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Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling
BACKGROUND: The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors into metabolic products can be taken as fingerprints of the metabolic events and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720290/ https://www.ncbi.nlm.nih.gov/pubmed/23837681 http://dx.doi.org/10.1186/1471-2105-14-218 |
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author | Ahmed, Zeeshan Zeeshan, Saman Huber, Claudia Hensel, Michael Schomburg, Dietmar Münch, Richard Eisenreich, Wolfgang Dandekar, Thomas |
author_facet | Ahmed, Zeeshan Zeeshan, Saman Huber, Claudia Hensel, Michael Schomburg, Dietmar Münch, Richard Eisenreich, Wolfgang Dandekar, Thomas |
author_sort | Ahmed, Zeeshan |
collection | PubMed |
description | BACKGROUND: The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors into metabolic products can be taken as fingerprints of the metabolic events and dynamics through the metabolic networks. An open-source software is required that easily and rapidly calculates from mass spectra of labelled metabolites, derivatives and their fragments global isotope excess and isotopomer distribution. RESULTS: The open-source software “Least Square Mass Isotopomer Analyzer” (LS-MIDA) is presented that processes experimental mass spectrometry (MS) data on the basis of metabolite information such as the number of atoms in the compound, mass to charge ratio (m/e or m/z) values of the compounds and fragments under study, and the experimental relative MS intensities reflecting the enrichments of isotopomers in (13)C- or (15) N-labelled compounds, in comparison to the natural abundances in the unlabelled molecules. The software uses Brauman’s least square method of linear regression. As a result, global isotope enrichments of the metabolite or fragment under study and the molar abundances of each isotopomer are obtained and displayed. CONCLUSIONS: The new software provides an open-source platform that easily and rapidly converts experimental MS patterns of labelled metabolites into isotopomer enrichments that are the basis for subsequent observation-driven analysis of pathways and fluxes, as well as for model-driven metabolic flux calculations. |
format | Online Article Text |
id | pubmed-3720290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37202902013-07-26 Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling Ahmed, Zeeshan Zeeshan, Saman Huber, Claudia Hensel, Michael Schomburg, Dietmar Münch, Richard Eisenreich, Wolfgang Dandekar, Thomas BMC Bioinformatics Software BACKGROUND: The knowledge of metabolic pathways and fluxes is important to understand the adaptation of organisms to their biotic and abiotic environment. The specific distribution of stable isotope labelled precursors into metabolic products can be taken as fingerprints of the metabolic events and dynamics through the metabolic networks. An open-source software is required that easily and rapidly calculates from mass spectra of labelled metabolites, derivatives and their fragments global isotope excess and isotopomer distribution. RESULTS: The open-source software “Least Square Mass Isotopomer Analyzer” (LS-MIDA) is presented that processes experimental mass spectrometry (MS) data on the basis of metabolite information such as the number of atoms in the compound, mass to charge ratio (m/e or m/z) values of the compounds and fragments under study, and the experimental relative MS intensities reflecting the enrichments of isotopomers in (13)C- or (15) N-labelled compounds, in comparison to the natural abundances in the unlabelled molecules. The software uses Brauman’s least square method of linear regression. As a result, global isotope enrichments of the metabolite or fragment under study and the molar abundances of each isotopomer are obtained and displayed. CONCLUSIONS: The new software provides an open-source platform that easily and rapidly converts experimental MS patterns of labelled metabolites into isotopomer enrichments that are the basis for subsequent observation-driven analysis of pathways and fluxes, as well as for model-driven metabolic flux calculations. BioMed Central 2013-07-09 /pmc/articles/PMC3720290/ /pubmed/23837681 http://dx.doi.org/10.1186/1471-2105-14-218 Text en Copyright © 2013 Ahmed et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Ahmed, Zeeshan Zeeshan, Saman Huber, Claudia Hensel, Michael Schomburg, Dietmar Münch, Richard Eisenreich, Wolfgang Dandekar, Thomas Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling |
title | Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling |
title_full | Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling |
title_fullStr | Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling |
title_full_unstemmed | Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling |
title_short | Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling |
title_sort | software ls-mida for efficient mass isotopomer distribution analysis in metabolic modelling |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720290/ https://www.ncbi.nlm.nih.gov/pubmed/23837681 http://dx.doi.org/10.1186/1471-2105-14-218 |
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