The pathogenesis underlining many neurodegenerative diseases remains incompletely understood. The lack of effective biomarkers and disease preventative medicine demands the development of new techniques to efficiently probe the mechanisms of disease and to detect early biomarkers predictive of disease onset. Raman spectroscopy is an established technique that allows the label-free fingerprinting and imaging of molecules based on their chemical constitution and structure. While analysis of isolated biological molecules has been widespread in the chemical community, applications of Raman spectroscopy to study clinically relevant biological species, disease pathogenesis, and diagnosis have been rapidly increasing since the past decade. The growing number of biomedical applications has shown the potential of Raman spectroscopy for detection of novel biomarkers that could enable the rapid and accurate screening of disease susceptibility and onset. Here we provide an overview of Raman spectroscopy and related techniques and their application to neurodegenerative diseases. We further discuss their potential utility in research, biomarker detection, and diagnosis. Challenges to routine use of Raman spectroscopy in the context of neuroscience research are also presented.

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 protein, with recent evidence also suggesting that distinct molecular conformers (strains) of the same protein can be observed in different diseases, as well is in sub-types 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-sheetrich) 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 non-regular 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.

We report that the physiochemical properties of the aggregation environment dictate the conformation of tau strains, which can be characterized and distinguished using Raman spectroscopy.

Current methods for diagnosing acute and complex infections mostly rely on culture-based methods and, for biofilms, fluorescence in-situ hybridization. These techniques are labor-intensive and can take 2-4 days to return a test result, especially considering an extra culturing step required for the antibiotic susceptibility testing (AST). This places a significant burden on healthcare providers, delaying treatment and leading to adverse patient outcomes. Here, we report the complementary use of our newly developed multi-excitation Raman spectroscopy (ME-RS) method with whole-genome sequencing (WGS). Four WHO priority pathogens are AST phenotyped and their antimicrobial resistance (AMR) profile determined by WGS. On application of ME-RS method we find high correlation with the WGS characterization. Highly accurate classification based on the species (98.93%), wild-type/non-wild type (99.45%), and presence or absence of thick peptidoglycan layers in cell walls (100%), as well as at the individual strain level (99.29%). These results clearly demonstrate the potential of ME-RS as a rapid and first-stage tool for species, resistance and strain-level classification which can be followed up by WGS for confirmation. Such a workflow can facilitate efficient antimicrobial stewardship to handle and prevent the spread of AMR.

Specific proteins and their aggregates form toxic amyloid plaques and neurofibrillary tangles in the brains of people suffering from neurodegenerative diseases such as Alzheimer’s and Parkinson’s. It is important to study these conformational changes to identify and differentiate these diseases at an early stage so that timely medication is provided to patients. Mid-infrared spectroscopy can be used to monitor these changes by studying the line-shapes and the relative absorbances of amide bands present in proteins. This work focusses on the spectroscopy of the protein, Bovine Serum Albumin as an exemplar, and its aggregates using germanium on silicon waveguides in the 1900–1000 cm −1 (5.3–10.0 µm) spectral region.