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The high prevalence of antibiotic heteroresistance in pathogenic bacteria is mainly caused by gene amplification

Nature Microbiologyvolume 4pages504514 (2019) | Download Citation

Abstract

When choosing antibiotics to treat bacterial infections, it is assumed that the susceptibility of the target bacteria to an antibiotic is reflected by laboratory estimates of the minimum inhibitory concentration (MIC) needed to prevent bacterial growth. A caveat of using MIC data for this purpose is heteroresistance, the presence of a resistant subpopulation in a main population of susceptible cells. We investigated the prevalence and mechanisms of heteroresistance in 41 clinical isolates of the pathogens Escherichia coli, Salmonella enterica, Klebsiella pneumoniae and Acinetobacter baumannii against 28 different antibiotics. For the 766 bacteria–antibiotic combinations tested, as much as 27.4% of the total was heteroresistant. Genetic analysis demonstrated that a majority of heteroresistance cases were unstable, with an increased resistance of the subpopulations resulting from spontaneous tandem amplifications, typically including known resistance genes. Using mathematical modelling, we show how heteroresistance in the parameter range estimated in this study can result in the failure of antibiotic treatment of infections with bacteria that are classified as antibiotic susceptible. The high prevalence of heteroresistance with the potential for treatment failure highlights the limitations of MIC as the sole criterion for susceptibility determinations. These results call for the development of facile and rapid protocols to identify heteroresistance in pathogens.

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Data availability

Chromosomes and plasmids are deposited at NCBI under the following accession numbers: DA33098 (CP029569–CP029573), DA33133 (CP029574 and CP029575), DA33135 (CP029576–CP029578), DA33137 (CP029579–CP029581), DA33140 (CP029582–CP029586), DA33141 (CP029587–CP029589), DA33144 (CP029590–CP029592), DA33145 (CP029597–CP029599), DA33382 (CP030106–CP030109), DA34821 (CP029567), DA34827 (CP029593 and CP029594), DA34833 (CP029595 and CP029596) and DA34837 (CP029568). Additional data supporting the findings of this study, such as raw data and bacterial strains, are available upon request.

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Acknowledgements

We thank F.F. Cuenca, P.G. Higgins and C.-H. Chiu for the A. baumannii isolates, L. Sandegren for the E. coli isolates, Å. Melhus and B. Lytsy for some K. pneumoniae isolates and C. Järnberg at The Public Health Agency, Sweden for the S. Typhimurium isolates. We also would like to thank O. Warsi and U. Lustig for helping with the MiSeq sequencer and DNA libraries preparations. This work was supported by grants from the Swedish Research Council, no. 2017-01527 (DIA), and the US National Institutes of General Medical Sciences, no. GM091875 (BRL).

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Author notes

  1. These authors contributed equally: Hervé Nicoloff, Karin Hjort.

Affiliations

  1. Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden

    • Hervé Nicoloff
    • , Karin Hjort
    •  & Dan I. Andersson
  2. Department of Biology, Emory University, Atlanta, GA, USA

    • Bruce R. Levin

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Contributions

H.N., K.H. and D.I.A. designed the study. H.N. and K.H. performed the experiments and B.R.L. the mathematical modelling. H.N., K.H., B.R.L. and D.I.A. wrote the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Dan I. Andersson.

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https://doi.org/10.1038/s41564-018-0342-0