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

J Biomed Opt. 2012 Oct;17(10):107004. doi: 10.1117/1.JBO.17.10.107004.

Abstract

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%.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Bacteria / chemistry*
  • Bacteria / classification*
  • Principal Component Analysis / methods*
  • Sensitivity and Specificity
  • Spectroscopy, Near-Infrared / methods*
  • Spectrum Analysis, Raman / methods*