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: 10794428
• 负责人: Idse Joannes Heemskerk
• 金额: $ 7.38万
• 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/10794428
• 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.

项目总结/摘要 只有少数几组信号通路（FGF、BMP、Wnt、Hh、Notch等）被重复利用来控制 从早期胚胎发育到成年组织稳态的几乎所有细胞间通讯的方面。 人们对这一小部分途径如何控制如此大量的现象知之甚少。我们和其他人 最近表明，信号响应不是二元的，基因表达取决于许多参数， 一个细胞的信号历史，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过程。首要目标 这项研究的目的是对细胞的信号历史如何进行预测性理解， 控制其命运，专注于人类多能干细胞的早期细胞命运决定。为了破解 信息被编码在动态信号中，我们将采取一种高度跨学科的方法， 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。拟议的相互关联的目标建立在以前发表的工作结合这些 PI的方法和实验室最近的初步数据。首先，我们将确定人口水平 信号动力学响应FGF。FGF信号转导的定量特征还不清楚 尽管在多能性维持和中内胚层分化中起着至关重要的作用， 是为第二个项目奠定基础的重要因素。第二，我们将超越人口水平动态 并在单个细胞中同时测量通过多种途径的信号传导， 识别预测命运的组合信号的精确特征。具体来说，我们将创建一个 表达我们发表的四种构建体的细胞系，以可视化参与早期乳腺癌的每种旁分泌途径。 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细胞 经过几天的分化。这将以单细胞多细胞的形式生成独特的高维数据， 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号 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， 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 获得FGF如何调节细胞间张力和粘附的生物物理学见解，以及张力和 粘附调节Wnt应答。最终目标是获得对复合体的定量了解 信号动力学，细胞力学和细胞命运之间的相互作用，并利用这些知识进行广泛的 治疗应用，包括用于定向干细胞分化的优化方案和更有效的 使用针对信号通路的药物。