Building a Systematic, Comprehensive Mammalian Cell Fate Map

构建系统、全面的哺乳动物细胞命运图谱

• 批准号: 10473094
• 负责人: Michelle Chan
• 金额: $ 143.88万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10473094
• 关键词: Address; Age; Biological; CRISPR/Cas technology; Catalogs; Cell Therapy; Cells; Clustered Regularly Interspaced Short Palindromic Repeats; Complex; Data; Data Analyses; Data Set; Development; Diabetes Mellitus; Embryonic Development; Future; Genetic; In Vitro; Link; Mammalian Cell; Mammals; Maps; Modeling; Mus; Muscle; Neurons; Organ; Parkinson Disease; Pathway interactions; Population; Process; Property; Protocols documentation; Recording of previous events; Resolution; Spinal cord injury; Structure; Techniques; Technology; Tissues; base; cell type; computer infrastructure; cost effective; embryonic stem cell; experimental study; genome editing; in vitro Model; innovation; mammalian genome; markov model; model design; mouse development; pluripotency; repaired; single-cell RNA sequencing; stem; stem cells; tool; transcriptome

PROJECT SUMMARY Cell fate maps are immensely powerful. They illuminate the pathways of differentiation and showcase the dynamics of and coordination by cells to achieve complex biological structures. Accordingly, a sufficiently high- resolution fate map of mammalian development would function as a guide to investigate factors that direct these processes, and serve as an invaluable tool to generate and evaluate in vitro models and design cellular therapies. The need for cellular therapies, including agents that might replace or repair damaged tissue or organs, are becoming more urgent as the population ages. Until recently, lineage tracing in mammals relied on techniques with limited precision, scope, and ability for new discovery. It is not surprisingly then that fundamental questions, such as how cells move from pluripotency to more restricted cells types, remain opaque. This project aims to address those questions by building a comprehensive catalogue of mammalian differentiation. Leveraging recent innovations in single-cell RNA-sequencing and mammalian genome editing using CRISPR-Cas9, this project seeks to establish a systematic, evolving lineage tracing platform capable of recording mammalian processes. Simultaneous capture of single cell transcriptomes along with lineage information facilitates the ability to link a cell’s current state with a piece of its history. An essential component to this technology is a complementary computational infrastructure for processing and analyzing data. To find differentiation pathways stemming from pluripotency, the lineage tracing platform will be applied to an in vitro model of mouse development, gastruloids. Gastruloids form from the aggregation of mouse embryonic stem cells and faithfully mimic many features of mammalian embryogenesis. Moreover, gastruloids are a well- defined, tractable model enabling higher throughput studies in a cost-effective manner. To interpret data produced from the lineage tracing experiments, a hidden Markov model is proposed to integrate information across data sets and identify differentiation trajectories. Importantly, multiple trajectories may be discovered for a given cell type showcasing the unbiased, data driven property of this technology. Finally, the modes by which the lineage tracing platform may be used to identify genetic regulators and to inform cell type manipulation in vitro are discussed.

项目摘要 细胞命运图非常强大。它们阐明了分化的途径，并展示了 细胞的动力学和协调以实现复杂的生物结构。因此，一个足够高的- 哺乳动物发育的分辨率命运图将作为指导，以调查的因素， 这些过程，并作为一个宝贵的工具，以产生和评估在体外模型和设计细胞 治疗对细胞疗法的需求，包括可能替代或修复受损组织或 器官，随着人口老龄化变得更加紧迫。直到最近，哺乳动物的谱系追踪依赖于 在有限的精度，范围和新发现的能力的技术。因此， 一些基本问题，如细胞如何从多能性转变为更有限的细胞类型， 不透明该项目旨在通过建立一个全面的哺乳动物目录来解决这些问题。 分化利用单细胞RNA测序和哺乳动物基因组编辑的最新创新 利用CRISPR-Cas9，该项目旨在建立一个系统的，不断发展的谱系追踪平台， 记录哺乳动物的活动过程单细胞转录组沿着与谱系的同时捕获 信息有助于将细胞的当前状态与其历史片段联系起来。一个重要组成部分 对于该技术是用于处理和分析数据的补充计算基础设施。找到 由于多能性的分化途径，谱系追踪平台将被应用于体外 小鼠发育模型，类胃体。小鼠胚胎干细胞聚集形成类胃体 细胞和忠实地模仿哺乳动物胚胎发生的许多特征。此外，胃状体是一个很好的- 定义的，易于处理的模型，以具有成本效益的方式实现更高的通量研究。解释数据 通过血统追踪实验，提出了一种隐马尔可夫模型来整合信息 并识别差异化轨迹。重要的是，可能会发现多个轨迹 显示了该技术的无偏的、数据驱动的特性。最后，模式由 谱系追踪平台可用于鉴定遗传调节因子并告知细胞类型 体外操作进行了讨论。