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Two PhD Projects available in the Phase Transitions in Health and Disease lab @IBEC
1. Drug screening for personalised medicine in Alzheimer’s Disease: thousands of molecules and thousands of protein variants
Alzheimer’s disease, the leading cause of dementia, affects 55 million people world-wide. Unfortunately, the search of therapies able to prevent or treat Alzheimer’s disease has faced 30 years of failed clinical trials. Familial forms of AD are caused by mutations in the amyloid-beta peptide speed up the aggregation of the peptide into amyloid fibrils. One of the challenges in developing molecules able to prevent amyloid-beta aggregation is that the process of amyloid nucleation is extremely difficult to characterise in vitro. It is even more difficult to envision methods that can do this at scale, i.e. approaches able to scan many molecules and to parallel asses their activity on all amyloid beta variants. We have developed a massively parallel reporter of amyloid nucleation which provides an excellent platform to screen for molecules and mechanisms able to prevent nucleation in vivo (Seuma et al 2021, Seuma et al 2022). This translational project will make use of this approach and involve three phases: 1) optimisation of our high-throughput in-vivo system for the uptake of small molecules; 2) screening of chemical libraries for their impact on amyloid nucleation; 3) validation of the top hits against all possible amyloid beta variants. As a result, we will be able to identify small molecules able to tamper the microscopic mechanism that is leading to AD.
1. MAVEs to systematic understand and predict amyloid formation in human disease
Amyloid fibrils form and precipitate in more than 50 incurable human diseases, including Alzheimer’s and Parkinson’s disease. While all proteins may be able to form amyloids, at least under certain circumstances, protein aggregation into fibrils is actually rare as the process of amyloid formation is controlled by a high kinetic barrier: protein sequences have to cross a free energy barrier to nucleate transition states which then seed irreversible fibril formation. These initial events in amyloid formation are particularly challenging to study by classic biophysical methods, due to the transient and high-energy nature of transition states. They are also likely the most critical steps to systematically study and understand as these are the events to target in order to prevent or slow down amyloid formation for therapeutic purposes. We have developed a massively parallel genomics approach that is able to quantify the rate of aggregation of thousands of protein sequences in parallel. We also proved that this multiplex assay of variant effects (MAVE) accurately classifies missense mutations in Amyloid Beta (Aß) that are known to cause familial forms of Alzheimer’s disease, as well as the effects of distinct types of genetic variation, such as insertions and deletions (Seuma et al 2021, Seuma et al 2022). By employing the same approach on the islet amyloid polypeptide (IAPP), the peptide that aggregates in >90% cases of Type-II diabetes, we find that the impact of mutations broadly resembles that observed for Aß as, in both cases, mutations that increase the propensity of the peptides to aggregate are enriched in those regions that remain unstructured in mature fibrils. However, the specific amino acid changes increasing aggregation change quite radically between the two peptides, making it challenging to use the results of one MAVE to accurately predict mutational impact in another sequence. In this project, we will generate MAVEs for all human amyloids and employ them for clinical variant interpretation. The Project will involve large screening of mutational libraries in the first phase, followed by data analysis and comparison of mutational effects with existing datasets (e.g. UK Biobank) and high-resolution phenotypic validation in disease specific cell types.
The lab: Phase Transitions in Health and Disease
Our lab at IBEC has a wide set of expertise ranging from genetics and molecular biology to biophysics and bioinformatics. As a student in our lab, you will get exposed to all of these disciplines. Most of the projects in the lab involve deep mutational scanning, but lab members are able to choose the appropriate system and approach for their specific question and for each stage of their project. This creates a highly inter-disciplinary environment, with many members of the lab using both computational and experimental approaches. Therefore, a strong interest in developing both experimental and computational skills is required. Experience with genomics, yeast genetics and bioinformatics will be beneficial. More specifically, in this project, you will also learn how to logistically organize a high-throughput screening platform. Our PhD students are encouraged and supported to “think big”, be ambitious and independent.
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