Determining the optimal developmental route of Strongyloides ratti: an evolutionarily stable strategy approach.
Understanding the processes that drive parasite evolution is crucial to the development of management programs that sustain long-term, effective control of infectious disease in the face of parasite adaptation. Here we present a novel evolutionarily stable strategy (ESS) model of the developmental decisions of a nematode parasite, Strongyloides ratti. The genus Strongyloides exhibits an unusual developmental plasticity such that progeny from an individual may either develop via a direct (homogonic) route, where the developing larvae are infective to new hosts, or an indirect (heterogonic) route, where the larvae develop into free-living, dioecious adults that undergo at least one bout of sexual reproduction outside the host, before producing offspring that develop into infective larvae. The model correctly predicts a number of observed features of the parasite's behavior and shows that this plasticity may be adaptive such that pure homogonic development, pure heterogonic development, or a mixed strategy may be optimal depending on the prevailing environmental conditions, both within and outside the host. Importantly, our results depend only on the benefits of an extra round of reproduction in the environment external to the host and not on benefits to sexual reproduction through the purging of deleterious mutation or the generation of novel, favorable genotypes. The ESS framework presented here provides a powerful, general approach to predict how macroparasites, the agents of many of the world's most important infectious diseases, will evolve in response to the various selection pressures imposed by different control regimes in the future.
Fenton
Andrew
A
Institute of Zoology, The Zoological Society of London, Regents Park, London NW1 4RY, United Kingdom. Andrew.Fenton@ioz.ac.uk
Paterson
Steve
S
Viney
Mark E
ME
Gardner
Michael P
MP
D000220:Adaptation, Biological; D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D008018:Life Cycle Stages / Q000502:physiology*; D008954:Models, Biological; D012098:Reproduction / Q000502:physiology; D012641:Selection, Genetic; D013321:Strongyloides / Q000254:growth & development*