Abstracts (first author)


Selection, characterization and the within-host ecology of drug resistant malaria parasites

Author(s): Pollitt LC, Huijben S, Read AF


The evolution of drug resistance is a key challenge for our ability to treat and control infections. For malaria parasites artemisinin based drugs are the front line weapons in the fight against disease, but reports from the field of slower clearance rates, are causing concern that the useful life-span of these drugs may be limited. Understanding whether slower clearance rates represent true resistance, and predicting the speed at which this could spread in the field, is challenging due to host effects on clearance rates and the lack of molecular markers. Here we show that Plasmodium chabaudi malaria parasites selected for Artesunate resistance evolve slower clearance rates, similar to those seen in the field, extremely rapidly. These slower clearance rates provide a fitness advantage to parasites exposed to drugs within single infections where overall parasite density, relapse after treatment and transmission potential is higher. Within mixed infections, the fitness advantage is even stronger, as selected parasites experience release from competition with susceptible strains, resulting in higher total parasite densities and greater transmission potential. Additionally, the magnitude of competitive release within mixed infections is dependent on the strength of drug treatment. More aggressive treatment results in a stronger selective advantage to resistant parasites, despite not providing an additional health benefit to hosts when compared to treatment with lower drug doses. Our results show that slower clearance rates can rapidly evolve and provide a strong fitness advantage both in single and mixed strain infections, suggesting this phenotype has the potential to spread within parasite populations. Furthermore, drug dose dramatically influences fitness and transmission potential of resistant parasites, suggesting careful consideration should be given to selecting optimal treatment regimes.


Chairman: Octávio S. Paulo
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XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon


Computational Biology & Population Genomics Group