Co-transmission of Related Malaria Parasite Lineages Shapes Within-Host Parasite Diversity

MOIRE: A software package for the estimation of allele frequencies and effective multiplicity of infection from polyallelic data

Malaria parasite genetic data can provide insight into parasite phenotypes, evolution, and transmission. However, estimating key parameters such as allele frequencies, multiplicity of infection (MOI), and within-host relatedness from genetic data has been challenging, particularly in the presence of multiple related coinfecting strains. Existing methods often rely on single nucleotide polymorphism (SNP) data and do not account for within-host relatedness. In this study, we introduce a Bayesian approach called MOIRE (Multiplicity Of Infection and allele frequency REcovery), designed to estimate allele frequencies, MOI, and within-host relatedness from genetic data subject to experimental error. Importantly, MOIRE is flexible in accommodating both polyallelic and SNP data, making it adaptable to diverse genotyping panels. We also introduce a novel metric, the effective MOI (eMOI), which integrates MOI and within-host relatedness, providing a robust and interpretable measure of genetic diversity. Using extensive simulations and real-world data from a malaria study in Namibia, we demonstrate the superior performance of MOIRE over naive estimation methods, accurately estimating MOI up to 7 with moderate sized panels of diverse loci (e.g. microhaplotypes). MOIRE also revealed substantial heterogeneity in population mean MOI and mean relatedness across health districts in Namibia, suggesting detectable differences in transmission dynamics. Notably, eMOI emerges as a portable metric of within-host diversity, facilitating meaningful comparisons across settings, even when allele frequencies or genotyping panels are different. MOIRE represents an important addition to the analysis toolkit for malaria population dynamics. Compared to existing software, MOIRE enhances the accuracy of parameter estimation and enables more comprehensive insights into within-host diversity and population structure. Additionally, MOIRE's adaptability to diverse data sources and potential for future improvements make it a valuable asset for research on malaria and other organisms, such as other eukaryotic pathogens. MOIRE is available as an R package at https://eppicenter.github.io/moire/.

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions

Here we introduce a new endpoint ″census population size″ to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (MOI var ), based on the hyper-diversity of the var multigene family. We present a Bayesian approach to estimate MOI var from sequencing and counting the number of unique DBLα tags (or DBLα types) of var genes, and derive from it census population size by summation of MOI var in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high-seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by > 90% and decreased parasite prevalence by ~40-50%, significant reductions in var diversity, MOI var , and population size were observed in ~2,000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short lived and 32-months after IRS was discontinued and SMC was introduced, var diversity and population size rebounded in all age groups except for the younger children (1-5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the var population genetic characteristics of a high-transmission system (high var diversity; low var repertoire similarity) demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Genetic surveillance reveals low, sustained malaria transmission with clonal replacement in Sao Tome and Principe

Despite efforts to eliminate malaria in Sao Tome and Principe (STP), cases have recently increased. Understanding residual transmission structure is crucial for developing effective elimination strategies. This study collected surveillance data and generated amplicon sequencing data from 980 samples between 2010 and 2016 to examine the genetic structure of the parasite population. The mean multiplicity of infection (MOI) was 1.3, with 11% polyclonal infections, indicating low transmission intensity. Temporal trends of these genetic metrics did not align with incidence rates, suggesting that changes in genetic metrics may not straightforwardly reflect changes in transmission intensity, particularly in low transmission settings where genetic drift and importation have a substantial impact. While 88% of samples were genetically linked, continuous turnover in genetic clusters and changes in drug-resistance haplotypes were observed. Principal component analysis revealed some STP samples were genetically similar to those from Central and West Africa, indicating possible importation. These findings highlight the need to prioritize several interventions such as targeted interventions against transmission hotspots, reactive case detection, and strategies to reduce the introduction of new parasites into this island nation as it approaches elimination. This study also serves as a case study for implementing genetic surveillance in a low transmission setting.

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.

From multiplicity of infection to force of infection for sparsely sampled Plasmodium falciparum populations at high transmission

High multiplicity of infection or MOI, the number of genetically distinct parasite strains co-infecting a single human host, characterizes infectious diseases including falciparum malaria at high transmission. It accompanies high asymptomatic Plasmodium falciparum prevalence despite high exposure, creating a large transmission reservoir challenging intervention. High MOI and asymptomatic prevalence are enabled by immune evasion of the parasite achieved via vast antigenic diversity. Force of infection or FOI, the number of new infections acquired by an individual host over a given time interval, is the dynamic sister quantity of MOI, and a key epidemiological parameter for monitoring the impact of antimalarial interventions and assessing vaccine or drug efficacy in clinical trials. FOI remains difficult, expensive, and labor-intensive to accurately measure, especially in high-transmission regions, whether directly via cohort studies or indirectly via the fitting of epidemiological models to repeated cross-sectional surveys. We propose here the application of queuing theory to obtain FOI on the basis of MOI, in the form of either a two-moment approximation method or Little's law. We illustrate these methods with MOI estimates obtained under sparse sampling schemes with the recently proposed " v a r coding" method, based on sequences of the v a r multigene family encoding for the major variant surface antigen of the blood stage of malaria infection. The methods are evaluated with simulation output from a stochastic agent-based model, and are applied to an interrupted time-series study from Bongo District in northern Ghana before and immediately after a three-round transient indoor residual spraying (IRS) intervention. We incorporate into the sampling of the simulation output, limitations representative of those encountered in the collection of field data, including under-sampling of v a r genes, missing data, and usage of antimalarial drug treatment. We address these limitations in MOI estimates with a Bayesian framework and an imputation bootstrap approach. We demonstrate that both proposed methods give good and consistent FOI estimates across various simulated scenarios. Their application to the field surveys shows a pronounced reduction in annual FOI during intervention, of more than 70%. The proposed approach should be applicable to the many geographical locations where cohort or cross-sectional studies with regular and frequent sampling are lacking but single-time-point surveys under sparse sampling schemes are available, and for MOI estimates obtained in different ways. They should also be relevant to other pathogens of humans, wildlife and livestock whose immune evasion strategies are based on large antigenic variation resulting in high multiplicity of infection.

A single cell atlas of sexual development in Plasmodium falciparum

The developmental decision made by malaria parasites to become sexual underlies all malaria transmission. Here, we describe a rich atlas of short- and long-read single-cell transcriptomes of over 37,000 Plasmodium falciparum cells across intraerythrocytic asexual and sexual development. We used the atlas to explore transcriptional modules and exon usage along sexual development and expanded it to include malaria parasites collected from four Malian individuals naturally infected with multiple P. falciparum strains. We investigated genotypic and transcriptional heterogeneity within and among these wild strains at the single-cell level, finding differential expression between different strains even within the same host. These data are a key addition to the Malaria Cell Atlas interactive data resource, enabling a deeper understanding of the biology and diversity of transmission stages.

Strong positive selection biases identity-by-descent-based inferences of recent demography and population structure in Plasmodium falciparum

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.

Microsatellites reveal high polymorphism and high potential for use in anti-malarial efficacy studies in areas with different transmission intensities in mainland Tanzania

BACKGROUND

Tanzania is currently implementing therapeutic efficacy studies (TES) in areas of varying malaria transmission intensities as per the World Health Organization (WHO) recommendations. In TES, distinguishing reinfection from recrudescence is critical for the determination of anti-malarial efficacy. Recently, the WHO recommended genotyping polymorphic coding genes, merozoite surface proteins 1 and 2 (msp1 and msp2), and replacing the glutamate-rich protein (glurp) gene with one of the highly polymorphic microsatellites in Plasmodium falciparum to adjust the efficacy of antimalarials in TES. This study assessed the polymorphisms of six neutral microsatellite markers and their potential use in TES, which is routinely performed in Tanzania.

METHODS

Plasmodium falciparum samples were obtained from four TES sentinel sites, Kibaha (Pwani), Mkuzi (Tanga), Mlimba (Morogoro) and Ujiji (Kigoma), between April and September 2016. Parasite genomic DNA was extracted from dried blood spots on filter papers using commercial kits. Genotyping was done using six microsatellites (Poly-α, PfPK2, TA1, C3M69, C2M34 and M2490) by capillary method, and the data were analysed to determine the extent of their polymorphisms and genetic diversity at the four sites.

RESULTS

Overall, 83 (88.3%) of the 94 samples were successfully genotyped (with positive results for ≥ 50.0% of the markers), and > 50.0% of the samples (range = 47.6-59.1%) were polyclonal, with a mean multiplicity of infection (MOI) ranging from 1.68 to 1.88 among the four sites. There was high genetic diversity but limited variability among the four sites based on mean allelic richness (RS = 7.48, range = 7.27-8.03, for an adjusted minimum sample size of 18 per site) and mean expected heterozygosity (He = 0.83, range = 0.80-0.85). Cluster analysis of haplotypes using STRUCTURE, principal component analysis, and pairwise genetic differentiation (FST) did not reveal population structure or clustering of parasites according to geographic origin. Of the six markers, Poly-α was the most polymorphic, followed by C2M34, TA1 and C3M69, while M2490 was the least polymorphic.

CONCLUSION

Microsatellite genotyping revealed high polyclonality and genetic diversity but no significant population structure. Poly-α, C2M34, TA1 and C3M69 were the most polymorphic markers, and Poly-α alone or with any of the other three markers could be adopted for use in TES in Tanzania.

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.

Population genomic evidence of structured and connected Plasmodium vivax populations under host selection in Latin America

Pathogen genomic epidemiology has the potential to provide a deep understanding of population dynamics, facilitating strategic planning of interventions, monitoring their impact, and enabling timely responses, and thereby supporting control and elimination efforts of parasitic tropical diseases. Plasmodium vivax, responsible for most malaria cases outside Africa, shows high genetic diversity at the population level, driven by factors like sub-patent infections, a hidden reservoir of hypnozoites, and early transmission to mosquitoes. While Latin America has made significant progress in controlling Plasmodium falciparum, it faces challenges with residual P. vivax. To characterize genetic diversity and population structure and dynamics, we have analyzed the largest collection of P. vivax genomes to date, including 1474 high-quality genomes from 31 countries across Asia, Africa, Oceania, and America. While P. vivax shows high genetic diversity globally, Latin American isolates form a distinctive population, which is further divided into sub-populations and occasional clonal pockets. Genetic diversity within the continent was associated with the intensity of transmission. Population differentiation exists between Central America and the North Coast of South America, vs. the Amazon Basin, with significant gene flow within the Amazon Basin, but limited connectivity between the Northwest Coast and the Amazon Basin. Shared genomic regions in these parasite populations indicate adaptive evolution, particularly in genes related to DNA replication, RNA processing, invasion, and motility - crucial for the parasite's survival in diverse environments. Understanding these population-level adaptations is crucial for effective control efforts, offering insights into potential mechanisms behind drug resistance, immune evasion, and transmission dynamics.

Single-cell analyses of polyclonal Plasmodium vivax infections and their consequences on parasite transmission

Most Plasmodium vivax infections contain genetically distinct parasites, but the consequences of this polyclonality on the development of asexual parasites, their sexual differentiation, and their transmission remain unknown. We describe infections of Saimiri monkeys with two strains of P. vivax and the analyses of 117,350 parasites characterized by single cell RNA sequencing and individually genotyped. In our model, consecutive inoculations fail to establish polyclonal infections. By contrast, simultaneous inoculations of two strains lead to sustained polyclonal infections, although without detectable differences in parasite regulation or sexual commitment. Analyses of sporozoites dissected from mosquitoes fed on coinfected monkeys show that all genotypes are successfully transmitted to mosquitoes. However, after sporozoite inoculation, not all genotypes contribute to the subsequent blood infections, highlighting an important bottleneck during pre-erythrocytic development. Overall, these studies provide new insights on the mechanisms regulating the establishment of polyclonal P. vivax infections and their consequences for disease transmission.

Genetic diversity and natural selection of apical membrane antigen-1 (ama-1) in Cameroonian Plasmodium falciparum isolates

Antigenic variation associated with genetic diversity in global Plasmodium falciparum apical membrane antigen-1 (PfAMA-1) is a major impediment to designing an effective malaria vaccine. Here, we report the first study on genetic diversity and natural selection of the Pfama-1 gene in P. falciparum isolates from Cameroon. A total of 328 P. falciparum positive samples collected during 2016 and 2019 from five localities of Cameroon were analysed. The ectodomain coding fragment of Pfama-1 gene was amplified for polymorphism profiling and natural selection analysis. A total of 108 distinct haplotypes were found in 203 P. falciparum isolates with considerable nucleotide diversity (π = 0.016) and haplotype diversity (Hd = 0.976). Most amino acid substitutions detected were scattered in ectodomain-I and few specific mutations viz P145L, K148Q, K462I, L463F, N471K, S482L, E537G, K546R and I547F were seen only in Cameroonian isolates. A tendency of natural selection towards positive diversifying selection was observed (Taj-D = 2.058). Five positively selected codon sites (P145L, S283L, Q308E/K, P330S and I547F) were identified, which overlapped with predicted B-cell epitopes and red blood cell (RBC) binding sites, suggesting their potential implication in host immune pressure and parasite-RBC binding complex modulation. The Cameroonian P. falciparum populations indicated a moderate level of genetic differentiation when compared with global sequences, with few exceptions from Vietnam and Venezuela. Our findings provide baseline data on existing Pfama-1 gene polymorphisms in Cameroonian field isolates, which will be useful information for malaria vaccine design.

Hyper-diverse antigenic variation and resilience to transmission-reducing intervention in falciparum malaria

Intervention against falciparum malaria in high transmission regions remains challenging, with relaxation of control efforts typically followed by rapid resurgence. Resilience to intervention co-occurs with incomplete immunity, whereby children eventually become protected from severe disease but not infection and a large transmission reservoir results from high asymptomatic prevalence across all ages. Incomplete immunity relates to the vast antigenic variation of the parasite, with the major surface antigen of the blood stage of infection encoded by the multigene family known as var. Recent deep sampling of var sequences from individual isolates in northern Ghana showed that parasite population structure exhibited persistent features of high-transmission regions despite the considerable decrease in prevalence during transient intervention with indoor residual spraying (IRS). We ask whether despite such apparent limited impact, the transmission system had been brought close to a transition in both prevalence and resurgence ability. With a stochastic agent-based model, we investigate the existence of such a transition to pre-elimination with intervention intensity, and of molecular indicators informative of its approach. We show that resurgence ability decreases sharply and nonlinearly across a narrow region of intervention intensities in model simulations, and identify informative molecular indicators based on var gene sequences. Their application to the survey data indicates that the transmission system in northern Ghana was brought close to transition by IRS. These results suggest that sustaining and intensifying intervention would have pushed malaria dynamics to a slow-rebound regime with an increased probability of local parasite extinction.

Can incorporating genotyping data into efficacy estimators improve efficiency of early phase malaria vaccine trials?

BACKGROUND

Early phase malaria vaccine field trials typically measure malaria infection by PCR or thick blood smear microscopy performed on serially sampled blood. Vaccine efficacy (VE) is the proportion reduction in an endpoint due to vaccination and is often calculated as VEHR = 1-hazard ratio or VERR = 1-risk ratio. Genotyping information can distinguish different clones and distinguish multiple infections over time, potentially increasing statistical power. This paper investigates two alternative VE endpoints incorporating genotyping information: VEmolFOI, the vaccine-induced proportion reduction in incidence of new clones acquired over time, and VEC, the vaccine-induced proportion reduction in mean number of infecting clones per exposure.

METHODS

Power of VEmolFOI and VEC was compared to that of VEHR and VERR by simulations and analytic derivations, and the four VE methods were applied to three data sets: a Phase 3 trial of RTS,S malaria vaccine in 6912 African infants, a Phase 2 trial of PfSPZ Vaccine in 80 Burkina Faso adults, and a trial comparing Plasmodium vivax incidence in 466 Papua New Guinean children after receiving chloroquine + artemether lumefantrine with or without primaquine (as these VE methods can also quantify effects of other prevention measures). By destroying hibernating liver-stage P. vivax, primaquine reduces subsequent reactivations after treatment completion.

RESULTS

In the trial of RTS,S vaccine, a significantly reduced number of clones at first infection was observed, but this was not the case in trials of PfSPZ Vaccine or primaquine, although the PfSPZ trial lacked power to show a reduction. Resampling smaller data sets from the large RTS,S trial to simulate phase 2 trials showed modest power gains from VEC compared to VEHR for data like those from RTS,S, but VEC is less powerful than VEHR for trials in which the number of clones at first infection is not reduced. VEmolFOI was most powerful in model-based simulations, but only the primaquine trial collected enough serial samples to precisely estimate VEmolFOI. The primaquine VEmolFOI estimate decreased after most control arm liver-stage infections reactivated (which mathematically resembles a waning vaccine), preventing VEmolFOI from improving power.

CONCLUSIONS

The power gain from the genotyping methods depends on the context. Because input parameters for early phase power calculations are often uncertain, these estimators are not recommended as primary endpoints for small trials unless supported by targeted data analysis.

TRIAL REGISTRATIONS

NCT00866619, NCT02663700, NCT02143934.

MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites

Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of noncoding variants in this unusual genome of malaria parasites remain elusive. We developed a sequence-based, ab initio deep learning framework, MalariaSED, for predicting chromatin profiles in malaria parasites. The MalariaSED performance was validated by published ChIP-qPCR and TF motifs results. Applying MalariaSED to ~ 1.3 million variants shows that geographically differentiated noncoding variants are associated with parasite invasion and drug resistance. Further analysis reveals chromatin accessibility changes at Plasmodium falciparum rings are partly associated with artemisinin resistance. MalariaSED illuminates the potential functional roles of noncoding variants in malaria parasites.

Can incorporating genotyping data into efficacy estimators improve efficiency of early phase malaria vaccine trials?

Background

Early phase malaria vaccine field trials typically measure malaria infection by PCR or thick blood smear microscopy performed on serially sampled blood. Vaccine efficacy (VE) is the proportion reduction in an endpoint due to vaccination and is often calculated as V E H R = 1 - hazard ratio or V E R R = 1 - risk ratio. Genotyping information can distinguish different clones and distinguish multiple infections over time, potentially increasing statistical power. This paper investigates two alternative VE endpoints incorporating genotyping information: V E m o l F O I , the vaccine-induced proportion reduction in incidence of new clones acquired over time, and V E C , the vaccine-induced proportion reduction in mean number of infecting clones per exposure.

Methods

We used simulations and analytic derivations to compare power of these methods to V E H R and V E R R and applied them to three data sets: a Phase 3 trial of RTS,S malaria vaccine in 6912 African infants, a Phase 2 trial of PfSPZ Vaccine in 80 Burkina Faso adults, and a trial comparing Plasmodium vivax incidence in 466 Papua New Guinean children after receiving chloroquine + artemether lumefantrine with or without primaquine (as these VE methods can also quantify effects of other prevention measures). By destroying hibernating liver-stage P. vivax, primaquine reduces subsequent reactivations after treatment completion.

Results

The RTS,S vaccine significantly reduced the number of clones at first infection, but PfSPZ vaccine and primaquine did not. Resampling smaller data sets from the large RTS,S trial to simulate phase 2 trials showed modest power gains from V E C compared to V E H R for data like RTS,S, but V E C is less powerful than V E H R for vaccines which do not reduce the number of clones at first infection. V E m o l F O I was most powerful in model-based simulations, but only the primaquine trial collected enough serial samples to precisely estimate V E m o l F O I . The primaquine V E m o l F O I estimate decreased after most control arm liver-stage infections reactivated (which mathematically resembles a waning vaccine), preventing V E m o l F O I from improving power.

Conclusions

The power gain from the genotyping methods depends on the context. Because input parameters for early phase power calculations are often uncertain, we recommend against these estimators as primary endpoints for small trials unless supported by targeted data analysis.

Trial registrations

NCT00866619, NCT02663700, NCT02143934.

Strong Positive Selection Biases Identity-By-Descent-Based Inferences of Recent Demography and Population Structure in Plasmodium falciparum

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 utilized simulations, a true IBD inference algorithm, and empirical datasets from different malaria transmission settings to investigate the extent of such bias and explore potential correction strategies. We analyzed whole genome sequence data generated from 640 new and 4,026 publicly available Plasmodium falciparum clinical isolates. Our findings demonstrated that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discovered that the removal of IBD peak regions partially restored the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

coiaf: Directly estimating complexity of infection with allele frequencies

In malaria, individuals are often infected with different parasite strains. The complexity of infection (COI) is defined as the number of genetically distinct parasite strains in an individual. Changes in the mean COI in a population have been shown to be informative of changes in transmission intensity with a number of probabilistic likelihood and Bayesian models now developed to estimate the COI. However, rapid, direct measures based on heterozygosity or FwS do not properly represent the COI. In this work, we present two new methods that use easily calculated measures to directly estimate the COI from allele frequency data. Using a simulation framework, we show that our methods are computationally efficient and comparably accurate to current approaches in the literature. Through a sensitivity analysis, we characterize how the distribution of parasite densities, the assumed sequencing depth, and the number of sampled loci impact the bias and accuracy of our two methods. Using our developed methods, we further estimate the COI globally from Plasmodium falciparum sequencing data and compare the results against the literature. We show significant differences in the estimated COI globally between continents and a weak relationship between malaria prevalence and COI.

Genomic variation during culture adaptation of genetically complex Plasmodium falciparum clinical isolates

Experimental studies on the biology of malaria parasites have mostly been based on laboratory-adapted lines, but there is limited understanding of how these may differ from parasites in natural infections. Loss-of-function mutants have previously been shown to emerge during culture of some Plasmodium falciparum clinical isolates in analyses focusing on single-genotype infections. The present study included a broader array of isolates, mostly representing multiple-genotype infections, which are more typical in areas where malaria is highly endemic. Genome sequence data from multiple time points over several months of culture adaptation of 28 West African isolates were analysed, including previously available sequences along with new genome sequences from additional isolates and time points. Some genetically complex isolates eventually became fixed over time to single surviving genotypes in culture, whereas others retained diversity, although proportions of genotypes varied over time. Drug resistance allele frequencies did not show overall directional changes, suggesting that resistance-associated costs are not the main causes of fitness differences among parasites in culture. Loss-of-function mutants emerged during culture in several of the multiple-genotype isolates, affecting genes (including AP2-HS, EPAC and SRPK1) for which loss-of-function mutants were previously seen to emerge in single-genotype isolates. Parasite clones were derived by limiting dilution from six of the isolates, and sequencing identified de novo variants not detected in the bulk isolate sequences. Interestingly, several of these were nonsense mutants and frameshifts disrupting the coding sequence of EPAC, the gene with the largest number of independent nonsense mutants previously identified in laboratory-adapted lines. Analysis of genomic identity by descent to explore relatedness among clones revealed co-occurring non-identical sibling parasites, illustrative of the natural genetic structure within endemic populations.

Measurably recombining malaria parasites

Genomic epidemiology has guided research and policy for various viral pathogens and there has been a parallel effort towards using genomic epidemiology to combat diseases that are caused by eukaryotic pathogens, such as the malaria parasite. However, the central concept of viral genomic epidemiology, namely that of measurably mutating pathogens, does not apply easily to sexually recombining parasites. Here we introduce the related but different concept of measurably recombining malaria parasites to promote convergence around a unifying theoretical framework for malaria genomic epidemiology. Akin to viral phylodynamics, we anticipate that an inferential framework developed around recombination will help guide practical research and thus realize the full public health potential of genomic epidemiology for malaria parasites and other sexually recombining pathogens.

Low genetic diversity of Plasmodium falciparum merozoite surface protein 1 and 2 and multiplicity of infections in western Ethiopia following effective malaria interventions

BACKGROUND

Genetic diversity of malaria parasites can inform the intensity of transmission and poses a major threat to malaria control and elimination interventions. Characterization of the genetic diversity would provide essential information about the ongoing control efforts. This study aimed to explore allelic polymorphism of merozoite surface protein 1 (msp1) and merozoite surface protein 2 (msp2) to determine the genetic diversity and multiplicity of Plasmodium falciparum infections circulating in high and low transmission sites in western Ethiopia.

METHODS

Parasite genomic DNA was extracted from a total of 225 dried blood spots collected from confirmed uncomplicated P. falciparum malaria-infected patients in western Ethiopia. Of these, 72.4% (163/225) and 27.6% (62/225) of the samples were collected in high and low transmission areas, respectively. Polymorphic msp1 and msp2 genes were used to explore the genetic diversity and multiplicity of falciparum malaria infections. Genotyping of msp1 was successful in 86.5% (141/163) and 88.7% (55/62) samples collected from high and low transmission areas, respectively. Genotyping of msp2 was carried out among 85.3% (139/163) and 96.8% (60/62) of the samples collected in high and low transmission sites, respectively. Plasmodium falciparum msp1 and msp2 genes were amplified by nested PCR and the PCR products were analysed by QIAxcel ScreenGel Software. A P-value of less or equal to 0.05 was considered significant.

RESULTS

High prevalence of falciparum malaria was identified in children less than 15 years as compared with those  ≥ 15 years old (AOR = 2.438, P = 0.005). The three allelic families of msp1 (K1, MAD20, and RO33) and the two allelic families of msp2 (FC27 and 3D7), were observed in samples collected in high and low transmission areas. However, MAD 20 and FC 27 alleles were the predominant allelic families in both settings. Plasmodium falciparum isolates circulating in western Ethiopia had low genetic diversity and mean MOI. No difference in mean MOI between high transmission sites (mean MOI 1.104) compared with low transmission area (mean MOI 1.08) (p > 0.05). The expected heterozygosity of msp1 was slightly higher in isolates collected from high transmission sites (He = 0.17) than in those isolates from low transmission (He = 0.12). However, the heterozygosity of msp2 was not different in both settings (Pfmsp2: 0.04 in high transmission; pfmsp2: 0.03 in low transmission).

CONCLUSION

Plasmodium falciparum from clinical malaria cases in western Ethiopia has low genetic diversity and multiplicity of infection irrespective of the intensity of transmission at the site of sampling. These may be signaling the effectiveness of malaria control strategies in Ethiopia; although further studies are required to determine how specific intervention strategies and other parameters that drive the pattern.

Targeting malaria parasites inside mosquitoes: ecoevolutionary consequences

Proof-of-concept studies demonstrate that antimalarial drugs designed for human treatment can also be applied to mosquitoes to interrupt malaria transmission. Deploying a new control tool is ideally undertaken within a stewardship programme that maximises a drug's lifespan by minimising the risk of resistance evolution and slowing its spread once emerged. We ask: what are the epidemiological and evolutionary consequences of targeting parasites within mosquitoes? Our synthesis argues that targeting parasites inside mosquitoes (i) can be modelled by readily expanding existing epidemiological frameworks; (ii) provides a functionally novel control method that has potential to be more robust to resistance evolution than targeting parasites in humans; and (iii) could extend the lifespan and clinical benefit of antimalarials used exclusively to treat humans.

Bulk segregant linkage mapping for rodent and human malaria parasites

In 2005 Richard Carter's group surprised the malaria genetics community with an elegant approach to rapidly mapping the genetic basis of phenotypic traits in rodent malaria parasites. This approach, which he termed "linkage group selection", utilized bulk pools of progeny, rather than individual clones, and exploited simple selection schemes to identify genome regions underlying resistance to drug treatment (or other phenotypes). This work was the first application of "bulk segregant" methodologies for genetic mapping in microbes: this approach is now widely used in yeast, and across multiple recombining pathogens ranging from Aspergillus fungi to Schistosome parasites. Genetic crosses of human malaria parasites (for which Richard Carter was also a pioneer) can now be conducted in humanized mice, providing new opportunities for exploiting bulk segregant approaches for a wide variety of malaria parasite traits. We review the application of bulk segregant approaches to mapping malaria parasite traits and suggest additional developments that may further expand the utility of this powerful approach.

Evolutionary genetics of malaria

Many standard-textbook population-genetic results apply to a wide range of species. Sometimes, however, population-genetic models and principles need to be tailored to a particular species. This is particularly true for malaria, which next to tuberculosis and HIV/AIDS ranks among the economically most relevant infectious diseases. Importantly, malaria is not one disease—five human-pathogenic species of Plasmodium exist. P. falciparum is not only the most severe form of human malaria, but it also causes the majority of infections. The second most relevant species, P. vivax, is already considered a neglected disease in several endemic areas. All human-pathogenic species have distinct characteristics that are not only crucial for control and eradication efforts, but also for the population-genetics of the disease. This is particularly true in the context of selection. Namely, fitness is determined by so-called fitness components, which are determined by the parasites live-history, which differs between malaria species. The presence of hypnozoites, i.e., dormant liver-stage parasites, which can cause disease relapses, is a distinct feature of P. vivax and P. ovale sp. In P. malariae inactivated blood-stage parasites can cause a recrudescence years after the infection was clinically cured. To properly describe population-genetic processes, such as the spread of anti-malarial drug resistance, these features must be accounted for appropriately. Here, we introduce and extend a population-genetic framework for the evolutionary dynamics of malaria, which applies to all human-pathogenic malaria species. The model focuses on, but is not limited to, the spread of drug resistance. The framework elucidates how the presence of dormant liver stage or inactivated blood stage parasites that act like seed banks delay evolutionary processes. It is shown that, contrary to standard population-genetic theory, the process of selection and recombination cannot be decoupled in malaria. Furthermore, we discuss the connection between haplotype frequencies, haplotype prevalence, transmission dynamics, and relapses or recrudescence in malaria.

A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data

The introduction of genomic methods facilitated standardized molecular disease surveillance. For instance, SNP barcodes in Plasmodium vivax and Plasmodium falciparum malaria allows the characterization of haplotypes, their frequencies and prevalence to reveal temporal and spatial transmission patterns. A confounding factor is the presence of multiple genetically distinct pathogen variants within the same infection, known as multiplicity of infection (MOI). Disregarding ambiguous information, as usually done in ad-hoc approaches, leads to less confident and biased estimates. We introduce a statistical framework to obtain maximum-likelihood estimates (MLE) of haplotype frequencies and prevalence alongside MOI from malaria SNP data, i.e., multiple biallelic marker loci. The number of model parameters increases geometrically with the number of genetic markers considered and no closed-form solution exists for the MLE. Therefore, the MLE needs to be derived numerically. We use the Expectation-Maximization (EM) algorithm to derive the maximum-likelihood estimates, an efficient and easy-to-implement algorithm that yields a numerically stable solution. We also derive expressions for haplotype prevalence based on either all or just the unambiguous genetic information and compare both approaches. The latter corresponds to a biased ad-hoc estimate of prevalence. We assess the performance of our estimator by systematic numerical simulations assuming realistic sample sizes and various scenarios of transmission intensity. For reasonable sample sizes, and number of loci, the method has little bias. As an example, we apply the method to a dataset from Cameroon on sulfadoxine-pyrimethamine resistance in P. falciparum malaria. The method is not confined to malaria and can be applied to any infectious disease with similar transmission behavior. An easy-to-use implementation of the method as an R-script is provided.

Population genomics in neglected malaria parasites

Malaria elimination includes neglected human malaria parasites Plasmodium vivax, Plasmodium ovale spp., and Plasmodium malariae. Biological features such as association with low-density infection and the formation of hypnozoites responsible for relapse make their elimination challenging. Studies on these parasites rely primarily on clinical samples due to the lack of long-term culture techniques. With improved methods to enrich parasite DNA from clinical samples, whole-genome sequencing of the neglected malaria parasites has gained increasing popularity. Population genomics of more than 2200 P. vivax global isolates has improved our knowledge of parasite biology and host-parasite interactions, identified vaccine targets and potential drug resistance markers, and provided a new way to track parasite migration and introduction and monitor the evolutionary response of local populations to elimination efforts. Here, we review advances in population genomics for neglected malaria parasites, discuss how the rich genomic information is being used to understand parasite biology and epidemiology, and explore opportunities for the applications of malaria genomic data in malaria elimination practice.

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.

Genetic Diversity of Plasmodium falciparum and Distribution of Antimalarial Drug Resistance Mutations in Symptomatic and Asymptomatic Infections

Malaria control relies on passive case detection, and this strategy fails detecting asymptomatic infections. In addition, infections in endemic areas harbor multiple parasite genotypes that could affect case management and malaria epidemiology.

Sympatric Recombination in Zoonotic Cryptosporidium Leads to Emergence of Populations with Modified Host Preference

Genetic recombination plays a critical role in the emergence of pathogens with phenotypes such as drug resistance, virulence, and host adaptation. Here, we tested the hypothesis that recombination between sympatric ancestral populations leads to the emergence of divergent variants of the zoonotic parasite Cryptosporidium parvum with modified host ranges. Comparative genomic analyses of 101 isolates have identified seven subpopulations isolated by distance. They appear to be descendants of two ancestral populations, IIa in northwestern Europe and IId from southwestern Asia. Sympatric recombination in areas with both ancestral subtypes and subsequent selective sweeps have led to the emergence of new subpopulations with mosaic genomes and modified host preference. Subtelomeric genes could be involved in the adaptive selection of subpopulations, while copy number variations of genes encoding invasion-associated proteins are potentially associated with modified host ranges. These observations reveal ancestral origins of zoonotic C. parvum and suggest that pathogen import through modern animal farming might promote the emergence of divergent subpopulations of C. parvum with modified host preference.

Maintenance of high temporal Plasmodium falciparum genetic diversity and complexity of infection in asymptomatic and symptomatic infections in Kilifi, Kenya from 2007 to 2018

Background

High levels of genetic diversity are common characteristics of Plasmodium falciparum parasite populations in high malaria transmission regions. There has been a decline in malaria transmission intensity over 12 years of surveillance in the community in Kilifi, Kenya. This study sought to investigate whether there was a corresponding reduction in P. falciparum genetic diversity, using msp2 as a genetic marker.

Methods

Blood samples were obtained from children (< 15 years) enrolled into a cohort with active weekly surveillance between 2007 and 2018 in Kilifi, Kenya. Asymptomatic infections were defined during the annual cross-sectional blood survey and the first-febrile malaria episode was detected during the weekly follow-up. Parasite DNA was extracted and successfully genotyped using allele-specific nested polymerase chain reactions for msp2 and capillary electrophoresis fragment analysis.

Results

Based on cross-sectional surveys conducted in 2007–2018, there was a significant reduction in malaria prevalence (16.2–5.5%: P-value < 0.001), however msp2 genetic diversity remained high. A high heterozygosity index (He) (> 0.95) was observed in both asymptomatic infections and febrile malaria over time. About 281 (68.5%) asymptomatic infections were polyclonal (> 2 variants per infection) compared to 46 (56%) polyclonal first-febrile infections. There was significant difference in complexity of infection (COI) between asymptomatic 2.3 [95% confidence interval (CI) 2.2–2.5] and febrile infections 2.0 (95% CI 1.7–2.3) (P = 0.016). Majority of asymptomatic infections (44.2%) carried mixed alleles (i.e., both FC27 and IC/3D7), while FC27 alleles were more frequent (53.3%) among the first-febrile infections.

Conclusions

Plasmodium falciparum infections in Kilifi are still highly diverse and polyclonal, despite the reduction in malaria transmission in the community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04213-7.

Amplicon sequencing as a potential surveillance tool for complexity of infection and drug resistance markers in Plasmodium falciparum asymptomatic infections

Background

Genotyping Plasmodium falciparum subpopulations in malaria infections is an important aspect of malaria molecular epidemiology to understand within-host diversity and the frequency of drug resistance markers.

Methods

We characterized P. falciparum genetic diversity in asymptomatic infections and subsequent first febrile infections using amplicon sequencing (AmpSeq) of ama1 in Coastal Kenya. We also examined temporal changes in haplotype frequencies of mdr1, a drug-resistant marker.

Results

We found >60% of the infections were polyclonal (complexity of infection [COI] >1) and there was a reduction in COI over time. Asymptomatic infections had a significantly higher mean COI than febrile infections based on ama1 sequences (2.7 [95% confidence interval {CI}, 2.65–2.77] vs 2.22 [95% CI, 2.17–2.29], respectively). Moreover, an analysis of 30 paired asymptomatic and first febrile infections revealed that many first febrile infections (91%) were due to the presence of new ama1 haplotypes. The mdr1-YY haplotype, associated with chloroquine and amodiaquine resistance, decreased over time, while the NY (wild type) and the NF (modulates response to lumefantrine) haplotypes increased.

Conclusions

This study emphasizes the utility of AmpSeq in characterizing parasite diversity as it can determine relative proportions of clones and detect minority clones. The usefulness of AmpSeq in antimalarial drug resistance surveillance is also highlighted.

Whole Genome Sequencing Contributions and Challenges in Disease Reduction Focused on Malaria

Malaria elimination remains an important goal that requires the adoption of sophisticated science and management strategies in the era of the COVID-19 pandemic. The advent of next generation sequencing (NGS) is making whole genome sequencing (WGS) a standard today in the field of life sciences, as PCR genotyping and targeted sequencing provide insufficient information compared to the whole genome. Thus, adapting WGS approaches to malaria parasites is pertinent to studying the epidemiology of the disease, as different regions are at different phases in their malaria elimination agenda. Therefore, this review highlights the applications of WGS in disease management, challenges of WGS in controlling malaria parasites, and in furtherance, provides the roles of WGS in pursuit of malaria reduction and elimination. WGS has invaluable impacts in malaria research and has helped countries to reach elimination phase rapidly by providing required information needed to thwart transmission, pathology, and drug resistance. However, to eliminate malaria in sub-Saharan Africa (SSA), with high malaria transmission, we recommend that WGS machines should be readily available and affordable in the region.

A cohort study on the duration of Plasmodium falciparum infections during the dry season in The Gambia

Background

In areas where Plasmodium falciparum malaria is seasonal, a dry season reservoir of blood-stage infection is essential for initiating transmission during the following wet season.

Methods

In The Gambia, a cohort of 42 individuals with quantitative polymerase chain reaction-positive P falciparum infections at the end of the transmission season (December) were followed monthly until the end of the dry season (May) to evaluate infection persistence. The influence of human host and parasitological factors was investigated.

Results

A large proportion of individuals infected at the end of the wet season had detectable infections until the end of the dry season (40.0%; 16 of 40). At the start of the dry season, the majority of these persistent infections (82%) had parasite densities >10 p/µL compared to only 5.9% of short-lived infections. Persistent infections (59%) were also more likely to be multiclonal than short-lived infections (5.9%) and were associated with individuals having higher levels of P falciparum-specific antibodies (P = .02).

Conclusions

Asymptomatic persistent infections were multiclonal with higher parasite densities at the beginning of the dry season. Screening and treating asymptomatic infections during the dry season may reduce the human reservoir of malaria responsible for initiating transmission in the wet season.

Killing the competition: a theoretical framework for liver-stage malaria

The first stage of malaria infections takes place inside the host's hepatocytes. Remarkably, Plasmodium parasites do not infect hepatocytes immediately after reaching the liver. Instead, they migrate through several hepatocytes before infecting their definitive host cells, thus increasing their chances of immune destruction. Considering that malaria can proceed normally without cell traversal, this is indeed a puzzling behaviour. In fact, the role of hepatocyte traversal remains unknown to date, implying that the current understanding of malaria is incomplete. In this work, we hypothesize that the parasites traverse hepatocytes to actively trigger an immune response in the host. This behaviour would be part of a strategy of superinfection exclusion aimed to reduce intraspecific competition during the blood stage of the infection. Based on this hypothesis, we formulate a comprehensive theory of liver-stage malaria that integrates all the available knowledge about the infection. The interest of this new paradigm is not merely theoretical. It highlights major issues in the current empirical approach to the study of Plasmodium and suggests new strategies to fight malaria.

Decrypting the complexity of the human malaria parasite biology through systems biology approaches

The human malaria parasite, Plasmodium falciparum, is a unicellular protozoan responsible for over half a million deaths annually. With a complex life cycle alternating between human and invertebrate hosts, this apicomplexan is notoriously adept at evading host immune responses and developing resistance to all clinically administered treatments. Advances in omics-based technologies, increased sensitivity of sequencing platforms and enhanced CRISPR based gene editing tools, have given researchers access to more in-depth and untapped information about this enigmatic micro-organism, a feat thought to be infeasible in the past decade. Here we discuss some of the most important scientific achievements made over the past few years with a focus on novel technologies and platforms that set the stage for subsequent discoveries. We also describe some of the systems-based methods applied to uncover gaps of knowledge left through single-omics applications with the hope that we will soon be able to overcome the spread of this life-threatening disease.

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.

The Rare, the Best: Spread of Antimalarial-Resistant Plasmodium falciparum Parasites by Anopheles Mosquito Vectors

The emergence of resistance to antimalarials has prompted the steady switch to novel therapies for decades. Withdrawal of antimalarials, such as chloroquine in sub-Saharan Africa in the late 1990s, led to rapid declines in the prevalence of resistance markers after a few years, raising the possibility of reintroducing them for malaria treatment. Here, we provide evidence that the mosquito vector plays a crucial role in maintaining parasite genetic diversity. We followed the transmission dynamics of Plasmodium falciparum parasites through its vector in natural infections from gametocytes contained in the blood of asymptomatic volunteers until sporozoites subsequently developed in the mosquito salivary glands. We did not find any selection of the mutant or wild-type pfcrt 76 allele during development in the Anopheles mosquito vector. However, microsatellite genotyping indicated that minority genotypes were favored during transmission through the mosquito. The analysis of changes in the proportions of mutant and wild-type pfcrt 76 alleles showed that, regardless of the genotype, the less-represented allele in the gametocyte population was more abundant in mosquito salivary glands, indicating a selective advantage of the minority allele in the vector. Selection of minority genotypes in the vector would explain the persistence of drug-resistant alleles in the absence of drug pressure in areas with high malaria endemicity and high genetic diversity. Our results may have important epidemiological implications, as they predict the rapid re-emergence and spread of resistant genotypes if antimalarials that had previously selected resistant parasites are reintroduced for malaria prevention or treatment.

IMPORTANCE Drug selection pressure in malaria patients is the cause of the emergence of resistant parasites. Resistance imposes a fitness cost for parasites in untreated infections, so withdrawal of the drug leads to the return of susceptible parasites. Little is known about the role of the malaria vector in this phenomenon. In an experimental study conducted in Cameroon, an area of high malaria transmission, we showed that the vector did not favor the parasites based on sensitivity or resistance criteria, but it did favor the selection of minority clones. This finding shows that the vector increases the diversity of plasmodial populations and could play an important role in falciparum malaria epidemiology by maintaining resistant clones despite the absence of therapeutic pressure.

Single-genome sequencing reveals within-host evolution of human malaria parasites

Population genomics of bulk malaria infections is unable to examine intrahost evolution; therefore, most work has focused on the role of recombination in generating genetic variation. We used single-cell sequencing protocol for low-parasitaemia infections to generate 406 near-complete single Plasmodium vivax genomes from 11 patients sampled during sequential febrile episodes. Parasite genomes contain hundreds of de novo mutations, showing strong signatures of selection, which are enriched in the ApiAP2 family of transcription factors, known targets of adaptation. Comparing 315 P. falciparum single-cell genomes from 15 patients with our P. vivax data, we find broad complementary patterns of de novo mutation at the gene and pathway level, revealing the importance of within-host evolution during malaria infections.

Single-cell genome sequencing of protozoan parasites

Despite considerable genetic variation within hosts, most parasite genome sequencing studies focus on bulk samples composed of millions of cells. Analysis of bulk samples is biased toward the dominant genotype, concealing cell-to-cell variation and rare variants. To tackle this, single-cell sequencing approaches have been developed and tailored to specific host-parasite systems. These are allowing the genetic diversity and kinship in complex parasite populations to be deciphered and for de novo genetic variation to be captured. Here, we outline the methodologies being used for single-cell sequencing of parasitic protozoans, such as Plasmodium and Leishmania spp., and how these tools are being applied to understand parasite biology.

Both co-infection and superinfection drive complex Anaplasma marginale strain structure in a natural transmission setting

Vector-borne pathogens commonly establish multi-strain infections, also called complex infections. How complex infections are established, either prior to or after the development of an adaptive immune response, termed co-infection or superinfection, respectively, has broad implications for the maintenance of genetic diversity, pathogen phenotype, epidemiology, and disease control strategies. Anaplasma marginale, a genetically diverse, obligate, intracellular tick-borne bacterial pathogen of cattle commonly establishes complex infections, particularly in regions with high transmission rates. Both co-infection and superinfection can be established experimentally, however it is unknown how complex infections develop in a natural transmission setting. To address this question, we introduced naïve animals into a herd in southern Ghana with high infection prevalence and high transmission pressure and tracked strain acquisition of A. marginale through time using multi-locus sequence typing. As expected, genetic diversity among strains was high and 97% of animals in the herd harboured multiple strains. All the introduced, naïve animals became infected, and three to four strains were typically detected in an individual animal prior to seroconversion, while one to two new strains were detected in an individual animal following seroconversion. On average, the number of strains acquired via superinfection was 16% less than those acquired via co-infection. Thus, while complex infections develop via both co-infection and superinfection, co-infection predominates in this setting. These findings have broad implications for the development of control strategies in high transmission settings.

Advances and opportunities in malaria population genomics

Almost 20 years have passed since the first reference genome assemblies were published for Plasmodium falciparum, the deadliest malaria parasite, and Anopheles gambiae, the most important mosquito vector of malaria in sub-Saharan Africa. Reference genomes now exist for all human malaria parasites and nearly half of the ~40 important vectors around the world. As a foundation for genetic diversity studies, these reference genomes have helped advance our understanding of basic disease biology and drug and insecticide resistance, and have informed vaccine development efforts. Population genomic data are increasingly being used to guide our understanding of malaria epidemiology, for example by assessing connectivity between populations and the efficacy of parasite and vector interventions. The potential value of these applications to malaria control strategies, together with the increasing diversity of genomic data types and contexts in which data are being generated, raise both opportunities and challenges in the field. This Review discusses advances in malaria genomics and explores how population genomic data could be harnessed to further support global disease control efforts.

Mechanistic within-host models of the asexual Plasmodium falciparum infection: a review and analytical assessment

Background

Malaria blood-stage infection length and intensity are important drivers of disease and transmission; however, the underlying mechanisms of parasite growth and the host’s immune response during infection remain largely unknown. Over the last 30 years, several mechanistic mathematical models of malaria parasite within-host dynamics have been published and used in malaria transmission models.

Methods

Mechanistic within-host models of parasite dynamics were identified through a review of published literature. For a subset of these, model code was reproduced and descriptive statistics compared between the models using fitted data. Through simulation and model analysis, key features of the models were compared, including assumptions on growth, immune response components, variant switching mechanisms, and inter-individual variability.

Results

The assessed within-host malaria models generally replicate infection dynamics in malaria-naïve individuals. However, there are substantial differences between the model dynamics after disease onset, and models do not always reproduce late infection parasitaemia data used for calibration of the within host infections. Models have attempted to capture the considerable variability in parasite dynamics between individuals by including stochastic parasite multiplication rates; variant switching dynamics leading to immune escape; variable effects of the host immune responses; or via probabilistic events. For models that capture realistic length of infections, model representations of innate immunity explain early peaks in infection density that cause clinical symptoms, and model representations of antibody immune responses control the length of infection. Models differed in their assumptions concerning variant switching dynamics, reflecting uncertainty in the underlying mechanisms of variant switching revealed by recent clinical data during early infection. Overall, given the scarce availability of the biological evidence there is limited support for complex models.

Conclusions

This study suggests that much of the inter-individual variability observed in clinical malaria infections has traditionally been attributed in models to random variability, rather than mechanistic disease dynamics. Thus, it is proposed that newly developed models should assume simple immune dynamics that minimally capture mechanistic understandings and avoid over-parameterization and large stochasticity which inaccurately represent unknown disease mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03813-z.

Single-cell sequencing of the small and AT-skewed genome of malaria parasites

Single-cell genomics is a rapidly advancing field; however, most techniques are designed for mammalian cells. We present a single-cell sequencing pipeline for an intracellular parasite, Plasmodium falciparum, with a small genome of extreme base content. Through optimization of a quasi-linear amplification method, we target the parasite genome over contaminants and generate coverage levels allowing detection of minor genetic variants. This work, as well as efforts that build on these findings, will enable detection of parasite heterogeneity contributing to P. falciparum adaptation. Furthermore, this study provides a framework for optimizing single-cell amplification and variant analysis in challenging genomes.

Assessment of Mixed Plasmodium falciparum sera5 Infection in Endemic Burkitt Lymphoma: A Case-Control Study in Malawi

BACKGROUND

Endemic Burkitt lymphoma (eBL) is the most common childhood cancer in Africa and is linked to Plasmodium falciparum (Pf) malaria infection, one of the most common and deadly childhood infections in Africa; however, the role of Pf genetic diversity is unclear. A potential role of Pf genetic diversity in eBL has been suggested by a correlation of age-specific patterns of eBL with the complexity of Pf infection in Ghana, Uganda, and Tanzania, as well as a finding of significantly higher Pf genetic diversity, based on a sensitive molecular barcode assay, in eBL cases than matched controls in Malawi. We examined this hypothesis by measuring diversity in Pf-serine repeat antigen-5 (Pfsera5), an antigenic target of blood-stage immunity to malaria, among 200 eBL cases and 140 controls, all Pf polymerase chain reaction (PCR)-positive, in Malawi.

METHODS

We performed Pfsera5 PCR and sequencing (~3.3 kb over exons II-IV) to determine single or mixed PfSERA5 infection status. The patterns of Pfsera5 PCR positivity, mixed infection, sequence variants, and haplotypes among eBL cases, controls, and combined/pooled were analyzed using frequency tables. The association of mixed Pfsera5 infection with eBL was evaluated using logistic regression, controlling for age, sex, and previously measured Pf genetic diversity.

RESULTS

Pfsera5 PCR was positive in 108 eBL cases and 70 controls. Mixed PfSERA5 infection was detected in 41.7% of eBL cases versus 24.3% of controls; the odds ratio (OR) was 2.18, and the 95% confidence interval (CI) was 1.12-4.26, which remained significant in adjusted results (adjusted odds ratio [aOR] of 2.40, 95% CI of 1.11-5.17). A total of 29 nucleotide variations and 96 haplotypes were identified, but these were unrelated to eBL.

CONCLUSIONS

Our results increase the evidence supporting the hypothesis that infection with mixed Pf infection is increased with eBL and suggest that measuring Pf genetic diversity may provide new insights into the role of Pf infection in eBL.

Extrachromosomal DNA amplicons in antimalarial-resistant Plasmodium falciparum

Extrachromosomal (ec) DNAs are genetic elements that exist separately from the genome. Since ecDNA can carry beneficial genes, they are a powerful adaptive mechanism in cancers and many pathogens. For the first time, we report ecDNA contributing to antimalarial resistance in Plasmodium falciparum, the most virulent human malaria parasite. Using pulse field gel electrophoresis combined with PCR-based copy number analysis, we detected two ecDNA elements that differ in migration and structure. Entrapment in the electrophoresis well and low susceptibility to exonucleases revealed that the biologically relevant ecDNA element is large and complex in structure. Using deep sequencing, we show that ecDNA originates from the chromosome and expansion of an ecDNA-specific sequence may improve its segregation or expression. We speculate that ecDNA is maintained using established mechanisms due to shared characteristics with the mitochondrial genome. Implications of ecDNA discovery in this organism are wide-reaching due to the potential for new strategies to target resistance development.

Dissection of haplotype-specific drug response phenotypes in multiclonal malaria isolates

Natural infections of Plasmodium falciparum, the parasite responsible for the deadliest form of human malaria, often comprise multiple parasite lineages (haplotypes). Multiclonal parasite isolates may exhibit variable phenotypes including different drug susceptibility profiles over time due to the presence of multiple haplotypes. To test this hypothesis, three P. falciparum Cambodian isolates IPC_3445 (MRA-1236), IPC_5202 (MRA-1240) and IPC_6403 (MRA-1285) suspected to be multiclonal were cloned by limiting dilution, and the resulting clones genotyped at 24 highly polymorphic single nucleotide polymorphisms (SNPs). Isolates harbored up to three constituent haplotypes, and exhibited significant variability (p < 0.05) in susceptibility to chloroquine, mefloquine, artemisinin and piperaquine as measured by half maximal drug inhibitory concentration (IC₅₀) assays and parasite survival assays, which measure viability following exposure to pharmacologically relevant concentrations of antimalarial drugs. The IC₅₀ of the most abundant haplotype frequently reflected that of the uncloned parental isolate, suggesting that a single haplotype dominates the antimalarial susceptibility profile and masks the effect of minor frequency haplotypes. These results indicate that phenotypic variability in parasite isolates is often due to the presence of multiple haplotypes. Depending on intended end-use, clinical isolates should be cloned to yield single parasite lineages with well-defined phenotypes and genotypes. The availability of such standardized clonal parasite lineages through NIAID's BEI Resources program will aid research directed towards the development of diagnostics and interventions including drugs against malaria.

Evaluating the Performance of Malaria Genetics for Inferring Changes in Transmission Intensity Using Transmission Modeling

Substantial progress has been made globally to control malaria, however there is a growing need for innovative new tools to ensure continued progress. One approach is to harness genetic sequencing and accompanying methodological approaches as have been used in the control of other infectious diseases. However, to utilize these methodologies for malaria, we first need to extend the methods to capture the complex interactions between parasites, human and vector hosts, and environment, which all impact the level of genetic diversity and relatedness of malaria parasites. We develop an individual-based transmission model to simulate malaria parasite genetics parameterized using estimated relationships between complexity of infection and age from five regions in Uganda and Kenya. We predict that cotransmission and superinfection contribute equally to within-host parasite genetic diversity at 11.5% PCR prevalence, above which superinfections dominate. Finally, we characterize the predictive power of six metrics of parasite genetics for detecting changes in transmission intensity, before grouping them in an ensemble statistical model. The model predicted malaria prevalence with a mean absolute error of 0.055. Different assumptions about the availability of sample metadata were considered, with the most accurate predictions of malaria prevalence made when the clinical status and age of sampled individuals is known. Parasite genetics may provide a novel surveillance tool for estimating the prevalence of malaria in areas in which prevalence surveys are not feasible. However, the findings presented here reinforce the need for patient metadata to be recorded and made available within all future attempts to use parasite genetics for surveillance.

A phased genome based on single sperm sequencing reveals crossover pattern and complex relatedness in tea plants

For diploid organisms that are highly heterozygous, a phased haploid genome can greatly aid in functional genomic, population genetic and breeding studies. Based on the genome sequencing of 135 single sperm cells of the elite tea cultivar 'Fudingdabai', we herein phased the genome of Camellia sinensis, one of the most popular beverage crops worldwide. High-resolution genetic and recombination maps of Fudingdabai were constructed, which revealed that crossover (CO) positions were frequently located in the 5' and 3' ends of annotated genes, while CO distributions across the genome were random. The low CO frequency in tea can be explained by strong CO interference, and CO simulation revealed the proportion of interference insensitive CO ranged from 5.2% to 11.7%. We furthermore developed a method to infer the relatedness between tea accessions and detected complex kinship and genetic signatures of 106 tea accessions. Among them, 59 accessions were closely related with Fudingdabai and 31 of them were first-degree relatives. We additionally identified genes displaying allele specific expression patterns between the two haplotypes of Fudingdabai and genes displaying significantly differential expression levels between Fudingdabai and other haplotypes. These results lay the foundation for further investigation of genetic and epigenetic factors underpinning the regulation of gene expression and provide insights into the evolution of tea plants as well as a valuable genetic resource for future breeding efforts.