Female genital tract infections (FGTIs) include vaginal infections (e.g., bacterial vaginosis [BV]), endometritis, pelvic inflammatory disease [PID], and chorioamnionitis [amniotic fluid infection]. They commonly occur in women of reproductive age and are strongly associated with multiple adverse health outcomes including increased risk of HIV/sexually transmitted infection acquisition and transmission, infertility, and adverse birth outcomes such as preterm birth. These FGTIs are characterized by a disruption of the cervicovaginal microbiota which largely affects host immunity through the loss of protective, lactic acid-producing Lactobacillus spp. and the overgrowth of facultative and strict anaerobic bacteria. Prevotella species (spp.), anaerobic Gram-negative rods, are implicated in the pathogenesis of multiple bacterial FGTIs. Specifically, P. bivia, P. amnii, and P. timonensis have unique virulence factors in this setting, including resistance to antibiotics commonly used in treatment. Additionally, evidence suggests that the presence of Prevotella spp. in untreated BV cases can lead to infections of the upper female genital tract by ascension into the uterus. This narrative review aims to explore the most common Prevotella spp. in FGTIs, highlight their important role in the pathogenesis of FGTIs, and propose future research in this area.

Key bacterial vaginosis (BV)-associated bacteria implicated in biofilm formation include Gardnerella species, Prevotella bivia , and Fannyhessea vaginae . We investigated their spatial organization in the BV biofilm over time from longitudinal vaginal specimens obtained from women with incident BV (iBV) using peptide nucleic acid-fluorescence in situ hybridization (PNA-FISH). Heterosexual women with optimal vaginal microbiota self-collected vaginal specimens twice daily for 60 days or until iBV development (Nugent score 7–10 on ≥4 consecutive specimens). Women who developed iBV were matched to healthy controls by age, race, and contraceptive method. Gardnerella spp., P. bivia , and F. vaginae were quantified using PNA-FISH 2 days pre-iBV, the day of iBV, and 2 days post-iBV across five optical layers ( z , z + 2, z + 4, z + 6, and z + 8 μm). Total counts of all three bacterial species were significantly higher on the day of iBV compared to 2 days pre-iBV ( P = 0.011) and remained elevated 2 days post-iBV. Across most layers and time points, pooled mean Gardnerella spp. counts were significantly higher than F. vaginae counts ( P ≤ 0.022-0.0003). On the day of iBV and 2 days post-iBV, pooled mean counts of Gardnerella spp. and F. vaginae progressively increased across most biofilm layers ( P ≤ 0.043-0.0012). Controls had significantly lower counts of Gardnerella spp. and F. vaginae. P. bivia had low counts in all specimens. During the critical time period surrounding iBV, Gardnerella spp. are abundant throughout the developing biofilm and facilitate F. vaginae incorporation at later time points and higher biofilm layers. Additional research, including other Prevotella spp., is needed. IMPORTANCE: Bacterial vaginosis (BV) is the most common vaginal infection in reproductive-age women worldwide with a global prevalence of 30%. Recurrence rates can be up to 60% within 1 year of treatment. While BV is characterized as a polymicrobial biofilm infection, the exact etiology remains unknown. The BV biofilm may persist after antibiotic treatment, possibly due to incomplete eradication by current antimicrobial therapies, contributing to recurrent infection. Data are limited in evaluating the spatial formation of the BV biofilm around the time of incident BV. Providing a better understanding of this critical time period in incident BV pathogenesis is necessary to inform the development of prevention methods aimed at inhibiting biofilm formation and improving long-term treatment outcomes.

Background: Bacterial vaginosis (BV) is a vaginal dysbiosis characterized by polymicrobial communities of BV-associated bacteria (BVAB) adhered to the vaginal epithelium. Despite decades of research, its etiology remains unknown. We aimed to investigate BV biofilm formation over time among women who developed incident BV (iBV) using peptide nucleic acid-fluorescence in situ hybridization (PNA-FISH), focusing on 3 key BVAB (Gardnerella species, Prevotella bivia, and Fannyhessea vaginae). Methods: Heterosexual, nonpregnant women ages 18–45 with optimal vaginal microbiota were enrolled to self-collect twice-daily vaginal specimens for 60 days. iBV was defined as a Nugent score of 7–10 on ≥4 consecutive specimens. For women who developed iBV (cases), Gardnerella spp., P. bivia, and F. vaginae were visualized and quantified by PNA-FISH for up to 14 days prior to iBV, the day of iBV, and 3 days post-iBV. Cases were matched to women maintaining optimal vaginal microbiota (controls) based on age, race, and contraceptive method. Control specimens were matched to case specimens by day of menses. Results: Among 135 women enrolled, 18 developed iBV and were matched to 18 controls. Pooled median Gardnerella spp. counts significantly increased starting 5 days before iBV, while pooled median F. vaginae counts significantly increased on the day of iBV diagnosis. In contrast, pooled median P. bivia counts were not significantly different between groups. Conclusions: These data suggest that Gardnerella spp. are early colonizers of the BV biofilm while F. vaginae is a secondary colonizer. P. bivia was not found to be significantly different between iBV case and control specimens.

Background: Bacterial vaginosis (BV) is a vaginal dysbiosis associated with adverse reproductive and infectious outcomes. Current diagnostics identify BV after symptom onset. We evaluated whether artificial neural network (ANN) models of the vaginal microbiome could predict incident BV (iBV) up to 14 days before clinical diagnosis. Methods: ANNs were trained using 16S rRNA gene sequencing data from 1,201 longitudinal vaginal specimens collected from 58 women across two prospective cohorts. Models classified individual specimens as pre-iBV or healthy using the relative abundance of vaginal bacterial taxa. Model performance was assessed using a held-out participant-level test set, participant-level cross-validation, and external validation. SHAP analysis was used to identify taxa associated with model predictions. Results: On the held-out participant-level test set, the ANN achieved 93% accuracy (AUC = 0.97, sensitivity = 95%, specificity = 92%). Models using only five taxa ( Lactobacillus crispatus , Gardnerella spp., L. iners , L. mulieris , and Megamonas spp.) maintained >91% accuracy, sensitivity, and specificity. SHAP analysis identified Lactobacillus spp. and Gardnerella spp. as the taxa most strongly associated with model predictions. Participant-level cross-validation produced lower and more variable performance (AUC = 0.826 ± 0.076; accuracy = 71.5% ± 8.2%), while external validation achieved approximately 80% balanced accuracy. Interpretation: Vaginal microbiome composition contains predictive information that can identify women at risk of iBV before clinical onset. Lower performance during participant-level cross-validation and external validation indicates that additional validation in larger, more diverse cohorts is required before clinical implementation.