Aggregation is a pathological hallmark of proteinopathies such as Alzheimer's disease and results in the deposition of β-sheet-rich amyloidogenic protein aggregates. Such proteinopathies can be classified by the identity of one or more aggregated proteins, with recent evidence also suggesting that distinct molecular conformers (strains) of the same protein can be observed in different diseases, as well is in subtypes of the same disease. Therefore, methods for the quantification of pathological changes in protein conformation are central to understanding and treating proteinopathies. In this work, the evolution of Raman spectroscopic molecular signatures of three conformationally distinct proteins, bovine serum albumin (α-helical-rich), β2-microglobulin (β-sheet-rich), and tau (natively disordered), was assessed during aggregation into oligomers and fibrils. The morphological evolution was tracked using atomic force microscopy and corresponding conformational changes were assessed by their Raman signatures acquired in both wet and dried conditions. A deconvolution model was developed which allowed us to quantify the conformation of the nonregular protein tau, as well as for the oligomeric and fibrillar species of each of the proteins. Principle component analysis of the fingerprint region allowed further identification of the distinguishing spectral features and unsupervised distinction. While an increase in β-sheet is seen on aggregation, crucially, however, each protein also retains a significant proportion of its native monomeric structure after aggregation. Thus, spectral analysis of each aggregated species, oligomeric, as well as fibrillar, for each protein resulted in a unique and quantitative "conformational fingerprint". This approach allowed us to provide the first differential detection of both oligomers and fibrils of the three different amyloidogenic proteins, including tau, whose aggregates have never before been interrogated using spontaneous Raman spectroscopy. Quantitative "conformational fingerprinting" by Raman spectroscopy thus demonstrates its huge potential and utility in understanding proteinopathic disease mechanisms and for providing strain-specific early diagnostic markers and targets for disease-modifying therapies.
Keywords: Alzheimer’s disease; Raman spectroscopy; amyloid; neurodegenerative diseases; protein aggregation; protein conformation.