Quantitative models for controlling collective cell fate selection in stem cells

描述（由申请人提供）：一个重要的生物医学研究目标是从诱导多能细胞重建人体组织，用于体外对人类疾病状态的询问。然而，我们诱导干细胞形成复杂的多细胞结构的能力目前受到深刻的概念和技术挑战的限制。虽然高通量基因表达和生化测量使我们能够重建控制干细胞命运的分子电路，但这些电路非常复杂，基因组学产生的图谱是静态的。因此，我们不了解单个干细胞如何动态整合来自其环境的信号，同时与其他细胞通信以协调和构建多细胞组织。我研究的主要目标是将高通量单细胞成像和数学建模结合起来，推导出细胞命运电路的简化预测模型，并利用这些模型与新的光遗传学工具来操纵具有空间和时间控制的干细胞命运。在这个应用程序中，我使用小鼠胚胎干细胞（ES）细胞分化作为一个强大的模型系统，用于干细胞群体命运选择的定量单细胞分析。在Wnt和Fgf信号的响应下，胚胎干细胞离开多能状态，并在两种生殖层细胞命运之间进行选择。一个复杂的转录因子网络控制着胚胎干细胞，但是，在之前的研究中，我发现只有两个转录因子Oct4和Sox2组成的回路控制着胚层命运的选择。现在，我使用Oct4和Sox2作为生殖层命运选择的定量和预测模型的基本节点，该模型结合了单细胞信息处理和细胞间通信。首先，我将对Oct4和Sox2蛋白水平进行高通量单细胞延时成像，以量化ES细胞对大量Wnt和Fgf输入的反应。通过统计分析，将这些测量结果简化为信号集成的预测动力系统模型。其次，为了确定细胞间通讯对ES细胞命运选择的影响，我将量化分化信号在ES细胞群体中通过Wnt、Fgf和Notch通路的时空传播，并构建细胞命运选择的群体水平模型。第三，我将结合新的光遗传学工具来调节单细胞对Wnt和Fgf的反应，从而通过空间控制来指导胚层分化。由于胚层分化是哺乳动物发育和体外分化的基础过程，光遗传学控制这一过程将为胚层衍生物在体外构建复杂的多细胞结构提供平台。总之，这些目标将提供概念性的见解，干细胞如何沟通执行多细胞过程，如组织发育，体内平衡和修复。此外，我的申请将为光遗传学光门控体外胚胎干细胞分化的原理证明，以合成用于人类疾病研究的组织。

DESCRIPTION (provided by applicant): An important biomedical research goal is to reconstitute human tissues from induced pluripotent cells for in vitro interrogation of human disease states. However, our ability to coax stem cells to form complex multi- cellular structures is currently limited by deep conceptual and technical challenges. While high-throughput gene expression and biochemical measurements allow us to reconstruct the molecular circuits that control stem cell fate, these circuits are enormously complex, and the maps produced by genomics are static. Therefore, we do not understand how individual stem cells dynamically integrate signals from their environment while communicating with other cells to coordinate and construct multi-cellular tissues. The major goal of my research is to combine high-throughput single cell imaging and mathematical modeling to derive reduced, predictive models of cell fate circuits and to exploit these models with new optogenetic tools to manipulate stem cell fate with spatial and temporal control. In this application, I use mouse Embryonic Stem (ES) cell differentiation as a powerful model system for quantitative single cell analysis of fate selection n a stem cell population. In response to Wnt and Fgf signals, ES cells leave the pluripotent state and select between two alternate germ layer cell fates. A complex network of transcription factors controls the ES cell, but, in previous research, I showed that a circuit of just two transcription factors, Oct4 and Sox2, controls germ layer fate selection. Now, I use Oct4 and Sox2 as the essential nodes in a quantitative and predictive model of germ layer fate selection that incorporates both single cell information processing and inter-cellular communication. First, I will perform high-throughput single cell time lapse imaging of Oct4 and Sox2 protein levels to quantify the ES cell's response to a large array of Wnt and Fgf inputs. With statistical analysis, will reduce these measurements to a predictive dynamical systems model of signal integration. Second, to determine the impact of inter-cellular communication on ES cell fate selection, I will quantify the spatial and temporal propagation of differentiation signals through the Wnt, Fgf, and Notch pathways in ES cell populations and construct a population level model of cell fate selection. Third, I will combine the model with new optogenetic tools to modulate the single cell response to Wnt and Fgf in order to direct germ layer differentiation with spatial control. Since germ layer differentiation is a foundational process of both mammalian development and in vitro differentiation, optogenetic control of this process would provide a platform for in vitro construction of complex multi-cellular structures from germ layer derivatives. Together, these aims will provide conceptual insight into how stem cells communicate to execute multi-cellular processes like tissue development, homeostasis, and repair. Further, my application will provide a proof of principle for optogenetic light-gated control of in vitro embryonic stem cell differentiation to synthetically generate tissues for studies of human disease.