Glutamate diffusion and AMPA receptor activation in the cerebellar glomerulus
Glutamate release onto a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) is the primary mechanism of fast synaptic transmission in the mammalian brain. Previous studies have revealed that at the cerebellar mossy-fibre to granule cell synapse, the AMPAR mediated synaptic current con sists of a fast-rising and a slow-rising component. The aim of this thesis is to examine the properties of release, diffusion and receptor activation underlying these two components. Two plausible mechanisms could underlie the slow-rising current: spillover of glutamate from neighbouring synaptic contacts and prolonged local release of glutamate via a narrow fusion pore. Using simulations of glutamate diffu sion and receptor activation, I show that lowering the diffusion coefficient of glutamate in the synaptic cleft (Dgjut), which is unknown but can be modulated with macromolecules, has different effects on currents mediated by these two mechanisms. Recordings of the effect of perfusion of dextran (43 kDa) are consis tent with the spillover model and also indicate that Dgiut is approximately 3-fold lower than in free solution. I show using simulations that linear diffusion cannot alone account for the acceleration of the decay of the synaptic current observed at this synapse in lower release probability, but that it can result from non-linear activation of AMPARs. Evidence is presented that diffusion is linear and only one vesicle is released per active zone. In addition, I have extended the diffusion-reaction model of the synapse to develop a framework for examining properties of synaptic AMPARs using glutamate uncaging. I demonstrate that certain kinetic properties of synap tic receptors can be measured using this technique and derive a kinetic model based on preliminary data. Together, these data fill shortcomings in our understanding of synaptic func tion. Based on the present results, I construct a model of synaptic transmission that explains previous observations.