Jia Chen, Singh Abhyudai, Grima Ramon
Applied and Computational Mathematics Division, Beijing Computational Science Research Center, Beijing 100193, China.
Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.
iScience. 2021 Feb 24;24(3):102220. doi: 10.1016/j.isci.2021.102220. eCollection 2021 Mar 19.
Recent advances in single-cell technologies have enabled time-resolved measurements of the cell size over several cell cycles. These data encode information on how cells correct size aberrations so that they do not grow abnormally large or small. Here, we formulate a piecewise deterministic Markov model describing the evolution of the cell size over many generations, for all three cell size homeostasis strategies (timer, sizer, and adder). The model is solved to obtain an analytical expression for the non-Gaussian cell size distribution in a cell lineage; the theory is used to understand how the shape of the distribution is influenced by the parameters controlling the dynamics of the cell cycle and by the choice of cell tracking protocol. The theoretical cell size distribution is found to provide an excellent match to the experimental cell size distribution of lineage data collected under various growth conditions.
单细胞技术的最新进展使得在多个细胞周期内对细胞大小进行时间分辨测量成为可能。这些数据编码了有关细胞如何校正大小偏差的信息，从而使它们不会生长得异常大或小。在这里，我们为所有三种细胞大小稳态策略（定时器、尺寸器和加法器）制定了一个分段确定性马尔可夫模型，描述细胞大小在许多代中的演变。求解该模型以获得细胞谱系中非高斯细胞大小分布的解析表达式；该理论用于理解分布形状如何受到控制细胞周期动态的参数以及细胞跟踪协议选择的影响。发现理论细胞大小分布与在各种生长条件下收集的谱系数据的实验细胞大小分布非常匹配。
