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Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment

Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination effi...

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Detalles Bibliográficos
Autores principales: Cokol, Murat, Li, Chen, Chandrasekaran, Sriram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329523/
https://www.ncbi.nlm.nih.gov/pubmed/30596642
http://dx.doi.org/10.1371/journal.pcbi.1006677
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author Cokol, Murat
Li, Chen
Chandrasekaran, Sriram
author_facet Cokol, Murat
Li, Chen
Chandrasekaran, Sriram
author_sort Cokol, Murat
collection PubMed
description Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination efficacy is unknown. To exhaustively explore the impact of diverse microenvironments on drug-combinations, here we develop a computational framework—Metabolism And GENomics-based Tailoring of Antibiotic regimens (MAGENTA). MAGENTA uses chemogenomic profiles of individual drugs and metabolic perturbations to predict synergistic or antagonistic drug-interactions in different microenvironments. We uncovered antibiotic combinations with robust synergy across nine distinct environments against both E. coli and A. baumannii by searching through 2556 drug-combinations of 72 drugs. MAGENTA also accurately predicted the change in efficacy of bacteriostatic and bactericidal drug-combinations during growth in glycerol media, which we confirmed experimentally in both microbes. Our approach identified genes in glycolysis and glyoxylate pathway as top predictors of synergy and antagonism respectively. Our systems approach enables tailoring of antibiotic therapies based on the pathogen microenvironment.
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spelling pubmed-63295232019-01-30 Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment Cokol, Murat Li, Chen Chandrasekaran, Sriram PLoS Comput Biol Research Article Antibiotics need to be effective in diverse environments in vivo. However, the pathogen microenvironment can have a significant impact on antibiotic potency. Further, antibiotics are increasingly used in combinations to combat resistance, yet, the effect of microenvironments on drug-combination efficacy is unknown. To exhaustively explore the impact of diverse microenvironments on drug-combinations, here we develop a computational framework—Metabolism And GENomics-based Tailoring of Antibiotic regimens (MAGENTA). MAGENTA uses chemogenomic profiles of individual drugs and metabolic perturbations to predict synergistic or antagonistic drug-interactions in different microenvironments. We uncovered antibiotic combinations with robust synergy across nine distinct environments against both E. coli and A. baumannii by searching through 2556 drug-combinations of 72 drugs. MAGENTA also accurately predicted the change in efficacy of bacteriostatic and bactericidal drug-combinations during growth in glycerol media, which we confirmed experimentally in both microbes. Our approach identified genes in glycolysis and glyoxylate pathway as top predictors of synergy and antagonism respectively. Our systems approach enables tailoring of antibiotic therapies based on the pathogen microenvironment. Public Library of Science 2018-12-31 /pmc/articles/PMC6329523/ /pubmed/30596642 http://dx.doi.org/10.1371/journal.pcbi.1006677 Text en © 2018 Cokol et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cokol, Murat
Li, Chen
Chandrasekaran, Sriram
Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
title Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
title_full Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
title_fullStr Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
title_full_unstemmed Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
title_short Chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
title_sort chemogenomic model identifies synergistic drug combinations robust to the pathogen microenvironment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329523/
https://www.ncbi.nlm.nih.gov/pubmed/30596642
http://dx.doi.org/10.1371/journal.pcbi.1006677
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