Ag NP-filter paper based SERS sensor coupled with multivariate analysis for rapid identification of bacteria

Area of Science:

• Analytical Chemistry
• Biotechnology
• Food Science

Background:

• Accurate bacterial identification is critical for food safety and preventing infections.
• Existing methods can be time-consuming or lack the required sensitivity.
• Development of rapid and efficient bacterial detection techniques is essential.

Purpose of the Study:

• To establish a highly efficient method for accurate bacterial species identification.
• To utilize silver nanoparticle (Ag NP)-functionalized filter paper for Surface-Enhanced Raman Spectroscopy (SERS).
• To employ Partial Least Squares-Discriminant Analysis (PLS-DA) for spectral data analysis.

Main Methods:

• Fabrication of a flexible Ag NP-filter paper substrate via a low-cost silver mirror reaction.
• Application of SERS for analyzing bacterial samples on the Ag NP filter paper.
• Utilizing PLS-DA statistical methods to differentiate SERS spectra of various bacterial species.

Main Results:

• The Ag NP filter paper demonstrated high sensitivity, uniformity, and desirable SERS activity.
• PLS-DA successfully distinguished SERS spectra of *S. aureus*, *E. faecalis*, and *L. monocytogenes*.
• Achieved high performance metrics: 93.3-100% sensitivity, 96.7-97% specificity, and 95.8% overall accuracy.

Conclusions:

• The Ag NP-filter paper based SERS sensor is a promising tool for bacterial detection.
• Coupling SERS with PLS-DA enables rapid and effective identification of bacterial species.
• This method holds significant potential for applications in food safety and clinical diagnostics.