Stable SERS Detection of Lactobacillus fermentum Using Optical Tweezers in a Microfluidic Environment

Area of Science:

• Microbiology
• Analytical Chemistry
• Biotechnology

Background:

• Rapid identification of lactic acid bacteria is crucial for quality control in the brewing industry.
• Current methods for bacterial identification can be time-consuming and labor-intensive.
• Developing faster, more accurate identification techniques is an ongoing challenge.

Purpose of the Study:

• To develop and validate a novel platform for the rapid, label-free identification of fermented lactic acid bacteria.
• To assess the efficacy of combining surface-enhanced Raman scattering (SERS) with optical tweezer technology.
• To evaluate the performance of machine learning algorithms for bacterial spectral analysis.

Main Methods:

• A microfluidic test platform was constructed integrating label-free SERS and optical tweezer technology.
• Six common industrial lactic acid bacteria strains were analyzed.
• Optical tweezers were used to immobilize bacteria, enhancing SERS spectral stability.
• Support Vector Machine (SVM) and XGBoost algorithms were employed for spectral data analysis.

Main Results:

• The integration of optical tweezers significantly improved the stability of SERS spectra.
• High identification accuracies, exceeding 95%, were achieved for all tested lactic acid bacteria using SVM and XGBoost.
• The developed platform demonstrated robust performance for distinguishing between different bacterial species.

Conclusions:

• The combination of optical tweezers and SERS in a microfluidic environment offers a powerful tool for stable spectral acquisition.
• This technology enables rapid and accurate identification of lactic acid bacteria, with potential applications beyond the brewing industry.
• The findings underscore the value of optical tweezers in enhancing SERS-based microbial analysis.