Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Tengda Huang; Jinyi He; Xinyi Zhou; Hongyuan Pan; Fang He; Ao Du; Bingxuan Yu; Nan Jiang; Xiaoquan Li; Kefei Yuan; Zhen Wang

doi:10.3389/fcimb.2023.1280223

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Front Cell Infect Microbiol. 2023 Dec 15:13:1280223. doi: 10.3389/fcimb.2023.1280223. eCollection 2023.

Authors

Tengda Huang^#¹, Jinyi He^#¹, Xinyi Zhou¹, Hongyuan Pan¹, Fang He², Ao Du¹, Bingxuan Yu¹, Nan Jiang¹, Xiaoquan Li¹, Kefei Yuan¹, Zhen Wang¹

Affiliations

¹ Division of Liver Surgery, Department of General Surgery and Laboratory of Liver Surgery, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
² Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.

^# Contributed equally.

Abstract

Introduction: The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood.

Methods: To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs.

Results: A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol.

Conclusion: This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Keywords: SARS-CoV-2; differentially expressed genes; drug molecule; hub gene; protein-protein interaction (PPI); tuberculosis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19*
Computational Biology
Gene Expression Profiling
Genes, Regulator
Humans
MicroRNAs*
Mycobacterium tuberculosis* / genetics
SARS-CoV-2 / genetics
Tuberculosis* / genetics

Substances

MicroRNAs

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by grants from the Natural Science Foundation of China (82370645, 82270643, 82070644, and 82170621), the National multidisciplinary collaborative diagnosis and treatment capacity building project for major diseases (TJZ202104), the Science and Technology Major Program of Sichuan Province (2022ZDZX0019), and the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (ZYJC18008, ZYGD22006).