Dixon Julie C, Frick Christopher L, Leveille Chantelle L, Garrison Philip, Lee Peyton A, Mogre Saurabh S, Morris Benjamin, Nivedita Nivedita, Vasan Ritvik, Chen Jianxu, Fraser Cameron L, Gamlin Clare R, Harris Leigh K, Hendershott Melissa C, Johnson Graham T, Klein Kyle N, Oluoch Sandra A, Thirstrup Derek J, Sluzewski M Filip, Wilhelm Lyndsay, Yang Ruian, Toloudis Daniel M, Viana Matheus P, Theriot Julie A, Rafelski Susanne M
Allen Institute for Cell Science, 615 Westlake Ave N, Seattle, WA 98109, USA.
Department of Biology and Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
Cell Syst. 2025 May 21;16(5):101265. doi: 10.1016/j.cels.2025.101265. Epub 2025 May 1.
To investigate how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we performed a data-driven analysis of nuclear growth variations in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days and developed open-source tools for image and data analysis and feature-based timelapse data exploration. Together, these data, tools, and workflows comprise a framework for systematic quantitative analysis of dynamics at individual and population levels, and the analysis further highlights important aspects to consider when interpreting timelapse data. We found that individual nuclear volume growth trajectories arise from short-timescale variations attributable to their spatiotemporal context within the colony. We identified a time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.
为了研究在一群相同的健康细胞中细胞变异是如何在时空尺度上产生的，我们对人诱导多能干细胞集落中的核生长变异进行了数据驱动分析，以此作为一个模型系统。我们生成了一个包含数千个细胞核在多天内的三维延时数据集，并开发了用于图像和数据分析以及基于特征的延时数据探索的开源工具。这些数据、工具和工作流程共同构成了一个用于在个体和群体水平上对动力学进行系统定量分析的框架，并且该分析进一步突出了在解释延时数据时需要考虑的重要方面。我们发现，单个细胞核体积生长轨迹源于其在集落中的时空背景所导致的短时间尺度变异。我们确定了群体中核生长持续时间和起始体积之间的时间不变体积补偿关系。值得注意的是，我们发现遗传在决定这两个关键的核生长特征方面起着至关重要的作用，而其他生长特征则由其时空背景决定且不具有遗传性。
