Ekaterina Smirnova, PhD.
Snahalata Huzurbazar, PhD.
University of Wyoming, Laramie, Wyoming
Bacterial Vaginosis (BV) affects approximately 30% of reproductive age women. This disease, caused by excessive bacteria in vagina, has a high rate of recurrence, and is associated with miscarriage, preterm birth, and increased risk of acquiring other sexually transmitted infections. The goal of this study is to classify microbial profile of women with bacterial vaginosis and develop a method to incorporate next generation microbiome sequencing in clinical diagnostics.
This study is a part of Vaginal Microbiome Project, design to investigate the relationships between the human microbiota composition, diet and health status. Visitors to Virginia Commonwealth Universityâ€™s outpatient clinics enrolled in the study. Next generation sequencing technology based on 16S ribosomal RNA (rRNA) gene marker was used to process vaginal samples and classify participantsâ€™ vaginal microbiome.
We use ordination methods to analyze 16S rRNA data collected for reproductive age women diagnosed with BV during a clinic visit and compare their vaginal taxa composition to healthy women. Eigendecomposition-based methods provide tools for not only representing data in lower dimensions, but also enable comparison of large data sets. In particular, correspondence analysis allows distinguish women with bacterial vaginosis based on their 16S taxa measurements, and co-inertia analysis provides a tool for coupling taxa measurements over two subsequent clinic visits.
Analysis of 16S taxa measurements allows to identify groups of women with a similar microbiome profile, distinguish differences in taxa composition between control and disease groups, and compare changes in vaginal microbiome over time. This study identifies new microbial species related to BV, and identifies species persistent in vaginal microflora over time.
Recent advances in various â€œomicsâ€ technologies allowed comprehensive examination of microbial communities, and study their association with common diseases. An important step towards clinical implementation of these technologies is to develop methods to characterize a healthy microbial profile and classify a species composition present in women with common vaginal diseases. Vaginal Human Microbiome studies discussed in this presentation enrich our understanding of the common structure in vaginal microflora and identify differences due to bacterial misbalance caused by bacterial vaginosis.