Exploring metabolic pathways in genome-scale networks via generating flux modes

Bioinformatics. 2011 Feb 15;27(4):534-40. doi: 10.1093/bioinformatics/btq681. Epub 2010 Dec 10.

Abstract

Motivation: The reconstruction of metabolic networks at the genome scale has allowed the analysis of metabolic pathways at an unprecedented level of complexity. Elementary flux modes (EFMs) are an appropriate concept for such analysis. However, their number grows in a combinatorial fashion as the size of the metabolic network increases, which renders the application of EFMs approach to large metabolic networks difficult. Novel methods are expected to deal with such complexity.

Results: In this article, we present a novel optimization-based method for determining a minimal generating set of EFMs, i.e. a convex basis. We show that a subset of elements of this convex basis can be effectively computed even in large metabolic networks. Our method was applied to examine the structure of pathways producing lysine in Escherichia coli. We obtained a more varied and informative set of pathways in comparison with existing methods. In addition, an alternative pathway to produce lysine was identified using a detour via propionyl-CoA, which shows the predictive power of our novel approach.

Availability: The source code in C++ is available upon request.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acyl Coenzyme A / metabolism
  • Computational Biology / methods*
  • Computer Simulation
  • Escherichia coli / genetics
  • Escherichia coli / metabolism
  • Genome, Bacterial
  • Lysine / biosynthesis
  • Metabolic Networks and Pathways / genetics*
  • Models, Theoretical*
  • Systems Biology / methods*

Substances

  • Acyl Coenzyme A
  • propionyl-coenzyme A
  • Lysine