Person:

Ndiaye, Daouda

We used a high-density single-nucleotide polymorphism array to genotype 75 Plasmodium falciparum isolates recently collected from Senegal and The Gambia to search for signals of selection in this malaria endemic region. We found little geographic or temporal stratification of the genetic diversity among the sampled parasites. Through application of the iHS and REHH haplotype-based tests for positive selection, we found evidence of recent selective sweeps at a known drug resistance locus, at several known antigenic loci, and at several genomic regions not previously identified as sites of recent selection. We discuss the value of deep population-specific genomic analyses for identifying selection signals within sampled endemic populations of parasites, which may correspond to local selection pressures such as distinctive therapeutic regimes or mosquito vectors.

The Plasmodium falciparum parasite's ability to adapt to environmental pressures, such as the human immune system and antimalarial drugs, makes malaria an enduring burden to public health. Understanding the genetic basis of these adaptations is critical to intervening successfully against malaria. To that end, we created a high-density genotyping array that assays over 17,000 single nucleotide polymorphisms (~1 SNP/kb), and applied it to 57 culture-adapted parasites from three continents. We characterized genome-wide genetic diversity within and between populations and identified numerous loci with signals of natural selection, suggesting their role in recent adaptation. In addition, we performed a genome-wide association study (GWAS), searching for loci correlated with resistance to thirteen antimalarials; we detected both known and novel resistance loci, including a new halofantrine resistance locus, PF10_0355. Through functional testing we demonstrated that PF10_0355 overexpression decreases sensitivity to halofantrine, mefloquine, and lumefantrine, but not to structurally unrelated antimalarials, and that increased gene copy number mediates resistance. Our GWAS and follow-on functional validation demonstrate the potential of genome-wide studies to elucidate functionally important loci in the malaria parasite genome.

To study the effects of malaria-control interventions on parasite population genomics, we examined a set of 1,007 samples of the malaria parasite Plasmodium falciparum collected in Thiès, Senegal between 2006 and 2013. The parasite samples were genotyped using a molecular barcode of 24 SNPs. About 35% of the samples grouped into subsets with identical barcodes, varying in size by year and sometimes persisting across years. The barcodes also formed networks of related groups. Analysis of 164 completely sequenced parasites revealed extensive sharing of genomic regions. In at least two cases we found first-generation recombinant offspring of parents whose genomes are similar or identical to genomes also present in the sample. An epidemiological model that tracks parasite genotypes can reproduce the observed pattern of barcode subsets. Quantification of likelihoods in the model strongly suggests a reduction of transmission from 2006-2010 with a significant rebound in 2012-2013. The reduced transmission and rebound were confirmed directly by incidence data from Thiès. These findings imply that intensive intervention to control malaria results in rapid and dramatic changes in parasite population genomics. The results also suggest that genomics combined with epidemiological modeling may afford prompt, continuous, and cost-effective tracking of progress toward malaria elimination.

Through rapid genetic adaptation and natural selection, the Plasmodium falciparum parasite—the deadliest of those that cause malaria—is able to develop resistance to antimalarial drugs, thwarting present efforts to control it. Genome-wide association studies (GWAS) provide a critical hypothesis-generating tool for understanding how this occurs. However, in P. falciparum, the limited amount of linkage disequilibrium hinders the power of traditional array-based GWAS. Here, we demonstrate the feasibility and power improvements gained by using whole-genome sequencing for association studies. We analyzed data from 45 Senegalese parasites and identified genetic changes associated with the parasites’ in vitro response to 12 different antimalarials. To further increase statistical power, we adapted a common test for natural selection, XP-EHH (cross-population extended haplotype homozygosity), and used it to identify genomic regions associated with resistance to drugs. Using this sequence-based approach and the combination of association and selection-based tests, we detected several loci associated with drug resistance. These loci included the previously known signals at pfcrt, dhfr, and pfmdr1, as well as many genes not previously implicated in drug-resistance roles, including genes in the ubiquitination pathway. Based on the success of the analysis presented in this study, and on the demonstrated shortcomings of array-based approaches, we argue for a complete transition to sequence-based GWAS for small, low linkage-disequilibrium genomes like that of P. falciparum.

Analysis of genome sequences of 159 isolates of Plasmodium falciparum from Senegal yields an extraordinarily high proportion (26.85%) of protein-coding genes with the ratio of nonsynonymous to synonymous polymorphism greater than one. This proportion is much greater than observed in other organisms. Also unusual is that the site-frequency spectra of synonymous and nonsynonymous polymorphisms are virtually indistinguishable. We hypothesized that the complicated life cycle of malaria parasites might lead to qualitatively different population genetics from that predicted from the classical Wright-Fisher (WF) model, which assumes a single random-mating population with a finite and constant population size in an organism with nonoverlapping generations. This paper summarizes simulation studies of random genetic drift and selection in malaria parasites that take into account their unusual life history. Our results show that random genetic drift in the malaria life cycle is more pronounced than under the WF model. Paradoxically, the efficiency of purifying selection in the malaria life cycle is also greater than under WF, and the relative efficiency of positive selection varies according to conditions. Additionally, the site-frequency spectrum under neutrality is also more skewed toward low-frequency alleles than expected with WF. These results highlight the importance of considering the malaria life cycle when applying existing population genetic tools based on the WF model. The same caveat applies to other species with similarly complex life cycles.

Background: The monitoring of Plasmodium falciparum sensitivity to anti-malarial drugs is a necessity for effective case management of malaria. This species is characterized by a strong resistance to anti-malarial drugs. In Senegal, the first cases of chloroquine resistance were reported in the Dakar region in 1988 with nearly 7% population prevalence, reaching 47% by 1990. It is in this context that sulfadoxine–pyrimethamine temporarily replaced chloroquine as first line treatment in 2003, pending the introduction of artemisinin-based combination therapy in 2006. The purpose of this study is to assess the ex vivo sensitivity to different anti-malarial drugs of the P. falciparum population from Pikine. Methods: Fifty-four samples were collected from patients with non-complicated malaria and aged between 2 and 20 years in the Deggo health centre in Pikine in 2014. An assay in which parasites are stained with 4′, 6-di-amidino-2-phenylindole (DAPI), was used to study the ex vivo sensitivity of isolates to chloroquine, amodiaquine, piperaquine, pyrimethamine, and dihydroartemisinin. High resolution melting was used for genotyping of pfdhps, pfdhfr, pfmdr1, and pfcrt genes. Results: The mean IC50s of chloroquine, amodiaquine, piperaquine, dihydroartemisinin, and pyrimethamine were, respectively, 39.44, 54.02, 15.28, 2.23, and 64.70 nM. Resistance mutations in pfdhfr gene, in codon 437 of pfdhps gene, and an absence of mutation at position 540 of pfdhps were observed. Mutations in codons K76T of pfcrt and N86Y of pfmdr1 were observed at 51 and 11% population prevalence, respectively. A relationship was found between the K76T and N86Y mutations and ex vivo resistance to chloroquine. Conclusion: An increase in sensitivity of isolates to chloroquine was observed. A high sensitivity to dihydroartemisinin was observed; whereas, a decrease in sensitivity to pyrimethamine was observed in the parasite population from Pikine.

Despite efforts to reduce malaria morbidity and mortality, drug-resistant parasites continue to evade control strategies. Recently, emphasis has shifted away from control and toward regional elimination and global eradication of malaria. Such a campaign requires tools to monitor genetic changes in the parasite that could compromise the effectiveness of antimalarial drugs and undermine eradication programs. These tools must be fast, sensitive, unambiguous, and cost-effective to offer real-time reports of parasite drug susceptibility status across the globe. We have developed and validated a set of genotyping assays using high-resolution melting (HRM) analysis to detect molecular biomarkers associated with drug resistance across six genes in Plasmodium falciparum. We improved on existing technical approaches by developing refinements and extensions of HRM, including the use of blocked probes (LunaProbes) and the mutant allele amplification bias (MAAB) technique. To validate the sensitivity and accuracy of our assays, we compared our findings to sequencing results in both culture-adapted lines and clinical isolates from Senegal. We demonstrate that our assays (i) identify both known and novel polymorphisms, (ii) detect multiple genotypes indicative of mixed infections, and (iii) distinguish between variants when multiple copies of a locus are present. These rapid and inexpensive assays can track drug resistance and detect emerging mutations in targeted genetic loci in P. falciparum. They pro- vide tools for monitoring molecular changes associated with changes in drug response across populations and for determining whether parasites present after drug treatment are the result of recrudescence or reinfection in clinical settings.

Using parasite genotyping tools, we screened patients with mild uncomplicated malaria seeking treatment at a clinic in Thiès, Senegal, from 2006 to 2011. We identified a growing frequency of infections caused by genetically identical parasite strains, coincident with increased deployment of malaria control interventions and decreased malaria deaths. Parasite genotypes in some cases persisted clonally across dry seasons. The increase in frequency of genetically identical parasite strains corresponded with decrease in the probability of multiple infections. Further, these observations support evidence of both clonal and epidemic population structures. These data provide the first evidence of a temporal correlation between the appearance of identical parasite types and increased malaria control efforts in Africa, which here included distribution of insecticide treated nets (ITNs), use of rapid diagnostic tests (RDTs) for malaria detection, and deployment of artemisinin combination therapy (ACT). Our results imply that genetic surveillance can be used to evaluate the effectiveness of disease control strategies and assist a rational global malaria eradication campaign.