Validation of a Metabolic Network for Saccharomyces cerevisiae Using Mixed Substrate Studies

Journal Article (1996)
Author(s)

Peter A. Vanrolleghem (External organisation)

Patricia De Jong-Gubbels (External organisation)

WM Van Gulik (École Polytechnique Fédérale de Lausanne)

Jack Pronk (TU Delft - BT/Biotechnologie)

Johannes P. Van Dijken (External organisation)

J.J. Heijnen (TU Delft - OLD BT/Cell Systems Engineering)

Department
BT/Biotechnologie
DOI related publication
https://doi.org/10.1021/bp960022i
More Info
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Publication Year
1996
Language
English
Department
BT/Biotechnologie
Issue number
4
Volume number
12
Pages (from-to)
434-448

Abstract

Setting up a metabolic network model for respiratory growth of Saccharomyces cerevisiae requires the estimation of only two (energetic) stoichiometric parameters: (1) the operational PO ratio and (2) a growth-related maintenance factor k. It is shown, both theoretically and practically, how chemostat cultivations with different mixtures of two substrates allow unique values to be given to these unknowns of the proposed metabolic model. For the yeast and model considered, an effective PO ratio of 1.09 mol of ATP/mol of O (95% confidence interval 1.07−1.11) and a k factor of 0.415 mol of ATP/C-mol of biomass (0.385−0.445) were obtained from biomass substrate yield data on glucose/ethanol mixtures. Symbolic manipulation software proved very valuable in this study as it supported the proof of theoretical identifiability and significantly reduced the necessary computations for parameter estimation. In the transition from 100% glucose to 100% ethanol in the feed, four metabolic regimes occur. Switching between these regimes is determined by cessation of an irreversible reaction and initiation of an alternative reaction. Metabolic network predictions of these metabolic switches compared well with activity measurements of key enzymes. As a second validation of the network, the biomass yield of S. cerevisiae on acetate was also compared to the network prediction. An excellent agreement was found for a network in which acetate transport was modeled with a proton symport, while passive diffusion of acetate gave significantly higher yield predictions.

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