Literature DB >> 15572364

Candidate metabolic network states in human mitochondria. Impact of diabetes, ischemia, and diet.

Ines Thiele1, Nathan D Price, Thuy D Vo, Bernhard Ø Palsson.   

Abstract

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.

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Year:  2004        PMID: 15572364     DOI: 10.1074/jbc.M409072200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  64 in total

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Review 2.  Network biology methods integrating biological data for translational science.

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5.  Linkage of organic anion transporter-1 to metabolic pathways through integrated "omics"-driven network and functional analysis.

Authors:  Sun-Young Ahn; Neema Jamshidi; Monica L Mo; Wei Wu; Satish A Eraly; Ankur Dnyanmote; Kevin T Bush; Tom F Gallegos; Douglas H Sweet; Bernhard Ø Palsson; Sanjay K Nigam
Journal:  J Biol Chem       Date:  2011-07-12       Impact factor: 5.157

6.  Candidate states of Helicobacter pylori's genome-scale metabolic network upon application of "loop law" thermodynamic constraints.

Authors:  Nathan D Price; Ines Thiele; Bernhard Ø Palsson
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Review 7.  Biochemical and statistical network models for systems biology.

Authors:  Nathan D Price; Ilya Shmulevich
Journal:  Curr Opin Biotechnol       Date:  2007-08-03       Impact factor: 9.740

8.  Squeezing Flux Out of Fat.

Authors:  Alba Gonzalez-Franquesa; Mary-Elizabeth Patti
Journal:  Trends Endocrinol Metab       Date:  2018-02-04       Impact factor: 12.015

9.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.

Authors:  Jan Schellenberger; Richard Que; Ronan M T Fleming; Ines Thiele; Jeffrey D Orth; Adam M Feist; Daniel C Zielinski; Aarash Bordbar; Nathan E Lewis; Sorena Rahmanian; Joseph Kang; Daniel R Hyduke; Bernhard Ø Palsson
Journal:  Nat Protoc       Date:  2011-08-04       Impact factor: 13.491

10.  A protocol for generating a high-quality genome-scale metabolic reconstruction.

Authors:  Ines Thiele; Bernhard Ø Palsson
Journal:  Nat Protoc       Date:  2010-01-07       Impact factor: 13.491

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