Analytical and Bioanalytical Chemistry

, Volume 404, Issue 2, pp 563–572

Spectral signatures for the classification of microbial species using Raman spectra

  • Bobbie-Jo M. Webb-Robertson
  • Vanessa L. Bailey
  • Sarah J. Fansler
  • Michael J. Wilkins
  • Nancy J. Hess
Original Paper

DOI: 10.1007/s00216-012-6152-y

Cite this article as:
Webb-Robertson, BJ.M., Bailey, V.L., Fansler, S.J. et al. Anal Bioanal Chem (2012) 404: 563. doi:10.1007/s00216-012-6152-y

Abstract

In general, classification-based methods based on confocal Raman microscopy are focused on targeted studies under which the spectral libraries are collected under controlled instrument parameters, which facilitate analyses via standard multivariate data analysis methods and cross-validation. We develop and compare approaches to transform spectra collected at different spectral ranges and varying levels of resolution into a single lower-dimension spectral signature library. This will result in a more robust analysis method able to accommodate spectra accumulated at different times and conditions. We demonstrate these approaches on a relevant test case; the identification of microbial species from a natural environment. The training data were based on samples prepared for three unique species collected at two time points and the test data consisted of blinded unknowns prepared and analyzed at a later date with different instrument parameters. The results indicate that using reduced dimension representations of the spectral signatures improves classification accuracy over basic alignment protocols. In particular, utilizing the microbial species partial least squares discriminant analysis classifier on the blinded samples based on alignment achieved ~78 % accuracy, while both binning and peak selection approaches yielded 100 % accuracy.

Figure

A probability heatmap associated with the identification of species di181 across 357 spectra collected from a single drop of a mixed microbial suspension, dry-mounted for Raman analysis

Keywords

Confocal Raman microscopy Classification Alignment Binning Peak selection 

Copyright information

© Springer-Verlag (outside the USA) 2012

Authors and Affiliations

  • Bobbie-Jo M. Webb-Robertson
    • 1
  • Vanessa L. Bailey
    • 1
  • Sarah J. Fansler
    • 1
  • Michael J. Wilkins
    • 1
  • Nancy J. Hess
    • 1
  1. 1.Pacific Northwest National LaboratoryRichlandUSA