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    Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis

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    Author
    Lee, C.Y.
    Cheu, R.K.
    Lemke, M.M.
    Gustin, A.T.
    France, M.T.
    Hampel, B.
    Thurman, A.R.
    Doncel, G.F.
    Ravel, J.
    Klatt, N.R.
    Arnold, K.B.
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    Date
    2020-12-01
    Journal
    Nature communications
    Publisher
    Nature Springer
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1038/s41467-020-19880-w
    Abstract
    Bacterial vaginosis is a condition associated with adverse reproductive outcomes and characterized by a shift from a Lactobacillus-dominant vaginal microbiota to a polymicrobial microbiota, consistently colonized by strains of Gardnerella vaginalis. Metronidazole is the first-line treatment; however, treatment failure and recurrence rates remain high. To understand complex interactions between Gardnerella vaginalis and Lactobacillus involved in efficacy, here we develop an ordinary differential equation model that predicts bacterial growth as a function of metronidazole uptake, sensitivity, and metabolism. The model shows that a critical factor in efficacy is Lactobacillus sequestration of metronidazole, and efficacy decreases when the relative abundance of Lactobacillus is higher pre-treatment. We validate results in Gardnerella and Lactobacillus co-cultures, and in two clinical cohorts, finding women with recurrence have significantly higher pre-treatment levels of Lactobacillus relative to bacterial vaginosis-associated bacteria. Overall results provide mechanistic insight into how personalized differences in microbial communities influence vaginal antibiotic efficacy.
    Keyword
    Metronidazole
    Models, Theoretical
    Vagina--microbiology
    Vaginosis, Bacterial--drug therapy
    Vaginosis, Bacterial--microbiology
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/14570
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41467-020-19880-w
    Scopus Count
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    UMB Open Access Articles 2020

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