Decoding the non-binary signaling logic that controls cell fate

项目摘要/摘要 只有少数几个信号通路(成纤维细胞生长因子、骨形态发生蛋白、Wnt、HH、Notch等)被重复利用来控制 从早期胚胎发育到成人组织动态平衡，几乎所有方面的细胞-细胞通讯都是如此。 这一小部分通路是如何控制如此大量的现象的，目前还知之甚少。我们和其他人 最近的研究表明，信号响应不是二元的，基因的表达取决于许多参数 小区的信令历史，包括持续时间、定时和信号变化率。因此，不同的反应 相同的信号分子可能部分归因于不同的暴露时间进程。首要目标 这项拟议的研究的目的是发展一种预测性的理解，即细胞的信号历史 控制其命运，专注于人类多能干细胞的早期细胞命运决定。破译是如何 信息是以动态信号编码的，我们将采取高度跨学科的方法，结合基因 编辑，定量荧光显微镜，干细胞环境工程，计算分析， 和数学建模。提议的相互关联的目标建立在先前发表的工作的基础上，结合了这些 PI的方法和实验室的最新初步数据。一是确定人口水平 反应成纤维细胞生长因子的信号动力学。成纤维细胞生长因子信号的数量特征还不是很清楚 尽管在维持多能性和中胚层分化方面起着至关重要的作用，但这一信息 在为第二个项目奠定基础方面很重要。第二，我们将超越人口层面的动态 并在单个细胞中同时测量通过多个路径的信号以 确定可以预测命运的组合信号的精确特征。具体地说，我们将创建一个 表达我们已发表的四个结构的细胞株，以可视化早期参与的每一条旁分泌途径 细胞命运(WNT、BMP、激活素/结节和成纤维细胞生长因子)，并利用我们的定制图像分析软件跟踪细胞 经过许多天的分化。这将生成形式为单单元多维数据的唯一高维数据。 与细胞命运相关的信号通路历史。然后我们将使用数据科学方法来确定信令 预测细胞命运的特征。第三，我们将研究组织力学和细胞信号之间的相互作用。 中胚层分化与上皮-间充质转化密切相关，并与 细胞间力。通过将我们的信号分析与力操纵和力测量相结合，我们将 了解成纤维细胞生长因子如何调节细胞间的张力和黏附，以及张力和黏附如何 黏附调节Wnt的反应。最终目标是对复杂事物有一个定量的了解。 信号动力学、细胞力学和细胞命运之间的相互作用，并广泛地利用这些知识 包括定向干细胞分化的优化方案和更有效的治疗应用 使用靶向信号通路的药物。

PROJECT SUMMARY / ABSTRACT Only a handful set of signaling pathways (FGF, BMP, Wnt, Hh, Notch, etc) are repeatedly utilized to control almost all aspects of cell-cell communication from early embryonic development to adult tissue homeostasis. How this small set of pathways controls such a large number of phenomena is poorly understood. We and others recently showed that signal response is not binary, and that gene expression depends on many parameters of a cell’s signaling history, including duration, timing, and rate of signal change. Therefore, different responses to the same signaling molecules may be in part attributed to different time courses of exposure. The primary goal of the proposed research is to develop a predictive understanding of how the signaling history of a cell controls its fate, focusing on early cell fate decisions in human pluripotent stem cells. To decipher how information is encoded in dynamic signals we will take a highly interdisciplinary approach that combines gene editing, quantitative fluorescence microscopy, engineering of the stem cell environment, computational analysis, and mathematical modeling. The proposed interrelated goals build on previously published work combining these approaches by the PI and recent preliminary data from the laboratory. First, we will determine population level signaling dynamics in response to FGF. The quantitative characteristics of FGF signaling are not well understood despite playing a crucial role in pluripotency maintenance and mesendoderm differentiation, and this information is important in laying the foundation for the second project. Second, we will go beyond population level dynamics of a single pathway, and measure signaling through multiple pathways simultaneously in individual cells to identify precise features of combinatorial signaling that are predictive of fate. Specifically, we will create a single cell line expressing four of our published constructs to visualize each of the paracrine pathways involved in early cell fate (Wnt, BMP, Activin/Nodal, and FGF), and utilize our custom image analysis software for tracking cells through many days of differentiation. This will generate unique high-dimensional data in the form single-cell multi- pathway signaling histories linked to cell fate. We will then use data science methods to determine signaling features that predict cell fate. Third, we will investigate the interplay between tissue mechanics and cell signaling. Mesoderm differentiation is closely linked to an epithelial-mesenchymal transition and dramatic changes in intercellular forces. By combining our signaling assays with force manipulation and force measurement, we will gain biophysical insight into how FGF regulates intercellular tension and adhesion, and how tension and adhesion modulate the Wnt response. The ultimate goal is to obtain a quantitative understanding of the complex interplay between signaling dynamics, cell mechanics, and cell fate, and exploit this knowledge for wide ranging therapeutic applications including optimized protocols for directed stem cell differentiation and more effective use of drugs that target signaling pathways.