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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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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. |
format | Online Article Text |
id | pubmed-6329523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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