Kedziora Katarzyna M, Stallaert Wayne
Department of Cell Biology, Center for Biologic Imaging (CBI), University of Pittsburgh, Pittsburgh, PA, USA.
Department of Computational and Systems Biology, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA.
Methods Mol Biol. 2024;2740:243-262. doi: 10.1007/978-1-0716-3557-5_15.
The development of technologies that allow measurement of the cell cycle at the single-cell level has revealed novel insights into the mechanisms that regulate cell cycle commitment and progression through DNA replication and cell division. These studies have also provided evidence of heterogeneity in cell cycle regulation among individual cells, even within a genetically identical population. Cell cycle mapping combines highly multiplexed imaging with manifold learning to visualize the diversity of "paths" that cells can take through the proliferative cell cycle or into various states of cell cycle arrest. In this chapter, we describe a general protocol of the experimental and computational components of cell cycle mapping. We also provide a comprehensive guide for the design and analysis of experiments, discussing key considerations in detail (e.g., antibody library preparation, analysis strategies, etc.) that may vary depending on the research question being addressed.
能够在单细胞水平上测量细胞周期的技术发展,揭示了调控细胞周期进入以及通过DNA复制和细胞分裂进行进程的机制的新见解。这些研究还提供了证据,表明即使在基因相同的群体中,单个细胞之间在细胞周期调控方面也存在异质性。细胞周期图谱结合了高度多重成像和流形学习,以可视化细胞在增殖细胞周期中或进入细胞周期停滞的各种状态时可以采取的“路径”的多样性。在本章中,我们描述了细胞周期图谱实验和计算组件的一般方案。我们还提供了实验设计和分析的全面指南,详细讨论了可能因所解决的研究问题而异的关键考虑因素(例如抗体文库制备、分析策略等)。