--- _id: '947' abstract: - lang: eng text: Viewing the ways a living cell can organize its metabolism as the phase space of a physical system, regulation can be seen as the ability to reduce the entropy of that space by selecting specific cellular configurations that are, in some sense, optimal. Here we quantify the amount of regulation required to control a cell's growth rate by a maximum-entropy approach to the space of underlying metabolic phenotypes, where a configuration corresponds to a metabolic flux pattern as described by genome-scale models. We link the mean growth rate achieved by a population of cells to the minimal amount of metabolic regulation needed to achieve it through a phase diagram that highlights how growth suppression can be as costly (in regulatory terms) as growth enhancement. Moreover, we provide an interpretation of the inverse temperature β controlling maximum-entropy distributions based on the underlying growth dynamics. Specifically, we show that the asymptotic value of β for a cell population can be expected to depend on (i) the carrying capacity of the environment, (ii) the initial size of the colony, and (iii) the probability distribution from which the inoculum was sampled. Results obtained for E. coli and human cells are found to be remarkably consistent with empirical evidence. article_number: '010401' article_processing_charge: No author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 - first_name: Fabrizio full_name: Capuani, Fabrizio last_name: Capuani - first_name: Andrea full_name: De Martino, Andrea last_name: De Martino citation: ama: De Martino D, Capuani F, De Martino A. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 2017;96(1). doi:10.1103/PhysRevE.96.010401 apa: De Martino, D., Capuani, F., & De Martino, A. (2017). Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.96.010401 chicago: De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2017. https://doi.org/10.1103/PhysRevE.96.010401. ieee: D. De Martino, F. Capuani, and A. De Martino, “Quantifying the entropic cost of cellular growth control,” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1. American Institute of Physics, 2017. ista: De Martino D, Capuani F, De Martino A. 2017. Quantifying the entropic cost of cellular growth control. Physical Review E Statistical Nonlinear and Soft Matter Physics . 96(1), 010401. mla: De Martino, Daniele, et al. “Quantifying the Entropic Cost of Cellular Growth Control.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 96, no. 1, 010401, American Institute of Physics, 2017, doi:10.1103/PhysRevE.96.010401. short: D. De Martino, F. Capuani, A. De Martino, Physical Review E Statistical Nonlinear and Soft Matter Physics 96 (2017). date_created: 2018-12-11T11:49:21Z date_published: 2017-07-10T00:00:00Z date_updated: 2023-09-22T10:03:50Z day: '10' department: - _id: GaTk doi: 10.1103/PhysRevE.96.010401 ec_funded: 1 external_id: isi: - '000405194200002' intvolume: ' 96' isi: 1 issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1703.00219 month: '07' oa: 1 oa_version: Submitted Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: ' Physical Review E Statistical Nonlinear and Soft Matter Physics ' publication_identifier: issn: - '24700045' publication_status: published publisher: American Institute of Physics publist_id: '6470' quality_controlled: '1' scopus_import: '1' status: public title: Quantifying the entropic cost of cellular growth control type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 96 year: '2017' ...