(298f) Application of Systems of Differential Algebraic Equations to Kinetic Models of Metabolism

Reaction stoichiometry encapsulates the metabolic network connectivity arising from metabolite transports and biochemical conversions that take place in an organism, with genome-scale metabolic models having long proven useful in strain redesign for metabolic engineering purposes. However, the requirement of steady-state approximations can limit the scope and detail of suggested changes. Kinetic descriptions of metabolism, on the other hand, use kinetic rate expressions to link reaction fluxes to the concentration of intracellular metabolites and enzymes in order to predict metabolic responses to genetic and environmental perturbations. Moreover, kinetic models allow examining regulatory interactions and enzymatic parameters that impact bioproduction of a metabolite, but can be computationally intensive to analyze for larger systems. Here, we develop a framework that incorporates systems of differential algebraic equations (DAE) that enables analysis of large-scale kinetic models of metabolism. We examine core kinetic models for Clostridium thermocellum and Escherichia coli as well as large-scale kinetic models of E. coli. The method accounts for different mechanisms of substrate binding, reversible inhibition and activation of enzymes, and permits dynamic optimization which we apply to elucidate strain design targets. Our DAE-based framework has the potential to accelerate design-build-test-learn cycles for metabolic engineering and to pinpoint modifications that enhance productivity.