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Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis
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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708644/ https://www.ncbi.nlm.nih.gov/pubmed/33262350 http://dx.doi.org/10.1038/s41467-020-19880-w |
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author | Lee, Christina Y. Cheu, Ryan K. Lemke, Melissa M. Gustin, Andrew T. France, Michael T. Hampel, Benjamin Thurman, Andrea R. Doncel, Gustavo F. Ravel, Jacques Klatt, Nichole R. Arnold, Kelly B. |
author_facet | Lee, Christina Y. Cheu, Ryan K. Lemke, Melissa M. Gustin, Andrew T. France, Michael T. Hampel, Benjamin Thurman, Andrea R. Doncel, Gustavo F. Ravel, Jacques Klatt, Nichole R. Arnold, Kelly B. |
author_sort | Lee, Christina Y. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7708644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77086442020-12-03 Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis Lee, Christina Y. Cheu, Ryan K. Lemke, Melissa M. Gustin, Andrew T. France, Michael T. Hampel, Benjamin Thurman, Andrea R. Doncel, Gustavo F. Ravel, Jacques Klatt, Nichole R. Arnold, Kelly B. Nat Commun Article 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. Nature Publishing Group UK 2020-12-01 /pmc/articles/PMC7708644/ /pubmed/33262350 http://dx.doi.org/10.1038/s41467-020-19880-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lee, Christina Y. Cheu, Ryan K. Lemke, Melissa M. Gustin, Andrew T. France, Michael T. Hampel, Benjamin Thurman, Andrea R. Doncel, Gustavo F. Ravel, Jacques Klatt, Nichole R. Arnold, Kelly B. Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
title | Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
title_full | Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
title_fullStr | Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
title_full_unstemmed | Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
title_short | Quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
title_sort | quantitative modeling predicts mechanistic links between pre-treatment microbiome composition and metronidazole efficacy in bacterial vaginosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708644/ https://www.ncbi.nlm.nih.gov/pubmed/33262350 http://dx.doi.org/10.1038/s41467-020-19880-w |
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