Quantitative models for controlling collective cell fate selection in stem cells

控制干细胞集体细胞命运选择的定量模型

• 批准号: 9135548
• 负责人: Matthew W. Thomson
• 金额: $ 22.67万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-25 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9135548
• 关键词: Accounting; Behavior; Biochemical; Biological Models; Biomedical Research; Cell Cycle; Cell division; Cell model; Cell physiology; Cells; Cellular Structures; Color; Communication; Communities; Complex; Data; Data Analyses; Decision Making; Development; Disease; Environment; Fibrinogen; Gene Expression; Genomics; Germ Layers; Goals; Homeostasis; Human; Human body; Image; In Vitro; Individual; Kinetics; Laboratories; Learning; Left; Libraries; Life; Light; Maps; Measurement; Measures; Methods; Microscopy; Modeling; Molecular; Mus; Muscle; Neurons; Pathway interactions; Pattern; Physics; Physiology; Population; Process; Proteins; Protocols documentation; Regenerative Medicine; Reporter; Research; Route; Signal Pathway; Signal Transduction; Signaling Molecule; Signaling Protein; Statistical Data Interpretation; Stem cells; Structure; System; Systems Biology; Techniques; Testing; Time; Tissues; Work; cell motility; cellular imaging; design; dynamic system; embryonic stem cell; genome-wide; human disease; human tissue; in vitro Model; information processing; insight; light gated; mathematical model; models and simulation; neural circuit; neural model; notch protein; optogenetics; predictive modeling; reconstitution; relating to nervous system; repaired; response; single cell analysis; small molecule; stem cell differentiation; stem cell fate; stem cell population; temporal measurement; tissue repair; tool; transcription factor

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.

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，用于体外研究人类疾病状态。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回路，但这些回路非常复杂，而且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，得出细胞命运回路的简化预测模型，并利用这些模型与新的光遗传学工具来通过空间和时间控制来操纵干细胞命运。在此应用中，我使用小鼠胚胎干 (ES) 细胞分化作为强大的模型系统，对干细胞群的命运选择进行定量单细胞分析。响应 Wnt 和 Fgf 信号，ES 细胞离开多能状态并在两种替代的胚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 ES 细胞，但是，在之前的研究中，我表明只有两个转录因子 Oct4 和 Sox2 的回路控制着胚层命运选择。现在，我使用 Oct4 和 Sox2 作为胚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积分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 ES 细胞群体中分化信号通过 Wnt、Fgf 和 Notch 通路的空间和时间传播，并构建细胞命运的群体水平模型选择。第三，我将将该模型与新的光遗传学工具结合起来，调节单细胞对 Wnt 和 Fgf 的反应，以便通过空间控制指导胚层分化。由于胚层分化是哺乳动物发育和体外分化的基础过程，因此该过程的光遗传学控制将为体外从胚层衍生物构建复杂的多细胞结构提供平台。总之，这些目标将为干细胞如何通信以执行组织发育、稳态和修复等多细胞过程提供概念性见解。此外，我的应用将为体外胚胎干细胞分化的光遗传学光门控控制提供原理证明，以合成生成用于人类疾病研究的组织。