Department of Bioengineering, University of Washington, William H. Foege Building, Box 355061, Seattle, Washington 98195, USA.
J Chem Phys. 2013 Oct 14;139(14):144108. doi: 10.1063/1.4822103.
Single-cell studies often show significant phenotypic variability due to the stochastic nature of intra-cellular biochemical reactions. When the numbers of molecules, e.g., transcription factors and regulatory enzymes, are in low abundance, fluctuations in biochemical activities become significant and such "noise" can propagate through regulatory cascades in terms of biochemical reaction networks. Here we develop an intuitive, yet fully quantitative method for analyzing how noise affects cellular phenotypes based on identifying a system's nonlinearities and noise propagations. We observe that such noise can simultaneously enhance sensitivities in one behavioral region while reducing sensitivities in another. Employing this novel phenomenon we designed three biochemical signal processing modules: (a) A gene regulatory network that acts as a concentration detector with both enhanced amplitude and sensitivity. (b) A non-cooperative positive feedback system, with a graded dose-response in the deterministic case, that serves as a bistable switch due to noise-induced ultra-sensitivity. (c) A noise-induced linear amplifier for gene regulation that requires no feedback. The methods developed in the present work allow one to understand and engineer nonlinear biochemical signal processors based on fluctuation-induced phenotypes.
单细胞研究经常由于细胞内生化反应的随机性而表现出显著的表型可变性。当分子数量（例如转录因子和调节酶）较少时，生化活性的波动变得显著，并且这种“噪声”可以在生化反应网络的调控级联中传播。在这里，我们开发了一种直观的、完全定量的方法，用于根据识别系统的非线性和噪声传播来分析噪声如何影响细胞表型。我们观察到，这种噪声可以同时增强一个行为区域的敏感性，同时降低另一个行为区域的敏感性。利用这一新颖现象，我们设计了三个生化信号处理模块：（a）基因调控网络，作为具有增强幅度和灵敏度的浓度检测器。（b）非合作正反馈系统，在确定性情况下具有分级剂量反应，但由于噪声诱导的超敏性而成为双稳态开关。（c）用于基因调控的噪声诱导线性放大器，不需要反馈。本工作中开发的方法允许人们根据波动诱导的表型来理解和设计非线性生化信号处理器。
