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Measuring and modeling the dynamics ofpatterning in human stem cells

测量和模拟人类干细胞模式的动态

基本信息

批准号：
10734567
负责人：
Sharad Ramanathan
金额：
$ 34.01万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-01-11 至 2027-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10734567
关键词：
Address Agreement Anterior Automobile Driving Biomedical Engineering Buffers CRISPR interference Cell Line Cells Complex Data Defect Development Developmental Biology Embryo Ethics Etiology Feedback Fetal Tissues Fibroblast Growth Factor Gene Expression Gene Expression Profile Genes Genetic Goals Growth Human Human Development Image In Situ In Vitro Ligands Maintenance Measures Mesoderm Mesoderm Cell Methods Microscopy Modeling Molecular Biology Monitor Morphogenesis Morphology Mus Neural tube Neurons Noise Organoids Paraxial Mesoderm Pattern Predisposition Process Proliferating Proteins Reporter Reproducibility Research Role Signal Pathway Signal Transduction Source Spinal Cord Spinal Dysraphism System Tail Testing Tissues Transcriptional Regulation Tretinoin Undifferentiated Vertebrates WNT Signaling Pathway Work cell type developmental disease dynamic system embryo tissue embryonic stem cell experimental study gene regulatory network human disease human model human stem cells image processing in situ sequencing in utero in vitro Model in vivo insight knock-down mathematical model model organism morphogens neural novel optogenetics predictive modeling prevent progenitor receptor scoliosis self-renewal single cell sequencing somitogenesis spatiotemporal stem cells tool transcription factor transcriptome sequencing

项目摘要

Abstract The long-term goal of this project is to understand how cells sense and process signals to make fate decisions and pattern into complex tissues, both during normal human development and in developmental diseases. How tissues of the embryo pattern and undergo morphogenesis is a fundamental question in developmental biology. This application will address the question in the context of the axial elongation of the human embryo during development, during which it breaks anterior-posterior (A-P) symmetry, forms a tailbud posteriorly, and elongates along the A-P axis. The progenitors in the tail bud proliferate to drive this extension and further differentiate to give rise to neural and mesodermal cell types. This proposal aims to understand how axial elongation is driven and how the progenitor cells in the tailbud maintain a self-sustaining pool, even as they differentiate into neural and mesodermal cells. Since the mechanisms underlying human axial elongation and patterning are not shared between other vertebrates, the generalizability of results from model organisms to humans remains unknown. While ethical reasons necessitate the use of in vitro models of human development, the large variability in such organoid systems has been a critical barrier. Preliminary work overcame this barrier to strikingly and reproducibly model human axial morphogenesis and patterning by developing an organoid system that elongates to generate the posterior neural tube and flanking paraxial mesoderm. Using this powerful system, the proposal seeks to answer two fundamental questions associated with this process: first, how morphogen signals break A-P symmetry and stably drive self-sustaining axial extension along a single axis. The goal is to uncover the underlying dynamical system that is activated to drive self-sustaining axial elongation and to understand how this system buffers against noise so as not to be susceptible to dynamical instabilities, for example, leading to branched or multiple axes. The second is to determine the dynamical system governing the maintenance of a proliferating pool of progenitors in the tailbud throughout axial elongation, even as they are driven to differentiate into neural and mesodermal tissues. The proposal brings together methods to infer and measure spatiotemporal profiles of gene expression; compare these profiles with other model organisms to determine similarities and differences in gene expression patterns driving axial elongation, and Bayesian ensemble modeling to build predictive models of the GRN driving axial elongation and experimental tools to test model predictions. The proposal will allow us to achieve a quantitative understanding of the dynamics across scales, from intracellular signaling and transcriptional regulation to cellular rearrangement to tissue-level axial extension made possible by new human stem cell lines, imaging, image processing, statistical inference, mathematical modeling, and bioengineering tools, to provide insights into principles governing human axial elongation. The ability to build and test quantitative predictive models of human axial extension will open novel avenues to understanding the mechanisms underlying human diseases.

摘要该项目的长期目标是了解细胞如何感知和处理信号以做出命运决定在正常的人类发育和发育性疾病中，都可以形成复杂的组织。胚胎的组织是如何形成和经历形态发生的，这是胚胎发育过程中的一个基本问题。生物学本申请将在人类胚胎的轴向伸长的背景下解决该问题在发育过程中，它打破前后（A-P）对称，向后形成尾芽，沿沿着A-P轴伸长。尾芽中的祖细胞增殖以驱动这种延伸，并进一步分化产生神经和中胚层细胞类型。该建议旨在了解轴向延伸是驱动的，以及尾芽中的祖细胞如何维持自我维持的池，即使它们分化成神经和中胚层细胞。由于人体轴向伸长和模式在其他脊椎动物之间不共享，模式生物的结果的普遍性，人类仍然未知。虽然伦理原因需要使用体外模型的人然而，在这种类器官系统中的大的可变性一直是关键的障碍。初步工作克服了这一障碍，以惊人且可重复的方式模拟了人类轴向形态发生，通过发展一个类器官系统来形成图案，该系统伸长以产生后部神经管和侧翼近轴中胚层。利用这个强大的系统，该提案试图回答两个基本问题与此过程相关的：首先，形态发生信号如何打破A-P对称性并稳定地驱动自我维持沿单个轴沿着轴向延伸。目标是揭示被激活的潜在动力系统，驱动自我维持的轴向伸长，并了解该系统如何缓冲噪音，易受动态不稳定性的影响，例如，导致分支或多个轴。二是确定维持尾芽中祖细胞增殖池的动力系统在整个轴向伸长过程中，甚至当它们被驱动分化成神经和中胚层组织时。的提案汇集了推断和测量基因表达时空概况的方法;比较这些模式与其他模式生物，以确定基因表达模式的相似性和差异驱动轴伸长和贝叶斯集成建模，以建立GRN驱动轴的预测模型延伸和实验工具来测试模型预测。该提案将使我们能够实现一个量化的了解跨尺度的动态，从细胞内信号传导和转录调控，新的人类干细胞系，成像，图像处理，统计推断，数学建模和生物工程工具，以提供见解人体轴向伸长的原理建立和测试定量预测模型的能力人类的轴向延伸将为理解人类疾病的潜在机制开辟新的途径。