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Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry
Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) is the best MS technology for obtaining exact mass measurements owing to its great resolution and accuracy, and several outstanding FT-ICR/MS-based metabolomics approaches have been reported. A reliable annotation scheme is need...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Springer-Verlag
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2491437/ https://www.ncbi.nlm.nih.gov/pubmed/18560811 http://dx.doi.org/10.1007/s00216-008-2195-5 |
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author | Takahashi, Hiroki Kai, Kosuke Shinbo, Yoko Tanaka, Kenichi Ohta, Daisaku Oshima, Taku Altaf-Ul-Amin, Md. Kurokawa, Ken Ogasawara, Naotake Kanaya, Shigehiko |
author_facet | Takahashi, Hiroki Kai, Kosuke Shinbo, Yoko Tanaka, Kenichi Ohta, Daisaku Oshima, Taku Altaf-Ul-Amin, Md. Kurokawa, Ken Ogasawara, Naotake Kanaya, Shigehiko |
author_sort | Takahashi, Hiroki |
collection | PubMed |
description | Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) is the best MS technology for obtaining exact mass measurements owing to its great resolution and accuracy, and several outstanding FT-ICR/MS-based metabolomics approaches have been reported. A reliable annotation scheme is needed to deal with direct-infusion FT-ICR/MS metabolic profiling. Correlation analyses can help us not only uncover relations between the ions but also annotate the ions originated from identical metabolites (metabolite derivative ions). In the present study, we propose a procedure for metabolite annotation on direct-infusion FT-ICR/MS by taking into consideration the classification of metabolite-derived ions using correlation analyses. Integrated analysis based on information of isotope relations, fragmentation patterns by MS/MS analysis, co-occurring metabolites, and database searches (KNApSAcK and KEGG) can make it possible to annotate ions as metabolites and estimate cellular conditions based on metabolite composition. A total of 220 detected ions were classified into 174 metabolite derivative groups and 72 ions were assigned to candidate metabolites in the present work. Finally, metabolic profiling has been able to distinguish between the growth stages with the aid of PCA. The constructed model using PLS regression for OD(600) values as a function of metabolic profiles is very useful for identifying to what degree the ions contribute to the growth stages. Ten phospholipids which largely influence the constructed model are highly abundant in the cells. Our analyses reveal that global modification of those phospholipids occurs as E. coli enters the stationary phase. Thus, the integrated approach involving correlation analyses, metabolic profiling, and database searching is efficient for high-throughput metabolomics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-008-2195-5) contains supplementary material, which is available to authorized users. |
format | Text |
id | pubmed-2491437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-24914372008-07-30 Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry Takahashi, Hiroki Kai, Kosuke Shinbo, Yoko Tanaka, Kenichi Ohta, Daisaku Oshima, Taku Altaf-Ul-Amin, Md. Kurokawa, Ken Ogasawara, Naotake Kanaya, Shigehiko Anal Bioanal Chem Original Paper Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) is the best MS technology for obtaining exact mass measurements owing to its great resolution and accuracy, and several outstanding FT-ICR/MS-based metabolomics approaches have been reported. A reliable annotation scheme is needed to deal with direct-infusion FT-ICR/MS metabolic profiling. Correlation analyses can help us not only uncover relations between the ions but also annotate the ions originated from identical metabolites (metabolite derivative ions). In the present study, we propose a procedure for metabolite annotation on direct-infusion FT-ICR/MS by taking into consideration the classification of metabolite-derived ions using correlation analyses. Integrated analysis based on information of isotope relations, fragmentation patterns by MS/MS analysis, co-occurring metabolites, and database searches (KNApSAcK and KEGG) can make it possible to annotate ions as metabolites and estimate cellular conditions based on metabolite composition. A total of 220 detected ions were classified into 174 metabolite derivative groups and 72 ions were assigned to candidate metabolites in the present work. Finally, metabolic profiling has been able to distinguish between the growth stages with the aid of PCA. The constructed model using PLS regression for OD(600) values as a function of metabolic profiles is very useful for identifying to what degree the ions contribute to the growth stages. Ten phospholipids which largely influence the constructed model are highly abundant in the cells. Our analyses reveal that global modification of those phospholipids occurs as E. coli enters the stationary phase. Thus, the integrated approach involving correlation analyses, metabolic profiling, and database searching is efficient for high-throughput metabolomics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-008-2195-5) contains supplementary material, which is available to authorized users. Springer-Verlag 2008-06-16 2008 /pmc/articles/PMC2491437/ /pubmed/18560811 http://dx.doi.org/10.1007/s00216-008-2195-5 Text en © The Author(s) 2008 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Original Paper Takahashi, Hiroki Kai, Kosuke Shinbo, Yoko Tanaka, Kenichi Ohta, Daisaku Oshima, Taku Altaf-Ul-Amin, Md. Kurokawa, Ken Ogasawara, Naotake Kanaya, Shigehiko Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry |
title | Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry |
title_full | Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry |
title_fullStr | Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry |
title_full_unstemmed | Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry |
title_short | Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry |
title_sort | metabolomics approach for determining growth-specific metabolites based on fourier transform ion cyclotron resonance mass spectrometry |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2491437/ https://www.ncbi.nlm.nih.gov/pubmed/18560811 http://dx.doi.org/10.1007/s00216-008-2195-5 |
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