Emerging investigators series: prioritization of suspect hits in a sensitive suspect screening workflow for comprehensive micropollutant characterization in environmental samples

Abstract

The emergence of suspect screening has enabled the comprehensive characterization of micropollutants in water systems. In this work, we developed a sensitive suspect screening workflow and applied it to characterize the occurrence of micropollutants in eighteen water samples collected from an urban water system in New York State. We used high-resolution mass spectrometry to collect full-scan and data-dependent tandem mass spectra from the water samples and compiled a suspect database that contained 1113 chemical substances including pesticides, pharmaceuticals, personal care products, and industrial chemicals. The suspect screening workflow included peak picking, suspect database matching, isotopic pattern scoring, a replication filter, blank subtraction and artifact removal, and clustering of suspect hits. Each step in the workflow relied only on the quality of the analytical data, and was optimized and validated using a set of compounds that covered a broad range of physicochemical properties. After applying the optimized suspect screening workflow to the data acquired from the water samples, we developed a series of prioritization strategies that ranked the resulting suspect hits according to metrics that we hypothesized would favor true positive detections. We then acquired authentic standards for suspect hits based on their ranking on the priority lists to confirm or reject their occurrence. With this approach, we confirmed the presence of 112 micropollutants in at least one of the eighteen water samples. Comparing these results to the scope of conventional micropollutant monitoring methods, we approximate that our suspect screening approach more than doubled the number of micropollutants that may otherwise have been identified.