TY - JOUR
T1 - Untargeted metabolomics analysis assisted by signal selection for comprehensively identifying metabolites of new psychoactive substances
T2 - 4-MeO-a-PVP as an example
AU - Wu, Hsin Yi
AU - Chen, Yuan Chih
AU - Hsu, Jing Fang
AU - Lu, Hsiang Ting
AU - Pan, Yu Yi
AU - Ma, Mi Chia
AU - Liao, Pao Chi
N1 - Funding Information:
This work was supported by the National Science and Technology Council, Taiwan [grant number MOST 109-2113-M-006-015, and MOST 110-2113-M-006-014]. The authors gratefully acknowledge the use of ICP00401 and MS004000 equipment belonging to the Core Facility Center of National Cheng Kung University, and the National Taiwan University Consortia of Key Technologies, National Taiwan University Instrumentation Center, and the Metabolomics Core Facility, Scientific Instrument Center at Academia Sinica.
Funding Information:
This work was supported by the National Science and Technology Council, Taiwan [grant number MOST109-2113-M-006-015, and MOST110-2113-M-006-014]. The authors gratefully acknowledge the use of ICP00401 and MS004000 equipment belonging to the Core Facility Center of National Cheng Kung University, and the National Taiwan University Consortia of Key Technologies, National Taiwan University Instrumentation Center, and the
Publisher Copyright:
© 2023, Taiwan Food and Drug Administration. All rights reserved.
PY - 2023
Y1 - 2023
N2 - 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-a-pyrrolidinovalerophenone (4-MeO-a-PVP), was studied by using this workflow. In this study, two different concentrations of 4-MeO-a-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-a-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 MS2 fragmentation prediction, 19 chemical structure identifications were achieved. Among which, 8 metabolites have been reported derived from 4-MeO-a-PVP in a previous literature while 11 novel 4-MeO-a-PVP metabolites were identified by using our strategy. Further in vivo animal experiment confirmed that 18 compounds were 4-MeO-a-PVP metabolites, which demonstrated the feasibility of our strategy for screening the 4-MeO-a-PVP metabolites. We antic-ipate that this procedure may support and facilitate traditional metabolism studies and potentially being applied for routine NPS metabolites screening.
AB - 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-a-pyrrolidinovalerophenone (4-MeO-a-PVP), was studied by using this workflow. In this study, two different concentrations of 4-MeO-a-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-a-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 MS2 fragmentation prediction, 19 chemical structure identifications were achieved. Among which, 8 metabolites have been reported derived from 4-MeO-a-PVP in a previous literature while 11 novel 4-MeO-a-PVP metabolites were identified by using our strategy. Further in vivo animal experiment confirmed that 18 compounds were 4-MeO-a-PVP metabolites, which demonstrated the feasibility of our strategy for screening the 4-MeO-a-PVP metabolites. We antic-ipate that this procedure may support and facilitate traditional metabolism studies and potentially being applied for routine NPS metabolites screening.
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U2 - 10.38212/2224-6614.3447
DO - 10.38212/2224-6614.3447
M3 - Article
C2 - 37224557
AN - SCOPUS:85150337613
SN - 1021-9498
VL - 31
SP - 137
EP - 151
JO - Journal of Food and Drug Analysis
JF - Journal of Food and Drug Analysis
IS - 1
ER -
