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Nature. 2017 Nov 2;551(7678):119-123. doi: 10.1038/nature24299. Epub 2017 Oct 25.

A global resource allocation strategy governs growth transition kinetics of Escherichia coli.

Author information

1
Department of Physics, University of California San Diego, La Jolla, California 92093, USA.
2
Physics of Complex Biosystems, Physics Department, Technical University of Munich, 85748 Garching, Germany.
3
Department of Integrative Structural and Computational Biology, Department of Chemistry, The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, California 92037, USA.

Abstract

A grand challenge of systems biology is to predict the kinetic responses of living systems to perturbations starting from the underlying molecular interactions. Changes in the nutrient environment have long been used to study regulation and adaptation phenomena in microorganisms and they remain a topic of active investigation. Although much is known about the molecular interactions that govern the regulation of key metabolic processes in response to applied perturbations, they are insufficiently quantified for predictive bottom-up modelling. Here we develop a top-down approach, expanding the recently established coarse-grained proteome allocation models from steady-state growth into the kinetic regime. Using only qualitative knowledge of the underlying regulatory processes and imposing the condition of flux balance, we derive a quantitative model of bacterial growth transitions that is independent of inaccessible kinetic parameters. The resulting flux-controlled regulation model accurately predicts the time course of gene expression and biomass accumulation in response to carbon upshifts and downshifts (for example, diauxic shifts) without adjustable parameters. As predicted by the model and validated by quantitative proteomics, cells exhibit suboptimal recovery kinetics in response to nutrient shifts owing to a rigid strategy of protein synthesis allocation, which is not directed towards alleviating specific metabolic bottlenecks. Our approach does not rely on kinetic parameters, and therefore points to a theoretical framework for describing a broad range of such kinetic processes without detailed knowledge of the underlying biochemical reactions.

PMID:
29072300
PMCID:
PMC5901684
DOI:
10.1038/nature24299
[Indexed for MEDLINE]
Free PMC Article

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