Modelling of Metabolic Networks with Gene Regulation in Yeast and in Vivo Determination of Rate Parameters

J.A. Asenjo, P. Moisset, I. Rapaport*, D. Vaisman, and B.A. Andrews

                               Centre for Biochemical Engineering and Biotechnology

                                              *Centre for Mathematical Modelling

Beauchef 850, Santiago, Chile

juasenjo@ing.uchile.cl

A model of the metabolic network including gene regulation to simulate metabolic fluxes during batch cultivation of the yeast Saccharomyces cerevisiae has been developed. The network includes reactions of glycolysis, gluconeogenesis, glycerol and ethanol synthesis and consumption, the tricarboxylic acid cycle and protein synthesis. Carbon sources considered were glucose and then ethanol synthesized during growth on glucose. The metabolic network is coupled with a gene regulation network which defines enzyme synthesis (activities) and incorporates regulation by glucose (enzyme induction and repression), modeled using ordinary differential equations. The model includes enzyme kinetics, equations that follow both mass-action law and transport as well as inducible, repressible and constitutive enzymes of the metabolism. The model was able to simulate the fermentation of yeast during the exponential growth phase on glucose and the exponential growth on ethanol using only one set of parameters very accurately.

A comparison between the simulation of the continuous model and the experimental data of the diauxic yeast fermentation for glucose, biomass and ethanol shows an extremely good match using the parameters found. The adjustment of the fermentation profiles of biomass, glucose and ethanol were 95%, 95% and 79%, respectively. With these results the simulation was considered very successful. The method proposed allows the obtention of a much larger number of unknowns than equations. Hence an important contribution is to present a convenient way to find in vivo rate parameters to model metabolic and genetic networks under different conditions. Furthermore, the model allowed the obtention of intracellular concentrations of metabolites (not measured) very similar to experimental values previously reported.