1st International ICST Workshop on Technologies for Ambient Information Society

Research Article

A noise-driven mechanism for adaptive growth rate regulation

  • @INPROCEEDINGS{10.4108/ICST.BIONETICS2008.4722,
        author={Chikara Furusawa and Kunihiko Kaneko and HIroshi Shimizu},
        title={A noise-driven mechanism for adaptive growth rate regulation},
        proceedings={1st International ICST Workshop on Technologies for Ambient Information Society},
        publisher={ACM},
        proceedings_a={TAIS},
        year={2010},
        month={5},
        keywords={Gene Network Noise Growth Rate Regulation},
        doi={10.4108/ICST.BIONETICS2008.4722}
    }
    
  • Chikara Furusawa
    Kunihiko Kaneko
    HIroshi Shimizu
    Year: 2010
    A noise-driven mechanism for adaptive growth rate regulation
    TAIS
    ICST
    DOI: 10.4108/ICST.BIONETICS2008.4722
Chikara Furusawa1,2,*, Kunihiko Kaneko3,4,*, HIroshi Shimizu1,*
  • 1: Department of Bioinformatic Engineering, Osaka University, 2-1 Yamadaoka, Suita Osaka 565-0871, Japan
  • 2: Complex Systems Biology Project, ERATO, JST 2-1 Yamadaoka, Suita Osaka 565-0871, Japan
  • 3: Department of Pure and Applied Sciences Univ. of Tokyo
  • 4: Complex Systems Biology Project, ERATO, JST Komaba, Meguro-ku Tokyo 153-8902, Japan
*Contact email: furusawa@ist.osaka-u.ac.jp, kaneko@complex.c.u-tokyo._ac.jp, shimizu@ist.osaka-u.ac.jp

Abstract

How can a microorganism adapt to a variety of environmental conditions despite there exists a limited number of signal transduction mechanisms? We show that for any growing cells whose gene expression fluctuate stochastically, adaptive cellular state is inevitably selected by noise, even without 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 non-adaptive 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 specific mechanisms for sensory adaptation. The result here provides a clue to understand flexible adaptation process in a cell, and also may provide a novel control mechanism useful in the field of engineering.