Evaluation of differentially expressed genes during replication using gene expression landscape of monkeypox-infected MK2 cells: A bioinformatics and systems biology approach to understanding the genomic pattern of viral replication

Purpose: The current outbreak of monkeypox (MPX) has created colossal concerns. However, immense research gaps have been noted in our understanding of the replication process, machinery, and genomic landscape during host cell infection. To fill this gap, differentially expressed genes (DEGs) were co...

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Bibliographic Details
Main Authors: Chiranjib Chakraborty, Manojit Bhattacharya, Kuldeep Dhama, Sang-Soo Lee
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Journal of Infection and Public Health
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1876034123000254
Description
Summary:Purpose: The current outbreak of monkeypox (MPX) has created colossal concerns. However, immense research gaps have been noted in our understanding of the replication process, machinery, and genomic landscape during host cell infection. To fill this gap, differentially expressed genes (DEGs) were comprehensively analyzed during viral replication in host (MK2) cells. Methods: We used a microarray GEO dataset which was divided into three groups: control, MPXV-infected MK2 cells at 3 h, and MPXV-infected MK2 cells at 7 h. Using the dataset, DEG analysis, PPI network analysis, co-expression, and pathway analysis were conducted using bioinformatics, systems biology, and statistical approaches. Results: We identified 250 DEGs and 24 top-ranked genes. During the DEG analysis, we identified eight up-regulated genes (LOC695323, TMEM107, LOC695427, HIST1H2AD, LOC705469, PMAIP1, HIST1H2BJ, and HIST1H3D) and 16 down-regulated genes (HOXA9, BAMBI, LMO4, PAX6, AJUBA, CREBRF, CD24, JADE1, SLC7A11, EID2, SOX4, B4GALT5, PPARGC1A, BUB3, SOS2, and CDK19). We also developed PPI networks and performed co-expression analyses using the top-ranked genes. Furthermore, five genes were listed for co-expression pattern analysis. Conclusions: This study will help in better understanding the replication process, machinery, and genomic landscape of the virus. This will further aid the discovery and development of therapeutics against viruses.
ISSN:1876-0341