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Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 63,
  • Issue 11,
  • pp. 1251-1255
  • (2009)

Fluorescence Spectroscopy for Rapid Detection and Classification of Bacterial Pathogens

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Abstract

This study deals with the rapid detection and differentiation of <i>Escherichia coli, Salmonella</i>, and <i>Campylobacter</i>, which are the most commonly identified commensal and pathogenic bacteria in foods, using fluorescence spectroscopy and multivariate analysis. Each bacterial sample cultured under controlled conditions was diluted in physiologic saline for analysis. Fluorescence spectra were collected over a range of 200–700 nm with 0.5 nm intervals on the PerkinElmer Fluorescence Spectrometer. The synchronous scan technique was employed to find the optimum excitation (λ<sub>ex</sub>) and emission (λ<sub>em</sub>) wavelengths for individual bacteria with the wavelength interval (Δλ) being varied from 10 to 200 nm. The synchronous spectra and two-dimensional plots showed two maximum λ<sub>ex</sub> values at 225 nm and 280 nm and one maximum λ<sub>em</sub> at 335–345 nm (λ<sub>em</sub> = λ<sub>ex</sub> + Δλ), which correspond to the λ<sub>ex</sub> = 225 nm, Δλ = 110–120 nm, and λ<sub>ex</sub> = 280 nm, Δλ = 60–65 nm. For all three bacterial genera, the same synchronous scan results were obtained. The emission spectra from the three bacteria groups were very similar, creating difficulty in classification. However, the application of principal component analysis (PCA) to the fluorescence spectra resulted in successful classification of the bacteria by their genus as well as determining their concentration. The detection limit was approximately 10<sup>3</sup>–10<sup>4</sup> cells/mL for each bacterial sample. These results demonstrated that fluorescence spectroscopy, when coupled with PCA processing, has the potential to detect and to classify bacterial pathogens in liquids. The methology is rapid (>10 min), inexpensive, and requires minimal sample preparation compared to standard analytical methods for bacterial detection.

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