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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...

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Autores principales: Takahashi, Hiroki, Kai, Kosuke, Shinbo, Yoko, Tanaka, Kenichi, Ohta, Daisaku, Oshima, Taku, Altaf-Ul-Amin, Md., Kurokawa, Ken, Ogasawara, Naotake, Kanaya, Shigehiko
Formato: Texto
Lenguaje:English
Publicado: Springer-Verlag 2008
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.
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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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