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Advances in Bioinformatics
Volume 2012, Article ID 159423, 16 pages
http://dx.doi.org/10.1155/2012/159423
Research Article

Flux Analysis of the Trypanosoma brucei Glycolysis Based on a Multiobjective-Criteria Bioinformatic Approach

1Laboratoire Bordelais de Recherche en Informatique, UMR CNRS 5800, Université Bordeaux, 351 Cours de la Libération, 33405 Talence Cedex, France
2Centre de Bioinformatique de Bordeaux, Université Bordeaux Segalen, 142 Rue Léo Saignat, 33076 Bordeaux Cedex, France
3Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, Université Bordeaux Segalen, CNRS, 146 rue Léo Saignat, 33076 Bordeaux, France
4The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
5Institut National de Recherche en Agronomie, UMR 1331 TOXALIM, 180 Chemin de Tournefeuille, 31027 Toulouse, France

Received 27 April 2012; Accepted 11 July 2012

Academic Editor: Aristotelis Chatziioannou

Copyright © 2012 Amine Ghozlane et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Trypanosoma brucei is a protozoan parasite of major of interest in discovering new genes for drug targets. This parasite alternates its life cycle between the mammal host(s) (bloodstream form) and the insect vector (procyclic form), with two divergent glucose metabolism amenable to in vitro culture. While the metabolic network of the bloodstream forms has been well characterized, the flux distribution between the different branches of the glucose metabolic network in the procyclic form has not been addressed so far. We present a computational analysis (called Metaboflux) that exploits the metabolic topology of the procyclic form, and allows the incorporation of multipurpose experimental data to increase the biological relevance of the model. The alternatives resulting from the structural complexity of networks are formulated as an optimization problem solved by a metaheuristic where experimental data are modeled in a multiobjective function. Our results show that the current metabolic model is in agreement with experimental data and confirms the observed high metabolic flexibility of glucose metabolism. In addition, Metaboflux offers a rational explanation for the high flexibility in the ratio between final products from glucose metabolism, thsat is, flux redistribution through the malic enzyme steps.