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Evolutionary rescue of a parasite population by mutation rate evolution

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  • Greenspoon, Philip B.
  • Mideo, Nicole

Abstract

The risk of antibiotic resistance evolution in parasites is a major problem for public health. Identifying factors which promote antibiotic resistance evolution is thus a priority in evolutionary medicine. The rate at which new mutations enter the parasite population is one important predictor; however, mutation rate is not necessarily a fixed quantity, as is often assumed, but can itself evolve. Here we explore the possible impacts of mutation rate evolution on the fate of a disease circulating in a host population, which is being treated with drugs, the use of which varies over time. Using an evolutionary rescue framework, we find that mutation rate evolution provides a dramatic increase in the probability that a parasite population survives treatment in only a limited region, while providing little or no advantage in other regions. Both epidemiological features, such as the virulence of infection, and population genetic parameters, such as recombination rate, play important roles in determining the probability of evolutionary rescue and whether mutation rate evolution enhances the probability of evolutionary rescue or not. While efforts to curtail mutation rate evolution in parasites may be worthwhile under some circumstances, our results suggest that this need not always be the case.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:thpobi:v:117:y:2017:i:c:p:64-75
    DOI: 10.1016/j.tpb.2017.08.004
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    References listed on IDEAS

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    1. Remy Chait & Allison Craney & Roy Kishony, 2007. "Antibiotic interactions that select against resistance," Nature, Nature, vol. 446(7136), pages 668-671, April.
    2. F. Taddei & M. Radman & J. Maynard-Smith & B. Toupance & P. H. Gouyon & B. Godelle, 1997. "Role of mutator alleles in adaptive evolution," Nature, Nature, vol. 387(6634), pages 700-702, June.
    3. Troy Day & Andrew F Read, 2016. "Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?," PLOS Computational Biology, Public Library of Science, vol. 12(1), pages 1-20, January.
    4. Haley A. Lindsey & Jenna Gallie & Susan Taylor & Benjamin Kerr, 2013. "Evolutionary rescue from extinction is contingent on a lower rate of environmental change," Nature, Nature, vol. 494(7438), pages 463-467, February.
    5. 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.
    6. Pia Abel zur Wiesch & Roger Kouyos & Sören Abel & Wolfgang Viechtbauer & Sebastian Bonhoeffer, 2014. "Cycling Empirical Antibiotic Therapy in Hospitals: Meta-Analysis and Models," PLOS Pathogens, Public Library of Science, vol. 10(6), pages 1-13, June.
    7. Csaba Pal & María D. Maciá & Antonio Oliver & Ira Schachar & Angus Buckling, 2007. "Coevolution with viruses drives the evolution of bacterial mutation rates," Nature, Nature, vol. 450(7172), pages 1079-1081, December.
    8. 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.
    9. Luis-Miguel Chevin & Russell Lande & Georgina M Mace, 2010. "Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory," Working Papers id:2494, eSocialSciences.
    10. Luis-Miguel Chevin & Russell Lande & Georgina M Mace, 2010. "Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory," PLOS Biology, Public Library of Science, vol. 8(4), pages 1-8, April.
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