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PLoS Comput Biol. 2016 Mar 24;12(3):e1004825. doi: 10.1371/journal.pcbi.1004825. eCollection 2016 Mar.

Cellular Growth Arrest and Persistence from Enzyme Saturation.

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The University of Texas MD Anderson Cancer Center, Department of Systems Biology, Houston, Texas, United States of America.
Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.
Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America.
SASTRA University, Tirumalaisamudram, Tamil Nadu, India.
Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America.
Laufer Center for Physical & Quantitative Biology and Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, United States of America.


Metabolic efficiency depends on the balance between supply and demand of metabolites, which is sensitive to environmental and physiological fluctuations, or noise, causing shortages or surpluses in the metabolic pipeline. How cells can reliably optimize biomass production in the presence of metabolic fluctuations is a fundamental question that has not been fully answered. Here we use mathematical models to predict that enzyme saturation creates distinct regimes of cellular growth, including a phase of growth arrest resulting from toxicity of the metabolic process. Noise can drive entry of single cells into growth arrest while a fast-growing majority sustains the population. We confirmed these predictions by measuring the growth dynamics of Escherichia coli utilizing lactose as a sole carbon source. The predicted heterogeneous growth emerged at high lactose concentrations, and was associated with cell death and production of antibiotic-tolerant persister cells. These results suggest how metabolic networks may balance costs and benefits, with important implications for drug tolerance.

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