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Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants
Metabolomics is an ‘omics’ approach that aims to analyze all metabolites in a biological sample comprehensively. The detailed metabolite profiling of thousands of plant samples has great potential for directly elucidating plant metabolic processes. However, both a comprehensive analysis and a high t...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2638709/ https://www.ncbi.nlm.nih.gov/pubmed/19054808 http://dx.doi.org/10.1093/pcp/pcn183 |
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author | Sawada, Yuji Akiyama, Kenji Sakata, Akane Kuwahara, Ayuko Otsuki, Hitomi Sakurai, Tetsuya Saito, Kazuki Hirai, Masami Yokota |
author_facet | Sawada, Yuji Akiyama, Kenji Sakata, Akane Kuwahara, Ayuko Otsuki, Hitomi Sakurai, Tetsuya Saito, Kazuki Hirai, Masami Yokota |
author_sort | Sawada, Yuji |
collection | PubMed |
description | Metabolomics is an ‘omics’ approach that aims to analyze all metabolites in a biological sample comprehensively. The detailed metabolite profiling of thousands of plant samples has great potential for directly elucidating plant metabolic processes. However, both a comprehensive analysis and a high throughput are difficult to achieve at the same time due to the wide diversity of metabolites in plants. Here, we have established a novel and practical metabolomics methodology for quantifying hundreds of targeted metabolites in a high-throughput manner. Multiple reaction monitoring (MRM) using tandem quadrupole mass spectrometry (TQMS), which monitors both the specific precursor ions and product ions of each metabolite, is a standard technique in targeted metabolomics, as it enables high sensitivity, reproducibility and a broad dynamic range. In this study, we optimized the MRM conditions for specific compounds by performing automated flow injection analyses with TQMS. Based on a total of 61,920 spectra for 860 authentic compounds, the MRM conditions of 497 compounds were successfully optimized. These were applied to high-throughput automated analysis of biological samples using TQMS coupled with ultra performance liquid chromatography (UPLC). By this analysis, approximately 100 metabolites were quantified in each of 14 plant accessions from Brassicaceae, Gramineae and Fabaceae. A hierarchical cluster analysis based on the metabolite accumulation patterns clearly showed differences among the plant families, and family-specific metabolites could be predicted using a batch-learning self-organizing map analysis. Thus, the automated widely targeted metabolomics approach established here should pave the way for large-scale metabolite profiling and comparative metabolomics. |
format | Text |
id | pubmed-2638709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-26387092009-02-25 Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants Sawada, Yuji Akiyama, Kenji Sakata, Akane Kuwahara, Ayuko Otsuki, Hitomi Sakurai, Tetsuya Saito, Kazuki Hirai, Masami Yokota Plant Cell Physiol Special Issue – Regular Papers Metabolomics is an ‘omics’ approach that aims to analyze all metabolites in a biological sample comprehensively. The detailed metabolite profiling of thousands of plant samples has great potential for directly elucidating plant metabolic processes. However, both a comprehensive analysis and a high throughput are difficult to achieve at the same time due to the wide diversity of metabolites in plants. Here, we have established a novel and practical metabolomics methodology for quantifying hundreds of targeted metabolites in a high-throughput manner. Multiple reaction monitoring (MRM) using tandem quadrupole mass spectrometry (TQMS), which monitors both the specific precursor ions and product ions of each metabolite, is a standard technique in targeted metabolomics, as it enables high sensitivity, reproducibility and a broad dynamic range. In this study, we optimized the MRM conditions for specific compounds by performing automated flow injection analyses with TQMS. Based on a total of 61,920 spectra for 860 authentic compounds, the MRM conditions of 497 compounds were successfully optimized. These were applied to high-throughput automated analysis of biological samples using TQMS coupled with ultra performance liquid chromatography (UPLC). By this analysis, approximately 100 metabolites were quantified in each of 14 plant accessions from Brassicaceae, Gramineae and Fabaceae. A hierarchical cluster analysis based on the metabolite accumulation patterns clearly showed differences among the plant families, and family-specific metabolites could be predicted using a batch-learning self-organizing map analysis. Thus, the automated widely targeted metabolomics approach established here should pave the way for large-scale metabolite profiling and comparative metabolomics. Oxford University Press 2009-01 2008-12-02 /pmc/articles/PMC2638709/ /pubmed/19054808 http://dx.doi.org/10.1093/pcp/pcn183 Text en © The Author 2008. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and the Japanese Society of Plant Physiologists are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org |
spellingShingle | Special Issue – Regular Papers Sawada, Yuji Akiyama, Kenji Sakata, Akane Kuwahara, Ayuko Otsuki, Hitomi Sakurai, Tetsuya Saito, Kazuki Hirai, Masami Yokota Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants |
title | Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants |
title_full | Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants |
title_fullStr | Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants |
title_full_unstemmed | Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants |
title_short | Widely Targeted Metabolomics Based on Large-Scale MS/MS Data for Elucidating Metabolite Accumulation Patterns in Plants |
title_sort | widely targeted metabolomics based on large-scale ms/ms data for elucidating metabolite accumulation patterns in plants |
topic | Special Issue – Regular Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2638709/ https://www.ncbi.nlm.nih.gov/pubmed/19054808 http://dx.doi.org/10.1093/pcp/pcn183 |
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