Discrimination of bacterial strains based on variation in cell surface composition detected by surface enhanced Raman spectroscopy (SERS)

Kate Eliza Stephen, Purdue University

Abstract

Surface enhanced Raman spectroscopy (SERS) is a rapid and highly sensitive spectroscopic technique that has the potential to measure chemical differences in bacterial cell surface properties in response to environmental changes. The objectives of this study were to determine whether SERS has sufficient resolution to differentiate (1) closely related bacteria within a genus when grown on solid versus liquid medium, (2) a single bacterial strain grown in different chromate concentrations, and (3) a single species grown as a biofilm exposed to chromate and iron. Fourteen closely related Arthrobacter strains, based on their 16S rRNA gene sequences, were used in this study. After performing principal component analysis in conjunction with linear discriminate analysis, we used a novel, adapted cross-validation method that more faithfully models the classification of spectra. All fourteen strains were classified with 85-100% accuracy. The hierarchical trees comparing SERS spectra from the liquid and solid media data sets were different. Additionally, hierarchical trees created from the Raman data were different from those obtained using 16S rRNA gene sequences (a phylogenetic measure). A single Arthrobacter strain FB24 grown in solid culture media with three different chromate concentrations also showed significant spectral distinction at discrete points, identified by the new Elastic Net regularized regression method, demonstrating the ability of SERS to detect environmentally induced differences in cell surface composition. Then SERS was used to differentiate between Shewanella oneidensis strain MRI biofilms grown in different chromate concentrations. Statistical classification rates of this experiment averaged at 75%, and attempts at identification of important spectral differences were not reproducible. The outcome of these experiments demonstrate that SERS is effective at distinguishing between a large number of closely related bacterial strains and could be a valuable tool for rapid monitoring and characterization of phenotypic variations in a single population in response to environmental conditions. However, using SERS to monitor biochemical changes in biofilms represents a significant challenge, and more research is needed to determine its applicability.

Degree

M.S.

Advisors

Nakatsu, Purdue University.

Subject Area

Microbiology|Statistics|Environmental Health

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