Measuring and modeling the dynamics ofpatterning in human stem cells

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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.