SWATH data independent acquisition mass spectrometry for screening of xenobiotics in biological fluids: Opportunities and challenges for data processing

SWATH data independent acquisition (DIA) mass spectrometry (MS) has become an established technique in MS-based ‘omics’ research and is increasingly used for the screening of xenobiotics (e.g. drugs, drug metabolites, pesticides, toxicants). Such xenobiotic screening methods are mostly applied for tentative compound identification purposes based on spectral library searching, while additional data processing techniques are scarcely used thereby leaving the full potential of these methods often unused. Here we present an analytical workflow for screening xenobiotics in human samples using SWATH/MS based on which we highlight opportunities for unlocking unused potential of these methods. The workflow was applied to urine samples from subjects who tested positive for THC and/or cocaine during roadside drug testing with the goal of confirming the positive roadside drug tests and identifying compounds that relate to illicit drug use (e.g. cutting agents, tobacco components) or associate with corresponding lifestyle choices (e.g. nasal decongestants, painkillers). These goals could only be reached by complementing spectral library search procedures with additional multivariate data analyses due to inherent incompleteness of the spectral library that was employed. Such incompleteness represents a common challenge for applications where limited or no metadata is available for study samples, for example in toxicology, doping control in sports, and workplace or roadside drug testing. It furthermore sets the stage for employing additional data processing techniques as is outlined in the presented work. [Display omitted] •A comprehensive SWATH/MS QUAL/QUANT workflow for targeted and untargeted screening (84/85 characters).•SWATH/MS gave high quality MS/MS for library search and potential quantification (82/85 characters).•Identification of drugs, metabolites, and adulterants with/without library search (83/85 characters).•PCA and PCVG analysis to characterize drugs, metabolites and unexpected compounds (83/85 characters).