TY - JOUR
T1 - Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale
AU - Hu, Mengqi
AU - Dinh, Hoang V.
AU - Shen, Yihui
AU - Suthers, Patrick F.
AU - Foster, Charles J.
AU - Call, Catherine M.
AU - Ye, Xuanjia
AU - Pratas, Jimmy
AU - Fatma, Zia
AU - Zhao, Huimin
AU - Rabinowitz, Joshua D.
AU - Maranas, Costas D.
N1 - This work was funded by the DOE Center for Advanced Bioenergy and Bioproducts Innovation ( U.S. Department of Energy , Office of Science , Office of Biological and Environmental Research under Award Number DE-SC0018420 ). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the U.S. Department of Energy . Funding also provided by the DOE Office of Science , Office of Biological and Environmental Research (Award Number DE-SC0018260 ) Computations for this research were performed on the Pennsylvania State University's Institute for Computational and Data Sciences' Roar supercomputer.
PY - 2023/3
Y1 - 2023/3
N2 - 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, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. 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 (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.
AB - 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, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. 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 (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.
KW - Allosteric regulation
KW - Elemental reactions
KW - Kinetic model
KW - Metabolic flux analysis
KW - Michaelis–menten kinetics
KW - Non-linear parameter estimation
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U2 - 10.1016/j.ymben.2023.01.001
DO - 10.1016/j.ymben.2023.01.001
M3 - Article
C2 - 36603705
AN - SCOPUS:85145780591
SN - 1096-7176
VL - 76
SP - 1
EP - 17
JO - Metabolic Engineering
JF - Metabolic Engineering
ER -