The self-assembly of prion precursors into oligomers and fibers has been linked to several neurodegenerative and systemic disorders. In particular, the aggregation of Amyloid-β (Aβ), tau and a-synuclein proteins in brain tissue have been associated with the neuropathological process of Alzheimer’s (AD) and Parkinson’s disease (PD). Numerous studies have shown that not only can these aggregates propagate from cell-to-cell in a prion-like manner, but their toxicity and linked pathology strongly depends on their conformations which define different strains of amyloid. Furthermore, the characterization of the biologically relevant strains is difficult to determine experimentally.
To overcome this problem, I investigated the molecular determinants of amyloid aggregation. I designed and implemented a signal processing pipeline for the analysis solid state NMR and spectroscopic data that allowed differentiating strains of fibrils relevant to neurodegenerative diseases.
For the first time, the heterogeneity and the variability in patient brain samples could be quantified. This understanding should lay groundwork for the development of effective treatments for neurodegenerative diseases linked to prions, such as Alzheimer’s and Parkinson’s diseases. I am currently improving this pipeline by integrating concepts from machine learning at the Eidgenössische Technische Hochschule Zürich (ETH Zurich).