Modelling neuronal trafficking and survival to predict the progression of neurodegenerative diseases

DTP overview:
This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to address hypothesis-led biomedical research questions. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice.

Project overview:
Dementia caused by Alzheimer's disease is an insidious process, and damage to the brain can often go unnoticed until cognitive impairment manifests itself in an obvious and diagnosable manner (e.g., memory loss). Whilst everyone ages and whilst ageing is a risk factor for Alzheimer's, dementia is not a necessary outcome of growing old. The progression of Alzheimer's disease is not well characterised, and whilst there currently isn't a cure for Alzheimer's, there are mitigating therapeutics which are more effective when implemented sooner rather than later through early detection.

A key molecule in preventing our brain cells from dying is Brain-derived neurotrophic factor (BDNF). Under Alzheimer's, this molecule's function slowly degrades as it's unable to move through our brain cells effectively - leading to our brain cells slowly shrinking and dying. If we could model how the process of Alzheimer's initiates the degradation of BDNF's function, this may help bring some clarity towards how the complex network of our brain cells begin to collapse in dementia. A novel and insightful way to model this collapse is as a communication network that becomes less reliable, i.e., modelling the brain as if it were a degrading computer network.

This project aims to use molecular communications modelling to follow the deterioration of BDNF's function through Alzheimer's. This may subsequently be used to make predictions on the health and connectivity of our brain cells, which may help better characterise the progression of our brain network collapse. To evaluate the model's accuracy, there will be coinciding experimental validation using cell cultures exerted under varying relevant conditions. The student will be required to generate, test, analyse, and validate the BDNF model, combining both computational modelling and experimental cell culture work.