The potential of omics approaches to elucidate mechanisms of biodiesel-induced pulmonary toxicity

Liza Selley*, David H. Phillips, Ian Mudway

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)

Abstract

Background: Combustion of biodiesels in place of fossil diesel (FD) has been proposed as a method of reducing transport-related toxic emissions in Europe. While biodiesel exhaust (BDE) contains fewer hydrocarbons, total particulates and carbon monoxide than FD exhaust (FDE), its high nitrogen oxide and ultrafine particle content may still promote pulmonary pathophysiologies. Main body: Using a complement of in vitro and in vivo studies, this review documents progress in our understanding of pulmonary responses to BDE exposure. Focusing initially on hypothesis-driven, targeted analyses, the merits and limitations of comparing BDE-induced responses to those caused by FDE exposure are discussed within the contexts of policy making and exploration of toxicity mechanisms. The introduction and progression of omics-led workflows are also discussed, summarising the novel insights into mechanisms of BDE-induced toxicity that they have uncovered. Finally, options for the expansion of BDE-related omics screens are explored, focusing on the mechanistic relevance of metabolomic profiling and offering rationale for expansion beyond classical models of pulmonary exposure. Conclusion: Together, these discussions suggest that molecular profiling methods have identified mechanistically informative, novel and fuel-specific signatures of pulmonary responses to biodiesel exhaust exposure that would have been difficult to detect using traditional, hypothesis driven approaches alone.

Original languageEnglish
Article number4
Pages (from-to)4
JournalParticle And Fibre Toxicology
Volume16
Issue number1
DOIs
Publication statusPublished - 8 Jan 2019

Keywords

  • Biodiesel
  • Hypothesis generation
  • Mechanism
  • Metabolomics
  • Pulmonary toxicity
  • Transcriptomics

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