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Experimental coevolution leads to a decrease in parasite-induced host mortality.

C Bérénos1, P Schmid-Hempel, K M Wegner

  • 1Institute of Integrative Biology, Experimental Ecology, ETH Zürich Universitätstrasse, Zürich, Switzerland. camillo.berenos@ed.ac.uk

Journal of Evolutionary Biology
|May 24, 2011
PubMed
Summary
This summary is machine-generated.

This study explored host-parasite coevolution in sexual organisms. Over 13 generations, parasite-induced mortality decreased, suggesting adaptation or reduced virulence in Tribolium castaneum and Nosema whitei.

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Area of Science:

  • Evolutionary Biology
  • Ecology
  • Genetics

Background:

  • Host-parasite coevolution is crucial for understanding biodiversity.
  • Experimental studies often focus on clonal organisms, neglecting sexual populations.
  • Obligately out-crossing organisms present unique challenges for coevolutionary studies.

Purpose of the Study:

  • To investigate host-parasite coevolution in an obligately out-crossing system.
  • To assess the impact of experimental coevolution on parasite virulence.
  • To understand the dynamics of adaptation in sexual host-parasite interactions.

Main Methods:

  • Utilized four distinct genetic lines of Tribolium castaneum (host).
  • Introduced the obligately killing microsporidian parasite, Nosema whitei.
  • Conducted a 13-generation experimental coevolution study.
  • Employed a time-shift experiment to assess parasite virulence across generations.

Main Results:

  • Initially, parasite-induced mortality fluctuated synchronously across host lines.
  • A general decrease in parasite-induced mortality was observed over 13 generations.
  • This decrease may indicate adaptation to sexual hosts or optimized virulence.

Conclusions:

  • Experimental coevolution in sexual organisms can lead to reduced parasite virulence.
  • The study highlights the importance of considering host mating systems in coevolutionary research.
  • Further investigation is needed to differentiate between adaptation and virulence optimization.