title: A computational procedure for optimal engineering interventions using kinetic models of metabolism.
abstract: 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.
authors.affiliation: Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
authors.forename: Francisco G
authors.initials: FG
authors.lastname: Vital-Lopez
authors.forename: Antonios
authors.initials: A
authors.lastname: Armaou
authors.forename: Evgeni V
authors.initials: EV
authors.lastname: Nikolaev
authors.forename: Costas D
authors.initials: CD
authors.lastname: Maranas
mesh_terms: 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
chemical_list: D029968:Escherichia coli Proteins; D009097:Multienzyme Complexes; D011994:Recombinant Proteins