Our work aims to understand how embryos communicate instructions to their cells. We work primarily with zebrafish embryos and human stem cells as model systems. Our approaches draw from classical embryology, fluorescence microscopy, optogenetics and mathematical modeling. We like problems that require us to invent new techniques. We’re interested in recruiting curious, optimistic people from biology, physics, engineering and mathematics.
Noise and robustness in development
Embryonic development is a marvel of coordination. The embryo seamlessly directs the fates, movements and growth of each of its cells, ensuring that development succeeds. This feat of control is remarkable in light of recent discoveries demonstrating that the core biological process underlying development— gene expression, signaling and cell fate decisions— are fundamentally noisy. How do embryos build an orderly developmental process out of noisy parts? How are the correct number and types of cells generated? Do embryos have mechanisms to correct mistakes when they arise? We aim to understand the mechanisms that allow embryos to develop reliably in the face of noise and unexpected perturbations.
Mechanisms of developmental pattern formation
Embryos communicate instructions to their cells by creating precise patterns of signaling and gene expression. Our lab is interested in dissecting the molecular circuits that make these patterns. Specifically, we want to (1) determine how developmental signaling is propagated through space and (2) understand how feedback on signaling ensures that the correct patterns are formed every time.
Decoding the language of developmental signaling
Embryonic cells infer instructions from the dynamics and distribution of signaling activity in their local neighborhood. Despite decades of study, it remains unclear what features of signaling cells ‘pay attention to’ when making decisions. Our lab will use cutting-edge optogenetics methods to decode the language of developmental signaling in live embryos. Over the long run, we hope to inform tissue engineering by learning to communicate precise instructions to in vitro developmental systems.