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...

Full description

Saved in:
Bibliographic Details
Main Authors: Daniele De Martino, Anna MC Andersson, Tobias Bergmiller, Călin C. Guet, Gašper Tkačik
Format: article
Language:EN
Published: Nature Portfolio 2018
Subjects:
Q
Online Access:https://doaj.org/article/047a842e2a584521b3b1c31d7ce5b03a
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.