AI Article Synopsis

  • - Diverse vaginal microbial communities are linked to negative health outcomes like preterm birth and STIs, yet their complex structures are not well understood.
  • - Traditional clustering methods used to study these communities struggle to accurately identify different sub-groups and transitions between them.
  • - This study introduces mixed membership topic models, which provide a clearer understanding of vaginal microbial compositions and highlight significant sub-communities and factors, including the impact of the menstrual cycle in non-pregnant individuals.

Article Abstract

Diverse and non--dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models. Using longitudinal data from cohorts of pregnant and non-pregnant study participants, we show that topic models more accurately describe sample composition, longitudinal changes, and better predict the loss of dominance. We identify several non--dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities, as well as the concentrations of half of the cytokines and 18% of metabolites. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10685114PMC
http://dx.doi.org/10.1098/rspb.2023.1461DOI Listing

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