Two decades of molecular surveillance in Senegal reveal rapid changes in known drug resistance mutations over time.

BACKGROUND: Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. Pathogen genomic surveillance could be invaluable for monitoring current and emerging parasite drug resistance. METHODS: Data from two decades (2000-2020) of continuous molecular surveillance of P. falciparum parasites from Senegal were retrospectively examined to assess historical changes in malaria drug resistance mutations. Several known drug resistance markers and their surrounding haplotypes were profiled using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole genome sequence based population genomics. RESULTS: This dataset was used to track temporal changes in drug resistance markers whose timing correspond to historically significant events such as the withdrawal of chloroquine (CQ) and the introduction of sulfadoxine-pyrimethamine (SP) in 2003. Changes in the mutation frequency at Pfcrt K76T and Pfdhps A437G coinciding with the 2014 introduction of seasonal malaria chemoprevention (SMC) in Senegal were observed. In 2014, the frequency of Pfcrt K76T increased while the frequency of Pfdhps A437G declined. Haplotype-based analyses of Pfcrt K76T showed that this rapid increase was due to a recent selective sweep that started after 2014. DISCUSSION (CONCLUSION): The rapid increase in Pfcrt K76T is troubling and could be a sign of emerging amodiaquine (AQ) resistance in Senegal. Emerging AQ resistance may threaten the future clinical efficacy of artesunate-amodiaquine (ASAQ) and AQ-dependent SMC chemoprevention. These results highlight the potential of molecular surveillance for detecting rapid changes in parasite populations and stress the need to monitor the effectiveness of AQ as a partner drug for artemisinin-based combination therapy (ACT) and for chemoprevention.

MalKinID: A Likelihood-Based Model for Identifying Malaria Parasite Genealogical Relationships Using Identity-by-Descent.

Pathogen genomics is a powerful tool for tracking infectious disease transmission. In malaria, identity-by-descent (IBD) is used to assess the genetic relatedness between parasites and has been used to study transmission and importation. In theory, IBD can be used to distinguish genealogical relationships to reconstruct transmission history or identify parasites for genotype-to-phenotype quantitative-trait-locus experiments. MalKinID (Malaria Kinship Identifier) is a new likelihood-based classification model designed to identify genealogical relationships among malaria parasites based on genome-wide IBD proportions and IBD segment distributions. MalKinID was calibrated to the genomic data from three laboratory-based genetic crosses (yielding 440 parent-child and 9060 full-sibling comparisons). MalKinID identified lab generated F1 progeny with >80% sensitivity and showed that 0.39 (95% CI 0.28, 0.49) of the second-generation progeny of a NF54 and NHP4026 cross were F1s and 0.56 (0.45, 0.67) were backcrosses of an F1 with the parental NF54 strain. In simulated outcrossed importations, MalKinID accurately reconstructs genealogy history with high precision and sensitivity, with F1-scores exceeding 0.84. However, when importation involves inbreeding, such as during serial co-transmission, the precision and sensitivity of MalKinID declined, with F1-scores of 0.76 (0.56, 0.92) and 0.23 (0.0, 0.4) for PC and FS and <0.05 for second-degree and third-degree relatives. Genealogical inference is most powered 1) when outcrossing is the norm or 2) when multi-sample comparisons based on a predefined pedigree are used. MalKinID lays the foundations for using IBD to track parasite transmission history and for separating progeny for quantitative-trait-locus experiments.

Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal.

BACKGROUND: Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. METHODS: This study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. RESULTS: Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]). CONCLUSIONS: When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Artemisinin resistance mutations in Pfcoronin impede hemoglobin uptake.

Artemisinin (ART) combination therapies have been critical in reducing malaria morbidity and mortality, but these important drugs are threatened by growing resistance associated with mutations in Pfcoronin and Pfkelch13 . Here, we describe the mechanism of Pfcoronin -mediated ART resistance. Pf Coronin interacts with Pf Actin and localizes to the parasite plasma membrane (PPM), the digestive vacuole (DV) membrane, and membrane of a newly identified preDV compartment-all structures involved in the trafficking of hemoglobin from the RBC for degradation in the DV. Pfcoronin mutations alter Pf Actin homeostasis and impair the development and morphology of the preDV. Ultimately, these changes are associated with decreased uptake of red blood cell cytosolic contents by ring-stage Plasmodium falciparum . Previous work has identified decreased hemoglobin uptake as the mechanism of Pfkelch 13-mediated ART resistance. This work demonstrates that Pf Coronin appears to act via a parallel pathway. For both Pfkelch13 -mediated and Pfcoronin -mediated ART resistance, we hypothesize that the decreased hemoglobin uptake in ring stage parasites results in less heme-based activation of the artemisinin endoperoxide ring and reduced cytocidal activity. This study deepens our understanding of ART resistance, as well as hemoglobin uptake and development of the DV in early-stage parasites.

Evaluating the performance of Plasmodium falciparum genetics for inferring National Malaria Control Program reported incidence in Senegal.

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programs (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. Here, we examined parasites from 3,147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, we constructed a series of Poisson generalized linear mixed-effects models to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. We compared the model-predicted incidence with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (<10/1000/annual [‰]). When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence >10 ‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was <10 ‰, we found that many of the correlations between parasite genetics and incidence were reversed, which we hypothesize reflects the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal.

We here analyze data from the first year of an ongoing nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal. The analysis is based on 1097 samples collected at health facilities during passive malaria case detection in 2019; it provides a baseline for analyzing parasite genetic metrics as they vary over time and geographic space. The study's goal was to identify genetic metrics that were informative about transmission intensity and other aspects of transmission dynamics, focusing on measures of genetic relatedness between parasites. We found the best genetic proxy for local malaria incidence to be the proportion of polygenomic infections (those with multiple genetically distinct parasites), although this relationship broke down at low incidence. The proportion of related parasites was less correlated with incidence while local genetic diversity was uninformative. The type of relatedness could discriminate local transmission patterns: two nearby areas had similarly high fractions of relatives, but one was dominated by clones and the other by outcrossed relatives. Throughout Senegal, 58% of related parasites belonged to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci and at one novel locus, reflective of ongoing selection pressure.

Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal.

Parasite genetic surveillance has the potential to play an important role in malaria control. We describe here an analysis of data from the first year of an ongoing, nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal, intended to provide actionable information for malaria control efforts. Looking for a good proxy for local malaria incidence, we found that the best predictor was the proportion of polygenomic infections (those with multiple genetically distinct parasites), although that relationship broke down in very low incidence settings (r = 0.77 overall). The proportion of closely related parasites in a site was more weakly correlated ( r = -0.44) with incidence while the local genetic diversity was uninformative. Study of related parasites indicated their potential for discriminating local transmission patterns: two nearby study areas had similarly high fractions of relatives, but one area was dominated by clones and the other by outcrossed relatives. Throughout the country, 58% of related parasites proved to belong to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci as well as at one novel locus, reflective of ongoing selection pressure.

Two decades of molecular surveillance in Senegal reveal changes in known drug resistance mutations associated with historical drug use and seasonal malaria chemoprevention.

Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. We analyzed data from two decades (2000-2020) of continuous molecular surveillance of P. falciparum parasite strains in Senegal to determine how historical changes in drug administration policy may have affected parasite evolution. We profiled several known drug resistance markers and their surrounding haplotypes using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole-genome sequence (WGS) based population genomics. We observed rapid changes in drug resistance markers associated with the withdrawal of chloroquine and introduction of sulfadoxine-pyrimethamine in 2003. We also observed a rapid increase in Pfcrt K76T and decline in Pfdhps A437G starting in 2014, which we hypothesize may reflect changes in resistance or fitness caused by seasonal malaria chemoprevention (SMC). Parasite populations evolve rapidly in response to drug use, and SMC preventive efficacy should be closely monitored.

Potent acyl-CoA synthetase 10 inhibitors kill Plasmodium falciparum by disrupting triglyceride formation.

Identifying how small molecules act to kill malaria parasites can lead to new "chemically validated" targets. By pressuring Plasmodium falciparum asexual blood stage parasites with three novel structurally-unrelated antimalarial compounds (MMV665924, MMV019719 and MMV897615), and performing whole-genome sequence analysis on resistant parasite lines, we identify multiple mutations in the P. falciparum acyl-CoA synthetase (ACS) genes PfACS10 (PF3D7_0525100, M300I, A268D/V, F427L) and PfACS11 (PF3D7_1238800, F387V, D648Y, and E668K). Allelic replacement and thermal proteome profiling validates PfACS10 as a target of these compounds. We demonstrate that this protein is essential for parasite growth by conditional knockdown and observe increased compound susceptibility upon reduced expression. Inhibition of PfACS10 leads to a reduction in triacylglycerols and a buildup of its lipid precursors, providing key insights into its function. Analysis of the PfACS11 gene and its mutations point to a role in mediating resistance via decreased protein stability.

R H: a genetic metric for measuring intrahost Plasmodium falciparum relatedness and distinguishing cotransmission from superinfection.

Multiple-strain (polygenomic) infections are a ubiquitous feature of Plasmodium falciparum parasite population genetics. Under simple assumptions of superinfection, polygenomic infections are hypothesized to be the result of multiple infectious bites. As a result, polygenomic infections have been used as evidence of repeat exposure and used to derive genetic metrics associated with high transmission intensity. However, not all polygenomic infections are the result of multiple infectious bites. Some result from the transmission of multiple, genetically related strains during a single infectious bite (cotransmission). Superinfection and cotransmission represent two distinct transmission processes, and distinguishing between the two could improve inferences regarding parasite transmission intensity. Here, we describe a new metric, R H, that utilizes the correlation in allelic state (heterozygosity) within polygenomic infections to estimate the likelihood that the observed complexity resulted from either superinfection or cotransmission. R H is flexible and can be applied to any type of genetic data. As a proof of concept, we used R H to quantify polygenomic relatedness and estimate cotransmission and superinfection rates from a set of 1,758 malaria infections genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode. Contrary to expectation, we found that cotransmission was responsible for a significant fraction of 43% to 53% of the polygenomic infections collected in three distinct epidemiological regions in Senegal. The prediction that polygenomic infections frequently result from cotransmission stresses the need to incorporate estimates of relatedness within polygenomic infections to ensure the accuracy of genomic epidemiology surveillance data for informing public health activities.

Using an antimalarial in mosquitoes overcomes Anopheles and Plasmodium resistance to malaria control strategies.

The spread of insecticide resistance in Anopheles mosquitoes and drug resistance in Plasmodium parasites is contributing to a global resurgence of malaria, making the generation of control tools that can overcome these roadblocks an urgent public health priority. We recently showed that the transmission of Plasmodium falciparum parasites can be efficiently blocked when exposing Anopheles gambiae females to antimalarials deposited on a treated surface, with no negative consequences on major components of mosquito fitness. Here, we demonstrate this approach can overcome the hurdles of insecticide resistance in mosquitoes and drug resistant in parasites. We show that the transmission-blocking efficacy of mosquito-targeted antimalarials is maintained when field-derived, insecticide resistant Anopheles are exposed to the potent cytochrome b inhibitor atovaquone, demonstrating that this drug escapes insecticide resistance mechanisms that could potentially interfere with its function. Moreover, this approach prevents transmission of field-derived, artemisinin resistant P. falciparum parasites (Kelch13 C580Y mutant), proving that this strategy could be used to prevent the spread of parasite mutations that induce resistance to front-line antimalarials. Atovaquone is also highly effective at limiting parasite development when ingested by mosquitoes in sugar solutions, including in ongoing infections. These data support the use of mosquito-targeted antimalarials as a promising tool to complement and extend the efficacy of current malaria control interventions.

Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering.

Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal-a region of exceptionally low malaria transmission (entomological inoculation rate less than 1). Genetic identity (identity by state, IBS) was established using a 24-single nucleotide polymorphism molecular barcode, identity by descent was calculated from whole genome sequence data, and a hierarchical Bayesian regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts.

Genetic surveillance for monitoring the impact of drug use on Plasmodium falciparum populations.

The use of antimalarial drugs is an effective strategy in the fight against malaria. However, selection of drug resistant parasites is a constant threat to the continued use of this approach. Antimalarial drugs are used not only to treat infections but also as part of population-level strategies to reduce malaria transmission toward elimination. While there is strong evidence that the ongoing use of antimalarial drugs increases the risk of the emergence and spread of drug-resistant parasites, it is less clear how population-level use of drug-based interventions like seasonal malaria chemoprevention (SMC) or mass drug administration (MDA) may contribute to drug resistance or loss of drug efficacy. Critical to sustained use of drug-based strategies for reducing the burden of malaria is the surveillance of population-level signals related to transmission reduction and resistance selection. Here we focus on Plasmodium falciparum and discuss the genetic signatures of a parasite population that are correlated with changes in transmission and related to drug pressure and resistance as a result of drug use. We review the evidence for MDA and SMC contributing to malaria burden reduction and drug resistance selection and examine the use and impact of these interventions in Senegal. Throughout we consider best strategies for ongoing surveillance of both population and resistance signals in the context of different parasite population parameters. Finally, we propose a roadmap for ongoing surveillance during population-level drug-based interventions to reduce the global malaria burden.

Genomic investigation of atypical malaria cases in Kanel, northern Senegal.

BACKGROUND: The diagnosis of malaria cases in regions where the malaria burden has decreased significantly and prevalence is very low is more challenging, in part because of reduced clinical presumption of malaria. The appearance of a cluster of malaria cases with atypical symptoms in Mbounguiel, a village in northern Senegal where malaria transmission is low, in September 2018 exemplifies this scenario. The collaboration between the National Malaria Control Programme (NMCP) at the Senegal Ministry of Health and the Laboratory of Parasitology and Mycology at Cheikh Anta Diop University worked together to evaluate this cluster of malaria cases using molecular and serological tools. METHODS: Malaria cases were diagnosed primarily by rapid diagnostic test (RDT), and confirmed by photo-induced electron transfer-polymerase chain reaction (PET-PCR). 24 single nucleotide polymorphisms (SNPs) barcoding was used for Plasmodium falciparum genotyping. Unbiased metagenomic sequencing and Luminex-based multi-pathogen antibody and antigen profiling were used to assess exposure to other pathogens. RESULTS: Nine patients, of 15 suspected cases, were evaluated, and all nine samples were found to be positive for P. falciparum only. The 24 SNPs molecular barcode showed the predominance of polygenomic infections, with identifiable strains being different from one another. All patients tested positive for the P. falciparum antigens. No other pathogenic infection was detected by either the serological panel or metagenomic sequencing. CONCLUSIONS: This work, undertaken locally within Senegal as a collaboration between the NMCP and a research laboratory at University of Cheikh Anta Diop (UCAD) revealed that a cluster of malaria cases were caused by different strains of P. falciparum. The public health response in real time demonstrates the value of local molecular and genomics capacity in affected countries for disease control and elimination.

Allelic diversity of MSP1 and MSP2 repeat loci correlate with levels of malaria endemicity in Senegal and Nigerian populations.

BACKGROUND: Characterizing the genetic diversity of malaria parasite populations in different endemic settings (from low to high) could be helpful in determining the effectiveness of malaria interventions. This study compared Plasmodium falciparum parasite population diversity from two sites with low (pre-elimination) and high transmission in Senegal and Nigeria, respectively. METHODS: Parasite genomic DNA was extracted from 187 dried blood spot collected from confirmed uncomplicated P. falciparum malaria infected patients in Senegal (94) and Nigeria (93). Allelic polymorphism at merozoite surface protein 1 (msp1) and merozoite surface protein- 2 (msp2) genes were assessed by nested PCR. RESULTS: The most frequent msp1 and msp2 allelic families are the K1 and IC3D7 allelotypes in both Senegal and Nigeria. Multiplicity of infection (MOI) of greater that 1 and thus complex infections was common in both study sites in Senegal (Thies:1.51/2.53; Kedougou:2.2/2.0 for msp1/2) than in Nigeria (Gbagada: 1.39/1.96; Oredo: 1.35/1.75]). The heterozygosity of msp1 gene was higher in P. falciparum isolates from Senegal (Thies: 0.62; Kedougou: 0.53) than isolates from Nigeria (Gbagada: 0.55; Oredo: 0.50). In Senegal, K1 alleles was associated with heavy than with moderate parasite density. Meanwhile, equal proportions of K1 were observed in both heavy and moderate infection types in Nigeria. The IC3D7 subtype allele of the msp2 family was the most frequent in heavily parasitaemic individuals from both countries than in the moderately infected participants. CONCLUSION: The unexpectedly low genetic diversity of infections high endemic Nigerian setting compared to the low endemic settings in Senegal is suggestive of possible epidemic outbreak in Nigeria.

Polymorphisms in Plasmodium falciparum chloroquine resistance transporter (Pfcrt) and multidrug-resistant gene 1 (Pfmdr-1) in Nigerian children 10 years post-adoption of artemisinin-based combination treatments.

The emergence and spread of Plasmodium falciparum parasites resistant to artemisinin derivatives and their partners in southeastern Asia threatens malaria control and elimination efforts, and heightens the need for an alternative therapy. We have explored the distribution of P. falciparum chloroquine resistance transporter (Pfcrt) and multidrug-resistant gene 1 (Pfmdr-1) haplotypes 10 years following adoption of artemisinin-based combination therapies in a bid to investigate the possible re-emergence of Chloroquine-sensitive parasites in Nigeria, and investigated the effect of these P. falciparum haplotypes on treatment outcomes of patients treated with artemisinin-based combination therapies. A total of 271 children aged <5 years with uncomplicated falciparum malaria were included in this study. Polymorphisms on codons 72-76 of the Pfcrt gene and codon 86 and 184 of Pfmdr-1 were determined using the high resolution melting assay. Of 240 (88.6%) samples successfully genotyped with HRM for Pfcrt, wildtype C72M74N75K76 (42.9%) and mutant C72I74E75T76 (53.8%) were observed. Also, wildtype N86Y184 (62.9%) and mutant N86F184 (21.1%), Y86Y184 (6.4%), and Y86F184 (0.4%) haplotypes of Pfmdr-1 were observed. Measures of responsiveness to ACTs were similar in children infected with P. falciparum crt haplotypes (C72I74E75T76 and C72M74N75K76) and major mdr-1 haplotypes (N86Y184, N86F184 and Y86Y184). Despite a 10 year gap since the malaria treatment policy changed to ACTs, over 50% of the P. falciparum parasites investigated in this study harboured the Chloroquine-resistant C72I74E75T76 haplotype, however this did not compromise the efficacy of artemisinin-based combination therapies. Should complete artemisinin resistance emerge from or spread to Nigeria, chloroquine might not be a good alternative therapy.

Genetic background and PfKelch13 affect artemisinin susceptibility of PfCoronin mutants in Plasmodium falciparum.

Malaria continues to impose a significant health burden in the continent of Africa with 213 million cases in 2018 alone, representing 93% of cases worldwide. Because of high transmission of malaria within the continent, the selection pressures to develop drug resistance in African parasites are distinct compared to the rest of the world. In light of the spread of resistance to artemisinin conferred by the C580Y mutation in the PfKelch13 propeller domain in Southeast Asia, and its independent emergence in South America, it is important to study genetic determinants of resistance in the African context using African parasites. Through in vitro evolution of Senegalese parasites, we had previously generated the artemisinin-resistant parasites Pikine_R and Thiès_R and established pfcoronin mutations to be sufficient to confer artemisinin resistance in the standard ring-stage survival assay (RSA). In the current study, we used genetic analysis of revertants to demonstrate pfcoronin to be the major driver of elevated RSA in the artemisinin-resistant parasites Pikine_R and Thiès_R evolved in vitro. We interrogated the role of a second gene PF3D7_1433800, which also had mutations in both the Pikine_R and Thiès_R selected lines, but found no evidence of a contribution to reduced susceptibility in the RSA survival assay. Nevertheless, our genetic analysis demonstrates that parasite genetic background is important in the level of pfcoronin mediated RSA survival, and therefore we cannot rule out a role for PF3D7_1433800 in other genetic backgrounds. Finally, we tested the potential synergy between the mutations of pfcoronin and pfkelch13 through the generation of single and double mutants in the Pikine genetic background and found that the contribution of pfcoronin to reduced susceptibility is masked by the presence of pfkelch13. This phenomenon was also observed in the 3D7 background, suggesting that pfcoronin may mediate its effects via the same pathway as pfkelch13. Investigating the biology of proteins containing the beta-propeller domain could further elucidate the different pathways that the parasite could use to attain resistance.

Population genomics of Plasmodium vivax in Panama to assess the risk of case importation on malaria elimination.

Malaria incidence in Panama has plateaued in recent years in spite of elimination efforts, with almost all cases caused by Plasmodium vivax. Notwithstanding, overall malaria prevalence remains low (fewer than 1 case per 1000 persons). We used selective whole genome amplification to sequence 59 P. vivax samples from Panama. The P. vivax samples were collected from two periods (2007-2009 and 2017-2019) to study the population structure and transmission dynamics of the parasite. Imported cases resulting from increased levels of human migration could threaten malaria elimination prospects, and four of the samples evaluated came from individuals with travel history. We explored patterns of recent common ancestry among the samples and observed that a highly genetically related lineage (termed CL1) was dominant among the samples (47 out of 59 samples with good sequencing coverage), spanning the entire period of the collection (2007-2019) and all regions of the country. We also found a second, smaller clonal lineage (termed CL2) of four parasites collected between 2017 and 2019. To explore the regional context of Panamanian P. vivax we conducted principal components analysis and constructed a neighbor-joining tree using these samples and samples collected worldwide from a previous study. Three of the four samples with travel history clustered with samples collected from their suspected country of origin (consistent with importation), while one appears to have been a result of local transmission. The small number of Panamanian P. vivax samples not belonging to either CL1 or CL2 clustered with samples collected from Colombia, suggesting they represent the genetically similar ancestral P. vivax population in Panama or were recently imported from Colombia. The low diversity we observe in Panama indicates that this parasite population has been previously subject to a severe bottleneck and may be eligible for elimination. Additionally, while we confirmed that P. vivax is imported to Panama from diverse geographic locations, the lack of impact from imported cases on the overall parasite population genomic profile suggests that onward transmission from such cases is limited and that imported cases may not presently pose a major barrier to elimination.

Molecular epidemiology of Plasmodium falciparum by multiplexed amplicon deep sequencing in Senegal.

BACKGROUND: Molecular epidemiology can provide important information regarding the genetic diversity and transmission of Plasmodium falciparum, which can assist in designing and monitoring elimination efforts. However, malaria molecular epidemiology including understanding the genetic diversity of the parasite and performing molecular surveillance of transmission has been poorly documented in Senegal. Next Generation Sequencing (NGS) offers a practical, fast and high-throughput approach to understand malaria population genetics. This study aims to unravel the population structure of P. falciparum and to estimate the allelic diversity, multiplicity of infection (MOI), and evolutionary patterns of the malaria parasite using the NGS platform. METHODS: Multiplex amplicon deep sequencing of merozoite surface protein 1 (PfMSP1) and merozoite surface protein 2 (PfMSP2) in fifty-three P. falciparum isolates from two epidemiologically different areas in the South and North of Senegal, was carried out. RESULTS: A total of 76 Pfmsp1 and 116 Pfmsp2 clones were identified and 135 different alleles were found, 56 and 79 belonged to the pfmsp1 and pfmsp2 genes, respectively. K1 and IC3D7 allelic families were most predominant in both sites. The local haplotype diversity (Hd) and nucleotide diversity (π) were higher in the South than in the North for both genes. For pfmsp1, a high positive Tajima's D (TD) value was observed in the South (D = 2.0453) while negative TD value was recorded in the North (D = - 1.46045) and F-Statistic (Fst) was 0.19505. For pfmsp2, non-directional selection was found with a highly positive TD test in both areas and Fst was 0.02111. The mean MOI for both genes was 3.07 and 1.76 for the South and the North, respectively, with a statistically significant difference between areas (p = 0.001). CONCLUSION: This study revealed a high genetic diversity of pfmsp1 and pfmsp2 genes and low genetic differentiation in P. falciparum population in Senegal. The MOI means were significantly different between the Southern and Northern areas. Findings also showed that multiplexed amplicon deep sequencing is a useful technique to investigate genetic diversity and molecular epidemiology of P. falciparum infections.

Genetic analysis reveals unique characteristics of Plasmodium falciparum parasite populations in Haiti.

BACKGROUND: With increasing interest in eliminating malaria from the Caribbean region, Haiti is one of the two countries on the island of Hispaniola with continued malaria transmission. While the Haitian population remains at risk for malaria, there are a limited number of cases annually, making conventional epidemiological measures such as case incidence and prevalence of potentially limited value for fine-scale resolution of transmission patterns and trends. In this context, genetic signatures may be useful for the identification and characterization of the Plasmodium falciparum parasite population in order to identify foci of transmission, detect outbreaks, and track parasite movement to potentially inform malaria control and elimination strategies. METHODS: This study evaluated the genetic signals based on analysis of 21 single-nucleotide polymorphisms (SNPs) from 462 monogenomic (single-genome) P. falciparum DNA samples extracted from dried blood spots collected from malaria-positive patients reporting to health facilities in three southwestern Haitian departments (Nippes, Grand'Anse, and Sud) in 2016. RESULTS: Assessment of the parasite genetic relatedness revealed evidence of clonal expansion within Nippes and the exchange of parasite lineages between Nippes, Sud, and Grand'Anse. Furthermore, 437 of the 462 samples shared high levels of genetic similarity-at least 20 of 21 SNPS-with at least one other sample in the dataset. CONCLUSIONS: These results revealed patterns of relatedness suggestive of the repeated recombination of a limited number of founding parasite types without significant outcrossing. These genetic signals offer clues to the underlying relatedness of parasite populations and may be useful for the identification of the foci of transmission and tracking of parasite movement in Haiti for malaria elimination.