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Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis
BACKGROUND: Airway epithelium is the primary target for pathogens. It functions not only as a mechanical barrier, but also as an important sentinel of the innate immune system. However, the interactions and processes between host airway epithelium and pathogens are not fully understood. RESULTS: In...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5994059/ https://www.ncbi.nlm.nih.gov/pubmed/29884128 http://dx.doi.org/10.1186/s12866-018-1187-7 |
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author | Li, Yinghua Liu, Guangnan Zhang, Jianquan Zhong, Xiaoning He, Zhiyi |
author_facet | Li, Yinghua Liu, Guangnan Zhang, Jianquan Zhong, Xiaoning He, Zhiyi |
author_sort | Li, Yinghua |
collection | PubMed |
description | BACKGROUND: Airway epithelium is the primary target for pathogens. It functions not only as a mechanical barrier, but also as an important sentinel of the innate immune system. However, the interactions and processes between host airway epithelium and pathogens are not fully understood. RESULTS: In this study, we identified responses of the human airway epithelium cells to respiratory pathogen infection. We retrieved three mRNA expression microarray datasets from the Gene Expression Omnibus database, and identified 116 differentially expressed genes common to all three datasets. Gene functional annotations were performed using Gene Ontology and pathway analyses. Using protein-protein interaction network analysis and text mining, we identified a subset of genes functioned as a group and associated with infection, inflammation, tissue adhesion, and receptor internalization in infected epithelial cells. These genes were further identified in BESE-2B cells in response to Talaromyces marneffei by Real-Time quantitative PCR (qRT-PCR). In addition, we performed an in silico prediction of microRNA-target interactions and examined our findings. CONCLUSIONS: Using bioinformatics analysis, we identified several genes that may serve as biomarkers for the diagnosis or the surveillance of early respiratory tract infection, and identified additional genes and miRNAs that warrant further fundamental experimental research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12866-018-1187-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5994059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59940592018-06-21 Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis Li, Yinghua Liu, Guangnan Zhang, Jianquan Zhong, Xiaoning He, Zhiyi BMC Microbiol Research Article BACKGROUND: Airway epithelium is the primary target for pathogens. It functions not only as a mechanical barrier, but also as an important sentinel of the innate immune system. However, the interactions and processes between host airway epithelium and pathogens are not fully understood. RESULTS: In this study, we identified responses of the human airway epithelium cells to respiratory pathogen infection. We retrieved three mRNA expression microarray datasets from the Gene Expression Omnibus database, and identified 116 differentially expressed genes common to all three datasets. Gene functional annotations were performed using Gene Ontology and pathway analyses. Using protein-protein interaction network analysis and text mining, we identified a subset of genes functioned as a group and associated with infection, inflammation, tissue adhesion, and receptor internalization in infected epithelial cells. These genes were further identified in BESE-2B cells in response to Talaromyces marneffei by Real-Time quantitative PCR (qRT-PCR). In addition, we performed an in silico prediction of microRNA-target interactions and examined our findings. CONCLUSIONS: Using bioinformatics analysis, we identified several genes that may serve as biomarkers for the diagnosis or the surveillance of early respiratory tract infection, and identified additional genes and miRNAs that warrant further fundamental experimental research. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12866-018-1187-7) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-08 /pmc/articles/PMC5994059/ /pubmed/29884128 http://dx.doi.org/10.1186/s12866-018-1187-7 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Research Article Li, Yinghua Liu, Guangnan Zhang, Jianquan Zhong, Xiaoning He, Zhiyi Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
title | Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
title_full | Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
title_fullStr | Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
title_full_unstemmed | Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
title_short | Identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
title_sort | identification of key genes in human airway epithelial cells in response to respiratory pathogens using microarray analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5994059/ https://www.ncbi.nlm.nih.gov/pubmed/29884128 http://dx.doi.org/10.1186/s12866-018-1187-7 |
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