Discrimination of Closely Related Vibrio Strains by Label-Free Surface-Enhanced Raman Spectroscopy (SERS)

Area of Science:

• Biotechnology
• Analytical Chemistry
• Aquaculture Health

Background:

• Aquaculture faces significant economic losses due to fish pathogens, necessitating rapid and accurate identification methods.
• Conventional bacterial identification is slow and expensive, hindering effective disease management in aquaculture.
• Raman spectroscopy presents a promising label-free alternative for bacterial species differentiation based on unique molecular signatures.

Purpose of the Study:

• To evaluate the efficacy of surface-enhanced Raman spectroscopy (SERS) for classifying three significant Vibrio species.
• To investigate the combined use of SERS with multivariate analysis techniques (PCA-LDA and PLS-DA) for accurate Vibrio identification.
• To establish a rapid, cost-effective, and label-free method for Vibrio species differentiation in aquaculture.

Main Methods:

• Bacterial cultures of Vibrio alginolyticus, Vibrio parahaemolyticus, and Vibrio vulnificus were analyzed using SERS.
• Spectral data were processed using principal component analysis with linear discriminant analysis (PCA-LDA) and partial least-squares discriminant analysis (PLS-DA).
• Species-specific spectral variations, including amide, sulfur, and lipid-related signals, were identified and correlated with bacterial species.

Main Results:

• SERS spectra revealed distinct molecular signatures for each Vibrio species, enabling differentiation.
• The PCA-LDA model achieved 100% classification accuracy and 97.06% cross-validation accuracy for the tested Vibrio species.
• The PLS-DA model demonstrated excellent discriminatory performance (AUC = 1.00) with strong calibration (R² > 0.80) for two species and good performance for V. alginolyticus (R² = 0.71).

Conclusions:

• SERS combined with multivariate analysis is a highly effective approach for rapid and label-free identification of Vibrio species.
• This method shows significant potential for improving disease diagnostics and management strategies in aquaculture.
• The study provides a proof-of-concept for using SERS as a powerful tool in microbial identification within controlled laboratory settings.