Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages
Tuberculosis (TB) is still a leading cause of death worldwide. Treatments remain unsatisfactory due to an incomplete understanding of the underlying host–pathogen interactions during infection. In the present study, weighted gene co-expression network analysis (WGCNA) was conducted to identify key m...
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MDPI AG
2021-01-01
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author | Lu Lu RanLei Wei Sanjib Bhakta Simon J. Waddell Ester Boix |
author_facet | Lu Lu RanLei Wei Sanjib Bhakta Simon J. Waddell Ester Boix |
author_sort | Lu Lu |
collection | DOAJ |
description | Tuberculosis (TB) is still a leading cause of death worldwide. Treatments remain unsatisfactory due to an incomplete understanding of the underlying host–pathogen interactions during infection. In the present study, weighted gene co-expression network analysis (WGCNA) was conducted to identify key macrophage modules and hub genes associated with mycobacterial infection. WGCNA was performed combining our own transcriptomic results using <i>Mycobacterium aurum</i>-infected human monocytic macrophages (THP1) with publicly accessible datasets obtained from three types of macrophages infected with seven different mycobacterial strains in various one-to-one combinations. A hierarchical clustering tree of 11,533 genes was built from 198 samples, and 47 distinct modules were revealed. We identified a module, consisting of 226 genes, which represented the common response of host macrophages to different mycobacterial infections that showed significant enrichment in innate immune stimulation, bacterial pattern recognition, and leukocyte chemotaxis. Moreover, by network analysis applied to the 74 genes with the best correlation with mycobacteria infection, we identified the top 10 hub-connecting genes: <i>NAMPT</i>, <i>IRAK2</i>, <i>SOCS3</i>, <i>PTGS2</i>, <i>CCL20</i>, <i>IL1B</i>, <i>ZC3H12A</i>, <i>ABTB2</i>, <i>GFPT2,</i> and <i>ELOVL7</i>. Interestingly, apart from the well-known Toll-like receptor and inflammation-associated genes, other genes may serve as novel TB diagnosis markers and potential therapeutic targets. |
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language | English |
last_indexed | 2024-03-09T04:15:30Z |
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spelling | doaj.art-e5d2a6e2265d4371970a94abf22959d12023-12-03T13:55:53ZengMDPI AGAntibiotics2079-63822021-01-011029710.3390/antibiotics10020097Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human MacrophagesLu Lu0RanLei Wei1Sanjib Bhakta2Simon J. Waddell3Ester Boix4College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 610000, ChinaLaboratory of Omics Technology and Bioinformatics, West China Hospital, Sichuan University, Chengdu 610017, ChinaMycobacteria Research Laboratory, Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London WC1E 7HX, UKGlobal Health and Infection, Brighton and Sussex Medical School, University of Sussex, Brighton BN1 9PX, UKDepartment of Biochemistry and Molecular Biology, Faculty of Biosciences, Universitat Autonoma de Barcelona, 08290 Cerdanyola del Vallès, SpainTuberculosis (TB) is still a leading cause of death worldwide. Treatments remain unsatisfactory due to an incomplete understanding of the underlying host–pathogen interactions during infection. In the present study, weighted gene co-expression network analysis (WGCNA) was conducted to identify key macrophage modules and hub genes associated with mycobacterial infection. WGCNA was performed combining our own transcriptomic results using <i>Mycobacterium aurum</i>-infected human monocytic macrophages (THP1) with publicly accessible datasets obtained from three types of macrophages infected with seven different mycobacterial strains in various one-to-one combinations. A hierarchical clustering tree of 11,533 genes was built from 198 samples, and 47 distinct modules were revealed. We identified a module, consisting of 226 genes, which represented the common response of host macrophages to different mycobacterial infections that showed significant enrichment in innate immune stimulation, bacterial pattern recognition, and leukocyte chemotaxis. Moreover, by network analysis applied to the 74 genes with the best correlation with mycobacteria infection, we identified the top 10 hub-connecting genes: <i>NAMPT</i>, <i>IRAK2</i>, <i>SOCS3</i>, <i>PTGS2</i>, <i>CCL20</i>, <i>IL1B</i>, <i>ZC3H12A</i>, <i>ABTB2</i>, <i>GFPT2,</i> and <i>ELOVL7</i>. Interestingly, apart from the well-known Toll-like receptor and inflammation-associated genes, other genes may serve as novel TB diagnosis markers and potential therapeutic targets.https://www.mdpi.com/2079-6382/10/2/97mycobacteriummacrophageWGCNAtranscriptomenetwork analysis |
spellingShingle | Lu Lu RanLei Wei Sanjib Bhakta Simon J. Waddell Ester Boix Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages Antibiotics mycobacterium macrophage WGCNA transcriptome network analysis |
title | Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages |
title_full | Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages |
title_fullStr | Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages |
title_full_unstemmed | Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages |
title_short | Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages |
title_sort | weighted gene co expression network analysis identifies key modules and hub genes associated with mycobacterial infection of human macrophages |
topic | mycobacterium macrophage WGCNA transcriptome network analysis |
url | https://www.mdpi.com/2079-6382/10/2/97 |
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