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.

项目摘要 发育进展的时机在早期胚胎中得到了充分研究，但细胞谱系是生成的 在生命的后期阶段，从干细胞前体开始随随机，对基因的了解很少 控制各个单元启动开发或其速率的可能性的网络 发展进展。小鼠T细胞从多能血液前体发育是一个有利的 揭示此类系统机制的模型。 T细胞路径内的阶段很好 在基因表达模式中定义，可以跟踪从沿该路径的特定阶段开始的细胞 通过体外发展有效。来自早期或后期胚胎的T细胞祖细胞的不同队列 产后生活在它们可以区分的速度方面具有细胞内在差异。我们假设 该途径中最早的细胞以正面稳定的“ 1阶段”基因调节网络状态开始 本质上反对分化，直到对信号的累积响应可以引起对新的翻转 网络状态。不同T细胞组之间的内在差异速度的差异和 在分化完成之前，他们发生的增殖量与持续存在相关 第1期监管状态。但是，到目前为止，很难批判性地剖析这些网络 因为T细胞发育最早的细胞很少见，并且可能具有不同的异质性。 该提议是由新的技术进步驱动的，这为剖析这一点开放了激动人心的机会 首次在单个单元中功能机制，并通过新的系统生物学协作提供 对基因和处于调节扰动的单细胞转录响应的卓越分析 细胞水平。优化了新的计算方法，以揭示基因网络改变如何变化 正常或异常发育状态之间的细胞子集。实验工具最近包括 用荧光记者开发了小鼠，这些小鼠报告了单个细胞的谱系承诺状态；成像 可以在整个承诺过程中追踪生活的条件；有效 Cas9转基因小鼠系统，使我们能够在主T细胞前体中有效删除基因，以便 扰动对基因表达和发育动力学的影响都可以定义。我们都可以 定义开始人群中的分子子群并监测特定调节因子的影响 使用单细胞RNA-seq（10Genomics）和一种新的高度多重单分子荧光的扰动 原位杂交技术，用于对低丰度转录本的高灵敏度定量。密钥的预测 网络调节器将在此处通过扰动和克隆的延时成像进行直接测试 来自单个细胞。最后，需要的小单元格数使我们能够在单个克隆和 研究最早的前体的个体生成波。我们建议应用这些新工具来确定 基因网络圆圈在不同的早期T细胞中维持或不稳定了未承诺的状态。