Malaria Journal (May 2011)

Selection of drug resistant mutants from random library of <it>Plasmodium falciparum </it>dihydrofolate reductase in <it>Plasmodium berghei </it>model

  • Yuthavong Yongyuth,
  • Kamchonwongpaisan Sumalee,
  • Srichairatanakool Somdet,
  • Tipsuwan Wachiraporn,
  • Uthaipibull Chairat

DOI
https://doi.org/10.1186/1475-2875-10-119
Journal volume & issue
Vol. 10, no. 1
p. 119

Abstract

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Abstract Background The prevalence of drug resistance amongst the human malaria Plasmodium species has most commonly been associated with genomic mutation within the parasites. This phenomenon necessitates evolutionary predictive studies of possible resistance mutations, which may occur when a new drug is introduced. Therefore, identification of possible new Plasmodium falciparum dihydrofolate reductase (PfDHFR) mutants that confer resistance to antifolate drugs is essential in the process of antifolate anti-malarial drug development. Methods A system to identify mutations in Pfdhfr gene that confer antifolate drug resistance using an animal Plasmodium parasite model was developed. By using error-prone PCR and Plasmodium transfection technologies, libraries of Pfdhfr mutant were generated and then episomally transfected to Plasmodium berghei parasites, from which pyrimethamine-resistant PfDHFR mutants were selected. Results The principal mutation found from this experiment was S108N, coincident with the first pyrimethamine-resistance mutation isolated from the field. A transgenic P. berghei, in which endogenous Pbdhfr allele was replaced with the mutant PfdhfrS108N, was generated and confirmed to have normal growth rate comparing to parental non-transgenic parasite and also confer resistance to pyrimethamine. Conclusion This study demonstrated the power of the transgenic P. berghei system to predict drug-resistant Pfdhfr mutations in an in vivo parasite/host setting. The system could be utilized for identification of possible novel drug-resistant mutants that could arise against new antifolate compounds and for prediction the evolution of resistance mutations.