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

Fernanda S. de Siqueira e Oliveira; Hector E. Giana; Landulfo Silveira Jr.

doi:10.1117/12.910439

22 February 2012 Discrimination of selected species of pathogenic bacteria using near-infrared Raman spectroscopy and principal components analysis

Fernanda S. de Siqueira e Oliveira, Hector E. Giana, Landulfo Silveira Jr.

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Proceedings Volume 8214, Advanced Biomedical and Clinical Diagnostic Systems X; 821409 (2012) https://doi.org/10.1117/12.910439
Event: SPIE BiOS, 2012, San Francisco, California, United States

Abstract

It has been proposed a method based on Raman spectroscopy for identification of different microorganisms involved in bacterial urinary tract infections. Spectra were collected from different bacterial colonies (Gram negative: E. coli, K. pneumoniae, P. mirabilis, P. aeruginosa, E. cloacae and Gram positive: S. aureus and Enterococcus sp.), grown in culture medium (Agar), using a Raman spectrometer with a fiber Raman probe (830 nm). Colonies were scraped from Agar surface placed in an aluminum foil for Raman measurements. After pre-processing, spectra were submitted to a Principal Component Analysis and Mahalanobis distance (PCA/MD) discrimination algorithm. It has been found that the mean Raman spectra of different bacterial species show similar bands, being the S. aureus 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 good sensitivity and high specificity.

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Fernanda S. de Siqueira e Oliveira, Hector E. Giana, and Landulfo Silveira Jr. "Discrimination of selected species of pathogenic bacteria using near-infrared Raman spectroscopy and principal components analysis", Proc. SPIE 8214, Advanced Biomedical and Clinical Diagnostic Systems X, 821409 (22 February 2012); https://doi.org/10.1117/12.910439

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KEYWORDS

Raman spectroscopy

Bacteria

Principal component analysis

Mahalanobis distance

Microorganisms

Spectroscopy

Pathogens

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