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Steering evolution with sequential therapy to prevent the emergence of bacterial antibiotic resistance

Abstract:

The increasing rate of antibiotic resistance and slowing discovery of novel antibiotic treatments presents a growing threat to public health. Here, we consider a simple model of evolution in asexually reproducing populations which considers adaptation as a biased random walk on a fitness landscape. This model associates the global properties of the fitness landscape with the algebraic properties of a Markov chain transition matrix and allows us to derive general results on the non-commutativi...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1004493

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Institution:
University of Oxford
Division:
MPLS
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Role:
Author
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Publisher:
Public Library of Science Publisher's website
Journal:
PLoS Computational Biology Journal website
Volume:
11
Issue:
9
Article number:
e1004493
Publication date:
2015-09-11
Acceptance date:
2019-08-07
DOI:
EISSN:
1553-7358
ISSN:
1553-734X
Source identifiers:
571800
Language:
English
Pubs id:
pubs:571800
UUID:
uuid:39c50aee-1ae7-4241-a792-8cd36d6bca03
Local pid:
pubs:571800
Deposit date:
2016-02-27

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