Mechanisms of signal integration in developmental control of organ size and tissue patterning

器官大小和组织模式发育控制中的信号整合机制

• 批准号: 10206726
• 负责人: Alexey Veraksa
• 金额: $ 31.86万
• 依托单位: UNIVERSITY OF MASSACHUSETTS BOSTON
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-05 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10206726
• 关键词: Acute; Address; Animals; Biochemical; Biological; Biological Assay; Cells; Computer Models; DNA Binding; Data; Development; Developmental Biology; Developmental Process; Disease; Down-Regulation; Drosophila genus; Embryo; Essential Genes; Event; Experimental Models; Extracellular Signal Regulated Kinases; Gene Expression Regulation; Genetic; Genetic Transcription; Genetic study; Goals; Human; Image; Malignant Neoplasms; Mesoderm; Modeling; Molecular; Nature; Neurodegenerative Disorders; Nuclear; Organ Size; Pathologic; Pathway interactions; Pattern; Phosphorylation Site; Play; Process; Proteins; Regulation; Research; Role; Signal Pathway; Signal Transduction; Site; System; Systems Biology; Testing; Time; Tissues; Transcription Repressor; Work; autism spectrum disorder; base; cancer type; cohort; design; gastrulation; gene repression; human disease; in vivo; in vivo evaluation; insight; mathematical model; neurocognitive disorder; novel strategies; optogenetics; phosphoproteomics; response; sensor

PROJECT SUMMARY/ABSTRACT The proposed work will investigate transcriptional interpretation of signaling through the ERK pathway, which plays critical roles in animal development and is commonly deregulated in human diseases. We will use Drosophila as an experimental model that offers unrivaled opportunities for dissecting gene regulation by ERK signaling at multiple levels of biological organization, from specific ERK substrates to the whole embryo. Aim 1 focuses on Capicua (Cic), a transcriptional repressor that was discovered in Drosophila and has recently emerged as a key sensor of ERK activation in developmental and pathological contexts. We will identify functionally significant phosphorylation sites in Cic and investigate their effects on the ERK-dependent control of Cic protein stability, nuclear localization, and DNA binding. Aim 2 is designed to bridge the gap between genetic studies, which commonly identify only a handful of ERK substrates, and omics-level studies, which suggest that ERK functions through large substrate cohorts. We will evaluate these two scenarios using an already working combination of acute optogenetic perturbations, quantitative phosphoproteomics, and live imaging of functionally significant transcriptional responses to ERK signaling. Finally, Aim 3 will study transcriptional effects of ERK signaling, which commonly works by simultaneously activating some cell fates and repressing others. We will use quantitative optogenetic perturbations and live imaging to test the hypothesis that activating and repressing effects of ERK signaling require different levels of ERK activation. Our experimental tests of this hypothesis will address a key issue in developmental ERK signaling and will provide quantitative data needed for predictive computational modeling. Feasibility of the proposed work is supported by preliminary data that include functional characterization of Cic phosphosites (Aim 1), a phosphoproteomics approach for the in vivo discovery of ERK substrates (Aim 2), and an optogenetic approach to data-driven design of predictive computational models (Aim 3).

项目总结/摘要 拟议的工作将调查通过ERK途径的信号转导的转录解释， 在动物发育中起着关键作用，在人类疾病中通常被解除管制。我们将使用 果蝇作为一个实验模型，提供了无与伦比的机会解剖基因调控的ERK 从特定的ERK底物到整个胚胎，在多个生物组织水平上进行信号传导。要求1 重点是Capicua（Cic），一种在果蝇中发现的转录抑制因子， 作为ERK激活的关键传感器出现在发展和病理背景下。我们将确定 Cic中功能显著的磷酸化位点，并研究它们对ERK依赖性调控的影响。 Cic蛋白稳定性、核定位和DNA结合。目标2旨在弥合遗传学之间的差距， 研究，通常只确定少数ERK底物，和组学水平的研究，这表明， ERK通过大的底物群发挥作用。我们将使用一个已经运行的 急性光遗传学扰动、定量磷酸化蛋白质组学和功能性蛋白质的实时成像的组合 对ERK信号传导的显著转录反应。最后，本研究的目的3是研究ERK的转录调控作用 信号传导，其通常通过同时激活一些细胞命运和抑制其他细胞命运来起作用。我们将 使用定量光遗传学扰动和活体成像来检验激活和抑制 ERK信号传导的作用需要不同水平的ERK激活。我们对这一假设的实验测试将 解决了发育ERK信号传导的关键问题，并将提供预测所需的定量数据。 计算建模拟议工作的可行性得到了初步数据的支持，其中包括功能数据 Cic磷酸化位点的表征（Aim 1），用于ERK体内发现的磷酸化蛋白质组学方法 底物（Aim 2）和预测计算模型的数据驱动设计的光遗传学方法（Aim 3）。