SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms

Area of Science:

• Microbiology
• Spectroscopy
• Biochemistry

Background:

• Accurate identification of vaginal microflora is vital for understanding dysbiosis and pathogenesis of vaginal infections.
• Distinguishing between beneficial symbiotic and pathogenic microorganisms is crucial for effective treatment and prevention.

Purpose of the Study:

• To establish spectral signatures of key vaginal microorganisms using surface-enhanced Raman spectroscopy (SERS).
• To build a spectral database for microorganism identification.
• To differentiate between beneficial vaginal flora and common vaginal pathogens.

Main Methods:

• Surface-enhanced Raman spectroscopy (SERS) was employed to capture spectral fingerprints of microorganisms.
• Partial Least Squares Regression (PLSR) was used to analyze spectral data and identify discriminating variables.
• The study focused on common vaginal microorganisms like *Lactobacillus* spp., *Bifidobacterium* spp., *Gardnerella vaginalis*, *Candida* spp., and *Trichomonas vaginalis*.

Main Results:

• Each microorganism exhibited a unique spectral fingerprint, enabling differentiation.
• High discrimination accuracy was achieved, with PLSR explaining significant variance (e.g., 98% for *Candida* spp. inter-species distinction).
• Specific marker bands were identified for *Lactobacillus* spp. (1400 cm⁻¹), fungi (905, 1209 cm⁻¹), and protozoa (805, 890, 1062, 1185, 1300, 1555, 1610 cm⁻¹).

Conclusions:

• SERS provides a powerful tool for the rapid and accurate identification of vaginal microorganisms.
• The identified spectral fingerprints and marker bands can be utilized for clinical analysis of vaginal swabs.
• This technique contributes to a better understanding of vaginal microbiota and pathogenesis of infections.