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A computational procedure for optimal engineering interventions using kinetic models of metabolism
Francisco G Vital-Lopez1, Antonios Armaou, Evgeni V Nikolaev
1Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Biotechnology Progress
|December 2, 2006
Summary
This study presents a computational method for optimizing microbial strain design by identifying gene and enzyme modifications. The approach uses mixed-integer linear programming to maximize product flux in metabolic engineering.
Area of Science:
- Metabolic Engineering
- Computational Biology
- Synthetic Biology
Background:
- Designing microbial strains with enhanced capabilities requires identifying optimal intervention strategies.
- Existing methods may not efficiently identify all necessary genetic and enzymatic modifications for maximizing product flux.
Purpose of the Study:
- To develop a general computational procedure for determining gene/enzyme modifications (elimination, repression, overexpression) to maximize flux through a target product.
- To provide a framework applicable to general kinetic models of metabolic systems.
Main Methods:
- Generalized linearization of kinetic models.
- Iterative application of mixed-integer linear programming (MILP) optimization.
- Hierarchical identification of reaction eliminations and enzyme level modulations.
Main Results:
- The proposed procedure successfully identifies optimal engineering interventions for metabolic flux maximization.
- The study investigates the impact of concentration and enzyme level changes, including a variant for high-fold changes.
- Demonstrated efficacy using a kinetic model of E. coli central carbon metabolism for serine overproduction.
Conclusions:
- The developed computational procedure offers a generalizable approach for metabolic engineering.
- This method facilitates the rational design of microbial strains for enhanced production of specific compounds.
- Applicable to any metabolic system with a provided kinetic description.
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