Modeling the temporal dynamics of the cervicovaginal microbiota identifies targets to promote reproductive health
Background: Cervicovaginal bacterial communities composed of diverse anaerobes with low Lactobacillus abundance are associated with poor reproductive outcomes such as preterm birth, infertility, cervicitis, and risk of sexually transmitted infections (STIs), including human immunodeficiency virus (HIV). Women in sub-Saharan Africa have higher prevalence of these high-risk bacterial communities when compared to Western populations. However, the transition of cervicovaginal communities between high- and low-risk community states over time are not well-described in African populations.
Results: We profiled the bacterial composition of 316 cervicovaginal swabs collected from 88 healthy young Black South African women at 3-month intervals with a median follow-up duration of 9 months per participant (range 3-21 months) and developed a Markov-based model of transition dynamics that accurately predicted bacterial composition within a broader cross-sectional cohort. We found that Lactobacillus iners-dominant, but not Lactobacillus crispatus-dominant, communities have high probability of transitioning to high-risk states. Simulating clinical interventions by manipulating the underlying transition probabilities, our model predicts that the population prevalence of low-risk microbial communities could most effectively be increased by manipulating the movement between L. iners- and L. crispatus-dominant communities.
Conclusions: The Markov-model we present here indicates that L. iners-dominant communities have high probability of transitioning to higher-risk states. We additionally identify transitions to target to increase the prevalence of L. crispatus-dominant communities. These findings may help guide future intervention strategies targeted at reducing bacteria-associated adverse reproductive outcomes among women living in sub-Saharan Africa.
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data/ - High-level analyses comparing transitions between cervicotypes found in
Markov_CTLevel.ipynb - Analyses examining specific taxa and bacterial species found in
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Alexander Munoz, Matthew R. Hayward, Seth M. Bloom, Muntsa Rocafort, Sinaye Ngcapu, Nomfuneko A. Mafunda, Jiawu Xu, Musie S. Ghebermichael, Douglas S. Kwon
From Ragon Institute of MGH, MIT, and Harvard; Division of Infectious Diseases, Massachusetts General Hospital; Harvard Medical School; and Centre for the AIDS Programme of Research in South Africa (CAPRISA), Doris Duke Medical Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal