Metabolic engineering under uncertainty-II: Analysis of yeast metabolism

Yeast metab. has been used extensively in scientific investigations and industrial applications. Understanding the properties of the yeast metabolic network is crucial, yet unaccomplished due to its high complexity, the different culture conditions, and the uncertainty assocd. with kinetic parameters. We recently developed a computational and math. framework using Monte Carlo method in which parameter uncertainty can be addressed through large-scale sampling procedure. This framework was applied on the compartmentalized central carbon pathways of Saccharomyces cerevisiae metab. considering the growth environment of batch and chemostat reactor and integrating information from metabolic flux anal. Statistical anal. of the results indicates that yeast cells growing in batch culture condition exhibit dramatically different control schemes from those growing in a chemostat. The difference is mainly due to the feedback introduced by the constraints of the chemostat. The control of the enzymes on the rates of the substrate uptake, product excretion, and cell growth and its practical implication are discussed. Clustering of the reaction steps according to the similarity of their responses to enzyme activity perturbations reveals functional coupling of metabolic reactions. [on SciFinder (R)]

Published in:
Metabolic Engineering, 8, 2, 142-159
16-8 FIELD Section Title:Fermentation and Bioindustrial Chemistry
10, 48
Department of Chemical and Biological Engineering,Northwestern University,Evanston,IL,USA. FIELD URL:
written in English.

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 Record created 2007-01-11, last modified 2018-03-17

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