Abstract

During development axons have to find their correct targets in order to ensure the accurate wiring and function of the peripheral nervous system. Despite depending upon this precision, variability during the process can be observed experimentally. The path-finding mechanism of axons requires coordination between specific combinations of cues and their receptors that they use to navigate. Although numerous guidance cues have been analyzed, the exact interactions and mechanisms behind growth cone movement and its variability remain unclear. We have created a stochastic model of human growth cone navigation that simulates the cellular processes guiding growth cone turning in response to guidance cues and that also captures its variability. In the model each filopodium is represented as a membrane protrusion of the cytoskeleton studded with receptors and simulated by a stochastic linear kinetic reaction that grows or shrinks the filopodium in response to the relative signal strength of each receptor. We model stoichiometry of each receptor and assume it only influences the growth of the closest filopodium. Our growth cone model reproduces the unequal partition ratios caused by the stochastic nature of the mechanism and can therefore be used to analyze variability in axon growth. We validate the parameters with experimental data obtained from cortical and spinal commissural neurons in mice and rats cultivated on controlled nano-dot gradients of signaling cues, which allows for a quantitative analysis as compared to the usual gradients with diffusive cues. This is joint work with my grad student Marta Garnelo and our experimental McGill colleagues Seb Ricoult, David Juncker and Tim Kennedy.