COVID-19 Research Paper Volume 13, Issue 7 pp 9160—9185
TMBIM6, a potential virus target protein identified by integrated multiomics data analysis in SARS-CoV-2-infected host cells
- 1 Guangdong Provincial Key Laboratory of Proteomics, State Key Laboratory of Organ Failure Research, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
- 2 Department of Respiratory and Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
Received: September 18, 2020 Accepted: February 16, 2021 Published: March 19, 2021
https://doi.org/10.18632/aging.202718How to Cite
Copyright: © 2021 Han et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we collected open access data to analyze the mechanisms associated with SARS-CoV-2 infection. Gene set enrichment analysis (GSEA) revealed that apoptosis-related pathways were enriched in the cells after SARS-CoV-2 infection, and the results of differential expression analysis showed that biological functions related to endoplasmic reticulum stress (ERS) and lipid metabolism were disordered. TMBIM6 was identified as a potential target for SARS-CoV-2 in host cells through weighted gene coexpression network analysis (WGCNA) of the time course of expression of host and viral proteins. The expression and related functions of TMBIM6 were subsequently analyzed to illuminate how viral proteins interfere with the physiological function of host cells. The potential function of viral proteins was further analyzed by GEne Network Inference with Ensemble of trees (GENIE3). This study identified TMBIM6 as a target protein associated with the pathogenesis of SARS-CoV-2, which might provide a novel therapeutic approach for COVID-19 in the future.
Abbreviations
COVID-19: Coronavirus disease 2019; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; GSEA: gene set enrichment analysis; ERS: endoplasmic reticulum stress; WGCNA: weighted gene coexpression network analysis; GENIE3: GEne Network Inference with Ensemble of trees; ARDS: acute respiratory distress syndrome; nsp: nonstructural protein; ORFs: open reading frames; RNA seq: RNA sequencing; S: spike; E: envelope; N: nucleocapsid; M: membrane; IAV: influenza A virus; RSV: respiratory syncytial virus; ER: endoplasmic reticulum; DEGs: differentially expressed genes; DEPs: differentially expressed proteins; NDEGs: non-differentially expressed genes; NDEPs: non-differentially expressed proteins; GO: Gene Ontology; GEPIA2: Gene Expression Profiling Interactive Analysis; HPA: the Human Protein Atlas; UPR: unfolded protein response; ROS: reactive oxygen species; TOM: topological overlap matrix; WebGestalt: WEB-based gene set analysis toolkit; PP: PredictProtein.