Dynamic optimization of metabolic networks coupled with gene expression

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Title: Dynamic optimization of metabolic networks coupled with gene expression
Author(s): Waldherr, S
Oyarzun, DA
Bockmayr, A
Item Type: Journal Article
Abstract: The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle.
Publication Date: 6-Nov-2014
Date of Acceptance: 27-Oct-2014
URI: http://hdl.handle.net/10044/1/21664
DOI: https://dx.doi.org/10.1016/j.jtbi.2014.10.035
ISSN: 1095-8541
Publisher: Elsevier
Start Page: 469
End Page: 485
Journal / Book Title: Journal of Theoretical Biology
Volume: 365
Copyright Statement: © 2014, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Publication Status: Published
Appears in Collections:Mathematics
Applied Mathematics and Mathematical Physics



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