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  Antibiotic combination efficacy (ACE) networks for a Pseudomonas aeruginosa model

Barbosa, C., Beardmore, R., Schulenburg, H., & Jansen, G. (2018). Antibiotic combination efficacy (ACE) networks for a Pseudomonas aeruginosa model. PLoS Biology, 16(4): e2004356, pp. 1-25. doi:10.1371/journal.pbio.2004356.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-7F8E-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-7F8F-1
Genre: Journal Article

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Barbosa, Camilo, Author
Beardmore, Robert, Author
Schulenburg, Hinrich1, Author              
Jansen, Gunther, Author
Affiliations:
1Max Planck Fellow Group Antibiotic Resistance Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_2600692              

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 Abstract: Author summary Bacterial infections are commonly treated with a combination of antibiotic drugs. However, not all combinations are equally effective, and success is variable. One reason for this variation is that we usually do not know to what extent bacteria are able to adapt to different types of drug combinations. If they can and do adapt, then antibiotic resistance can spread, potentially aggravating the current antibiotic crisis. In the current study, we therefore asked whether combination therapy can be improved by considering the evolutionary potential of the bacteria. To address this question, we systematically assessed the efficacy of antibiotic combinations using controlled laboratory evolution experiments with the opportunistic human pathogen Pseudomonas aeruginosa as a model. We found that 2 factors consistently increase treatment efficacy. First, synergism between the combined drugs (i.e., the 2 drugs enhance each other’s effects) increases the rate of bacterial population extinction and thus clearance rate. Second, evolved trade-offs such as collateral sensitivity (i.e., evolution of resistance to one drug increases susceptibility to the other drug) limit the ability of bacteria to adapt to the antibiotic pair. Our findings may help to optimize combination therapy by focusing on drug pairs that interact synergistically and also lead to evolved collateral sensitivities.

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Language(s): eng - English
 Dates: 2017-09-272018-03-282018-04-302018-05
 Publication Status: Published in print
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 Identifiers: DOI: 10.1371/journal.pbio.2004356
BibTex Citekey: 10.1371/journal.pbio.2004356
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Title: PLoS Biology
  Other : PLoS Biol.
Source Genre: Journal
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Publ. Info: San Francisco, California, US : Public Library of Science
Pages: - Volume / Issue: 16 (4) Sequence Number: e2004356 Start / End Page: 1 - 25 Identifier: ISSN: 1544-9173
CoNE: /journals/resource/111056649444170