Paulsson J, Berg O G, Ehrenberg M
Department of Cell and Molecular Biology, Biomedical Center Box 596, SE 75124 Uppsala, Sweden.
Proc Natl Acad Sci U S A. 2000 Jun 20;97(13):7148-53. doi: 10.1073/pnas.110057697.
Many regulatory molecules are present in low copy numbers per cell so that significant random fluctuations emerge spontaneously. Because cell viability depends on precise regulation of key events, such signal noise has been thought to impose a threat that cells must carefully eliminate. However, the precision of control is also greatly affected by the regulatory mechanisms' capacity for sensitivity amplification. Here we show that even if signal noise reduces the capacity for sensitivity amplification of threshold mechanisms, the effect on realistic regulatory kinetics can be the opposite: stochastic focusing (SF). SF particularly exploits tails of probability distributions and can be formulated as conventional multistep sensitivity amplification where signal noise provides the degrees of freedom. When signal fluctuations are sufficiently rapid, effects of time correlations in signal-dependent rates are negligible and SF works just like conventional sensitivity amplification. This means that, quite counterintuitively, signal noise can reduce the uncertainty in regulated processes. SF is exemplified by standard hyperbolic inhibition, and all probability distributions for signal noise are first derived from underlying chemical master equations. The negative binomial is suggested as a paradigmatic distribution for intracellular kinetics, applicable to stochastic gene expression as well as simple systems with Michaelis-Menten degradation or positive feedback. SF resembles stochastic resonance in that noise facilitates signal detection in nonlinear systems, but stochastic resonance is related to how noise in threshold systems allows for detection of subthreshold signals and SF describes how fluctuations can make a gradual response mechanism work more like a threshold mechanism.
许多调节分子在每个细胞中的拷贝数很低,因此会自发出现显著的随机波动。由于细胞活力取决于关键事件的精确调控,这种信号噪声被认为构成了一种威胁,细胞必须小心消除。然而,控制的精度也受到调节机制的灵敏度放大能力的极大影响。在这里,我们表明,即使信号噪声降低了阈值机制的灵敏度放大能力,但对实际调节动力学的影响可能相反:随机聚焦(SF)。随机聚焦特别利用概率分布的尾部,可以被表述为传统的多步灵敏度放大,其中信号噪声提供了自由度。当信号波动足够快时,信号依赖速率中的时间相关性影响可以忽略不计,随机聚焦的作用就像传统的灵敏度放大。这意味着,与直觉相反,信号噪声可以降低调节过程中的不确定性。标准双曲线抑制就是随机聚焦的一个例子,信号噪声的所有概率分布首先从基础化学主方程推导得出。负二项分布被认为是细胞内动力学的典型分布,适用于随机基因表达以及具有米氏降解或正反馈的简单系统。随机聚焦类似于随机共振,即噪声有助于非线性系统中的信号检测,但随机共振涉及阈值系统中的噪声如何允许检测亚阈值信号,而随机聚焦描述了波动如何使渐进响应机制更像阈值机制那样工作。