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Yeast Systems Biology

Volume 759 of the series Methods in Molecular Biology pp 483-497

Date:

Use of Genome-Scale Metabolic Models in Evolutionary Systems Biology

  • Balázs PappAffiliated withInstitute of Biochemistry, Biological Research Center of the Hungarian Academy of SciencesDepartment of Genetics, Cambridge Systems Biology Centre, University of Cambridge Email author 
  • , Balázs SzappanosAffiliated withInstitute of Biochemistry, Biological Research Center
  • , Richard A. NotebaartAffiliated withCentre for Molecular and Biomolecular Informatics (NCMLS), Radboud University Nijmegen Medical CentreCentre for Systems Biology and Bioenergetics, Radboud University Nijmegen Medical Centre

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Abstract

One of the major aims of the nascent field of evolutionary systems biology is to test evolutionary hypotheses that are not only realistic from a population genetic point of view but also detailed in terms of molecular biology mechanisms. By providing a mapping between genotype and phenotype for hundreds of genes, genome-scale systems biology models of metabolic networks have already provided valuable insights into the evolution of metabolic gene contents and phenotypes of yeast and other microbial species. Here we review the recent use of these computational models to predict the fitness effect of mutations, genetic interactions, evolutionary outcomes, and to decipher the mechanisms of mutational robustness. While these studies have demonstrated that even simplified models of biochemical reaction networks can be highly informative for evolutionary analyses, they have also revealed the weakness of this modeling framework to quantitatively predict mutational effects, a challenge that needs to be addressed for future progress in evolutionary systems biology.

Key words

Flux balance analysis (FBA) constraint-based modeling gene essentiality genetic interaction genome evolution fitness landscape metabolic network Saccharomyces cerevisiae