Software supporting a workflow of quantitative dynamic flux maps estimation in central metabolism from SIRM experimental data

Vitaly A. Selivanov, Silvia Marin, Josep Tarragó-Celada, Andrew N. Lane, Richard M. Higashi, Teresa W.M. Fan, Pedro de Atauri, Marta Cascante

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
Pages271-298
Number of pages28
DOIs
StatePublished - 2020

Publication series

NameMethods in Molecular Biology
Volume2088
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Bibliographical note

Funding Information:
This work was supported by the European Commission (PhenoMeNal EC-654241), MINECO-European Commission FEDER funds—“Una manera de hacer Europa” (SAF2017-89673-R and SAF2015-70270-REDT), Instituto de Salud Carlos III and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD, CB17/04/00023 and INB-Bioinfor-matics Platform, of the ISCIII, PT17/0009/0018), Agència de Gestió d’Ajuts Universitaris i de Recerca—Generalitat de Catalunya (2017SGR-1033), and Ministerio de Educación y Formación Pro-fesional (FPU14-05992); and by the Redox Metabolism Shared Resource of the University of Kentucky Markey Cancer Center (P30CA177558). M.C. also acknowledges the prize “ICREA Academia” for the excellence in research, funded by ICREA foundation—Generalitat de Catalunya.

Funding Information:
This work was supported by the European Commission (PhenoM-eNal EC-654241), MINECO-European Commission FEDER funds—“Una manera de hacer Europa” (SAF2017-89673-R and SAF2015-70270-REDT), Instituto de Salud Carlos III and Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD, CB17/04/00023 and INB-Bioinfor-matics Platform, of the ISCIII, PT17/0009/0018), Agència de Gestió d’Ajuts Universitaris i de Recerca—Generalitat de Catalunya (2017SGR-1033), and Ministerio de Educación y Formación Profesional (FPU14-05992); and by the Redox Metabolism Shared Resource of the University of Kentucky Markey Cancer Center (P30CA177558). M.C. also acknowledges the prize “ICREA Aca-demia” for the excellence in research, funded by ICREA founda-tion—Generalitat de Catalunya.

Publisher Copyright:
© Springer Science+Business Media, LLC, part of Springer Nature 2020.

Keywords

  • Central energy metabolism
  • Computational analysis
  • Isotopolog distribution
  • Kinetic models of metabolism
  • Mass spectrometry
  • Metabolic fluxes
  • Stable isotope tracing
  • Stable isotope-resolved metabolomics

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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