Biochemical characterization of pathogenic bacterial species using Raman spectroscopy and discrimination model based on selected spectral features.

This study aimed to evaluate the differences in the Raman spectra of nine clinical species of bacteria isolated from infections (three Gram-positive and six Gram-negative species), correlating the spectra with the chemical composition of each species and to develop a classification model through discriminant analysis to categorize each bacterial strain using the peaks with the most significant differences. Bacteria were cultured in Mueller Hinton agar and a sample of biomass was harvested and placed in an aluminum sample holder. A total of 475 spectra from 115 different strains were obtained through a dispersive Raman spectrometer (830 nm) with exposure time of 50 s. The intensities of the peaks were evaluated by one-way analysis of variance (ANOVA) and the peaks with significant differences were related to the differences in the biochemical composition of the strains. Discriminant analysis based on quadratic distance applied to the peaks with the most significant differences and partial least squares applied to the whole spectrum showed 89.5% and 90.1% of global accuracy, respectively, for classification of the spectra in all the groups. Raman spectroscopy could be a promising technique to identify spectral differences related to the biochemical content of pathogenic microorganisms and to provide a faster diagnosis of infectious diseases.

Discrimination of selected species of pathogenic bacteria using near-infrared Raman spectroscopy and principal components analysis.

ABSTRACT. A method, based on Raman spectroscopy, for identification of different microorganisms involved in bacterial urinary tract infections has been proposed. Spectra were collected from different bacterial colonies (Gram-negative: Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Pseudomonas aeruginosa and Enterobacter cloacae, and Gram-positive: Staphylococcus aureus and Enterococcus spp.), grown on culture medium (agar), using a Raman spectrometer with a fiber Raman probe (830 nm). Colonies were scraped from the agar surface and placed on an aluminum foil for Raman measurements. After preprocessing, spectra were submitted to a principal component analysis and Mahalanobis distance (PCA/MD) discrimination algorithm. We found that the mean Raman spectra of different bacterial species show similar bands, and S. aureus was well characterized by strong bands related to carotenoids. PCA/MD could discriminate Gram-positive bacteria with sensitivity and specificity of 100% and Gram-negative bacteria with sensitivity ranging from 58 to 88% and specificity ranging from 87% to 99%.