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Software LS-MIDA for efficient mass isotopomer distribution analysis in metabolic modelling

Please always quote using this URN: urn:nbn:de:bvb:20-opus-95882
  • 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. ResultsBackground 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 13C- 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.show moreshow less

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Metadaten
Author: Thomas Dandekar, Zeeshan Ahmed, Zeeshan Saman, Claudia Huber, Michael Hensel, Dietmar Schomburg, Richard Münch, Wolfgang Eisenreich
URN:urn:nbn:de:bvb:20-opus-95882
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):BMC Bioinformatics
Year of Completion:2013
Source:In: BMC Bioinformatics (2013) 14: 218, doi:10.1186/1471-2105-14-218
URL:http://www.biomedcentral.com/1471-2105/14/218
DOI:https://doi.org/10.1186/1471-2334-13-266
Sonstige beteiligte Institutionen:EMBL, Structural and Computational Biology Unit, Heidelberg, Germany
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:LS-MIDA
Release Date:2014/04/23
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2013
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung