A bioinformatics approach to systematically analyze the molecular patterns of monkeypox virus-host cell interactions

Autor: Zhongxiang Tang, Ying Han, Yuting Meng, Jiani Li, Xiangjie Qiu, Ousman Bajinka, Guojun Wu, Yurong Tan
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Heliyon, Vol 10, Iss 9, Pp e30483- (2024)
Druh dokumentu: article
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2024.e30483
Popis: Monkeypox has been spreading worldwide since May 2022, when the World Health Organization (WHO) declared the outbreak a “public health emergency of international concern.” The spread of monkeypox has posed a serious threat to the health of people around the world, but few studies have been conducted, and the molecular mechanism of monkeypox after infection remains unclear. We therefore implemented a transcriptome analysis to identify signaling pathways and biomarkers in monkeypox-infected cells to help understand monkeypox-host cell interactions. In this study, datasets GSE36854 and GSE11234 were obtained from GEO. Of these, 84 significantly different genes were identified in the dataset GSE36854, followed by KEGG, GO analysis protein-protein interaction (PPI) construction, and Hub gene extraction. We also analyzed the expression regulation of hub genes and screened for drugs targeting hub genes. The results showed that monkeypox-infected cells significantly activated the cellular immune response. The top 10 hub genes are IER3, IFIT2, IL11, ZC3H12A, EREG, IER2, NFKBIE, FST, IFIT1 and AREG. AP-26113 and itraconazole can be used to counteract the inhibitory effect of monkeypox on IFIT1 and IFIT2 and serve as candidate drugs for the treatment of monkeypox virus infection. IRF1 may also be a transcription factor of IFIT. Our results provide a new entry point for understanding how monkeypox virus interacts with its host.
Databáze: Directory of Open Access Journals