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Optimization‐based metabolic control analysis
Author(s) -
Uygun Korkut,
Uygun Basak,
Matthew Howard W. T.,
Huang Yinlun
Publication year - 2010
Publication title -
biotechnology progress
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 129
eISSN - 1520-6033
pISSN - 8756-7938
DOI - 10.1002/btpr.482
Subject(s) - metabolic control analysis , biological system , metabolic network , nad+ kinase , metabolite , glycolysis , work (physics) , chemistry , control theory (sociology) , metabolic pathway , control (management) , computer science , metabolism , biochemistry , enzyme , thermodynamics , biology , physics , microbiology and biotechnology , artificial intelligence , insulin
In this work, a novel optimization‐based metabolic control analysis (OMCA) method is introduced for reducing data requirement for metabolic control analysis (MCA). It is postulated that using the optimal control approach, the fluxes in a metabolic network are correlated to metabolite concentrations and enzyme activities as a state‐feedback control system that is optimal with respect to a homeostasis objective. It is then shown that the optimal feedback gains are directly related to the elasticity coefficients (ECs) of MCA. This approach requires determination of the relative “importance” of metabolites and fluxes for the system, which is possible with significantly reduced experimental data, as compared with typical MCA requirements. The OMCA approach is applied to a top–down control model of glycolysis in hepatocytes. It is statistically demonstrated that the OMCA model is capable of predicting the ECs observed experimentally with few exceptions. Further, an OMCA‐based model reconciliation study shows that the modification of four assumed stoichiometric coefficients in the model can explain most of the discrepancies, with the exception of elasticities with respect to the NADH/NAD ratio. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010