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The widely used antimalarial combination therapy dihydroartemisinin + piperaquine (DHA + PPQ) has failed in Cambodia. Here, we perform a genomic analysis that reveals a rapid increase in the prevalence of novel mutations in the Plasmodium falciparum chloroquine resistance transporter PfCRT following DHA + PPQ implementation. These mutations occur in parasites harboring the K13 C580Y artemisinin resistance marker. By introducing PfCRT mutations into sensitive Dd2 parasites or removing them from resistant Cambodian isolates, we show that the H97Y, F145I, M343L, or G353V mutations each confer resistance to PPQ, albeit with fitness costs for all but M343L. These mutations sensitize Dd2 parasites to chloroquine, amodiaquine, and quinine. In Dd2 parasites, multicopy plasmepsin 2 , a candidate molecular marker, is not necessary for PPQ resistance. Distended digestive vacuoles were observed in pfcrt -edited Dd2 parasites but not in Cambodian isolates. Our findings provide compelling evidence that emerging mutations in PfCRT can serve as a molecular marker and mediator of PPQ resistance. Increasing resistance of Plasmodium falciparum strains to piperaquine (PPQ) in Southeast Asia is of concern and resistance mechanisms are incompletely understood. Here, Ross et al. show that mutations in the P . falciparum chloroquine resistance transporter are rapidly increasing in prevalence in Cambodia and confer resistance to PPQ.

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is increasingly being used in Plasmodium population genomics to estimate genetic relatedness, effective population size ( N e ), population structure, and signals of positive selection. Despite its potential, a thorough evaluation of IBD segment detection tools for species with high recombination rates, such as Plasmodium falciparum , remains absent. Here, we perform comprehensive benchmarking of IBD callers – probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD) – using population genetic simulations tailored for high recombination, and IBD quality metrics at both the IBD segment level and the IBD-based downstream inference level. Our results demonstrate that low marker density per genetic unit, related to high recombination relative to mutation, significantly compromises the accuracy of detected IBD segments. In genomes with high recombination rates resembling P. falciparum , most IBD callers exhibit high false negative rates for shorter IBD segments, which can be partially mitigated through optimization of IBD caller parameters, especially those related to marker density. Notably, IBD detected with optimized parameters allows for more accurate capture of selection signals and population structure; IBD-based N e inference is very sensitive to IBD detection errors, with IBD called from hmmIBD uniquely providing less biased estimates of N e in this context. Validation with empirical data from the MalariaGEN Pf 7 database, representing different transmission settings, corroborates these findings. We conclude that context-specific evaluation and parameter optimization are essential for accurate IBD detection in high-recombining species and recommend hmmIBD for Plasmodium species, especially for quality-sensitive analyses, such as estimation of N e . Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population’s background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings. Identity-by-descent (IBD) is used to infer malaria parasite population demography, but positive selection imposed by drug pressure can bias IBD estimates. This study shows that strong selection distorts IBD distributions impacting downstream inferences and presents an approach to correct these biases.

Background Identity-by-descent (IBD), which describes recent genetic co-ancestry between pairs of genomes, is a fundamental concept in population genomics. It has been used to estimate genetic relatedness, detect selection signals, and understand population demography. The IBD detection method hmmIBD demonstrates high accuracy in inferring IBD segments between haploid genomes, including Plasmodium falciparum , and is widely used in malaria genomic surveillance. However, the current single-threaded implementation of hmmIBD does not utilize the full capacity of multi-processor computers, making it difficult to apply to large data sets, and does not accommodate non-uniform recombination rates across the genome. Methods We developed an enhanced implementation of hmmIBD , named hmmibd-rs , which leverages multi-threaded computing to parallelize IBD inference over genome pairs and which supports optional, user-defined recombination rate maps for more accurate IBD detection and filtration from genomes with non-uniform recombination. We further streamlined large-scale IBD detection by incorporating auxiliary built-in functionalities to preprocess input directly from the standard binary variant call format (BCF) and filter IBD output to reduce disk usage. Results Our new implementation significantly reduces IBD detection computation time nearly linearly with the increased number of CPU threads used; using 128 threads shortens IBD detection time from 5.2 days to 1.3 h for 220 million pairs of simulated Plasmodium falciparum -like chromosomes, increasing computational speed by approximately 100 × over the single-threaded hmmIBD algorithm. Incorporating non-uniform recombination rates in hmmibd-rs enhances the accuracy of IBD inference by mitigating the overestimation of IBD breakpoints in recombination cold spots and their underestimation in hot spots. Non-uniform rates also improve length filtration of IBD segments, dramatically reducing the rate of false positive in recombination cold spots. When applied to empirical data sets, hmmibd-rs completes the detection of IBD from MalariaGEN Pf7 (n ≈ 10,000 monoclonal samples) within hours, enabling a single-day IBD analysis pipeline for large genomic data sets. Conclusion hmmibd-rs builds upon, accelerates, and enhances hmmIBD for efficient and accurate IBD detection, serving as a crucial tool for advancing large-scale malaria genomic surveillance.

Background Extensive genetic diversity in vaccine antigens may contribute to the lack of efficacy of blood stage malaria vaccines. Apical membrane antigen-1 (AMA1) is a leading blood stage malaria vaccine candidate with extreme diversity, potentially limiting its efficacy against infection and disease caused by Plasmodium falciparum parasites with diverse forms of AMA1. Methods Three hundred Malian children participated in a Phase 2 clinical trial of a bivalent malaria vaccine that found no protective efficacy. The vaccine consists of recombinant AMA1 based on the 3D7 and FVO strains of P. falciparum adjuvanted with aluminum hydroxide (AMA1-C1). The gene encoding AMA1 was sequenced from P. falciparum infections experienced before and after immunization with the study vaccine or a control vaccine. Sequences of ama1 from infections in the malaria vaccine and control groups were compared with regard to similarity to the vaccine antigens using several measures of genetic diversity. Time to infection with parasites carrying AMA1 haplotypes similar to the vaccine strains with respect to immunologically important polymorphisms and the risk of infection with vaccine strain haplotypes were compared. Results Based on 62 polymorphic AMA1 residues, 186 unique ama1 haplotypes were identified among 315 ama1 sequences that were included in the analysis. Eight infections had ama1 sequences identical to 3D7 while none were identical to FVO. Several measures of genetic diversity showed that ama1 sequences in the malaria vaccine and control groups were comparable both at baseline and during follow up period. Pre- and post-immunization ama1 sequences in both groups all had a similar degree of genetic distance from FVO and 3D7 ama1 . No differences were found in the time of first clinical episode or risk of infection with an AMA1 haplotype similar to 3D7 or FVO with respect to a limited set of immunologically important polymorphisms found in the cluster 1 loop of domain I of AMA1. Conclusion This Phase 2 trial of a bivalent AMA1 malaria vaccine found no evidence of vaccine selection or strain-specific efficacy, suggesting that the extreme genetic diversity of AMA1 did not account for failure of the vaccine to provide protection.

Based on the emergence and spread throughout the Greater Mekong Subregion (GMS) of multiple artemisinin-resistant lineages, the prevalence of multidrug resistance leading to high rates of artemisinin-based combination treatment failure in parts of the GMS, and the declining malaria burden in the region, the World Health Organization has recommended complete elimination of falciparum malaria from the GMS. Mass drug administration (MDA) is being piloted as one elimination intervention to be employed as part of this effort. However, concerns remain as to whether MDA might exacerbate the already prevalent problem of multidrug resistance in the region. In this review, we briefly discuss challenges of MDA, the use of MDA in the context of multidrug-resistant malaria, and the potential of different drug combinations and drug-based elimination strategies for mitigating the emergence and spread of resistance.

Background Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. Methods A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum . Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. Results A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92–0.99] and 0.92 [95% CI: 0.83–0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28–0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35–3.68]. Conclusions A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Background Estimating malaria risk associated with work locations and travel across a region provides local health officials with information useful to mitigate possible transmission paths of malaria as well as understand the risk of exposure for local populations. This study investigates malaria exposure risk by analysing the spatial pattern of malaria cases (primarily Plasmodium vivax) in Ubon Ratchathani and Sisaket provinces of Thailand, using an ecological niche model and machine learning to estimate the species distribution of P. vivax malaria and compare the resulting niche areas with occupation type, work locations, and work-related travel routes. Methods A maximum entropy model was trained to estimate the distribution of P. vivax malaria for a period between January 2019 and April 2020, capturing estimated malaria occurrence for these provinces. A random simulation workflow was developed to make region-based case data usable for the machine learning approach. This workflow was used to generate a probability surface for the ecological niche regions. The resulting niche regions were analysed by occupation type, home and work locations, and work-related travel routes to determine the relationship between these variables and malaria occurrence. A one-way analysis of variance (ANOVA) test was used to understand the relationship between predicted malaria occurrence and occupation type. Results The MaxEnt (full name) model indicated a higher occurrence of P. vivax malaria in forested areas especially along the Thailand–Cambodia border. The ANOVA results showed a statistically significant difference between average malaria risk values predicted from the ecological niche model for rubber plantation workers and farmers, the two main occupation groups in the study. The rubber plantation workers were found to be at higher risk of exposure to malaria than farmers in Ubon Ratchathani and Sisaket provinces of Thailand. Conclusion The results from this study point to occupation-related factors such as work location and the routes travelled to work, being risk factors in malaria occurrence and possible contributors to transmission among local populations.

In Bandiagara, Mali, children experience on average two clinical malaria episodes per year. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, can vary dramatically among children. We simultaneously characterize host and parasite gene expression profiles from 136 Malian children with symptomatic falciparum malaria and examine differences in the relative proportion of immune cells and parasite stages, as well as in gene expression, associated with infection and or patient characteristics. Parasitemia explains much of the variation in host and parasite gene expression, and infections with higher parasitemia display proportionally more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child’s age also strongly correlates with variations in gene expression: Plasmodium falciparum genes associated with age suggest that older children carry more male gametocytes, while variations in host gene expression indicate a stronger innate response in younger children and stronger adaptive response in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children’s age when studying and treating malaria infections. Here the authors use dual RNA sequencing to characterize host and parasite gene expression from 136 Malian children with symptomatic Plasmodium falciparum infection. They find that parasitemia levels correlate with neutrophil and T cell levels and that the child’s age correlates with innate immune gene expression as well as gametocyte levels.

Intensive malaria control and elimination efforts have led to substantial reductions in malaria incidence over the past two decades. However, the reduction in Plasmodium falciparum malaria cases has led to a species shift in some geographic areas, with P. vivax predominating in many areas outside of Africa. Despite its wide geographic distribution, P. vivax vaccine development has lagged far behind that for P. falciparum, in part due to the inability to cultivate P. vivax in vitro, hindering traditional approaches for antigen identification. In a prior study, we have used a positive-unlabeled random forest (PURF) machine learning approach to identify P. falciparum antigens based on features of known antigens for consideration in vaccine development efforts. Here we integrate systems data from P. falciparum (the better-studied species) to improve PURF models to predict potential P. vivax vaccine antigen candidates. We further show that inclusion of known antigens from the other species is critical for model performance, but the inclusion of only the unlabeled proteins from the other species can result in misdirection of the model toward predictors of species classification, rather than antigen identification. Beyond malaria, incorporating antigens from a closely related species may aid in vaccine development for emerging pathogens having few or no known antigens.