Surface-enhanced Raman spectroscopy for the rapid identification of fosfomycin resistant and sensitive strains of E. coli.

Development of rapid detection and discrimination technique for the antibiotic resistant and sensitive bacterial strains is required for this purpose, Surface-enhanced Raman spectroscopy (SERS) technique is considered to have great potential. To develop a fast and sensitive detection and discrimination methodology based on SERS technique along with chemometric tools for the differentiation among fosfomycin sensitive and resistant Escherichia coli (E. coli) strains. In this research work, three E. coli strains resistant to fosfomycin with three fosfomycin sensitive E. coli strains were characterized in which silver nanoparticles were employed as SERS substrate. Moreover, MATLAB 7.8 (2009a) was used for the preprocessing, baseline correction and normalization of SERS spectra. Using principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA), several E. coli strains were identified on the basis of their distinctive SERS spectral properties. The differentiating SERS spectral features which can be associated with the resistance and sensitivity against fosfomycin antibiotic, are obtained by comparing mean SERS spectrum of strains of resistant E. coli with sensitive E. coli strains. Chemometric techniques, such as principal components analysis, have been proven effective for qualitative analysis. Additionally, PLSDA was employed to classify the SERS spectra acquired from the pellets of several bacterial strains. SERS is a useful analytical method for quickly differentiating between E. coli strains that are sensitive to fosfomycin and those that are resistant to it.