Staphylococcus epidermidis is considered major cause of nosocomial infections. Its pathogenicity is mainly due to the ability to form biofilms on different surfaces, particularly indwelling medical devices. This bacterium consists of different strains consisting of non, medium and strong biofilm forming ones. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique that can be used to detect and analyze biochemical composition of the supernatant samples of different strains of bacteria including non, medium and strong biofilm forming bacterial strains. SERS is a powerful technique for the robust, reliable, rapid detection and discrimination of bacteria in the form of characteristic SERS spectral features which can be used for detection and classification. SERS is used to differentiate three classes of bacteria with respect to their biofilm forming ability. Silver nanoparticles (Ag NPs) are used as SERS substrate and synthesized with chemical reduction method. Principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) are used to discriminate SERS spectral data sets of non, medium and strong biofilm forming bacteria. PLS-DA analysis is a multivariate statistical technique that can be used to analyze data from bacterial sets.
Keywords: Biofilm formation; Partial least square discriminant analysis; Staphylococcus epidermidis; Surface-enhanced Raman spectroscopy.
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