Rapid decline of bacterial drug-resistance in an antibiotic-free environment through phenotypic reversion
Abstract
Antibiotic resistance typically induces a fitness cost that shapes the fate of antibiotic-resistant bacterial populations. However, the cost of resistance can be mitigated by compensatory mutations elsewhere in the genome, and therefore the loss of resistance may proceed too slowly to be of practical importance. We present our study on the efficacy and phenotypic impact of compensatory evolution in Escherichia coli strains carrying multiple resistance mutations. We have demonstrated that drug-resistance frequently declines within 480 generations during exposure to an antibiotic-free environment. The extent of resistance loss was found to be generally antibiotic-specific, driven by mutations that reduce both resistance level and fitness costs of antibiotic-resistance mutations. We conclude that phenotypic reversion to the antibiotic-sensitive state can be mediated by the acquisition of additional mutations, while maintaining the original resistance mutations. Our study indicates that restricting antimicrobial usage could be a useful policy, but for certain antibiotics only.
Data availability
Sequencing data have been deposited in the NCBI Sequence Read Archive (SRA) under the accession number of PRJNA529335.
-
WGSS of antibiotic resistant E. coli strains evolved on antibiotic-free mediumNCBI Sequence Read Archive, PRJNA529335.
Article and author information
Author details
Funding
H2020 European Research Council (H2020-ERC-2014-CoG 648364 - Resistance Evolution)
- Csaba Pal
Magyar Tudományos Akadémia (Lendület Programme LP 2012-32/2018)
- Csaba Pal
Magyar Tudományos Akadémia (Postdoctoral Programme PD-007/2016)
- Viktoria Lazar
Magyar Tudományos Akadémia (Postdoctoral Programme PD-038/2015)
- Zoltán Farkas
National Research, Development and Innovation Office (NKFI-112294)
- Laszlo Bodai
Magyar Tudományos Akadémia (Lendület Programme LP2009-013/2012)
- Balazs Papp
Gazdaságfejlesztési és Innovációs Operatív Programm (GINOP-2.3.2-15-2016-00014)
- Csaba Pal
Gazdaságfejlesztési és Innovációs Operatív Programm (GINOP-2.3.2-15-2016-00020)
- Csaba Pal
Momentum Programme of the Hungarian Academy of Sciences (LP-2017-10/2017)
- Csaba Pal
National Research, Development and Innovation Office (Élvonal Programme KKP 126506)
- Csaba Pal
Wellcome Trust (WT 098016/Z/11/Z)
- Balazs Papp
Gazdaságfejlesztési és Innovációs Operatív Programm (GINOP-2.3.2-15-2016-00026)
- Balazs Papp
Wellcome Trust (WT 084314/Z/07/Z)
- Csaba Pal
National Research, Development and Innovation Office (FK 128775)
- Zoltán Farkas
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Dunai et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 6,093
- views
-
- 676
- downloads
-
- 71
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 71
- citations for umbrella DOI https://doi.org/10.7554/eLife.47088