Open AccessDesign of stable metabolic networks
Author(s) -
Di Maggio Jimena,
Blanco Aníbal M.,
Bandoni J. Alberto,
Díaz Ricci Juan Carlos,
Diaz M. Soledad
Publication year - 2017
Publication title -
engineering in life sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 57
eISSN - 1618-2863
pISSN - 1618-0240
DOI - 10.1002/elsc.201700065
Subject(s) - metabolic network , bioprocess , mathematical optimization , biological system , metabolic engineering , stability (learning theory) , metabolic pathway , pentose phosphate pathway , maximization , computer science , biochemical engineering , mathematics , chemistry , enzyme , biochemistry , glycolysis , biology , paleontology , machine learning , engineering
In this work, we propose eigenvalue optimization combined with Lyapunov theory concepts to ensure stability of the Embden—Meyerhof–Parnas pathway, the pentose‐phosphate pathway, the phosphotransferase system and fermentation reactions of Escherichia coli . We address the design of a metabolic network for the maximization of different metabolite production rates. The first case study focuses on serine production, based on a model that consists of 18 differential equations corresponding to dynamic mass balances for extracellular glucose and intracellular metabolites, and thirty kinetic rate expressions. A second case study addresses the design problem to maximize ethanol production, based on a dynamic model that involves mass balances for 25 metabolites and 38 kinetic rate equations. The nonlinear optimization problem including stability constraints has been solved with reduced space Successive Quadratic Programming techniques. Numerical results provide useful insights on the stability properties of the studied kinetic models.