Chabot Jeffrey R, Pedraza Juan M, Luitel Prashant, van Oudenaarden Alexander
Department of Physics and George Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Nature. 2007 Dec 20;450(7173):1249-52. doi: 10.1038/nature06395.
Recent advances in measuring gene expression at the single-cell level have highlighted the stochastic nature of messenger RNA and protein synthesis. Stochastic gene expression creates a source of variability in the abundance of cellular components, even among isogenic cells exposed to an identical environment. Recent integrated experimental and modelling studies have shed light on the molecular sources of this variability. However, many of these studies focus on systems that have reached a steady state and therefore do not address a large class of dynamic phenomena including oscillatory gene expression. Here we develop a general protocol for analysing and predicting stochastic gene expression in systems that never reach steady states. We use this framework to analyse experimentally stochastic expression of genes driven by the Synechococcus elongatus circadian clock. We find that, although the average expression at two points in the circadian cycle separated by 12 hours is identical, the variability at these two time points can be different. We show that this is a general feature of out-of-steady-state systems. We demonstrate how intrinsic noise sources, owing to random births and deaths of mRNAs and proteins, or extrinsic noise sources, which introduce fluctuations in rate constants, affect the cell-to-cell variability. To distinguish experimentally between these sources, we measured how the correlation between expression fluctuations of two identical genes is modulated during the circadian cycle. This quantitative framework is generally applicable to any out-of-steady-state system and will be necessary for understanding the fidelity of dynamic cellular systems.
单细胞水平上基因表达测量技术的最新进展凸显了信使核糖核酸（mRNA）和蛋白质合成的随机性。随机基因表达在细胞成分丰度上产生了变异性来源，即使是在暴露于相同环境的同基因细胞之间也是如此。最近的综合实验和建模研究揭示了这种变异性的分子来源。然而，这些研究大多集中在已达到稳态的系统上，因此没有涉及包括振荡基因表达在内的一大类动态现象。在这里，我们开发了一种通用方案，用于分析和预测从未达到稳态的系统中的随机基因表达。我们使用这个框架来分析由聚球藻昼夜节律时钟驱动的基因的实验性随机表达。我们发现，尽管昼夜节律周期中相隔12小时的两个时间点的平均表达相同，但这两个时间点的变异性可能不同。我们表明，这是非稳态系统的一个普遍特征。我们展示了由于mRNA和蛋白质的随机产生和降解导致的内在噪声源，或引入速率常数波动的外在噪声源，如何影响细胞间的变异性。为了在实验中区分这些来源，我们测量了两个相同基因的表达波动之间的相关性在昼夜节律周期中是如何被调节的。这个定量框架普遍适用于任何非稳态系统，对于理解动态细胞系统的保真度将是必要的。
