Statistical mechanics for metabolic networks during steady state growth

Single cell growth rate variability has been difficult to understand. Here, the authors apply a generalization of flux balance analysis to single cells based on maximum entropy modeling, and find that growth rate fluctuations of E. coli reflect metabolic flux variability and growth sub-optimality, i...

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Autores principales:	Daniele De Martino, Anna MC Andersson, Tobias Bergmiller, Călin C. Guet, Gašper Tkačik
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/047a842e2a584521b3b1c31d7ce5b03a
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spelling	oai:doaj.org-article:047a842e2a584521b3b1c31d7ce5b03a2021-12-02T15:34:26ZStatistical mechanics for metabolic networks during steady state growth10.1038/s41467-018-05417-92041-1723https://doaj.org/article/047a842e2a584521b3b1c31d7ce5b03a2018-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-05417-9https://doaj.org/toc/2041-1723Single cell growth rate variability has been difficult to understand. Here, the authors apply a generalization of flux balance analysis to single cells based on maximum entropy modeling, and find that growth rate fluctuations of E. coli reflect metabolic flux variability and growth sub-optimality, in turn highlighting information costs for growth optimization.Daniele De MartinoAnna MC AnderssonTobias BergmillerCălin C. GuetGašper TkačikNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-9 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Daniele De Martino Anna MC Andersson Tobias Bergmiller Călin C. Guet Gašper Tkačik Statistical mechanics for metabolic networks during steady state growth
description	Single cell growth rate variability has been difficult to understand. Here, the authors apply a generalization of flux balance analysis to single cells based on maximum entropy modeling, and find that growth rate fluctuations of E. coli reflect metabolic flux variability and growth sub-optimality, in turn highlighting information costs for growth optimization.
format	article
author	Daniele De Martino Anna MC Andersson Tobias Bergmiller Călin C. Guet Gašper Tkačik
author_facet	Daniele De Martino Anna MC Andersson Tobias Bergmiller Călin C. Guet Gašper Tkačik
author_sort	Daniele De Martino
title	Statistical mechanics for metabolic networks during steady state growth
title_short	Statistical mechanics for metabolic networks during steady state growth
title_full	Statistical mechanics for metabolic networks during steady state growth
title_fullStr	Statistical mechanics for metabolic networks during steady state growth
title_full_unstemmed	Statistical mechanics for metabolic networks during steady state growth
title_sort	statistical mechanics for metabolic networks during steady state growth
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/047a842e2a584521b3b1c31d7ce5b03a
work_keys_str_mv	AT danieledemartino statisticalmechanicsformetabolicnetworksduringsteadystategrowth AT annamcandersson statisticalmechanicsformetabolicnetworksduringsteadystategrowth AT tobiasbergmiller statisticalmechanicsformetabolicnetworksduringsteadystategrowth AT calincguet statisticalmechanicsformetabolicnetworksduringsteadystategrowth AT gaspertkacik statisticalmechanicsformetabolicnetworksduringsteadystategrowth
_version_	1718386820080730112

Statistical mechanics for metabolic networks during steady state growth

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