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Browsing by Author "Naicker, Deshanta."

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    A novel study to detect and quantify microorganisms associated with bacterial vaginosis from urine samples.
    (2019) Naicker, Deshanta.; Abbai, Nathlee Samantha.; Naicker, Meleshni.
    Bacterial vaginosis (BV) is the most common vaginal condition found in women of reproductive age. The lack of published data on the detection of BV-associated pathogens from urine, a non-invasive sample, lends novelty to the present study. This study aimed to detect and quantify Gardnerella vaginalis, Prevotella bivia, Atopobium vaginae and Lactobacilllus crispatus from urine, as an alternative non-invasive method to vaginal swabs from pregnant women using droplet digital PCR (ddPCR). A total of n=100 DNA samples (50 paired urine and swabs) were tested. The samples were stratified as BV negative and positive using the BD MAX Vaginal panel assay (Becton Dickinson). Total DNA was extracted from urine (10 ml) and swabs (1 ml) using the PureLink Microbiome Kit (ThermoFisher Scientific). The concentration of extracted DNA for urine and swab samples was determined using the Nanodrop Spectrophotometer (ThermoScientific). Droplet digital PCR was used to determine the absolute quantification of the pathogens using commercially available primer and probe sets. G. vaginalis was observed as the most abundant microorganism, followed by A. vaginae and P. bivia in the BV positive samples. When comparing abundance of microorganisms across urine and swab, it was shown that there was no significant difference across both sample types in the BV negative group. A significant difference in the BV positive group (p=0.004) was only observed for A. vaginae. Good correlation between the urine and swab was observed for G. vaginalis (R=0.63, p<0.0001), L. crispatus (R=0.71, p<0.0001) and P. bivia (R=0.50, p<0.0001). However, a weak correlation across both sample types was observed for A. vaginae (R= 0.21, p=0.001). We observed that urine has the potential to serve as an alternative sample collection method to detect BV-associated bacteria. In addition, the data generated in this study provides a basis for the development of ddPCR as a diagnostic tool for BV.