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Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize

The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in...

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Autores principales: Xue, Weifeng, Yang, Chunguang, Liu, Mengyao, Lin, Xiaomei, Wang, Mei, Wang, Xiaowen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330060/
https://www.ncbi.nlm.nih.gov/pubmed/35897888
http://dx.doi.org/10.3390/molecules27154711
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author Xue, Weifeng
Yang, Chunguang
Liu, Mengyao
Lin, Xiaomei
Wang, Mei
Wang, Xiaowen
author_facet Xue, Weifeng
Yang, Chunguang
Liu, Mengyao
Lin, Xiaomei
Wang, Mei
Wang, Xiaowen
author_sort Xue, Weifeng
collection PubMed
description The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL(−1)) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg(−1) and 0.3~2.1 µg kg(−1) in lettuce and maize matrices, respectively.
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spelling pubmed-93300602022-07-29 Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize Xue, Weifeng Yang, Chunguang Liu, Mengyao Lin, Xiaomei Wang, Mei Wang, Xiaowen Molecules Article The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL(−1)) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg(−1) and 0.3~2.1 µg kg(−1) in lettuce and maize matrices, respectively. MDPI 2022-07-23 /pmc/articles/PMC9330060/ /pubmed/35897888 http://dx.doi.org/10.3390/molecules27154711 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xue, Weifeng
Yang, Chunguang
Liu, Mengyao
Lin, Xiaomei
Wang, Mei
Wang, Xiaowen
Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize
title Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize
title_full Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize
title_fullStr Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize
title_full_unstemmed Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize
title_short Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize
title_sort metabolomics approach on non-targeted screening of 50 ppcps in lettuce and maize
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330060/
https://www.ncbi.nlm.nih.gov/pubmed/35897888
http://dx.doi.org/10.3390/molecules27154711
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