Artemisinin-based therapies are central to malaria treatment, but their efficacy is threatened by the emergence of resistant Plasmodium falciparum strains. While the role of Pfkelch13 mutations in clinical resistance is well established, recent reports from Africa implicate Pfcoronin mutations in treatment failure, adding to the complexity of resistance mechanisms. Here, we show that Pf Coronin, a non-essential actin regulator active during the ring-stage, facilitates efficient hemoglobin uptake. We demonstrate that resistance-associated Pfcoronin mutations disrupt Pf Coronin's interaction with Pf Actin and its ring-stage localization, leading to impaired endocytosis and reduced hemoglobin acquisition. Pf Coronin and Pf Kelch13 function in distinct cellular regions; mutations in both converge to limit heme availability and artemisinin activation. Although Pf Coronin is dispensable for parasite viability, our findings demonstrate that Pfcoronin mutations reduce endocytosis and modulate artemisinin susceptibility during the clinically relevant ring stage-highlighting how non-essential, temporally restricted proteins can shape antimalarial drug response and resistance.

Pathogen genomics is a powerful tool for tracking infectious disease transmission. In malaria, identity-by-descent is used to assess the genetic relatedness between parasites and has been used to study transmission and importation. In theory, identity-by-descent can be used to distinguish genealogical relationships to reconstruct transmission history or identify parasites for QTL experiments. MalKinID (Malaria Kinship Identifier) is a new classification model designed to identify genealogical relationships among malaria parasites based on genome-wide identity-by-descent proportions and identity-by-descent segment distributions. MalKinID was calibrated to the genomic data from 3 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 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 (the harmonic mean of precision and sensitivity) of 0.76 (0.56, 0.92) and 0.23 (0.0, 0.4) for parent-child and full-sibling and <0.05 for second-degree and third-degree relatives. Disentangling inbred relationships required adapting MalKinID to perform multisample comparisons. Genealogical inference is most powered when (1) outcrossing is the norm or (2) multisample comparisons based on a predefined pedigree are used. MalKinID lays the foundations for using identity-by-descent to track parasite transmission history and for separating progeny for quantitative-trait-locus experiments.

The evolutionary mechanisms that drive the emergence of genome architecture remain poorly understood but can now be assessed with unprecedented power due to the massive accumulation of genome assemblies spanning phylogenetic diversity. Transposable elements (TEs) are a rich source of large-effect mutations since they directly and indirectly drive genomic structural variation and changes in gene expression. Here, we demonstrate universal patterns of TE compartmentalization across eukaryotic genomes spanning ~1.7 billion years of evolution, in which TEs colocalize with gene families under strong predicted selective pressure for dynamic evolution and involved in specific functions. For non-pathogenic species these genes represent families involved in defense, sensory perception and environmental interaction, whereas for pathogenic species, TE-compartmentalized genes are highly enriched for pathogenic functions. Many TE-compartmentalized gene families display signatures of positive selection at the molecular level. Furthermore, TE-compartmentalized genes exhibit an excess of high-frequency alleles for polymorphic TE insertions in fruit fly populations. We postulate that these patterns reflect selection for adaptive TE insertions as well as TE-associated structural variants. This process may drive the emergence of a shared TE-compartmentalized genome architecture across diverse eukaryotic lineages.

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.

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. 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. 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. 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.

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.

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.

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.

[This corrects the article DOI: 10.1093/pnasnexus/pgac187.].

Gregor Mendel was an Augustinian priest in the Monastery of St. Thomas in Brünn (Brno, Czech Republic) as well as a civilian employee who taught natural history and physics in the Brünn Modern School. The monastery’s secular function was to provide teachers for the public schools across Moravia. It was a cultural, educational, and artistic center with an elite core of friar-teachers with a well-stocked library and other amenities including a gourmet kitchen. It was wealthy, with far-flung holdings yielding income from agricultural productions. Mendel had failed his tryout as a parish priest and did not complete his examination for teaching certification despite 2 y of study at the University of Vienna. In addition to his teaching and religious obligations, Mendel carried out daily meteorological and astronomical observations, cared for the monastery's fruit orchard and beehives, and tended plants in the greenhouse and small outdoor gardens. In the years 1856 to 1863, he carried out experiments on heredity of traits in garden peas regarded as revolutionary today but not widely recognized during his lifetime and until 16 y after his death. In 1868 he was elected abbot of the monastery, a significantly elevated position in the ecclesiastical and civil hierarchy. While he had hoped to be elected, and was honored to accept, he severely underestimated its administrative responsibilities and gradually had to abandon his scientific interests. The last decade of his life was marred by an ugly dispute with civil authorities over monastery taxation.

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.

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, RH, 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. RH is flexible and can be applied to any type of genetic data. As a proof of concept, we used RH 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.

Background Large-scale variation in ecological parameters across Madagascar is hypothesized to drive varying spatial patterns of malaria infection. However, to date, few studies of parasite prevalence with resolution at finer, sub-regional spatial scales are available. As a result, there is a poor understanding of how Madagascar’s diverse local ecologies link with variation in the distribution of infections at the community and household level. Efforts to preserve Madagascar’s ecological diversity often focus on improving livelihoods in rural communities near remaining forested areas but are limited by a lack of data on their infectious disease burden. Methods To investigate spatial variation in malaria prevalence at the sub-regional scale in Madagascar, we sampled 1476 households (7117 total individuals, all ages) from 31 rural communities divided among five ecologically distinct regions. The sampled regions range from tropical rainforest to semi-arid, spiny forest and include communities near protected areas including the Masoala, Makira, and Mikea forests. Malaria prevalence was estimated by rapid diagnostic test (RDT) cross-sectional surveys performed during malaria transmission seasons over 2013–2017. Results Indicative of localized hotspots, malaria prevalence varied more than 10-fold between nearby (< 50 km) communities in some cases. Prevalence was highest on average in the west coast region (Morombe district, average community prevalence 29.4%), situated near protected dry deciduous forest habitat. At the household level, communities in southeast Madagascar (Mananjary district) were observed with over 50% of households containing multiple infected individuals at the time of sampling. From simulations accounting for variation in household size and prevalence at the community level, we observed a significant excess of households with multiple infections in rural communities in southwest and southeast Madagascar, suggesting variation in risk within communities. Conclusions Our data suggest that the malaria infection burden experienced by rural communities in Madagascar varies greatly at smaller spatial scales (i.e., at the community and household level) and that the southeast and west coast ecological regions warrant further attention from disease control efforts. Conservation and development efforts in these regions may benefit from consideration of the high, and variable, malaria prevalences among communities in these areas.

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.