Lineage correlations of single cell division time as a probe of cell-cycle dynamics
Lineage correlations of single cell division time as a probe of cell-cycle dynamics
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DOI：
10.1038/nature14318
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发表时间：
2015-03-26
期刊：
影响因子：
64.8
通讯作者：
Balaban, Nathalie Q.
中科院分区：
文献类型：
--
作者：
Sandler, Oded;Mizrahi, Sivan Pearl;Balaban, Nathalie Q.
细胞中的随机过程与mRNA（1）、蛋白质产生和降解（2，3）、分裂时细胞组分的噪声分配（4）以及其他细胞过程的波动相关。细胞克隆群体内的变异性源于这种随机过程，其可能被确定性因素放大或减少（5）。细胞间的变异性，如细菌对抗生素或癌细胞对治疗的异质性反应，被认为是随机性的必然结果。细胞周期持续时间的变异性很久以前就被观察到了;然而，其来源仍然未知。一个中心问题是，所观察到的分布的方差是否源于随机过程，或者它是否主要来自于一个只看起来是随机的确定性过程。细胞周期持续时间遗传的一个令人惊讶的特征是，它似乎在一代内丢失，但在下一代中仍然存在，导致母细胞和子细胞之间的相关性较差，但表亲细胞之间的相关性较高（6）。这一观察结果表明，存在潜在的决定性因素，决定了细胞间变异的主要部分。我们开发了一个实验系统，精确测量细胞周期的持续时间的数千个哺乳动物细胞沿着几代和一个数学框架，允许之间的歧视随机和确定性过程的细胞谱系。我们发现，代间和代内的相关性揭示了复杂的遗传细胞周期的持续时间。最后，我们建立了一个确定性的非线性玩具模型的细胞周期的继承，再现我们的数据的主要特征。我们的方法构成了一个通用的方法来识别细胞或生物体的谱系中的确定性变异，这可能有助于预测，并最终减少各种系统中的细胞间异质性，例如治疗中的癌细胞。
Stochastic processes in cells are associated with fluctuations in mRNA(1), protein production and degradation(2,3), noisy partition of cellular components at division(4), and other cell processes. Variability within a clonal population of cells originates from such stochastic processes, which may be amplified or reduced by deterministic factors(5). Cell-to-cell variability, such as that seen in the heterogeneous response of bacteria to antibiotics, or of cancer cells to treatment, is understood as the inevitable consequence of stochasticity. Variability in cell-cycle duration was observed long ago; however, its sources are still unknown. A central question is whether the variance of the observed distribution originates from stochastic processes, or whether it arises mostly from a deterministic process that only appears to be random. A surprising feature of cell-cycle-duration inheritance is that it seems to be lost within one generation but to be still present in the next generation, generating poor correlation between mother and daughter cells but high correlation between cousin cells(6). This observation suggests the existence of underlying deterministic factors that determine the main part of cell-to-cell variability. We developed an experimental system that precisely measures the cell-cycle duration of thousands of mammalian cells along several generations and a mathematical framework that allows discrimination between stochastic and deterministic processes in lineages of cells. We show that the inter-and intra-generation correlations reveal complex inheritance of the cell-cycle duration. Finally, we build a deterministic nonlinear toy model for cell-cycle inheritance that reproduces the main features of our data. Our approach constitutes a general method to identify deterministic variability in lineages of cells or organisms, which may help to predict and, eventually, reduce cell-to-cell heterogeneity in various systems, such as cancer cells under treatment.