Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data.

TitleReconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data.
Publication TypeJournal Article
Year of Publication2004
AuthorsVo TD, Greenberg HJ, Palsson BØ
JournalThe Journal of biological chemistry
Volume279
Issue38
Pagination39532-40
PubMed Date2004 Sep 17
ISSN0021-9258
KeywordsAmino Acids, Databases, Protein, Energy Metabolism, Fatty Acids, Glucose, Heme, Humans, Mitochondria, Proteomics, Reactive Oxygen Species
Abstract

Diverse datasets including genomic, proteomic, isotopomer, and DNA sequence variation are becoming available for human mitochondria. Thus there is a need to integrate these data within an in silico modeling framework where mitochondrial biology and related disorders can be studied and analyzed. This paper reports a reconstruction and characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. The 189 reactions included in this reconstruction are both elementally and charge-balanced and are assigned to their respective cellular compartments (mitochondrial, cytosol, or extracellular). The capabilities of the reconstructed network to fulfill three metabolic functions (ATP production, heme synthesis, and mixed phospholipid synthesis) were determined. Network-based analysis of the mitochondrial energy conversion process showed that the overall ATP yield per glucose is 31.5. Network flexibility, characterized by allowable variation in reaction fluxes, was evaluated using flux variability analysis and analysis of all of the possible optimal flux distributions. Results showed that the network has high flexibility for the biosynthesis of heme and phospholipids but modest flexibility for maximal ATP production. A subset of all of the optimal network flux distributions, computed with respect to the three metabolic functions individually, was found to be highly correlated, suggesting that this set may contain physiological meaningful fluxes. Examinations of optimal flux distributions also identified correlated reaction sets that form functional modules in the network.

Alternate JournalJ. Biol. Chem.
PubMed ID15205464

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