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

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：一个保留其分化为各种细胞类型的能力，另一个允许其自我更新，同时阻止或推迟分化。使细胞 如果要区分，这两个程序组件之间的链接必须断开。分化与自我更新的决定必须涉及基因调控网络中不同回路的激活和交叉抑制，但这些网络结构还没有得到很好的理解。在分子水平上尚不清楚个体多能干细胞如何控制其决定分化的时机，或相对于克隆扩增到给定命运的分化速度。这是我们建议使用单细胞活体成像，基因网络分析，以及在一个特别易于处理的实验系统中的种群动态和基因网络动态的计算建模相结合来解决的问题。在造血中，这个更广泛的问题可以得到解决，因为存在短期和长期多能干细胞的优异表征，加上各种部分受限的祖细胞，其具有不同的发育潜能库，但仍然延迟线性定型，保持多种选择。T淋巴细胞发育途径是造血的一个分支，在这个分支中，这个普遍的问题可能是不寻常的。它是基于一系列定义明确的中间状态，具有可重复的发育和基因表达特征，并且T细胞程序可以在体外实验中在造血前体中触发和引导。与此同时，T细胞谱系定型的途径涉及广泛的增殖，提出了如何将促进分化的增殖与自我更新区分开来的问题，并提供了一个测试控制这种区分的因素的系统。 我们已经组装了一个多学科的系统生物学合作，解剖的基础上选择进入T细胞通路，通过计算建模和实验分析的综合策略。我们的初步工作表明，T细胞前体细胞最初经历一个自我更新样增殖的阶段，其中分化能力被延迟，并且最终通过内在调控变化提供了在单细胞中分化的准备。这种开关背后的调控电路现在可以通过利用新的单细胞活追踪和基因表达分析方法来获得，同时利用我们最近对早期T细胞前体的全基因组转录组分析的结果。在此，我们建议：通过模拟T细胞系分化选择相对于单个细胞增殖的动力学来建立问题的框架;通过活体成像来跟踪单个细胞在T细胞发育过程中的前后命运;确定最能预测其发育行为的单个细胞的基因表达特征;并以交错、迭代的方式使用计算和实验方法来推导控制进入T细胞途径的基因网络结构，并验证其关键联系。

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.