BME Master's Defense Announcement for Nina Render (D. Brubaker, Chair) Title: Characterizing Vaginal Microbiome Regulation of Progesterone Receptor Expression via Secondary Analysis of Host and Microbiome Multi-omics Data Everyone is invited to attend the public presentation beginning at 2:00 pm. Date/Time: March 8th, 2:00 pm Location: MJIS 2001 / https://purdue-edu.zoom.us/j/3663959794<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fpurdue-edu.zoom.us%2Fj%2F3663959794&data=05%7C02%7Cbmegradstudents-list%40ecn.purdue.edu%7C03bab308be1d44ba696908dc32531da0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638440579751381531%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=gZ61CSVR%2F%2Fi0%2FAC4hXh9ciTZm%2F9%2FOelga55r4%2FjbZ8s%3D&reserved=0> Committee: Douglas K. Brubaker (chair) PhD, Leopold N. Green PhD, Alicia Berard PhD Abstract: 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. 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. Clinical phenotypes did not significantly alter the association between the biological explanatory variables and PGR expression. It is proposed that progesterone in the host regulates sugar metabolic pathways in vaginal microbiome bacteria, which produce metabolites that regulate PGR expression back in the host. Furthermore, how vaginal microbiome metabolites regulate PGR signaling is dependent upon microbial composition. 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.