Transcriptome sequencing reveals e-cigarette vapor and mainstream-smoke from tobacco cigarettes activate different gene expression profiles in human bronchial epithelial cells

Sci Rep. 2016 Apr 4:6:23984. doi: 10.1038/srep23984.


Electronic cigarettes (e-cigarettes) generate an aerosol vapor (e-vapor) thought to represent a less risky alternative to main stream smoke (MSS) of conventional tobacco cigarettes. RNA-seq analysis was used to examine the transcriptomes of differentiated human bronchial epithelial (HBE) cells exposed to air, MSS from 1R5F tobacco reference cigarettes, and e-vapor with and without added nicotine in an in vitro air-liquid interface model for cellular exposure. Our results indicate that while e-vapor does not elicit many of the cell toxicity responses observed in MSS-exposed HBE cells, e-vapor exposure is not benign, but elicits discrete transcriptomic signatures with and without added nicotine. Among the cellular pathways with the most significantly enriched gene expression following e-vapor exposure are the phospholipid and fatty acid triacylglycerol metabolism pathways. Our data suggest that alterations in cellular glycerophopholipid biosynthesis are an important consequences of e-vapor exposure. Moreover, the presence of nicotine in e-vapor elicits a cellular response distinct from e-vapor alone including alterations of cytochrome P450 function, retinoid metabolism, and nicotine catabolism. These studies establish a baseline for future analysis of e-vapor and e-vapor additives that will better inform the FDA and other governmental bodies in discussions of the risks and future regulation of these products.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aerosols / adverse effects
  • Aerosols / analysis
  • Bronchi / cytology*
  • Bronchi / drug effects
  • Electronic Nicotine Delivery Systems / adverse effects*
  • Epithelial Cells / drug effects*
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation / drug effects
  • Gene Regulatory Networks / drug effects
  • Humans
  • Sequence Analysis, RNA / methods*
  • Smoke / adverse effects*
  • Tobacco / adverse effects*


  • Aerosols
  • Smoke