Functional Analysis of Monkeypox and Interrelationship between Monkeypox and COVID-19 by Bioinformatic Analysis.

IF 1.4 4区 生物学 Q4 GENETICS & HEREDITY Genetics research Pub Date : 2023-03-23 eCollection Date: 2023-01-01 DOI:10.1155/2023/8511036
Eun Jung Sohn
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Abstract

The outbreak of monkeypox may be considered a novel and urgent threat after the coronavirus disease (COVID-19). No wide-ranging studies have been conducted on this disease since it was first reported. We systematically assessed the functional role of gene expression in cells infected with the monkeypox virus using transcriptome profiling and compared the functional relation with that of COVID-19. Based on the Gene Expression Omnibus database, we obtained 212 differentially expressed genes (DEGs) of GSE36854 and GSE21001 of monkeypox datasets. Enrichment analyses, including KEGG and gene ontology (GO) analyses, were performed to identify the common function of 212 DEGs of GSE36854 and GSE21001. CytoHubba and Molecular Complex Detection were performed to determine the core genes after a protein-protein interaction (PPI). Metascape/COVID-19 was used to compare DEGs of monkeypox and COVID-19. GO analysis of 212 DEGs of GSE36854 and GSE21001 for monkeypox infection showed cellular response to cytokine stimulus, cell activation, and cell differentiation regulation. KEGG analysis of 212 DEGs of GSE36854 and GSE21001 for monkeypox infection showed involvement of monkeypox in COVID-19, cytokine-cytokine receptor interaction, inflammatory bowel disease, atherosclerosis, TNF signaling, and T cell receptor signaling. By comparing our data with published transcriptome of severe acute respiratory syndrome coronavirus 2 infections in other cell lines, the common function of monkeypox and COVID-19 includes cytokine signaling in the immune system, TNF signaling, and MAPK cascade regulation. Thus, our data suggest that the molecular connections identified between COVID-19 and monkeypox elucidate the causes of monkeypox.

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通过生物信息学分析对猴痘的功能分析以及猴痘与 COVID-19 的相互关系。
继冠状病毒病(COVID-19)之后,猴痘的爆发可被视为一种新的紧迫威胁。自首次报道以来,尚未对该疾病进行过广泛的研究。我们利用转录组图谱系统地评估了猴痘病毒感染细胞中基因表达的功能作用,并比较了其与 COVID-19 的功能关系。基于基因表达总库(Gene Expression Omnibus)数据库,我们从猴痘数据集 GSE36854 和 GSE21001 中获得了 212 个差异表达基因(DEGs)。我们进行了富集分析,包括KEGG和基因本体(GO)分析,以确定GSE36854和GSE21001中212个差异表达基因的共同功能。为了确定蛋白-蛋白相互作用(PPI)后的核心基因,研究人员进行了 CytoHubba 和分子复合物检测。Metascape/COVID-19 用于比较猴痘和 COVID-19 的 DEGs。对猴痘感染的 GSE36854 和 GSE21001 的 212 个 DEGs 进行的 GO 分析表明,细胞对细胞因子刺激的反应、细胞活化和细胞分化调控。对猴痘感染的GSE36854和GSE21001的212个DEGs进行的KEGG分析表明,猴痘参与了COVID-19、细胞因子-细胞因子受体相互作用、炎症性肠病、动脉粥样硬化、TNF信号转导和T细胞受体信号转导。通过将我们的数据与已发表的其他细胞系感染严重急性呼吸系统综合征冠状病毒2的转录组进行比较,猴痘和COVID-19的共同功能包括免疫系统中的细胞因子信号转导、TNF信号转导和MAPK级联调控。因此,我们的数据表明,在 COVID-19 和猴痘之间发现的分子联系阐明了猴痘的病因。
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来源期刊
Genetics research
Genetics research 生物-遗传学
自引率
6.70%
发文量
74
审稿时长
>12 weeks
期刊介绍: Genetics Research is a key forum for original research on all aspects of human and animal genetics, reporting key findings on genomes, genes, mutations and molecular interactions, extending out to developmental, evolutionary, and population genetics as well as ethical, legal and social aspects. Our aim is to lead to a better understanding of genetic processes in health and disease. The journal focuses on the use of new technologies, such as next generation sequencing together with bioinformatics analysis, to produce increasingly detailed views of how genes function in tissues and how these genes perform, individually or collectively, in normal development and disease aetiology. The journal publishes original work, review articles, short papers, computational studies, and novel methods and techniques in research covering humans and well-established genetic organisms. Key subject areas include medical genetics, genomics, human evolutionary and population genetics, bioinformatics, genetics of complex traits, molecular and developmental genetics, Evo-Devo, quantitative and statistical genetics, behavioural genetics and environmental genetics. The breadth and quality of research make the journal an invaluable resource for medical geneticists, molecular biologists, bioinformaticians and researchers involved in genetic basis of diseases, evolutionary and developmental studies.
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