falciparum dihydrofolate reductase and

Trends in drug resistance codons in Plasmodiu

The Genotypic and Phenotypic Stability of Plasmodium falciparum Field Isolates in Continuous In Vitro Culture.

The Plasmodium falciparum in vitro culture system is critical for genotypic and phenotypic analyses of the parasites. For genotypic analysis, the genomic DNA can be obtained directly from the patient blood sample or from culture adapted parasites whereas for phenotypic analysis, immediate ex vivo or in vitro culture adapted parasites are used. However, parasite biology studies have not investigated whether culture adaptation process affects genotypic and/or phenotypic characteristics of the parasites in short- or long-term cultures. Here, we set out to study the dynamics and stability of parasite genetic and phenotypic profiles as field isolate parasites were adapted in continuous cultures. Parasites collected from three different patients presenting with uncomplicated malaria were adapted and maintained in drug-free continuous cultures. Aliquots from the continuous cultures were collected every 24-48 hours for analyses. Each aliquot was treated as a separate parasite sample. For genetic analysis, microsatellite (MS) typing and single nucleotide polymorphism (SNP) analyses of 23 drug resistance markers were done. The 50% inhibitory concentrations (IC50) for some of the samples were also established for four antimalarial drugs. Samples from each patient (parasite-line) were compared as they were passed through the continuous culture. Data revealed genotypic and phenotypic profiles for the three parasite-lines fluctuated from one generation to the next with no specific pattern or periodicity. With few exceptions, multilocus analysis revealed samples from each parasite-line had high genetic diversity with unique haplotypes. Interestingly, changes in MS and SNP profiles occurred simultaneously. The difference in the IC50s of samples in each parasite-line reached statistical significance. However, phenotypic changes did not correspond or correlate to genotypic changes. Our study revealed parasite genetic and phenotypic characteristics fluctuates in short- and long-term cultures, which indicates parasite genetic information obtained even in short cultures is likely to be different from the natural infection parasites

Median-joining network diagram for MS data.

<p>Diagram showing relationship of the different parasite generations in H63 parasite-line samples. The multilocus MS haplotypes profiles were constructed for each of the parasite generations using the 12 MS markers located across the <i>P</i>. <i>falciparum</i> genome. The 26 generations of the cultured <i>P</i>. <i>falciparum</i> field isolates analyzed formed 18 unique 12-loci microsatellite haplotypes. For allele sizes please refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143565#pone.0143565.s004" target="_blank">S4 Table</a>. Each circle in the network represents a unique MS haplotype with the size of the circle being proportional to the number of isolates showing that particular haplotype. The red dots are hypothetical median vectors generated by the software to connect existing haplotypes within the network with maximum parsimony.</p

Phylogeny tree diagram for SNP data.

<p>Phylogeny tree constructed using SNP haplotypes of samples in H63 parasite-line. The SNP haplotype profiles are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143565#pone.0143565.s003" target="_blank">S3 Table</a>. Bayesian algorithm was used to infer the number of genetically related clusters from the individual SNP haplotype profiles generated using the 30-drug resistance SNPs.</p

Selective sweeps and genetic lineages of Plasmodium falciparum multi-drug resistance (pfmdr1) gene in Kenya

Abstract Background There are concerns that resistance to artemisinin-based combination therapy might emerge in Kenya and sub-Saharan Africa (SSA) in the same pattern as was with chloroquine and sulfadoxine–pyrimethamine. Single nucleotide polymorphisms (SNPs) in critical alleles of pfmdr1 gene have been associated with resistance to artemisinin and its partner drugs. Microsatellite analysis of loci flanking genes associated with anti-malarial drug resistance has been used in defining the geographic origins, dissemination of resistant parasites and identifying regions in the genome that have been under selection. Methods This study set out to investigate evidence of selective sweep and genetic lineages in pfmdr1 genotypes associated with the use of artemether–lumefantrine (AL), as the first-line treatment in Kenya. Parasites (n = 252) from different regions in Kenya were assayed for SNPs at codons 86, 184 and 1246 and typed for 7 neutral microsatellites and 13 microsatellites loci flanking (± 99 kb) pfmdr1 in Plasmodium falciparum infections. Results The data showed differential site and region specific prevalence of SNPs associated with drug resistance in the pfmdr1 gene. The prevalence of pfmdr1 N86, 184F, and D1246 in western Kenya (Kisumu, Kericho and Kisii) compared to the coast of Kenya (Malindi) was 92.9% vs. 66.7%, 53.5% vs. to 24.2% and 96% vs. to 87.9%, respectively. The NFD haplotype which is consistent with AL selection was at 51% in western Kenya compared to 25% in coastal Kenya. Conclusion Selection pressures were observed to be different in different regions of Kenya, especially the western region compared to the coastal region. The data showed independent genetic lineages for all the pfmdr1 alleles. The evidence of soft sweeps in pfmdr1 observed varied in direction from one region to another. This is challenging for malaria control programs in SSA which clearly indicate effective malaria control policies should be based on the region and not at a country wide level

Genetically Determined Response to Artemisinin Treatment in Western Kenyan <i>Plasmodium falciparum</i> Parasites

<div><p>Genetically determined artemisinin resistance in <i>Plasmodium falciparum</i> has been described in Southeast Asia. The relevance of recently described Kelch 13-propeller mutations for artemisinin resistance in Sub-Saharan Africa parasites is still unknown. Southeast Asia parasites have low genetic diversity compared to Sub-Saharan Africa, where parasites are highly genetically diverse. This study attempted to elucidate whether genetics provides a basis for discovering molecular markers in response to artemisinin drug treatment in <i>P</i>. <i>falciparum</i> in Kenya. The genetic diversity of parasites collected pre- and post- introduction of artemisinin combination therapy (ACT) in western Kenya was determined. A panel of 12 microsatellites and 91 single nucleotide polymorphisms (SNPs) distributed across the <i>P</i>. <i>falciparum</i> genome were genotyped. Parasite clearance rates were obtained for the post-ACT parasites. The 12 microsatellites were highly polymorphic with post-ACT parasites being significantly more diverse compared to pre-ACT (p < 0.0001). The median clearance half-life was 2.55 hours for the post-ACT parasites. Based on SNP analysis, 15 of 90 post-ACT parasites were single-clone infections. Analysis revealed 3 SNPs that might have some causal association with parasite clearance rates. Further, genetic analysis using Bayesian tree revealed parasites with similar clearance phenotypes were more closely genetically related. With further studies, SNPs described here and genetically determined response to artemisinin treatment might be useful in tracking artemisinin resistance in Kenya.</p></div

Principal Coordinate Analysis.

<p>Microsatellite data for both pre- and post-ACTs were used to find out patterns and relationships within a multivariate dataset. This graph was plotted using genetic distance matrix; blue dots for pre- and red dots for post-ACTs populations. This data shows the separation of the parasite genetic profiles in the two ACTs eras.</p

SNP-based genotypes and genetic variation seen in 15 single clones in Western Kenya in 2013–2014.

<p>Median-joining network diagram above shows genetic relationship of the western Kenya samples using 78 SNP haplotypes. Each circle in the network represents a unique haplotype profile with the size of the circle being proportional to the number of clones showing that particular haplotypes. The circle shown in red stands for samples with clearance rate < 2.55 slope half-life (hours) while those colored in blue represent those with clearance rate >2.55 hours. The black dots are hypothetical median vector generated by the software to connect existing haplotypes within the network with maximum parsimony.</p

Post-test Analysis of the 3 SNPs using Bonferroni’s multiple comparison test.

<p>Post-test Analysis of the 3 SNPs using Bonferroni’s multiple comparison test.</p

Correlation between 78 genome-wide SNPs and parasite clearance half-life.

<p>The 3 SNPs out of 78 genome-wide SNPs genotyped which showed positive correlation with clearance half-life with statistical significance (p < 0.05; CI 95%). The SNPs are as follows: <b>*MAL12-1156125 (MAL12), MAL14-1199184 (MAL14A) and MAL14-3017684 (MAL14B)</b> showing their wild type (WT) and mutant (MT) states.</p