Abstract
The vaginal microbiota plays an important role in women's reproductive and urogenital health. It is now well accepted that a "healthy"vaginal microbiome is dominated by Lactobacillus species. Disturbances in this microbial community can lead to several adverse outcomes, including pelvic inflammatory disease and bacterial vaginosis (BV), as well as increased susceptibility to sexually transmitted infections, miscarriage, and preterm births. However, vaginal communities, especially those of women in the developing world, can be comprised of a diverse set of microorganisms in the absence of overt clinical symptoms. The implications of these diverse vaginal microbiomes for women's health remain poorly understood. Rhesus macaques are an excellent translational animal model to address these questions due to significant physiological and genetic homology with humans. In this study, we performed a longitudinal analysis of clinical and microbiome data from 16 reproductive-age female rhesus macaques. At both the taxonomic and functional levels, the rhesus macaque vaginal microbiome was most similar to that of women who harbor a diverse vaginal community associated with asymptomatic/ symptomatic bacterial vaginosis. Specifically, rhesus macaque vaginal microbiomes harbored a diverse set of anaerobic Gram-negative bacteria, including Sneathia, Prevotella, Porphyromonas, and Mobiluncus. Interestingly, some animals were transiently colonized by Lactobacillus and some with Gardnerella. Our in-depth and comprehensive analysis highlights the importance of the model to understand the health implications of a diverse vaginal microbiome and test interventions for manipulating this community.
Original language | English (US) |
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Article number | e01322-20 |
Journal | mSystems |
Volume | 6 |
Issue number | 2 |
DOIs | |
State | Published - 2021 |
Keywords
- Bacterial vaginosis
- Metagenomics
- Microbiome
- Rhesus macaque
- Vagina
ASJC Scopus subject areas
- Microbiology
- Ecology, Evolution, Behavior and Systematics
- Biochemistry
- Physiology
- Modeling and Simulation
- Molecular Biology
- Genetics
- Computer Science Applications