Differential Gene Expression Using RNA Sequencing Profiling in a Reconstituted Airway Epithelium Exposed to Conventional Cigarette Smoke or Electronic Cigarette Aerosols

Abstract

The use of electronic cigarettes (e-cigarettes) potentially offers a safer alternative to conventional tobacco products. The advance in molecular biology and computational sciences offers new perspective to assess adverse biological responses for product risk assessment by combining omics screens with knowledge-based biological pathways. Our aim was to compare transcriptomic perturbations in MucilAir, a commercially available lung epithelial tissue, after short repeated exposure to cigarette smoke (3R4F) and e-cigarette (Vype ePen) aerosols. We performed deep RNA sequencing and secreted inflammatory cytokine profiling postexposure. One hundred twenty-three genes were differentially expressed at fold change (FC) >1.5 and p-false discovery rate (pFDR) <0.1 for 3R4F exposure and 0 genes for Vype ePen aerosol exposure. When a relaxed filter pFDR <0.5 and FC >1.5 was applied, 29 genes were identified with e-cigarette aerosol exposure and used for validation of potential candidates by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Gene enrichment analysis was conducted and predicted a response to 3R4F smoke exposure in biological processes involving inflammation and oxidative stress pathways. No enrichment could be performed for Vype ePen aerosol exposure due to the lack of regulated gene candidates at those exposure conditions even after qRT-PCR validation. Of a panel of 33 cytokines screened, 8 were upregulated (FC >1.5 p < 0.05) following 3R4F smoke exposure, which was in agreement with our enrichment analysis. In conclusion, aerosol from the tested e-cigarette caused limited perturbations in gene and inflammatory cytokine expression compared to conventional cigarette smoke, as assessed using next-generation sequencing-based systems biology approaches in 3D commercially available reconstituted lung epithelial tissues.