Genome-scale metabolic network reconstruction analysis identifies bacterial vaginosis-associated metabolic interactions.

ABSTRACT: Bacterial vaginosis (BV) is the most prevalent vaginal condition among reproductive-age women presenting with vaginal complaints. Despite its significant impact on women's health, limited knowledge exists regarding the microbial community composition and metabolic interactions associated with BV. In this study, we analyze metagenomic data obtained from human vaginal swabs to generate in silico predictions of BV-associated bacterial metabolic interactions via genome-scale metabolic network reconstructions (GENREs). While most efforts to characterize symptomatic BV (and thus guide therapeutic intervention by identifying responders and non-responders to treatment) are based on genomic profiling, our in silico simulations reveal functional metabolic relatedness between species as quite distinc

SUBMITTER: Dillard LR 

PROVIDER: S-EPMC12098912 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature