Basic Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Oct 21, 2020; 26(39): 5983-5996
Published online Oct 21, 2020. doi: 10.3748/wjg.v26.i39.5983
Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
Lei Shi, Xiao Han, Jun-Xiang Li, Yu-Ting Liao, Fu-Shun Kou, Zhi-Bin Wang, Rui Shi, Xing-Jie Zhao, Zhong-Mei Sun, Yu Hao
Lei Shi, Yu Hao, Department of Immunology and Microbiology, School of Life Sciences, Beijing University of Chinese Medicine, Beijing 100029, China
Xiao Han, Jun-Xiang Li, Fu-Shun Kou, Zhi-Bin Wang, Rui Shi, Xing-Jie Zhao, Zhong-Mei Sun, Gastroenterology Department, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, China
Yu-Ting Liao, Department of Internal Medicine, Beijing Social Welfare Hospital, Beijing 100085, China
Author contributions: Shi L wrote the article and Han X edited it; Liao YT, Kou FS and Sun ZM performed the animal experiments; Wang ZB, Shi R and Zhao XJ analyzed the bioinformatics data; Hao Y and Li JX conducted the study.
Supported by Chinese Medicine Inheritance and Innovation “One Hundred Million” Talent Project Qihuang Scholar (to Li JX); The National Key R&D Program of China during the 13th Five-Year Plan Period, No. 2018YFC1705405; and The 66th China Postdoctoral Science Foundation, No. 2019M660575.
Institutional review board statement: The data of ulcerative colitis we analyzed in this study were all from the National Center for Biotechnology Information-Gene Expression Omnibus database. According to the guidelines approved by the National Center for Biotechnology Information-Gene Expression Omnibus, our study did not require the separate ethics committee approval.
Institutional animal care and use committee statement: We complied with the ethics standard for research activity established by the Animal Ethics Committee of Beijing University of Chinese Medicine in accordance with the guidelines issued by the Regulations of Beijing Laboratory Animal Management.
Conflict-of-interest statement: The authors declare that they have no conflicts of interest.
Data sharing statement: Database we used in this study can be shared from the National Center for Biotechnology Information-Gene Expression Omnibus databases.
ARRIVE guidelines statement: The authors have read the ARRIVE guidelines, and the manuscript was prepared and revised according to the ARRIVE guidelines.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yu Hao, PhD, Professor, Department of Immunology and Microbiology, School of Life Sciences, Beijing University of Chinese Medicine, No. 11 North Third Ring East Road, Chaoyang District, Beijing 100029, China. yuhao64@sina.com
Received: June 10, 2020
Peer-review started: June 10, 2020
First decision: August 22, 2020
Revised: August 30, 2020
Accepted: September 16, 2020
Article in press: September 16, 2020
Published online: October 21, 2020
Processing time: 133 Days and 0.3 Hours
Abstract
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 cytokine-cytokine 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.

Keywords: Ulcerative colitis; Bioinformatics analysis; C-X-C motif chemokine ligand 13; Neuropeptide Y receptor Y1; C-X-C motif chemokine receptor 2; Colitis model mice

Core Tip: Two microarray datasets were used, and differentially expressed genes were analyzed. Seventeen core genes were upregulated, and one was downregulated. These genes were markedly enriched in the cytokine-cytokine receptor interaction and chemokine signaling pathways. The top three core genes [C-X-C motif chemokine ligand 13, neuropeptide Y receptor Y1, C-X-C motif chemokine receptor 2 (CXCR2)] were verified in a dextran sulfate sodium-induced colitis model mice by real-time polymerase chain reaction and showed an increased expression, but only CXCR2 was statistically different. CXCR2 may represent a new biomarker to determine the degree of inflammation or a treatment target in ulcerative colitis.