Identifying factors that influence the temporal stability of the vaginal microbiome


Identification: France, Michael


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Identifying factors that influence the temporal stability of the vaginal microbiome
 
Michael France1, Lindsay Rutt1, Mike Humphrys1, Larry Forney2, Jacques Ravel1
1Institute of Genome Sciences, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, United States 2Institute for Bioinformatics and Evolutionary Studies, Department of Biological Sciences, University of Idaho, Moscow Idaho
 
Longitudinal profiling of the human vaginal microbiome has demonstrated that the composition of these communities can be temporally variable. This dynamic behavior has been shown to differ among women: some have a relatively constant community composition over time (stable) while others experience a high degree of change over time (unstable). Shifts in community composition, particularly shifts to states that have low-Lactobacillus abundance, have been hypothesized to be associated with risk of adverse health outcomes including increased susceptibility to sexually transmitted infections. Unfortunately, the factors that drive changes in community composition of the vagina are not well understood. In this study, we used a systems biology approach to identify the factors that drive the stability of the vaginal microbiome. We leveraged a rich dataset derived from the daily sampling of over 100 women. Stability can be defined as a combination of a communities' ability to withstand perturbation (resistance) and its ability to rebound following perturbation (resilience). We developed a metric for community stability and classified the longitudinal profiles of these women into five categories: 1) stable Lactobacillus, 2) unstable Lactobacillus, 3) stable Non-Lactobacillus, 4) unstable Non-Lactobacillus, and 5) highly unstable. A multi-omics approach is being applied to compare and contrast these communities, in order to identify drivers of community stability. Here, we present new metrics to evaluate functional redundancy and diversity from metagenomic datasets, and their contribution to the resistance and resilience of vaginal microbial communities.
 

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