Genomic structure and diversity of Plasmodium falciparum in Southeast Asia reveal recent parasite migration patterns

Multi-omics profiling of mouse polycystic kidney disease progression at a single cell resolution

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease and causes significant morbidity, ultimately leading to end-stage kidney disease. PKD pathogenesis is characterized by complex and dynamic alterations in multiple cell types during disease progression, hampering a deeper understanding of disease mechanism and the development of therapeutic approaches. Here, we generate a single nucleus multimodal atlas of an orthologous mouse PKD model at early, mid and late timepoints, consisting of 125,434 single-nucleus transcriptomic and epigenetic multiomes. We catalogue differentially expressed genes and activated epigenetic regions in each cell type during PKD progression, characterizing cell-type-specific responses to Pkd1 deletion. We describe heterogeneous, atypical collecting duct cells as well as proximal tubular cells that constitute cyst epithelia in PKD. The transcriptional regulation of the cyst lining cell marker GPRC5A is conserved between mouse and human PKD cystic epithelia, suggesting shared gene regulatory pathways. Our single nucleus multiomic analysis of mouse PKD provides a foundation to understand the earliest changes molecular deregulation in a mouse model of PKD at a single-cell resolution.

Variation in spatial population structure in the Anopheles gambiae species complex

Anopheles gambiae, Anopheles coluzzii , and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of these closely related species, including the extent to which populations are connected by gene flow, is essential for understanding how vector control implemented in one location might indirectly affect vector populations in other locations. Here, we assessed the population structure of each species based on whole-genome sequences from the third phase of the Anopheles gambiae 1000 Genomes Project. The data set included single nucleotide polymorphisms from whole genomes of 2,242 individual mosquitoes sampled from 119 locations across 19 African countries. We found that A. gambiae sampled from several countries in West and Central Africa showed low genetic differentiation from each other according to principal components analysis (PCA) and ADMIXTURE modeling. Using Estimated Effective Migration Surfaces (EEMS), we showed that this low genetic differentiation indicates high effective migration rates for A. gambiae across this region. Outside of this region, we found six groups of sampling locations from Central, East, and Southern Africa for which A. gambiae showed higher genetic differentiation, and lower effective migration rates, between each other and the West/Central Africa group. These results indicate that the barriers to and corridors for migration between populations of A. gambiae differ across the geographical range of this malaria vector species. Using the same methods, we found higher genetic differentiation and lower migration rates between populations of A. coluzzii in West and Central Africa than for A. gambiae in the same region. On the other hand, we found lower genetic differentiation and higher migration rates between populations of A. arabiensis in Tanzania, compared to A. gambiae in the same region. These differences between A. gambiae, A. coluzzii , and A. arabiensis indicate that migration barriers and corridors may vary between species, even for very closely related species. Overall, our results demonstrate that migration rates vary both between and within species of Anopheles mosquitoes, presumably based on species-specific responses to the ecological or environmental conditions that may impede or facilitate migration, and the geographical patterns of these conditions across the landscape. Together with previous findings, this study provides robust evidence that migration rates between populations of malaria vectors depend on the ecological context, which should be considered when planning surveillance of vector populations, monitoring for insecticide resistance, and evaluating interventions.

Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in Plasmodium falciparum

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is being used in Plasmodium population genomics to estimate genetic relatedness, effective population size ( N e ) , population structure, and positive selection. However, a comprehensive evaluation of IBD segment detection tools is lacking for species with high rates of recombination. Here, we employ genetic simulations reflecting P. falciparum's high recombination rate and decreasing N e to benchmark IBD callers, including probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD), using genealogy-based true IBD and downstream inference of population characteristics. Our findings reveal that low marker density per genetic unit, related to high recombination rates relative to mutation rates, significantly affects the quality of detected IBD segments. Most IBD callers suffer from high false negative rates, which can be improved with parameter optimization. Optimized parameters allow for more accurate capture of selection signals and population structure, but hmmIBD is unique in providing less biased estimates of N e . Empirical data subsampled from the MalariaGEN Pf7 database, representing different transmission settings, confirmed these patterns. We conclude that the detection of IBD in high-recombining species requires context-specific evaluation and parameter optimization and recommend that hmmIBD be used for quality-sensitive analysis, such as estimation of N e in these species.

Study protocol: improving response to malaria in the Amazon through identification of inter-community networks and human mobility in border regions of Ecuador, Peru and Brazil

INTRODUCTION

Understanding human mobility's role in malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission.

METHODS

We measure community connectivity across the study area using a respondent driven sampling design among key informants who are at least 18 years of age. 45 initial communities will be selected: 10 in Brazil, 10 in Ecuador and 25 in Peru. Participants will be recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses will be ranked and the 2-3 most connected communities will then be selected and surveyed. This process will be repeated for a third round of data collection. Community network matrices will be linked with each country's malaria surveillance system to test the effects of mobility on disease risk.

ETHICS AND DISSEMINATION

This study protocol has been approved by the institutional review boards of Duke University (USA), Universidad San Francisco de Quito (Ecuador), Universidad Peruana Cayetano Heredia (Peru) and Universidade Federal Minas Gerais (Brazil). Results will be disseminated in communities by the end of the study.

Genomics reveals heterogeneous Plasmodium falciparum transmission and selection signals in Zambia

BACKGROUND

Genomic surveillance is crucial for monitoring malaria transmission and understanding parasite adaptation to interventions. Zambia lacks prior nationwide efforts in malaria genomic surveillance among African countries.

METHODS

We conducted genomic surveillance of Plasmodium falciparum parasites from the 2018 Malaria Indicator Survey in Zambia, a nationally representative household survey of children under five years of age. We whole-genome sequenced and analyzed 241 P. falciparum genomes from regions with varying levels of malaria transmission across Zambia and estimated genetic metrics that are informative about transmission intensity, genetic relatedness between parasites, and selection.

RESULTS

We provide genomic evidence of widespread within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in Zambia. Our analysis reveals country-level clustering of parasites from Zambia and neighboring regions, with distinct separation in West Africa. Within Zambia, identity by descent (IBD) relatedness analysis uncovers local spatial clustering and rare cases of long-distance sharing of closely related parasite pairs. Genomic regions with large shared IBD segments and strong positive selection signatures implicate genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Furthermore, differences in selection signatures, including drug resistance loci, are observed between eastern and western Zambian parasite populations, suggesting variable transmission intensity and ongoing drug pressure.

CONCLUSIONS

Our findings enhance our understanding of nationwide P. falciparum transmission in Zambia, establishing a baseline for analyzing parasite genetic metrics as they vary over time and space. These insights highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.

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.

Genomics reveals heterogeneous Plasmodium falciparum transmission and population differentiation in Zambia and bordering countries

Genomic surveillance plays a critical role in monitoring malaria transmission and understanding how the parasite adapts in response to interventions. We conducted genomic surveillance of malaria by sequencing 241 Plasmodium falciparum genomes from regions with varying levels of malaria transmission across Zambia. We found genomic evidence of high levels of within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in the country. We identified country-level clustering of parasites from Zambia and neighboring countries, and distinct clustering of parasites from West Africa. Within Zambia, our identity by descent (IBD) relatedness analysis uncovered spatial clustering of closely related parasite pairs at the local level and rare cases of long-distance sharing. Genomic regions with large shared IBD segments and strong positive selection signatures identified genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Together, our findings enhance our understanding of P. falciparum transmission nationwide in Zambia and highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.

Genomic complexity of parasites and vectors challenges malaria control in Southeast Asia

Southeast Asia is a uniquely complex region of malaria transmission that maintains an astounding level of species diversity among potential malaria vectors and also generates drug-resistant and quickly diverging populations of malaria parasites. All five human malaria species circulate in Southeast Asia with over 50 Anopheles species that vary in their ability to transmit these pathogens. The intricate relationships of these parasites and vectors are not well-understood. Human activity in Southeast Asian countries has created an increasingly fragmented landscape, bringing humans and mosquitoes into more frequent contact, sustaining malaria transmission in a region where few control tools are effective. Genomic shifts at the species, population, and individual level in parasites and vectors introduce variation that has produced drug- and insecticide resistance. The goal of this review is to highlight genomic studies of Southeast Asian malaria parasites and vectors that demonstrate how diversity in these organisms presents unique challenges and opportunities for global malaria control and eradication efforts.

Network Profile: Improving Response to Malaria in the Amazon through Identification of Inter-Community Networks and Human Mobility in Border Regions of Ecuador, Peru, and Brazil

Objectives

Understanding human mobility's role on malaria transmission is critical to successful control and elimination. However, common approaches to measuring mobility are ill-equipped for remote regions such as the Amazon. This study develops a network survey to quantify the effect of community connectivity and mobility on malaria transmission.

Design

A community-level network survey.

Setting

We collect data on community connectivity along three river systems in the Amazon basin: the Pastaza river corridor spanning the Ecuador-Peru border; and the Amazon and Javari river corridors spanning the Brazil-Peru border.

Participants

We interviewed key informants in Brazil, Ecuador, and Peru, including from indigenous communities: Shuar, Achuar, Shiwiar, Kichwa, Ticuna, and Yagua. Key informants are at least 18 years of age and are considered community leaders.

Primary outcome

Weekly, community-level malaria incidence during the study period.

Methods

We measure community connectivity across the study area using a respondent driven sampling design. Forty-five communities were initially selected: 10 in Brazil, 10 in Ecuador, and 25 in Peru. Participants were recruited in each initial node and administered a survey to obtain data on each community's mobility patterns. Survey responses were ranked and the 2-3 most connected communities were then selected and surveyed. This process was repeated for a third round of data collection. Community network matrices will be linked with eadch country's malaria surveillance system to test the effects of mobility on disease risk.

Findings

To date, 586 key informants were surveyed from 126 communities along the Pastaza river corridor. Data collection along the Amazon and Javari river corridors is ongoing. Initial results indicate that network sampling is a superior method to delineate migration flows between communities.

Conclusions

Our study provides measures of mobility and connectivity in rural settings where traditional approaches are insufficient, and will allow us to understand mobility's effect on malaria transmission.

Multiplexed ddPCR-amplicon sequencing reveals isolated Plasmodium falciparum populations amenable to local elimination in Zanzibar, Tanzania

Zanzibar has made significant progress toward malaria elimination, but recent stagnation requires novel approaches. We developed a highly multiplexed droplet digital PCR (ddPCR)-based amplicon sequencing method targeting 35 microhaplotypes and drug-resistance loci, and successfully sequenced 290 samples from five districts covering both main islands. Here, we elucidate fine-scale Plasmodium falciparum population structure and infer relatedness and connectivity of infections using an identity-by-descent (IBD) approach. Despite high genetic diversity, we observe pronounced fine-scale spatial and temporal parasite genetic structure. Clusters of near-clonal infections on Pemba indicate persistent local transmission with limited parasite importation, presenting an opportunity for local elimination efforts. Furthermore, we observe an admixed parasite population on Unguja and detect a substantial fraction (2.9%) of significantly related infection pairs between Zanzibar and the mainland, suggesting recent importation. Our study provides a high-resolution view of parasite genetic structure across the Zanzibar archipelago and provides actionable insights for prioritizing malaria elimination efforts.

Resolving drug selection and migration in an inbred South American Plasmodium falciparum population with identity-by-descent analysis

The human malaria parasite Plasmodium falciparum is globally widespread, but its prevalence varies significantly between and even within countries. Most population genetic studies in P. falciparum focus on regions of high transmission where parasite populations are large and genetically diverse, such as sub-Saharan Africa. Understanding population dynamics in low transmission settings, however, is of particular importance as these are often where drug resistance first evolves. Here, we use the Pacific Coast of Colombia and Ecuador as a model for understanding the population structure and evolution of Plasmodium parasites in small populations harboring less genetic diversity. The combination of low transmission and a high proportion of monoclonal infections means there are few outcrossing events and clonal lineages persist for long periods of time. Yet despite this, the population is evolutionarily labile and has successfully adapted to changes in drug regime. Using newly sequenced whole genomes, we measure relatedness between 166 parasites, calculated as identity by descent (IBD), and find 17 distinct but highly related clonal lineages, six of which have persisted in the region for at least a decade. This inbred population structure is captured in more detail with IBD than with other common population structure analyses like PCA, ADMIXTURE, and distance-based trees. We additionally use patterns of intra-chromosomal IBD and an analysis of haplotypic variation to explore past selection events in the region. Two genes associated with chloroquine resistance, crt and aat1, show evidence of hard selective sweeps, while selection appears soft and/or incomplete at three other key resistance loci (dhps, mdr1, and dhfr). Overall, this work highlights the strength of IBD analyses for studying parasite population structure and resistance evolution in regions of low transmission, and emphasizes that drug resistance can evolve and spread in small populations, as will occur in any region nearing malaria elimination.

Genetic diversity in the transmission-blocking vaccine candidate Plasmodium vivax gametocyte protein Pvs230 from the China-Myanmar border area and central Myanmar

BACKGROUND

Sexual stage surface antigens are potential targets of transmission-blocking vaccines (TBVs). The gametocyte and gamete surface antigen P230, a leading TBV candidate, is critical for red blood cell binding during exflagellation and subsequent oocyst development. Here, the genetic diversity of Pvs230 was studied in Plasmodium vivax parasite isolates from the China-Myanmar border (CMB) and central Myanmar.

METHODS

Plasmodium vivax isolates were collected in clinics from malaria-endemic areas of the CMB (143 samples) and Myanmar (23 samples). The interspecies variable part (IVP, nucleotides 1-807) and interspecies conserved part (ICP, 808-2862) of Pvs230 were amplified by PCR and sequenced. Molecular evolution studies were conducted to evaluate the genetic diversity, signature of selection, population differentiation, haplotype network, and population structure of the study parasite populations and publicly available Pvs230 sequences from six global P. vivax populations.

RESULTS

Limited genetic diversity was observed for the CMB (π = 0.002) and Myanmar (π = 0.001) isolates. Most amino acid substitutions were located in the IVP and cysteine-rich domain of Pvs230. Evidence of positive selection was observed for IVP and purifying selection for ICP. Codon-based tests identified specific codons under natural selection in both IVP and ICP. The fixation index (F_ST) showed low genetic differentiation between East and Southeast Asian populations, with F_ST ranging from 0.018 to 0.119. The highest F_ST value (F_ST = 0.503) was detected between the Turkey and Papua New Guinea populations. A total of 92 haplotypes were identified in global isolates, with the major haplotypes 2 and 9 being the most abundant and circulating in East and Southeast Asia populations. Several detected non-synonymous substitutions were mapped in the predicted structure and B-cell epitopes of Pvs230.

CONCLUSIONS

We detected low levels of genetic diversity of Pvs230 in global P. vivax populations. Geographically specific haplotypes were identified for Pvs230. Some mutations are located within a potential B-cell epitope region and need to be considered in future TBV designs.

Multidisciplinary Investigations of Sustained Malaria Transmission in the Greater Mekong Subregion

In the course of malaria elimination in the Greater Mekong Subregion (GMS), malaria epidemiology has experienced drastic spatiotemporal changes with residual transmission concentrated along international borders and the rising predominance of Plasmodium vivax. The emergence of Plasmodium falciparum parasites resistant to artemisinin and partner drugs renders artemisinin-based combination therapies less effective while the potential spread of multidrug-resistant parasites elicits concern. Vector behavioral changes and insecticide resistance have reduced the effectiveness of core vector control measures. In recognition of these problems, the Southeast Asian International Center of Excellence for Malaria Research (ICEMR) has been conducting multidisciplinary research to determine how human migration, antimalarial drug resistance, vector behavior, and insecticide resistance sustain malaria transmission at international borders. These efforts allow us to comprehensively understand the ecology of border malaria transmission and develop population genomics tools to identify and track parasite introduction. In addition to employing in vivo, in vitro, and molecular approaches to monitor the emergence and spread of drug-resistant parasites, we also use genomic and genetic methods to reveal novel mechanisms of antimalarial drug resistance of parasites. We also use omics and population genetics approaches to study insecticide resistance in malaria vectors and identify changes in mosquito community structure, vectorial potential, and seasonal dynamics. Collectively, the scientific findings from the ICEMR research activities offer a systematic view of the factors sustaining residual malaria transmission and identify potential solutions to these problems to accelerate malaria elimination in the GMS.

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.

Genome-wide analysis of Schistosoma mansoni reveals limited population structure and possible praziquantel drug selection pressure within Ugandan hot-spot communities

Populations within schistosomiasis control areas, especially those in Africa, are recommended to receive regular mass drug administration (MDA) with praziquantel (PZQ) as the main strategy for controlling the disease. The impact of PZQ treatment on schistosome genetics remains poorly understood, and is limited by a lack of high-resolution genetic data on the population structure of parasites within these control areas. We generated whole-genome sequence data from 174 individual miracidia collected from both children and adults from fishing communities on islands in Lake Victoria in Uganda that had received either annual or quarterly MDA with PZQ over four years, including samples collected immediately before and four weeks after treatment. Genome variation within and between samples was characterised and we investigated genomic signatures of natural selection acting on these populations that could be due to PZQ treatment. The parasite population on these islands was more diverse than found in nearby villages on the lake shore. We saw little or no genetic differentiation between villages, or between the groups of villages with different treatment intensity, but slightly higher genetic diversity within the pre-treatment compared to post-treatment parasite populations. We identified classes of genes significantly enriched within regions of the genome with evidence of recent positive selection among post-treatment and intensively treated parasite populations. The differential selection observed in post-treatment and pre-treatment parasite populations could be linked to any reduced susceptibility of parasites to praziquantel treatment.

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.

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.

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.

Elucidating relationships between P.falciparum prevalence and measures of genetic diversity with a combined genetic-epidemiological model of malaria

There is an abundance of malaria genetic data being collected from the field, yet using these data to understand the drivers of regional epidemiology remains a challenge. A key issue is the lack of models that relate parasite genetic diversity to epidemiological parameters. Classical models in population genetics characterize changes in genetic diversity in relation to demographic parameters, but fail to account for the unique features of the malaria life cycle. In contrast, epidemiological models, such as the Ross-Macdonald model, capture malaria transmission dynamics but do not consider genetics. Here, we have developed an integrated model encompassing both parasite evolution and regional epidemiology. We achieve this by combining the Ross-Macdonald model with an intra-host continuous-time Moran model, thus explicitly representing the evolution of individual parasite genomes in a traditional epidemiological framework. Implemented as a stochastic simulation, we use the model to explore relationships between measures of parasite genetic diversity and parasite prevalence, a widely-used metric of transmission intensity. First, we explore how varying parasite prevalence influences genetic diversity at equilibrium. We find that multiple genetic diversity statistics are correlated with prevalence, but the strength of the relationships depends on whether variation in prevalence is driven by host- or vector-related factors. Next, we assess the responsiveness of a variety of statistics to malaria control interventions, finding that those related to mixed infections respond quickly (∼months) whereas other statistics, such as nucleotide diversity, may take decades to respond. These findings provide insights into the opportunities and challenges associated with using genetic data to monitor malaria epidemiology.

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples

MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

Discovery and development of 2-aminobenzimidazoles as potent antimalarials

The emergence of Plasmodium falciparum resistance to frontline antimalarials, including artemisinin combination therapies, highlights the need for new molecules that act via novel mechanisms of action. Herein, we report the design, synthesis and antimalarial activity of a series of 2-aminobenzimidazoles, featuring a phenol moiety that is crucial to the pharmacophore. Two potent molecules exhibited IC₅₀ values against P. falciparum 3D7 strain of 42 ± 4 (3c) and 43 ± 2 nM (3g), and high potency against strains resistant to chloroquine (Dd2), artemisinin (Cam3.II^C580Y) and PfATP4 inhibitors (SJ557733), while demonstrating no cytotoxicity against human cells (HEK293, IC₅₀ > 50 μM). The most potent molecule, possessing a 4,5-dimethyl substituted phenol (3r) displayed an IC₅₀ value of 6.4 ± 0.5 nM against P. falciparum 3D7, representing a 12-fold increase in activity from the parent molecule. The 2-aminobenzimidazoles containing a N¹-substituted phenol represent a new class of molecules that have high potency in vitro against P. falciparum malaria and low cytotoxicity. They possessed attractive pharmaceutical properties, including low molecular weight, high ligand efficiency, high solubility, synthetic tractability and low in vitro clearance in human liver microsomes.

Antimalarial Drug Resistance and Implications for the WHO Global Technical Strategy

PURPOSE OF REVIEW

Five years have passed since the World Health Organization released its Global Technical Strategy for Malaria (GTS). In that time, progress against malaria has plateaued. This review focuses on the implications of antimalarial drug resistance for the GTS and how interim progress in parasite genomics and antimalarial pharmacology offer a bulwark against it.

RECENT FINDINGS

For the first time, drug resistance-conferring genes have been identified and validated before their global expansion in malaria parasite populations. More efficient methods for their detection and elaboration have been developed, although low-density infections and polyclonality remain a nuisance to be solved. Clinical trials of alternative regimens for multidrug-resistant malaria have delivered promising results. New agents continue down the development pipeline, while a nascent infrastructure in sub-Saharan Africa for conducting phase I trials and trials of transmission-blocking agents has come to fruition after years of preparation.

SUMMARY

These and other developments can help inform the GTS as the world looks ahead to the next two decades of its implementation. To remain ahead of the threat that drug resistance poses, wider application of genomic-based surveillance and optimization of existing and forthcoming antimalarial drugs are essential.

Efficacy and Safety of Pyronaridine-Artesunate for the Treatment of Uncomplicated Plasmodium falciparum and Plasmodium vivax Malaria in Myanmar

Four single-arm, prospective, clinical studies of pyronaridine–artesunate efficacy in uncomplicated Plasmodium falciparum or Plasmodium vivax malaria were conducted in Myanmar between 2017 and 2019. Eligible subjects were aged at least 6 years, with microscopically confirmed P. falciparum (n = 196) or P. vivax mono-infection (n = 206). Patients received pyronaridine–artesunate once daily for 3 days with follow-up until day 42 for P. falciparum or day 28 for P. vivax. For the primary efficacy analysis, adequate clinical and parasitological response (ACPR) in the per-protocol population at day 42 for P. falciparum malaria was 100% (88/88; 95% CI: 95.9, 100) in northern Myanmar (Kachin State and northern Shan State), and 100% (101/101; 95% CI: 96.4, 100) in southern Myanmar (Tanintharyi Region and Kayin State). Plasmodium falciparum day-3 parasite clearance was observed for 96.9% (190/196) of patients. Mutations in the P. falciparum Kelch propeller domain (K13) were detected in 39.0% (69/177) of isolates: F446I (14.7% [26/177]), R561H (13.0% [23/177]), C580Y (10.2% [18/177]), and P574L (1.1% [2/177]). For P. vivax, the day-28 ACPR was 100% (104/104; 95% CI: 96.5, 100) in northern Myanmar and 100% (97/97; 95% CI: 96.3, 100) in southern Myanmar. Across both P. vivax studies, 100% (206/206) of patients had day-3 parasite clearance. There were no adverse events. Pyronaridine–artesunate had excellent efficacy in Myanmar against P. falciparum and P. vivax and was well tolerated. This study supports the inclusion of pyronaridine–artesunate in national malaria treatment guidelines for Myanmar.

Identity-by-descent with uncertainty characterises connectivity of Plasmodium falciparum populations on the Colombian-Pacific coast

Characterising connectivity between geographically separated biological populations is a common goal in many fields. Recent approaches to understanding connectivity between malaria parasite populations, with implications for disease control efforts, have used estimates of relatedness based on identity-by-descent (IBD). However, uncertainty around estimated relatedness has not been accounted for. IBD-based relatedness estimates with uncertainty were computed for pairs of monoclonal Plasmodium falciparum samples collected from five cities on the Colombian-Pacific coast where long-term clonal propagation of P. falciparum is frequent. The cities include two official ports, Buenaventura and Tumaco, that are separated geographically but connected by frequent marine traffic. Fractions of highly-related sample pairs (whose classification using a threshold accounts for uncertainty) were greater within cities versus between. However, based on both highly-related fractions and on a threshold-free approach (Wasserstein distances between parasite populations) connectivity between Buenaventura and Tumaco was disproportionally high. Buenaventura-Tumaco connectivity was consistent with transmission events involving parasites from five clonal components (groups of statistically indistinguishable parasites identified under a graph theoretic framework). To conclude, P. falciparum population connectivity on the Colombian-Pacific coast abides by accessibility not isolation-by-distance, potentially implicating marine traffic in malaria transmission with opportunities for targeted intervention. Further investigations are required to test this hypothesis. For the first time in malaria epidemiology (and to our knowledge in ecological and epidemiological studies more generally), we account for uncertainty around estimated relatedness (an important consideration for studies that plan to use genotype versus whole genome sequence data to estimate IBD-based relatedness); we also use threshold-free methods to compare parasite populations and identify clonal components. Threshold-free methods are especially important in analyses of malaria parasites and other recombining organisms with mixed mating systems where thresholds do not have clear interpretation (e.g. due to clonal propagation) and thus undermine the cross-comparison of studies.

Population genomics reveals the expansion of highly inbred Plasmodium vivax lineages in the main malaria hotspot of Brazil

BACKGROUND

Plasmodium vivax is a neglected human malaria parasite that causes significant morbidity in the Americas, the Middle East, Asia, and the Western Pacific. Population genomic approaches remain little explored to map local and regional transmission pathways of P. vivax across the main endemic sites in the Americas, where great progress has been made towards malaria elimination over the past decades.

METHODOLOGY/PRINCIPAL FINDINGS

We analyze 38 patient-derived P. vivax genome sequences from Mâncio Lima (ML)-the Amazonian malaria hotspot next to the Brazil-Peru border-and 24 sequences from two other sites in Acre State, Brazil, a country that contributes 23% of malaria cases in the Americas. We show that the P. vivax population of ML is genetically diverse (π = 4.7 × 10-4), with a high polymorphism particularly in genes encoding proteins putatively involved in red blood cell invasion. Paradoxically, however, parasites display strong genome-wide linkage disequilibrium, being fragmented into discrete lineages that are remarkably stable across time and space, with only occasional recombination between them. Using identity-by-descent approaches, we identified a large cluster of closely related sequences that comprises 16 of 38 genomes sampled in ML over 26 months. Importantly, we found significant ancestry sharing between parasites at a large geographic distance, consistent with substantial gene flow between regional P. vivax populations.

CONCLUSIONS/SIGNIFICANCE

We have characterized the sustained expansion of highly inbred P. vivax lineages in a malaria hotspot that can seed regional transmission. Potential source populations in hotspots represent a priority target for malaria elimination in the Amazon.

No evidence of amplified Plasmodium falciparum plasmepsin II gene copy number in an area with artemisinin-resistant malaria along the China-Myanmar border

Background

The emergence and spread of artemisinin resistance in Plasmodium falciparum poses a threat to malaria eradication, including China’s plan to eliminate malaria by 2020. Piperaquine (PPQ) resistance has emerged in Cambodia, compromising an important partner drug that is widely used in China in the form of dihydroartemisinin (DHA)-PPQ. Several mutations in a P. falciparum gene encoding a kelch protein on chromosome 13 (k13) are associated with artemisinin resistance and have arisen spread in the Great Mekong subregion, including the China–Myanmar border. Multiple copies of the plasmepsin II/III (pm2/3) genes, located on chromosome 14, have been shown to be associated with PPQ resistance.

Methods

The therapeutic efficacy of DHA-PPQ for the treatment of uncomplicated P. falciparum was evaluated along the China–Myanmar border from 2010 to 2014. The dry blood spots samples collected in the efficacy study prior DHA-PPQ treatment and from the local hospital by passive detection were used to amplify k13 and pm2. Polymorphisms within k13 were genotyped by capillary sequencing and pm2 copy number was quantified by relative-quantitative real-time polymerase chain reaction. Treatment outcome was evaluated with the World Health Organization protocol. A linear regression model was used to estimate the association between the day 3 positive rate and k13 mutation and the relationship of the pm2 copy number variants and k13 mutations.

Results

DHA-PPQ was effective for uncomplicated P. falciparum infection in Yunnan Province with cure rates > 95%. Twelve non synonymous mutations in the k13 domain were observed among the 268 samples with the prevalence of 44.0% and the predominant mutation was F446I with a prevalence of 32.8%. Only one sample was observed with multi-copies of pm2, including parasites with and without k13 mutations. The therapeutic efficacy of DHA-PPQ was > 95% along the China–Myanmar border, consistent with the lack of amplification of pm2.

Conclusion

DHA-PPQ for uncomplicated P. falciparum infection still showed efficacy in an area with artemisinin-resistant malaria along the China–Myanmar border. There was no evidence to show PPQ resistance by clinical study and molecular markers survey. Continued monitoring of the parasite population using molecular markers will be important to track emergence and spread of resistance in this region.

Population genomics identifies a distinct Plasmodium vivax population on the China-Myanmar border of Southeast Asia

Plasmodium vivax has become the predominant malaria parasite and a major challenge for malaria elimination in the Greater Mekong Subregion (GMS). Yet, our knowledge about the evolution of P. vivax populations in the GMS is fragmental. We performed whole genome sequencing on 23 P. vivax samples from the China-Myanmar border (CMB) and used 21 high-coverage samples to compare to over 200 samples from the rest of the GMS. Using genome-wide single nucleotide polymorphisms (SNPs), we analyzed population differentiation, genetic structure, migration and potential selection using an array of methods. The CMB parasites displayed a higher proportion of monoclonal infections, and 52% shared over 90% of their genomes in identity-by-descent segments with at least one other sample from the CMB, suggesting preferential expansion of certain parasite strains in this region, likely resulting from the P. vivax outbreaks occurring during this study period. Principal component, admixture, fixation index and phylogenetic analyses all identified that parasites from the CMB were genetically distinct from parasites from eastern parts of the GMS (Cambodia, Laos, Vietnam, and Thailand), whereas the eastern GMS parasite populations were largely undifferentiated. Such a genetic differentiation pattern of the P. vivax populations from the GMS parasite was largely explainable through geographic distance. Using the genome-wide SNPs, we narrowed down to a set of 36 SNPs for differentiating parasites from different areas of the GMS. Genome-wide scans to determine selection in the genome with two statistical methods identified genes potentially under drug selection, including genes associated with antifolate resistance and genes linked to chloroquine resistance in Plasmodium falciparum.

Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces

BACKGROUND

Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. Estimated effective migration surfaces (EEMS) is an approach that allows visualization of the spatial patterns in genomic data to understand population structure and migration. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam.

METHODS

The optimal density of EEMS grids was determined based on a new workflow created using density clustering to define genomic clusters and the spatial distance between genomic clusters. Topological skeletons were used to capture the spatial distribution for each genomic cluster and to determine the EEMS grid density; i.e., both genomic and spatial clustering were used to guide the optimization of EEMS grids. Model accuracy for migration estimates using the optimized workflow was tested and compared to grid resolutions selected without the optimized workflow. As a test case, the optimized workflow was applied to genomic data generated from P. falciparum sampled in Cambodia and bordering regions, and migration maps were compared to estimates of malaria endemicity, as well as geographic properties of the study area, as a means of validating observed migration patterns.

RESULTS

Optimized grids displayed both high model accuracy and reduced computing time compared to grid densities selected in an unguided manner. In addition, EEMS migration maps generated for P. falciparum using the optimized grid corresponded to estimates of malaria endemicity and geographic properties of the study region that might be expected to impact malaria parasite migration, supporting the validity of the observed migration patterns.

CONCLUSIONS

Optimized grids reduce spatial uncertainty in the EEMS contours that can result from user-defined parameters, such as the resolution of the spatial grid used in the model. This workflow will be useful to a broad range of EEMS users as it can be applied to analyses involving other organisms of interest and geographic areas.

Dynamics of Plasmodium vivax populations in border areas of the Greater Mekong sub-region during malaria elimination

Background

Countries within the Greater Mekong Sub-region (GMS) of Southeast Asia have committed to eliminating malaria by 2030. Although the malaria situation has greatly improved, malaria transmission remains at international border regions. In some areas, Plasmodium vivax has become the predominant parasite. To gain a better understanding of transmission dynamics, knowledge on the changes of P. vivax populations after the scale-up of control interventions will guide more effective targeted control efforts.

Methods

This study investigated genetic diversity and population structures in 206 P. vivax clinical samples collected at two time points in two international border areas: the China-Myanmar border (CMB) (n = 50 in 2004 and n = 52 in 2016) and Thailand-Myanmar border (TMB) (n = 50 in 2012 and n = 54 in 2015). Parasites were genotyped using 10 microsatellite markers.

Results

Despite intensified control efforts, genetic diversity remained high (H_E = 0.66–0.86) and was not significantly different among the four populations (P > 0.05). Specifically, H_E slightly decreased from 0.76 in 2004 to 0.66 in 2016 at the CMB and increased from 0.80 in 2012 to 0.86 in 2015 at the TMB. The proportions of polyclonal infections varied significantly among the four populations (P < 0.05), and showed substantial decreases from 48.0% in 2004 to 23.7 at the CMB and from 40.0% in 2012 to 30.7% in 2015 at the TMB, with corresponding decreases in the multiplicity of infection. Consistent with the continuous decline of malaria incidence in the GMS over time, there were also increases in multilocus linkage disequilibrium, suggesting more fragmented and increasingly inbred parasite populations. There were considerable genetic differentiation and sub-division among the four tested populations. Temporal genetic differentiation was observed at each site (F_ST = 0.081 at the CMB and F_ST = 0.133 at the TMB). Various degrees of clustering were evident between the older parasite samples collected in 2004 at the CMB and the 2016 CMB and 2012 TMB populations, suggesting some of these parasites had shared ancestry. In contrast, the 2015 TMB population was genetically distinctive, which may reflect a process of population replacement. Whereas the effective population size (N_e) at the CMB showed a decrease from 4979 in 2004 to 3052 in 2016 with the infinite allele model, the N_e at the TMB experienced an increase from 6289 to 10,259.

Conclusions

With enhanced control efforts on malaria, P. vivax at the TMB and CMB showed considerable spatial and temporal differentiation, but the presence of large P. vivax reservoirs still sustained genetic diversity and transmission. These findings provide new insights into P. vivax transmission dynamics and population structure in these border areas of the GMS. Coordinated and integrated control efforts on both sides of international borders are essential to reach the goal of regional malaria elimination.

A seven-year surveillance of epidemiology of malaria reveals travel and gender are the key drivers of dispersion of drug resistant genotypes in Kenya

Malaria drug resistance is a global public health concern. Though parasite mutations have been associated with resistance, other factors could influence the resistance. A robust surveillance system is required to monitor and help contain the resistance. This study established the role of travel and gender in dispersion of chloroquine resistant genotypes in malaria epidemic zones in Kenya. A total of 1,776 individuals presenting with uncomplicated malaria at hospitals selected from four malaria transmission zones in Kenya between 2008 and 2014 were enrolled in a prospective surveillance study assessing the epidemiology of malaria drug resistance patterns. Demographic and clinical information per individual was obtained using a structured questionnaire. Further, 2 mL of blood was collected for malaria diagnosis, parasitemia quantification and molecular analysis. DNA extracted from dried blood spots collected from each of the individuals was genotyped for polymorphisms in Plasmodium falciparum chloroquine transporter gene (Pfcrt 76), Plasmodium falciparum multidrug resistant gene 1 (Pfmdr1 86 and Pfmdr1 184) regions that are putative drug resistance genes using both conventional polymerase chain reaction (PCR) and real-time PCR. The molecular and demographic data was analyzed using Stata version 13 (College Station, TX: StataCorp LP) while mapping of cases at the selected geographic zones was done in QGIS version 2.18. Chloroquine resistant (CQR) genotypes across gender revealed an association with chloroquine resistance by both univariate model (p = 0.027) and by multivariate model (p = 0.025), female as reference group in both models. Prior treatment with antimalarial drugs within the last 6 weeks before enrollment was associated with carriage of CQR genotype by multivariate model (p = 0.034). Further, a significant relationship was observed between travel and CQR carriage both by univariate model (p = 0.001) and multivariate model (p = 0.002). These findings suggest that gender and travel are significantly associated with chloroquine resistance. From a gender perspective, males are more likely to harbor resistant strains than females hence involved in strain dispersion. On the other hand, travel underscores the role of transport network in introducing spread of resistant genotypes, bringing in to focus the need to monitor gene flow and establish strategies to minimize the introduction of resistance strains by controlling malaria among frequent transporters.

Genome-Wide Analysis of Genetic Diversity in Plasmodium falciparum Isolates From China-Myanmar Border

Plasmodium falciparum isolates from China-Myanmar border (CMB) have experienced regional special selective pressures and adaptive evolution. However, the genomes of P. falciparum isolates from this region to date are poorly characterized. Herein, we performed whole-genome sequencing of 34 P. falciparum isolates from CMB and a series of genome-wide sequence analyses to reveal their genetic diversity, population structures, and comparisons with the isolates from other epidemic regions (Thai-Cambodia border, Thai-Myanmar border, and West Africa). Totally 59,720 high-quality single-nucleotide polymorphisms (SNPs) were identified in the P. falciparum isolates from CMB, with average nucleotide diversity (π = 4.59 × 10^-4) and LD decay (132 bp). The Tajima's D and Fu and Li's D values of the CMB isolates were -0.8 (p < 0.05) and -0.84 (p < 0.05), respectively, suggesting a demographic history of recent population expansion or purifying selection. Moreover, 78 genes of the parasite were identified that could be under positive selection, including those genes conferring drug resistance such as pfubp1. In addition, 33 SNPs were identified for tracing the source of the parasites with a high accuracy by analysis of the most differential SNPs among the four epidemic regions. Collectively, our data demonstrated high diversity of the CMB isolates' genomes forming a distinct population, and the identification of 33-SNP barcode provides a valuable surveillance of parasite migration among the regions.