What goes wrong in Alzheimer's disease? Elucidating pathology-driven synaptic signalling defects in brain circuits. (Project no 2253)

Lead Research Organisation: University of Sussex
Department Name: Sch of Life Sciences

Abstract

A hallmark of Alzheimer's disease (AD) is the accumulated failure of normal synaptic function, an event associated with catastrophic cognitive decline. However, remarkably little is known about the fundamental events responsible. This lack of understanding makes it challenging to identify suitable therapeutic targets. An exciting but largely untested hypothesis is that key AD-related defects are linked to changes in the properties of the neurotransmitter-containing vesicles themselves. Synaptic vesicles are small spherical organelles organized in clusters at specialized sites in the presynaptic terminal which are responsible for most information transmission in the brain. Using highly-sensitive fluorescent proteins and high-resolution cameras, we can now directly and dynamically track these vesicles, their associated proteins and the transmitter release events that they facilitate. In this way, it is possible to gain significant new understanding of what goes wrong in signalling in the brain in Alzheimer's disease mouse models. The project will also exploit state-of-the-art high-pressure freezing technology that permits extraordinary preservation of synaptic structures for nanoscale investigation. The logic for targeting vesicle pools builds on extensive high-profile research in our lab showing that these are key control points for setting and adjusting the signalling properties of synapses in basal activity and plasticity. Here we hypothesize that changes to specific pool properties in central and retinal neurons; their size, their physical arrangement, and the speed they are used and re-used during neuronal activity, explains key neuronal signalling deficits seen in AD. In this project you will use a range of cutting-edge techniques, including optical imaging, electrophysiology and machine-learning analysis approaches, to identify how synapses go wrong. You will then test synaptically-targeted compounds to try and restore function and therefore offer possible avenues for disease therapy. This PhD will provide a talented student with a great opportunity for a neuroscience career.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/T008768/1 01/10/2020 30/09/2028
2766121 Studentship BB/T008768/1 01/10/2022 30/09/2026