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通过生物信息学和系统生物学方法发现 COVID-19 和结核病之间的共同发病机制。

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

机构信息

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.

Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, China.

出版信息

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

DOI:10.3389/fcimb.2023.1280223
PMID:38162574
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10757339/
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 () 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.

摘要

简介

由严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的 2019 年冠状病毒病(COVID-19)大流行持续威胁着全球卫生系统。与此同时,在世界许多地区,由 ()引起的结核病(TB)仍然流行。COVID-19 和 TB 的临床特征有一定程度的相似,但 COVID-19 和 TB 之间潜在的发病机制过程尚不清楚。

方法

为了阐明 COVID-19 和 TB 之间的共同发病机制,我们进行了生物信息学和系统研究,以获得共享途径和分子生物标志物。在这里,使用 RNA-seq 数据集(GSE196822 和 GSE126614)提取 COVID-19 和 TB 的共享差异表达基因(DEGs)。将共同的 DEGs 用于识别共同途径、枢纽基因、转录调控网络和潜在药物。

结果

共选择了 96 个共同的 DEGs 进行后续分析。功能富集分析表明,病毒基因组复制和免疫相关途径共同促进了 TB 和 COVID-19 的发生和发展。基于蛋白质-蛋白质相互作用(PPI)网络分析,我们鉴定出 10 个枢纽基因,包括 IFI44L、ISG15、MX1、IFI44、OASL、RSAD2、GBP1、OAS1、IFI6 和 HERC5。随后,转录因子(TF)-基因相互作用和 microRNA(miRNA)-基因核心调控网络鉴定出 61 个 TF 和 29 个 miRNA。值得注意的是,我们发现了 10 种治疗 TB 和 COVID-19 的潜在药物,即舒洛地特、prenylamine、乙酰己脲、特非那定、丙氯拉嗪、3'-叠氮-3'-脱氧胸苷、叶绿素、依托泊苷、氯喹醇和异丙酚。

结论

本研究为结核病和 COVID-19 的治疗提供了新的策略和有价值的参考。

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