Kinetic modeling and single-cell molecular mechanisms of early T-cell commitment

早期 T 细胞定型的动力学模型和单细胞分子机制

• 批准号: 9066200
• 负责人: Carsten Peterson
• 金额: $ 59.36万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9066200
• 关键词: Accounting; Address; Adult; Affect; Algorithm Design; Architecture; Back; Behavior; Biological; Blood Cells; Cell Cycle; Cell Lineage; Cell division; Cells; Characteristics; Choices and Control; Clonal Expansion; Cluster Analysis; Collaborations; Competence; Computational Biology; Computer Simulation; DNA Binding; Data; Data Set; Development; Developmental Biology; Developmental Gene; Developmental Process; Disease; Embryo; Environment; Equilibrium; Evolution; Failure; Gene Expression; Gene Expression Profiling; Gene Expression Regulation; Generations; Genes; Health; Hematopoiesis; Hematopoietic; Image; In Vitro; Indium; Individual; Kinetics; Length; Life; Link; Logic; Measurement; Methods; Microscopy; Modeling; Molecular; Molecular Biology; Monte Carlo Method; Multipotent Stem Cells; Network-based; Pathway Analysis; Pathway interactions; Phase; Phenotype; Population; Population Dynamics; Process; Readiness; Regulator Genes; Role; Series; Signal Transduction; Speed; Stem cells; System; Systems Biology; T-Cell Development; T-Lymphocyte; Testing; Thymus Gland; Time; Tissues; Work; adult stem cell; base; cell behavior; cell type; control theory; cost; design; experimental analysis; feeding; genome-wide; in vivo; live cell imaging; movie; multi-scale modeling; multidisciplinary; multipotent cell; network architecture; network models; offspring; operation; prevent; programs; research study; self-renewal; transcription factor; transcriptome; zygote

DESCRIPTION (provided by applicant): Adult tissue multipotent stem cells have a double regulatory program: one that preserves their ability to differentiate into various cell types, and one that allows them to self-renew while preventing or postponing differentiation. For the cells to differentiate, the link between these two program components must be broken. Differentiation vs. self-renewal decisions must involve activation and cross-inhibition of different circuits in a gene regulatory network, but these network architectures are not well understood. It is not known at a molecular level how individual multipotent stem cells control the timing of their decisions to differentiate, or the speed with which they will differentiate relative to clonal expansion to a given fate. This is the problem that we propose to address using a combination of single-cell live imaging, gene network analysis, and computational modeling of population dynamics and gene network dynamics in a particularly tractable experimental system. In hematopoiesis, this wider problem can be addressed because there is excellent characterization of short- term and long-term multipotent stem cells, plus a variety of partially restricted progenitor cells which have different repertoires of developmental potential but still defer lineag commitment, keeping multiple options open. The T-lymphocyte developmental pathway is one branch of hematopoiesis in which this general question may be unusually accessible. It is based on a well-defined series of intermediate states with reproducible developmental and gene expression characteristics, and the T cell program can be triggered and guided in hematopoietic precursors experimentally in vitro. At the same time, the path to T-cell lineage commitment involves extensive proliferation, raising the question of how proliferation that advances differentiation may be distinguished from self-renewal, and providing a system in which to test factors that control this distinction. We have assembled a multidisciplinary systems biology collaboration to dissect the basis of the choice to enter the T-cell pathway, by an integrated strategy of computational modeling and experimental analysis. Our initial work has shown that T cell precursors initially go through a phase of self-renewal-like proliferation in which differentiation competence is delayed, and that readiness to differentiate in single cells is finaly provided by intrinsic regulatory changes. The regulatory circuitry underlying this switch is now accessible by exploiting new access to single-cell live tracking and gene expression analysis methods while leveraging the results of our recent genome-wide transcriptome analyses of early T-cell precursors. Here we propose: to establish a framework for the problem by modeling the kinetics of T-lineage differentiation choices relative to proliferation in individual cells; to trak individual cell fates forward and backward through the T-cell developmental process by live imaging; to determine gene expression features of individual cells that best predict their developmental behavior; and to use computational and experimental approaches in an interlaced, iterative way to deduce the gene network architecture that controls entry into the T-cell pathway, and to validate its key linkages.

描述（由申请人提供）：成体组织多能干细胞具有双重调节程序：一种保持其分化成各种细胞类型的能力，另一种允许它们自我更新，同时防止或推迟分化。为了使细胞 区分，这两个程序组件之间的链接必须被打破。分化与自我更新决策必须涉及基因调控网络中不同电路的激活和交叉抑制，但这些网络架构尚不清楚。目前尚不清楚单个多能干细胞如何在分子水平上控制其分化决定的时间，或者相对于克隆扩增至给定命运的分化速度。这就是我们建议在一个特别容易处理的实验系统中结合使用单细胞实时成像、基因网络分析以及群体动态和基因网络动态的计算模型来解决的问题。在造血过程中，这个更广泛的问题可以得到解决，因为短期和长期多能干细胞具有出色的特征，加上各种部分受限的祖细胞，它们具有不同的发育潜力，但仍然推迟谱系承诺，从而保持多种选择。 T 淋巴细胞发育途径是造血作用的一个分支，这一普遍问题在其中可能异常容易被理解。它基于一系列明确的中间状态，具有可重复的发育和基因表达特征，并且可以通过体外实验在造血前体中触发和引导 T 细胞程序。与此同时，T细胞谱系定型的路径涉及广泛的增殖，这就提出了如何区分促进分化的增殖与自我更新的问题，并提供了一个系统来测试控制这种区别的因素。 我们组建了多学科系统生物学合作机构，通过计算建模和实验分析的综合策略来剖析选择进入 T 细胞途径的基础。我们的初步工作表明，T 细胞前体最初会经历一个类似自我更新的增殖阶段，其中分化能力被延迟，并且最终由内在调节变化提供单细胞分化的准备。现在，通过利用新的单细胞实时跟踪和基因表达分析方法，同时利用我们最近对早期 T 细胞前体进行的全基因组转录组分析的结果，可以访问这种开关背后的调节电路。在这里，我们建议：通过对 T 谱系分化选择相对于单个细胞增殖的动力学进行建模，建立一个解决该问题的框架；通过实时成像在 T 细胞发育过程中向前和向后追踪单个细胞的命运；确定最能预测其发育行为的单个细胞的基因表达特征；以交错、迭代的方式使用计算和实验方法来推断控制进入 T 细胞途径的基因网络架构，并验证其关键联系。