Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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
_version_ 1783617581852131328
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
work_keys_str_mv AT leechristinay quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT cheuryank quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT lemkemelissam quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT gustinandrewt quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT francemichaelt quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT hampelbenjamin quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT thurmanandrear quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT doncelgustavof quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT raveljacques quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT klattnicholer quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis
AT arnoldkellyb quantitativemodelingpredictsmechanisticlinksbetweenpretreatmentmicrobiomecompositionandmetronidazoleefficacyinbacterialvaginosis