Identification of hub genes associated with Helicobacter pylori infection and type 2 diabetes mellitus:A pilot bioinformatics study

BACKGROUND Helicobacter pylori(H.pylori)infection is related to various extragastric diseases including type 2 diabetes mellitus(T2DM).However,the possible mechanisms connecting H.pylori infection and T2DM remain unknown.AIM To explore potential molecular connections between H.pylori infection and T2DM.METHODS We extracted gene expression arrays from three online datasets(GSE60427,GSE27411 and GSE115601).Differentially expressed genes(DEGs)commonly present in patients with H.pylori infection and T2DM were identified.Hub genes were validated using human gastric biopsy samples.Correlations between hub genes and immune cell infiltration,miRNAs,and transcription factors(TFs)were further analyzed.RESULTS A total of 67 DEGs were commonly presented in patients with H.pylori infection and T2DM.Five significantly upregulated hub genes,including TLR4,ITGAM,C5AR1,FCER1G,and FCGR2A,were finally identified,all of which are closely related to immune cell infiltration.The gene-miRNA analysis detected 13 miRNAs with at least two gene cross-links.TF-gene interaction networks showed that TLR4 was coregulated by 26 TFs,the largest number of TFs among the 5 hub genes.CONCLUSION We identified five hub genes that may have molecular connections between H.pylori infection and T2DM.This study provides new insights into the pathogenesis of H.pylori-induced onset of T2DM.

Transcriptomic and bioinformatics analysis of the mechanism by which erythropoietin promotes recovery from traumatic brain injury in mice

Recent studies have found that erythropoietin promotes the recovery of neurological function after traumatic brain injury.However,the precise mechanism of action remains unclea r.In this study,we induced moderate traumatic brain injury in mice by intrape ritoneal injection of erythro poietin for 3 consecutive days.RNA sequencing detected a total of 4065 differentially expressed RNAs,including 1059 mRNAs,92 microRNAs,799 long non-coding RNAs,and 2115circular RNAs.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses revealed that the coding and non-coding RNAs that were differentially expressed after traumatic brain injury and treatment with erythropoietin play roles in the axon guidance pathway,Wnt pathway,and MAPK pathway.Constructing competing endogenous RNA networks showed that regulatory relationship between the differentially expressed non-coding RNAs and mRNAs.Because the axon guidance pathway was repeatedly enriched,the expression of Wnt5a and Ephb6,key factors in the axonal guidance pathway,was assessed.Ephb6 expression decreased and Wnt5a expression increased after traumatic brain injury,and these effects were reversed by treatment with erythro poietin.These findings suggest that erythro poietin can promote recove ry of nerve function after traumatic brain injury through the axon guidance pathway.

Research advance of Bacillus velezensis:bioinformatics,characteristics,and applications

Bacillus velezensis is a Gram-positive and spore-forming bacterium.It has potent antimicrobial properties that can be used to promote plant growth and as a pesticide by inhibiting pathogens.B.velezensis has the capability to generate a diverse range of enzymes that have potential applications in various fields,such as enzyme production,fermented food,degradation of pollutants,and bioenergy.In addition,B.velezensis is a promising probiotic.It possesses high bile-salt tolerance characteristics and has a high success rate of colonization in the intestinal mucosa.Besides,the strain can also regulate gut microbiota constitute by increasing the number of beneficial microorganisms and decreasing the number of pathogens.Furthermore,based on its special properties,including high-yield protease production and high salt-tolerance,B.velezensis shows potential for use in marine protein fermentation,opening up new avenues for the development of novel food products and bioactive peptides.In addition,B.velezensis can shorten the fermentation time as well as improve the nutritional value and flavor of fermented food.The safety of B.velezensis for food production was evaluated.This review provides valuable insights into the potential uses and benefits of B.velezensis,particularly in the context of fermented foods.

Identification and Validation of Vascular-Associated Biomarkers for the Prognosis and Potential Pathogenesis of Hypertension Using Comprehensive Bioinformatics Methods

Background: Hypertension, also known as increased blood pressure, is a phenomenon in which blood flows in blood vessels and causes persistently higher-than-normal pressure on the vessel wall. The identification of novel prognostic and pathogenesis biomarkers plays a key role in the management of hypertension. Methods: The GSE7483 and GSE75815 datasets from the gene expression omnibus (GEO) database were used to identify the genes associated with hypertension that were differentially expressed genes (DEGs). The functional role of the DEGs was elucidated by gene body (GO) enrichment analysis. In addition, we performed an immune infiltration assay and GSEA on the DEGs of hypertensive patients and verified the expression of novel DEGs in the blood of hypertensive patients by RT-qPCR. Results: A total of 267 DEGs were identified from the GEO database. GO analysis revealed that these genes were associated mainly with biological processes such as fibroblast proliferation, cell structural organization, extracellular matrix organization, vasculature development regulation, and angiogenesis. We identified five possible biomarkers, Ecm1, Sparc, Sphk1, Thbsl, and Mecp2, which correlate with vascular development and angiogenesis characteristic of hypertension by bioinformatics, and explored the clinical expression levels of these genes by RT-qPCR, and found that Sparc, Sphk1, and Thbs1 showed significant up-regulation, in agreement with the results of the bioinformatics analysis. Conclusion: Our study suggested that Sparc, Sphk1 and Thbs1 may be potential novel biomarkers for the diagnosis, treatment and prognosis of hypertension and that they are involved in the regulation of vascular development and angiogenesis in hypertension.

Identification and Validation of Novel Biomarkers Related to the Calcium Metabolism Pathway in Hypertension Patients Based on Comprehensive Bioinformatics Methods

Background: Hypertension is a universal risk factor for cardiovascular diseases and is thus the leading cause of death worldwide. The identification of novel prognostic and pathogenesis biomarkers plays a key role in disease management. Methods: The GSE145854 and GSE164494 datasets were downloaded from the Gene Expression Omnibus (GEO) database and used for screening and validating hypertension signature genes, respectively. Gene Ontology (GO) enrichment analysis was performed on the differentially expressed genes (DEGs) related to calcium ion metabolism in patients with hypertension. The core genes related to immune infiltration were analyzed and screened, and the activity of the signature genes and related pathways was quantified using gene set enrichment analysis (GSEA). The infiltration of immune cells in the blood samples was analyzed, and the DEGs that were abnormally expressed in the clinical blood samples of patients with hypertension were verified via RT-qPCR. Results: A total of 176 DEGs were screened. GO showed that DEGs was involved in the regulation of calcium ion metabolism in biological processes (BP), actin mediated cell contraction, negative regulation of cell movement, and calcium ion transmembrane transport, and in the regulation of protease activity in molecular functions (MF). KEGG analysis revealed that the DEGs were involved mainly in the cGMP-PKG signaling pathway, ubiquitin-protein transferase, tight junction-associated proteins, and the regulation of myocardial cells. MF analysis revealed the immune infiltration function of the cells. RT-qPCR revealed that the expression of Cacna1d, Serpine1, Slc8a3, and Trpc4 was up regulated in hypertension, the expression of Myoz2 and Slc25a23 was down regulated. Conclusion: Cacna1d, Serpine1, Slc8a3, Trpc4, Myoz2 and Slc25a23 may be involved in the regulation of calcium metabolism pathways and play key roles in hypertension. These differentially expressed calcium metabolism-related genes may serve as prognostic markers of hypertension.

Bioinformatics Analysis of the Association between Ewing’s Sarcoma and Tuberculosis Comorbidity

Objective To screen and analyze the differentially expressed genes of Ewing’s sarcoma (ES) and Tuberculosis (TB) by bioinformatics. Methods GEO gene chip public database in NCBI was used for data retrieval, and chip data GSE17674 and GSE57736 were selected as analysis objects. The R language limma toolkit was used to screen DEmRNAs, and the data were standardized, and the common differentially expressed genes were screened by Venn diagram. The GO function and KEGG pathway enrichment of common differentially expressed genes were analyzed by using the R cluster Profiler package. String database was selected for PPI analysis, and the results were imported into Cytoscape software to obtain PPI interaction map, core module and Hub gene. Import Hub gene into BioGPS database. Results: A total of 3 Hub genes were screened, namely CD3D, LCK, KLRB1;The genes were imported into BioGPS database to obtain the specific genes. Conclusion The selected differential genes and related signaling pathways are helpful to understand the molecular mechanism of ES and TB, and can provide the basis for early diagnosis of ES complicated with TB. It also provides new ideas for clinical treatment and diagnosis.

Bioinformatics Analysis of the Biological Properties of Ewing Sarcoma

Purpose: Bioinformatics-based approach to screen and analyze differentially expressed genes associated with the biological characteristics of Ewing sarcoma. Means: The GSE17674 dataset was selected for analysis, obtained by data retrieval based on the GEO public database. The R language limma toolkit was used to screen DEmRNAs. After the data were normalized, the Metascape online analysis software and the R language clusterProfiler package were used to analyze the GO function and KEGG pathway enrichment of DEmRNAs lines, respectively. The string database was selected for PPI analysis, and the results were imported into Cytoscape software to derive the core modules and predicted core genes. The genes selected above were analyzed for tissue localization specificity. Results: Through the analysis of GSE17674, differentially expressed genes were screened out, and GO and KEGG analyses were performed on the differentially expressed genes. The GO functional enrichment analysis was mainly enriched in the process of muscle system, muscle contraction, myocyte development, contractile fibers, myogenic fibers, myofibers, myofibrillar segments, actin binding, structural composition of muscle, and actin filament binding. KEGG pathway analysis showed that the core pathways associated with the development of ES were the core genes for myocardial contraction, congestive cardiomyopathy, and hypertrophic cardiomyopathy. Five Hub genes were obtained based on Cytoscape prediction. Tissue localization specificity analysis of Hub genes was performed, and a total of 2 Hub genes with tissue specificity were screened;MYH6 was specifically expressed in cardiac cells and MYL1 was specifically expressed in skeletal muscle cells. Conclusions: The differential genes screened will help to understand the molecular mechanisms underlying the highly invasive and metastasis-prone biological characteristics of ES, as well as provide new ideas for clinical drug-targeted treatment of ES.

Identification of anti-gastric cancer effects and molecular mechanisms of resveratrol: From network pharmacology and bioinformatics to experimental validation

BACKGROUND Gastric cancer(GC)is one of the most aggressive malignancies with limited therapeutic options and a poor prognosis.Resveratrol,a non-flavonoid poly-phenolic compound found in a variety of Chinese medicinal materials,has shown excellent anti-GC effect.However,its exact mechanisms of action in GC have not been clarified.AIM To identify the effects of resveratrol on GC progression and explore the related molecular mechanisms.METHODS Action targets of resveratrol and GC-related targets were screened from public databases.The overlapping targets between the two were confirmed using a Venn diagram,and a“Resveratrol-Target-GC”network was constructed using Cyto-scape software version 3.9.1.The protein-protein interaction(PPI)network was constructed using STRING database and core targets were identified by PPI network analysis.The Database for Annotation,Visualization and Integrated A total of 378 resveratrol action targets and 2154 GC disease targets were obtained from public databases,and 181 intersection targets between the two were screened by Venn diagram.The top 20 core targets were identified by PPI network analysis of the overlapping targets.GO function analysis mainly involved protein binding,identical protein binding,cytoplasm,nucleus,negative regulation of apoptotic process and response to xenobiotic stimulus.KEGG enrichment analysis suggested that the involved signaling pathways mainly included PI3K-AKT signaling pathway,MAPK signaling pathway,IL-17 signaling pathway,TNF signaling pathway,ErbB signaling pathway,etc.FBJ murine osteosarcoma viral oncogene homolog(FOS)and matrix metallopeptidase 9(MMP9)were selected by differential expression analysis,and they were closely associated with immune infiltration.Molecular docking results showed that resveratrol docked well with these two targets.Resveratrol treatment arrested the cell cycle at the S phase,induced apoptosis,and weakened viability,migration and invasion in a dose-dependent manner.Furthermore,resveratrol could exhibit anti-GC effect by regulating FOS and MMP9 expression.CONCLUSION The anti-GC effects of resveratrol are related to the inhibition of cell proliferation,migration,invasion and induction of cell cycle arrest and apoptosis by targeting FOS and MMP9.

Identification of Prognosis-Related Genes and Key Target Genes for Pancreatic Cancer: A Bioinformatics Analysis

Objective: The mortality and morbidity rates associated with pancreatic cancer (PaCa) are extremely high. Various studies have demonstrated that pancreatic cancer will be the fourth cancer-related death by 2030, raising more concern for scholars to find effective methods to prevent and treat in order to improve the pancreatic cancer outcome. Using bioinformatic analysis, this study aims to pinpoint key genes that could impact PaCa patients’ prognosis and could be used as therapeutic targets. Methods: The TCGA and GEO datasets were integratively analyzed to identify prognosis-related differentially expressed genes. Next, the STRING database was used to develop PPI networks, and the MCODE and CytoNCA Cytoscape in Cytoscape were used to screen for critical genes. Through CytoNCA, three kinds of topology analysis were considered (degree, betweenness, and eigenvector). Essential genes were confirmed as potential target treatment through Go function and pathways enrichment analysis, a developed predictive risk model based on multivariate analysis, and the establishment of nomograms using the clinical information. Results: Overall, the GSE183795 and TCGA datasets associated 1311 and 2244 genes with pancreatic cancer prognosis, respectively. We identified 132 genes that were present in both datasets. The PPI network analysis using, the centrality analysis approach with the CytoNCA plug-in, showed that CDK2, PLK1, CCNB1, and TOP2A ranked in the top 5% across all three metrics. The independent analysis of a risk model revealed that the four key genes had a Hazard Ratio (HR) > 1. The monogram showed the predictive risk model and individual patient survival predictions were accurate. The results indicate that the effect of the selected vital genes was significant and that they could be used as biomarkers to predict a patient’s outcome and as possible target therapy in patients with pancreatic cancer. GO function and pathway analysis demonstrated that crucial genes might affect the P53 signaling pathway and FoxO signaling pathway, through which Meiotic nuclear division and cell cycle may have a significant function in essential genes affecting the outcome of patients who have pancreatic cancer. Conclusions: This study suggests that CDK2, CCNB1, PLK1 and TOP2A are four key genes that have a significant influence on PaCa migration and proliferation. CDK2, CCNB1, PLK1, and TOP2A can be used as potential PaCa prognostic biomarkers and therapeutic targets. However, experimental validation is necessary to confirm these predictions. Our study comes into contributions to the development of personalized target therapy for pancreatic cancer patients.

Identification and Validation of SLC9A2 as A Potential Tumor Suppressor in Colorectal Cancer:Integrating Bioinformatics Analysis with Experimental Confirmation

Objective To uncover the mechanisms underlying the development of colorectal cancer(CRC),we applied bioinformatic analyses to identify key genes and experimentally validated their possible roles in CRC onset and progression.Methods We performed Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis on differentially expressed genes(DEGs),constructed a protein-protein interaction(PPI)network to find the top 10 hub genes,and analyzed their expression in colon adenocarcinoma(COAD)and rectum adenocarcinoma(READ).We also studied the correlation between these genes and immune cell infiltration and prognosis and validated the expression of SLC9A2 in CRC tissues and cell lines using qRT-PCR and Western blotting.Functional experiments were conducted in vitro to investigate the effects of SLC9A2 on tumor growth and metastasis.Results We found 130 DEGs,with 45 up-regulated and 85 down-regulated in CRC.GO analysis indicated that these DEGs were primarily enriched in functions related to the regulation of cellular pH,zymogen granules,and transmembrane transporter activity.KEGG pathway analysis revealed that the DEGs played pivotal roles in pancreatic secretion,rheumatoid arthritis,and the IL-17 signaling pathway.We identified 10 hub genes:CXCL1,SLC26A3,CXCL2,MMP7,MMP1,SLC9A2,SLC4A4,CLCA1,CLCA4,and ZG16.GO enrichment analysis showed that these hub genes were predominantly involved in the positive regulation of transcription.Gene expression analysis revealed that CXCL1,CXCL2,MMP1,and MMP7 were highly expressed in CRC,whereas CLCA1,CLCA4,SLC4A4,SLC9A2,SLC26A3,and ZG16 were expressed at lower levels.Survival analysis revealed that 5 key genes were significantly associated with the prognosis of CRC.Both mRNA and protein expression levels of SLC9A2 were markedly reduced in CRC tissues and cell lines.Importantly,SLC9A2 overexpression in SW480 cells led to a notable inhibition of cell proliferation,migration,and invasion.Western blotting analysis revealed that the expression levels of phosphorylated ERK(p-ERK)and phosphorylated JNK(p-JNK)proteins were significantly increased,whereas there were no significant changes in the expression levels of ERK and JNK following SLC9A2 overexpression.Correlation analysis indicated a potential link between SLC9A2 expression and the MAPK signaling pathway.Conclusion Our study suggests that SLC9A2 acts as a tumor suppressor through the MAPK pathway and could be a potential target for CRC diagnosis and therapy.

Machine learning and bioinformatics to identify biomarkers in response to Burkholderia pseudomallei infection in mice

Objective:In the realm of Class I pathogens,Burkholderia pseudomallei(BP)stands out for its propensity to induce severe pathogenicity.Investigating the intricate interactions between BP and host cells is imperative for comprehending the dynamics of BP infection and discerning biomarkers indicative of the host cell response process.Methods:mRNA extraction from BP-infected mouse macrophages constituted the initial step of our study.Employing gene expression arrays,the extracted RNA underwent conversion into digital signals.The percentile shift method facilitated data processing,with the identification of genes manifesting significant differences accomplished through the application of the t-test.Subsequently,a comprehensive analysis involving Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway was conducted on the differentially expressed genes(DEGs).Leveraging the ESTIMATE algorithm,gene signatures were utilized to compute risk scores for gene expression data.Support vector machine analysis and gene enrichment scores were instrumental in establishing correlations between biomarkers and macrophages,followed by an evaluation of the predictive power of the identified biomarkers.Results:The functional and pathway associations of the DEGs predominantly centered around G protein-coupled receptors.A noteworthy positive correlation emerged between the blue module,consisting of 416 genes,and the StromaScore.FZD4,identified through support vector machine analysis among intersecting genes,indicated a robust interaction with macrophages,suggesting its potential as a robust biomarker.FZD4 exhibited commendable predictive efficacy,with BP infection inducing its expression in both macrophages and mouse lung tissue.Western blotting in macrophages confirmed a significant upregulation of FZD4 expression from 0.5 to 24 h post-infection.In mouse lung tissue,FZD4 manifested higher expression in the cytoplasm of pulmonary epithelial cells in BP-infected lungs than in the control group.Conclusion:Thesefindings underscore the upregulation of FZD4 expression by BP in both macrophages and lung tissue,pointing to its prospective role as a biomarker in the pathogenesis of BP infection.

Unraveling autophagy-related pathogenesis in active ulcerative colitis:A bioinformatics approach

In this editorial,we provide commentary on the study by Gong et al.In this original research article,Gong et al employed a bioinformatics approach to investigate the involvement of autophagy in active ulcerative colitis(UC).Through differential gene expression analysis,they identified 58 differentially expressed autophagy-related genes in UC patients compared to healthy controls.Notably,HSPA5,CASP1,SERPINA1,CX3CL1,and BAG3,were found to be upregulated in active UC patients,suggesting their significance as core autophagyrelated targets.Enrichment analysis unveiled associations with crucial signaling pathways and diseases such as middle cerebral artery occlusion and glomerulonephritis.Moreover,immune cell infiltration analysis revealed notable differences in immune cell composition between UC patients and healthy controls.These findings offer valuable insights into the role of autophagy in UC pathogenesis and potential therapeutic targets.

Bioinformatics and network pharmacology identify the therapeutic role and potential targets of diosgenin in Alzheimer disease and COVID-19

Objective: This study aims to investigate the potential targets of diosgenin for the treatment of Alzheimer's disease (AD) and Coronavirus Disease 2019 (COVID-19) through the utilization of bioinformatics, network pharmacology, and molecular docking techniques. Methods: Differential expression genes (DEGs) shared by AD and COVID-19 were enriched by bioinformatics. Additionally, regulatory networks were analyzed to identify key genes in the Transcription Factor (TF) of both diseases. The networks were visualized using Cytoscape. Utilizing the DGIdb database, an investigation was conducted to identify potential drugs capable of treating both Alzheimer's disease (AD) and COVID-19. Subsequently, a Venn diagram analysis was performed using the drugs associated with AD and COVID-19 in the CTD database, leading to the identification of diosgenin as a promising candidate for the treatment of both AD and COVID-19.SEA, SuperPred, Swiss Target Prediction and TCMSP were used to predict the target of diosgenin in the treatment of AD and COVID-19, and the target of diosgenin in the treatment of AD and COVID-19 was determined by Wayne diagram intersection analysis with the differentially expressed genes of AD and COVID- 19. Their Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed jointly. Genomes The Protein Protein Interaction (PPI) network of these drug targets was constructed, and core targets with the highest correlation were screened out. The binding of diosgenin to these core targets was analyzed by molecular docking. Results: Through enrichment and cluster analysis, it was found that the biological processes, pathways and diseases enriched by DEGs in AD and COVID-19 were all related to inflammation and immune regulation. These common DEGs and Trust databases were used to construct AD and COVID-19 TFs regulatory networks. Diosgenin was predicted as a potential drug for the treatment of AD and COVID-19 by network pharmacology, and 36 targets of diosgenin for the treatment of AD and 27 targets for COVID-19 were revealed. The six core targets with the highest correlation were selected for molecular docking with diosgenin using CytohHubba to calculate the scores. Conclusions: This study firstly revealed that the common TFs regulatory network of AD and COVID-19, and predicted and verified diosgenin as a potential drug for the treatment of AD and COVID-19. The binding of diosgenin to the core pharmacological targets for the treatment of AD and COVID-19 was determined by molecular docking, which provides a theoretical basis for developing a new approach to clinical treatment of AD and COVID-19.

Bioinformatics Analysis of the Relationship between Dilated Cardiomyopathy and Chronic Heart Failure

Objective: To screen and analyze the differentially expressed genes between dilated cardiomyopathy (DCM) and chronic heart failure (CHF) based on bioinformatics methods. Methods: The Gene Expression Omnibus (GEO) database was used for data retrieval, and the chip data GSE3585 was downloaded, which was the original data of DCM and normal control group. At the same time, the chip data GSE76701 was downloaded, which was the original data of CHF and control group. Differentially expressed mRNAs (DEmRNAs) were screened by R language limma package, the data were standardized, and the common differentially expressed genes were screened. GO function and KEGG pathway enrichment analysis were performed on the common differentially expressed genes. String11.0 online tool was used for data analysis to obtain differentially expressed genes, and the results were imported into Cytoscape 3.9.1 software. The results were imported into Cytoscape 3.9.1 software, and the common expression gene module was obtained by MOCDE algorithm. Nine Hub genes were obtained by 10 algorithms such as MCC. Results: A total of 248 differentially expressed genes were screened. GO analysis showed that differentially expressed genes were mainly concentrated in 9 different physiological and pathological processes. KEGG analysis showed that the main signaling pathways involved in differentially expressed genes were 2, and 9 key differentially expressed genes were predicted: NPPB, NPPA, MYH6, FRZB, ASPN, SFRP4, RPS4Y1, DDX3Y. Conclusion: This study preliminarily explored the molecular mechanism of DCM and CHF, and obtained the common differentially expressed genes of the two diseases. Further experimental studies are needed to verify the correlation between gene expression and clinicopathological features. Provide new ideas for clinical drug treatment research.

Molecular Cloning of clpX Gene from Vibrio alginolyticus HY9901 and Its Bioinformatics Analysis

According to the clpX gene sequence of Vibrio alginolyticus HY9901,a pair of specific primers were designed,and the full length was cloned by PCR and subjected to bioinformatics analysis.The results showed that the clpX gene was 1281 bp in length and encoded 426 amino acids.Its molecular structure formula was C 3842 H 6405 N 1281 O 1598 S 260,with a theoretical protein molecular weight of approximately 1044473.4 kDa and a theoretical pI value of 5.04.The clpX gene was predominantly situated within the cytoplasm,exhibiting unstable and hydrophilic protein characteristics.It possessed a signal peptide cleavage site,lacked a transmembrane region,and was not associated with any KEGG metabolic pathway.Additionally,it possessed 2 glycine phosphorylation sites,a CAMP-dependent protein kinase phosphorylation site,a C-terminal amidation modification site,6 protein kinase C phosphorylation sites,7 microbody C-terminal target signal sites,and an ATP/GTP site.The clpX phylogenetic tree was constructed using the MEGA 5.0 software via the neighbor-joining method.The results demonstrated that the clpX of V.alginolyticus exhibited up to 100%affinity with the clpX of Vibrio spp.The single subunit 3D structure model of the ClpX protein was obtained using the SWISS-MODEL program.A structural and functional analysis of the protein revealed the presence of three distinct ClpX structural and functional domains.In the prediction of secondary structure,the proportions ofα-helix,random coil,β-sheet and extended strand were 40.38%,37.09%,5.40%and 17.14%,respectively.The analysis of the ClpX protein through the STRING database revealed that the proteins interacting with the ClpX protein were Tig,Atpd,Hflb,Msrb-2,Rpod,Clpp,Clpa,Lon-1,Hfq,and ANP63951.1.A computational analysis of the ClpX protein identified a number of post-translational modification sites,including phosphorylation,acetylation,ubiquitination,glycosylation,methylation,S-palmitoylation,and lactylation.The significance of this study is to analyze the function of the clpX gene and establish a robust foundation for subsequent investigations into the mechanism of the clpX gene in Vibrio alginolyticus.

Elucidating the interplay of ferroptosis-related genes in keloid formation:Insights from bioinformatics analysis

Background:Keloids are benign skin tumors characterized by fibroblast proliferation,tumor-like biological behavior,and excessive deposition of extracellular matrix in wounded skin.Ferroptosis,a type of programmed cell death,is critical in tumor pathogenesis.We aimed to investigate the role of ferroptosis in keloid formation.Methods:We downloaded public high-throughput sequencing raw count data(GSE92566),containing three normal skin and four keloid samples,from the Gene Expression Omnibus database.Ferroptosis-related genes were obtained from the Ferroptosis database website.The ferroptosis-related differentially expressed genes(FRDEGs)were obtained by merging differentially expressed genes with ferroptosis-related genes.The FRDEGs were then used for Gene Ontology,Kyoto Encyclopedia of Genes and Genomes,Gene Set Enrichment Analysis,proteinprotein interaction(PPI)network,and microRNA(miRNA)-mRNA network analysis.Finally,real-time quantitative polymerase chain reaction(RT-qPCR)was performed to validate our findings.Results:We found 25 FRDEGs,including 8 up-regulated and 17 down-regulated genes.Pathway enrichment analysis revealed that the Hippo and transforming growth factorβsignaling pathways were significantly upregulated in keloids.In contrast,regulation of the peroxisome proliferator-activated receptor signaling pathway,glutathione metabolism,and unsaturated fatty acid metabolic process were down-regulated.PPI and FRDEGs hub networks were constructed using the STRING database and Cytoscape software.Ten hub genes were identified,including PLA2G6,RARRES2,SNCA,CYP4F8,CDKN2A,ALOX12,FABP4,ALOX12B,NEDD4,and NEDD4L.We constructed a miRNA-mRNA network,which predicted hsa-mir-155-5p,hsa-let-7b-5p,hsa-mir-124-3p,hsa-mir-145-5p,hsa-mir-328-3p,hsa-mir-24-3p,and hsa-mir-10b-5p as the most connected miRNAs regulating ferroptosis in keloids.Finally,we verified the expression levels of the hub genes by RT-qPCR,which confirmed that ALOX12,ALOX12B,and CYP4F8 expression were reduced in keloids.Conclusions:This study provides novel information on ferroptosis-mediated keloid pathogenesis,underscoring the importance of further research in this area to unlock new therapeutic avenues for keloid treatment.

Construction of the underlying circRNA-miRNA-mRNA regulatory network and a new diagnostic model in ulcerative colitis by bioinformatics analysis

BACKGROUND Circular RNAs(circRNAs)are involved in the pathogenesis of many diseases through competing endogenous RNA(ceRNA)regulatory mechanisms.AIM To investigate a circRNA-related ceRNA regulatory network and a new predictive model by circRNA to understand the diagnostic mechanism of circRNAs in ulcerative colitis(UC).METHODS We obtained gene expression profiles of circRNAs,miRNAs,and mRNAs in UC from the Gene Expression Omnibus dataset.The circRNA-miRNA-mRNA network was constructed based on circRNA-miRNA and miRNA-mRNA interactions.Functional enrichment analysis was performed to identify the biological mechanisms involved in circRNAs.We identified the most relevant differential circRNAs for diagnosing UC and constructed a new predictive nomogram,whose efficacy was tested with the C-index,receiver operating characteristic curve(ROC),and decision curve analysis(DCA).RESULTS A circRNA-miRNA-mRNA regulatory network was obtained,containing 12 circRNAs,three miRNAs,and 38 mRNAs.Two optimal prognostic-related differentially expressed circRNAs,hsa_circ_0085323 and hsa_circ_0036906,were included to construct a predictive nomogram.The model showed good discrimination,with a C-index of 1(>0.9,high accuracy).ROC and DCA suggested that the nomogram had a beneficial diagnostic ability.CONCLUSION This novel predictive nomogram incorporating hsa_circ_0085323 and hsa_circ_0036906 can be conveniently used to predict the risk of UC.The circRNa-miRNA-mRNA network in UC could be more clinically significant.

Gene Cloning and Bioinformatics Analysis of phoR Gene from Vibrio alginolyticus HY9901

PhoR is a histidine kinase in a two-component regulatory system that regulates phosphorus metabolic pathways and undertakes the key mission of information transmission in pathogenic bacteria.The full-length phoR gene was successfully cloned from the Vibrio alginolyticus HY9901 strain.A comprehensive analysis of the cloned gene was conducted using bioinformatics.Sequence analysis revealed that the total length of the phoR gene(GenBank accession No.:KJ958404.1)is 1299 bp,with the coding region containing a total of 432 amino acid residues.The phylogenetic tree of PhoR revealed that it belongs to the same subclade as V.diabolicus.The SMART program was employed for the purpose of functional domain prediction,which revealed that PhoR possesses three major functional domains:PAS(amino acids 98-166),HisKA(amino acids 205-272),and HATPase_c(amino acids 317-429).

Effects of OGFOD1 in bladder cancer progression and its prognostic significance:Insights from bioinformatics analysis

Background:Previous studies have established the role of 2-oxoglutarate and Fe(II)-dependent oxygenase domain–containing protein 1(OGFOD1)in oncogenesis.The objective of this investigation was to discern the diagnostic and prognostic relevance of OGFOD1 within the context of bladder cancer(BLCA)using bioinformatics methodologies.Methods:We collected RNA sequencing data from The Cancer Genome Atlas database and verified it using the GSE13507 dataset.Immunohistochemical analysis was based on data from the human protein atlas,and the protein-protein interaction network was constructed using the STRING database.Bioinformatics analysis was performed using the R application,analyzing the correlation between clinical characteristics and OGFOD1 expression,exploring the potential mechanisms of OGFOD1 in BLCA through Kyoto Encyclopedia of Genes and Genomes analysis,and evaluating the diagnostic and prognostic value of OGFOD1 expression in BLCA through receiver operating characteristic curve analysis,Kaplan-Meier analysis,and multivariate Cox analysis.Furthermore,a BLCA prognostic nomogram was constructed.Results:We report higher expression levels of OGFOD1 in BLCA specimens compared with those in noncancerous tissues;this can be used to predict the outcome of the disease.Further,results suggest that OGFOD1 is implicated in the activation of the peroxisome proliferator-activated receptor signaling cascade,potentially interacting with other genes linked to expression in promoting the onset and progression of BLCA.Conclusions:OGFOD1 is a promising candidate as a prognostic indicator in BLCA.

Cloning and Bioinformatics Analysis of hcp Gene in Aeromonas hydrophila

[Objectives]To explore the function of hcp gene in Aeromonas hydrophila.[Methods]A pair of specific primers was designed referring to the hcp gene sequence of A.hydrophila.The hcp gene was amplified by PCR,and performed bioinformatics analysis.[Results]The hcp gene had a total length of 1650 bp and encoded 549 amino acids.The theoretical molecular weight of the protein predicted was about 59476.44 kDa.After predicting the N-terminal signal peptide structure of the amino acid sequence,neither obvious signal peptide cleavage site nor signal peptide was found,and the protein had no transmembrane region.The amino acid sequence had a N-glycosylation site,4 protein kinase C phosphorylation sites,7 casein kinase II phosphorylation sites,9 N-myristoylation sites,4 isoprene binding sites,10 microbody C-terminal target signal sites,and an ATP/GTP binding site motif A(P-ring).The amino acid sequence of hcp gene of A.hydrophila was performed homology analysis with other Aeromonas strains,and it showed higher homology with A.veronii.In the secondary structure,theα-helix,β-sheet,random coil and extended strand accounted for 45.36%,6.01%,37.52%and 11.11%,respectively.The tertiary structure model consisted of 18α-helix and 22β-sheet.Analysis of protein-protein network interaction demonstrated that the proteins interacting with Hcp protein were AHA_3407,nrfA,nirB-1,nirB-2 and AHA_1112.[Conclusions]Through the bioinformatics prediction results,the basic information of hcp gene of A.hydrophila is preliminarily understood,and the possible function of this protein is predicted,in order to provide guidance for subsequent vaccine research.