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.

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.

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.

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.

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.

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.

Computational and bioinformatics tools for understanding disease mechanisms

Computational methods have significantly transformed biomedical research,offering a comprehensive exploration of disease mechanisms and molecular protein functions.This article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease states.The utilization of protein/gene interaction and genetic variation databases,coupled with pathway analysis can facilitate the identification of potential drug targets.By bridging the gap between molecular-level information and disease understanding,this review contributes insights into the impactful utilization of computational methods,paving the way for targeted interventions and therapeutic advancements in biomedical research.

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.

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.

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.

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.

To analyze the differentially expressed genes in chronic rejection after renal transplantation by bioinformatics

Objective: To use bioinformatics technology to analyse differentially expressed genes in chronic rejection after renal transplantation, we can screen out potential pathogenic targets associated with the development of this disease, providing a theoretical basis for finding new therapeutic targets. Methods: Gene microarray data were downloaded from the Gene Expression Profiling Integrated Database (GEO) and cross-calculated to identify differentially expressed genes (DEGs). Analysis of differentially expressed genes (DEGs) with gene ontology (GO) is a method used to study the differences in gene expression under different conditions as well as their functions and interrelationships, while Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis is a tool used to explore the functions and pathways of genes in specific biological processes. By calculating the distribution of immune cell infiltration, the result of immune infiltration in the rejection group can be analysed as a trait in Weighted Gene Co-Expression Network Analysis (WGCNA) for genes associated with rejection. Then, protein-protein interaction networks (PPI) were constructed using the STRING database and Cytoscape software to identify hub gene markers. Results: A total of 60 integrated DEGs were obtained from 3 datasets (GSE7392, GSE181757, GSE222889). By GO and KEGG analysis, the GEDs were mainly concentrated in the regulation of immune response, defence response, regulation of immune system processes, and stimulation response. The pathways were mainly enriched in antigen processing and presentation, EBV infection, graft-versus-host, allograft rejection, and natural killer cell-mediated cytotoxicity. After further screening using WGCNA and PPI networks, HLA-A, HLA-B, HLA-F, and TYROBP were identified as hub genes (Hub genes). The data GSE21374 with clinical information was selected to construct the diagnostic efficacy and risk prediction model plots of the four hub genes, and the results concluded that all four Hub genes had good diagnostic value (area under the curve in the range of 0.794-0.819). From the inference, it can be concluded that the four genes, HLA-A, HLA-B, HLA-F and TYROBP, may have an important role in the development and progression of chronic rejection after renal transplantation. Conclusion: DEGs play an important role in the study of the pathogenesis of chronic rejection after renal transplantation, and can provide theoretical support for further research on the pathogenesis of chronic rejection after renal transplantation and the discovery of new therapeutic targets through enrichment analysis and pivotal gene screening, as well as inferential analyses of related diagnostic efficacy and disease risk prediction.

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.

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).

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.

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.

Study on the effect and mechanism of Swertia mussotii Franch. in the treatment of primary biliary cholangitis based on bioinformatics and in vitro experiments

Background:Primary biliary cholangitis(PBC)is a chronic biliary autoimmune liver disease characterized by intrahepatic cholestasis.Swertia mussotii Franch.(SMF)is a Tibetan medicine with hepatoprotective and anti-inflammatory activities.In this study,the therapeutic effect and potential mechanisms of SMF on PBC were investigated by bioinformatics analysis and in vitro experimental validation,with the aim of promoting the progress of SMF and PBC research.Methods:We first explored the therapeutic effects and key targets of SMF on PBC using a network pharmacology approach,further screened the core targets using the GSE79850 dataset,and finally validated the results using molecular docking techniques and in vitro experiments.Results:By bioinformatics analysis,we identified core targets of SMF for PBC treatment(STAT3,JAK2,TNF-α,and IL-1β)and important signaling pathways:JAK-STAT,TNF,and PI3K-AKT.The molecular docking results showed that the significant components of SMF had good binding properties to the core targets.In vitro experiments showed that SMF extracts improved the extent of epithelial-mesenchymal transition in human intrahepatic biliary epithelial cells and had a significant reversal effect on epithelial-mesenchymal transition process markers and potential targets in PBC.Conclusion:SMF may exert its therapeutic effects on PBC by acting on important targets such as STAT3,JAK2,TNF-α,IL-1β,Vimentin,and E-cadherin and the pathways in which they are involved.

Molecular Cloning and Bioinformatics Analysis of sucC Gene of Vibrio alginolyticus Strain HY9901

[Objectives]To clone the sucC gene of Vibrio alginolyticus strain HY9901 and conduct the bioinformatics analysis.[Methods]Based on the sucC gene of V.alginolyticus strain HY9901,specific primers were designed to amplify the full length sequence by PCR and make further analysis.[Results]The theoretical molecular weight of SucC protein was about 41528.45 Da,and the full length was 1167 bp,encoding 388 amino acids.It has no signal peptide and transmembrane region,and has a variety of functional sites.It is predicted that it is mainly located in the cytoplasm,and the ubiquitin and lactate modification sites overlap,and it has high gene homology with Vibrio parahaemolyticus.Theα-helix,random coil and extended strand are the main secondary structures.The similarity between the constructed three-level structure model and the template is high.[Conclusions]This study reveals the structural characteristics and functional potential of SucC protein,and provides a theoretical basis for the study of drug resistance mechanism and prevention strategies.

Study on the expression and prognostic relationship of MYL6B in liver cancer based on bioinformatics

BACKGROUND Primary liver cancer is a prevalent and deadly cancer type.Despite treatment advances,prognosis remains poor,with high recurrence rates.Early detection is crucial but challenging due to the disease’s insidious nature.Myosin proteins play significant roles in cancer development,influencing cell migration,invasion,and tumor suppression.MYL6B,a myosin light chain,is involved in various cellular processes and has been associated with poor prognosis in colorectal adenocarcinoma and potential as a biomarker in breast cancer.AIM To investigate the expression of MYL6B in liver hepatocellular carcinoma(LIHC)and its impact on prognosis and potential mechanisms of action using bioinformatics methods.METHODS The expression of MYL6B in pan-cancer and normal tissues was analyzed using the gene expression profiling interactive analysis 2 and tumor immune estimation resource databases.The expression level of MYL6B in LIHC tissues and its relationship with prognosis were analyzed,immunohistochemical analysis of MYL6B and its effect on immune cell infiltration,and the protein network were further studied.RESULTS MYL6B was highly expressed in diffuse large b-cell lymphoma,LIHC,pancreatic adenocarcinoma,skin cutaneous melanoma,thymoma,uterine corpus endometrial carcinoma,uterine carcinosarcoma,and lowly expressed in kidney chromophobe,acute myeloid leukemia,testicular germ cell tumors.The expression level of MYL6B was significantly different between cancer and normal tissues.It had a significant impact on both overall survival and disease-free survival.MYL6B is highly expressed in hepatocellular carcinoma and its expression level increases with cancer progression.High MYL6B expression is associated with poor prognosis in terms of overall survival and recurrence-free survival.The immunohistochemical level of MYL6B is high in hepatocellular carcinoma tissues,and MYL6B has a high level of immune infiltration inflammation.In protein network analysis,MYL6B is correlated with MYL2,MYL6,MYL9,MYLK4,MYLK2,MYL12A,MYL12B,MYH11,MYH9 and MYH10.CONCLUSION The expression level of MYL6B in LIHC was significantly higher than in normal liver tissues,and it was correlated with the degree of differentiation survival rate,and immune infiltration.MYL6B is a potential target for LIHC treatment.

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

Vibrio alginolyticus is a zoonotic bacterium.A pair of specific primers was designed using the sodB gene sequence of Vibrio alginolyticus HY9901 in order to amplify the full length of the gene by PCR.The results indicated that the total length of the sodB gene was 585 bp and that it could encode 194 amino acids.The predicted amino acid sequence derivation indicated that the molecular weight of the protein was approximately 21.56 kDa,with an isoelectric point of 4.95.Upon prediction of the N-terminal signal peptide structure of the protein,no significant signal peptide cleavage site was observed,indicating that the protein lacked both a signal peptide and a transmembrane region.The amino acid sequence contained an N-glycosylation site,a casein kinase II phosphorylation site,a microsomal C-terminal target signal site,and a manganese and iron superoxide dismutase signal site.The probability of intracytoplasmic localization of the SodB protein was 56.5%,which was analyzed according to the subcellular localization of the protein.The amino acid sequence of the sodB gene of V.alginolyticus exhibited 98%-100%homology to other Vibrio species,clustering into the same subfamily with V.parahaem,indicating a relatively close relationship between them.In the prediction of protein structure,the proportions ofα-helix,random coil,β-sheet,and extended strand were 48.45%,30.41%,5.67%,and 15.46%,respectively.The similarity to template 1dt0.1.A reached 71.58%.A PTM site analysis revealed the presence of phosphorylation,glycosylation,ubiquitination,sumoylation,acetylation,and methylation modification sites,as well as the absence of lactylation modification sites.