Online Prioritization of Toxic Compounds in Water Samples through Intelligent HRMS Data Acquisition.

LC-HRMS-based nontarget screening (NTS) has become the method of choice to monitor organic micropollutants (OMPs) in drinking water and its sources. OMPs are identified by matching experimental fragmentation (MS2) spectra with library or in silico-predicted spectra. This requires informative experimental spectra and prioritization to reduce feature numbers, currently performed post data acquisition. Here, we propose a different prioritization strategy to ensure high-quality MS2 spectra for OMPs that pose an environmental or human health risk. This online prioritization triggers MS2 events based on detection of suspect list entries or isotopic patterns in the full scan or an additional MS2 event based on fragment ion(s)/patterns detected in a first MS2 spectrum. Triggers were determined using cheminformatics; potentially toxic compounds were selected based on the presence of structural alerts, in silico-fragmented, and recurring fragments and mass shifts characteristic for a given structural alert identified. After MS acquisition parameter optimization, performance of the online prioritization was experimentally examined. Triggered methods led to increased percentages of MS2 spectra and additional MS2 spectra for compounds with a structural alert. Application to surface water samples resulted in additional MS2 spectra of potentially toxic compounds, facilitating more confident identification and emphasizing the method's potential to improve monitoring studies.

Risk-based prioritization of suspects detected in riverine water using complementary chromatographic techniques.

Surface waters are widely used as drinking water sources and hence their quality needs to be continuously monitored. However, current routine monitoring programs are not comprehensive as they generally cover only a limited number of known pollutants and emerging contaminants. This study presents a risk-based approach combining suspect and non-target screening (NTS) to help extend the coverage of current monitoring schemes. In particular, the coverage of NTS was widened by combining three complementary separations modes: Reverse phase (RP), Hydrophilic interaction liquid chromatography (HILIC) and Mixed-mode chromatography (MMC). Suspect lists used were compiled from databases of relevant substances of very high concern (e.g., SVHCs) and the concentration of detected suspects was evaluated based on ionization efficiency prediction. Results show that suspect candidates can be prioritized based on their potential risk (i.e., hazard and exposure) by combining ionization efficiency-based concentration estimation, in vitro toxicity data or, if not available, structural alerts and QSAR.based toxicity predictions. The acquired information shows that NTS analyses have the potential to complement target analyses, allowing to update and adapt current monitoring programs, ultimately leading to improved monitoring of drinking water sources.