Abstract

While specific mutations allow organisms to adapt to stressful environments, most changes in an organism's DNA negatively impact fitness. The mutation rate is therefore strictly regulated and often considered a slowly-evolving parameter. In contrast, we demonstrate an unexpected flexibility in cellular mutation rates as a response to changes in selective pressure. We show that hypermutation independently evolves when different Escherichia coli cultures adapt to high ethanol stress. Furthermore, hypermutator states are transitory and repeatedly alternate with decreases in mutation rate. Specifically, population mutation rates rise when cells experience higher stress and decline again once cells are adapted. Interestingly, we identified cellular mortality as the major force driving the quick evolution of mutation rates. Together, these findings show how organisms balance robustness and evolvability and help explain the prevalence of hypermutation in various settings, ranging from emergence of antibiotic resistance in microbes to cancer relapses upon chemotherapy.

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Article and author information

Author details

  1. Toon Swings

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1225-3377
  2. Bram Van den Bergh

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  3. Sander Wuyts

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  4. Eline Oeyen

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  5. Karin Voordeckers

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  6. Kevin J Verstrepen

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  7. Maarten Fauvart

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  8. Natalie Verstraeten

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  9. Jan Michiels

    Centre of Microbial and Plant Genetics, KU Leuven - University of Leuven, Leuven, Belgium
    For correspondence
    jan.michiels@kuleuven.be
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5829-0897

Funding

Agentschap voor Innovatie door Wetenschap en Technologie (Strategic Basic Research Fellowship,121525)

  • Toon Swings

Fonds Wetenschappelijk Onderzoek (Postdoctoral Fellowship,1249117N)

  • Karin Voordeckers

Onderzoeksraad, KU Leuven (IDO/09/010)

  • Kevin J Verstrepen
  • Jan Michiels

Onderzoeksraad, KU Leuven (IDO/13/008)

  • Jan Michiels

Onderzoeksraad, KU Leuven (CREA/13/019)

  • Maarten Fauvart

Onderzoeksraad, KU Leuven (DBOF/12/035; DBOF/14/049)

  • Kevin J Verstrepen
  • Jan Michiels

Fonds Wetenschappelijk Onderzoek (KAN2014 1.5.222.14)

  • Maarten Fauvart

Onderzoeksraad, KU Leuven (PF/10/010)

  • Kevin J Verstrepen
  • Jan Michiels

Interuniversity Attraction Poles-Belgian Science Policy Office (IAP P7/28)

  • Jan Michiels

H2020 European Research Council (241426)

  • Kevin J Verstrepen

Human Frontier Science Program (RGP0050/2013)

  • Kevin J Verstrepen

Fonds Wetenschappelijk Onderzoek (G047112N)

  • Jan Michiels

Vlaams Instituut voor Biotechnologie

  • Kevin J Verstrepen

European Molecular Biology Organization

  • Kevin J Verstrepen

Fonds Wetenschappelijk Onderzoek (Postdoctoral Fellowship,12O1917N)

  • Bram Van den Bergh

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Wenying Shou, Fred Hutchinson Cancer Research Center, United States

Version history

  1. Received: November 3, 2016
  2. Accepted: April 18, 2017
  3. Accepted Manuscript published: May 2, 2017 (version 1)
  4. Version of Record published: May 12, 2017 (version 2)

Copyright

© 2017, Swings 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.

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  1. Toon Swings
  2. Bram Van den Bergh
  3. Sander Wuyts
  4. Eline Oeyen
  5. Karin Voordeckers
  6. Kevin J Verstrepen
  7. Maarten Fauvart
  8. Natalie Verstraeten
  9. Jan Michiels
(2017)
Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli
eLife 6:e22939.
https://doi.org/10.7554/eLife.22939

Share this article

https://doi.org/10.7554/eLife.22939

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    End-stage renal disease (ESRD) patients experience immune compromise characterized by complex alterations of both innate and adaptive immunity, and results in higher susceptibility to infection and lower response to vaccination. This immune compromise, coupled with greater risk of exposure to infectious disease at hemodialysis (HD) centers, underscores the need for examination of the immune response to the COVID-19 mRNA-based vaccines.

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    The immune response to the COVID-19 BNT162b2 mRNA vaccine was assessed in 20 HD patients and cohort-matched controls. RNA sequencing of peripheral blood mononuclear cells was performed longitudinally before and after each vaccination dose for a total of six time points per subject. Anti-spike antibody levels were quantified prior to the first vaccination dose (V1D0) and 7 d after the second dose (V2D7) using anti-spike IgG titers and antibody neutralization assays. Anti-spike IgG titers were additionally quantified 6 mo after initial vaccination. Clinical history and lab values in HD patients were obtained to identify predictors of vaccination response.

    Results:

    Transcriptomic analyses demonstrated differing time courses of immune responses, with prolonged myeloid cell activity in HD at 1 wk after the first vaccination dose. HD also demonstrated decreased metabolic activity and decreased antigen presentation compared to controls after the second vaccination dose. Anti-spike IgG titers and neutralizing function were substantially elevated in both controls and HD at V2D7, with a small but significant reduction in titers in HD groups (p<0.05). Anti-spike IgG remained elevated above baseline at 6 mo in both subject groups. Anti-spike IgG titers at V2D7 were highly predictive of 6-month titer levels. Transcriptomic biomarkers after the second vaccination dose and clinical biomarkers including ferritin levels were found to be predictive of antibody development.

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    Funding:

    F30HD102093, F30HL151182, T32HL144909, R01HL138628. This research has been funded by the University of Illinois at Chicago Center for Clinical and Translational Science (CCTS) award UL1TR002003.