Plasmodium falciparum parasites that are resistant to artemisinins have been detected in Southeast Asia. Resistance is associated with several polymorphisms in the parasite's K13-propeller gene. The molecular epidemiology of these artemisinin resistance genotypes in African parasite populations is unknown. We developed an assay to quantify rare polymorphisms in parasite populations that uses a pooled deep-sequencing approach to score allele frequencies, validated it by evaluating mixtures of laboratory parasite strains, and then used it to screen P. falciparum parasites from >1100 African infections collected since 2002 from 14 sites across sub-Saharan Africa. We found no mutations in African parasite populations that are associated with artemisinin resistance in Southeast Asian parasites. However, we observed 15 coding mutations, including 12 novel mutations, and limited allele sharing between parasite populations, consistent with a large reservoir of naturally occurring K13-propeller variation. Although polymorphisms associated with artemisinin resistance in P. falciparum in Southeast Asia are not prevalent in sub-Saharan Africa, numerous K13-propeller coding polymorphisms circulate in Africa. Although their distributions do not support a widespread selective sweep for an artemisinin-resistant phenotype, the impact of these mutations on artemisinin susceptibility is unknown and will require further characterization. Rapid, scalable molecular surveillance offers a useful adjunct in tracking and containing artemisinin resistance.

Diagnosis and treatment of Plasmodium falciparum infections are required for effective malaria control and are pre-requisites for malaria elimination efforts; hence we need to monitor emergence, evolution and spread of drug- and diagnostics-resistant parasites. We deep sequenced key drug-resistance mutations and 1,832 SNPs in the parasite genomes of 609 malaria cases collected during a diagnostic-resistance surveillance study in Ethiopia. We found that 8.0% (95% CI 7.0–9.0) of malaria cases were caused by P. falciparum carrying the candidate artemisinin partial-resistance kelch13 (K13) 622I mutation, which was less common in diagnostic-resistant parasites mediated by histidine-rich proteins 2 and 3 (pfhrp2/3) deletions than in wild-type parasites (P = 0.03). Identity-by-descent analyses showed that K13 622I parasites were significantly more related to each other than to wild type (P < 0.001), consistent with recent expansion and spread of this mutation. Pfhrp2/3-deleted parasites were also highly related, with evidence of clonal transmissions at the district level. Of concern, 8.2% of K13 622I parasites also carried the pfhrp2/3 deletions. Close monitoring of the spread of combined drug- and diagnostic-resistant parasites is needed.

The Democratic Republic of the Congo (DRC) harbors 11% of global malaria cases, yet little is known about the spatial and genetic structure of the parasite population in that country. We sequence 2537 Plasmodium falciparum infections, including a nationally representative population sample from DRC and samples from surrounding countries, using molecular inversion probes - a high-throughput genotyping tool. We identify an east-west divide in haplotypes known to confer resistance to chloroquine and sulfadoxine-pyrimethamine. Furthermore, we identify highly related parasites over large geographic distances, indicative of gene flow and migration. Our results are consistent with a background of isolation by distance combined with the effects of selection for antimalarial drug resistance. This study provides a high-resolution view of parasite genetic structure across a large country in Africa and provides a baseline to study how implementation programs may impact parasite populations.

Malaria infections commonly contain multiple genetically distinct variants. Mathematical and animal models suggest that interactions among these variants have a profound impact on the emergence of drug resistance. However, methods currently used for quantifying parasite diversity in individual infections are insensitive to low-abundance variants and are not quantitative for variant population sizes. To more completely describe the in-host complexity and ecology of malaria infections, we used massively parallel pyrosequencing to characterize malaria parasite diversity in the infections of a group of patients. By individually sequencing single strands of DNA in a complex mixture, this technique can quantify uncommon variants in mixed infections. The in-host diversity revealed by this method far exceeded that described by currently recommended genotyping methods, with as many as sixfold more variants per infection. In addition, in paired pre- and posttreatment samples, we show a complex milieu of parasites, including variants likely up-selected and down-selected by drug therapy. As with all surveys of diversity, sampling limitations prevent full discovery and differences in sampling effort can confound comparisons among samples, hosts, and populations. Here, we used ecological approaches of species accumulation curves and capture-recapture to estimate the number of variants we failed to detect in the population, and show that these methods enable comparisons of diversity before and after treatment, as well as between malaria populations. The combination of ecological statistics and massively parallel pyrosequencing provides a powerful tool for studying the evolution of drug resistance and the in-host ecology of malaria infections.