Decoding the non-binary signaling logic that controls cell fate

解码控制细胞命运的非二进制信号逻辑

• 批准号: 10624915
• 负责人: Idse Joannes Heemskerk
• 金额: $ 38.25万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10624915
• 关键词: Activins; Adhesions; Adult; Biological Assay; Biophysics; Cell Communication; Cell Fate Control; Cell Line; Cells; Characteristics; Complex; Computer Analysis; Computer software; Custom; Data; Data Science; Disease; Drug Targeting; Drug usage; Embryonic Development; Environment; Fibroblast Growth Factor; Fluorescence Microscopy; Foundations; Gene Combinations; Gene Expression; Goals; Health; Homeostasis; Image Analysis; Individual; Knowledge; Laboratories; Link; Logic; Maintenance; Measurement; Measures; Mechanics; Mesoderm; Methods; Nodal; Pathway interactions; Play; Population; Protocols documentation; Publishing; Recording of previous events; Research; Role; Signal Pathway; Signal Transduction; Signaling Molecule; Therapeutic; Time; Tissues; Visualization; Work; cell behavior; cell type; combinatorial; engineered stem cells; epithelial to mesenchymal transition; human pluripotent stem cell; improved; insight; interdisciplinary approach; mathematical model; mechanical signal; multidimensional data; nonbinary; notch protein; paracrine; pluripotency; response; stem cell differentiation; stem cell therapy; tissue regeneration

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.

项目摘要 /摘要 仅用少数一组信号通路（FGF，BMP，Wnt，HH，Notch等）反复使用 从早期胚胎发育到成人组织稳态的几乎所有方面。 这一小途径如何控制如此大量现象的理解很少。我们和其他人 最近表明信号响应不是二进制的，并且基因表达取决于许多参数 单元的信号历史，包括持续时间，时机和信号变化速率。因此，对 相同的信号分子可能部分归因于不同的暴露时间过程。主要目标 拟议的研究是对细胞的信号传导历史的预测理解 控制其命运，重点是人多能干细胞中的早期细胞命运决策。破译如何 信息是在动态信号中编码的，我们将采用一种高度跨学科的方法来结合基因 编辑，定量荧光显微镜，干细胞环境的工程，计算分析， 和数学建模。提出的相互关联的目标是基于以前发表的工作结合这些的 PI的方法和实验室的最新初步数据。首先，我们将确定人口水平 响应FGF的信号动力学。 FGF信号的定量特征尚不清楚 尽管在多能维护和肠系膜分化中起着至关重要的作用，并且这些信息 对于为第二个项目奠定基础很重要。其次，我们将超越人口水平的动态 单个途径，并通过单个细胞中的多个途径进行测量信号传导 确定组合信号传导的精确特征，这些特征可预测命运的能力。具体来说，我们将创建一个 表达我们已发表的四个结构的细胞系，可视化早期涉及的每种旁分泌途径 细胞命运（Wnt，BMP，Activin/Nodal和FGF），并利用我们的自定义图像分析软件跟踪单元 在许多天的差异化中。这将以单细胞多形式产生独特的高维数据 途径信号传导历史与细胞命运有关。然后，我们将使用数据科学方法来确定信号传导 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传导之间的相互作用。 中胚层分化与上皮 - 间质转变和急剧变化紧密相关 细胞间力。通过将我们的信号传导测定与强制操纵和力测量相结合，我们将 对FGF如何调节细胞间张力和粘合剂以及张力和张力和如何调节 粘附调节WNT响应。最终目标是获得对复合物的定量理解 信号动力学，细胞力学和细胞命运之间的相互作用，并利用这些知识对广泛范围 治疗应用，包括针对定向干细胞分化的优化方案和更有效的 使用靶向信号通路的药物。