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Bioinformatics Advance Access published online on March 7, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm065
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

From Structure to Dynamics of Metabolic Pathways: Application to the Plant Mitochondrial TCA Cycle

Ralf Steuer a,c, Adriano Nunes Nesi b, Alisdair R. Fernie b, Thilo Gross c, Bernd Blasius c and Joachim Selbig a,b

aUniversity Potsdam, Institute for Biochemistry and Biology, Karl-Liebknecht-Strasse 24-25, Haus 20, 14476 Potsdam, Germany. bMax-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. cUniversity Potsdam, Institute for Physics, Nonlinear Dynamics Group, Am Neuen Palais 10, 14469 Potsdam, Germany.

To whom correspondence should be addressed. Dr. Ralf Steuer, E-mail: steuer{at}agnld.uni-potsdam.de


  Abstract

Motivation: Mitochondrial metabolism, dominated by the reactions of the tricarboxylic acid (TCA) cycle, is of vital importance for a wide range of metabolic processes. In particular for autotrophic tissue, such as plant leaves, the TCA cycle marks the point of divergence of anabolic pathways and plays an essential role in biosynthesis. However, despite extensive knowledge about its stoichiometric properties, the function and the dynamical capabilities of the TCA cycle remain largely unknown.

Methods and Results: Based on a recently proposed formalism, we investigate the dynamic and functional properties of the mitochondrial TCA cycle of plants. Starting with the structural properties, as described by the elementary flux modes of the system, we aim for the transition from structure to the dynamics of the TCA cycle. Using a parametric description of the system, encompassing all possible differential equations and parameter values, we detect and quantify regimes of different dynamic behavior. Optimizing the system with respect to dynamic stability, we demonstrate that maximal stability is associated with specific (relative) metabolite concentrations and flux values that are subsequently compared to the experimental literature. Our analysis also serves as a general example how to elucidate the transition from the structure to the dynamics of metabolic pathways.

Associate Editor: Prof. Alfonso Valencia

Received on August 20, 2006; revised on February 1, 2007; accepted on February 19, 2007

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