ANALYSIS AND DESIGN OF METABOLIC REACTION NETWORKS VIA MIXED-INTEGER LINEAR OPTIMIZATION

Improvements in bioprocess performance can be achieved by genetic modi fications of metabolic control structures. A novel optimization proble m helps quantitative understanding and rational metabolic engineering of metabolic reaction pathways. Maximizing the performance of a metabo lic reaction pathway is treated as a mixed-integer linear programming formulation to identify changes in regulatory structure and strength a nd in cellular content of pertinent enzymes which should be implemente d to optimize a particular metabolic process. A regulatory superstruct ure proposed contains all alternative regulatory structures that can b e considered for a given pathway. This is approach is followed. to fin d the optimal regulatory structure for maximization of phenylalanine s electivity in the microbial aromatic amino acid synthesis pathway. The solution suggests that from the eight feedback inhibitory loops in th e original regulatory structure of this pathway, inactivation of at le ast three loops and over expression of three enzymes will increase phe nylalanine selectivity by 42%. Moreover, novel regulatory structures w ith only two loops, none of which exists in the original pathway could result in a selectivity up to 95%.