests. Anatomical evaluation is performed using muscle biopsy followed by a histological exam, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasonography. Muscle biopsy followed by histological evaluation is considered a highly accurate method to diagnose myopathic changes of SAMW. However, the biopsy method can be accompanied by some complications such as bleeding, pain, and nerve injury; therefore, alternative diagnostic tools have been considered instead. A CT scan is widely accepted as the gold standard method for skeletal muscle mass quantification. An observational study using a CT scan reported on the measurement and evaluation of the rectus femoris muscle in patients with sepsis [64]. The measurement was confirmed at the vertebral level of L4 on the CT scan; the area of the psoas major muscle was traced in 2 to 4 cuts, depending on the thickness of the CT slice. The technique was also used in the rectus femoris muscle to assess muscle volume [64]. MRI is also used for diagnoses of SAMW and, similar to CT, has a highly accurate diagnostic value for muscle mass [65]. However, an MRI scan takes a long time, and most metallic devices are contraindicated based on major concerns regarding the powerful magnetic field generated by MRI. Thus, patients who undergo MRI scan need to be hemodynamically stable. Ultrasonography is easy to use, with almost no complications, and therefore can become a useful diagnostic option for SAMW. Recently, many studies focused on ultrasonography for evaluating mass volume in sepsis instead of MRI and CT imaging. The authors of a study using ultrasonography measured muscle thickness of the rectus femoris muscle over time after the admission of patients with sepsis [66]. The ultrasonography method could reveal that rapid muscle wasting started early during hospitalization, and muscle thickness continued to decrease from day 3 to day 10 [66]. Other studies using ultrasound to measure rectus femoris muscle thickness reported a decrease in muscle thickness of approximately 10% during the ICU stay [67] and a 1.45% decrease in the CSA of the rectus femoris muscle per day [68]. In addition to muscle thickness, alterations in muscle echotextures in the early stages of sepsis also have been reported [69]. Patients with sepsis are generally not so easy to move to CT or MRI rooms because of the severity of disease; therefore, ultrasonography is recommended for the diagnosis of SAMW. Functional tests are also useful for evaluating SAMW because muscle volume does not always correlate with muscle strength. Thus, handgrip strength, the medical research council (MRC) scores, and the functional independence measure (FIM) are widely used for assessing SAMW [70]. Regarding the MRC score, muscle strength is graded as follows in 12 skeletal muscle groups: 0, “no visible or palpable contraction;” 1, “visible or palpable contraction without limb movement;” 2, “movement of the limb, but not against gravity;” 3, “movement against gravity;” 4, “movement against moderate resistance;” 5, “movement against complete resistance (normal)” [71]. The total score ranges between 0 and 60, and the sum score < 48 points indicates “muscle weakness.” The FIM consists of 18 items assessing six areas of function, and each item is graded from 1 (total assistance needed) to 7 (total independence) points. The final sum score ranges from 18 (lowest) to 126 (highest). MicroRNAs (miRNAs) may become a potential biomarker of SAMW although further evidence is required. Innate and adaptive immunity associated miRNA regulates the TNF and the TLR/NF-kB signaling pathway in sepsis [72]. A study reported that myo-miRNA (c-miR-486) and inflammation-related miRNA (c-miR-146a) in plasma may serve as a predictive biomarker of muscle wasting [73]. There are some risk factors in SAMW. Sepsis patients often have decreased insulin resistance and have shown hyperglycemia. Moreover, increased levels of insulin resistance and hyperglycemia easily cause SAMW. Thus, sepsis patients often require insulin administration, and insulin can activate mTOR1 which promotes muscle synthesis. Glucocorticoid use is also one of the risk factors of SAMW. Muscle wasting due to glucocorticoids is triggered by the activation of ubiquitin–proteasome system and the catabolic effect may differ with sepsis severity. Avoiding use of glucocorticoid can prevent SAMW. Myostatin may be associated with increasing SAMW, although checking serum myostatin levels is not popular in current clinical settings. Myostatin is both produced and released by monocytes and promote muscle wasting through the ubiquitin–proteasome system (Figure 1). Avoiding those risk factors can be useful for preventing SAMW. There are no established pharmacological treatments for improving SAMW. Thus, we present several physiological interventions that are clinically used for preventing or improving SAMW. Electrical muscular stimulation (EMS) is commonly used as a part of strength training in the fields of orthopedics and sports medicine; it uses electrical stimulation to force muscle contraction. Passive electrical stimulation of inactive muscles and active electrical stimulation of voluntary muscles can be used for task-specific rehabilitation [74]. It has also been suggested that the early introduction of EMS may contribute to reducing muscle atrophy in ICUs [75,76,77]. Nevertheless, previous studies on the effects of EMS in patients with sepsis showed conflicting results [78,79]. Low-frequency (35 Hz) electrical stimulation was ineffective in maintaining muscle mass, whereas high-frequency (100 Hz) electrical stimulation increased muscle strength [78,79]; therefore, frequency of EMS may have a role in preventing SAMW. Animal experiments have suggested that EMS improves muscle mass and reduces markers of muscle atrophy and apoptosis [80]. EMS is expected to effectively improve disused muscle atrophy in patients hospitalized in the ICU, where muscle atrophy is attributed to long-term bedridden conditions and progresses with the transition from type I to type II muscle fibers [41,42]. However, muscle atrophy resulting from sepsis causes significant atrophy of fast-twitch fibers, requiring specific and effective fast-twitch fiber stimulation. Recruitment of more motor units is required for the recovery of fast-twitch fibers. Physiotherapy and early mobilization during ICU care are known to be effective in reducing functional decline due to many diseases [81]. It has been reported that physiotherapy has an improvement effect regarding the following three points. The first is bedrest conditioning. Many studies have shown that long-term bedrest causes many physiological changes and ailments [82]. Additionally, muscle atrophy progresses at a very high rate since sepsis itself promotes protein degradation and inhibits protein synthesis. The second is the suppression of the activation of mechanisms leading to sarcopenia. It has been suggested that sepsis and sarcopenia have the common risk factor of aging [83], and although sarcopenia usually progresses with aging, it is also known to be accelerated and exacerbated by diseases. The third is an increase in lung and tissue aerobic capacity. Several studies have reported that physical therapy and early mobilization interventions ameliorate the above-mentioned issues related to ICU care. In previous studies, physiotherapy and early mobilization were shown to reduce the number of days on a ventilator [77,81], shorten the duration of hospital stay [84], and improve functional capacity at hospital discharge [85,86,87]. Furthermore, physiotherapy within 90 days of hospitalization is associated with the risk of death 10 years later [88]. Patients hospitalized in the ICU experience accelerated systemic protein degradation. Clinical research has suggested that nutritional therapy plays a major role in disease outcomes and improvement [89,90]. Some advocate that high protein intake (1.5–2.5 g/kg per day) for critically ill patients contributes to improving some clinical outcomes compared with conventional protein intake (~0.8 g/kg per day) [91,92]. Several studies have focused on muscle fiber type shifts and nutrition. First, type II fibers are said to undergo significant muscle protein degradation during starvation owing to malnutrition [93]. At the onset of sepsis, a starvation response by autophagy occurs in the body, indicating that muscular atrophy resulting from sepsis causes significant type II fiber atrophy. Type II fibers use sugars such as glycogen as an energy source, and consumed glycogen takes approximately 24–48 h to be resynthesized. High carbohydrate intake may increase the recovery rate from type II fibers loss via rapid glycogen synthesis [94]. Leucine, an essential amino acid, has also been reported to provide nutritional support for muscle synthesis. Leucine is the main component of muscle fibers, and its function is to increase insulin secretion, helping muscle cells uptake glucose as an energy source. By promoting insulin secretion, leucine increases endurance and explosive power during exercise, promoting muscle growth, repair, and strength after exercise [95]. Since the underlying mechanisms of the disease differ between patients, these nutritional therapies cannot be applied uniformly to all patients. We should provide nutrition for patients with sepsis, considering the patient’s condition and nutritional balance. Currently, EMS, physiotherapy, early mobilization, and nutrition support are conducted for preventing and treating SAMW in clinical practice; however, no drug therapy has been found. A new treatment method for SAMW using pharmacological therapy has been eagerly anticipated. Hibernations have some organ protective effects, although the cellular and molecular basis of mammalian hibernation remains poorly understood. The proportions of monounsaturated fatty acids in the muscles of hibernating animals are higher during hibernation, suggesting an increased ability to utilize fat tissues for energy [96]. To prevent muscle atrophy, hibernating animals increase the reabsorption rate of urea from their urine, which decreases the necessity to use amino acids by degrading protein from skeletal muscles [97]. Some mammals also retain the hibernation gene, referred to as the hibernation-specific protein; it has been reported that this protein is produced in the liver and acts on the brain during hibernation [98]. Hibernation-specific proteins work to overcome the winter months and starvation by switching to a low metabolic state [99,100]. Hibernation is characterized by a dormant period lasting from several days to several weeks, depending on the species, in which the basal metabolic rate drops to 2–4% of normal conditions, and the body temperature is maintained at a few degrees above ambient temperature [101,102]. Such hypothermia and hypometabolism lead to irreversible cell membrane damage and loss of cellular ionic homeostasis in critical organs, such as the brain and heart in humans and most mammals, which do not retain hibernation genes and cannot withstand prolonged hypothermia and hypoxia. In contrast, drug-induced hibernation, “artificial hibernation,” may maintain homeostasis of the human body by adjusting doses of the drug and keeping moderate hypothermia. The hibernation effect could become a treatment option for SAMW through the above-suggested mechanisms. A drug-induced hibernation effect, namely “artificial hibernation,” may prevent and treat SAMW. We have shown a summary flow chart of SAMW (Figure 2). Muscle wasting resulting from sepsis develops in 40–70% of patients with sepsis; it is a clinically important complication that greatly affects the exacerbation, recovery, and prognosis of sepsis. Muscle proteins throughout the body deplete rapidly during the initial stage of sepsis. EMS, physiotherapy, early mobilization, and nutritional support are clinically used for the purpose of preventing or treating SAMW. Future research for treatment focused on SAMW is warranted.

PMC10003569

Wan-Ting Meng,Hai-Dong Guo

Small Extracellular Vesicles Derived from Induced Pluripotent Stem Cells in the Treatment of Myocardial Injury

26-02-2023

induced pluripotent stem cells,extracellular vesicles,exosome,myocardial injury,heart,mechanisms

Induced pluripotent stem cell (iPSC) therapy brings great hope to the treatment of myocardial injuries, while extracellular vesicles may be one of the main mechanisms of its action. iPSC-derived small extracellular vesicles (iPSCs-sEVs) can carry genetic and proteinaceous substances and mediate the interaction between iPSCs and target cells. In recent years, more and more studies have focused on the therapeutic effect of iPSCs-sEVs in myocardial injury. IPSCs-sEVs may be a new cell-free-based treatment for myocardial injury, including myocardial infarction, myocardial ischemia–reperfusion injury, coronary heart disease, and heart failure. In the current research on myocardial injury, the extraction of sEVs from mesenchymal stem cells induced by iPSCs was widely used. Isolation methods of iPSCs-sEVs for the treatment of myocardial injury include ultracentrifugation, isodensity gradient centrifugation, and size exclusion chromatography. Tail vein injection and intraductal administration are the most widely used routes of iPSCs-sEV administration. The characteristics of sEVs derived from iPSCs which were induced from different species and organs, including fibroblasts and bone marrow, were further compared. In addition, the beneficial genes of iPSC can be regulated through CRISPR/Cas9 to change the composition of sEVs and improve the abundance and expression diversity of them. This review focused on the strategies and mechanisms of iPSCs-sEVs in the treatment of myocardial injury, which provides a reference for future research and the application of iPSCs-sEVs.

Small Extracellular Vesicles Derived from Induced Pluripotent Stem Cells in the Treatment of Myocardial Injury Induced pluripotent stem cell (iPSC) therapy brings great hope to the treatment of myocardial injuries, while extracellular vesicles may be one of the main mechanisms of its action. iPSC-derived small extracellular vesicles (iPSCs-sEVs) can carry genetic and proteinaceous substances and mediate the interaction between iPSCs and target cells. In recent years, more and more studies have focused on the therapeutic effect of iPSCs-sEVs in myocardial injury. IPSCs-sEVs may be a new cell-free-based treatment for myocardial injury, including myocardial infarction, myocardial ischemia–reperfusion injury, coronary heart disease, and heart failure. In the current research on myocardial injury, the extraction of sEVs from mesenchymal stem cells induced by iPSCs was widely used. Isolation methods of iPSCs-sEVs for the treatment of myocardial injury include ultracentrifugation, isodensity gradient centrifugation, and size exclusion chromatography. Tail vein injection and intraductal administration are the most widely used routes of iPSCs-sEV administration. The characteristics of sEVs derived from iPSCs which were induced from different species and organs, including fibroblasts and bone marrow, were further compared. In addition, the beneficial genes of iPSC can be regulated through CRISPR/Cas9 to change the composition of sEVs and improve the abundance and expression diversity of them. This review focused on the strategies and mechanisms of iPSCs-sEVs in the treatment of myocardial injury, which provides a reference for future research and the application of iPSCs-sEVs. Cardiovascular disease (CVD) is the leading cause of global morbidity and mortality [1,2], with a 50% increase in associated mortality over the last 30 years [3]. In view of the heavy social burden, there is an urgent need for effective prevention and control measures. At present, surgery and drugs are the standard methods for the treatment of CVD, but they cannot promote the regeneration of damaged myocardial tissue [4]. The myocardial injury caused by a large number of cardiomyocyte apoptoses is irreversible [5]. Induced pluripotent stem cells (iPSCs) are reprogrammed cells that have features similar to embryonic stem cells, such as self-regeneration without restriction and differentiation into different tissue or cell types [6,7,8]. Compared with embryonic stem cells, they have abundant sources and have no ethical issues. Moreover, iPSCs induced by autologous cells can also reduce the risk of immune rejection and can be used as a potential treatment for CVD [9,10]. Like other cell therapies, iPSCs also have disadvantages such as low cell survival, retention and implantation rates of cells [11]. Recently, many studies have confirmed that stem cells play a therapeutic role in CVD mainly by inducing paracrine/autocrine growth factors, immunomodulators, and other bioactive molecules stored in their extracellular vesicles (EVs) [12,13,14]. EVs can be classified into apoptotic bodies (50~1000 nm in diameter), microvesicles (MVs) (100~1000 nm), and exosomes (40~160 nm, average ~100 nm) based on their origin [15]. With respect to the biogenesis of EVs, apoptotic bodies are released by dying cells, which are seldomly used for study possibly due to their large and uneven particle size. MVs are formed by the direct outward budding of plasma membranes. The specific process of exosome biogenesis is recognized as a “swallow and spit” process [16] (Figure 1A). Given that the latest MISEV guidelines suggest the use of “EVs” to generally denote a heterogeneous extracellular vesicle population, and “exosomes” are defined as small extracellular vesicles (sEVs), in this review, we focus on exosomes. In the myocardial infarction (MI), myocardial ischemia–reperfusion injury (MIRI), and heart failure (HF) models, studies using stem cell EVs have shown that they can improve cardiac contractile function in the long term by reducing the initial infarct size, promoting angiogenesis, reducing fibrosis, and remodeling [17]. EVs derived from stem cells regulate gene expression by transferring different substances (including protein, DNA, mRNA, microRNA (miRNA), long-stranded non-coding RNA (lncRNA), and circular RNA (circRNA)) to achieve targeted regulation between cells [18,19], and they have the advantages of high biocompatibility, circulatory stability, and low immunogenicity [20], which open up a new field for resolving the obstacles of stem cell therapy (Figure 1B). IPSC-derived extracellular vesicles (iPSCs-EVs) can play a therapeutic role similar to that of iPSCs, and iPSCs-EVs are easier to store and transport [21]. At the same time, some limitations of cell therapy, such as embolism and tumor occurrence, are avoided [22,23]. According to the comparison of EVs secreted from mesenchymal stem cells (MSCs) and iPSCs, it was found that while iPSC-EVs enclose proteins that modulate RNA and microRNA stability and protein sorting, MSC-derived EVs are rich in proteins that organize the extracellular matrix, regulate locomotion, and influence cell–substrate adhesion. Moreover, compared to their respective cells, iPSC-EVs share 76.63% of proteins with iPSCs [24], including proteins involved in angiogenesis signaling pathways (VEGF, TGFB1, and Angiogenin) [25], proteins related to membrane organization and the wound-healing process (HSPA5, RAB10, and CLIC1) [26], and proteins involved in cardiac development and cardiac mechanical and electrical function (GSTM, ARGBP2, CDH11, and ACTA2) [27]. The efficacious extraction of iPSC-derived extracellular vesicles (iPSC-sEVs) is a prerequisite for them to play a therapeutic role. How the high yield, high purity, and high biological activity of small extracellular vesicles can be obtained is directly related to future research and applications [28,29]. At present, many techniques for isolating sEVs have been developed, which depend to a large extent on the physical and chemical properties of sEVs, and the choice of methods should also take into account specific research needs. The isolation methods of iPSC-sEVs for the treatment of CVD include ultracentrifugation (UCF) [30,31], size-exclusion chromatography (SEC) [32], polymer-based precipitation [33], affinity capture [34], magnetic [35,36] and anion-exchange-based methods [37], or a combination of the aforementioned methods [38]. In this mini review, we will introduce three of the most common ones in detail. UCF is the “gold standard” for isolating sEVs and the most commonly used technology [39]. The substances with different densities and sizes are separated by using different centrifugal forces and velocities (Figure 2A). First, larger cells, cell debris, and dead cells are removed by low-speed centrifugation [40]; then, resuspension with PBS is performed, and finally, ultracentrifugation is carried out to remove contaminated proteins to obtain granular exosomes [41]. The temperature of the whole centrifugation process is kept at 4 °C to ensure that proteases, DNA enzymes, and ribonucleases are inactivated [42]. The concentration of exosomes is determined using an enhanced BCA protein analysis kit [43,44] or nanoparticle tracking analysis, which is an optical particle tracking method developed to determine the concentration and size distribution of particles [45]. In addition, Western blotting can provide useful information on the size of the different proteins [46]. ELISA is another established technique for protein quantification and could be executed in multiple different assay formats [47]. Unlike Western blotting and ELISA, which quantify targeted proteins on a relatively small scale, mass spectrometry enables high-throughput peptide profiling [48]. Additionally, small EVs can be characterized by observation under a transmission electron microscope (TEM) [49]. Moreover, a TEM can also be coupled with immunogold labeling (immuno-EM) to provide molecular characterization [50]. UCF has advantages of simple operation, low cost, and repeatability, and it is suitable for large volume samples [51]. Dong et al. [52] found that when exosomes were separated from plasma, UCF had the highest separation purity. However, UCF is time-consuming, and different individual operations will also lead to different results [53]. In particular, repeated ultra-high-speed centrifugation has adverse effects on the quality and quantity of exosomes [54,55]. Their structural and biological integrity may also be damaged [56]. The appearance of the isodensity gradient centrifugation method is an improvement of UCF. By constructing a density gradient medium (gradually increasing from the top to the bottom of the centrifuge tube), exosomes and the corresponding isodensity area settle together under the effect of centrifugal force, thus removing most of the contaminated proteins [57] (Figure 2B). SEC is a widely recognized method that uses polymers to form porous stationary phases in chromatographic columns. Exosomes are separated according to the different path lengths of molecules or particles with different sizes [58] (Figure 2C). Compared with UCF, the exosomes separated via SEC have more complete physical structures and biological functions [59] and are suitable for various biological fluids [60]. However, the products obtained via the SEC method may be contaminated by a large number of proteins with low purity, which means the method is suitable for samples with small size and high yield. EVs can transfer encapsulated proteins and genetic information to recipient cells and act as information messengers between cells [61]. They are natural biologics with autologous origin, while they also maintain cargo integrity and stability. Furthermore, exosomal membranes contain certain proteins that have binding affinities to specific receptors on the surface of the recipient cells. EV uptake may occur through three mechanisms: endocytosis, ligand–receptor uptake, and fusion [62]. Upon binding to a specific target cell, EVs have the ability to initiate intracellular signaling via receptor–ligand interactions, undergo internalization via endocytosis and/or phagocytosis, or even fuse with the target cell’s membrane, resulting in the transfer of their contents to the cytosol of the recipient cell. These processes ultimately lead to the modification of the physiological state of the recipient cell [63]. Rab GTP enzymes such as Rab11, Rab35, Rab27a, and Rab27b participate in the production of exosomes through vesicle budding [64,65,66]. The expression of exosomal markers such as CD63 was shown to be reduced by the silencing of Rab27a and Rab27b [67,68]. To demonstrate in vivo EV transfer between cells, a few groups have recently developed clever modifications of EVs, allowing their behavior and target cells to be tracked in vivo. For example, Lai et al. combined Gaussia luciferase with metabolic biotinylation to create a sensitive EV reporter for multimode imaging, showing that the dynamic processing of EVs has an accurate spatio-temporal resolution [69]. In order to further evaluate the accuracy of time and space, Lai et al. also designed optical reporters to label multiple EV populations, and they found that EV-borne mRNA transfer between cells and the process is dynamic and multidirectional [70]. IPSC-sEVs contain mRNAs which participate in a variety of biological processes of cell proliferation, promoting angiogenesis and paracrine response [71]. In addition to proteins and mRNAs, miRNAs and other non-coding RNAs are also possible active EVs cargoes. The miRNA secreted in sEVs can be functionally delivered to target cells, resulting in the direct modulation of their mRNA targets [72]. Mendel et al. reported miRNAs to be present in both iPSCs and iPSC-sEVs; they found miR-19b, miR-20a, miR-126-3p, miR-130a-3p and miR-210-3p were reportedly involved in the promotion of angiogenesis, adaptation to hypoxic stress, and regulation of cell cycles [73]. Exosomes are also highly engineerable, and the strategies include genetic engineering and chemical modification [74,75]. The engineering of exosomal surface proteins confers cell and tissue specificity [76]. The surface molecules anchored on exosomes from different cell sources vary, which endows them with selectivity for specific recipient cells. Bobis-Wozowicz et al. showed that iPSC-sEVs are able to transfer bioactive molecules delivered to human cardiac mesenchymal stromal cells and were found to exert protective effects by affecting the transcriptomes and proteomic profiles of the recipient cells [77]. Additionally, iPSC-sEVs combined with small-molecule RNA (miR-499) induce myocardial differentiation and improve cardiac function through the wnt/β-catenin signaling pathway in rats [78]. Jung et al. found that exosomal cargo containing miR-106a-363 improved the murine LV ejection fraction and reduced the myocardial fibrosis of the injured myocardium [79]. For the application of an in vivo model, 15–100 μg is the commonly used dose for the treatment of mouse or rat models [44], while 2–40 μg/mL is the commonly used intervention dose for in vitro studies [80]. Consequently, EVs from gene-edited patient-specific iPSCs can be directed to the specific lesions of each individual patient to promote the salvage of the existing injured cells. IPSC-sEVs hold potential for a wide spectrum of beneficial effects on cell function recovery to restore the myocardial injury by simulating and activating the endogenous repair, consisting of the native transfer of proteins, mRNAs, and miRNAs (Table 1). EVs represent the most feasible approach to translate the enormous potential of pluripotent stem cell biology. Studies have found that iPSC-sEVs play a protective role in the treatment of CVD by regulating apoptosis, inflammation, and fibrosis, as well as promoting angiogenesis [94,95,96]. These are achieved through cell-to-cell communication, which is promoted by substances such as miRNA, small molecules, and proteins (Figure 3). The death of many CMs after MI leads to strong inflammation. IPSC-sEVs show angiogenesis and anti-inflammatory potential in the cell therapy of MI [97]. Angiogenesis is the main mechanism of improving left ventricular function through cell therapy after ischemic myocardial injury, which indicates that iPSC-sEVs are a potential target for MI therapy [98]. More and more studies have shown that exosomes derived from iPSCs can promote endogenous repair and enhance cardiac function after MI [79,99]. Takeda et al. [83] isolated exosomes from human iPSCs and administered them successively in the ischemic myocardial model of mice, which showed that iPSC-sEVs significantly improved myocardial injury after MI by reducing apoptosis and fibrosis. In vitro studies have also shown that angiogenesis and anti-apoptotic effects depend on the increased survival of CMs derived from iPSCs, and exosomes from iPSC-derived CMs (iPSC-CMs) improve myocardial recovery without increasing the probability of arrhythmogenic complications [100]. Gao et al. [101] demonstrated that exosomes from human iPSC-CMs also have cardioprotective effects in a swine MI model according to the ejection fraction, wall stress, myocardial bioenergetics, and cardiac hypertrophy. In vitro studies also showed their angiogenic and anti-apoptotic effects depending on increased endothelial cell tube formation and the survival of CMs derived from hiPSCs. IPSCs-sEVs can promote myocardial regeneration in MIRI, partly due to its ability to shuttle between cells, which contains a large amount of miRNA, especially miR-146a [102]. MiR-146a inhibits IRAK1 and TNF receptor-related factor 6 to reduce the activation of NF-κβ to increase cardiac function and reduce myocardial fibrosis after MIRI [103]. Furthermore, miR-21 has been proved to have beneficial effects on damaged myocardium [104,105]. MiR-21 reduces cardiomyocyte apoptosis by regulating the expression of PDCD4 and AKT pathways [106]. IPSC-sEVs are also involved in regulating signaling pathways such as WNT [107], which partially remuscularize the injured region, restore cardiac function, and reduce fibrosis in the infarcted hearts of rats by regulating actin cytoskeleton and immunogenicity. IPSC-sEVs have anti-apoptotic and antioxidant effects [108]. For example, iPSC-EVs can protect H9c2 cells from H2O2-induced oxidative stress by inhibiting the activation of caspase3/7. The intramyocardial injection of iPSC-sEVs before reperfusion can protect against MIRI. Furthermore, IPSC-sEVs deliver cardioprotective miRNAs, including nanog-regulated miR-21 and HIF-1α-regulated miR-210 [82]. Coronary heart disease (CAD) is caused by coronary artery stenosis or obstruction due to atherosclerosis. According to the current view, oxidative stress, endothelial dysfunction, and inflammation are the three key factors for the occurrence and development of CAD [109,110]. Many studies have focused on the use of natural drugs and biodegradable synthetic materials for scaffolds. However, recent studies have combined the use of EVs derived from iPSCs, providing a promising solution for vascular tissue engineering [111]. IPSC-sEVs participate in paracrine and autocrine communication between cardiovascular cells through miRNAs and other mediators [112]. EVs released from iPSCs have been shown to have myocardial protective effects, which can improve the survival rate of CMs. This process is achieved by inducing macrophage polarization and reducing the transcription level of protein kinase by miR-181b [113]. Wang et al. [114] pointed out that iPSC-sEVs can increase type III collagen and fibronectin, increase vascular permeability, optimize the vascular environment, and improve cardiac function. More and more studies have confirmed that EVs from mesenchymal stem cells (MSCs) are effective drug carriers for the treatment of CAD, but their application is hindered by donor variation and traditional tissue-derived MSC expansion limitations [102,115]. While small EVs prepared from standardized MSCs derived from iPSCs (iMSC-sEVs) have unlimited scalability and have the ability to target CAD therapy [116], some studies show that they have a better protein structure than iPSC-sEVs, providing more possibilities for the prevention and treatment of CAD [117,118]. The lost myocardium after MI is usually replaced by non-contractile scar tissue, which can lead to congestive heart failure (HF). As CMs are terminally differentiated cells with minimal regenerative capacity, heart transplantation is the gold standard for the treatment of HF, which faces the obstacles of the shortage of donor hearts, complications after transplantation, and the long-term failure of the transplanted heart [119]. Tian et al. [120] reviewed that the regulation of miRNAs rich in iPSCs-sEVs on Nrf2 and antioxidant proteins in the heart and brain mediates cardiac function and sympathetic excitation during HF. It is speculated that the targeted uptake ability of receptor cells can be increased when engineering exosomes with specific miRNAs or antagomirs is used to treat HF. Qiao et al. [121] confirmed that iPSC-sEVs alleviate cardiac dysfunction by regulating the Akt pathway through miR-21-5p. In recent years, lncRNA has become a key regulator of biological processes involved in the progression of HF [122]. Viereck et al. [123] focused on the potential of highly conservative lncRNAH19 and found that its expression was down-regulated in HF. The iMSC-sEVs also play an important role in heart failure. Hou et al. [124] found that iMSC-sEVs protected endothelial cells from oxidative stress by activating the Akt/Nrf2/HO-1 signaling pathway in HF models. It has been confirmed that iPSC-sEVs promote heart repair after MI, which means they are superior to iPSCs [21]. EVs provide a feasible alternative cell-free therapy in iPSC medicine. Because of their low immunogenicity, they does not seek a host immune response, so there is no need to match donor and recipient [125,126]. However, there are still many problems with the treatment of EVs, such as their production, stability, half-life, and delivery efficiency. Therefore, it is particularly necessary to comprehensively analyze the chemical and functional characteristics of the EVs and to study their physiological characteristics, diversity, and transport mode. Chandy et al. [127] drew a map of microRNAs in cardiac extracellular secretions derived from human iPSCs. Human iPSCs were differentiated into iPSC-CMs, iPSC-ECs and iPSC-CFs, and the EVs were isolated. Their miRNA content was sequenced and compared with the source cells. Interestingly, only a part of cells miRNAs was found to be secreted in the EVs and was cell-specific. A comparative analysis showed a decrease in miR-22 expression in exosomes from cardiac-fibroblast-derived hiPSCs compared with dermal-fibroblast-derived hiPSC exosomes [27]. Future research needs to conduct in-depth sequencing analyses to understand the role of other non-coding RNAs in mediating the improvement of cardiac function. In addition, since iPSC-sEVs carry miRNA and each miRNA has multiple target genes, it is also necessary to prevent the occurrence of adverse non-target effects. IPSCs differentiate into CMs, which are equivalent to fetal CMs, and lack the electrophysiological and ultrastructural characteristics of mature CMs [128,129], such as fully functional seromuscular reticular structure and transverse canal system. After differentiation, the maximum contractility was lower, calcium storage and circulation decreased, and the mitochondrial function was immature [130]. In addition, the EVs’ function was also affected. The current research is mainly focused on using the paracrine function of iPSCs to play a role, rather than ensuring they differentiate into therapeutic cells [131,132,133]. Even so, the content and level of iPSC-sEVs will change after serum starvation and hypoxia treatment [134,135], which makes clinical treatment more difficult. Nachlas et al. [136] highlight the importance of a 3D culture environment to influence cell phenotype and function. In addition, 3D-printed cardiac patches and personalized hydrogel can help iPSCs’ further maturation [136,137,138]. Furthermore, gene editing technology can be used to achieve the richness of iPSC cells [26,139]. For instance, CRISPR/Cas9 is used for gene editing based on homologous recombination to obtain mutation-corrected iPSCs so that the pathogenic mutation can be corrected without preserving the genetic footprint [26]. However, if these molecules are to be used in clinical therapy, the standard procedures for purifying exosomes need to be optimized. Overall, small EVs play critical roles in cell–cell communication through endocytosis, phagocytosis, and membrane fusion. EV uptake was found to correlate with intracellular and microenvironmental acidity [140,141], suggesting that the microenvironment influences the delivery efficiency of EVs. In the case of factors operating at the intracellular level, delivery into the correct cellular compartments while maintaining the stability, integrity, and biological potency of these factors remains challenging. Furthermore, the content of exosomes can be modified by stress preconditioning [142], serum deprivation [143], or the genetic modification and epigenetic reprogramming of iPSCs [144,145,146]. Recent studies show that exosomes can cross the BBB (blood–brain barrier), and a leaky BBB state in mental disorders (such as stress, depression, and schizophrenia) may be initiated by exosomes released from cells being influenced by this disease state [147]. Chronic stress can cause immune disorders and inflammatory responses. Moreover, exosomal components are strongly influenced by inflammatory signals such as LPS, tumor necrosis factor (TNF)-α [148], and interferon (IFN)-γ [149]. They could modulate the therapeutic efficacy via the regulation of differential gene expressions [150,151] and largely influence the effect of iPSC-sEV treatment. The potential of IPSC-sEVs in the treatment of CVD is exciting. Compared with cells, EVs cannot self-replicate, which reduces tumor toxicity. The future application of IPSC-sEVs is likely to be combined with other drugs or systems. With the development of front-line technologies, including scRNA-seq, multi-omics, genome editing, and machine learning, they possess great potential for the analysis of exosome contents and their transfer specificity [152]. Exosomes can be endogenously modified by the genetic modification of production cells to produce cells overexpressing desired therapeutic substances that are eventually incorporated into exosomes upon secretion [153]. Alternatively, exosomes can be loaded exogenously using various techniques, such as sonication [154], membrane permeabilization [155], and extrusion [156]. Therefore, in order to ensure their safety and effectiveness, a number of challenges must be addressed, including the characteristics of the content, specific molecular mechanisms for disease treatment, and biosafety as a drug delivery system. In short, more basic research and new technologies are needed to fully realize the therapeutic potential of exosomes derived from iPSCs and accelerate their clinical application.