A biopolymer encapsulated with silver nanoparticles was prepared using silver nitrate, polyvinyl alcohol (PVA) solution, and trisodium citrate. It was deposited on a mica sheet to use as SERS substrate. Fresh cultures of Salmonella Typhimurium, Escherichia coli, Staphylococcus aureus and Listeria innocua were washed from chicken rinse and suspended in 10 ml of sterile deionized water. Approximately 5 μl of the bacterial suspensions was placed on the substrate individually and exposed to 785 nm HeNe laser excitation. SERS spectral data were recorded over the Raman shift between 400 and 1800 cm(-1) from 15 different spots on the substrate for each sample; and three replicates were done on each bacteria type. Principal component analysis (PCA) model was developed to classify foodborne bacteria types. PC1 identified 96% of the variation among the given bacteria specimen, and PC2 identified 3%, resulted in a total of 99% classification accuracy. Soft Independent Modeling of Class Analogies (SIMCA) of validation set gave an overall correct classification of 97%. Comparison of the SERS spectra of different types of gram-negative and gram-positive bacteria indicated that all of them have similar cell walls and cell membrane structures. Conversely, major differences were noted around the nucleic acid and amino acid structure information between 1200 cm(-1) and 1700 cm(-1) and at the finger print region between 400 cm(-1) and 700 cm(-1). Silver biopolymer nanoparticle substrate could be a promising SERS tool for pathogen detection. Also this study indicates that SERS technology could be used for reliable and rapid detection and classification of food borne pathogens.
Keywords: E. coli; Listeria innocua; Principal component analysis; Salmonella Typhimurium; Staphylococcus aureus; Surface enhanced Raman scattering.
Published by Elsevier B.V.