Unraveling Mechanisms of Bacterial Vaginosis through Metabolic Modeling and Metabolomics Analysis

Bacterial vaginosis (BV) is a common vaginal condition that has a significant impact on women's health. However, our understanding of its microbial community structure and metabolic interactions is limited. In this dissertation, I focus on investigating the metabolic pathways within the Gardnerella pangenome and defining the functional metabolic relationships between Gardnerella and other vaginal microbial species associated with BV. By constructing metabolic network models and conducting in silico analysis, I uncover both conserved and unique metabolic mechanisms within the Gardnerella pangenome. Notably, I find that genetic similarity does not always correspond to metabolic functional similarity.

To further explore the dynamics of Gardnerella strains in the vaginal metabolic environment, I used flux balance analysis to identify essential genes and potential drug targets. Through in silico simulations of pair-wise bacterial interactions, I observe significant clustering of Gardnerella species based on mutualistic benefits, underscoring the complex nature of these interactions. To validate my findings, I integrate clinical data, in silico analysis, in vitro experiments, and metabolomics to unravel the intricate BV-associated bacterial community structures.

Overall, this research enhances our understanding of BV and provides insights for personalized treatments and novel intervention development. By elucidating the metabolic relationships within the Gardnerella pangenome and unraveling the complex BV-associated bacterial community structures, we can improve the management and outcomes of this common vaginal condition.