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Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design
Antibiotic resistance is an important public health problem. One potential solution is the development of synergistic antibiotic combinations, in which the combination is more effective than the component drugs. However, experimental progress in this direction is severely limited by the number of sa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333450/ https://www.ncbi.nlm.nih.gov/pubmed/35849634 http://dx.doi.org/10.1371/journal.pcbi.1010311 |
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author | Brennan, Jennifer Jain, Lalit Garman, Sofia Donnelly, Ann E. Wright, Erik Scott Jamieson, Kevin |
author_facet | Brennan, Jennifer Jain, Lalit Garman, Sofia Donnelly, Ann E. Wright, Erik Scott Jamieson, Kevin |
author_sort | Brennan, Jennifer |
collection | PubMed |
description | Antibiotic resistance is an important public health problem. One potential solution is the development of synergistic antibiotic combinations, in which the combination is more effective than the component drugs. However, experimental progress in this direction is severely limited by the number of samples required to exhaustively test for synergy, which grows exponentially with the number of drugs combined. We introduce a new metric for antibiotic synergy, motivated by the popular Fractional Inhibitory Concentration Index and the Highest Single Agent model. We also propose a new experimental design that samples along all appropriately normalized diagonals in concentration space, and prove that this design identifies all synergies among a set of drugs while only sampling a small fraction of the possible combinations. We applied our method to screen two- through eight-way combinations of eight antibiotics at 10 concentrations each, which requires sampling only 2,560 unique combinations of antibiotic concentrations. |
format | Online Article Text |
id | pubmed-9333450 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93334502022-07-29 Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design Brennan, Jennifer Jain, Lalit Garman, Sofia Donnelly, Ann E. Wright, Erik Scott Jamieson, Kevin PLoS Comput Biol Research Article Antibiotic resistance is an important public health problem. One potential solution is the development of synergistic antibiotic combinations, in which the combination is more effective than the component drugs. However, experimental progress in this direction is severely limited by the number of samples required to exhaustively test for synergy, which grows exponentially with the number of drugs combined. We introduce a new metric for antibiotic synergy, motivated by the popular Fractional Inhibitory Concentration Index and the Highest Single Agent model. We also propose a new experimental design that samples along all appropriately normalized diagonals in concentration space, and prove that this design identifies all synergies among a set of drugs while only sampling a small fraction of the possible combinations. We applied our method to screen two- through eight-way combinations of eight antibiotics at 10 concentrations each, which requires sampling only 2,560 unique combinations of antibiotic concentrations. Public Library of Science 2022-07-18 /pmc/articles/PMC9333450/ /pubmed/35849634 http://dx.doi.org/10.1371/journal.pcbi.1010311 Text en © 2022 Brennan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Brennan, Jennifer Jain, Lalit Garman, Sofia Donnelly, Ann E. Wright, Erik Scott Jamieson, Kevin Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
title | Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
title_full | Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
title_fullStr | Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
title_full_unstemmed | Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
title_short | Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
title_sort | sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333450/ https://www.ncbi.nlm.nih.gov/pubmed/35849634 http://dx.doi.org/10.1371/journal.pcbi.1010311 |
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