Browsing by Subject "Suspect screening method"

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    Suspect Screening of Exogenous Compounds Using Multiple Reaction Screening (MRM) Profiling in Human Urine Samples
    (Elsevier, 2022) Marasco, César A., Jr.; Edwards, Madison E.; Lamarca, Rafaela S.; Sobreira, Tiago J. P.; Caterino, Jeffrey M.; Hains, David S.; Schwaderer, Andrew L.; de Lima Gomes, Paulo C. F.; Ferreira, Christina R.; Pediatrics, School of Medicine
    Thousands of chemical compounds produced by industry are dispersed in the human environment widely enough to reach the world population, and the introduction of new chemicals constantly occurs. As new synthetic molecules emerge, rapid analytical workflows for screening possible presence of exogenous compounds in biofluids can be useful as a first pass analysis to detect chemical exposure and guide the development and application of more elaborate LC-MS/MS methods for quantification. In this study, a suspect screening workflow using the multiple reaction monitoring (MRM) profiling method is proposed as a first pass exploratory technique to survey selected exogenous molecules in human urine samples. The workflow was applied to investigate 12 human urine samples using 310 MRMs related to the chemical functionalities of 87 exogenous compounds present in the METLIN database and reported in the literature. A total of 11 MRMs associated with five different compounds were detected in the samples. Product ion scans for the precursor ions of the selected MRMs were acquired as a further identification step for these chemicals. The suspect screening results suggested the presence of five exogenous compounds in the human urine samples analyzed, namely metformin, metoprolol, acetaminophen, paraxanthine and acrylamide. LC-MS/MS was applied as a last step to confirm these results, and the presence of four out of the five targets selected by MRM profiling were corroborated, indicating that this workflow can support the selection of suspect compounds to screen complex samples and guide more time-consuming and specific quantification analyses.