Ribeiro Andre S
Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, Finland.
Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Dec;78(6 Pt 1):061902. doi: 10.1103/PhysRevE.78.061902. Epub 2008 Dec 2.
We study how cells can optimize fitness in variable environments by tuning the internal fluctuations of protein expression of a bistable genetic switch. We model cells as bistable toggle switches whose dynamics are governed by a delayed stochastic simulation algorithm. Each state of the toggle switch makes the cell more fit in one of two environmental conditions. Different noise levels in protein expression yield different fitness values for cells in an environment that randomly switches between the two conditions. We compare the behavior of two cell types, one that can sense the environmental condition and one that cannot. In fast changing environments both cell types evolve to be as noisy as possible while maintaining bistability of the toggle switch. In slowly changing environments, evolved nonsensing cells are less noisy while sensing cells evolve the same noise level as in fast changing environments. Sensing removes the need of genotypic changes to adapt to changes in the environment fluctuation rate, providing an evolutionary advantage in unpredictable environments.
我们研究细胞如何通过调节双稳态遗传开关的蛋白质表达内部波动，在可变环境中优化适应性。我们将细胞建模为双稳态触发开关，其动力学由延迟随机模拟算法控制。触发开关的每种状态都会使细胞在两种环境条件之一中更具适应性。蛋白质表达中的不同噪声水平，会为在两种条件之间随机切换的环境中的细胞产生不同的适应度值。我们比较了两种细胞类型的行为，一种能够感知环境条件，另一种则不能。在快速变化的环境中，两种细胞类型都会进化到尽可能嘈杂，同时保持触发开关的双稳态。在缓慢变化的环境中，进化出的无感知细胞噪声较小，而有感知细胞则进化到与快速变化环境中相同的噪声水平。感知消除了基因型变化以适应环境波动率变化的需求，在不可预测的环境中提供了进化优势。
