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Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity
A novel framework for automated elucidation of metabolite structures in liquid chromatography–mass spectrometer metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355805/ https://www.ncbi.nlm.nih.gov/pubmed/22645535 http://dx.doi.org/10.3389/fpls.2011.00040 |
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author | Matsuda, Fumio Nakabayashi, Ryo Sawada, Yuji Suzuki, Makoto Hirai, Masami Y. Kanaya, Shigehiko Saito, Kazuki |
author_facet | Matsuda, Fumio Nakabayashi, Ryo Sawada, Yuji Suzuki, Makoto Hirai, Masami Y. Kanaya, Shigehiko Saito, Kazuki |
author_sort | Matsuda, Fumio |
collection | PubMed |
description | A novel framework for automated elucidation of metabolite structures in liquid chromatography–mass spectrometer metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three distinct databases, KNApSAcK, ReSpect, and the PRIMe standard compound database, were employed for the structural elucidation. The outputs were retrieved using the CAS metabolite identifier for identification and putative annotation. A simple metabolite ontology system was also introduced to attain putative characterization of the metabolite signals. The automated method was applied for the metabolome data sets obtained from the rosette leaves of 20 Arabidopsis accessions. Phenotypic variations in novel Arabidopsis metabolites among these accessions could be investigated using this method. |
format | Online Article Text |
id | pubmed-3355805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-33558052012-05-29 Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity Matsuda, Fumio Nakabayashi, Ryo Sawada, Yuji Suzuki, Makoto Hirai, Masami Y. Kanaya, Shigehiko Saito, Kazuki Front Plant Sci Plant Science A novel framework for automated elucidation of metabolite structures in liquid chromatography–mass spectrometer metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three distinct databases, KNApSAcK, ReSpect, and the PRIMe standard compound database, were employed for the structural elucidation. The outputs were retrieved using the CAS metabolite identifier for identification and putative annotation. A simple metabolite ontology system was also introduced to attain putative characterization of the metabolite signals. The automated method was applied for the metabolome data sets obtained from the rosette leaves of 20 Arabidopsis accessions. Phenotypic variations in novel Arabidopsis metabolites among these accessions could be investigated using this method. Frontiers Research Foundation 2011-08-22 /pmc/articles/PMC3355805/ /pubmed/22645535 http://dx.doi.org/10.3389/fpls.2011.00040 Text en Copyright © 2011 Matsuda, Nakabayashi, Sawada, Suzuki, Hirai, Kanaya and Saito. http://www.frontiersin.org/licenseagreement This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with. |
spellingShingle | Plant Science Matsuda, Fumio Nakabayashi, Ryo Sawada, Yuji Suzuki, Makoto Hirai, Masami Y. Kanaya, Shigehiko Saito, Kazuki Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity |
title | Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity |
title_full | Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity |
title_fullStr | Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity |
title_full_unstemmed | Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity |
title_short | Mass Spectra-Based Framework for Automated Structural Elucidation of Metabolome Data to Explore Phytochemical Diversity |
title_sort | mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355805/ https://www.ncbi.nlm.nih.gov/pubmed/22645535 http://dx.doi.org/10.3389/fpls.2011.00040 |
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