Discrimination of bacteria using surface-enhanced Raman spectroscopy

Area of Science:

• Microbiology
• Analytical Chemistry
• Spectroscopy

Background:

• Raman spectroscopy is a powerful whole-organism fingerprinting technique for microbial identification.
• The weak Raman effect necessitates long collection times (minutes per sample).
• Surface-enhanced Raman scattering (SERS) significantly amplifies the Raman signal (10^3-10^6-fold).

Purpose of the Study:

• To investigate the utility of SERS for analyzing clinical bacterial isolates.
• To apply multivariate statistical methods for bacterial grouping based on SERS spectral fingerprints.
• To demonstrate bacterial discrimination, including strain-level differentiation, using SERS.

Main Methods:

• Analysis of clinical bacterial isolates associated with urinary tract infections using SERS.
• Utilized an aggregated silver colloid as the SERS substrate.
• Applied discriminant function analysis (DFA) and hierarchical cluster analysis (HCA) for spectral data analysis.

Main Results:

• SERS spectral acquisition time per bacterium was approximately 8 minutes (50 spectra x 10 seconds).
• DFA and HCA successfully grouped bacteria based on their SERS spectral fingerprints.
• Achieved accurate discrimination, including differentiation to the strain level for Escherichia coli isolates.

Conclusions:

• SERS, combined with multivariate statistical analysis, is effective for bacterial discrimination.
• This study represents the first report demonstrating bacterial discrimination using SERS.
• SERS shows promise as a rapid and accurate technique in microbial systematics and clinical diagnostics.