标题： 分解生化信号系统中的噪声 突显了蛋白质降解的作用 显示英文标题

标题： Decomposing Noise in Biochemical Signalling Systems Highlights the Role of Protein Degradation

摘要： 生化过程中的随机性现象在过去几十年中一直吸引着生命科学家。我们现在知道，活细胞在某些情况下利用随机性，在其他情况下则对抗随机效应。生物分子系统中内在随机性的来源是单个反应的随机时间，这些时间累积驱动了此类系统输出的变异性。尽管随机性在活细胞功能中的重要性已被认可，但尚未提出一种严格的方法来精确识别变异的来源。在本文中，我们提出了一种新方法，使我们能够计算单个反应对系统输出变异的贡献。我们证明了一些反应对噪声的影响与其他反应有显著不同。令人惊讶的是，在作为信号转导近似模型的开放转换系统类别中，输出的降解贡献了总噪声的一半。我们还证明了降解在其他相关系统中的重要性，并提出了一种具有有效噪声抑制能力的降解反馈控制机制。将我们的方法应用于一些广泛研究的生化系统，如基因表达、米氏酶动力学和p53系统，表明我们的方法揭示了生化系统中变异起源的前所未有的见解。对于许多系统，解析分解不可用；因此该方法已作为Matlab包实现，并可根据要求从作者处获得。 显示英文摘要

摘要： The phenomena of stochasticity in biochemical processes have been intriguing life scientists for the past few decades. We now know that living cells take advantage of stochasticity in some cases and counteract stochastic effects in others. The source of intrinsic stochasticity in biomolecular systems are random timings of individual reactions, which cumulatively drive the variability in outputs of such systems. Despite the acknowledged relevance of stochasticity in the functioning of living cells no rigorous method have been proposed to precisely identify sources of variability. In this paper we propose a novel methodology that allows us to calculate contributions of individual reactions into the variability of a system's output. We demonstrate that some reactions have dramatically different effects on noise than others. Surprisingly, in the class of open conversion systems that serve as an approximate model of signal transduction, the degradation of an output contributes half of the total noise. We also demonstrate the importance of degradation in other relevant systems and propose a degradation feedback control mechanism that has the capability of an effective noise suppression. Application of our method to some well studied biochemical systems such as: gene expression, Michaelis-Menten enzyme kinetics, and the p53 system indicates that our methodology reveals an unprecedented insight into the origins of variability in biochemical systems. For many systems an analytical decomposition is not available; therefore the method has been implemented as a Matlab package and is available from the authors upon request.