CycleFlow simultaneously quantifies cell-cycle phase lengths and quiescence in vivo.
CycleFlow simultaneously quantifies cell-cycle phase lengths and quiescence in vivo.
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DOI：
10.1016/j.crmeth.2022.100315
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发表时间：
2022-10-24
期刊：
影响因子：
--
通讯作者：
Höfer T
中科院分区：
文献类型：
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作者：
Jolly A;Fanti AK;Kongsaysak-Lengyel C;Claudino N;Gräßer I;Becker NB;Höfer T
干细胞、祖细胞或癌细胞群体在体内显示出增殖异质性，包括增殖和静止细胞。静止亚群和增殖细胞在细胞周期各个阶段的进展的一致定量尚未实现。在这里，我们描述CycleFlow，一种方法，该方法从标准的脉冲追踪实验与胸苷类似物有力地推断出这一全面的信息。推断是基于细胞周期的数学模型，与现实的等待时间分布的G1，S和G2/M阶段和长期静止G 0状态。我们在体外用指数生长的癌细胞系验证CycleFlow。将其应用于体内稳态的T祖细胞，我们发现了强烈的增殖异质性，少数CD 4 + CD 8 + T祖细胞非常快速地循环，然后进入静止期。CycleFlow适合作为定量细胞周期分析的常规方法。CycleFlow定量静止和细胞周期在异质群体在体内CycleFlow结合脉冲追逐与胸腺嘧啶核苷类似物与数学推理会计实验的不确定性产生强大的估计细胞周期参数应用T细胞发育定量胸腺细胞静止测定细胞周期与胸腺嘧啶核苷类似物在体内是一个标准的方法。然而，感兴趣的细胞群通常是异质的，由周期和静止细胞的亚群组成。因此，正确测定细胞周期持续时间需要同时评估静止分数。在这里，我们表明，一个简单的扩展标准的脉冲追逐协议，与一个单一的胸苷类似物，允许准确测定的静止细胞分数和细胞周期阶段的持续时间在增殖亚群。我们的方法CycleFlow依赖于在追踪过程中的几个时间点进行测量，并使用细胞周期的现实数学模型解释数据。CycleFlow在面对典型的实验不确定性来源时产生了对细胞周期特征的稳健估计。细胞在循环和静止之间的转换是发育、组织稳态和免疫反应的基本过程。乔利等人描述了一种广泛适用的方法，该方法将胸苷类似物标记与基于模型的推断相结合，以解开并量化静止和周期定时。
Populations of stem, progenitor, or cancer cells show proliferative heterogeneity in vivo, comprising proliferating and quiescent cells. Consistent quantification of the quiescent subpopulation and progression of the proliferating cells through the individual phases of the cell cycle has not been achieved. Here, we describe CycleFlow, a method that robustly infers this comprehensive information from standard pulse-chase experiments with thymidine analogs. Inference is based on a mathematical model of the cell cycle, with realistic waiting time distributions for the G1, S, and G2/M phases and a long-term quiescent G0 state. We validate CycleFlow with an exponentially growing cancer cell line in vitro. Applying it to T cell progenitors in steady state in vivo, we uncover strong proliferative heterogeneity, with a minority of CD4+CD8+ T cell progenitors cycling very rapidly and then entering quiescence. CycleFlow is suitable as a routine method for quantitative cell-cycle analysis. CycleFlow quantifies quiescence and cell cycling in heterogeneous populations in vivo CycleFlow combines pulse chase with a thymidine analog with mathematical inference Accounting for experimental uncertainty yields robust estimates of cell-cycle parameters Application to T cell development quantifies thymocyte quiescence Assaying cell cycling with thymidine analogs in vivo is a standard method. However, the cell populations of interest are often heterogeneous, consisting of subpopulations of cycling and quiescent cells. Hence, the correct determination of the cell-cycle duration requires the simultaneous assessment of the quiescent fraction. Here, we show that a straightforward extension of the standard pulse-chase protocol, with a single thymidine analog, allows accurate determination of the quiescent cell fraction and of the cell-cycle phase durations in the proliferating subpopulation. Our method, CycleFlow, relies on measuring at several time points during the chase and interpreting the data with a realistic mathematical model of the cell cycle. CycleFlow yields robust estimates of the cell-cycle characteristics in the face of typical sources of experimental uncertainty. The switching of cells between cycling and quiescence is a fundamental process in development, tissue homeostasis, and immune responses. Jolly et al. describe a broadly applicable method that combines thymidine-analog labeling with model-based inference to disentangle and quantify quiescence and cycle timing.