Qi Mingran, Liu Bin, Li Shuai, Ni Zhaohui, Li Fan
Department of Pathogenobiology, The Key Laboratory of Zoonosis, Chinese Ministry of Education, College of Basic Medicine, Jilin University, Changchun, Jilin, People's Republic of China.
Cardiovascular Disease Center, The First Hospital of Jilin University, Changchun, Jilin, People's Republic of China.
Int J Gen Med. 2021 Oct 12;14:6647-6659. doi: 10.2147/IJGM.S335162. eCollection 2021.
The current COVID-19 pandemic caused by a novel coronavirus SARS-CoV-2 is a quickly developing global health crisis, yet the mechanisms of pathogenesis in COVID-19 are not fully understood.
The RNA sequencing data of SARS-CoV-2-infected cells was obtained from the Gene Expression Omnibus (GEO). The differentially expressed mRNAs (DEmRNAs), long non-coding RNAs (DElncRNAs), and microRNAs (DEmiRNAs) were identified by edgeR, and the SARS-CoV-2-associated competing endogenous RNA (ceRNA) network was constructed based on the prediction of bioinformatic databases. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted with the SARS-CoV-2-related DEmRNAs, and the protein-protein interaction network was also built basing on STRING database. The ROC analysis was performed for assessing the diagnostic efficiency of hub genes.
The results indicated that SARS-CoV-2-related DEmRNAs were associated with the interferon signaling pathway and other antiviral processes, such as IFNL3, IFNL1 and CH25H. Our analysis suggested that lncRNA NEAT1 might regulate the host immune response through two miRNAs, hsa-miR-374-5p and hsa-miR-155-5p, which control the expression of SOCS1, IL6, IL1B, CSF1R, CD274, TLR6, and TNF. Additionally, IFI6, HRASLS2, IGFBP4 and PTN may be potential targets based on an analysis comparing the transcriptional responses of SARS-CoV-2 infection with that of other respiratory viruses.
The unique ceRNA network identified potential non-coding RNAs and their possible targets as well as a new perspective to understand the molecular mechanisms of the host immune response to SARS-CoV-2. This study may also aid in the development of innovative diagnostic and therapeutic strategies.
由新型冠状病毒SARS-CoV-2引起的当前COVID-19大流行是一场迅速发展的全球健康危机，然而COVID-19的发病机制尚未完全了解。
从基因表达综合数据库（GEO）获得SARS-CoV-2感染细胞的RNA测序数据。通过edgeR鉴定差异表达的mRNA（DEmRNA）、长链非编码RNA（DElncRNA）和微小RNA（DEmiRNA），并基于生物信息学数据库的预测构建SARS-CoV-2相关的竞争性内源性RNA（ceRNA）网络。使用与SARS-CoV-2相关的DEmRNA进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析，并基于STRING数据库构建蛋白质-蛋白质相互作用网络。进行ROC分析以评估枢纽基因的诊断效率。
结果表明，与SARS-CoV-2相关的DEmRNA与干扰素信号通路和其他抗病毒过程相关，如IFNL3、IFNL1和CH25H。我们的分析表明，lncRNA NEAT1可能通过两种miRNA，即hsa-miR-374-5p和hsa-miR-155-5p调节宿主免疫反应，这两种miRNA控制SOCS1、IL6、IL1B、CSF1R、CD274、TLR6和TNF的表达。此外，基于比较SARS-CoV-2感染与其他呼吸道病毒的转录反应分析，IFI6、HRASLS2、IGFBP4和PTN可能是潜在靶点。
独特的ceRNA网络确定了潜在的非编码RNA及其可能的靶点，以及理解宿主对SARS-CoV-2免疫反应分子机制的新视角。本研究也可能有助于创新诊断和治疗策略的开发。
