Regulation of future RNA and protein numbers is a key process by which cells continuously best fit the environment. In bacteria, RNA and proteins exist in small numbers and their regulatory processes are stochastic. Consequently, there is cell-to-cell variability in these numbers, even between sister cells. Traditionally, the two most studied sources of this variability are gene expression and RNA and protein degradation, with evidence suggesting that the latter is subject to little regulation, when compared to the former. However, time-lapse microscopy and single molecule fluorescent tagging have produced evidence that cell division can also be a significant source of variability due to asymmetries in the partitioning of RNA and proteins. Relevantly, the impact of this noise differs from noise in production and degradation since, unlike these, it is not continuous. Rather, it occurs at specific time points, at which moment it can introduce major fluctuations. Several models have now been proposed that integrate noise from cell division, in addition to noise in gene expression, to mimic the dynamics of RNA and protein numbers of cell lineages. This is expected to be particularly relevant in genetic circuits, where significant fluctuations in one component protein, at specific time moments, are expected to perturb near-equilibrium states of the circuits, which can have long-lasting consequences. Here we review stochastic models coupling these processes in Escherichia coli, from single genes to small circuits.

调节未来RNA和蛋白质数量是细胞不断适应环境的关键过程。在细菌中，RNA和蛋白质数量很少，其调节过程是随机的。因此，即使在姐妹细胞之间，这些数目也存在细胞间差异。传统上，对这种变异性进行研究最多的两个来源是基因表达以及RNA和蛋白质降解，有证据表明，与前者相比，后者几乎不受任何调控。但是，延时显微镜和单分子荧光标记已产生证据表明，由于RNA和蛋白质分配的不对称性，细胞分裂也可能是变异的重要来源。与此相关，此噪声的影响不同于生产和降级中的噪声，因为与这些不同，它不是连续的。相反，它发生在特定的时间点，在那一刻它可能会引起重大波动。现在已经提出了几种模型，这些模型除了整合了基因表达中的噪声外，还整合了来自细胞分裂的噪声，以模仿细胞谱系中RNA和蛋白质数量的动态变化。预期这在遗传回路中尤其重要，在遗传回路中，一种成分蛋白质的特定波动在特定时刻会扰乱回路的近平衡状态，这可能会产生长期的后果。在这里，我们回顾耦合这些过程的随机模型 模仿细胞谱系中RNA和蛋白质数量的动态变化。预期这在遗传回路中特别重要，在遗传回路中，特定时间某一成分蛋白质的显着波动预计会扰乱回路的近平衡状态，这可能会产生长期的后果。在这里，我们回顾耦合这些过程的随机模型 模仿细胞谱系中RNA和蛋白质数量的动态变化。预期这在遗传回路中尤其重要，在遗传回路中，一种成分蛋白质的特定波动在特定时刻会扰乱回路的近平衡状态，这可能会产生长期的后果。在这里，我们回顾耦合这些过程的随机模型大肠杆菌，从单一基因到小型电路。