Gene Set Enrichment Analysis and western blotting were performed to explore the downstream signaling pathway. S100A10 was significantly upregulated in gastric cancer. Its expression was associated with poor survival. S100A10 increased glucose consumption, lactate production, and the switch from oxidative phosphorylation to aerobic glycolysis. S100A10 promoted malignant proliferation and suppressed cell apoptosis in gastric cancer. S100A10 activated the mTOR pathway by interacting with annexin A2 (ANXA2) to accelerate tumor glycolysis, resulting in tumor malignant progression. S100A10 contributed to aerobic glycolysis and accelerated malignant growth by modulating the Src/ANXA2/AKT/mTOR signaling pathway. Thus, S100A10 may have pivotal roles in gastric cancer.S100 calcium-binding protein A10 (S100A10) is crucially involved in the tumorigenesis of multiple malignant tumors. Reprogrammed glucose metabolism is emerging as a hallmark of various human cancers. However, the function of S100A10 in aerobic glycolysis is unclear. The expression of S100A10 was analyzed using the Oncomine database, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and the UALCAN cancer database. Prognostic analysis was performed using the Kaplan–Meier Plotter. The correlation between S100A10 and key glycolytic factors was assessed by GEPIA. The glycolysis level was examined by determining glucose consumption, lactate production, adenosine triphosphate production, cellular oxygen consumption rate, and extracellular acidification rate. Cell apoptosis was investigated by flow cytometry. Colony formation and BrdU assays were performed to detect cell proliferation. A subcutaneous xenograft mouse model was established to evaluate the effects of S100A10  Gastric cancer (GC) is the fifth most frequently diagnosed cancer and the third leading cause of cancer-related deaths worldwide . GC, a hThese traditional classifications have not considered the molecular heterogeneity of GC and remain inadequate for individualized precision treatment . Lei et GC treatment and survival are largely dependent on the tumor stage. GC staging is divided into four stages according to the tumor node metastasis (TNM) classification system. The TNM staging system has fully considered the extent of the primary tumor (T), regional lymph nodes (N), and distant metastases (M) and provides a “stage grouping” based on T, N, and M . The TNMUncontrolled proliferation and evasion of apoptosis are essential features of malignant tumors . Tumor cIn silico analysis has revealed that S100 proteins are upregulated in GC  is a member of the S100 protein family located in the plasma membrane. S100 proteins regulate a broad range of biological functions, such as phosphorylation regulation, maintenance of cell motility, and transduction pathway signaling . Recent ed in GC . Typicaled in GC  is impored in GC . Spijkered in GC . Moreoveed in GC . Interesed in GC . Thus, wTo explore this hypothesis in the current study, we explored the function of S100A10 in GC aerobic glycolysis and investigated the underlying molecular mechanisms. To the best of our knowledge, this is the first evaluation of the biological functions and mechanisms of S100A10 involved in aerobic glycolysis in the progression of GC.1 is a cancer microarray database and web-based data-mining platform  is directly proportional to the significance level of upregulation or downregulation, respectively.Oncomineplatform . It was 2 is an interactive web application for gene expression analysis based on RNA sequencing data of 9736 tumors and 8587 normal samples from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases .To determine the expression of S100A10 in GC tissues, 375 GC and 32 normal tissue samples in which S100A10 was expressed were collected from the TCGA database4 is an interactive and user-friendly web portal to perform in-depth analyses of TCGA gene expression data  GEO databaseP-value, and false discovery rate (FDR) were used to sort the pathways enriched in each phenotype.GSEA is a computational analysis that is valuable in revealing the collective behavior of genes in various states of health and disease . In this2 at 37°C. All cell lines were authenticated by morphological observation and mycoplasma testing. Cells were grown for no more than 10 passages in total for any experiment.Human GC cell lines that were used included AGS (well-differentiated gastric cancer cell line), HGC-27 (undifferentiated gastric cancer cell line), and MKN-45 (poorly differentiated gastric cancer cell line). They were purchased from the American Type Culture Collection  and the Chinese Academy of Sciences . AGS was cultured in F12K medium supplemented with 10% fetal bovine serum . The other two cell types were incubated in RPMI-1640 medium supplemented with 10% FBS. Cells were maintained in a humidified atmosphere of 5% COCATCATCACCATCACCATCCATCTCAAA TGGAACACG-3′) and reverse (5′-ATCTCGAGCTAATGGTGATGGTGATGATGCTTCTTTCCCTTCTGCTTCATG-3′) primers. The underlined nucleotides represent the sequence encoding the 6 × His His tag fused in frame with S100A10. The amplified sequences were inserted into the pcDNA3.1 (+) (pcDNA3.1 (+)-S100A10) expression plasmid as described previously  tag was amplified by PCR with forward  were transiently transfected into GC cells using Lipofectamine 3000 . The transfection was performed 12 to 16 h after cells were seeded into 6- or 12-well plates with a cell density of 2 or 1 × 105′-CCUGGACCAGUGUAG AGAUTT-3′ and 5′-AUCUCUACACUGGUCCAGGTT-3′), si-NC (5′-UUCUCCGAACGU GUC ACGUTT-3′ and 5′-ACGUGACACGUUCGGAGAATT-3′). The si-S100A10 (60 nM) was transfected into cells using Lipofectamine 3000 according to the manufacturer’s instructions.S100A10 siRNA si-S100A10) and respective negative control (si-NC) were purchased from GenePharma . The sequences are si-S100A10 (8 transduction units (TU)/mL. The infection rate of lentivirus was determined by fluorescence microscopy 72 h after infection. Puromycin (2 μg/mL) was added to the medium to kill the uninfected cells.The S100A10-silencing lentivirus (short hairpin [sh]-S100A10), S100A10-overexpression lentivirus (OE-S100A10), and negative control lentivirus (sh-NC or OE-NC) were constructed by Genecopoeia . GC cells were seeded in 6-well plates, grown overnight, and infected with lentivirus. The lentivirus titer was 1 × 10® qPCR RT Master Mix with gDNA Remover  according to the manufacturer’s instructions. RT-qPCR was performed using SYBR® Green Real-time PCR Master Mix (Toyobo) using the recommended thermal cycling settings of one initial cycle at 95°C for 60 s, followed by 40 cycles of 15 s at 95°C, 15 s at 60°C, and 45 s at 72°C. Gene expression was normalized to the expression of the housekeeping gene glyceraldehyde 3-phosphate dehydrogenase (gapdh). The primer sequences are listed in Total RNA was extracted using TRIzol reagent (Invitrogen). cDNA synthesis was performed using the ReverTra AceTotal protein was extracted from cells using RIPA Lysis Buffer  and protein concentration was measured using the BCA Protein Assay Kit . The proteins were separated by 10% SDS-PAGE and transferred to a polyvinylidene fluoride membrane. After blocking with 5% non-fat skim milk, the membrane was incubated with one of the following primary antibodies: 6 × His tag , S100A10 , Annexin A2 , phosphor (p)-Annexin A2 , Src , p-Src , AKT , p-AKT , mTOR , p-mTOR , 5′ adenosine monophosphate-activated protein kinase , p-AMPK , Glucose transporter 1 , LDHA , PFKFB3 , B-cell lymphoma 2 , GAPDH , and β-actin . S100A10-overexpression efficiency was determined using 6×. His tag or S10010 antibody. S100A10 antibody was used to detect knockdown efficiency. Protein bands were quantified using Image J software  and expression levels were normalized to the internal reference. The experiments were repeated at least three times.To examine the apoptotic effects of S100A10, GC cells transfected with siRNA or plasmids were grown in 6−well plates and incubated for 48 h. The apoptotic inducer tumor necrosis factor-related apoptosis-including ligand was added to the culture medium to a final concentration of 100 ng/mL for 24 h. The cells were collected by trypsin digestion in the absence of EDTA. Apoptosis was measured in the harvested cells using flow cytometry by the Annexin V-FITC Apoptosis Detection Kit  following the manufacturer’s protocol. Apoptosis rate (%) was calculated as the  × 100. The experiments were repeated at least three times.Cell proliferation was detected using a colony formation assay and Bromodeoxyuridine/5-bromo-2′-deoxyuridine (BrdU) assay. After transfection, 1000 cells were seeded in 6-well plates and grown for 2 weeks. The colonies were fixed, stained with 1% crystal violet, and counted to enumerate formative clones. The BrdU assay was performed as previously described . BrieflyFollowing transfection, cells were seeded into 6-well plates. Six hours later, the culture medium was replaced with complete medium and incubated for 48 h. Subsequently, the medium was collected to measure the glucose concentrations using a glucose assay kit  according to the manufacturer’s instructions. Glucose consumption was calculated as the difference between the original glucose concentration in fresh medium and the measured glucose concentration in the collected medium. All results were normalized to the corresponding protein concentration values. The experiments were repeated at least three times.Lactate production in the culture supernatant was evaluated using a lactate assay kit  according to the manufacturer’s instructions. All results were normalized to the corresponding protein concentration values. The experiments were repeated at least three times.The ATP production of GC cells was measured using an ATP assay kit  according to the manufacturer’s instructions. All results were normalized to the corresponding protein concentration values. The experiments were repeated at least three times.LDH activity was determined using an LDH assay (Nanjing Jiancheng Bioengineering Institute) in accordance with the manufacturer’s instructions. The values were normalized to the protein levels. The experiments were repeated at least three times.4 cells were seeded into an XF96 well plate and allowed to adhere. To measure the OCR (pMoles/min), oligomycin, carbonylcyanide-4-(trifluoromethoxy) phenylhydrazone (FCCP), rotenone and antimycin A were sequentially added to each well. For ECAR, glucose, oligomycin, and glycolytic inhibitor 2-deoxyglucose (2-DG) were sequentially injected. The experiments were performed in triplicate.OCR and ECAR were monitored using the XF96 Flux Analyzer  following the manufacturer’s instructions. Briefly, 1 × 10in vivo tumorigenicity, we established subcutaneous gastric cancer animal models. Firstly, we purchased S100A10-overexpression lentivirus (OE-S100A10) and negative control lentivirus (OE-NC) from Genecopoeia. The lentiviral overexpression system contained the enhanced green fluorescent protein (GFP) gene for tracking the infection efficiencies. HGC-27 cells were seeded in 6-well plates, grown overnight, and infected with lentivirus (OE-S100A10 or OE-NC). The infection rate of lentivirus was determined by fluorescence microscopy 72 h after infection. Green fluorescence of tagged GFP protein was monitored with excitation wavelength of 485 nm and emission wavelength of 525 nm in fluorescence microscopy. Successfully infected cells show green fluorescence under a fluorescence microscope. Puromycin was added to the medium to kill the uninfected cells, in order to ensure all cells were successfully infected with OE-S100A10 or OE-NC lentivirus. At last, fluorescence microscope was used to ensure that all cells were infected with lentivirus.To determine the 7) stably overexpressing S100A10 (OE-S100A10) or the corresponding control cells (OE-NC) were suspended in 200 μL PBS and subcutaneously injected into the right flank of 4-week-old BALB/c nude mice. After 3 days, the mice were randomly divided into rapamycin and PBS groups. Rapamycin was delivered by intra-peritoneal (i.p.) injection (100 μL) at 1.5 mg/kg/d body weight. The control group was administered 100 μL PBS. The tumor volumes were monitored every 5 days. The tumor volume was calculated as volume = (width2 × length) ÷ 2. After 35 days, the mice were sacrificed and the xenografts were removed for further study. The animal experiments were approved by the Shandong University Animal Care and Use Committee.Then HGC-27 cells  or GraphPad Prism 8.0 . Data from at least three independent experiments are expressed as mean ± standard deviation (SD). Differences between groups were analyzed using Student’s t-test (two-tailed). The correlation between genes was analyzed using Pearson’s correlation. The level of significance was determined with cut-offs at To assess the role of S100A10 in human carcinogenesis, S100A10 expression levels in various human cancers were analyzed using the Oncomine database. Compared to normal tissues, S100A10 was overexpressed in bladder cancer, brain cancer, breast cancer, GC, head and neck cancer, kidney cancer, leukemia, liver cancer, lymphoma, myeloma, pancreatic cancer, and prostate cancer . To furtConsistent with the results from the Oncomine and GEPIA databases, data from the TCGA database confirmed that the expression of S100A10 was elevated in GC samples compared to adjacent normal tissues . MoreoveTo determine the potential oncogenic effect of S100A10 in GC, we examined the normalized data from GEO datasets GSE35809. S100A10 showed maximum expression in the metabolic subtype . GSEA waThere was no evidence of S100A10 involvement in cancer glycolysis. Therefore, we aimed to explore the role of S100A10 in GC glycolysis. A correlation analysis was performed between S100A10 and glycolytic components, such as glucose transporter (SLC2A1 and SLC2A2), glycolytic enzymes , the key regulatory enzyme for the tricarboxylic acid (TCA) cycle (IDH1), and lactate generation catalytic enzyme (LDHA), using data from the GEPIA database. All the glycolytic components analyzed were closely related to S100A10 , indicatWe next asked whether S100A10 promotes glycolysis in GC. First, the protein expression levels of S100A10 in GC cells were verified by western blotting . AccordiRT-qPCR was performed to investigate the changes in glycolytic components affected by S100A10. Consistently, S100A10-overexpressing cells exhibited increased GLUT1, GLUT4, LDHA, and PFKFB3 mRNA expression levels and decreased IDH1 mRNA expression levels, while S100A10 knockdown produced the opposite trend. Additionally, S100A10 had no remarkable effects on HK and PKM expression . CollectElevated glucose consumption, which leads to aerobic glycolysis, is considered an evolutionary advantage for cancer cells . GlucoseAerobic glycolysis markedly increases the lactate concentration. This produces an acidic microenvironment and drives cancer progression. A lactate assay kit was used to measure the production of lactate in GC. As shown in Most cancer cells are more likely to adopt a less efficient aerobic glycolysis for energy supply, which is critical for their rapid proliferation. Cellular ATP levels were measured using an ATP assay kit. As shown in The effect of S100A10 on GC cell growth was examined by plate colony formation and BrdU assay in GC cells. Overexpression of S100A10 dramatically promoted GC cell proliferation and DNA synthesis activities, whereas knockdown of S100A10 significantly suppressed cell rapid growth . The colThe role of S100A10 in cell apoptosis was evaluated by flow cytometry. High S100A10 expression decreased the rate of apoptosis , while tThe results of GSEA using the TCGA database demonstrated that the mTOR signaling pathway was closely correlated with S100A10 expression. Previous studies reported that S100A10 is usually bound to its ligand ANXA2 to form the S100A10-ANXA2 complex . High exWestern blot analysis was performed. The phospho-Src (p-Src), phospho-ANXA2 (p-ANXA2), phospho-AKT (p-AKT) and phospho-mTOR (p-mTOR) expression levels were normalized to total Src, ANXA2, AKT and mTOR . Presently, the p-Src/Src, p-ANXA2/ANXA2, p-AKT/AKT, p-mTOR/mTOR ratios were increased in both AGS and HGC-27 cells after S100A10 overexpression , suggestGiven the molecular association of S100A10 with the mTOR pathway, we next explored whether mTOR mediates the facilitative effects of S100A10 on GC cell proliferation and glycolysis. A rescue experiment was performed to confirm that the inhibition of the mTOR pathway could abolish the promotion of glycolysis and the malignant phenotype of GC cells induced by ectopic S100A10 expression. In the experiment, we abolished the activity of mTOR with rapamycin (RAPA) and inhibited LDHA using GSK-2837808A (GSK) in GC cells. Glycolytic activity was examined. Rapamycin and GSK could significantly decrease cancer cell proliferation, glucose consumption, lactate production and LDH activity. As expected, rapamycin and GSK completely abrogated the effects of S100A10 overexpression on colony formation and aerobic glycolysis . Taken tin vivo, a subcutaneous tumor model was established in nude mice. First, we established HGC-27 cells that stably overexpressed S100A10 (OE-S100A10) and the corresponding control cells (OE-NC). After lentiviral infection, all HGC-27 cells expressed green fluorescent protein (GFP), suggesting successful cell infection  can be found in the article/The animal study was reviewed and approved by Ethical Committee on Scientific Research of Shandong University Qilu Hospital.YL, X-YL, R-CZ, XG, B-YJ, and BL performed all experiments. YL, L-XL, and YS performed data analysis. YL wrote the manuscript. X-LZ, Y-QL, and YL designed the overall project and revised the manuscript. All authors have read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


UBE3A gene, is a multifaceted ubiquitin ligase that controls diverse signaling pathways involved in cancer and neurological disorders. The oncogenic role of E6AP in papillomavirus-induced cancers is well known, with its action to trigger p53 degradation in complex with the E6 viral oncoprotein. However, the roles of E6AP in non-viral cancers remain poorly defined. It is well established that loss-of-function alterations of the UBE3A gene cause Angelman syndrome, a severe neurodevelopmental disorder with autosomal dominant inheritance modified by genomic imprinting on chromosome 15q. Moreover, excess dosage of the UBE3A gene markedly increases the penetrance of autism spectrum disorders, suggesting that the expression level of UBE3A must be regulated tightly within a physiologically tolerated range during brain development. In this review, current the knowledge about the substrates of E6AP-mediated ubiquitination and their functions in cancer and neurological disorders is discussed, alongside with the ongoing efforts to pharmacologically modulate this ubiquitin ligase as a promising therapeutic target.The HECT (Homologous to the E6-AP Carboxyl Terminus)-family protein E6AP (E6-associated protein), encoded by the  Ubiquitination is a major posttranslational modification which governs the fates of modified protein substrates, i.e., changes in stability, subcellular localization and enzymatic activities . The mul2+-binding N-terminal ) domain and a catalytic HECT domain of ~350 amino acids at the C terminus  oncoprotein E6 mediates degradation of the tumor suppressor protein p53 by activating this E3 , which iHPV induces a variety of human cancers such as cervical and head and neck cancers. The involvement of E6AP in viral oncogenesis was first established in HPV-associated cervical cancer ,25. The Chronic inflammation from hepatitis C virus (HCV) infection leads to hepatocellular carcinoma . E6AP prPML was first identified as a gene fused with the retinoic acid receptor (RAR) gene in acute promyelocytic leukemia patients with  chromosomal translocation. The fusion gene product suppresses the wild type tumor suppressor PML in a dominant negative fashion .,32.20,32 fashion ,34. Furt fashion . PML for fashion . The PML fashion ,48,49,50 fashion ,47,49,50Ube3a gene can attenuate murine B-cell lymphomagenesis driven by the Eμ (immunoglobulin enhancer)-Myc transgene with concomitant upregulation of PML [Hyperactivation of the E3 ligase activity of E6AP is evident in Epstein–Barr virus-associated Burkitt’s lymphoma. Approximately 60% of Burkitt’s lymphomas show downregulation of PML expression correlated with high levels of E6AP . Hemizygn of PML , recapitKip1, which is characteristic in aggressive and late stages of prostate cancer [E6AP functions as a transcriptional co-activator of AR, and plays an oncogenic role in prostate glands ,51. E6APe cancer ,52. A ree cancer . Among tINK4A. E6AP binds to the transcription factor E2F1 as a co-factor, repressing the expression of CDC6, a key transcriptional repressor of the INK4/ARF locus encoding p16INK4A and p14ARF. Therefore, downregulation of E6AP in NSCLC results in the decrease in p16INK4A expression. NSCLC patients with the characteristic of E6AP-low/CDC6-high/p16-low exhibit reduced overall survival. Furthermore, this characteristic is associated also with KRAS mutations in lung adenocarcinomas, implying a prognostic value of E6AP-low/CDC6-high/p16-low in the adenocarcinoma subtype of NSCLC [In non-small cell lung cancer (NSCLC), E6AP may exert a tumor suppressive function . E6AP exof NSCLC .E6AP acts as a transcriptional co-activator, promoting the transactivation by ER-α and PR, as well as AR . E6AP coUBE3A locus are linked with AS and chromosome 15q11.2–q13.3 duplication syndrome (Dup15q) [E6AP/UBE3A is widely known for its involvement in neurodevelopmental disorders. Genetic alterations in the (Dup15q) . IdentifUBE3A gene dosage is critical for neuronal development. Loss of neuronal UBE3A expression results in AS, while increased dosage of the gene is associated tightly with autism spectrum disorders (ASD)  . The UBE neurons ,71. This neurons . Conseque of ASD   is also important for the induction of LTP and synaptic plasticity. SK2 has been shown to undergo E6AP-mediated ubiquitination. In response to N-methyl-D-aspartate (NMDA) receptor activation, SK2 channels are activated. E6AP ubiquitinates SK2 to promote internalization of the channel. asticity . Ephexinasticity . Epilepsasticity . Alteredasticity ,86. Decrdel mice , and tredel mice . HoweverUBE3A-deficient mice have elevated levels of BMAL1 accompanied by impaired circadian rhythm [Sleep disturbances are reported in 75% of AS patients . Brain an rhythm .It has been demonstrated that E6AP activates the Wnt signaling pathway with stabilization of β-catenin . Wnt sigUBE3A-deficient mice exhibit increased levels of Ring1B and H2A in cerebellar purkinje neurons, suggesting its involvement in the development of AS neuronal deficits.Among the targets of E6AP that are controlled at the transcriptional level are the E3 ligase Ring1B . It inteESR2 gene encoding ER-β [E6AP also activates the transcription of the ing ER-β . ESR2 ising ER-β ,100. ESRing ER-β ,102. Oveing ER-β .26S subunit, non-ATPase 4 (PSMD4), is a subunit of the 26S proteasome and an E6AP substrate . The ubiUBE3A dosage. Administration of an RA antagonist or overexpression of UBE3A recapitulated the synaptic defects in ASD, while these defects were rescued by administration of RA [Xu et al., identified ALDH1A2, the rate-limiting enzyme of retinoic acid synthesis to be negatively regulated by E6AP. RA-mediated synaptic plasticity is altered with excessive on of RA .Ptpa gene or pharmacological inhibition of PP2A can ameliorate the defects in dendritic spine maturation of the AS model neurons, suggesting the significance of the E6AP-PTPA-PP2A pathway in AS pathophysiology.A recent study identified phosphotyrosyl phosphatase activator (PTPA), an activator of protein phosphatase 2A (PP2A), as a substrate of E6AP-mediated ubiquitination . NeuronsHECT E3 ligases are attractive therapeutic targets because of their involvement in a variety of human diseases. However, the efforts to develop small molecule inhibitors of HECT E3s are still in their infancy. The complexity of ubiquitination reactions and weak interactions between E3s and their substrates pose a challenge in identifying inhibitors of HECT E3s by high-throughput screens ,122. SmaHPV-induced cancers are still highly prevalent. Although the HPV vaccines have been widely introduced, it will take decades for their preventive effects against cancers to become dominant. Thus, target-based therapies against HPV-induced cancers are still in critical need. Disruption of the E6AP–E6-p53 complex serves as an attractive therapeutic target, as it would ultimately re-activate p53, leading to growth arrest and apoptosis of HPV-transformed cells.The crystal structure of E6AP-E6-p53 ternary complex was identified by Zapien et al. . This stMutagenesis of critical residues at the E6–p53 interface abrogates p53 degradation. According to the structural model, p53 is bound on a cleft spanning both the N-terminal and C-terminal domains of E6 . N-termiThe LxxLL-containing alpha helix of E6AP within the HECT domain binds to a hydrophobic binding groove in E6 . This biOther approaches to inhibit E6 activity include peptides that interact with the E6AP-binding groove . IntraceBiochemical and structural analyses of E6AP have shown that the fully active form of E6AP is a trimer, and E6 oncoprotein promotes the trimerization. The interaction between the Phe727 residue in the HECT domain of E6AP and a hydrophobic pocket of E6 is critical to the formation of this trimer. N-acetyl phenylalanine blocks E6AP trimerization by substituting Phe727 and inhibits its E3 activity at a high concentration (Ki = 12 mM) . AnotherCurrent therapies for AS are only directed toward mitigating symptoms, such as anti-seizure medications and physical therapies. There have been multiple approaches to develop mechanism-based therapies for AS .UBE3A in AS with mutations or deletions on the maternal allele. Several topoisomerase inhibitors, including topotecan, have been demonstrated to inhibit the transcription of the nuclear-localized long non-coding RNA Ube3A-ATS and allow the expression of UBE3A from the paternal allele [UBE3A regulation are encouraging for the future development of drugs that can unleash expression of the imprinted UBE3A allele.Efforts have been ongoing to reverse the paternal silencing of l allele . Althougl allele ,142, theUBE3A allele in neurons, and ameliorate some cognitive deficits  in AS model mice. However, the ASO shows no effects on other behavioral defects [Antisense oligonucleotides (ASO) offer an approach for gene therapies with high specificity, while the delivery of nucleotides remains challenging. ASO targeting Ube3a-ATS can effectively unsilence the paternal  defects . RecentlUBE3A promoter or repression of UBE3A-ATS using artificial transcription factors is another feasible strategy. An artificial transcription factor, TAT-S1, which represses the locus encoding UBE3A-ATS, has been shown to increase Ube3a expression throughout the brain of AS model mice [An alternate approach to unsilence the paternal allele was to provide dietary supplements of methionine to increase methylation, thereby repressing the transcript which includes UBE3A ATS. However, two clinical trials with methionine supplementation reported no significant difference in the clinical outcome between the control and the treatment groups ,145. Fordel mice .Ube3a-deficient mice, whereas there were no observed changes in motor deficit or ultrasonic vocalizations [UBE3A-deficient mice is apparently associated with motor dysfunction and deficits in LTP, fear conditioning and memory, which could be restored by the mTORC1 inhibitor Rapamycin as well as the mTORC2 activator A-443654 [Several experimental studies evaluated the effects of therapeutic interventions of effectors downstream of UBE3A in AS models. Reducing the expression levels of ARC alleviated audiogenic seizures in izations . Excessiizations . Levodopizations . A cliniizations ,116,149.izations ,150. HypA-443654 .It has been shown that E6AP regulates mTORC1 signaling by targeting p18, a subunit of the Ragulator complex . HyperacTherapeutic targeting of E3 ligases requires a multi-faceted approach including comprehensive profiling of the ubiquitination substrates, thorough analyses of the enzyme structures and efficient development of small molecule modulators. In this review, we have discussed the roles of E6AP/UBE3A in the pathophysiology of cancers and neurodevelopmental disorders, and highlighted the E6AP-substrate interactions and downstream pathways that could be therapeutic targets. With the development of novel substrate profiling technologies such as Orthogonal Ubiquitin Transfer , more in


Background: Complement C4 gene copy number variation plays an important role as a determinant of genetic susceptibility to common diseases, such as systemic lupus erythematosus, schizophrenia, rheumatoid arthritis, and infectious diseases. This study aimed to develop an assay for the quantification of copy number variations in the C4 locus. Methods: the assay was based on a gene ratio analysis copy enumeration (GRACE) PCR combined with high resolution melting (HRM) PCR. The test was optimized using samples of a known genotype and validated with 72 DNA samples from healthy blood donors. Results: to validate the assay, standard curves were generated by plotting the C4/RP1 ratio values against copy number variation (CNV) for each gene, using genomic DNA with known C4 CNV. The range of copy numbers in control individuals was comparable to distributions observed in previous studies of European descent. Conclusions: the method herein described significantly simplifies C4 CNV diagnosis to validate the assay. C4 is an essential component of the complement system, acting as an effector protein in the activation of the classical and lectin pathways as a subunit of the C3 and C5 convertases [The complement system is a key element of innate and acquired immunity, and acts as the first line of host defense. vertases . C4 gene is located on the long arm of human chromosome 6 (6q21.3) in the major histocompatibility complex (MHC) class III region. This gene has two paralogs C4A and C4B, sharing 99% sequence identity, each of which is polymorphic in itself. These paralogs have different functional activities and affinities to antigenic surfaces. C4A forms a covalent amide bond with antigens containing amino groups. On the other hand, C4B forms covalent ester bond with targets containing hydroxyl groups. C4A participates also in the withdrawal of immune-complexes through CR1 binding. On the contrary, C4B functions as the main cofactor in the C3 and C5 convertases and the formation of the membrane attack complex [The some 6 6q1.3 in thComplement C4 locus exhibits an unusual, complex pattern of genetic diversity, where nonsynonymous SNPs affect protein structure, and insertion-deletion polymorphisms cause frameshifts and premature stop codons. Additionally, C4 genes harbor polymorphic endogenous retrovirus insertions (HERV-K) that influence mRNA transcription efficiency. Lastly, a complex array of CNV in both C4A and C4B genes in the region as a result of deletions , duplications, and triplications, among others, gives rise to at least 22 haplotypes that include a complex range of genomic structures [The ructures  . The remaining 24% of the C4 genes do not have this retrovirus and are known as short C4 genes (C4S). A wide variation in these polymorphisms according to human populations has been described [C4 genes. The number of C4A gene copies varies between zero to five; for C4B between zero to four and for C4S and C4L genes, respectively, between zero to five copies [The total number of 4B genes . C4 diveescribed . Approxie copies  , gene copy numbers have been associated with disease susceptibilities or differential immune responses. As a case in point, C4 genes with low copy number are associated with increased predisposition to systematic lupus erythematosus (SLE), rheumatoid arthritis (RA), Grave’s disease, juvenile idiopathic arthritis [C4A deficiencies are correlated with immunization failure after Hepatitis B vaccination, acute otitis media, sinusitis and pneumonia [Finally, according to their clinical significance, genetic variations have been classified into three categories: benign, pathogenic, and variants of uncertain significance . Moreoverthritis , Schizoprthritis  or Alzherthritis . Additioneumonia ,13,14. Considering the above, different techniques have been used for CNV detection, such as RFLP, Southern blot, TaqMan ,15,16, mC4A, C4B, C4S, and C4L gene copy number polymorphisms.A new strategy, named Gene Ratio Assay Copy Enumeration (GRACE)-PCR was developed and validated for α-globin gene rearrangement detection. It is a simple, closed-tube assay that allows direct visual identification of copy number variations . TherefoInitially, primers at different concentrations were assayed. For the C4A/ RP1, C4B/ RP1 and C4L/ RP1 primer pairs, amplification of the reference gene RP1 was very efficient; thus, it was necessary to increase the concentration for the C4A, C4B and C4L primers. In contrast, for the C4S gene, it was necessary to double RP1 primer concentration in relation to C4S primers. DNA samples of known C4 DNA genotype  were useC4A short isoform. BS haplotype carrying only the C4B short isoform. AL haplotype carrying only the long C4A gene. BL haplotype carrying only the long C4B gene. The order is not determined and they are listed alphabetically. AS haplotype carrying only the All five pairs of primers successfully amplified the corresponding genes with dissociation of a single peak. The negative control produced no dissociation peak. The HRM assay resulted in two distinguishable peaks with melting temperatures described in C4/RP1 ratio against known target C4 gene copy numbers. For all reactions correlation coefficients were always greater than 0.90 . Linear functions were calculated by plotting the -dF/dT han 0.90 . C4 copyhan 0.90 A–D.C4 gene  was genotyped in a 48-well plate, including 19 unknown samples, four control samples with known C4 haplotypes and a negative control, all the samples were tested in duplicate. The range of C4 copy numbers in Spanish blood donors was similar to the distributions previously described in cohorts of individuals of European ancestry [The assay was validated with 72 DNA samples from anonymous healthy blood donors. Each target ancestry . The disC4 copy number variation polymorphism, where the overall time of analysis is approximately 2 hours. The system consists of a combination of HRM with GRACE-PCR methods, which allow for detection and quantification of C4 gene copy numbers for the C4A, C4B, C4S and C4L isoforms, using the peak ratio between the C4 genes and a reference gene that correlates with the variation in the number of copies. A concurrent analysis of the standard curve with samples of known genotype increases result reliability with exact C4 gene copy number quantification. Additionally, because the change in peak heights was not linear, intra-assay standards were necessary [n = 76) displayed a normal C4 CNV distribution pattern ranging from 1–6 total copies, as has been previously described in other studies. A healthy control with complete deficiency of C4A and C4B components was found, which is very rare in this population. Previous studies have demonstrated that complete or partial deficiencies of C4B are associated with susceptibility to infectious diseases [C4A and C4B copy number variations are related to autoimmune disorders. This has led to the development and validation of a wide variety of assays to quantify the copy numbers of these genes and establish disease associations with C4 CNV in genetic epidemiological studies.We describe a widely accessible procedure to study ecessary . Analyzediseases . AdditioHBB) gene. They detected 44 distinct pathological genotypes, resulting in a primary, quick, sensitive, specific and cost-effective screening test. The system herein described for C4 CNV diagnostics, broadens HRM applications for gene dose quantification, increasing the range of laboratories that can perform C4 gene dosage. Turner et al. (2015),  developeC4A and C4B genes is clinically relevant, because there is a strong association between copy number variations and autoimmune disease susceptibility.According to Szilagyi et al. (2006)  quantifiC4 genotype were used. Samples were obtained from subjects who deposited their DNA in the International Histocompatibility Working Group DNA Bank (IHWG) . Samples were selected to represent all C4 possible copy number variations (CNV) from 0 to 6 copies and different haplotypes  was selected as an endogenous reference gene (located at 6p21.33). In a diploid genome it is always present in two copies, acting as normalizing gene. The RP1 gene has no known sequence polymorphism or duplicated regions in the human genome [The single-copy gene serine/threonine kinase 19  (http://www.bioinformatics.nl/cgi-bin/primer3plus/ primer3plus.cgi). Primers were selected to generate products with different melting temperatures, ranging approximately 3 to 5 °C, with similar annealing temperatures and minimal homology with each other. All primers were verified for specificity using NCBI  Primer BLAST program (http://www.ncbi.nlm.nih.gov/ tools/primer-blast). High performance liquid chromatograph (HPLC) purified primers were commercially synthesized . Primer sequences are presented in Primers for escribed . ForwardTo limit amplification saturation during the PCR’s exponential phase, reactions of 24, 26, 28 and 30 cycles were performed. Thus, ensuring the amount of each PCR product matched the one present in the analyzed sample to avoid an increase in initial copy number .RP1; C4B-RP1; C4S-RP1 and C4L-RP1. All reactions were performed in a final volume of 12 µL, containing 10 ng of genomic DNA, 6 µL of Precision Melt Supermix , and the following primer pairs . Each plate contained four control samples for result validation and a standard calibration curve. All samples were tested in duplicate on at least three different days. The run assay had four HRM- GRACE-PCRs each with two primer pairs, C4A-er pairs . Final vC4 vs. RP1 peak ratio values against CNV for each gene  was used as standard (To calculate the CNV of genomic DNA samples, a standard curve for each of the target genes was performed. Curves were generated by plotting ach gene . To ensustandard .C4 gene and RP1 maximum peak height value. This resulted in a plot in which the peak heights between RP1 and C4 melting regions were dependent on C4: RP1 gene copy number ratio (The ratio was calculated by dividing er ratio . For unkC4 and RP1 genes is proportional to the height of the peak on the -dF/dT versus temperature plots. In addition, an internal control was conducted for each sample from an individual, where the sum of C4A copies plus the C4B copies should equal the sum of C4L copies plus C4S copies. The intra-assay coefficient of variation was determined by triplicate testing of the control and donor samples. Data acquisition and analysis were performed using Illumina’s Eco Real-Time PCR System software EcoStudy version 5.0 and Microsoft Office Excel. The amount of PCR amplification from C4 genes’ CNVs. In conclusion, the assay developed in this study offers an attractive alternative for rapid, sensitive and specific quantification of


Bovine rotavirus A (RVA), a major causative pathogen of diarrhea in dairy and Japanese beef calves, has led to severe economic losses in numerous countries. A dual genotyping system based on genomic segments encoding VP7 (G genotype) and VP4 (P genotype), comprising the outer layer of the virion, has been used to understand the epidemiological dynamics of RVAs at the national and global levels. This study aimed to investigate occurrence frequency of G and P genotypes for multiple bovine RVAs from calf diarrheic samples collected in Japan from 2017 to 2020. After we produced anti-bovine RVA immunoglobulin yolks (IgYs) from hens immunized with the two RVAs with different genotypes (G6P[5] and G10P[11]) selected on the basis of the current epidemiological survey, we investigated cross-reactivity against bovine RVAs with different G and P combinations owing to establish a useful strategy to protect calves from RVA infections using the two IgYs. Consequently, the two produced anti-bovine IgYs showed strong cross-reactivity against bovine RVAs with the same G and/or P genotypes in neutralization assay, respectively. Therefore, our data suggest the possibility of a passive immunization to protect calves from a bovine RVA infections epidemic in Japan via oral administration of the two IgYs into calves. The findings presented herein will provide important information that IgY is one of the effective tools to prevent infections of various pathogens. Escherichia coli, Cryptosporidium spp., and Eimeria spp. ) and SMN35 (G6P[5]), based on our current survey described above, as antigens for the production of anti-bovine RVA IgY, according to the methods described previously . Prior teviously . The antTen bovine RVA strains with different G and P genotypes  have been used in neutralization assay . Six bov5 cells/mL) were incubated at 37 °C for 72 h to prepare a confluent monolayer in glass tubes. IgY samples were heat-inactivated at 56 °C for 30 min and then diluted serially twofold from 1:10 with serum-free EMEM containing 1.5 µg/mL trypsin. The diluted IgYs were mixed with an equal volume (500 µL) of virus solution containing 200 TCID50 of each bovine RVA strain, respectively. The mixture was incubated at 37 °C for 1 h. After incubation, 100 µL of the mixture at each dilution were added in quadruplicate to a tube (4 tubes per dilution) containing a confluent MA-104 cell monolayer. IgY-virus mixture was allowed to adsorb at 37 °C for 90 min. The culture was fed with serum-free EMEM containing 1.5 µg/mL trypsin and then incubated at 37 °C for 7 days. The end-point titers were calculated according to the Reed and Muench method, with four replicates for titration –P[31]) according to the cutoff value of 80% at the nucleotide level . As a rep < 0.05) in the frequency of occurrence of G and P genotypes according to cattle type. Briefly, G6P[5] and G6P[11], and G6P[5] and G10P[11] were the most predominant in Holsteins and F1 hybrids. In addition, all of the bovine RVAs (100%) detected in Japanese beef cattle had the G6P[5] genotype.As a whole, the frequencies of occurrence of G and P genotypes among 99 bovine RVA strains used in this study were 55 for G6P[5] (56%), 21 for G6P[11] (21%), 13 for G10P[11] (13%), 5 for G6P[x] (5%), 3 for G10P[x] (3%), and 2 for GxP[11] (2%) . FurtherAnti-SMN35 and OKY31 IgYs, and control IgY were partially purified from egg yolks from chickens immunized with two bovine RVAs, and culture medium from mock-infected MA-104 cells, respectively, and measured their protein concentrations using Bio-Rad protein assay. Protein concentrations of anti-SMN35 and OKY31 IgYs, and control IgY were recorded as 40.1, 53.4, and 30.3 mg/mL, respectively. Thereafter, the measured protein concentration of each IgY sample was adjusted with 10 mg/mL for the neutralization assay., homologous and heterologous with the two via neutralization assay , G6P[11] (21%), and G10P[11] (13%) have been widely distributed throughout Japan during 2017–2020. In addition, bovine RVAs with G6P[5] have been mainly identified in Japanese beef cattle. Moreover, bovine RVAs with G6P[11] and G10P[11], in addition to G6P[5], respectively, have been dominantly detected in Holstein and F1 hybrid cattle. The relationship between bovine RVA and cattle type might be closely associated with the breeding, feeding, and movement of cows, which depend on cattle type, and/or host-virus interaction. To clarify this possibility, further continuous surveillance is warranted on the spread of bovine RVAs in Japan.Several reports on the molecular epidemiology of bovine RVAs in calves distributed in Japan have been published so far ,43. A coIn the present study, we produced two different types of IgY based on our current surveillance for bovine RVAs distributed in Japan, and investigated cross-reactivity for bovine RVAs with several different G and P genotypes using the two IgYs. One antibody (anti-SMN35 IgY: G6P[5]) showed broad cross-reactivity against six bovine RVA strains with the same G6 genotype, but lower cross-reactivity (8- to >64-fold reduction) than those of the homologous neutralization antibody titers against bovine RVAs with different G genotypes. Another antibody (anti-OKY31 IgY: G10P[11]) highly cross-reacted with bovine RVAs with identical G and P genotypes, and did with bovine RVAs with the same P genotypes at the level of 4-fold reduction of the homologous neutralization antibody titers. In addition, our findings reveal that the two produced anti-bovine RVA IgYs have a potential to be a useful tool to control bovine RVAs in cattle herd dominantly circulating in Japan, because oral administration of antibody with neutralization antibody titers of over 320 can provide a sufficient passive immunization to calves as reported in previous studies ,45. FurtIn conclusion, we presented the current epidemiological dynamics of bovine RVAs using multiple diarrheic samples of calves collected in recent years. Our data demonstrated that bovine RVAs with multiple genotypes have been maintained and transmitted among herds from various cattle types. Moreover, order-made production of IgY based on the epidemiological survey can be a new strategy to control and prevent epidemic bovine RVAs. These insights would be useful for prompting an application of IgY to protect calves from enteric viruses other than hygiene management.


ATP8B1 is critical for maintaining the epithelium membrane stability and polarity. However, the prognostic values of ATP8B1 in colorectal cancer (CRC) patients remain unclear. We analyzed transcriptomics, genomics, and clinical data of CRC samples from The Cancer Genome Atlas (TCGA). ATP8B1 was the only potential biomarker of phospholipid transporters in CRC. Its prognostic value was also validated with the data from the Gene Expression Omnibus (GEO). Compared to the normal group, the expression of ATP8B1 was downregulated in the tumor group and the CRC cell lines, which declined with disease progression. The lower expression level of ATP8B1 was also significantly associated with worse survival outcomes in both the discovery samples (359 patients) and the validation samples (566 patients). In multivariate analyses, low ATP8B1 levels predicted unfavorable OS  and were associated with poor progress-free interval (PFI) . The pathway analysis results showed that the underexpression of ATP8B1 was negatively associated with phospholipid transport, phospholipid metabolic process, and cell-cell adherent junction and positively associated with the epithelial-mesenchymal transition in CRC. Our analysis suggests that ATP8B1 is a potential cancer suppressor in CRC patients and may offer new strategies for CRC therapy.Homeostasis of membrane phospholipids plays an important role in cell oncogenesis and cancer progression. The flippase ATPase class I type 8b member 1 (ATP8B1), one of the P4-ATPases, translocates specific phospholipids from the exoplasmic to the cytoplasmic leaflet of membranes.  Colorectal cancer (CRC) is the third most common cancer and the fourth leading cause of cancer-related deaths globally . Early dABCB4 or ATP11C (a member of P4-ATPases) is associated with liver oncogenesis [PLSCR1 expression (a member of scramblases) can inhibit tumor growth and proliferation [ATP8B1 has also been detected in CRC and hepatocellular carcinoma [ATP8B1 may be a novel oncogene suppressor in CRC patients. The correlation of ATP8B1 with the normal function of membrane phospholipids and proteins coupled with its underexpression could be a valuable indicator of unfavorable clinical outcomes of CRC patients.Membrane phospholipid homeostasis plays a vital role in several biological processes. This depends on three transporter families, including P4-ATPases (flippases), ATP-binding cassette (ABC) transporters (floppases), and scramblases . Decreasogenesis , 9. Upreferation . The genarcinoma . Howeverhttps://xenabrowser.net/datapages/). Gene expression was normalized to eliminate computational batch effects [https://www.ncbi.nlm.nih.gov/geo/) to validate the retrieved information. GSE39582 was measured using the Affymetrix Human Genome U133 Plus 2.0 Array. All the raw data for mRNA expression were normalized using the Limma R package and transformed into a log2 scale. The probe showing the highest expression level was selected for scenarios where two or more probes were annotated to one gene symbol. The tidy RNASeq and protein spectra data were obtained from Wang et al. [ATP8B1 expressions in 44 CRC cell lines by comparing the TCGA colorectal tumor and normal tissue samples. Informative data on gene mutations for KRAS, BRAF, and TP53 and microsatellite instability in TCGA were obtained from the Genomic Data Commons (GDC) through the TCGAbiolinks R package [The TCGA pan-cancer data for Toil RNA sequencing Recompute was downloaded from the UCSC Xena browser   was used to explore the ATP8B1expression level in previous studies [P value of 0.01, fold change of 1.5, and top 10% gene rank. The relationship between ATP8B1 expression and genomic details in CRC was displayed through the cBioportal  [ATP8B1 DNA methylation on MEXPRESS (https://mexpress.be/index.html) were determined between colorectal tumors and normal tissues [The Oncomine database  . Besides tissues . The resATP8B1 significantly related genes (217 genes) in TCGA and GSE39582 dataset were selected for Gene Ontology (GO) analysis using the clusterProfiler R package. The default-weighted statistic was considered significantly enriched at 1000 times permutations with P < 0.05. The results were generated using the clusterProfiler and ComplexHeatmap R package.Gene set enrichment analysis (GSEA) of TCGA colorectal data was performed using the clusterProfiler R package . The KyoP value < 0.05 was considered statistically significant. A two-tailed Wilcoxon test was used to determine significant differences between the subgroups. To analyze the survival differences, patients were categorized into a “high” or “low” group based on the ATP8B1 best-cutoff expression using the MaxStat R package  [ATP8B1 expression was the independent prognostic value in TCGA or GSE39582 datasets.All statistical analyses were performed using the R software 3.6.2. A tistics) . The KapA total of 925 patients were engaged in the prognostic study. The clinicopathological features, including gender, age, American Joint Committee on Cancer (AJCC) 7th edition staging, and mutational status of KRAS/BRAF/TP53, of discovery and validation sets, are shown in ATP8B1 genes were selected using univariate Cox regression duo with a significant P value of <0.01 , PFI (P < 0.001), and DSS  (P < 0.001) compared with the high-expression group  in the univariate Cox analysis (ATP8B1 level was associated with shorter OS with an adjusted hazard ratio (HR) of 1.512  and a worse PFI . Assessment of the OS and PFI subgroups of CRC patients was also performed. In CRC subgroup evaluation, the Kaplan-Meier curve results showed that gender , age , stages III-IV, KRAS mutation, KRAS wild type, BRAF wild type, and TP53 mutation in the low ATP8B1 expression group were closely associated with poor OS  and RFS (P = 0.003) as shown in Figures ATP8B1 expression was correlated with shorter RFS . This was after adjustment for stages III-IV vs. I-II and KRAS mutation status; however, it was not independent in OS  were highly enriched in high-expression ATP8B1 patients (ATP8B1 patients (ATP8B1 patients (ATP8B1 (Pearson's R ≥ 0.4 in TCGA and GSE39582), to explore the potential biological functions affected by ATP8B1 expression. Based on the cutoff criteria, 1023 and 485 genes were selected from the TCGA and GSE39582 datasets, respectively. The overlapped genes (217 genes) in the two datasets were selected for GO analysis. The results revealed that ATP8B1 expression was enriched in phospholipid transport, phospholipid metabolic process, and cell-cell adherent junction pathways . From the TCGA data, the BRAF mutant was more common in higher ATP8B1 expression cases , whereas the other molecular status (KRAS or TP53) did not show any difference. This highlighted that lower ATP8B1 expression may be associated with malignancy and poor survival rates in CRC patients.To explore the pathway changes in CRC influenced by patients . Similarpatients . We alsopatients . Further Figures  and 7. I Figures  and CMS4 Figures  mainly eATP8B1 expression in CRC and also reported its downregulation as an independent prognostic biomarker for unfavorable survival outcomes of CRC patients. In CRC samples and cell lines, both the RNA and protein expressions of ATP8B1 declined (Figures ATP8B1 expression was correlated with stage progression (Colorectal cancer is a heterogeneous disease classified into four molecular subtypes based on the large-scale gene expression analysis . This cl Figures  and S1D.gression .ATP8B1 expression was a prognostic factor for predicting worse CRC outcomes in stratified survival analyses of the advanced stage, older age, and other molecular features. In addition, TP53, KRAS, and BRAF influenced CRC patient outcomes [ATP8B1 have no prognostic value in the early stage or TP53 wild-type subgroup. This could be due to the higher expression of ATP8B1 in the early stages and TP53 wild type, which was considered a protective factor for prognosis (In this study, lower outcomes . It is nrognosis . Howeverrognosis . HoweverATP8B1 was abundantly expressed in the gastrointestinal tract, and its downregulated expression led to aberrant microvilli morphology [ATP8B1 mutation frequency at 6%, which was not correlated with the expression level in CRC patients (Figure ATP8B1 promoter sequence. Using the TCGA data, ATP8B1 promoter hypermethylation was not detected in the CRC samples (Figure ATP8B1 mutations and promoter hypermethylation inadequately explain the low ATP8B1 expression in CRC patients. Interestingly, chromosome 18q of most CRC patients has lost the diploid copy number where the ATP8B1 is located (Figure ATP8B1 expression might be due to genomic deletion; however, an in-depth analysis is needed to fully explore this mechanism.rphology . This harphology . Degradas Figure . Besidess Figure . Therefod Figure . A corred Figure . The majATP8B1 and is related to poor outcomes [ATP8B1 expression and low activity of phospholipid-related metabolism or transport pathways was essential for maintaining membrane phospholipid function (Figures 5ATP8B1-deficient cells [ATP8B1 expression group (ATP8B1 expression level in CRC (Figures ATP8B1 expression (ATP8B1 expression deficiency might lead to the abnormal distribution or metabolism of the membrane phospholipids and the malfunction of membrane junction proteins, thereby enhancing CRC progression. This study was limited by the lack of an antibody to verify protein expression of ATP8B1 in the CRC samples. Besides, mRNA expression is not a locally available clinical parameter due to the high cost of storage and fresh tissue processing. Other methods for detecting ATP8B1 protein expression in CRC should be explored. Moreover, superior results could be achieved with stable mRNA expression obtained from formalin-fixed, paraffin-embedded tissue samples at a low cost.Membrane phosphatidylserine is translocated by ATP8B1 from the outer layer to the inner layer of the cell membrane . This ploutcomes , 35. OurFigures 5. Besidesnt cells . During nt cells . Moreovent cells . In our on group . Similar Figures  and 7. Cpression . This stATP8B1 is associated with advanced stages, adverse molecular types, and poor outcomes in CRC patients. Moreover, ATP8B1 expression positively regulates phospholipid localization, metabolism, and intercellular adhesion function. These findings improve our understanding of malignant progression in CRC patients. Although the precise molecular mechanisms remain indefinite, ATP8B1 gene expression has shown great potential in predicting the prognosis and treatment of CRC patients.In conclusion, the downregulation of


NAA10 c.29A>G p.(D10G) exhibits normal intrinsic NatA activity and reduced monomeric NAA10 NAT activity, NAA10 c.32T>G p.(L11R) displays reduced NatA activity and normal NAA10 NAT activity. This study expands the scope of research into the functional consequences of NAA10 variants and underlines the importance of understanding the diverse cellular roles of NAA10 in disease mechanisms.The majority of the human proteome is subjected to N-terminal (Nt) acetylation catalysed by N-terminal acetyltransferases (NATs). The NatA complex is composed of two core subunits—the catalytic subunit NAA10 and the ribosomal anchor NAA15. Furthermore, NAA10 may also have catalytic and non-catalytic roles independent of NatA. Several inherited and de novo NAA10 variants have been associated with genetic disease in humans. In this study, we present a functional analysis of two de novo NAA10 variants, c.29A>G p.(D10G) and c.32T>G p.(L11R), previously identified in a male and a female, respectively. Both of these neighbouring amino acids are highly conserved in NAA10. Immunoprecipitation experiments revealed that both variants hamper complex formation with NAA15 and are thus likely to impair NatA-mediated Nt-acetylation in vivo. Despite their common impact on NatA formation, in vitro Nt-acetylation assays showed that the variants had opposing impacts on NAA10 catalytic activity. While  N-terminal (Nt) acetylation is a pivotal protein modification occurring in a majority of eukaryotic proteins, either co- or post-translationally, which is catalysed by a family of eight N-terminal acetyltransferases (NATs) named NatA to NatH ,2,3. TheNatA consists of the catalytic subunit NAA10 and the large auxiliary subunit NAA15 ,13,14. NNAA10 gene is essential for normal cell function, and dysregulation of NAA10 has been associated with several human cancers such as lung, breast, prostate and colon cancer -Ac-CoA  and acetylation buffer to a final volume of 25 µL. Negative control reactions contained either immunoprecipitated β-gal-V5 or no substrate peptide. Reactions were incubated at 37 °C for 30 min on a thermoshaker . To measure product formation, the reaction was quenched by transferring 23 µL of the reaction mixture onto P81 phosphocellulose filter discs . The filter discs were washed three times in 10 mM HEPES buffer (pH 7.4) and dried before adding them to 5 mL Ultima Gold F scintillation mixture (PerkinElmer). Product formation was measured by a TriCarb 2900TR Liquid Scintillation Analyzer (PerkinElmer). The two variants were tested in independent setups compared to the WT enzyme, thus explaining some variability in the relative activity of WT NAA10 towards different substrates.In vitro Nt-acetylation assays were performed as described . Triplic


Mal, which is associated with Toll-like receptor signaling and T cell differentiation. There were 28 upregulated genes. It is concluded that maternal influenza A virus infection impairs fetal thymic gene expression as well as restricting placental and fetal growth.Maternal influenza A viral infections in humans are associated with low birth weight, increased risk of pre-term birth, stillbirth and congenital defects. To examine the effect of maternal influenza virus infection on placental and fetal growth, pregnant C57BL/6 mice were inoculated intranasally with influenza A virus A/CA/07/2009 pandemic H1N1 or phosphate-buffered saline (PBS) at E3.5, E7.5 or E12.5, and the placentae and fetuses collected and weighed at E18.5. Fetal thymuses were pooled from each litter. Placentae were examined histologically, stained by immunohistochemistry (IHC) for CD34 (hematopoietic progenitor cell antigen) and vascular channels quantified. RNA from E7.5 and E12.5 placentae and E7.5 fetal thymuses was subjected to RNA sequencing and pathway analysis. Placental weights were decreased in litters inoculated with influenza at E3.5 and E7.5. Placentae from E7.5 and E12.5 inoculated litters exhibited decreased labyrinth development and the transmembrane protein 150A gene was upregulated in E7.5 placentae. Fetal weights were decreased in litters inoculated at E7.5 and E12.5 compared to controls. RNA sequencing of E7.5 thymuses indicated that 957 genes were downregulated ≥2-fold including  Maternal viral infections are recognized to have detrimental effects on the human fetus with serious consequences for the development and viability of the child . AnalysiMx gene [The effects of maternal influenza A virus infection of the health of pregnant females and their offspring have been investigated using susceptible mouse strains with mutations in the antiviral Mx gene . These sMx gene ,19,20,21Mx gene . In a CoMx gene .Our focus on the fetal thymus is based on previous experiments using a bovine virus diarrhea virus (BVDV) maternal infection model in cattle, in which significant changes in gene expression in the fetal thymus and spleen were found at different time points during gestation ,25. MoreMx−/−) mice were inoculated intranasally with influenza A virus A/CA/07/2009 pandemic H1N1 (influenza) or phosphate-buffered saline  at pre-implantation (E3.5) corresponding to the period prior to day 7 in humans, peri-implantation (E7.5) corresponding to days 7 to 9 in humans, and post-implantation (E12.5), corresponding to post-day 12 pregnancy in humans [To examine the effects of maternal viral infection on gene expression in the developing fetal thymus, pregnant C57BL/6 . Eight-week-old female and male C57BL/6 mice were obtained from Jackson Laboratories . Mice were provided with mouse chow and water ab libitum and housed in a temperature-controlled room on a 12 h light/dark cycle. Five female mice were housed in each cage and males were housed in individual cages. Females in proestrus were placed in a male’s cage in the afternoon and were examined for vaginal plugs the following morning. A gestational date of E0.5 was assigned to females with vaginal plugs.4 plaque forming units (PFU) in 25 µL. In a preliminary experiment, this intranasal dose caused transient weight loss, but no overt signs of disease or mortality in pregnant female C57BL/6 mice.A/California/07/2009 H1N1 pandemic influenza A virus was grown in embryonated chicken eggs and aliquots of the allantoic fluid containing virus was stored at −80 °C until used as inoculum. The inoculum was titrated on Madin-Darby canine kidney (MDCK-London) cells obtained from R.A.Bowen and the dose inoculated was determined to be 6.5 × 10n = 3), E7.5 (n = 4) and E12.5 (n = 5), or with 6.5 × 104 PFU influenza A virus  in 25 µL on E3.5 (n = 5), E7.5 (n = 5) and E12.5 (n = 5). Since a significant decrease in both fetal and placental weight was seen in the litters of females inoculated with influenza on E7.5 compared to controls, this time point was selected for additional maternal inoculations in Experiment 2. In Experiment 2, pregnant females were inoculated with PBS on E7.5 (n = 4) or with influenza A virus (n = 4). Female mice were weighed and observed for clinical signs of disease daily. On E18.5, females were anesthetized with 100 µg/kg ketamine + 10 µg/kg xylazine administered by intraperitoneal route, blood samples collected by cardiac puncture, and the mice were euthanized by cervical dislocation. The uterus was removed and placed into a sterile Petri dish. The individual fetuses and placentae from each litter were removed from the uterus and each of the fetuses and placentae weighed. Individual placentae were placed into microcentrifuge tubes, frozen on dry ice and stored at −80 °C for RNA extraction or fixed in 4% paraformaldehyde solution for histology. Fetal dissections were performed under a dissecting microscope . Fine scissors were used to incise the thorax of each fetus on ventral midline, and both lobes of the thoracic thymus were removed with forceps. Because of their small size, thymuses were pooled within each litter, placed in microcentrifuge tubes, frozen on dry ice and stored at −80 °C for RNA extraction. The size of fetal thymuses also limited the extraction of protein from the same tissue. Fetal lung lobes were similarly dissected, pooled within each litter, placed in microcentrifuge tubes, frozen on dry ice and stored at −80 °C for RNA extraction. Instruments were rinsed with 70% ethanol between thymus and lung sample collection and between fetuses.Mouse inoculations were performed in a biosafety cabinet. Pregnant females were anesthetized with 100 µg/kg ketamine + 10 µg/kg xylazine administered by intraperitoneal route. When the mice were immobile, they were held vertically and inoculated by intranasal route, i.e., the inoculum administered into both nares using a 200 µL pipettor  and sterile, filter pipet tip (Rainin 9930-384). The mice were wrapped in tissue to retain body heat, replaced in their cages and monitored until ambulatory. Pregnant females were inoculated with 25 µL of sterile PBS (sham-inoculated controls) on E3.5  and examined microscopically on a Nikon Eclipse 50i microscope . Sections were also scanned using Aperio Scanner  and the width of the decidua and the labyrinth plus chorionic plate measured at the widest (middle) part of the placenta using Aperio ImageScope version 12.3.2.8013 . ConsecuInfection of influenza A virus-inoculated females and the absence of infection in control females was confirmed by determining the antibody titer to A/California/07/2009 pdm H1N1 by hemagglutination inhibition (HI) .Myog) [Sry) was indicated by the amplification product (350 bp) and the amplification of Myog product (250 bp) confirmed amplification of mouse DNA.DNA was extracted from the tail of individual fetuses and the sex of the fetus determined by multiplex polymerase chain reaction (PCR) using primers for the YMT2/B locus on the Y chromosome and autosomal myogenin gene (Myog) . The preRNA was extracted from two to three individual placentae from each litter and from pooled fetal thymuses from sham- and influenza-inoculated female  groups using TRIzol reagent . RNA samples were further purified using Qiagen MiniElute columns according to the manufacturer’s instructions . The RNA quantity and quality for quantitative real-time polymerase chain reaction (RT-qPCR) were assessed using a Nanodrop ND-1000 spectrophotometer . RNA concentrations for all samples had 260/280 ratios >2.03.RNA extracted from an individual placenta from each of 3 litters (E7.5 and E12.5) from Experiment 1 were selected at random for RNA sequencing (RNA seq) and analysis . In addition, RNA extracted from 3 control and 3 influenza-inoculated E7.5 litters pooled fetal thymuses were submitted for RNA seq. The quantity of RNA was determined using TECAN . The quality and integrity of the RNA samples was assessed using Agilent Tape Station 2200 or 4200 prior to library prep: RNA sequencing and data analysis were performed. Briefly, messenger RNA (mRNA) was purified, disrupted and a double-stranded cDNA library was synthesized using the TruSight mRNA kit . The cDNA library was sequenced using an Illumina HiSeq2500 platform and the quality of single-end (SE) reads using Real-Time Analysis (RTA) v2.7.3. FASTQ files were subjected to quality control analysis using the Rqc Bioconductor package in R. Reads were mapped using the STAR algorithm. The annotation database for alignment was built using GenomicFeatures Bioconductor package in R utilizing the University of California Santa Cruz  genome browser files (TXDb object) for the mouse mm10 genome. RNA-seq files were aligned to the mouse genome with the GenomeFeatures Bioconductor R package. Aligned reads were filtered based on read counts; genes with reads <2 was discarded from analysis. After filtering, 20,776 genes were analysis ready and analyzed using DESeq2 package in R. Multiple comparison adjustments were made using the Benjamini–Hochberg procedure to control the false discovery rate (FDR) method. The data have been archived in the NCBI GEO database: Accession GSE157132.p ≤ 0.05 and fold change >1.5.The Ingenuity Pathway Analysis  software package was used for the analysis of the data . Transcript expression was significantly different between influenza A virus-inoculated and control samples with an adjusted RNA from pooled fetal lungs from each litter and RNA extracted from three individual placentae randomly selected from control and influenza A virus-inoculated E7.5 and E12.5 litters were assayed for influenza A virus matrix (M) RNA by RT-qPCR .Gpi1), hypoxanthine-guanine phosphoribosyl transferase (Hprt) were used for placental RT-qPCR, and the reference genes Hprt and taldolase1  for thymic RT-qPCR. Primer sequences and gene accession numbers are listed in Primers were designed using Primer Blast (NIH NCBI) and optimized for amplicons between 100 and 150 bp in length, annealing temperature of 60 °C ± 3 °C and selected for the least self-complementarity. Validation of primer sets were established by the following criteria: (1) RT-PCR of placental or thymic RNA and PCR to produce an amplicon of the predicted size, (2) DNA sequence of amplicons determined  to confirm identity to the target gene (NCBI Primer Blast), and (3) primer efficiency between 90 and 120% for RT-qPCR was assessed using 1:5 dilutions of cDNA from placental or pooled thymus RNA extracts. Primers for reference genes glucose-6-phosphate isomerase 1 (Acta1), (2) tight junctions: claudin 3 (Cldn3), (3) cellular effects and (4) hepatic fibrosis myosin light chain, phosphorylatable, fast skeletal muscle (Mylpf), and (5) neuroprotective: angiotensinogen  (Agt). The following immune system genes were selected for further study based on their connection with thymic development: (1) myelin and lymphocyte protein  also known as T cell differentiation protein aka toll-interleukin 1 receptor domain containing adaptor (Tirap), (2) T-cell differentiation protein 2 , (3) cytokine receptor like factor 1 (Crlf1), and (4) annexin 1 (Anxa1). Placental targets were: pro platelet basic protein (Ppbp) and transmembrane protein 150A (Tmem150A). See oligonucleotide primer sequences in Representative genes for each of the top 5 canonical pathways discovered using IPA on thymus RNA seq, were selected for validation: (1) calcium signaling pathways: actin, alpha 1, skeletal muscle  and 3 separate replicate plates were assayed. Gene-specific amplification was performed on a Lightcycler 480  using IQ SYBR green Supermix . The reactions were performed as follows: 95 °C for 3 min, followed by 41 cycles of . Each placental target gene Ct values were normalized to the geometric mean of two references genes, glucose phosphate isomerase 1(Gpi1) and hypoxanthine-guanine phosphoribosyl transferase (Hprt). Each thymic target gene Ct values were normalized to the geometric mean of two reference genes, hypoxanthine-guanine phosphoribosyltransferase (Hprt) and taldolase 1 . The RT-qPCR Ct values were calculated using the comparative Ct method . Ct values for 2 replicates of each gene repeated on 3 plates were averaged for each influenza and control samples. The geomean of the reference genes for the influenza samples was subtracted from the influenza average Ct for each female/litter in the influenza-inoculated group to derive the ΔCt; and the geomean of the references genes for the control samples was subtracted from the control average Ct values for each control female/litter to give the ΔCt. The 2−ΔCt values for each sample were calculated.cDNA was synthesized using iScript RT Supermix  according to the manufacturer’s instructions. Duplicate samples of each pooled thymus or placental sample’s cDNA were assayed on each 384 well, clear plates . The data were evaluated for normality and compared using the unpaired t-test . Correlation between E7.5 fetal and placental weights and fetal sex was analyzed using two-way analysis of variance .Statistical analysis of the number of fetuses per litter, fetal and placental weights, RT-qPCR data, fetal vascular lumen area and fetal capillary segments in placenta was performed in GraphPad Prism 8. The data were checked for normality using Shapiro–Wilks test. Unpaired, two-tailed Student’s To determine the effect of maternal influenza infection on fetal development, we inoculated pregnant C57BL/6 mice by the intranasal route on pre-implantation (E3.5), peri-implantation (E7.5) and post-implantation (E12.5). All females were euthanized on E18.5 and individual fetuses and placentae were collected and weighed. Maternal infection was confirmed in influenza virus inoculated  female mice by HI assay with positive HI titers (4 to 80) at the time of euthanasia (E18.5). All the control female mouse sera were negative for influenza virus antibodies. Clinical signs of disease were not observed, and no deaths occurred in any of the control or influenza A virus-inoculated female mice. There was no difference in the litter sizes of control E3.5, E7.5 or E12.5 and influenza virus inoculated E3.5, E7.5 or E12.5 female mice at E18.5 . At the p = 0.78)  A. The E1= 0.78) ( influenz= 0.78) (B. There Krt13)  = 5.4), keratin 15 (Krt15) , Ppbp  and Tmem150A  collected at E18.5 of gestation. Upregulation of the transcript for Tmem150A in E7.5 placentae (p = 0.0004) was confirmed by RT-qPCR in placentae (n = 9) from each of 4 control litters and (n = 13) from 5 influenza inoculated litters in Experiment 1. In contrast to the RNA seq data, RT-qPCR analysis with two different primer sets  in placentae from influenza-inoculated litters compared to controls. There were no significant differences in any transcripts between influenza-inoculated and control placentae from litters born to females inoculated on E12.5 by RNA seq.To discover placental transcriptome changes caused by maternal influenza A virus infection, RNA seq was performed on an individual placenta from each of three E7.5  and E12.To determine the residual effect of influenza on the placentae, two to four placentae per litter were examined histologically. Placentae from females challenged with influenza virus on E7.5 and E12.5 variably appeared with a less well-developed labyrinth, reflected morphologically both as being narrower in width compared to placentae from control mice, with a higher decidua-to-chorionic ratio and narrower vascular channels . Frank nn = 3) or PBS (n = 3) on E7.5. Differentially expressed genes (Bioconductor software v3.2.3) in R; 1.5-fold; p ≤ 0.05) were detected using the DESeq2 package. The Benjamini–Hochberg procedure was used to control the false discovery rate. Analysis (p ≤ 0.05). IPA analysis of 1.5 fold or greater changes in gene expression is described in To examine the impact of maternal influenza infection on fetal thymic development, RNA-Seq was performed on fetal thymic RNA collected at E18.5 (Experiment 1). Fetal thymuses were pooled within each litter from females inoculated with influenza . Six activated miRNAs, miR-1237-5p, miR-3180-3p, miR-4667-5p, miR-6827-5p, miR-6873-5p and miR-7108-3p  associated with decreased body size and increased risk of neonatal death (see IPA pathway in p < 0.05) in the fetal thymuses from influenza virus-inoculated litters compared to controls in the RNA seq data. In addition, four of the transcripts, Acta1, Mylpf, Mal and Mal2, were confirmed to be downregulated in E7.5 influenza virus inoculated fetal thymuses compared to controls by RT-qPCR  calcium signaling, (2) cellular effects of Sildenafil (Viagra), (3) tight junction signalling, (4) hepatic fibrosis/hepatic stellate cell activation and (5) neuroprotective role of Thimet Oligopeptidase 1 (THOP)1 in Alzheimer’s disease . The pri RT-qPCR . The IPA RT-qPCR D; and, r RT-qPCR .Mal, a gene related to T cell differentiation/maturation was found to be significantly downregulated by 10.4-fold (p = 2.46 × 10−25) in influenza-inoculated litters compared to controls. Mal was identified as one of the top 10 most significantly differentially expressed genes in influenza-treated fetal thymuses  and E7.5 influenza-inoculated fetal thymic RNA in Experiment 1 (p < 0.0001) and in Experiment 2 (p = 0.05) but was not different in E12.5 influenza-inoculated fetal thymic RNA  in RNA-seq data from E7.5 influenza-inoculated fetal thymuses compared to controls. By RT-qPCR, Mal2 tended to be decreased in influenza-inoculated fetal thymic RNA in Experiment 1 (p = 0.1) and was decreased in Experiment 2 (p = 0.05) compared to controls.In the RNA-seq data from E7.5 influenza-inoculation fetal thymuses, thymuses C. Downreymic RNA . Mal2, aListeria monocytogenes, Toxoplasma gondii and Zika virus infect and cross the placenta, directly infecting the fetus, leading to microencephaly and other congenital defects [Maternal infections have long been recognized as inflicting damage on the fetus with serious consequences for the development and viability of the child . Microor defects ,37. Repl defects . InfluenTo investigate the effects of influenza A virus infection on the developing fetal immune system, we infected pregnant mice with influenza A virus and examined placental morphology, placental and fetal weight and assayed thymic gene responses by RNA seq and RT-qPCR. The significant findings are that: (1) the maternal influenza infection affects placental morphology and weight; (2) fetal weights are decreased when maternal infection occurs at pre- and peri-implantation; and (3) during the peri-implantation period of placental implantation, maternal influenza infection is associated with decreased expression of a large number of fetal thymic genes. The latter suggest that fetal immune development may be impaired which could compromise subsequent postnatal immunocompetency. The data are consistent with our hypothesis that maternal influenza infection during pregnancy leads to intrauterine growth restriction and impaired fetal thymic development. Future studies will determine if the fetal immune system is affected such that postnatal health and responses to secondary infections are compromised in the offspring.Proposed mechanisms for the effects of maternal influenza A virus infection on the human fetus include direct infection of the placental and fetal membranes, apoptosis and placentitis ,41,42,43Tmem150A in placentae compared to controls that was sustained through E18.5. Increased Tmem150A has been described as an antiviral response in endoplasmic reticulum (ER) permeability to hepatitis C viral replication [Tmem150A [Corresponding to the decreased weight of placentae from E7.5 influenza-inoculated females and to a lesser degree on E12.5, there was a reduction in the thickness of the labyrinth. This observation points to a negative influence of the infection on vasculogenesis. The vitelline vessels normally start forming around E7.5 to E8.0, and any adverse effects on this process would lead to a reduced labyrinth with consequences for nutrient and oxygen supply to the fetus and hence overall growth or adverse effect on select organs such as brain and lymphoid organs ,56. Infllication . InfluenTmem150A . An incrTmem150A . It is iMal (10-fold) and myelin and lymphocyte protein 2  (9-fold), which were categorized as T cell differentiation/maturation proteins. Very little is known about MAL2 other than its role in transcytosis [Il17d) a cytokine/chemokine that inhibits CD8+ T cell activation; (2) epidermal growth factor receptor (Erbb) expressed by thymic myoid cells, thymic epithelial cells and thymocytes and postulated to play a role in the induction and maintenance of tolerance; (3) transcription factor Fosl2, involved in the regulation of IL-1 and IL-2 activation and signaling; (4) CCAAT enhancer binding protein delta (Cebpd) a transcription factor involved in immune and inflammatory responses and differentiation of macrophages; and (5) E74 like erythroblast transformation Specific (ETS) transcription factor 3 (Elf3) important for thymic natural killer T (NKT) cell development and T cell differentiation [Most of the 957 fetal thymic genes downregulated following maternal influenza infection have functions in non-immune developmental pathways . Two majscytosis . In contscytosis . MAL is scytosis ,64,65,66scytosis ,65,66,67scytosis . Based ontiation ,72,73,74Mal observed on E18.5 likely is the result of actions on gene expression 11 days earlier when endodermal cells are undergoing differentiation into thymic epithelial cells and not directly on developing T cells.The mouse fetal thymus, derived from the third pharyngeal pouch endoderm and neural crest-derived mesenchyme, is first visible at E10.5. Lymphopoietic precursor cells of bone marrow origin seed the thymus anlage at E11.5–E12.5, and by E14.5 differentiation of lymphoid cells into T cells begins. In the thymus, MAL is localized primarily to the cortex . MAL hasThe large-scale inhibition of fetal thymic genes by maternal influenza infection supports further examination of the consequences of maternal infection on the fetal immune system and consequent susceptibility of the offspring to immunologic challenges. Understanding the mechanisms by which maternal influenza infection impacts pregnancy and fetal outcomes is necessary to identify targets to detect and therapeutically manage pregnancies and offspring at risk and for managing long-term postnatal impacts of the infection.


Following publication of the original article , the autIn the published version, the vertical dashed line is incorrectly positioned and the dummy variables are erroneously omitted from the y-axis.To correct the version provided in the published article, please find (the corrected version of) Fig. The authors apologize for any inconvenience caused.Additional file 1: Table S1. Genome features of Actinoalloteichus sp. AHMU CJ021; Table S2. Number of genes associated with the general COG functional categories; Table S3. The biosynthetic gene clusters of secondary metabolites in Actinoalloteichus sp. AHMU CJ021 analyzed by antiSMASH 5.0; Table S4. Deduced functions of the open reading frames (ORFs) indicated in Fig. 2; Table S5. Fermentation media used for caerulomycin A (CRM A) production; Table S6. The mutants obtained from ribosome engineering experiments; Table S7. The CRM A production comparison of three camE-expressing mutants; Table S8.1H NMR and 13C NMR spectral data of CRM A in DMSO-d6; Table S9. The comparison of selected mutants generated from UV mutagenesis; Table S10. CRM A production titer of optimal mutant XC-11GUR; Table S11. The dose of all factors in medium N2 by using Plackett-Burman Design; Table S12. Screening of significant variables for CRM A production in Medium N2 by using Plackett-Burman Design; Table S13. The effects of all factors of Medium N2 for CRM A production by using Plackett-Burman Design; Table S14. The dose of important factors in response surface analysis; Table S15. The design of experiments and response of CRM A production; Table S16. The primers used in identification of gentamycin-resistant mutant; Table S17. The primers used in gene expression analysis; Fig. S1. Phylogenetic tree of Actinoalloteichus sp. AHMU CJ021; Fig. S2. HR-ESI-MS spectrum of CRM A; Fig. S3.1H NMR spectrum of CRM A in DMSO-d6; Fig. S4.13C NMR spectrum of CRM A in DMSO-d6; Fig. S5. CRM A production comparison of different generations of mutants; Fig. S6. The quantitative HPLC standard curves.


There is a pressing need for improved sensors, but improving them is challenging because testing them involves a low throughput, labor-intensive processes. Our goal was to create synthetic, excitable cells that can be activated with brief pulses of blue light and serve as a medium throughput platform for screening the next generation of sensors. In this live cell system, blue light activates an adenylyl cyclase enzyme (bPAC) that increases intracellular cAMP . In turn, the cAMP opens a cAMP-gated ion channel. This produces slow, whole-cell Ca2+ transients and voltage changes. To increase the speed of these transients, we add the inwardly rectifying potassium channel Kir2.1, the bacterial voltage-gated sodium channel NAVROSD, and Connexin-43. The result is a highly reproducible, medium-throughput, live cell system that can be used to screen voltage and Ca2+ sensors.Genetically encoded fluorescent biosensors are powerful tools for studying complex signaling in the nervous system, and now both Ca B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in [Kir2.1]:[NavD] optimized Kuhl-CKNa cells C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. D) The total number of Ca2+ transients per cell (ROI) for experimental [Kir2.1]:[NavD] optimized Kuhl-CKNa cells. E) Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).A) The total peaks for each Ca(TIF)Click here for additional data file.S5 Fig2+ transient within a trial was recorded, and the experiment with [1e8 Kir2.1]:[1e8 NavD] VG/μL had the greatest recorded peaks. B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in [Kir2.1]:[NavD] optimized Kuhl-CKNaCx cells C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. D) The total number of Ca2+ transients per cell (ROI) for experimental [Kir2.1]:[NavD] optimized Kuhl-CKNaCx. E) Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).A) The total peaks for each Ca(TIF)Click here for additional data file.S6 Fig2+ transient within a trial was recorded, and the experiment with [Cx 1e5] VG/μL had the greatest recorded peaks. B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in Cx-43 optimized Kuhl-CKNaCx cells. C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. D) The number of Ca2+ transients per cell (ROI) for Cx-43 optimized Kuhl-CKNaCx cells. E) Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).Corresponding (TIF)Click here for additional data file.S7 Fig2+ transient within a trial was recorded, and the experiment with [CNG 1e3] VG/μL had the greatest recorded peaks. B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in CNG optimized Kuhl-CKNaCx cells C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. The wells without CNG and Cx were very interesting because it appears that without blue light there is a D) The total number of Ca2+ transients per cell (ROI) for experimental CNG optimized Kuhl-CKNaCx cells. E) Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).Corresponding (TIF)Click here for additional data file.S8 Fig2+ transient within a trial (T = 300s) was recorded. The experiment with [HCN2 1e2] VG/μL had the greatest recorded peaks. B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in HCN2 optimized Kuhl-HKNaCx cells C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. D) The total number of Ca2+ transients per cell (ROI) for experimental HCN2 optimized Kuhl-HKNaCx. E) Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).Corresponding (TIF)Click here for additional data file.S9 Fig2+ transient within a trial (T = 25m) was recorded. B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in optimized Kuhl-CKNaCx cells C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. D) The total number of Ca2+ transients per cell (ROI) for optimized Kuhl-CKNaCx cells. Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).Corresponding (TIF)Click here for additional data file.S10 Fig2+ transient within a trial (T = 25m) was recorded. B) The △F is the difference between the baseline fluorescence and the maximum fluorescence of each peak. The mean and S.E.M of the Ca2+ transients in optimized Kuhl-CKNaCx cells C) Blue line indicates point of 20s blue light stimulus. The time of each fluorescence peak was recorded and is indicated by a black dot. D) The total number of Ca2+ transients per cell (ROI) for optimized Kuhl-CKNaCx. Representative duration of elevated R-GECO1 fluorescence over time per Ca2+ transient. Black dot indicates the Ca2+ transients FWHM for each peak. F) Black dot indicates the time between Ca2+ transient events per cell. Red bars indicate mean and ± S.E.M (n = 150 cells per condition).Corresponding (TIF)Click here for additional data file.S11 Fig2+ transient frequency (n = 150 cells per condition).A) Activity was optimized by varying the viral concentration of CNG. Differences were analyzed using Dunnett’s multiple comparison test on the Carequency  compared(TIF)Click here for additional data file.S1 TableThe table shows the experimental set up, the final viral concentration used, and their corresponding figures.(TIF)Click here for additional data file.S2 TableThe table shows all test run using Dunnetts where stated in the manuscript.(TIF)Click here for additional data file.S1 MovieThe authors do not know what these come from.(AVI)Click here for additional data file.S2 Movie2+ bursting rosette pattern following a stimulus, while HCN2 seems to have a spreading wave-like pattern.Rose like patterns. The behavior of HCN2 was visually different from CNG. While both wells have random activity, there is a brief somewhat coordinated activity after a blue light stimulus  Figs. S2(AVI)Click here for additional data file.S3 MovieWave-like spreading pattern.(AVI)Click here for additional data file.S4 MovieCells imaged for 15 minutes with robust, repeatable activity.(AVI)Click here for additional data file.S5 MovieAn image created by the OptoSplit II is shown where the green and red emission from both sensors are split and imaged on two different portions of the EMCCD camera.(AVI)Click here for additional data file.S6 MovieActivity of Kuhl-CKNaCx cells with the GEVI ArcLight.(AVI)Click here for additional data file.S7 MovieActivity of Kuhl-CKNaCx cells with the GEVI ArcLight from the same well.(AVI)Click here for additional data file.S8 MovieActivity of Kuhl-CKNaCx cells with the GEVI ArcLight from the same well.(MOV)Click here for additional data file.