P4-S4.04 Temporal dynamics of vaginal bacterial communities

Abstract

BackgroundDysbiosis of vaginal bacterial communities have been associated with increased risk for sexually transmitted infections and bacterial vaginosis. This is the first observational study to model temporal dynamics of vaginal microbiota using frequently collected samples, behavioural data and culture-independent methods.MethodsThirty-three asymptomatic, reproductive-age women self-collected mid-vaginal swabs every 3rd day for 16 weeks (998 samples). Participants reported behaviours and menstrual data on daily diaries. Bacterial communities were determined by pyrosequencing of barcoded 16S rRNA genes (V1–V2 region). Participants were clustered into five community classes based on temporal patterns of vaginal bacterial community composition using transition probabilities. A linear mixed effect model for the log of Jensen-Shannon rate of community change was utilised. The model accounted for correlations between samples from the same participant and was adjusted for time-varying confounders and normalised menstrual cycle time.ResultsThree of the community classes were most often dominated byLactobacillus iners,L crispatus, orL gasseri, respectively, while two lacked significant numbers ofLactobacillusspp. The latter classes were split into subtype A typified by Corynebacterium, Anaerococcus, Peptinophilus, Prevotella, and Finegoldia, while those of subtype B showed a higher abundance of the genus Atopobium. The rank abundance and species composition of bacterial communities in some women changed markedly over short periods of time while others were relatively stable. Classes dominated byL crispatusandL gasseriexperienced the fewest fluctuations in community composition, and communities that lacked significant number ofLactobacillus spp. also demonstrated some stability. Vaginal communities dominated byL inersdemonstrated either a lack of constancy or notable stability. The menstrual cycle was associated with temporal dynamics, but these effects were influenced by bacterial community class. Sexual activity the day prior to sampling was of borderline statistical significance (p=0.065) and is a variable of interest in supplementary modelling.ConclusionsVaginal microbiota can fluctuate rapidly. Future studies should investigate the role of temporal changes in vaginal microbiota on sexually transmitted infection risk. Longitudinal studies of the vaginal microbiome may allow for the future development of targeted individualised therapeutic approaches.