Measuring and modeling the dynamics ofpatterning in human stem cells

摘要 这个项目的长期目标是了解细胞如何感知和处理信号来做出命运决定 并形成复杂的组织，无论是在正常的人类发育过程中还是在发育性疾病中。 胚胎组织如何进行形态发生是发育过程中的一个基本问题 生物学。这项申请将在人类胚胎的轴向延长的背景下解决这个问题 在发育过程中，它打破前后(A-P)对称性，在后面形成尾芽，并 沿A-P轴拉长。尾芽中的祖细胞增殖以驱动这一延伸并进一步 分化形成神经细胞和中胚层细胞类型。这项提议旨在了解轴向 伸长是驱动的，以及尾芽中的祖细胞如何维持一个自我维持的池，即使它们 分化为神经细胞和中胚层细胞。由于人类轴向伸长的潜在机制和 模式不在其他脊椎动物之间共享，模式生物的结果可以推广到 人类仍然不为人知。虽然出于伦理原因，有必要使用人类的体外模型 尽管这类有机物系统的发展具有很大的可变性，但它一直是一个严重的障碍。 初步工作克服了这一障碍，以惊人的和可重复的方式模拟人类的轴向形态发生和 通过开发一个有机系统来形成图案，该系统可以伸长以产生后神经管和侧翼 近轴中胚层。利用这一强大的系统，该提案试图回答两个基本问题 与这一过程相关的是：第一，形态信号如何打破A-P对称性并稳定地驱动自我维持 沿单一轴的轴向延伸。目标是发现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，以避免 易受动力不稳定性的影响，例如，导致分支或多个轴。第二个是 确定维持尾芽中增殖的祖细胞池的动力系统 在整个轴向伸长过程中，即使它们被驱动分化为神经和中胚层组织。这个 Proposal集合了各种方法来推断和测量基因表达的时空分布；比较 这些图谱与其他模式生物一起确定基因表达模式的相似性和差异性 驱动轴向伸长和贝叶斯系综建模以建立GRN驱动轴向的预测模型 延伸率和测试模型预测的实验工具。这项提议将使我们能够实现 理解跨尺度的动态，从细胞内信号和转录调控到 通过新的人类干细胞系，成像，使细胞重排成为可能 图像处理、统计推断、数学建模和生物工程工具，以提供见解 变成了控制人类轴向伸长的原则。构建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。

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.