SWATH-F: A Novel Nontarget Strategy Based on the SWATH-MS Deconvolution Method Assisting in Annotating PFAS Homologues in Multisample Studies.

In order to identify emerging per- and polyfluoroalkyl substances (PFASs) and their alternatives in the environment or population, we need to perform extensive profiling of PFASs to determine their distribution in samples. The sequential window acquisition of all theoretical fragment-ion spectra (SWATH mode) is capable of obtaining a wide range of MS2 spectra but is difficult for direct identification of PFASs due to its complex MS2 spectra, and the nontarget screening method is difficult to identify due to its lack of a priori information. In this study, we demonstrated the great potential of SWATH-F, a nontarget fragment-based homologue screening method in combination with the SWATH-MS deconvolution, for detecting PFASs. We evaluated the application of SWATH-F to gradient spiked samples and real population serum samples, compared it with nontarget homologue screening in the information-dependent acquisition mode (IDA mode), and obtained better results for SWATH-F with 276% improvement (IDA:17 PFASs, SWATH-F: 64 PFASs) in identification. In addition, we automated the screening and identification process of SWATH-F to facilitate its use by researchers. SWATH-F is freely available on GitHub (https://github.com/njuIrene/SWATH-F) under an MIT license.

Nontarget Discovery of Antimicrobial Transformation Products in Wastewater Based on Molecular Networks.

Antimicrobial transformation products (ATPs) in the environment have raised extensive concerns in recent years due to their potential health risks. However, only a few ATPs have been investigated, and most of the transformation pathways of antimicrobials have not been completely elucidated. In this study, we developed a nontarget screening strategy based on molecular networks to detect and identify ATPs in pharmaceutical wastewater. We identified 52 antimicrobials and 49 transformation products (TPs) with a confidence level of three or above. Thirty of the TPs had not been previously reported in the environment. We assessed whether TPs could be classified as persistent, mobile, and toxic (PMT) substances based on recent European criteria for industrial substances. Owing to poor experimental data, definitive PMT classifications could not be established for novel ATPs. PMT assessment based on structurally predictive physicochemical properties revealed that 47 TPs were potential PMT substances. These results provide evidence that novel ATPs should be the focus of future research.