Jafarinejad-Farsangi Saeideh, Jazi Maryam Moazzam, Rostamzadeh Farzaneh, Hadizadeh Morteza
Physiology Research Center, Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences, Kerman, Iran.
Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Noncoding RNA Res. 2020 Dec;5(4):222-231. doi: 10.1016/j.ncrna.2020.11.005. Epub 2020 Nov 21.
Coronavirus disease 2019 (COVID-19) caused by a novel betacoronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has attracted top health concerns worldwide within a few months after its appearance. Since viruses are highly dependent on the host small RNAs (microRNAs) for their replication and propagation, in this study, top miRNAs targeting SARS-CoV-2 genome and top miRNAs targeting differentially expressed genes (DEGs) in lungs of patients infected with SARS-CoV-2, were predicted.
All human mature miRNA sequences were acquired from miRBase database. MiRanda tool was used to predict the potential human miRNA binding sites on the SARS-CoV-2 genome. EdgeR identified differentially expressed genes (DEGs) in response to SARS-CoV-2 infection from GEO147507 data. Gene Set Enrichment Analysis (GSEA) and DEGs annotation analysis were performed using ToppGene and Metascape tools.
160 miRNAs with a perfect matching in the seed region were identified. Among them, there was 15 miRNAs with more than three binding sites and 12 miRNAs with a free energy binding of -29 kCal/Mol. MiR-29 family had the most binding sites (11 sites) on the SARS-CoV-2 genome. MiR-21 occupied four binding sites and was among the top miRNAs that targeted up-regulated DEGs. In addition to miR-21, miR-16, let-7b, let-7e, and miR-146a were the top miRNAs targeting DEGs.
Collectively, more experimental studies especially miRNA-based studies are needed to explore detailed molecular mechanisms of SARS-CoV-2 infection. Moreover, the role of DEGs including STAT1, CCND1, CXCL-10, and MAPKAPK2 in SARS-CoV-2 should be investigated to identify the similarities and differences between SARS-CoV-2 and other respiratory viruses.
由一种名为严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的新型β冠状病毒引起的2019冠状病毒病(COVID-19)在出现后的几个月内引起了全球最高的健康关注。由于病毒高度依赖宿主小RNA(微小RNA)进行复制和传播,在本研究中,预测了靶向SARS-CoV-2基因组的顶级微小RNA以及靶向感染SARS-CoV-2患者肺部差异表达基因(DEG)的顶级微小RNA。
从miRBase数据库获取所有人类成熟微小RNA序列。使用MiRanda工具预测SARS-CoV-2基因组上潜在的人类微小RNA结合位点。EdgeR从GEO147507数据中识别出响应SARS-CoV-2感染的差异表达基因(DEG)。使用ToppGene和Metascape工具进行基因集富集分析(GSEA)和DEG注释分析。
鉴定出160个在种子区域完全匹配的微小RNA。其中,有15个微小RNA具有三个以上的结合位点,12个微小RNA的结合自由能为-29千卡/摩尔。MiR-29家族在SARS-CoV-2基因组上具有最多的结合位点(11个位点)。MiR-21占据四个结合位点,是靶向上调DEG的顶级微小RNA之一。除了MiR-21,MiR-16、let-7b、let-7e和MiR-146a是靶向DEG的顶级微小RNA。
总体而言,需要更多的实验研究,尤其是基于微小RNA的研究,以探索SARS-CoV-2感染的详细分子机制。此外,应研究包括STAT1、CCND1、CXCL-10和MAPKAPK2在内的DEG在SARS-CoV-2中的作用,以确定SARS-CoV-2与其他呼吸道病毒之间的异同。