Systematic Multi-scale Analysis of Tissue Morphogenesis

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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.