---
_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'
...