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ObjectiveEvaluate safety of Ovaprene, an investigational non-hormonal vaginal contraceptive designed for monthly use.Study designOpen-label, multicenter study enrolling heterosexually-active women with previous permanent contraception who underwent assessments during five menstrual cycles: baseline postcoital test cycle, diaphragm postcoital test cycle, Ovaprene safety cycle, and two Ovaprene postcoital test cycles. Safety outcomes included treatment emergent adverse events (TEAEs), systemic laboratory findings, pelvic examinations, colposcopies, Nugent scores, determination of community state types of vaginal microbiota, and anti-Escherichia coli activity and inflammatory markers in cervicovaginal fluids.ResultsWe enrolled 38 participants. Of these, 33 used Ovaprene and completed 77 Ovaprene cycles. The most common product-related urogenital TEAEs were bacterial vaginosis (BV) and vaginal odor. The frequency of transitioning from Lactobacillus-dominated community state type to community state type IV (not Lactobacillus-dominated) was similar before Ovaprene use and afterwards. Mean Nugent scores were

BackgroundTaxonomic profiles of vaginal microbial communities can be sorted into a discrete number of categories termed community state types (CSTs). This approach is advantageous because collapsing a hyper-dimensional taxonomic profile into a single categorical variable enables efforts such as data exploration, epidemiological studies, and statistical modeling. Vaginal communities are typically assigned to CSTs based on the results of hierarchical clustering of the pairwise distances between samples. However, this approach is problematic because it complicates between-study comparisons and because the results are entirely dependent on the particular set of samples that were analyzed. We sought to standardize and advance the assignment of samples to CSTs.ResultsWe developed VALENCIA (VAginaL community state typE Nearest CentroId clAssifier), a nearest centroid-based tool which classifies samples based on their similarity to a set of reference centroids. The references were defined using a comprehensive set of 13,160 taxonomic profiles from 1975 women in the USA. This large dataset allowed us to comprehensively identify, define, and characterize vaginal CSTs common to reproductive age women and expand upon the CSTs that had been defined in previous studies. We validated the broad applicability of VALENCIA for the classification of vaginal microbial communities by using it to classify three test datasets which included reproductive age eastern and southern African women, adolescent girls, and a racially/ethnically and geographically diverse sample of postmenopausal women. VALENCIA performed well on all three datasets despite the substantial variations in sequencing strategies and bioinformatics pipelines, indicating its broad application to vaginal microbiota. We further describe the relationships between community characteristics (vaginal pH, Nugent score) and participant demographics (race, age) and the CSTs defined by VALENCIA.ConclusionVALENCIA provides a much-needed solution for the robust and reproducible assignment of vaginal community state types. This will allow unbiased analysis of both small and large vaginal microbiota datasets, comparisons between datasets and meta-analyses that combine multiple datasets. Video abstract.

We characterized the composition and structure of the vaginal microbiota in a cohort of 149 women with genital Chlamydia trachomatis infection at baseline who were followed quarterly for 9 months after antibiotic treatment. At time of diagnosis, the vaginal microbiota was dominated by Lactobacillus iners or a diverse array of bacterial vaginosis-associated bacteria including Gardnerella vaginalis. Interestingly, L. iners-dominated communities were most common after azithromycin treatment (1 g monodose), consistent with the observed relative resistance of L. iners to azithromycin. Lactobacillus iners-dominated communities have been associated with increased risk of C. trachomatis infection, suggesting that the impact of antibiotic treatment on the vaginal microbiota could favor reinfections. These results provide support for the dual need to account for the potential perturbing effect(s) of antibiotic treatment on the vaginal microbiota, and to develop strategies to protect and restore optimal vaginal microbiota.

The mechanism(s) by which Lactobacillus-dominated cervicovaginal microbiota provide a barrier to Chlamydia trachomatis infection remain(s) unknown. Here we evaluate the impact of different Lactobacillus spp. identified via culture-independent metataxonomic analysis of C. trachomatis-infected women on C. trachomatis infection in a three-dimensional (3D) cervical epithelium model. Lactobacillus spp. that specifically produce d(-) lactic acid were associated with long-term protection against C. trachomatis infection, consistent with reduced protection associated with Lactobacillus iners, which does not produce this isoform, and with decreased epithelial cell proliferation, consistent with the observed prolonged protective effect. Transcriptomic analysis revealed that epigenetic modifications involving histone deacetylase-controlled pathways are integral to the cross talk between host and microbiota. These results highlight a fundamental mechanism whereby the cervicovaginal microbiota modulates host functions to protect against C. trachomatis infection.IMPORTANCE The vaginal microbiota is believed to protect women against Chlamydia trachomatis, the etiologic agent of the most prevalent sexually transmitted infection (STI) in developed countries. The mechanism underlying this protection has remained elusive. Here, we reveal the comprehensive strategy by which the cervicovaginal microbiota modulates host functions to protect against chlamydial infection, thereby providing a novel conceptual mechanistic understanding. Major implications of this work are that (i) the impact of the vaginal microbiota on the epithelium should be considered in future studies of chlamydial infection and other STIs and (ii) a fundamental understanding of the cervicovaginal microbiota's role in protection against STIs may enable the development of novel microbiome-based therapeutic strategies to protect women from infection and improve vaginal and cervical health.

Sequence analyses and subtyping of Bacillus anthracis strains from Georgia reveal a single distinct lineage (Aust94) that is ecologically established. Phylogeographic analysis and comparisons to a global collection reveals a clade that is mostly restricted to Georgia. Within this clade, many groups are found around the country, however at least one subclade is only found in the eastern part. This pattern suggests that dispersal into and out of Georgia has been rare and despite historical dispersion within the country, for at least for one lineage, current spread is limited.

Sequence analyses and subtyping of Bacillus anthracis strains from Georgia reveal a single distinct lineage (Aust94) that is ecologically established. Phylogeographic analysis and comparisons to a global collection reveals a clade that is mostly restricted to Georgia. Within this clade, many groups are found around the country, however at least one subclade is only found in the eastern part. This pattern suggests that dispersal into and out of Georgia has been rare and despite historical dispersion within the country, for at least for one lineage, current spread is limited.

BackgroundUnderstanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.ResultsWe find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.ConclusionsDNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.

BackgroundUnderstanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.ResultsWe find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.ConclusionsDNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.