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Updated: Jun 8, 2026

Exploring the Application of Surface-enhanced Raman Scattering-based Biosensing of Individual sEVs in Disease Diagnosis and Therapeutics
Published on: March 13, 2026
Identification of individual genotypes of measles virus using surface enhanced Raman spectroscopy
Vinh Hoang1, Ralph A Tripp, Paul Rota
1Department of Chemistry, University of Georgia, Athens, GA 30602, USA.
Abstract:
A spectroscopic assay based on surface-enhanced Raman spectroscopy (SERS) has been developed for rapid genotyping of the measles virus (MeV). Silver nanorods fabricated using an oblique angle vapor deposition method acted as the SERS-active substrate. The SERS spectra of four separate MeV genotypes, i.e. A, H1, D4 and D9, and two separate negative media control samples were analyzed using multivariate statistical methods. Principal components analysis (PCA) and hierarchical cluster analysis (HCA) successfully separated three of the four MeV genotypes studied. The MeV genotypes used in this study had >96% sequence similarity as monitored using the MeV hemagglutinin (H) gene, and the clustering seen in PCA and HCA mirrored this sequence diversity. For example, the MeV genotypes with the highest sequence diversity (~3%, A and H1) were the most widely separated in the PCA scores plot and HCA dendogram. Conversely, the MeV genotypes with the lowest sequence diversity (~0.5%, D4 and D9) could not be statistically differentiated. However, a supervised chemometric method, partial least squares-discriminant analysis (PLS-DA) was able to separate each of the four MeV strains, the two negative controls, and the background, with >90% sensitivity and >96% selectivity based solely on their inherent SERS spectra. These results demonstrate that SERS, in combination with multivariate statistical methods, is a highly sensitive and rapid viral identification and classification method that can be applied to MeV genotyping.
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