Statistical mechanics for metabolic networks during steady state growth Journal Article


Author(s): De Martino, Daniele; MC Andersson Anna; Bergmiller, Tobias; Guet, Cǎlin C; Tkačik, Gašper
Article Title: Statistical mechanics for metabolic networks during steady state growth
Affiliation IST Austria
Abstract: Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.
Journal Title: Nature Communications
Volume: 9
Issue 1
ISSN: 2041-1723
Publisher: Nature Publishing Group  
Date Published: 2018-07-30
Start Page: Article number: 2988
URL:
DOI: 10.1038/s41467-018-05417-9
Notes: We acknowledge the support of the Austrian Science Fund grant FWF P28844 (G.T.) and of the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. [291734] (D.D.M).
Open access: yes (OA journal)