Barcoding bacterial cells: a SERS-based methodology for pathogen identification
Article first published online: 17 OCT 2008
Copyright © 2008 John Wiley & Sons, Ltd.
Journal of Raman Spectroscopy
Special Issue: Commemorative Issue: for Hiro-o Hamaguchi on the Occasion of his 60th Birthday
Volume 39, Issue 11, pages 1660–1672, November 2008
How to Cite
Patel, I. S., Premasiri, W. R., Moir, D. T. and Ziegler, L. D. (2008), Barcoding bacterial cells: a SERS-based methodology for pathogen identification. J. Raman Spectrosc., 39: 1660–1672. doi: 10.1002/jrs.2064
- Issue published online: 29 OCT 2008
- Article first published online: 17 OCT 2008
- Manuscript Accepted: 15 JUN 2008
- Manuscript Received: 2 MAY 2008
- Army Research Laboratory (Cooperative Agreement DAAD19-00-2-0005) and the National Institutes of Health. Grant Number: AI066641
- principal component analysis
A principal component analysis (PCA) based on the sign of the second derivative of the surface-enhanced Raman scattering (SERS) spectrum obtained on in situ grown Au-cluster-covered SiO2 substrates results in improved reproducibility and enhanced specificity for bacterial diagnostics. The barcode-generated clustering results are systematically compared with those obtained from the corresponding spectral intensities, first derivatives and second derivatives for the SERS spectra of closely related cereus group Bacillus strains. PCA plots and the corresponding hierarchical cluster analysis (HCA) dendrograms illustrate the improved bacterial identification resulting from the barcode spectral data reduction. Supervised discriminant function analysis (DFA) plots result in slightly improved group separation but show more susceptibility to false positive classifications than the corresponding PCA contours. In addition, this PCA treatment is used to highlight the enhanced bacterial species specificity observed for SERS as compared to normal bulk (non-SERS) Raman spectra. The identification algorithm described here is critical for the development of SERS microscopy as a rapid, reagentless and portable diagnostic of bacterial pathogens. Copyright © 2008 John Wiley & Sons, Ltd.