Measuring and modeling the dynamics of patterning in human stem cells

摘要 这个项目的长期目标是了解复杂人体组织中的细胞如何感知、处理和 在正常的人类发育和发育性疾病期间对信号作出反应。 发育生物学中的一个基本问题是了解组织在发育过程中是如何形成模式的 动物。本申请将在人类多能性模式的背景下解决该问题 细胞分化为中胚层和内胚层。要研究的第一个问题是细胞如何感知信号， 然后更仔细地观察内部基因调控网络是如何处理这一信号的 当细胞选择自己的命运时，转录反应。 这项提议的第一个目的是使用新型微流控技术的组合来控制信号、基因组的梯度 荧光标记关键转录因子的修饰技术研究其动力学 并用图像处理和数学工具对数据进行分析。它进一步跟进了 申请人最近的发现是，感知信号的关键受体是基本定位的。本研究 演示了由于受体被定位，细胞感知活跃心尖信号的能力 从根本上影响图案形成。这是申请者意识到的第一项试图量化的研究 了解人类干细胞是如何构思出来的。 第二个目标是了解细胞内基因调控网络的状态 在人和小鼠生殖层分化过程中影响对转化生长因子-β信号的反应。事实上，细胞 即使从胚胎的同一区域获得的发育间隔12小时也显示出数字上的不同 对相同信号的反应。在发育过程中获得的单细胞基因表达数据如下 用于建立细胞内基因调控网络的预测数学模型。建造这样的建筑 预测数学模型在过去一直是非常具有挑战性的。使用这些模型，目标是 目的是揭示细胞是否能够以不同的方式对相同的形态发生信号做出反应，这取决于 核心基因调控回路的状态。这些预测是在早期的背景下进行实验验证的 人类和小鼠利用成像和分子技术来干扰基因表达。 该提议所取得的发现将有助于更好地理解多能人类细胞是如何 在发育过程中和癌症中都会对信号做出反应。此外，建立预测模型的能力 对潜在基因调控网络的研究为理解疾病的潜在机制开辟了道路 未来的国家。

Abstract The long-term goal of this project is to understand how cells in complex human tissues sense, process and respond to signal during normal human development and developmental diseases. A fundamental question in developmental biology is to understand how tissues are patterned in a developing animal. This Application will address the question in the context of the patterning of the human pluripotent cells into mesoderm and endoderm. The first question that will be investigated is how cells sense signal, followed by a closer look at how the internal gene regulatory network processes this signal to launch a transcriptional response as the cell chooses its fate. The first aim of this proposal uses a combination of novel microfluidics to control gradients of signals, genome modification techniques to fluorescently tag key transcription factors to study their dynamics using epifluorescence, and image processing and mathematical tools to analyze the data. It further follows up on the applicant’s recent discovery that key receptors that sense signals are basally localized. This study demonstrates how the (in)ability of the cell to sense active apical signal due its receptors being localized basally affect patterning. This is the first study the applicants are aware of to attempt to quantitatively understand how human stem cells are patterned. The second aim focuses on understanding how the state of the gene regulatory network within the cell affects the response to TGF-beta signal during germ layer differentiation in human and mouse. Indeed, cells even twelve hours apart in development obtained from the same region of the embryo show digitally distinct responses to the same signal. Single cell gene expression data obtained during the course of development is used to build a predictive mathematical model of the intracellular gene regulatory network. Building such predictive mathematical models has been very challenging in the past. Using these models, the goal of this aim is to uncover whether cells can respond to the same morphogenetic signal in distinct ways depending on the state of a core gene regulatory circuit. The predictions are checked experimentally in the context of early human and mouse development using imaging and molecular techniques to perturb gene expression. The discoveries made by the proposal will lead to a better understanding of how multipotent human cells respond to signal both during development and in cancer. Furthermore, the ability to build predictive models of the underlying gene regulatory network opens avenues to understand the mechanisms underlying disease states in the future.