(106a) Building a Large-Scale Kinetic Model for Saccharomyces Cerevisiae: Challenges and Insights
- Conference: AIChE Annual Meeting
- Year: 2022
- Proceeding: 2022 Annual Meeting
- Group: Computing and Systems Technology Division
- Time: Monday, November 14, 2022 - 12:30pm-12:49pm
The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain chosen, it remains unclear whether kinetic models constructed for different strains of the same microbial species may lead to similar or significantly different parameterizations. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (k-Sce307-CEN), and growth-deficient FY4 (derived from S288C, k-Sce307-FY4). The metabolic network for each model contains 307 reactions, 230 metabolites, and 114 substrate level regulatory interactions covering central metabolism and growth-essential biosynthetic metabolism. The two models (for CEN.PK and FY4 respectively) were able to recapitulate, within one standard deviation, 92% and 74% of the training dataset which includes 13C-MFA fluxes for wild-type and eight single-knockout mutants of each strain. We further use the kinetic models to simulate of overproduction strains for biochemicals revealing kinetically compatible strain-compound-intervention combinations. The kinetic models presented in this study validate the possibility of using kinetic models parameterized with fluxomics datasets to identify key enzymes responsible for phenotypic differences in different strains.