Identifying sources of variation and the flow of information in biochemical networks
Identifying sources of variation and the flow of information in biochemical networks
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DOI：
10.1073/pnas.1119407109
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发表时间：
2012-05-15
影响因子：
11.1
通讯作者：
Swain, Peter S.
中科院分区：
文献类型：
--
作者：
Bowsher, Clive G.;Swain, Peter S.
为了理解细胞如何控制和利用生化波动，我们必须确定随机性的来源，量化它们的影响，并区分信息变异和混杂的“噪音”。“我们提出了一种分析，允许生化网络的波动被分解为多个组件，为实验报告者的设计提供了测量所有组件的条件，并提供了一种技术来预测模型中这些组件的大小。此外，我们确定了一个特定的组成部分的变化，可用于量化的信息流通过生化网络的功效。通过将我们的方法应用于酵母中的渗透传感，我们可以预测野生型酵母所经历的不同渗透条件的概率，并表明如果我们包括响应于细胞环境而产生的变化，则大多数变化可以是信息性的。我们的研究结果是量化变异来源的基础，因此是理解生物“设计”的一种手段。"
To understand how cells control and exploit biochemical fluctuations, we must identify the sources of stochasticity, quantify their effects, and distinguish informative variation from confounding "noise." We present an analysis that allows fluctuations of biochemical networks to be decomposed into multiple components, gives conditions for the design of experimental reporters to measure all components, and provides a technique to predict the magnitude of these components from models. Further, we identify a particular component of variation that can be used to quantify the efficacy of information flow through a biochemical network. By applying our approach to osmosensing in yeast, we can predict the probability of the different osmotic conditions experienced by wild-type yeast and show that the majority of variation can be informational if we include variation generated in response to the cellular environment. Our results are fundamental to quantifying sources of variation and thus are a means to understand biological "design."