Journal Article

Computing the shortest elementary flux modes in genome-scale metabolic networks

Luis F. de Figueiredo, Adam Podhorski, Angel Rubio, Christoph Kaleta, John E. Beasley, Stefan Schuster and Francisco J. Planes

in Bioinformatics

Volume 25, issue 23, pages 3158-3165
Published in print December 2009 | ISSN: 1367-4803
Published online September 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp564
Computing the shortest elementary flux modes in genome-scale metabolic networks

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Motivation: Elementary flux modes (EFMs) represent a key concept to analyze metabolic networks from a pathway-oriented perspective. In spite of considerable work in this field, the computation of the full set of elementary flux modes in large-scale metabolic networks still constitutes a challenging issue due to its underlying combinatorial complexity.

Results: In this article, we illustrate that the full set of EFMs can be enumerated in increasing order of number of reactions via integer linear programming. In this light, we present a novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks. Our method was applied to find the K-shortest EFMs that produce lysine in the genome-scale metabolic networks of Escherichia coli and Corynebacterium glutamicum. A detailed analysis of the biological significance of the K-shortest EFMs was conducted, finding that glucose catabolism, ammonium assimilation, lysine anabolism and cofactor balancing were correctly predicted. The work presented here represents an important step forward in the analysis and computation of EFMs for large-scale metabolic networks, where traditional methods fail for networks of even moderate size.

Contact: fplanes@tecnun.es

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  6351 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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