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.

抽象的该项目的长期目标是了解细胞如何了解和过程信号做出命运决定在正常的人类发育和发育疾病中，无论是在复杂组织中的模式。胚胎模式和形态发生的组织如何是发展的基本问题生物学。该应用程序将在人类胚胎的轴向伸长的背景下解决这个问题在开发过程中，它破坏了前后验（A-P）对称性，向后形成尾扣，并且沿A-P轴伸长。尾芽中的祖细胞扩散以驱动这一延伸和进一步区分产生神经和中胚层细胞类型。该建议旨在了解轴向伸长率是驱动的，即使它们是如何保持自我维持的池，即使它们分化为神经和中胚层细胞。由于人类轴向伸长的基础机制和在其他脊椎动物之间并未共享图案，而是模型生物的结果的普遍性人类仍然未知。虽然道德原因需要使用人类体外模型开发，这种类器官系统的巨大变化一直是一个关键的障碍。初步工作克服了这一障碍，以惊人的和可重复地模拟人类的轴向形态发生和通过开发一个细胞系统来形成图案，该系统会伸长以产生后神经管和侧翼近期中胚层。该提案使用这个强大的系统，试图回答两个基本问题与此过程相关联：首先，形态学信号如何破坏A-P对称性并稳定驱动自我维持沿单个轴的轴向伸展。目的是揭示激活为驱动自我维持的轴向伸长，并了解该系统如何缓冲噪声，以免易受动态不稳定性，例如，导致分支或多个轴。第二个是确定管理尾袋中祖细胞增殖池维持的动态系统整个轴向伸长，即使它们被驱动到神经和中胚层组织中。这提案汇集了推断和测量基因表达的时空特征的方法。比较这些与其他模型生物的特征以确定基因表达模式的相似性和差异驱动轴向伸长和贝叶斯合奏建模，以构建GRN驱动轴向的预测模型伸长和实验工具测试模型预测。该提案将使我们能够实现定量了解从细胞内信号传导和转录调控到跨尺度的动力学的理解细胞重排向组织水平的轴向延伸，由新的人类干细胞系，成像，图像处理，统计推断，数学建模和生物工程工具，以提供见解纳入管理人类轴向伸长的原则。建立和测试定量预测模型的能力人轴向扩展将开放新的途径，以理解人类疾病的基础机制。