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Evolution of high mutation rates in experimental populations of E. coli

Author

Listed:
  • Paul D. Sniegowski

    (University of Pennsylvania)

  • Philip J. Gerrish

    (†Center for Microbial Ecology, Michigan State University)

  • Richard E. Lenski

    (†Center for Microbial Ecology, Michigan State University)

Abstract

Most mutations are likely to be deleterious, and so the spontaneous mutation rate is generally held at a very low value1. Nonetheless, evolutionary theory predicts that high mutation rates can evolve under certain circumstances2,3,4. Empirical observations have previously been limited to short-term studies of the fates of mutator strains deliberately introduced into laboratory populations of Escherichia coli5,6,7, and to the effects of intense selective events on mutator frequencies in E. coli8. Here we report the rise of spontaneously originated mutators in populations of E. coli undergoing long-term adaptation to a new environment. Our results corroborate computer simulations of mutator evolution in adapting clonal populations4, and may help to explain observations that associate high mutation rates with emerging pathogens9 and with certain cancers10.

Suggested Citation

  • Paul D. Sniegowski & Philip J. Gerrish & Richard E. Lenski, 1997. "Evolution of high mutation rates in experimental populations of E. coli," Nature, Nature, vol. 387(6634), pages 703-705, June.
    • Handle: RePEc:nat:nature:v:387:y:1997:i:6634:d:10.1038_42701
    DOI: 10.1038/42701
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    Citations

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    Cited by:

    1. Rachel L. Moran & Emilie J. Richards & Claudia Patricia Ornelas-García & Joshua B. Gross & Alexandra Donny & Jonathan Wiese & Alex C. Keene & Johanna E. Kowalko & Nicolas Rohner & Suzanne E. McGaugh, 2023. "Selection-driven trait loss in independently evolved cavefish populations," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    2. Richard E. Lenski & Terence C. Burnham, 2018. "Experimental evolution of bacteria across 60,000 generations, and what it might mean for economics and human decision-making," Journal of Bioeconomics, Springer, vol. 20(1), pages 107-124, April.
    3. Jeremy W Fox & Richard E Lenski, 2015. "From Here to Eternity—The Theory and Practice of a Really Long Experiment," PLOS Biology, Public Library of Science, vol. 13(6), pages 1-9, June.
    4. Nicholas Leiby & Christopher J Marx, 2014. "Metabolic Erosion Primarily Through Mutation Accumulation, and Not Tradeoffs, Drives Limited Evolution of Substrate Specificity in Escherichia coli," PLOS Biology, Public Library of Science, vol. 12(2), pages 1-10, February.
    5. Qiming Zhang & Zhilin Xia & Yi-Bing Cheng & Min Gu, 2018. "High-capacity optical long data memory based on enhanced Young’s modulus in nanoplasmonic hybrid glass composites," Nature Communications, Nature, vol. 9(1), pages 1-6, December.
    6. Michael Habig & Cecile Lorrain & Alice Feurtey & Jovan Komluski & Eva H. Stukenbrock, 2021. "Epigenetic modifications affect the rate of spontaneous mutations in a pathogenic fungus," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    7. Greenspoon, Philip B. & Mideo, Nicole, 2017. "Evolutionary rescue of a parasite population by mutation rate evolution," Theoretical Population Biology, Elsevier, vol. 117(C), pages 64-75.
    8. Joao A. Ascensao & Kelly M. Wetmore & Benjamin H. Good & Adam P. Arkin & Oskar Hallatschek, 2023. "Quantifying the local adaptive landscape of a nascent bacterial community," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    9. M’Gonigle, L.K. & Shen, J.J. & Otto, S.P., 2009. "Mutating away from your enemies: The evolution of mutation rate in a host–parasite system," Theoretical Population Biology, Elsevier, vol. 75(4), pages 301-311.
    10. Wen Wei & Wei-Chin Ho & Megan G. Behringer & Samuel F. Miller & George Bcharah & Michael Lynch, 2022. "Rapid evolution of mutation rate and spectrum in response to environmental and population-genetic challenges," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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