Implementing parasite genotyping into national surveillance frameworks: feedback from control programmes and researchers in the Asia-Pacific region

Plasmodium vivax genomic surveillance in the Peruvian Amazon with Pv AmpliSeq assay

BACKGROUND

Plasmodium vivax is the most predominant malaria species in Latin America, constituting 71.5% of malaria cases in 2021. With several countries aiming for malaria elimination, it is crucial to prioritize effectiveness of national control programs by optimizing the utilization of available resources and strategically implementing necessary changes. To support this, there is a need for innovative approaches such as genomic surveillance tools that can investigate changes in transmission intensity, imported cases and sources of reintroduction, and can detect molecular markers associated with drug resistance.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we apply a modified highly-multiplexed deep sequencing assay: Pv AmpliSeq v2 Peru. The tool targets a newly developed 41-SNP Peru barcode for parasite population analysis within Peru, the 33-SNP vivaxGEN-geo panel for country-level classification, and 11 putative drug resistance genes. It was applied to 230 samples from the Peruvian Amazon (2007-2020), generating baseline surveillance data. We observed a heterogenous P. vivax population with high diversity and gene flow in peri-urban areas of Maynas province (Loreto region) with a temporal drift using all SNPs detected by the assay (nSNP = 2909). In comparison, in an indigenous isolated area, the parasite population was genetically differentiated (FST = 0.07-0.09) with moderate diversity and high relatedness between isolates in the community. In a remote border community, a clonal P. vivax cluster was identified, with distinct haplotypes in drug resistant genes and ama1, more similar to Brazilian isolates, likely representing an introduction of P. vivax from Brazil at that time. To test its applicability for Latin America, we evaluated the SNP Peru barcode in P. vivax genomes from the region and demonstrated the capacity to capture local population clustering at within-country level.

CONCLUSIONS/SIGNIFICANCE

Together this data shows that P. vivax transmission is heterogeneous in different settings within the Peruvian Amazon. Genetic analysis is a key component for regional malaria control, offering valuable insights that should be incorporated into routine surveillance.

Cost analyses for malaria molecular diagnosis for research planners in India and beyond

BACKGROUND

Malaria elimination mandates early and accurate diagnosis of infection. Although malaria diagnosis is programmatically dependent on microscopy/RDTs, molecular diagnosis has much better diagnostic accuracy. Higher cost of molecular diagnoses is a recognized challenge for use at the point of care. Because funding is always a recognized constraint, we performed financial cost-analyses of available molecular platforms for better utilization of available budget.

METHODS

Two strategies were applied to deduce the cost per sample. Strategy 1 included recurring components (RC) in minimum pack size, and biologist's time whereas strategy 2 included only RC and non-recurring components and costs are calculated for sample sizes (1-1,000,000) to infer the sample size effect.

RESULTS

Spin column-based manual DNA extraction (US$ 3.93 per sample) is the lowest-cost method, followed by magnetic bead-based automated, semi-automated, and PCI-based manual method. Further, DNA extraction cost per sample via spin column-based manual method and semi-automated method decreases with an increase in sample size up to 10,000. Real-time PCRs are ~ 2-fold more economical than conventional PCR, regardless of sample size.

CONCLUSIONS

This study is the first for malaria to estimate systematic molecular diagnosis financial costs. Kit-based and automated methods may replace conventional DNA extraction and amplification methods for a frugal high-throughput diagnosis.

Genome-based tools for onchocerciasis elimination: utility of the mitochondrial genome for delineating Onchocerca volvulus transmission zones

National programs in Africa have expanded their objectives from control of onchocerciasis (river blindness) as a public health problem to elimination of parasite transmission, motivated by the reduction of Onchocerca volvulus infection prevalence in many African meso- and hyperendemic areas due to mass drug administration of ivermectin (MDAi). Given the large, contiguous hypo-, meso-, and hyperendemic areas, sustainable elimination of onchocerciasis in sub-Saharan Africa requires delineation of geographic boundaries for parasite transmission zones, so that programs can consider the risk of parasite re-introduction through vector or human migration from areas with ongoing transmission when making decisions to stop MDAi. We propose that transmission zone boundaries can be delineated by characterising the parasite genetic population structure within and between potential zones. We analysed whole mitochondrial genome sequences of 189 O. volvulus adults to determine the pattern of genetic similarity across three West African countries: Ghana, Mali, and Côte d'Ivoire. Population genetic structure indicates that parasites from villages near the Pru, Daka, and Black Volta rivers in central Ghana belong to one parasite population, indicating that the assumption that river basins constitute individual transmission zones is not supported by the data. Parasites from Mali and Côte d'Ivoire are genetically distinct from those from Ghana. This research provides the basis for developing tools for elimination programs to delineate transmission zones, to estimate the risk of parasite re-introduction via vector or human movement when intervention is stopped in one area while transmission is ongoing in others, to identify the origin of infections detected post-treatment cessation, and to investigate whether persisting prevalence despite ongoing interventions in one area is due to parasites imported from others.

Molecular markers for malaria genetic epidemiology: progress and pitfalls

Over recent years, progress in molecular markers for genotyping malaria parasites has enabled informative studies of epidemiology and transmission dynamics. Results have highlighted the value of these tools for surveillance to support malaria control and elimination strategies. There are many different types and panels of markers available for malaria parasite genotyping, and for end users, the nuances of these markers with respect to 'use case', resolution, and accuracy, are not well defined. This review clarifies issues surrounding different molecular markers and their application to malaria control and elimination. We describe available marker panels, use cases, implications for different transmission settings, limitations, access, cost, and data accuracy. The information provided can be used as a guide for molecular epidemiology and surveillance of malaria.

Genomic analysis of Plasmodium vivax describes patterns of connectivity and putative drivers of adaptation in Ethiopia

Ethiopia has the greatest burden of Plasmodium vivax in Africa, but little is known about the epidemiological landscape of parasites across the country. We analysed the genomic diversity of 137 P. vivax isolates collected nine Ethiopian districts from 2012 to 2016. Signatures of selection were detected by cross-country comparisons with isolates from Thailand (n = 104) and Indonesia (n = 111), representing regions with low and high chloroquine resistance respectively. 26% (35/137) of Ethiopian infections were polyclonal, and 48.5% (17/35) of these comprised highly related clones (within-host identity-by-descent > 25%), indicating frequent co-transmission and superinfection. Parasite gene flow between districts could not be explained entirely by geographic distance, with economic and cultural factors hypothesised to have an impact on connectivity. Amplification of the duffy binding protein gene (pvdbp1) was prevalent across all districts (16-75%). Cross-population haplotype homozygosity revealed positive selection in a region proximal to the putative chloroquine resistance transporter gene (pvcrt-o). An S25P variant in amino acid transporter 1 (pvaat1), whose homologue has recently been implicated in P. falciparum chloroquine resistance evolution, was prevalent in Ethiopia (96%) but not Thailand or Indonesia (35-53%). The genomic architecture in Ethiopia highlights circulating variants of potential public health concern in an endemic setting with evidence of stable transmission.

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

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

A new Plasmodium vivax reference genome for South American isolates

BACKGROUND

Plasmodium vivax is the second most important cause of human malaria worldwide, and accounts for the majority of malaria cases in South America. A high-quality reference genome exists for Papua Indonesia (PvP01) and Thailand (PvW1), but is lacking for South America. A reference genome specifically for South America would be beneficial though, as P. vivax is a genetically diverse parasite with geographical clustering.

RESULTS

This study presents a new high-quality assembly of a South American P. vivax isolate, referred to as PvPAM (P. vivax Peruvian AMazon). The genome was obtained from a low input patient sample from the Peruvian Amazon and sequenced using PacBio technology, resulting in a highly complete assembly with 6497 functional genes. Telomeric ends were present in 17 out of 28 chromosomal ends, and additional (sub)telomeric regions are present in 12 unassigned contigs. A comparison of multigene families between PvPAM and the PvP01 genome revealed remarkable variation in vir genes, and the presence of merozoite surface proteins (MSP) 3.6 and 3.7. Three dhfr and dhps drug resistance associated mutations are present in PvPAM, similar to those found in other Peruvian isolates. Mapping of publicly available South American whole genome sequencing (WGS) data to PvPAM resulted in significantly fewer variants and truncated reads compared to the use of PvP01 or PvW1 as reference genomes. To minimize the number of core genome variants in non-South American samples, PvW1 is most suited for Southeast Asian isolates, both PvPAM and PvW1 are suited for South Asian isolates, and PvPAM is recommended for African isolates. Interestingly, non-South American samples still contained the least subtelomeric variants when mapped to PvPAM, indicating high quality of the PvPAM subtelomeric regions.

CONCLUSIONS

Our findings show that the PvPAM reference genome more accurately represents South American P. vivax isolates in comparison to PvP01 and PvW1. In addition, PvPAM has a high level of completeness, and contains a similar number of annotated genes as PvP01 or PvW1. The PvPAM genome therefore will be a valuable resource to improve future genomic analyses on P. vivax isolates from the South American continent.

Procedure for Handling and Storage of Onchocerca volvulus Microfilariae Obtained from Skin Snips for Downstream Genetic Work

WHO and endemic countries target elimination of transmission of Onchocerca volvulus, the parasite causing onchocerciasis. Population genetic analysis of O. volvulus may provide data to improve the evidence base for decisions on when, where, and for how long to deploy which interventions and post-intervention surveillance to achieve elimination. Development of necessary methods and tools requires parasites suitable for genetic analysis. Based on our experience with microfilariae obtained from different collaborators, we developed a microfilariae transfer procedure for large-scale studies in the Democratic Republic of Congo (DRC) comparing safety and efficacy of ivermectin, the mainstay of current onchocerciasis elimination strategies, and moxidectin, a new drug. This procedure is designed to increase the percentage of microfilariae in skin snips suitable for genetic analysis, improve assignment to metadata, and minimize time and materials needed by the researchers collecting the microfilariae. Among 664 microfilariae from South Sudan, 35.7% and 39.5% failed the mitochondrial and nuclear qPCR assay. Among the 576 microfilariae from DRC, 16.0% and 16.7% failed these assays, respectively. This difference may not only be related to the microfilariae transfer procedure but also to other factors, notably the ethanol concentration in the tubes in which microfilariae were stored (64% vs. ≥75%).

Molecular surveillance of Plasmodium falciparum drug-resistance markers in Vietnam using multiplex amplicon sequencing (2000-2016)

Emergence and spread of Plasmodium falciparum resistance to artemisinin-based combination therapies (ACT) is a major challenge for Greater Mekong Subregion countries in their goal to eliminate malaria by 2030. Tools to efficiently monitor drug resistance beyond resource-demanding therapeutic efficacy studies are necessary. A custom multiplex amplicon sequencing assay based on Illumina technology was designed to target the marker of partial resistance to artemisinin (K13), five candidate modulators of artemisinin resistance, the marker of resistance to chloroquine (crt), and four neutral microsatellite loci. The assay was used to genotype 635 P. falciparum-positive blood samples collected across seven provinces of Vietnam and one of Cambodia between 2000 and 2016. Markers of resistance to artemisinin partner-drugs piperaquine (copy number of plasmepsin-2) and mefloquine (copy number of multidrug-resistance 1) were determined by qPCR. Parasite population structure was further assessed using a 101-SNP barcode. Validated mutations of artemisinin partial resistance in K13 were found in 48.1% of samples, first detection was in 2000, and by 2015 prevalence overcame > 50% in Central Highlands and Binh Phuoc province. K13-C580Y variant became predominant country-wide, quickly replacing an outbreak of K13-I543T in Central Highlands. Mutations in candidate artemisinin resistance modulator genes paralleled the trends of K13 mutants, whereas resistance to piperaquine and mefloquine remained low (≈ 10%) by 2015-2016. Genomic tools applied to malaria surveillance generate comprehensive information on dynamics of drug resistance and population structure and reflect drug efficacy profiles from in vivo studies.

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

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

minSNPs: an R package for the derivation of resolution-optimised SNP sets from microbial genomic data

Here, we present the R package, minSNPs. This is a re-development of a previously described Java application named Minimum SNPs. MinSNPs assembles resolution-optimised sets of single nucleotide polymorphisms (SNPs) from sequence alignments such as genome-wide orthologous SNP matrices. MinSNPs can derive sets of SNPs optimised for discriminating any user-defined combination of sequences from all others. Alternatively, SNP sets may be optimised to determine all sequences from all other sequences, i.e., to maximise diversity. MinSNPs encompasses functions that facilitate rapid and flexible SNP mining, and clear and comprehensive presentation of the results. The minSNPs' running time scales in a linear fashion with input data volume and the numbers of SNPs and SNPs sets specified in the output. MinSNPs was tested using a previously reported orthologous SNP matrix of Staphylococcus aureus and an orthologous SNP matrix of 3,279 genomes with 164,335 SNPs assembled from four S. aureus short read genomic data sets. MinSNPs was shown to be effective for deriving discriminatory SNP sets for potential surveillance targets and in identifying SNP sets optimised to discriminate isolates from different clonal complexes. MinSNPs was also tested with a large Plasmodium vivax orthologous SNP matrix. A set of five SNPs was derived that reliably indicated the country of origin within three south-east Asian countries. In summary, we report the capacity to assemble comprehensive SNP matrices that effectively capture microbial genomic diversity, and to rapidly and flexibly mine these entities for optimised marker sets.

Lineage-informative microhaplotypes for spatio-temporal surveillance of Plasmodium vivax malaria parasites

Challenges in understanding the origin of recurrent Plasmodium vivax infections constrains the surveillance of antimalarial efficacy and transmission of this neglected parasite. Recurrent infections within an individual may arise from activation of dormant liver stages (relapse), blood-stage treatment failure (recrudescence) or new inoculations (reinfection). Molecular inference of familial relatedness (identity-by-descent or IBD) based on whole genome sequence data, together with analysis of the intervals between parasitaemic episodes ("time-to-event" analysis), can help resolve the probable origin of recurrences. Whole genome sequencing of predominantly low-density P. vivax infections is challenging, so an accurate and scalable genotyping method to determine the origins of recurrent parasitaemia would be of significant benefit. We have developed a P. vivax genome-wide informatics pipeline to select specific microhaplotype panels that can capture IBD within small, amplifiable segments of the genome. Using a global set of 615 P. vivax genomes, we derived a panel of 100 microhaplotypes, each comprising 3-10 high frequency SNPs within <200 bp sequence windows. This panel exhibits high diversity in regions of the Asia-Pacific, Latin America and the horn of Africa (median HE = 0.70-0.81) and it captured 89% (273/307) of the polyclonal infections detected with genome-wide datasets. Using data simulations, we demonstrate lower error in estimating pairwise IBD using microhaplotypes, relative to traditional biallelic SNP barcodes. Our panel exhibited high accuracy in predicting the country of origin (median Matthew's correlation coefficient >0.9 in 90% countries tested) and it also captured local infection outbreak and bottlenecking events. The informatics pipeline is available open-source and yields microhaplotypes that can be readily transferred to high-throughput amplicon sequencing assays for surveillance in malaria-endemic regions.

Malaria Molecular Surveillance in the Peruvian Amazon with a Novel Highly Multiplexed Plasmodium falciparum AmpliSeq Assay

Molecular surveillance for malaria has great potential to support national malaria control programs (NMCPs). To bridge the gap between research and implementation, several applications (use cases) have been identified to align research, technology development, and public health efforts. For implementation at NMCPs, there is an urgent need for feasible and cost-effective tools. We designed a new highly multiplexed deep sequencing assay (Pf AmpliSeq), which is compatible with benchtop sequencers, that allows high-accuracy sequencing with higher coverage and lower cost than whole-genome sequencing (WGS), targeting genomic regions of interest. The novelty of the assay is its high number of targets multiplexed into one easy workflow, combining population genetic markers with 13 nearly full-length resistance genes, which is applicable for many different use cases. We provide the first proof of principle for hrp2 and hrp3 deletion detection using amplicon sequencing. Initial sequence data processing can be performed automatically, and subsequent variant analysis requires minimal bioinformatic skills using any tabulated data analysis program. The assay was validated using a retrospective sample collection (n = 254) from the Peruvian Amazon between 2003 and 2018. By combining phenotypic markers and a within-country 28-single-nucleotide-polymorphism (SNP) barcode, we were able to distinguish different lineages with multiple resistance haplotypes (in dhfr, dhps, crt and mdr1) and hrp2 and hrp3 deletions, which have been increasing in recent years. We found no evidence to suggest the emergence of artemisinin (ART) resistance in Peru. These findings indicate a parasite population that is under drug pressure but is susceptible to current antimalarials and demonstrate the added value of a highly multiplexed molecular tool to inform malaria strategies and surveillance systems. IMPORTANCE While the power of next-generation sequencing technologies to inform and guide malaria control programs has become broadly recognized, the integration of genomic data for operational incorporation into malaria surveillance remains a challenge in most countries where malaria is endemic. The main obstacles include limited infrastructure, limited access to high-throughput sequencing facilities, and the need for local capacity to run an in-country analysis of genomes at a large-enough scale to be informative for surveillance. In addition, there is a lack of standardized laboratory protocols and automated analysis pipelines to generate reproducible and timely results useful for relevant stakeholders. With our standardized laboratory and bioinformatic workflow, malaria genetic surveillance data can be readily generated by surveillance researchers and malaria control programs in countries of endemicity, increasing ownership and ensuring timely results for informed decision- and policy-making.

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.

A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.

Genomic approaches for monitoring transmission dynamics of malaria: A case for malaria molecular surveillance in Sub-Saharan Africa

Transmission dynamics is an important indicator for malaria control and elimination. As we move closer to eliminating malaria in Sub-Saharan Africa (sSA), transmission indices with higher resolution (genomic approaches) will complement our current measurements of transmission. Most of the present programmatic knowledge of malaria transmission patterns are derived from assessments of epidemiologic and clinical data, such as case counts, parasitological estimates of parasite prevalence, and Entomological Inoculation Rates (EIR). However, to eliminate malaria from endemic areas, we need to track changes in the parasite population and how they will impact transmission. This is made possible through the evolving field of genomics and genetics, as well as the development of tools for more in-depth studies on the diversity of parasites and the complexity of infections, among other topics. If malaria elimination is to be achieved globally, country-specific elimination activities should be supported by parasite genomic data from regularly collected blood samples for diagnosis, surveillance and possibly from other programmatic interventions. This presents a unique opportunity to track the spread of malaria parasites and shed additional light on intervention efficacy. In this review, various genetic techniques are highlighted along with their significance for an enhanced understanding of transmission patterns in distinct topological settings throughout Sub-Saharan Africa. The importance of these methods and their limitations in malaria surveillance to guide control and elimination strategies, are explored.

The many definitions of multiplicity of infection

The presence of multiple genetically different pathogenic variants within the same individual host is common in infectious diseases. Although this is neglected in some diseases, it is well recognized in others like malaria, where it is typically referred to as multiplicity of infection (MOI) or complexity of infection (COI). In malaria, with the advent of molecular surveillance, data is increasingly being available with enough resolution to capture MOI and integrate it into molecular surveillance strategies. The distribution of MOI on the population level scales with transmission intensities, while MOI on the individual level is a confounding factor when monitoring haplotypes of particular interests, e.g., those associated with drug-resistance. Particularly, in high-transmission areas, MOI leads to a discrepancy between the likelihood of a haplotype being observed in an infection (prevalence) and its abundance in the pathogen population (frequency). Despite its importance, MOI is not universally defined. Competing definitions vary from verbal ones to those based on concise statistical frameworks. Heuristic approaches to MOI are popular, although they do not mine the full potential of available data and are typically biased, potentially leading to misinferences. We introduce a formal statistical framework and suggest a concise definition of MOI and its distribution on the host-population level. We show how it relates to alternative definitions such as the number of distinct haplotypes within an infection or the maximum number of alleles detectable across a set of genetic markers. It is shown how alternatives can be derived from the general framework. Different statistical methods to estimate the distribution of MOI and pathogenic variants at the population level are discussed. The estimates can be used as plug-ins to reconstruct the most probable MOI of an infection and set of infecting haplotypes in individual infections. Furthermore, the relation between prevalence of pathogenic variants and their frequency (relative abundance) in the pathogen population in the context of MOI is clarified, with particular regard to seasonality in transmission intensities. The framework introduced here helps to guide the correct interpretation of results emerging from different definitions of MOI. Especially, it excels comparisons between studies based on different analytical methods.

Novel highly-multiplexed AmpliSeq targeted assay for Plasmodium vivax genetic surveillance use cases at multiple geographical scales

Although the power of genetic surveillance tools has been acknowledged widely, there is an urgent need in malaria endemic countries for feasible and cost-effective tools to implement in national malaria control programs (NMCPs) that can generate evidence to guide malaria control and elimination strategies, especially in the case of Plasmodium vivax. Several genetic surveillance applications (‘use cases’) have been identified to align research, technology development, and public health efforts, requiring different types of molecular markers. Here we present a new highly-multiplexed deep sequencing assay (Pv AmpliSeq). The assay targets the 33-SNP vivaxGEN-geo panel for country-level classification, and a newly designed 42-SNP within-country barcode for analysis of parasite dynamics in Vietnam and 11 putative drug resistance genes in a highly multiplexed NGS protocol with easy workflow, applicable for many different genetic surveillance use cases. The Pv AmpliSeq assay was validated using: 1) isolates from travelers and migrants in Belgium, and 2) routine collections of the national malaria control program at sentinel sites in Vietnam. The assay targets 229 amplicons and achieved a high depth of coverage (mean 595.7 ± 481) and high accuracy (mean error-rate of 0.013 ± 0.007). P. vivax parasites could be characterized from dried blood spots with a minimum of 5 parasites/µL and 10% of minority-clones. The assay achieved good spatial specificity for between-country prediction of origin using the 33-SNP vivaxGEN-geo panel that targets rare alleles specific for certain countries and regions. A high resolution for within-country diversity in Vietnam was achieved using the designed 42-SNP within-country barcode that targets common alleles (median MAF 0.34, range 0.01-0.49. Many variants were detected in (putative) drug resistance genes, with different predominant haplotypes in the pvmdr1 and pvcrt genes in different provinces in Vietnam. The capacity of the assay for high resolution identity-by-descent (IBD) analysis was demonstrated and identified a high rate of shared ancestry within Gia Lai Province in the Central Highlands of Vietnam, as well as between the coastal province of Binh Thuan and Lam Dong. Our approach performed well in geographically differentiating isolates at multiple spatial scales, detecting variants in putative resistance genes, and can be easily adjusted to suit the needs in other settings in a country or region. We prioritize making this tool available to researchers and NMCPs in endemic countries to increase ownership and ensure data usage for decision-making and malaria policy.

Heterogeneity in prevalence of subclinical Plasmodium falciparum and Plasmodium vivax infections but no parasite genomic clustering in the Chittagong Hill Tracts, Bangladesh

BACKGROUND

Malaria remains endemic in Bangladesh, with the majority of cases occurring in forested, mountainous region in the Chittagong Hill Tracts (CHT). This area is home to Bengali and diverse groups of indigenous people (Pahari) residing largely in mono-ethnic villages.

METHODS

1002 individuals of the 9 most prominent Pahari and the Bengali population were randomly selected and screened by RDT and qPCR. Parasites were genotyped by msp2 and deep sequencing of 5 amplicons (ama1-D3, cpmp, cpp, csp, and msp7) for Plasmodium falciparum (n = 20), and by microsatellite (MS) typing of ten loci and amplicon sequencing of msp1 for Plasmodium vivax (n = 21). Population structure was analysed using STRUCTURE software. Identity-by-state (IBS) was calculated as a measure of parasite relatedness and used to generate relatedness networks.

RESULTS

The prevalence of P. falciparum and P. vivax infection was 0.7% by RDT (P. falciparum 6/1002; P. vivax 0/1002, mixed: 1/1002) and 4% by qPCR (P. falciparum 21/1002; P. vivax 16/1002, mixed: 5/1002). Infections were highly clustered, with 64% (27/42) of infections occurring in only two Pahari groups, the Khumi and Mro. Diversity was high; expected heterozygosity was 0.93 for P. falciparum and 0.81 for P. vivax. 85.7% (18/21) of P. vivax and 25% (5/20) of P. falciparum infections were polyclonal. No population structure was evident for either species, suggesting high transmission and gene flow among Pahari groups.

CONCLUSIONS

High subclinical infection prevalence and genetic diversity mirror ongoing transmission. Control activities should be specifically directed to Pahari groups at greatest risk.

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.

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.

Distinguishing gene flow between malaria parasite populations

Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report examines the use of population-level summaries of genetic divergence (F_ST) and relatedness (identity-by-descent) to distinguish levels of gene flow between malaria populations, focused on field-relevant questions about data size, sampling, and interpretability of observations from genomic surveillance studies. To do this, we use P. falciparum whole genome sequence data and simulated sequence data approximating malaria populations evolving under different current and historical epidemiological conditions. We employ mobile-phone associated mobility data to estimate parasite migration rates over different spatial scales and use this to inform our analysis. This analysis underscores the complementary nature of divergence- and relatedness-based metrics for distinguishing gene flow over different temporal and spatial scales and characterizes the data requirements for using these metrics in different contexts. Our results have implications for the design and implementation of malaria genomic surveillance studies.

Malaria is a leading infectious cause of illness and death worldwide. Understanding how malaria parasites are spread between different geographic locations can provide useful information for disease control efforts. Examples include identifying source locations for imported infections in lower-incidence “sink” locations and delineating the routes over which drug-resistant malaria strains disperse across geographic space. Genomic surveillance methods use geolocated genetic sequence data from malaria infections to estimate gene flow and connectivity between parasites populations in different locations. This approach has yielded important insights into patterns of connectivity between malaria populations over local, national, and global scales. However, there are multiple unresolved questions about the design and interpretation of these studies. This study evaluates how much data is needed to distinguish different levels of gene flow between parasite populations (“Are the malaria populations in locations i and j linked by higher or lower connectivity than those in locations k and l?”). We examine data size requirements (including the number of genetic markers and number of individual infections analyzed) for this important, implementation-relevant task across multiple epidemiological scenarios, providing practical guidance for the design and interpretation of similar studies.

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.

High Proportion of Genome-Wide Homology and Increased Pretreatment pvcrt Levels in Plasmodium vivax Late Recurrences: a Chloroquine Therapeutic Efficacy Study

Chloroquine (CQ) is the first-line treatment for Plasmodium vivax malaria in most countries where malaria is endemic. Monitoring P. vivax CQ resistance (CQR) is critical but remains challenged by the difficulty to distinguish real treatment failure from reinfection or liver relapse. The therapeutic efficacy of CQ against uncomplicated P. vivax malaria was evaluated in Gia Lai Province, Vietnam. Sixty-seven patients were enrolled and followed for 42 days using microscopy and quantitative PCR. Adequate clinical and parasitological response (ACPR) was 100% (66/66) on day 28 but 75.4% (49/65) on day 42. Eighteen recurrences (27.7%) were detected, with a median time to recurrence of 42 days (interquartile range [IQR], 35 to 42) and blood CQ concentration of <100 ng/ml. Primary infections leading to recurrence occurred in younger individuals (median age for ACPR = 25 years [IQR, 20 to 28]; recurrences = 18 [16 to 21]; P = 0.002) had a longer parasite clearance time (PCT for ACPR = 47.5 h [IQR, 36.2 to 59.8 h]; recurrences = 54.2 [48.4 to 62.0]; P = 0.035) and higher pvcrt gene expression (median relative expression ratio for ACPR = 0.09 [IQR, 0.05 to 0.22]; recurrences = 0.20 [0.15 to 0.56]; P = 0.002), but showed no differences in ex vivo CQ sensitivity. Parasite genotyping by microsatellites, single nucleotide polymorphism (SNP) barcoding, and whole-genome sequencing (WGS) identified a majority of homologous recurrences, with 80% (8/10) showing >98% identity by descent to paired day 0 samples. This study shows that CQ remained largely efficacious to treat P. vivax in Gia Lai; i.e., recurrences occurred late (>day 28) and in the presence of low blood CQ concentrations. However, the combination of both WGS and gene expression analysis (pvcrt) data with clinical data (PCT) allowed us to identify potential emergence of low-grade CQR, which should be closely monitored. (This study has been registered at ClinicalTrials.gov under identifier NCT02610686.).

Malaria in the 'Omics Era'

Genomics has revolutionised the study of the biology of parasitic diseases. The first Eukaryotic parasite to have its genome sequenced was the malaria parasite Plasmodium falciparum. Since then, Plasmodium genomics has continued to lead the way in the study of the genome biology of parasites, both in breadth—the number of Plasmodium species’ genomes sequenced—and in depth—massive-scale genome re-sequencing of several key species. Here, we review some of the insights into the biology, evolution and population genetics of Plasmodium gained from genome sequencing, and look at potential new avenues in the future genome-scale study of its biology.

The changing epidemiology of Plasmodium vivax: Insights from conventional and novel surveillance tools

Sarah Auburn and co-authors discuss the unique biology and epidemiology of P. vivax and current evidence on conventional and new approaches to surveillance.