Identifying Toxicologically Significant Compounds in Urban Wildfire Ash Using In Vitro Bioassays and High-Resolution Mass Spectrometry

Urban wildfires may generate numerous unidentified chemicals of toxicity concern. Ash samples were collected from burned residences and from an undeveloped upwind reference site, following the Tubbs fire in Sonoma County, California. The solvent extracts of ash samples were analyzed using GC– and LC...

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Veröffentlicht in:Environmental science & technology 2021-03, Vol.55 (6), p.3657-3667
Hauptverfasser: Young, Thomas M, Black, Gabrielle P, Wong, Luann, Bloszies, Clayton S, Fiehn, Oliver, He, Guochun, Denison, Michael S, Vogel, Christoph F.A, Durbin-Johnson, Blythe
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Sprache:eng
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Zusammenfassung:Urban wildfires may generate numerous unidentified chemicals of toxicity concern. Ash samples were collected from burned residences and from an undeveloped upwind reference site, following the Tubbs fire in Sonoma County, California. The solvent extracts of ash samples were analyzed using GC– and LC–high-resolution mass spectrometry (HRMS) and using a suite of in vitro bioassays for their bioactivity toward nuclear receptors [aryl hydrocarbon receptor (AhR), estrogen receptor (ER), and androgen receptor (AR)], their influence on the expression of genetic markers of stress and inflammation [interleukin-8 (IL-8) and cyclooxygenase-2 (COX-2)], and xenobiotic metabolism [cytochrome P4501A1 (CYP1A1)]. Genetic markers (CYP1A1, IL-8, and COX-2) and AhR activity were significantly higher with wildfire samples than in solvent controls, whereas AR and ER activities generally were unaffected or reduced. The bioassay responses of samples from residential areas were not significantly different from the samples from the reference site despite differing chemical compositions. Suspect and nontarget screening was conducted to identify the chemicals responsible for elevated bioactivity using the multiple streams of HRMS data and open-source data analysis workflows. For the bioassay endpoint with the largest available database of pure compound results (AhR), nontarget features statistically related to whole sample bioassay response using Spearman’s rank-order correlation coefficients or elastic net regression were significantly more likely (by 10 and 15 times, respectively) to be known AhR agonists than the overall population of compounds tentatively identified by nontarget analysis. The findings suggest that a combination of nontarget analysis, in vitro bioassays, and statistical analysis can identify bioactive compounds in complex mixtures.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.0c06712