| Autor: |
Rourke-Funderburg AS; Department of Biomedical Engineering, Vanderbilt, University, Nashville, TN, USA. andrea.locke@vanderbilt.edu.; Vanderbilt Biophotonics Center, Vanderbilt University, Nashville, TN, USA., Mahadevan-Jansen A; Department of Biomedical Engineering, Vanderbilt, University, Nashville, TN, USA. andrea.locke@vanderbilt.edu.; Vanderbilt Biophotonics Center, Vanderbilt University, Nashville, TN, USA., Locke AK; Department of Biomedical Engineering, Vanderbilt, University, Nashville, TN, USA. andrea.locke@vanderbilt.edu.; Vanderbilt Biophotonics Center, Vanderbilt University, Nashville, TN, USA.; Department of Chemistry, Vanderbilt University, Nashville, TN, USA. |
| Abstrakt: |
The native vaginal microbiome plays a crucial role in maintaining vaginal health and disruption can have significant consequences for women during their lifetime. While the composition of the vaginal microbiome is important, current methods for monitoring this community are lacking. Clinically used techniques routinely rely on subjective analysis of vaginal fluid characteristics or time-consuming microorganism culturing. Surface-enhanced Raman spectroscopy (SERS) can aid in filling this gap in timely detection of alterations in the vaginal microbiome as it can discriminate between bacterial species in complex solutions including bacterial mixtures and biofluids. SERS has not previously been applied to study variations in vaginal Lactobacillus , the most common species found in the vaginal microbiome, in complex solutions. Herein, the SERS spectra of Lactobacillus crispatus ( L. crispatus ) and Lactobacillus iners ( L. iners ), two of the most common vaginal bacteria, was characterized at physiologically relevant concentrations. Subsequently, the ability of SERS to detect L. crispatus and L. iners in both pure mixtures and when mixed with a synthetic vaginal fluid mimicking solution was determined. In both pure and complex solutions, SERS coupled with partial least squares regression predicted the ratiometric bacterial content with less than 10% error and strong goodness of prediction ( Q 2 > 0.9). This developed method highlights the applicability of SERS to predict the dominant Lactobacillus in the vaginal micro-environment toward the monitoring of this community. |
