Large scale enzyme based xenobiotic identification for exposomics

Advances in genomics have revealed many of the genetic underpinnings of human disease, but exposomics methods are currently inadequate to obtain a similar level of understanding of environmental contributions to human disease. Exposomics methods are limited by low abundance of xenobiotic metabolites...

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Veröffentlicht in:Nature communications 2021-09, Vol.12 (1), p.5418-9, Article 5418
Hauptverfasser: Liu, Ken H., Lee, Choon M., Singer, Grant, Bais, Preeti, Castellanos, Francisco, Woodworth, Michael H., Ziegler, Thomas R., Kraft, Colleen S., Miller, Gary W., Li, Shuzhao, Go, Young-Mi, Morgan, Edward T., Jones, Dean P.
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Sprache:eng
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Zusammenfassung:Advances in genomics have revealed many of the genetic underpinnings of human disease, but exposomics methods are currently inadequate to obtain a similar level of understanding of environmental contributions to human disease. Exposomics methods are limited by low abundance of xenobiotic metabolites and lack of authentic standards, which precludes identification using solely mass spectrometry-based criteria. Here, we develop and validate a method for enzymatic generation of xenobiotic metabolites for use with high-resolution mass spectrometry (HRMS) for chemical identification. Generated xenobiotic metabolites were used to confirm identities of respective metabolites in mice and human samples based upon accurate mass, retention time and co-occurrence with related xenobiotic metabolites. The results establish a generally applicable enzyme-based identification (EBI) for mass spectrometry identification of xenobiotic metabolites and could complement existing criteria for chemical identification. Humans are exposed to many xenobiotic chemicals, but identification of low abundance xenobiotic exposures is limited by a lack of authentic standards for xenobiotic metabolites. Here the authors develop methods for enzymatic generation of diverse xenobiotic metabolites for use with high-resolution mass spectrometry for biology-based chemical identification.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-021-25698-x