Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses

BACKGROUND Ulcerative colitis(UC)is an inflammatory bowel disease that is difficult to diagnose and treat.To date,the degree of inflammation in patients with UC has mainly been determined by measuring the levels of nonspecific indicators,such as C-reactive protein and the erythrocyte sedimentation rate,but these indicators have an unsatisfactory specificity.In this study,we performed bioinformatics analysis using data from the National Center for Biotechnology Information-Gene Expression Omnibus(NCBI-GEO)databases and verified the selected core genes in a mouse model of dextran sulfate sodium(DSS)-induced colitis.AIM To identify UC-related differentially expressed genes(DEGs)using a bioinformatics analysis and verify them in vivo and to identify novel biomarkers and the underlying mechanisms of UC.METHODS Two microarray datasets from the NCBI-GEO database were used,and DEGs between patients with UC and healthy controls were analyzed using GEO2R and Venn diagrams.We annotated these genes based on their functions and signaling pathways,and then protein-protein interactions(PPIs)were identified using the Search Tool for the Retrieval of Interacting Genes.The data were further analyzed with Cytoscape software and the Molecular Complex Detection(MCODE)app.The core genes were selected and a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed.Finally,colitis model mice were established by administering DSS,and the top three core genes were verified in colitis mice using real-time polymerase chain reaction(PCR).RESULTS One hundred and seventy-seven DEGs,118 upregulated and 59 downregulated,were initially identified from the GEO2R analysis and predominantly participated in inflammation-related pathways.Seven clusters with close interactions in UC formed:Seventeen core genes were upregulated[C-X-C motif chemokine ligand 13(CXCL13),C-X-C motif chemokine receptor 2(CXCR2),CXCL9,CXCL5,C-C motif chemokine ligand 18,interleukin 1 beta,matrix metallopeptidase 9,CXCL3,formyl peptide receptor 1,complement component 3,CXCL8,CXCL1,CXCL10,CXCL2,CXCL6,CXCL11 and hydroxycarboxylic acid receptor 3]and one was downregulated[neuropeptide Y receptor Y1(NYP1R)]in the top cluster according to the PPI and MCODE analyses.These genes were substantially enriched in the cytokinecytokine receptor interaction and chemokine signaling pathways.The top three core genes(CXCL13,NYP1R,and CXCR2)were selected and verified in a mouse model of colitis using real-time PCR Increased expression was observed compared with the control mice,but only CXCR2 expression was significantly different.CONCLUSION Core DEGs identified in UC are related to inflammation and immunity inflammation,indicating that these reactions are core features of the pathogenesis of UC.CXCR2 may reflect the degree of inflammation in patients with UC.

Differential analysis of intestinal microbiota and metabolites in mice with dextran sulfate sodium-induced colitis

BACKGROUND Intestinal micro-ecological imbalances impair the intestinal barrier and induce intestinal inflammation,for example,ulcerative colitis(UC).According to the latest research,abnormalities in intestinal microbiota structure and their metabolites play a dominant role in UC progression;in addition,they could affect the mucus barrier based on different factors.Although numerous studies have confirmed the important role of intestinal microbiota in UC pathogenesis,the intricate connection between microbiota and metabolites and mucus barrier in UC occurrence remains unclear,and correlation analyses of differential microbiota and their metabolites under UC are relatively scarce.AIM To reveal the differential intestinal microbiota and metabolites in UC pathogenesis and explore more sensitive biomarker compositions.METHODS We used the antibiotic combination method to establish intestinal pseudo-aseptic mice;afterward,dextran sulfate sodium(DSS)was applied to establish an acute experimental colitis mice model.Colitis severity,assessed based on disease activity index,colorectal length,colorectal wet weight,and histological lesions,and mucus-related staining(mucopolysaccharide alcian blue and immunofluorescence of mucin),was compared between the pseudo-aseptic and bacterial colitis mice.Finally,differential intestinal microbiota,metabolites,and their association and correlations,were analyzed by 16s rDNA sequencing in combination with non-targeted metabolomics,through gas chromatography-mass spectrometry.RESULTS Compared with the pseudo-aseptic mice,intestinal bacteria positive mice were more severely ill and their intestinal mucus loss was more pronounced in DSS-induced colitis(P<0.05),suggesting that different microbiota and metabolites could cause the different degrees of colitis.Subsequently,we observed that in addition to Klebsiella,and Bacteroides,which were widely associated with colitis,Candidatus Stoquefichus,Anaerobiospirillum,Muribaculum,and Negativibacillus may be involved in protection against colitis.Furthermore,differential metabolites of the microbiota were mainly enriched in the synthesis-related pathways of key structural sequences of mucin.In combination with the mucin-related staining and immunofluorescence results,the findings indicate that the differential microbiota and their metabolites potentially regulate the composition and function of mucus under colitis.CONCLUSION Microbiota and their metabolites are major factors regulating the composition and function of mucus,in turn influencing the function and structure of intestinal mucus barrier under colitis.The different microbiota and metabolites identified in the present study could be novel biomarkers for colitis.