Math Biology Seminar: Ajay Chitnis

Damian Dalle Nogare, Jeffery Head, Katherine Somers, Miho Matsuda and Ajay B Chitnis. The posterior Lateral Line primordium (pLLp) migrates from the ear to the tip of the tail in the zebrafish embryo periodically depositing neuromasts to pioneer establishment of the posterior lateral line system. We have developed three sets of agent-based models of the pLLp to visualize how interactions between cells coordinate morphogenesis of the pLLp system. The first explores how the polarized expression of chemokine receptors, CXCR4b and CXCR7b, facilitates directed migration of the pLLp along a stripe of chemokine expression. A second model explores how polarized Wnt and FGF signaling systems coordinate morphogenesis and cell fate in the pLLp. A Wnt signaling system that dominates in the leading domain, helps maintain the mesenchymal morphology of leading cells, while driving expression of FGF ligands that periodically initiate FGF signaling centers in a trailing zone. FGF signaling initiates formation of protoneuromasts by promoting morphogenesis of epithelial rosettes and expression of atoh1a to determine specification of a hair cell progenitor at the center of protoneuromasts. Our model explores how interactions between Wnt and FGF signaling systems could establish a reaction diffusion system to initiate center-biased FGF signaling and atoh1a expression in developing protoneuromasts. In the context of this center-biased expression, Notch-mediated lateral inhibition ensures atoh1a and hair cell fate is restricted to the central cell. Finally, we have used high-resolution time-lapse imaging to track movement, fate and lineage of every cell in the pLLp. These observations are used to develop a quantitative agent-based model that illustrates how proliferation and a progressively shrinking Wnt system determine the deposition pattern of neuromasts from the migrating pLLp. Together, our models provide a platform to integrate what has been learnt from a wide range of experimental studies and they allow us to evaluate if current hypotheses are adequate to account for various phenomena. Failure of our models identifies gaps in our understanding and helps define testable hypothesis that can be evaluated by future experiments.