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Cited by 264

The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.

Alternating antibiotic treatments constrain evolutionary paths to multidrug resistance

Open access
Kim, Seungsoo, Lieberman, Tami D., Kishony, Roy·2014·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1409800111
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Abstract

Significance: Antibiotic resistance is a growing threat, but the pace of drug discovery remains slow. Combination therapy can inhibit the emergence of de novo resistance but is often too toxic for long-term use. Alternating treatments, in which drugs are used sequentially with periodic switching, have been proposed as a substitute, but it remains uncertain when and how they slow the evolution of resistance. Using experimental evolution and whole-genome sequencing, we find that alternating drugs slows the rate of increase in resistance compared with single-drug treatments, by constraining resistance mutations with trade-offs in resistance to a second drug. Thus, drug combinations can exploit these trade-offs to slow the evolution of resistance, even when the drugs are not used simultaneously.

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Crossref · 10.1073/pnas.1409800111

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Metadata

Authors
Kim, S., Lieberman, T. D., & Kishony, R.
Venue
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Published
2014-09-22
Volume
111
Issue
40
Pages
14494-14499
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1409800111
OpenAlex
W2111020219
Cited by
264
References
44
FWCI
13.47
Type
journal article
Language
en
Open access
bronze

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.