Chemical Imaging of RNA-Tau Amyloid Fibrils at the Nanoscale Using Tip-Enhanced Raman Spectroscopy.

In the presence of cofactors, tau protein can form amyloid deposits in the brain which are implicated in many neurodegenerative disorders. Heparin, lipids, and RNA are used to recreate tau aggregates in vitro from recombinant protein. However, the mechanism of interaction of these cofactors and the interactions between cofactors and tau are poorly understood. Herein, we use tip-enhanced Raman spectroscopy (TERS) to visualize the spatial distribution of adenine, protein secondary structure, and amino acids (arginine, lysine and histidine) in single polyadenosine (polyA)-induced tau fibrils with nanoscale spatial resolution (<10-20 nm). Based on reference unenhanced and surface-enhanced Raman spectra, we show that the polyA anionic cofactor is incorporated in the fibril structure and seems to be superficial to the ß-sheet core, but nonetheless enveloped within the random-coiled fuzzy coat. TERS images also prove the colocalization of positively charged arginine, lysine, and histidine amino acids and negatively charged polyA, which constitutes an important step forward to better comprehend the action of RNA cofactors in the mechanism of formation of toxic tau fibrils. TERS appears as a powerful technique for the identification of cofactors in individual tau fibrils and their mode of interaction.

Discrimination of human and animal bloodstains using hyperspectral imaging.

Blood is the most encountered type of biological evidence in violent crimes and contains pertinent information to a forensic investigation. The false presumption that blood encountered at a crime scene is human may not be realised until after costly and sample-consuming tests are performed. To address the question of blood origin, the novel application of visible-near infrared hyperspectral imaging (HSI) is used for the detection and discrimination of human and animal bloodstains. The HSI system used is a portable, non-contact, non-destructive method for the determination of blood origin. A support vector machine (SVM) binary classifier was trained for the discrimination of bloodstains of human (n = 20) and five animal species: pig (n = 20), mouse (n = 16), rat (n = 5), rabbit (n = 5), and cow (n = 20). On an independent test set, the SVM model achieved accuracy, precision, sensitivity, and specificity values of 96, 97, 95, and 96%, respectively. Segmented images of bloodstains aged over a period of two months were produced, allowing for the clear visualisation of the discrimination of human and animal bloodstains. The inclusion of such a system in a forensic investigation workflow not only removes ambiguity surrounding blood origin, but can potentially be used in tandem with HSI bloodstain age determination methods for rapid on-scene forensic analysis.