System dynamics and gene network architecture of early T-cell development

早期 T 细胞发育的系统动力学和基因网络架构

• 批准号: 9978118
• 负责人: ELLEN V. ROTHENBERG
• 金额: $ 54.87万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-15 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9978118
• 关键词: Acute; Affect; Algorithms; Architecture; Automobile Driving; Back; Behavior; Binding Sites; Birth; Blood; Blood Cells; Cell Count; Cell Differentiation process; Cell Lineage; Cell Maturation; Cell Proliferation; Cells; Clone Cells; Collaborations; Collection; Computational Biology; Computer Analysis; Computing Methodologies; Data; Development; Developmental Process; Elements; Embryo; Embryology; Etiology; Family; Fluorescent in Situ Hybridization; Gene Expression; Gene Expression Profile; Gene Targeting; Generations; Genes; Genetic Transcription; Genomics; Growth; Growth and Development function; Guilt; Heterogeneity; Image; In Vitro; Individual; Kinetics; Life; Link; Mammals; Measurement; Methods; Modeling; Molecular; Molecular Biology; Monitor; Mus; Pathway interactions; Phase; Population; Probability; Process; RNA; Regulator Genes; Reporter; Reporting; Role; Series; Signal Transduction; Speed; System; Systems Biology; T cell differentiation; T-Cell Development; T-Cell Leukemia; T-Lymphocyte; Technology; Testing; Time; Transcript; Transgenic Mice; Tumor stage; Work; base; cell type; cellular imaging; cohort; early embryonic stage; embryo cell; fetal; gain of function; genetic analysis; leukemia; network architecture; network models; postnatal; progenitor; response; single cell analysis; single molecule; single-cell RNA sequencing; stem; stem cells; tissue regeneration; tool; transcription factor; transcriptome

PROJECT SUMMARY Timing of developmental progression is well-studied in early embryos, but cell lineages are generated stochastically from stem-cell precursors in later stages of life, and relatively little is known about the gene networks that control the probabilities that individual cells will initiate development or their rates of developmental progression. Mouse T cell development from multipotent blood precursors is an advantageous model for revealing mechanisms of these kinds of systems. The stages within the T-cell pathway are well defined in gene expression patterns, and cells starting from specific stages along the pathway can be tracked efficiently through development in vitro. Different cohorts of T cell progenitors from earlier or later embryonic and postnatal life have cell-intrinsic differences in the speeds with which they can differentiate. We hypothesize that the earliest cells in this pathway begin with a positively stabilized “Phase 1” gene regulatory network state that intrinsically opposes differentiation, until cumulative responses to signaling can induce a flip to a new network state. The differences in intrinsic differentiation speeds between different T-cell cohorts, and the extents of proliferation they undergo before differentiation is complete, are correlated with the persistence of the phase 1 regulatory state. However, until now it has been difficult to dissect these networks critically because cells in the earliest stages of T-cell development are rare and may have varied kinds of heterogeneity. This proposal is driven by new technological advances that open an exciting opportunity to dissect this mechanism functionally in single cells for the first time, and by a new systems biology collaboration that offers superior analyses of single-cell transcriptional responses to regulatory perturbation, both at the gene and at the cell levels. The new computational methods are optimized for revealing how gene network alterations shift subsets of cells between normal or abnormal developmental states. The experimental tools include recently developed mice with fluorescent reporters that report lineage commitment status of individual cells; imaging conditions that allow tracking living, individual clones through the whole commitment process; and an effective Cas9 transgenic mouse system that allows us to delete genes efficiently in primary T-cell precursors, so that impacts of perturbations on both gene expression and developmental kinetics can be defined. We can both define molecular sub-states in the starting population and monitor the impacts of specific regulatory factor perturbations using single-cell RNA-seq (10Genomics) and a new highly multiplex single-molecule fluorescent in situ hybridization technology for high sensitivity quantitation of low-abundance transcripts. Predictions of key network regulators will be directly tested here by perturbations and time-lapse imaging of clones differentiating from single cells. Finally, the small cell numbers needed allow us to define variances within single clones and to study the earliest ontogenic waves of precursors. We propose to apply these new tools to determine the gene network circuitries that sustain or destabilize the uncommitted state in different waves of early T cells.

项目概要 发育进程的时间在早期胚胎中得到了充分研究，但细胞谱系是产生的 随机地来自生命后期的干细胞前体，并且对该基因知之甚少 控制单个细胞启动发育的概率或其速率的网络 小鼠 T 细胞从多能血液前体发育而来是有利的。 揭示此类系统机制的模型很好。 定义在基因表达模式中，并且可以跟踪从该途径的特定阶段开始的细胞 来自早期或晚期胚胎的不同 T 细胞祖细胞群在体外有效地发育。 和出生后的生命在细胞分化速度方面存在内在差异。 该途径中最早的细胞以正稳定的“第一阶段”基因调控网络状态开始 本质上反对分化，直到对信号的累积反应可以诱导转向新的 不同 T 细胞群之间内在分化速度的差异，以及 它们在分化完成之前经历的增殖程度，与 然而，到目前为止，我们还很难批判性地剖析这些网络。 因为处于 T 细胞发育早期阶段的细胞非常罕见，并且可能具有多种异质性。 该提案是由新技术进步推动的，为剖析这一问题提供了令人兴奋的机会 该机制首次在单细胞中发挥作用，并通过新的系统生物学合作提供 对单细胞转录对基因和调控扰动的反应进行了卓越的分析 新的计算方法经过优化，可揭示基因网络改变如何变化。 实验工具包括最近的正常或异常发育状态之间的细胞亚群。 开发出带有荧光报告基因的小鼠，可报告单个细胞成像的谱系定型状态； 允许在整个承诺过程中跟踪活的个体克隆的条件； Cas9转基因小鼠系统使我们能够有效地删除原代T细胞前体中的基因，从而 我们可以定义扰动对基因表达和发育动力学的影响。 定义起始群体中的分子亚状态并监测特定调节因素的影响 使用单细胞 RNA-seq (10Genomics) 和新型高度多重单分子荧光进行扰动 原位杂交技术用于低丰度转录本的高灵敏度定量预测。 网络调节器将在这里通过克隆分化的扰动和延时成像直接进行测试 最后，所需的小细胞数量使我们能够定义单个克隆内的差异 我们建议应用这些新工具来研究前体的最早个体波。 维持或破坏早期 T 细胞不同波中未承诺状态的基因网络电路。