Research: Overview and Philosophy
Biologists have made astonishing progress in identifying and characterizing the molecular networks of that both regulate and implement developmental processes. The challenge we face now is to comprehend how these networks operate, in the physical context of living embryos, to orchestrate the cell and tissue-level behaviors that unfold a functional organism from a fertilized egg. Our efforts to address this challenge focus in two main areas:
1) Dynamics of cell polarization and cytokinesis in early embryos of the nematode worm C. elegans.
- How do interactions among conserved polarity determinants known as Par proteins, small GTPases and the actomyosin cytoskeleton endow a single cell with the ability to establish and maintain molecular asymmetries in response to a transient polarizing cue?
- How does the same machinery organize to locate, form and then constrict a contractile ring in response to spatial signals from the mitotic apparatus?
2) Dynamics of tissue morphogenesis in Ascidians and fruit flies.
- How do the stereotyped patterns of cell shape change and rearrangement that form embryonic tissues emerge through the interplay between polarized actomyosin contractility, cell motility, and the dynamics of cell-cell adhesion?
We work at the interface between experimental and computational biology, combining quantitative microscopy, molecular genetic and physical manipulations, and detailed computer simulations. We use quantitative light microscopy to characterize the dynamics of cell and tissue level behaviors, and to characterize the organization and dynamics of the molecular machinery that governs these behaviors. We use multi-scale agent-based computer simulations to explore how the cell and tissue dynamics we observe might emerge from known or hypothesized molecular and subcellular properties and interactions - to develop intuition about the underlying mechanisms and to frame testable hypotheses. Finally, we use a combination of molecular, genetic, pharmacological and physical manipulations to test these hypotheses, thus closing an iterative cycle of modeling and experiment.