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Gene network in pulmonary tuberculosis based on bioinformatic analysis
BACKGROUND: Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear. METHODS: This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436983/ https://www.ncbi.nlm.nih.gov/pubmed/32811479 http://dx.doi.org/10.1186/s12879-020-05335-6 |
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author | Li, Lili Lv, Jian He, Yuan Wang, Zhihua |
author_facet | Li, Lili Lv, Jian He, Yuan Wang, Zhihua |
author_sort | Li, Lili |
collection | PubMed |
description | BACKGROUND: Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear. METHODS: This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment. RESULTS: Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy. CONCLUSIONS: Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs. |
format | Online Article Text |
id | pubmed-7436983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-74369832020-08-20 Gene network in pulmonary tuberculosis based on bioinformatic analysis Li, Lili Lv, Jian He, Yuan Wang, Zhihua BMC Infect Dis Research Article BACKGROUND: Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear. METHODS: This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment. RESULTS: Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy. CONCLUSIONS: Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs. BioMed Central 2020-08-18 /pmc/articles/PMC7436983/ /pubmed/32811479 http://dx.doi.org/10.1186/s12879-020-05335-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Li, Lili Lv, Jian He, Yuan Wang, Zhihua Gene network in pulmonary tuberculosis based on bioinformatic analysis |
title | Gene network in pulmonary tuberculosis based on bioinformatic analysis |
title_full | Gene network in pulmonary tuberculosis based on bioinformatic analysis |
title_fullStr | Gene network in pulmonary tuberculosis based on bioinformatic analysis |
title_full_unstemmed | Gene network in pulmonary tuberculosis based on bioinformatic analysis |
title_short | Gene network in pulmonary tuberculosis based on bioinformatic analysis |
title_sort | gene network in pulmonary tuberculosis based on bioinformatic analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436983/ https://www.ncbi.nlm.nih.gov/pubmed/32811479 http://dx.doi.org/10.1186/s12879-020-05335-6 |
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