Surface-Enhanced Raman Spectroscopy Method

Abstract

Surface-enhanced Raman scattering (SERS) in combination with advanced multivariate methods for pattern recognition has been used for rapid, sensitive, and accurate identification of miRNAs. The strength of the SERS-based sensor is its sensitivity to detect extremely low levels of analyte and specificity to provide the molecular fingerprint of the analyte. The SERS spectra of related and unrelated miRNAs can be detected in near-real time; that detection is sequence dependent, and that SERS spectra can be used to classify miRNA patterns with high accuracy. This technique requires oblique-angle deposition (OAD) fabrication of nanostructured SERS substrate, spotting of RNA or miRNA onto the SERS substrate, and measurement of SERS spectra, followed by classification of the SERS spectra using partial least squares discriminate analysis (PLS–DA). The first application of this technique to miRNA profiling was made recently by Driskell et al. from the Department of Infectious Diseases, Center for Disease Intervention, University of Georgia (AHRC, USA) (Biosens Bioelectron 24:923–928, 2008). This technology is well suited for routine miRNA expression profiling in clinic laboratory. However, the SERS technique requires sophisticated read-out system, complicated analysis skill, and convoluted data interpretation and verification, which requires highly trained professionals to handle.