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Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora.

ABSTRACT: Bacterial vaginosis (BV) is a highly prevalent disease in women, and increases the risk of pelvic inflammatory disease. It has been given wide attention because of the high recurrence rate. Traditional diagnostic methods based on microscope providing limited information on the vaginal microbiota increase the difficulty in tracing the development of the disease in bacteria resistance condition. In this study, we used deep-sequencing technology to observe dynamic variation of the vaginal microbiota at three major time points during treatment, at D0 (before treatment), D7 (stop using the antibiotics) and D30 (the 30-day follow-up visit). Sixty-five patients with BV were enrolled (48 were cured and 17 were not cured), and their bacterial composition of the vaginal microbiota was compared. Interestingly, we identified 9 patients might be recurrence. We also introduced a new measurement point of D7, although its microbiota were significantly inhabited by antibiotic and hard to be observed by traditional method. The vaginal microbiota in deep-sequencing-view present a strong correlation to the final outcome. Thus, coupled with detailed individual bioinformatics analysis and deep-sequencing technology, we may illustrate a more accurate map of vaginal microbial to BV patients, which provide a new opportunity to reduce the rate of recurrence of BV.

SUBMITTER: Xiao B

PROVIDER: S-EPMC4890590 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora.

Xiao Bingbing B Niu Xiaoxi X Han Na N Wang Ben B Du Pengcheng P Na Risu R Chen Chen C Liao Qinping Q

Scientific reports 20160602

Bacterial vaginosis (BV) is a highly prevalent disease in women, and increases the risk of pelvic inflammatory disease. It has been given wide attention because of the high recurrence rate. Traditional diagnostic methods based on microscope providing limited information on the vaginal microbiota increase the difficulty in tracing the development of the disease in bacteria resistance condition. In this study, we used deep-sequencing technology to observe dynamic variation of the vaginal microbiot ...[more]

PMID: 27253522

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Project description:Background and objectiveBacterial vaginosis (BV) is the most common vaginal disorder, characterized by depletion of the normal lactobacillus-dominant microbiota and overgrowth of commensal anaerobic bacteria. This study aimed to investigate the composition of the vaginal microbiota in women of reproductive age (healthy women and women with BV), with the view of developing molecular criteria for BV diagnosis.Materials and methodsVaginal samples from 163 women (79 control, 73 BV and 11 intermediate (Lactobacillary grade II flora) cases) were analyzed using 454 pyrosequencing of the hypervariable regions V3-V4 of the 16S rRNA gene and 16 quantitative bacterial species/genus-specific real-time PCR assays. Sensitivities and specificities of potential BV markers were computed using the Amsel criteria as reference standard for BV. The use of quantitative thresholds for prediction of BV, determined for both relative abundance measured with 454 pyrosequencing and bacterial load measured with qPCR, was evaluated.ResultsRelative to the healthy women, the BV patients had in their vaginal microbiota significantly higher prevalence, loads and relative abundances of the majority of BV associated bacteria. However, only Gardnerella vaginalis, Atopobium vaginae, Eggerthella, Prevotella, BVAB2 and Megasphaera type 1 detected at or above optimal thresholds were highly predictable for BV, with the best diagnostic accuracy shown for A. vaginae. The depletion of Lactobacillus species combined with the presence of either G. vaginalis or A. vaginae at diagnostic levels was a highly accurate BV predictor.ConclusionsQuantitative determination of the presence of G. vaginalis, A. vaginae, Eggerthella, Prevotella, BVAB2 and Megasphaera type 1 as well as the depletion of Lactobacillus was highly accurate for BV diagnosis. Measurements of abundance of normal and BV microbiota relative to total bacteria in vaginal fluid may provide more accurate BV diagnosis, and be used for test-of-cure, rather than qualitative detection or absolute counts of BV related microorganisms.

Project description:BackgroundBacterial vaginosis (BV) is an ecological disorder of the vaginal microbiota that affects millions of women annually, and is associated with numerous adverse health outcomes including pre-term birth and the acquisition of sexually transmitted infections. However, little is known about the overall structure and composition of vaginal microbial communities; most of the earlier studies focused on predominant vaginal bacteria in the process of BV. In the present study, the diversity and richness of vaginal microbiota in 50 BV positive and 50 healthy women from China were investigated using culture-independent PCR-denaturing gradient gel electrophoresis (DGGE) and barcoded 454 pyrosequencing methods, and validated by quantitative PCR.ResultsOur data demonstrated that there was a profound shift in the absolute and relative abundances of bacterial species present in the vagina when comparing populations associated with healthy and diseased conditions. In spite of significant interpersonal variations, the diversity of vaginal microbiota in the two groups could be clearly divided into two clusters. A total of 246,359 high quality pyrosequencing reads was obtained for evaluating bacterial diversity and 24,298 unique sequences represented all phylotypes. The most predominant phyla of bacteria identified in the vagina belonged to Firmicutes, Bacteroidetes, Actinobacteria and Fusobacteria. The higher number of phylotypes in BV positive women over healthy is consistent with the results of previous studies and a large number of low-abundance taxa which were missed in previous studies were revealed. Although no single bacterium could be identified as a specific marker for healthy over diseased conditions, three phyla - Bacteroidetes, Actinobacteria and Fusobacteria, and eight genera including Gardnerella, Atopobium, Megasphaera, Eggerthella, Aerococcus, Leptotrichia/Sneathia, Prevotella and Papillibacter were strongly associated with BV (p < 0.05). These genera are potentially excellent markers and could be used as targets for clinical BV diagnosis by molecular approaches.ConclusionsThe data presented here have clearly profiled the overall structure of vaginal communities and clearly demonstrated that BV is associated with a dramatic increase in the taxonomic richness and diversity of vaginal microbiota. The study also provides the most comprehensive picture of the vaginal community structure and the bacterial ecosystem, and significantly contributes to the current understanding of the etiology of BV.

Dataset Information

Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora.

Publications

Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora.

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