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Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics

In this study, an integrative high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF) based metabolomics approach was performed to evaluate the enantioselective metabolic perturbations in MCF-7 cells after treatment with R-metalaxyl and S-me...

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Autores principales: Zhang, Ping, Zhu, Wentao, Wang, Dezhen, Yan, Jin, Wang, Yao, He, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5297775/
https://www.ncbi.nlm.nih.gov/pubmed/28085117
http://dx.doi.org/10.3390/ijms18010142
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author Zhang, Ping
Zhu, Wentao
Wang, Dezhen
Yan, Jin
Wang, Yao
He, Lin
author_facet Zhang, Ping
Zhu, Wentao
Wang, Dezhen
Yan, Jin
Wang, Yao
He, Lin
author_sort Zhang, Ping
collection PubMed
description In this study, an integrative high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF) based metabolomics approach was performed to evaluate the enantioselective metabolic perturbations in MCF-7 cells after treatment with R-metalaxyl and S-metalaxyl, respectively. Untargeted metabolomics profile, multivariate pattern recognition, metabolites identification, and pathway analysis were determined after metalaxyl enantiomer exposure. Principal component analysis (PCA) and partitial least-squares discriminant analysis (PLS-DA) directly reflected the enantioselective metabolic perturbations induced by metalaxyl enantiomers. On the basis of multivariate statistical results, a total of 49 metabolites including carbohydrates, amino acids, nucleotides, fatty acids, organic acids, phospholipids, indoles, derivatives, etc. were found to be the most significantly changed metabolites and metabolic fluctuations caused by the same concentration of R-metalaxyl and S-metalaxyl were enantioselective. Pathway analysis indicated that R-metalaxyl and S-metalaxyl mainly affected the 7 and 10 pathways in MCF-7 cells, respectively, implying the perturbed pathways induced by metalaxyl enantiomers were also enantioselective. Furthermore, the significantly perturbed metabolic pathways were highly related to energy metabolism, amino acid metabolism, lipid metabolism, and antioxidant defense. Such results provide more specific insights into the enantioselective metabolic effects of chiral pesticides in breast cancer progression, reveal the underlying mechanisms, and provide available data for the health risk assessments of chiral environmental pollutants at the molecular level.
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spelling pubmed-52977752017-02-10 Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics Zhang, Ping Zhu, Wentao Wang, Dezhen Yan, Jin Wang, Yao He, Lin Int J Mol Sci Article In this study, an integrative high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF) based metabolomics approach was performed to evaluate the enantioselective metabolic perturbations in MCF-7 cells after treatment with R-metalaxyl and S-metalaxyl, respectively. Untargeted metabolomics profile, multivariate pattern recognition, metabolites identification, and pathway analysis were determined after metalaxyl enantiomer exposure. Principal component analysis (PCA) and partitial least-squares discriminant analysis (PLS-DA) directly reflected the enantioselective metabolic perturbations induced by metalaxyl enantiomers. On the basis of multivariate statistical results, a total of 49 metabolites including carbohydrates, amino acids, nucleotides, fatty acids, organic acids, phospholipids, indoles, derivatives, etc. were found to be the most significantly changed metabolites and metabolic fluctuations caused by the same concentration of R-metalaxyl and S-metalaxyl were enantioselective. Pathway analysis indicated that R-metalaxyl and S-metalaxyl mainly affected the 7 and 10 pathways in MCF-7 cells, respectively, implying the perturbed pathways induced by metalaxyl enantiomers were also enantioselective. Furthermore, the significantly perturbed metabolic pathways were highly related to energy metabolism, amino acid metabolism, lipid metabolism, and antioxidant defense. Such results provide more specific insights into the enantioselective metabolic effects of chiral pesticides in breast cancer progression, reveal the underlying mechanisms, and provide available data for the health risk assessments of chiral environmental pollutants at the molecular level. MDPI 2017-01-12 /pmc/articles/PMC5297775/ /pubmed/28085117 http://dx.doi.org/10.3390/ijms18010142 Text en © 2017 by the authors; 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Ping
Zhu, Wentao
Wang, Dezhen
Yan, Jin
Wang, Yao
He, Lin
Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics
title Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics
title_full Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics
title_fullStr Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics
title_full_unstemmed Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics
title_short Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics
title_sort enantioselective effects of metalaxyl enantiomers on breast cancer cells metabolic profiling using hplc-qtof-based metabolomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5297775/
https://www.ncbi.nlm.nih.gov/pubmed/28085117
http://dx.doi.org/10.3390/ijms18010142
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