Characterizing vaginal microbiome regulation of progesterone receptor expression via secondary analysis of host and microbiome multi-omics data

The vaginal microbiome and female sex hormones are both involved in the development and progression of gynecological pathologies. The individual mechanisms by which the vaginal microbiome leads to disease progression and how female sex hormones are known. However, the mechanisms by which the vaginal microbiome regulates female sex hormones, such as progesterone, are not well understood. This study seeks to understand how the vaginal microbiome regulates progesterone receptor (PGR) expression via secondary analysis of host and vaginal microbiome multi-omics data from the Partners PrEP cohort. This dataset consists of cervicovaginal samples of women enrolled in the Partners PrEP study. Partial Least Squares Regression (PLSR) models were created for each biological data type (microbial composition, metabolomics, metaproteomics) to assess how these factors regulate PGR expression. Significant factors were identified through variable importance of projection (VIP) and correlation analysis. Partial correlation analysis and follow-up PLSR models incorporating clinical and demographic variables were performed to assess the robustness of the vaginal microbiome-PGR associations. The PLSR models indicated lower PGR expression was associated with G. vaginalis, and higher PGR expression was associated with Lactobacillus species. Cytosine, guanine, and tyrosine were among metabolites significantly associated with higher PGR expression and experimentally determined to be produced by Lactobacillus species. Conversely, citrulline and succinate were associated with lower PGR expression and experimentally determined to be produced by G. vaginalis. The models indicated that bacterial metabolic pathways involved in glucose metabolism, such as glucagon signaling and starch and sugar metabolism, may regulate PGR expression. Demographic phenotypes were also considered from the dataset and did not significantly alter the association between the biological explanatory variables and PGR expression. The results indicate that guanine, cytosine, succinate, starch and sucrose metabolism, and glycolysis gluconeogenesis may be regulators of PGR abundance and function. The models suggest vaginal microbiome factors could play a role in gynecological conditions where progesterone signaling is suppressed. Future experimental work is needed to validate the results of these models and support their use as predictive tools to understand the role of the vaginal microbiome.