The online version of this article (doi:10.1186/1475-2875-11-77) contains supplementary material, which is available to authorized users.
Andrea M McCollum, Kristan A Schneider contributed equally to this work.
The authors declare that they have no competing interests.
AMM, KAS, AAE, and VU designed the study and drafted the manuscript. AMM, SMG, and ZZ carried out the molecular genetics studies. KAS carried out the theoretical and statistical analyses. SK, FK, YPS, LS, and AAL participated in the design and coordination of sample collection. All authors read and approved the final manuscript.
Understanding the origin and spread of mutations associated with drug resistance, especially in the context of combination therapy, will help guide strategies to halt and prevent the emergence of resistance. Unfortunately, studies have assessed these complex processes when resistance is already highly prevalent. Even further, information on the evolutionary dynamics leading to multidrug-resistant parasites is scattered and limited to areas with low or seasonal malaria transmission. This study describes the dynamics of strong selection for mutations conferring resistance against sulphadoxine-pyrimethamine (SP), a combination therapy, in western Kenya between 1992 and 1999, just before SP became first-line therapy (1999). Importantly, the study is based on longitudinal data, which allows for a comprehensive analysis that contrasts with previous cross-sectional studies carried out in other endemic regions.
This study used 236 blood samples collected between 1992 and 1999 in the Asembo Bay area of Kenya. Pyrosequencing was used to determine the alleles of dihydrofolate reductase (dhfr) and dihydropterote synthase (dhps) genes. Microsatellite alleles spanning 138 kb around dhfr and dhps, as well as, neutral markers spanning approximately 100 kb on chromosomes 2 and 3 were characterized.
By 1992, the South-Asian dhfr triple mutant was already spreading, albeit in low frequency, in this holoendemic Kenyan population, prior to the use of SP as a first-line therapy. Additionally, dhfr triple mutant alleles that originated independently from the predominant Southeast Asian lineage were present in the sample set. Likewise, dhps double mutants were already present as early as 1992. There is evidence for soft selective sweeps of two dhfr mutant alleles and the possible emergence of a selective sweep of double mutant dhps alleles between 1992 and 1997. The longitudinal structure of the dataset allowed estimation of selection pressures on various dhfr and dhps mutants relative to each other based on a theoretical model tailored to P. falciparum. The data indicate that drug selection acted differently on the resistant alleles of dhfr and dhps, as evidenced by fitness differences. Thus a combination drug therapy such as SP, by itself, does not appear to select for "multidrug"-resistant parasites in areas with high recombination rate.
The complexity of these observations emphasizes the importance of population-based studies to evaluate the effects of strong drug selection on Plasmodium falciparum populations.
Additional file 1: Table S1. PCR primers used for dhps microsatellite amplification. (DOC 48 KB)12936_2011_2051_MOESM1_ESM.DOC
Additional file 2: Figure S1. Haplotype frequencies for dhfr alleles: A) 59R/108N (n = 40), B) 51I/108N (n = 72), and C) 51I/59R/108N (n = 26). Haplotypes are along the X axis and frequency in the sample set is along the y axis. (DOC 35 KB)12936_2011_2051_MOESM2_ESM.DOC
Additional file 3: Figure S2. Haplotype frequencies for dhps alleles: A) wildtype (n = 57) and B) 437G/540E (n = 95). Haplotypes are along the X axis and frequency in the sample set is along the y axis. (DOC 36 KB)12936_2011_2051_MOESM3_ESM.DOC
Additional file 4: Figure S3. Relationships among 95 8-locus dhfr microsatellite haplotypes from populations in Western Kenya as determined by eBURST analysis. Samples from 1992-1999 (n = 134 samples) and 2002-2004 (n = 37 samples) were used. Each line connects haplotypes that are identical at 7 of 8 loci. The size of the circles is proportional to the number of isolates of the given haplotype. The blue circles represent founders for the clusters and the yellow circle represent subgroup founders. Black circles without any shading represent haplotypes only present for the samples collected in 1992-1999, green shading represents haplotypes present only in the 2002-2004 collection, and pink shading represents haplotypes present in both collections. 51I/59R/108N haplotypes circled in red are triple mutants that originated independently from the SE Asian haplotype. Two genotypes that include the mutation 164L are noted not being connected to any other haplotype. (DOC 62 KB)12936_2011_2051_MOESM4_ESM.DOC
Additional file 5: Figure S4. Relationships among 128 9-locus dhps microsatellite haplotypes from western Kenya as determined by eBURST analysis. Each line connects haplotypes that are identical at 8 out of 9 loci. The size of the circles is proportional to the number of isolates of the given haplotype. Haplotypes shown as single points differ from the other haplotypes by alleles in at least 2 loci. The central complex represents haplotypes from the 437G/540E allele. A total of 44 samples with the wildtype allele and 84 samples with the 437G/540E allele were utilized for this analysis. (DOC 47 KB)12936_2011_2051_MOESM5_ESM.DOC
Additional file 6: Table S2. Number of alleles (A) and heterozygosity (H e ) per locus and averaged over loci. (DOC 52 KB)12936_2011_2051_MOESM6_ESM.DOC
Additional file 7: Figure S5. Relationships among 128 9-locus dhps microsatellite haplotypes from western Kenya as determined by eBURST analysis. Each line connects haplotypes that are identical at 8 out of 9 loci. The size of the circles is proportional to the number of isolates of the given haplotype. Haplotypes shown as single points differ from the other haplotypes by alleles in at least 2 loci. The central complex represents haplotypes from the 437G/540E allele. A total of 44 samples with the wildtype allele and 84 samples with the 437G/540E allele were utilized for this analysis. (DOC 121 KB)12936_2011_2051_MOESM7_ESM.DOC
Additional file 8: Figure S6. Observed and predicted H e at ms loci around the (A) dhfr allele 51I/59R/108N and (B) dhps allele 437G/540E. For the dhfr prediction (A) we used H e among all samples that did not include the 51I/59R/108N triple mutant (i.e. infections with the mixed codons N51I/S108N and C59R/S108N were included). For the dhps prediction (B) we used H e among wildtype alleles as an estimate for the initial heterozygosity. Loci are labelled according to their positions relative to dhfr or dhps (kb from the gene). Sampling variance is indicated by error bars. (DOC 202 KB)12936_2011_2051_MOESM8_ESM.DOC
Additional file 9: Figure S7. Pairwise LD between microsatellite loci on different chromosomes (A) and between sites in dhfr and dhps (B). Each cell represents one comparison between polymorphic pairs of loci. Gray cells represent significance at p value < 0.01. (A) The position of dhfr and dhps along the chromosome is denoted by the gray bar. The location of each microsatellite locus is at the top of the matrix (loci are named according to their positions relative to dhfr or dhps or along chromosome 2 or 3 according to the 3D7 genome sequence available from NCBI). (B) Pairwise LD between sites in dhfr (51, 59, 108) and dhps (436, 437, 540). (DOC 429 KB)12936_2011_2051_MOESM9_ESM.DOC
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- Differences in selective pressure on dhps and dhfr drug resistant mutations in western Kenya
Andrea M McCollum
Kristan A Schneider
Sean M Griffing
Ya Ping Shi
Altaf A Lal
Ananias A Escalante
- BioMed Central
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