Furusawa Chikara, Kaneko Kunihiko
Department of Bioinformatics Engineering, Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan.
PLoS Comput Biol. 2008 Jan;4(1):e3. doi: 10.1371/journal.pcbi.0040003.
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 specific mechanisms for sensory adaptation. The present scheme may help explain a wide range of cellular adaptive responses including the metabolic flux optimization for maximal cell growth.
尽管信号转导机制数量有限,微生物如何适应各种环境条件?我们表明,对于任何基因表达随机波动的生长细胞,即使没有特定的信号转导网络,适应性细胞状态也不可避免地由噪声选择。一般来说,细胞中蛋白质浓度的变化由其合成量减去稀释量和降解量给出,这两者都与细胞生长速率成正比。在具有较高生长速度的适应状态下,这两个项都很大且平衡。在基因表达存在噪声的情况下,适应状态受随机性的影响较小,因为合成项和稀释项都很大,而对于非适应状态,这两个项都较小,因此细胞很容易被噪声踢出原始状态。因此,从细胞状态逃逸的时间与细胞生长速率呈负相关。这导致选择具有较高生长速率的适应状态,模型模拟证实这种选择通常会发生。结果表明了一种从未被揭示的一般适应形式——一个不需要特定感觉适应机制的过程。目前的方案可能有助于解释广泛的细胞适应性反应,包括为实现最大细胞生长而进行的代谢通量优化。