Characterizing stochastic cell-cycle dynamics in exponential growth.
Characterizing stochastic cell-cycle dynamics in exponential growth.
复制标题
表征指数生长中随机细胞周期动力学。
DOI：
10.1103/physreve.105.014420
复制
发表时间：
2022-01
影响因子：
2.4
通讯作者：
Wiggins, Paul A.
中科院分区：
文献类型：
--
作者：
Huang, Dean;Lo, Teresa;Merrikh, Houra;Wiggins, Paul A.
两种强大且互补的实验方法通常用于研究细胞周期和细胞生物学：一类实验表征不同步指数增长群体的统计数据（或人口统计），而另一类实验通过完整细胞周期的延时成像或同步群体的批量实验来捕获细胞周期动态。在本文中，我们研究了这两种不同实验方法中观察结果之间的微妙关系。我们从现有模型开始：细胞周期动力学的单细胞确定性描述，其中细胞状态（即周期或阶段）具有精确的寿命。然后，我们将此描述推广到随机模型，其中状态具有随机寿命，如任意概率分布函数所描述。我们对指数文化人口统计的分析揭示了确定性模型和随机模型之间简单而精确的对应关系：确定性模型中相应的状态年龄等于随机模型中年龄的指数平均值。因此，一个重要的含义是，即使状态时间是随机的，指数文化的人口统计数据也将非常适合确定性模型。尽管我们探索了这些模型在大肠杆菌细胞周期中的含义，但我们期望这些模型以及指数平均寿命的重要性能够在其他生物系统中细胞周期动力学的定量分析中找到许多应用。
Two powerful and complementary experimental approaches are commonly used to study the cell cycle and cell biology: One class of experiments characterizes the statistics (or demographics) of an unsynchronized exponentially-growing population, while the other captures cell cycle dynamics, either by time-lapse imaging of full cell cycles or in bulk experiments on synchronized populations. In this paper, we study the subtle relationship between observations in these two distinct experimental approaches. We begin with an existing model: a single-cell deterministic description of cell cycle dynamics where cell states (i.e. periods or phases) have precise lifetimes. We then generalize this description to a stochastic model in which the states have stochastic lifetimes, as described by arbitrary probability distribution functions. Our analyses of the demographics of an exponential culture reveal a simple and exact correspondence between the deterministic and stochastic models: The corresponding state ages in the deterministic model are equal to the exponential mean of the age in the stochastic model. An important implication is therefore that the demographics of an exponential culture will be well-fit by a deterministic model even if the state timing is stochastic. Although we explore the implications of the models in the context of the Escherichia coli cell cycle, we expect both the models as well as the significance of the exponential-mean lifetimes to find many applications in the quantitative analysis of cell cycle dynamics in other biological systems.