On the evolutionary ecology of multidrug resistance in bacteria
File(s)
Author(s)
Type
Journal Article
Abstract
Resistance against different antibiotics appears on the same bacterial strains more often
than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics
and/or bacterial species, whereas the trend is pervasive. Here, we consider the question
in terms of strain ecology: explaining why resistance to different antibiotics is often seen on
the same strain requires an understanding of the competition between strains with different
resistance profiles. This work builds on models originally proposed to explain another aspect
of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed
in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance
between these sub-populations, thus creating niches for sensitivity and resistance. We then
generalise this unified underlying model to multidrug resistance and show that models with
this structure predict high levels of association between resistance to different drugs and
high multidrug resistance frequencies. We test predictions from this model in six bacterial
datasets and find them to be qualitatively consistent with observed trends. The higher than
expected frequencies of multidrug resistance are often interpreted as evidence that these
strains are out-competing strains with lower resistance multiplicity. Our work provides an
alternative explanation that is compatible with long-term stability in resistance frequencies.
than expected by chance, leading to high frequencies of multidrug resistance. There are multiple explanations for this observation, but these tend to be specific to subsets of antibiotics
and/or bacterial species, whereas the trend is pervasive. Here, we consider the question
in terms of strain ecology: explaining why resistance to different antibiotics is often seen on
the same strain requires an understanding of the competition between strains with different
resistance profiles. This work builds on models originally proposed to explain another aspect
of strain competition: the stable coexistence of antibiotic sensitivity and resistance observed
in a number of bacterial species. We first identify a partial structural similarity in these models: either strain or host population structure stratifies the pathogen population into evolutionarily independent sub-populations and introduces variation in the fitness effect of resistance
between these sub-populations, thus creating niches for sensitivity and resistance. We then
generalise this unified underlying model to multidrug resistance and show that models with
this structure predict high levels of association between resistance to different drugs and
high multidrug resistance frequencies. We test predictions from this model in six bacterial
datasets and find them to be qualitatively consistent with observed trends. The higher than
expected frequencies of multidrug resistance are often interpreted as evidence that these
strains are out-competing strains with lower resistance multiplicity. Our work provides an
alternative explanation that is compatible with long-term stability in resistance frequencies.
Date Issued
2019-05-13
Date Acceptance
2019-04-15
Citation
PLoS Pathogens, 2019, 15 (5)
ISSN
1553-7366
Publisher
Public Library of Science (PLoS)
Journal / Book Title
PLoS Pathogens
Volume
15
Issue
5
Copyright Statement
© 2019 Lehtinen et al. 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.
Sponsor
Wellcome Trust
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000471180400026&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
104169/Z/14/Z
Subjects
Science & Technology
Life Sciences & Biomedicine
Microbiology
Parasitology
Virology
MULTIPLE-DRUG RESISTANCE
ANTIBIOTIC-RESISTANCE
ESCHERICHIA-COLI
COEXISTENCE
EPISTASIS
MECHANISM
Publication Status
Published
Article Number
e1007763
Date Publish Online
2019-05-13