Identification of differentially expressed genes and pathways in BEAS-2B cells upon long-term exposure to particulate matter (PM2.5) from biomass combustion using bioinformatics analysis.

Abstract

Long-term exposure to PM2.5 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 PM2.5 toxicity in human bronchial epithelial BEAS-2B cells. 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. 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 PM2.5 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 PM2.5. 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 PM2.5.