# Systematic Multi-scale Analysis of Tissue Morphogenesis

> **NIH NIH R01** · SLOAN-KETTERING INST CAN RESEARCH · 2020 · $366,457

## Abstract

Systematic Multi-scale Analysis of Tissue Morphogenesis
Recent progress in live imaging offers unprecedented opportunities to examine cellular behaviors and how cell-
cell interactions give rise to complex tissues in vivo. We propose to develop novel computational approaches
to analyze and synthesize the complex phenotypic data from live imaging and apply them to study how
collective cell behaviors mediate cell movement in tissue morphogenesis and achieve robust cell positioning.
We use C. elegans embryogenesis as our model, where we have developed techniques for high throughput
imaging and automated cell tracking that allow us to perturb hundreds of genes and conduct detailed lineage
analysis in thousands of embryos. We propose three aims. First, we will develop new algorithms for accurate
cell tracking in dense tissues, including a new method based on multi-color labeling of nuclei. Accuracy in cell
tracking is a major bottleneck in systematic analysis of individual cell behaviors, especially in dense tissues.
This effort will provide novel tools with improved accuracy, which in turn allows more effective analysis of
individual cell behaviors in large image datasets. Second, We will examine novel mechanisms that mediate cell
movement in tissue morphogenesis and achieve robust cell positioning. These include a novel form of
multicellular rosette where sequential edge contraction and resolution events mediate directional cell
movement. We also propose a novel model of robust cell positioning where cells assess their neighborhoods
and activate movement when a desired neighbor is missing. We will elucidate the underlying molecular and
cellular mechanisms combining genetic perturbations, systematic single-cell analysis and a novel method for
real-time tracking and optical manipulation of single cells. This study will broaden our understanding of
developmental noise control at the cellular and tissue levels. Third, We will develop a novel agent-based
modeling framework to integrate complex phenotypic data for multi-scale analysis of complex tissues. We will
develop a software package for general use beyond C. elegans. We will then apply it to examine lineage
differentiation and tissue morphogenesis in C. elegans embryogenesis based on the thousands of perturbed
embryos collected in this and our previous studies. In particular, we will further examine robustness in cell
positioning by integrating the model above with a PCP-like model of Wnt-based spindle control. This work will
provide a powerful tool to examine complex tissues across molecular, cellular and tissue levels, and further
insights on the robustness of tissue morphogenesis.

## Key facts

- **NIH application ID:** 9929616
- **Project number:** 5R01GM097576-09
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Zhirong Bao
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $366,457
- **Award type:** 5
- **Project period:** 2011-08-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9929616

## Citation

> US National Institutes of Health, RePORTER application 9929616, Systematic Multi-scale Analysis of Tissue Morphogenesis (5R01GM097576-09). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9929616. Licensed CC0.

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