Lineage-Specific Mechanisms of Cell Cycle Timing Control

项目摘要 几十年来研究动物发育和体外人类细胞培养已经产生了许多观察到的紧密联系。 细胞周期的持续时间与其身份或其后代的命运之间的相关性。这些链接 代表了一个独特的机会，了解细胞遗传程序之间的调控关系， 命运和细胞周期的调节，这两个核心问题，在研究发展，组织 体内平衡、再生和增殖性疾病如癌症。秀丽隐杆线虫 已经成为研究细胞命运调控和细胞周期控制的有力模型，这是由于其 遗传易处理性、透明体和胚胎以及定型的细胞谱系。与大多数线虫一样，C. 秀丽线虫在同一性别的每个个体中表现出完整的或固定数量的体细胞。细胞命运 因此，野生型动物可以仅根据其谱系历史来确定，我们已经开发了 广泛的工具和方法，通过3D时移显微镜自动重建。利用C. elegans 和遗传扰动，导致细胞命运与其谱系的转变，结合 自动化谱系追踪和空间转录组学方法，我们将研究的机制， 哪种细胞命运影响干细胞的细胞周期的持续时间，以及干细胞在细胞周期中的作用机制。 细胞周期的持续时间可以影响细胞命运。 本提案中描述的工作代表了一种考虑这些联系的新方法， 发展谱系追踪技术和定量方法来发现细胞结构 血统基于这种专业知识，以及我们的成像资源和与其他工具的合作， 开发人员，理论家和发育生物学家，我们将继续推进最先进的血统- 解决了后生动物发育的研究。特别是，利用我们在深度学习技术方面的进步， 在转基因仍然不可能的非模式物种中实现无标记自动谱系追踪，或 困难，我们将利用进化的方法来理解基因网络的设计原则 在早期胚胎中驱动细胞命运决定和控制细胞周期进程。在接下来的五年里，我们 将完成细胞周期时间和细胞命运之间的共同依赖性的详细表征，在C。 elegans胚胎，创建野生型和突变型C. elegans中的细胞命运模式受到干扰，并完成重建和定量分析， S. stercoralis、P. pacificus和C. angaria。从长远来看，我们计划扩大我们的 对这些物种的分子分析，从C.安加拉是一个有吸引力的模式， 细胞命运控制网络的演变及其与细胞周期调节因子的相互作用。这些见解将 对我们理解发展过程具有广泛的价值，我们将建立的资源将 便利其他人就新出现的示范系统中的各种问题开展工作。

Project Summary Decades of studying animal development and in vitro human cell culture have produced many observed tight correlations between the duration of a cell’s cycle and its identity or the fates of its progeny. These links represent a unique opportunity to understand the regulatory relationships between genetic programs of cell fate and the regulation of the cell cycle, both central questions in the study of development, tissue homeostasis, regeneration, and proliferative disorders such as cancer. The nematode Caenorhabditis elegans has been a powerful model in which to study the regulation of cell fate and cell cycle control owing to its genetic tractability, transparent body and embryo, and stereotyped cell lineage. Like most nematodes, C. elegans exhibits eutely or a fixed number of somatic cells in each individual of the same sex. Cell fate in the wild-type animal can thus be determined solely on the basis of its lineage history, for which we have developed extensive tools and approaches for automated reconstruction via 3D timelapse microscopy. Using C. elegans and genetic perturbations that result in transformations of cell fate with its lineage, in combination with automated lineage tracing and spatial transcriptomics approaches, we will investigate the mechanisms by which cell fate influences the duration of a stem cell’s cell cycle as well as the mechanisms by which the duration of a cell cycle can influence cell fate. The work described in this proposal represents a novel approach to considering these links, enabled by our development of lineage tracing technologies and quantitative approaches to discovering structure in cell lineages. Building on this expertise, as well as our imaging resources and collaborations with other tools developers, theorists, and developmental biologists, we will continue to advance the state-of-the-art in lineage- resolved studies of metazoan development. In particular, using our advances in deep learning techniques to enable label-free automated lineage tracing in non-model species in which transgenesis remains impossible or difficult, we will leverage an evolutionary approach to understanding the design principles of gene networks that drive cell fate decisions and control cell cycle progression in the early embryo. Over the next five years we will complete detailed characterizations of co-dependencies between cell cycle timing and cell fate in the C. elegans embryo, create a molecular atlas of cell fate and cell cycle regulation in wild type and mutant C. elegans where cell fate patterning is perturbed, and complete the reconstruction and quantitative analysis of the embryonic lineages of S. stercoralis, P. pacificus, and C. angaria. In the long term, we plan to extend our molecular analyses to these species as well, beginning with C. angaria as an attractive model for studying the evolution of cell fate control networks and their interactions with regulators of the cell cycle. These insights will be of broad value to our understanding of developmental processes, and the resources we will establish will facilitate the work of others on diverse problems in emerging model systems.