Unlocking the future potential of SWATH-MS: Advancing non-target screening workflow for the qualitative and quantitative analysis of emerging contaminants.

Water Res

South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China; Australian Laboratory for Emerging Contaminants, School of Chemistry, University of Melbourne, Victoria 3010, Australia. Electronic address:

Published: February 2025

SWATH-MS offers a robust data-independent acquisition method for complex proteomics and metabolomics. This study presents a detailed non-target screening workflow utilizing SWATH-MS to detect and analyze emerging contaminants (ECs) in aquatic environments. Our workflow, covering peak picking, alignment, prioritization, structure identification, and quantification, effectively identified all qualifying peaks from 298 standard compounds with different concentrations, discarding any that did not meet the criteria. In extracts of real water samples spiked at 100 and 10 ng/mL, our workflow prioritized 2083 and 1328 features, respectively. Following structure identification, these features were assigned confidence levels ranging from 1 to 5. Of these, 215 and 92 spiked standards achieved level 1. The remaining standards were not recognized as level 1 due to low intensities or poor peak shapes that failed to meet certain criteria. Additionally, using fragment ion peak areas for quantification significantly improved the linearity of standard curves, enhancing R values for ∼63 % of the standards. Incorporating fragment ion data improved quantification accuracy, increasing compounds within the 80 %-120 % range from 78 % to 90 % at 100 ng/mL and within the 50 %-150 % range from 36 % to 69 % at 10 ng/mL. These findings underscore SWATH-MS's potential to enhance monitoring of ECs and ecological risk assessments, providing critical insights for environmental management.

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http://dx.doi.org/10.1016/j.watres.2025.123323DOI Listing

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