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Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis
BACKGROUND: Long-term exposure to PM(2.5) from burning domestic substances has been linked to an increased risk of lung disease, but the underlying mechanisms are unclear. This study is to explore the hub genes and pathways involved in PM(2.5) toxicity in human bronchial epithelial BEAS-2B cells. ME...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Japanese Society for Hygiene
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10519835/ https://www.ncbi.nlm.nih.gov/pubmed/37722877 http://dx.doi.org/10.1265/ehpm.22-00272 |
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author | Yuan, Qian Zhang, Haiqiao |
author_facet | Yuan, Qian Zhang, Haiqiao |
author_sort | Yuan, Qian |
collection | PubMed |
description | BACKGROUND: Long-term exposure to PM(2.5) from burning domestic substances has been linked to an increased risk of lung disease, but the underlying mechanisms are unclear. This study is to explore the hub genes and pathways involved in PM(2.5) toxicity in human bronchial epithelial BEAS-2B cells. METHODS: The GSE158954 dataset is downloaded from the GEO database. Differentially expressed genes (DEGs) were screened using the limma package in RStudio (version 4.2.1). In addition, DEGs analysis was performed by Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A protein-protein interaction (PPI) network was constructed, MCODE plug-in and the cytoHubba plug-in in Cytoscape software was used to identify the hub genes. Finally, CytoHubba and DEGs were used to integrate the hub genes, and preliminary validation was performed by comparing the toxicology genomics database (CTD). Differential immune cell infiltration was investigated using the CIBERSORT algorithm. RESULTS: A total of 135 DEGs were identified, of which 57 were up-regulated and 78 were down-regulated. Functional enrichment analyses in the GO and KEGG indicated the potential involvement of DEGs was mainly enriched in the regulation of endopeptidase activity and influenza A. Gene Set Enrichment Analysis revealed that Chemical Carcinogenesis - DNA adducts were remarkably enriched in PM(2.5) groups. 53 nodes and 198 edges composed the PPI network. Besides, 5 direct-acting genes were filtered at the intersection of cytohubba plug-in, MCODE plug-in and CTD database. There is a decreasing trend of dendritic cells resting after BEAS-2B cells long-term exposure to PM(2.5). CONCLUSIONS: The identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of BEAS-2B cells upon long-term exposure to PM(2.5). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1265/ehpm.22-00272. |
format | Online Article Text |
id | pubmed-10519835 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Japanese Society for Hygiene |
record_format | MEDLINE/PubMed |
spelling | pubmed-105198352023-09-27 Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis Yuan, Qian Zhang, Haiqiao Environ Health Prev Med Research Article BACKGROUND: Long-term exposure to PM(2.5) from burning domestic substances has been linked to an increased risk of lung disease, but the underlying mechanisms are unclear. This study is to explore the hub genes and pathways involved in PM(2.5) toxicity in human bronchial epithelial BEAS-2B cells. METHODS: The GSE158954 dataset is downloaded from the GEO database. Differentially expressed genes (DEGs) were screened using the limma package in RStudio (version 4.2.1). In addition, DEGs analysis was performed by Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A protein-protein interaction (PPI) network was constructed, MCODE plug-in and the cytoHubba plug-in in Cytoscape software was used to identify the hub genes. Finally, CytoHubba and DEGs were used to integrate the hub genes, and preliminary validation was performed by comparing the toxicology genomics database (CTD). Differential immune cell infiltration was investigated using the CIBERSORT algorithm. RESULTS: A total of 135 DEGs were identified, of which 57 were up-regulated and 78 were down-regulated. Functional enrichment analyses in the GO and KEGG indicated the potential involvement of DEGs was mainly enriched in the regulation of endopeptidase activity and influenza A. Gene Set Enrichment Analysis revealed that Chemical Carcinogenesis - DNA adducts were remarkably enriched in PM(2.5) groups. 53 nodes and 198 edges composed the PPI network. Besides, 5 direct-acting genes were filtered at the intersection of cytohubba plug-in, MCODE plug-in and CTD database. There is a decreasing trend of dendritic cells resting after BEAS-2B cells long-term exposure to PM(2.5). CONCLUSIONS: The identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of BEAS-2B cells upon long-term exposure to PM(2.5). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1265/ehpm.22-00272. Japanese Society for Hygiene 2023-09-15 /pmc/articles/PMC10519835/ /pubmed/37722877 http://dx.doi.org/10.1265/ehpm.22-00272 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Yuan, Qian Zhang, Haiqiao Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis |
title | Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis |
title_full | Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis |
title_fullStr | Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis |
title_full_unstemmed | Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis |
title_short | Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM(2.5)) from biomass combustion using bioinformatics analysis |
title_sort | identification of differentially expressed genes and pathways in beas-2b cells upon long-term exposure to particulate matter (pm(2.5)) from biomass combustion using bioinformatics analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10519835/ https://www.ncbi.nlm.nih.gov/pubmed/37722877 http://dx.doi.org/10.1265/ehpm.22-00272 |
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