Untargeted metabolomics analysis assisted by signal selection for comprehensively identifying metabolites of new psychoactive substances: 4-MeO-α-PVP as an example

Abstract

New psychoactive substances (NPS) have been rapidly emerged as legal alternatives to controlled drugs, which raised severe public health issue. The detection and monitoring of its intake by complete metabolic profiling is an urgent and vital task. Untargeted metabolomics approach has been applied for several NPS metabolites studies. Although the number of such works is relatively limited but with a rapidly growing need. The present study aimed to propose a procedure that includes liquid chromatography high-resolution mass spectrometry (LC-HRMS) analysis and a signal selection software, MetaboFinder, programed as a web tool. The comprehensive metabolites profile of one kind of NPS, 4-methoxy-α-pyrrolidinovalerophenone (4-MeO-α-PVP), was studied by using this workflow. In this study, two different concentrations of 4-MeO-α-PVP along with as blank sample were incubated with human liver S9 fraction for the conversion to their metabolites and followed by LC-MS analysis. After retention time alignment and feature identification, 4640 features were obtained and submitted to statistical analysis for signal selection by using MetaboFinder. A total of 50 features were considered as 4-MeO-α-PVP metabolite candidates showing significant changes ( p < 0.00001 and fold change >2) between the two investigated groups. Targeted LC-MS/MS analysis was conducted focusing on these significantly expressed features. Assisted by chemical formula determination according to high mass accuracy and in silico MS 2 fragmentation prediction, 19 chemical structure identifications were achieved. Among which, 8 metabolites have been reported derived from 4-MeO-α-PVP in a previous literature while 11 novel 4-MeO-α-PVP metabolites were identified by using our strategy. Further in vivo animal experiment confirmed that 18 compounds were 4-MeO-α-PVP metabolites, which demonstrated the feasibility of our strategy for screening the 4-MeO-α-PVP metabolites. We anticipate that this procedure may support and facilitate traditional metabolism studies and potentially being applied for routine NPS metabolites screening.

Identification of Xenobiotic Biotransformation Products Using Mass Spectrometry-Based Metabolomics Integrated with a Structural Elucidation Strategy by Assembling Fragment Signatures

“…Information on the biotransformation products of illicit drugs is indispensable for forensic toxicologists, because such information can enhance drug toxicity 39 research and expand the window to detect targeted drugs. 40 For the 4-MeO-α-PVP data set, the data were from the reported study 41 with the incubation conditions described in the experimental section. Among the 22,081 features in the alignment table, 5578 passed the MDF, and 52 of them were also filtered by multiple-group comparison (Figure S6).…”