S147: Model-based approaches for metabolic engineering

Bioprocess development for biofuels and biochemicals typically requires several rounds of metabolic engineering to meet process targets including product yield, titer and productivity, all of which impact the process economics. Recent advances in experimental and computational technologies have enabled the detailed characterization of biological systems. In particular, the molecular components of these systems including the list of genes, proteins they encode, and compounds that interact with these proteins can be determined. Similar advances in computational modeling techniques have allowed the development of genome-scale models of metabolism in several organisms.  In first part, a rational approach based on bi-level optimization to enhance bioprocess productivity by forcing co-utilization of substrates will be shown.  In the next part of the talk, a novel nested nonlinear optimization method for metabolic engineering resulting in over hundred different strain design strategies for biochemicals production will be presented. We will also examine the role of the redundant pathways from a design perspective and present computational results on how these pathways is valuable for robust design. Finally, we will present a novel computational approach that incorporate all three bioprocess targets to obtain computational strain designs that have balanced productivity, yield and titer.