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Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities.

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons50384

Klipp,  Edda
Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Klipp, E., Heinrich, R., & Holzhütter, H.-G. (2002). Prediction of temporal gene expression. Metabolic opimization by re-distribution of enzyme activities. European Journal of Biochemistry, 269(22), 1432-1033.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-8B73-4
Abstract
A computational approach is used to analyse temporal gene expression in the context of metabolic regulation. It is based on the assumption that cells developed optimal adaptation strategies to changing environmental conditions. Time-dependent enzyme profiles are calculated which optimize the function of a metabolic pathway under the constraint of limited total enzyme amount. For linear model pathways it is shown that wave-like enzyme profiles are optimal for a rapid substrate turnover. For the central metabolism of yeast cells enzyme profiles are calculated which ensure long-term homeostasis of key metabolites under conditions of a diauxic shift. These enzyme profiles are in close correlation with observed gene expression data. Our results demonstrate that optimality principles help to rationalize observed gene expression profiles.