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Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis
Influenza A virus (IAV) requires the host cellular machinery for many aspects of its life cycle. Knowledge of these host cell requirements not only reveals molecular pathways exploited by the virus or triggered by the immune system but also provides further targets for antiviral drug development. To...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332270/ https://www.ncbi.nlm.nih.gov/pubmed/35893690 http://dx.doi.org/10.3390/v14081625 |
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author | Chen, Gao Li, Haoyue Hao, Mingzhao Li, Xiaolei Dong, Yizhi Zhang, Yue Liu, Xiping Lu, Cheng Zhao, Jing |
author_facet | Chen, Gao Li, Haoyue Hao, Mingzhao Li, Xiaolei Dong, Yizhi Zhang, Yue Liu, Xiping Lu, Cheng Zhao, Jing |
author_sort | Chen, Gao |
collection | PubMed |
description | Influenza A virus (IAV) requires the host cellular machinery for many aspects of its life cycle. Knowledge of these host cell requirements not only reveals molecular pathways exploited by the virus or triggered by the immune system but also provides further targets for antiviral drug development. To uncover critical pathways and potential targets of influenza infection, we assembled a large amount of data from 8 RNA sequencing studies of IAV infection for integrative network analysis. Weighted gene co-expression network analysis (WGCNA) was performed to investigate modules and genes correlated with the time course of infection and/or multiplicity of infection (MOI). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the biological functions and pathways of the genes in 5 significant modules. Top hub genes were identified using the cytoHubba plugin in the protein interaction network. The correlation between expression levels of 7 top hub genes and time course or MOI was displayed and validated, including BCL2L13, PLSCR1, ARID5A, LMO2, NDRG4, HAP1, and CARD10. Dysregulated expression of these genes potently impacted the development of IAV infection through modulating IAV-related biological processes and pathways. This study provides further insights into the underlying molecular mechanisms and potential targets in IAV infection. |
format | Online Article Text |
id | pubmed-9332270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93322702022-07-29 Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis Chen, Gao Li, Haoyue Hao, Mingzhao Li, Xiaolei Dong, Yizhi Zhang, Yue Liu, Xiping Lu, Cheng Zhao, Jing Viruses Article Influenza A virus (IAV) requires the host cellular machinery for many aspects of its life cycle. Knowledge of these host cell requirements not only reveals molecular pathways exploited by the virus or triggered by the immune system but also provides further targets for antiviral drug development. To uncover critical pathways and potential targets of influenza infection, we assembled a large amount of data from 8 RNA sequencing studies of IAV infection for integrative network analysis. Weighted gene co-expression network analysis (WGCNA) was performed to investigate modules and genes correlated with the time course of infection and/or multiplicity of infection (MOI). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the biological functions and pathways of the genes in 5 significant modules. Top hub genes were identified using the cytoHubba plugin in the protein interaction network. The correlation between expression levels of 7 top hub genes and time course or MOI was displayed and validated, including BCL2L13, PLSCR1, ARID5A, LMO2, NDRG4, HAP1, and CARD10. Dysregulated expression of these genes potently impacted the development of IAV infection through modulating IAV-related biological processes and pathways. This study provides further insights into the underlying molecular mechanisms and potential targets in IAV infection. MDPI 2022-07-26 /pmc/articles/PMC9332270/ /pubmed/35893690 http://dx.doi.org/10.3390/v14081625 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Gao Li, Haoyue Hao, Mingzhao Li, Xiaolei Dong, Yizhi Zhang, Yue Liu, Xiping Lu, Cheng Zhao, Jing Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis |
title | Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis |
title_full | Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis |
title_fullStr | Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis |
title_full_unstemmed | Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis |
title_short | Identification of Critical Genes and Pathways for Influenza A Virus Infections via Bioinformatics Analysis |
title_sort | identification of critical genes and pathways for influenza a virus infections via bioinformatics analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332270/ https://www.ncbi.nlm.nih.gov/pubmed/35893690 http://dx.doi.org/10.3390/v14081625 |
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