4.6 Article

Development of thermodynamic optimum searching (TOS) to improve the prediction accuracy of flux balance analysis

Journal

BIOTECHNOLOGY AND BIOENGINEERING
Volume 110, Issue 3, Pages 914-923

Publisher

WILEY
DOI: 10.1002/bit.24739

Keywords

flux balance analysis; constraint-based metabolic model; maximum entropy production principle; energy loop law

Funding

  1. National Basic Research Program of China (973 program) [2011CBA00807, 2011CBA00804]
  2. National High Technology Research and Development Program of China (863 program) [2011AA02A208]
  3. Hundreds of Talents Program of the Chinese Academy of Sciences
  4. National Health and Medical Research Council of Australia (NHMRC) Peter Doherty Fellowship [490989]
  5. Australian Research Council (ARC)
  6. National Natural Science Foundation of China [61202167]
  7. Knowledge Innovation Program of the Chinese Academy of Sciences [KSCX2-EW-Q-14, KSCX2-EW-G-8]
  8. Tianjin Municipal Science and Technology Commission [10ZCKFSY05600]

Ask authors/readers for more resources

Flux balance analysis (FBA) has been widely used in calculating steady-state flux distributions that provide important information for metabolic engineering. Several thermodynamics-based methods, for example, quantitative assignment of reaction directionality and energy balance analysis have been developed to improve the prediction accuracy of FBA. However, these methods can only generate a thermodynamically feasible range, rather than the most thermodynamically favorable solution. We therefore developed a novel optimization method termed as thermodynamic optimum searching (TOS) to calculate the thermodynamically optimal solution, based on the second law of thermodynamics, the minimum magnitude of the Gibbs free energy change and the maximum entropy production principle (MEPP). Then, TOS was applied to five physiological conditions of Escherichia coli to evaluate its effectiveness. The resulting prediction accuracy was found significantly improved (10.748.5%) by comparing with the 13C-fluxome data, indicating that TOS can be considered an advanced calculation and prediction tool in metabolic engineering. Biotechnol. Bioeng. 2013; 110: 914923. (c) 2012 Wiley Periodicals, Inc.

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