Peer-Reviewed Journal Details
Mandatory Fields
Fleming, RMT,Thiele, I,Nasheuer, HP
2009
December
Biophysical Chemistry
Quantitative assignment of reaction directionality in constraint-based models of metabolism: Application to Escherichia coli
Published
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Optional Fields
Systems biology Constraint-based modeling Thermodynamics HIGH-THROUGHPUT THERMODYNAMIC ANALYSIS REGULATORY NETWORK IONIC-STRENGTH OPTIMAL-GROWTH FLUX ANALYSIS PH CAPABILITIES RECONSTRUCTIONS OPTIMIZATION
145
47
56
Constraint-based modeling is an approach for quantitative prediction of net reaction flux in genome-scale biochemical networks. In vivo, the second law of thermodynamics requires that net macroscopic flux be forward, when the transformed reaction Gibbs energy is negative. We calculate the latter by using (i) group contribution estimates of metabolite species Gibbs energy, combined with (ii) experimentally measured equilibrium constants. In an application to a genome-scale stoichiometric model of Escherichia coli metabolism, iLAF1260, we demonstrate that quantitative prediction of reaction directionality is increased in scope and accuracy by integration of both data sources, transformed appropriately to in vivo pH, temperature and ionic strength. Comparison of quantitative versus qualitative assignment of reaction directionality in iAF1260, assuming an accommodating reactant concentration range of 0.02-20 mM, revealed that quantitative assignment leads to a low false positive, but high false negative, prediction of effectively irreversible reactions. The latter is partly due to the uncertainty associated with group contribution estimates. We also uncovered evidence that the high intracellular concentration of glutamate in E coli may be essential to direct otherwise thermodynamically unfavorable essential reactions, such as the leucine transaminase reaction, in an anabolic direction. (C) 2009 Elsevier B.V. All rights reserved.
DOI 10.1016/j.bpc.2009.08.007
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