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

The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms ( spp. and spp.) and vaginal pathogens: bacteria (e.g., , , ), fungi (e.g., , ), and protozoa (). The obtained results proved that each microorganism has its unique spectral fingerprint that differentiates it from the rest. Moreover, the discrimination was obtained at a high level of explained information by subsequent factors, e.g., in the inter-species distinction of spp. the first three factors explain 98% of the variance in block Y with 95% of data within the X matrix, while in differentiation between spp. and spp. (natural flora) and pathogen (e.g., ) the information is explained at the level of 45% of the Y matrix with 94% of original data. PLSR gave us insight into discriminating variables based on which the marker bands representing specific compounds in the outer structure of microorganisms were found: for spp. 1400 cm, for fungi 905 and 1209 cm, and for protozoa 805, 890, 1062, 1185, 1300, 1555, and 1610 cm. Then, they can be used as significant marker bands in the analysis of clinical subjects, e.g., vaginal swabs.