Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Hub Genes Associated with Mycobacterial Infection of Human Macrophages
Lu, Lu (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Waddell, Simon J. (University of Sussex. Brighton and Sussex Medical School)
Boix i Borràs, Esther (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Wei, RanLei (Sichuan University. Laboratory of Omics Technology and Bioinformatics)
Bhakta, Sanjib (University of London. Department of Biological Sciences)

Data:	2021
Resum:	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 Mycobacterium aurum-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: NAMPT, IRAK2, SOCS3, PTGS2, CCL20, IL1B, ZC3H12A, ABTB2, GFPT2, and ELOVL7. 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.
Ajuts:	Ministerio de Economía y Competitividad SAF2015-66007P Ministerio de Economía y Competitividad PID2019-106123GB-I00
Nota:	E.B. va ser guardonat amb un ajut de la Fundació La Marató de TV3, ref. 20180310.
Nota:	Aquest article té una correcció a 10.3390/antibiotics10070792
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Mycobacterium ; Macrophage ; WGCNA ; Transcriptome ; Network analysis
Publicat a:	Antibiotics, Vol. 10, Num. 2 (February 2021) , art. 97, ISSN 2079-6382

Correcció de l'article: https://ddd.uab.cat/record/256309
DOI: 10.3390/antibiotics10020097
PMID: 33498280

16 p, 3.9 MB

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