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Originally published In Press as doi:10.1074/jbc.M409072200 on November 30, 2004
J. Biol. Chem., Vol. 280, Issue 12, 11683-11695, March 25, 2005
Candidate Metabolic Network States in Human Mitochondria
IMPACT OF DIABETES, ISCHEMIA, AND DIET*
Ines Thiele ,
Nathan D. Price ,
Thuy D. Vo , and
Bernhard Ø. Palsson, Serves on the scientific advisory board of Genomatica Inc. ¶
From the
Department of Bioengineering, University of California, San Diego, California 92093-0412 and the Ecole Supérieure de Biotechnologie de Strasbourg, 67412 Strasbourg, France
The human mitochondrial metabolic network was recently reconstructed based on proteomic and biochemical data. Linear programming and uniform random sampling were applied herein to identify candidate steady states of the metabolic network that were consistent with the imposed physico-chemical constraints and available experimental data. The activity of the mitochondrion was studied under four metabolic conditions: normal physiologic, diabetic, ischemic, and dietetic. Pairwise correlations between steady-state reaction fluxes were calculated in each condition to evaluate the dependence among the reactions in the network. Applying constraints on exchange fluxes resulted in predictions for intracellular fluxes that agreed with experimental data. Analyses of the steady-state flux distributions showed that the experimentally observed reduced activity of pyruvate dehydrogenase in vivo could be a result of stoichiometric constraints and therefore would not necessarily require enzymatic inhibition. The observed changes in the energy metabolism of the mitochondrion under diabetic conditions were used to evaluate the impact of previously suggested treatments. The results showed that neither normalized glucose uptake nor decreased ketone body uptake have a positive effect on the mitochondrial energy metabolism or network flexibility. Taken together, this study showed that sampling of the steady-state flux space is a powerful method to investigate network properties under different conditions and provides a basis for in silico evaluations of effects of potential disease treatments.
Received for publication, August 9, 2004
, and in revised form, October 25, 2004.
* This work was supported by grants from the Thieles, Bourse d'Alsace, France and a grant from the National Science Foundation (NSF/BES-01-20363). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The on-line version of this article (available at http://www.jbc.org) contains supplemental figures and tables.
¶ To whom correspondence should be addressed: Dept. of Bioengineering, 9500 Gilman Dr. 0412, La Jolla, CA 92093-0412; Tel.: 858-534-5668; Fax: 858-822-3120; E-mail: palsson{at}ucsd.edu.

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Copyright © 2005 by the American Society for Biochemistry and Molecular Biology.
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