Pluto Bioinformatics

GSE144770: Genome-wide analysis reveals mucociliary remodeling of the airway epithelium induced by PM2.5

Bulk RNA sequencing

Air pollution particulate matter <2.5 microns (PM2.5) is associated with poor respiratory outcomes. Mechanisms underlying PM2.5-induced lung pathobiology are poorly understood, but likely involve cellular and molecular changes to the airway epithelium. We extracted and chemically characterized the organic and water-soluble components of contemporary ambient air pollution PM2.5 samples. We then determined the whole transcriptome responses of human mucociliary airway epithelial cultures (n=12) to a dose series of PM2.5 extracts. We found PM2.5 organic, but not water-soluble, constituents elicited a potent, dose-dependent transcriptomic response from the mucociliary epithelium. Epithelial exposure to a moderate organic extract (OE) dose modified the expression of 424 genes, which included activation of aryl-hydrocarbon receptor (AHR) signaling and an interleukin-1 inflammatory program. We generated an OE response network composed of 8 metagroups, which exhibited high connectivity through the CYP1A1, IL1A, and IL1B genes. This OE exposure also robustly activated a mucus secretory expression program (>100 genes), which included transcriptional drivers of mucus metaplasia (SPDEF, FOXA3). Exposure to a higher OE dose modified the expression of 1,240 genes and further exacerbated expression responses observed at the moderate dose, including the mucus secretory program. Moreover, the higher OE dose significantly increased the MUC5AC/MUC5B gel-forming mucin expression ratio and strongly downregulated ciliated cell expression programs, including key ciliating cell transcription factors (FOXJ1, MCIDAS). Our results suggest organic chemicals in PM2.5 likely drive cellular remodeling of the airway epithelium, punctuated by mucus metaplasia and loss of ciliated cells. This epithelial remodeling may underlie poor respiratory outcomes associated with high PM2.5 exposure. SOURCE: Satria Sajuthi ( - Seibold National Jewish Health

View this experiment on Pluto Bioinformatics