A computational procedure for optimal engineering interventions using kinetic models of metabolism.
The identification of optimal intervention strategies is a key step in designing microbial strains with enhanced capabilities. In this paper, we propose a general computational procedure to determine which genes/enzymes should be eliminated, repressed or overexpressed to maximize the flux through a product of interest for general kinetic models. The procedure relies on the generalized linearization of a kinetic description of the investigated metabolic system and the iterative application of mixed-integer linear programming (MILP) optimization to hierarchically identify all engineering interventions allowing for reaction eliminations and/or enzyme level modulations. The effect of the magnitude of the allowed changes in concentrations and enzyme levels is investigated, and a variant of the method to explore high-fold changes in enzyme levels is also analyzed. The proposed framework is demonstrated using a kinetic model modeling part of the central carbon metabolism of E. coli for serine overproduction. The proposed computational procedure is a general approach that can be applied to any metabolic system for which a kinetic description is provided.
Vital-Lopez
Francisco G
FG
Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Armaou
Antonios
A
Nikolaev
Evgeni V
EV
Maranas
Costas D
CD
D003198:Computer Simulation; D004926:Escherichia coli / Q000502:physiology*; D029968:Escherichia coli Proteins / Q000235:genetics* / Q000378:metabolism*; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology*; D005818:Genetic Engineering / Q000379:methods*; D007700:Kinetics; D008657:Metabolic Clearance Rate; D008954:Models, Biological; D009097:Multienzyme Complexes / Q000235:genetics / Q000378:metabolism*; D011994:Recombinant Proteins / Q000378:metabolism
D029968:Escherichia coli Proteins; D009097:Multienzyme Complexes; D011994:Recombinant Proteins