Comparative metabolic network flux analysis to identify differences in cellular metabolism

Sarah McGarrity, Sigurður T. Karvelsson, Ólafur E. Sigurjónsson, Óttar Rolfsson*

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Metabolic network flux analysis uses genome-scale metabolic reconstructions to integrate transcriptomics, proteomics, and/or metabolomics data to allow for comprehensive interpretation of genotype to metabolic phenotype relationships. The compilation of many Constraint-based model analysis methods into one MATLAB package, the COBRAtoolbox, has opened the possibility of using these methods to the many biologists with some knowledge of the commonly used statistical program, MATLAB. Here we outline the steps required to take a published genome-scale metabolic reconstruction and interrogate its consistency and biological feasibility. Subsequently, we demonstrate how mRNA expression data and metabolomics data, relating to one or more cell types or biological contexts, can be applied to constrain and generate metabolic models descriptive of metabolic flux phenotypes. Finally, we describe the comparison of the resulting models and model outputs with the aim of identifying metabolic biomarkers and changes in cellular metabolism.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages223-269
Number of pages47
DOIs
Publication statusPublished - 2020

Publication series

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

Bibliographical note

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

Other keywords

  • Constraint-based metabolic models
  • Data integration
  • Flux balance analysis
  • Genome-scale reconstruction
  • Metabolomics
  • Systems biology
  • Transcriptomics

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