Identification of Key Pathways and Genes in SARS-CoV-2 Infecting Human Intestines by Bioinformatics Analysis.

Autor: Chen JC; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China., Xie TA; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China., Lin ZZ; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China., Li YQ; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China., Xie YF; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China., Li ZW; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China., Guo XG; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com.; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com.; Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com.; Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com.
Jazyk: angličtina
Zdroj: Biochemical genetics [Biochem Genet] 2022 Jun; Vol. 60 (3), pp. 1076-1094. Date of Electronic Publication: 2021 Nov 17.
DOI: 10.1007/s10528-021-10144-w
Abstrakt: COVID-19 is a serious infectious disease that has recently swept the world, and research on its causative virus, SARS-CoV-2, remains insufficient. Therefore, this study uses bioinformatics analysis techniques to explore the human digestive tract diseases that may be caused by SARS-CoV-2 infection. The gene expression profile data set, numbered GSE149312, is from the Gene Expression Omnibus (GEO) database and is divided into a 24-h group and a 60-h group. R software is used to analyze and screen out differentially expressed genes (DEGs) and then gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses are performed. In KEGG, the pathway of non-alcoholic fatty liver disease exists in both the 24-h group and 60-h group. STRING is used to establish a protein-protein interaction (PPI) network, and Cytoscape is then used to visualize the PPI and define the top 12 genes of the node as the hub genes. Through verification, nine statistically significant hub genes are identified: AKT1, TIMP1, NOTCH, CCNA2, RRM2, TTK, BUB1B, KIF20A, and PLK1. In conclusion, the results of this study can provide a certain direction and basis for follow-up studies of SARS-CoV-2 infection of the human digestive tract and provide new insights for the prevention and treatment of diseases caused by SARS-CoV-2.
(© 2021. The Author(s).)
Databáze: MEDLINE
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