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）：成人组织多能干细胞具有双重调节程序：保留其分化为各种细胞类型的能力，并且可以在防止或推迟分化的同时自我更新。用于细胞 区分，这两个程序组件之间的链接必须打破。分化与自我更新决策必须涉及基因调节网络中不同电路的激活和交叉抑制，但是这些网络体系结构尚不清楚。在分子水平上，单个多能干细胞如何控制其决策的时机或它们将相对于克隆扩张到给定命运的速度的速度。这是我们建议使用单细胞实时成像，基因网络分析以及在特别可触及的实验系统中的人群动态和基因网络动力学的计算建模的组合来解决的问题。在造血中，可以解决这个更广泛的问题，因为短期和长期多能干细胞以及各种部分受限制的祖细胞具有出色的表征，这些细胞具有不同的发育潜力，但仍会推迟谱系承诺，保持多个选择的范围。 T淋巴细胞发育途径是造血的一个分支，其中这个一般问题可能异常地访问。它基于具有可重复发育和基因表达特征的一系列定义明确的中间状态，并且可以在体外实验触发和引导T细胞程序在造血前体中进行引导。同时，通往T细胞谱系承诺的途径涉及广泛的增殖，这提出了一个问题，即如何将分化的扩散与自我更新区分开，并提供了一个系统来测试控制这种区别的系统。 我们已经组建了一个多学科系统生物学协作，以通过计算建模和实验分析的综合策略来剖析进入T细胞途径的选择的基础。我们的最初工作表明，T细胞前体最初经历了一种自我更新样的增殖阶段，在这种增殖中，分化能力被延迟了，并且在单个细胞中进行分化的准备就最终是由固有的调节变化提供的。现在可以通过利用对单细胞实时跟踪和基因表达分析方法的新访问来访问此开关的监管电路，同时利用了我们最近全基因组T-CELL前体的近期全基因组转录组分析的结果。在这里，我们建议：通过对单个细胞中T-LineAge分化选择的动力学进行建模来建立问题的框架；通过实时成像，通过T细胞的发育过程向前和向后进行单个细胞的命运；确定最能预测其发育行为的单个细胞的基因表达特征；并以一种交错的迭代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体系结构并验证其关键链接。