Rapid identification of five species of bacteria based on confocal Raman spectroscopy of single bacterial cells

Abstract:

[Background] Despite the extensive research on the application of confocal Raman spectroscopy in imaging and component identification, there are few studies focusing on the rapid detection and identification of a variety of bacteria. [Objective] A method for rapid classification and identification of single bacterial cells was established with confocal Raman spectroscopy. [Methods] We optimized the excitation wavelength of confocal Raman spectroscopy by using the single cells of Escherichia coli, and studied the influence of storage time on the Raman spectrum of E. coli. Furthermore, we performed confocal Raman spectroscopy tests for Staphylococcus albus, Escherichia coli, Staphylococcus aureus, Salmonella, and Pseudomonas aeruginosa. We then analyzed the Raman spectra of the 5 bacterial species to design a rapid identification method combining confocal Raman spectroscopy with support vector machine (SVM) model for the 5 bacterial species. [Results] Among the three common Raman detection wavelengths of 532, 633, and 785 nm, 532 nm had the best excitation efficiency and spectral signal-to-noise ratio for the identification of single bacterial cells. The SVM model showed the sensitivity and specificity above 96.00% and the overall accuracy rate of 98.25% for the identification of these bacteria. Moreover, the Raman spectra showed good repeatability and stability for the E. coli stored for different time, and the matching rate of SVM model was above 90.00%. [Conclusion] Single-cell Raman spectroscopy combined with SVM model can quickly and accurately classify the five bacterial species, and different storage time has little effect on the identification of E. coli based on Raman spectra.

Key words:confocal Raman spectroscopy;single bacterial cells;classification and identification;support vector machine