A generic mechanism for adaptive growth rate regulation

PLoS Computational Biology
Chikara Furusawa, Kunihiko Kaneko

Abstract

How can a microorganism adapt to a variety of environmental conditions despite the existence of a limited number of signal transduction mechanisms? We show that for any growing cells whose gene expression fluctuate stochastically, the adaptive cellular state is inevitably selected by noise, even without a specific signal transduction network for it. In general, changes in protein concentration in a cell are given by its synthesis minus dilution and degradation, both of which are proportional to the rate of cell growth. In an adaptive state with a higher growth speed, both terms are large and balanced. Under the presence of noise in gene expression, the adaptive state is less affected by stochasticity since both the synthesis and dilution terms are large, while for a nonadaptive state both the terms are smaller so that cells are easily kicked out of the original state by noise. Hence, escape time from a cellular state and the cellular growth rate are negatively correlated. This leads to a selection of adaptive states with higher growth rates, and model simulations confirm this selection to take place in general. The results suggest a general form of adaptation that has never been brought to light--a process that requires no spec...Continue Reading

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Citations

Apr 23, 2008·Theory in Biosciences = Theorie in Den Biowissenschaften·Kunihiko Kaneko, Chikara Furusawa
May 15, 2013·PloS One·Chikara Furusawa, Kunihiko Kaneko
Apr 18, 2013·PLoS Computational Biology·Masayo Inoue, Kunihiko Kaneko
Jul 8, 2008·Chaos·Kunihiko Kaneko
Jun 24, 2011·PloS One·Elad Stolovicki, Erez Braun
Apr 22, 2017·Nature Communications·Hallel I SchreierNaama Brenner
Dec 3, 2008·IET Systems Biology·K Kaneko, C Furusawa
Jul 2, 2008·Nature Reviews. Genetics·Luis López-MauryJürg Bähler
Sep 29, 2018·Physical Review Letters·Yoshiya J Matsubara, Kunihiko Kaneko
Jan 18, 2020·Scientific Reports·Yusuke Himeoka, Kunihiko Kaneko
Jul 1, 2020·PLoS Computational Biology·Shintaro Nagata, Macoto Kikuchi
Nov 7, 2014·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Yusuke Himeoka, Kunihiko Kaneko
Jul 25, 2019··Eduard BrokanFelix Sadyrbaev

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