# Measuring and modeling the dynamics ofpatterning in human stem cells

> **NIH NIH R01** · HARVARD UNIVERSITY · 2024 · $340,135

## Abstract

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 tool...

## Key facts

- **NIH application ID:** 10890895
- **Project number:** 5R01GM131105-06
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Sharad Ramanathan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $340,135
- **Award type:** 5
- **Project period:** 2019-01-11 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10890895

## Citation

> US National Institutes of Health, RePORTER application 10890895, Measuring and modeling the dynamics ofpatterning in human stem cells (5R01GM131105-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10890895. Licensed CC0.

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