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 Pf 7 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.

Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing.

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

Positive-unlabeled learning identifies vaccine candidate antigens in the malaria parasite Plasmodium falciparum.

Malaria vaccine development is hampered by extensive antigenic variation and complex life stages of Plasmodium species. Vaccine development has focused on a small number of antigens, many of which were identified without utilizing systematic genome-level approaches. In this study, we implement a machine learning-based reverse vaccinology approach to predict potential new malaria vaccine candidate antigens. We assemble and analyze P. falciparum proteomic, structural, functional, immunological, genomic, and transcriptomic data, and use positive-unlabeled learning to predict potential antigens based on the properties of known antigens and remaining proteins. We prioritize candidate antigens based on model performance on reference antigens with different genetic diversity and quantify the protein properties that contribute most to identifying top candidates. Candidate antigens are characterized by gene essentiality, gene ontology, and gene expression in different life stages to inform future vaccine development. This approach provides a framework for identifying and prioritizing candidate vaccine antigens for a broad range of pathogens.

Gene expression analyses reveal differences in children's response to malaria according to their age.

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

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.

Gene expression analyses reveal differences in children's response to malaria according to their age.

In Bandiagara, Mali, children experience on average two clinical malaria episodes per season. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, vary dramatically among children. To examine the factors contributing to these variations, we simultaneously characterized the host and parasite gene expression profiles from 136 children with symptomatic falciparum malaria and analyzed the expression of 9,205 human and 2,484 Plasmodium genes. We used gene expression deconvolution to estimate the relative proportion of immune cells and parasite stages in each sample and to adjust the differential gene expression analyses. Parasitemia explained much of the variation in both host and parasite gene expression and revealed that infections with higher parasitemia had more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child's age was also strongly correlated with gene expression variations. Plasmodium falciparum genes associated with age suggested that older children carried more male gametocytes, while host genes associated with age indicated a stronger innate response (through TLR and NLR signaling) in younger children and stronger adaptive immunity (through TCR and BCR signaling) in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children's age when studying and treating malaria infections.

Gene expression analyses reveal differences in children's response to malaria according to their age.

In Bandiagara, Mali, children experience on average two clinical malaria episodes per season. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, vary dramatically among children. To examine the factors contributing to these variations, we simultaneously characterized the host and parasite gene expression profiles from 136 children with symptomatic falciparum malaria and analyzed the expression of 9,205 human and 2,484 Plasmodium genes. We used gene expression deconvolution to estimate the relative proportion of immune cells and parasite stages in each sample and to adjust the differential gene expression analyses. Parasitemia explained much of the variation in both host and parasite gene expression and revealed that infections with higher parasitemia had more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child's age was also strongly correlated with gene expression variations. Plasmodium falciparum genes associated with age suggested that older children carried more male gametocytes, while host genes associated with age indicated a stronger innate response (through TLR and NLR signaling) in younger children and stronger adaptive immunity (through TCR and BCR signaling) in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children's age when studying and treating malaria infections.

Natural immunity to malaria preferentially targets the endothelial protein C receptor-binding regions of PfEMP1s.

Antibody responses to variant surface antigens (VSAs) produced by the malaria parasite Plasmodium falciparum may contribute to age-related natural immunity to severe malaria. One VSA family, P. falciparum erythrocyte membrane protein-1 (PfEMP1), includes a subset of proteins that binds endothelial protein C receptor (EPCR) in human hosts and potentially disrupts the regulation of inflammatory responses, which may lead to the development of severe malaria. We probed peptide microarrays containing segments spanning five PfEMP1 EPCR-binding domain variants with sera from 10 Malian adults and 10 children to determine the differences between adult and pediatric immune responses. We defined serorecognized peptides and amino acid residues as those that elicited a significantly higher antibody response than malaria-naïve controls. We aimed to identify regions consistently serorecognized among adults but not among children across PfEMP1 variants, potentially indicating regions that drive the development of immunity to severe malaria. Adult sera consistently demonstrated broader and more intense serologic responses to constitutive PfEMP1 peptides than pediatric sera, including peptides in EPCR-binding domains. Both adults and children serorecognized a significantly higher proportion of EPCR-binding peptides than peptides that do not directly participate in receptor binding, indicating a preferential development of serologic responses at functional residues. Over the course of a single malaria transmission season, pediatric serological responses increased between the start and the peak of the season, but waned as the transmission season ended. IMPORTANCE Severe malaria and death related to malaria disproportionately affect sub-Saharan children under 5 years of age, commonly manifesting as cerebral malaria and/or severe malarial anemia. In contrast, adults in malaria-endemic regions tend to experience asymptomatic or mild disease. Our findings indicate that natural immunity to malaria targets specific regions within the EPCR-binding domain, particularly peptides containing EPCR-binding residues. Epitopes containing these residues may be promising targets for vaccines or therapeutics directed against severe malaria. Our approach provides insight into the development of natural immunity to a binding target linked to severe malaria by characterizing an "adult-like" response as recognizing a proportion of epitopes within the PfEMP1 protein, particularly regions that mediate EPCR binding. This "adult-like" response likely requires multiple years of malaria exposure, as increases in pediatric serologic response over a single malaria transmission season do not appear significant.

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

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD). Yet, strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we utilized simulations, a true IBD inference algorithm, and empirical datasets from different malaria transmission settings to investigate the extent of such bias and explore potential correction strategies. We analyzed whole genome sequence data generated from 640 new and 4,026 publicly available Plasmodium falciparum clinical isolates. Our findings demonstrated that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discovered that the removal of IBD peak regions partially restored the accuracy of IBD-based inferences, with this effect contingent on the population's background genetic relatedness. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Understanding work-related travel and its relation to malaria occurrence in Thailand using geospatial maximum entropy modelling.

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

Malian children infected with Plasmodium ovale and Plasmodium falciparum display very similar gene expression profiles.

Plasmodium parasites caused 241 million cases of malaria and over 600,000 deaths in 2020. Both P. falciparum and P. ovale are endemic to Mali and cause clinical malaria, with P. falciparum infections typically being more severe. Here, we sequenced RNA from nine pediatric blood samples collected during infections with either P. falciparum or P. ovale, and characterized the host and parasite gene expression profiles. We found that human gene expression varies more between individuals than according to the parasite species causing the infection, while parasite gene expression profiles cluster by species. Additionally, we characterized DNA polymorphisms of the parasites directly from the RNA-seq reads and found comparable levels of genetic diversity in both species, despite dramatic differences in prevalence. Our results provide unique insights into host-pathogen interactions during malaria infections and their variations according to the infecting Plasmodium species, which will be critical to develop better elimination strategies against all human Plasmodium parasites.

Understanding the Intransigence of Malaria in Malawi.

Despite the scale-up of interventions against malaria over the past decade, this disease remains a leading threat to health in Malawi. To evaluate the epidemiology of both Plasmodium falciparum infection and malaria disease, the Malawi International Center of Excellence for Malaria Research (ICEMR) has developed and implemented diverse and robust surveillance and research projects. Descriptive studies in ICEMR Phase 1 increased our understanding of the declining effectiveness of long-lasting insecticidal nets (LLINs), the role of school-age children in malaria parasite transmission, and the complexity of host-parasite interactions leading to disease. These findings informed the design of ICEMR Phase 2 to test hypotheses about LLIN use and effectiveness, vector resistance to insecticides, demographic targets of malaria control, patterns and causes of asymptomatic to life-threatening disease, and the impacts of RTS,S vaccination plus piperonyl butoxide-treated LLINs on infection and disease in young children. These investigations are helping us to understand mosquito-to-human and human-to-mosquito transmission in the context of Malawi's intransigent malaria problem.

An In Silico Analysis of Malaria Pre-Erythrocytic-Stage Antigens Interpreting Worldwide Genetic Data to Suggest Vaccine Candidate Variants and Epitopes.

Failure to account for genetic diversity of antigens during vaccine design may lead to vaccine escape. To evaluate the vaccine escape potential of antigens used in vaccines currently in development or clinical testing, we surveyed the genetic diversity, measured population differentiation, and performed in silico prediction and analysis of T-cell epitopes of ten such Plasmodium falciparum pre-erythrocytic-stage antigens using whole-genome sequence data from 1010 field isolates. Of these, 699 were collected in Africa (Burkina Faso, Cameroon, Guinea, Kenya, Malawi, Mali, and Tanzania), 69 in South America (Brazil, Colombia, French Guiana, and Peru), 59 in Oceania (Papua New Guinea), and 183 in Asia (Cambodia, Myanmar, and Thailand). Antigens surveyed include cell-traversal protein for ookinetes and sporozoites, circumsporozoite protein, liver-stage antigens 1 and 3, sporozoite surface proteins P36 and P52, sporozoite asparagine-rich protein-1, sporozoite microneme protein essential for cell traversal-2, and upregulated-in-infectious-sporozoite 3 and 4 proteins. The analyses showed that a limited number of these protein variants, when combined, would be representative of worldwide parasite populations. Moreover, predicted T-cell epitopes were identified that could be further explored for immunogenicity and protective efficacy. Findings can inform the rational design of a multivalent malaria vaccine.

Differential Incidence of Malaria in Neighboring Villages in a High-Transmission Setting of Southern Mali.

Throughout a phase IIIb/IV efficacy study of repeated treatment with four artemisinin-based combination therapies, significant heterogeneity was found in the number of clinical episodes experienced by individuals during the 2-year follow-up. Several factors, including host, parasite, and environmental factors, may contribute to the differential malaria incidence. We aimed to identify risk factors of malaria incidence in the context of a longitudinal study of the efficacy of different artemisinin-based combination therapy regimens in Bougoula-Hameau, a high-transmission setting in Mali. Risk factors including age, residence, and treatment regimen were compared among individuals experiencing eight or more clinical episodes of malaria ("high-incidence group") and individuals experiencing up to three clinical episodes ("low-incidence group"). Consistent with the known association between age and malaria risk in high-transmission settings, individuals in the high incidence group were significantly younger than individuals in the low-risk group (mean age, 7.0 years versus 10.6 years, respectively; t-test, P < 0.0001). Compared with individuals receiving artemether-lumefantrine, those receiving artesunate-amodiaquine had greater odds of being in the high-incidence group (odds ratio [OR], 2.24; 95% CI, 1.03 - 4.83, P = 0.041), while individuals receiving dihydroartemisinin-piperaquine had a lower odds of being in high incidence group (OR: 0.30, 95% CI, 0.11-0.85; P = 0.024). Individuals residing in the forested areas of Sokourani and Karamogobougou had significantly greater odds of being in the high-incidence group compared with individuals residing in the semi-urban area of Bougoula-Hameau 1 (Karamogobougou: OR, 3.68; 95% CI, 1.46-9.31; P = 0.0059; Sokourani: OR, 11.46; 95% CI, 4.49-29.2; P < 0.0001). This study highlights the importance of fine-mapping malaria risks even at sub-district levels for targeted and customized interventions.

STRIDE: a command-line HMM-based identifier and sub-classifier of Plasmodium falciparum RIFIN and STEVOR variant surface antigen families.

BACKGROUND: RIFINs and STEVORs are variant surface antigens expressed by P. falciparum that play roles in severe malaria pathogenesis and immune evasion. These two highly diverse multigene families feature multiple paralogs, making their classification challenging using traditional bioinformatic methods. RESULTS: STRIDE (STevor and RIfin iDEntifier) is an HMM-based, command-line program that automates the identification and classification of RIFIN and STEVOR protein sequences in the malaria parasite Plasmodium falciparum. STRIDE is more sensitive in detecting RIFINs and STEVORs than available PFAM and TIGRFAM tools and reports RIFIN subtypes and the number of sequences with a FHEYDER amino acid motif, which has been associated with severe malaria pathogenesis. CONCLUSIONS: STRIDE will be beneficial to malaria research groups analyzing genome sequences and transcripts of clinical field isolates, providing insight into parasite biology and virulence.

Successful Profiling of Plasmodium falciparum var Gene Expression in Clinical Samples via a Custom Capture Array.

var genes encode Plasmodium falciparum erythrocyte membrane protein-1 (PfEMP1) antigens. These highly diverse antigens are displayed on the surface of infected erythrocytes and play a critical role in immune evasion and sequestration of infected erythrocytes. Studies of var expression using non-leukocyte-depleted blood are challenging because of the predominance of host genetic material and lack of conserved var segments. Our goal was to enrich for parasite RNA, allowing de novo assembly of var genes and detection of expressed novel variants. We used two overall approaches: (i) enriching for total mRNA in the sequencing library preparations and (ii) enriching for parasite RNA with a custom capture array based on Roche's SeqCap EZ enrichment system. The capture array was designed with probes based on the whole 3D7 reference genome and an additional >4,000 full-length var gene sequences from other P. falciparum strains. We tested each method on RNA samples from Malian children with severe or uncomplicated malaria infections. All reads mapping to the human genome were removed, the remaining reads were assembled de novo into transcripts, and from these, var-like transcripts were identified and annotated. The capture array produced the longest maximum length and largest numbers of var gene transcripts in each sample, particularly in samples with low parasitemia. Identifying the most-expressed var gene sequences in whole-blood clinical samples without the need for extensive processing or generating sample-specific reference genome data is critical for understanding the role of PfEMP1s in malaria pathogenesis. IMPORTANCE Malaria parasites display antigens on the surface of infected red blood cells in the human host that facilitate attachment to blood vessels, contributing to the severity of infection. These antigens are highly variable, allowing the parasite to evade the immune system. Identifying these expressed antigens is critical to understanding the development of severe malarial disease. However, clinical samples contain limited amounts of parasite genetic material, a challenge for sequencing efforts further compounded by the extreme diversity of the parasite surface antigens. We present a method that enriches for these antigen sequences in clinical samples using a custom capture array, requiring minimal processing in the field. While our results are focused on the malaria parasite Plasmodium falciparum, this approach has broad applicability to other highly diverse antigens from other parasites and pathogens such as those that cause giardiasis and leishmaniasis.

Immunoprofiles associated with controlled human malaria infection and naturally acquired immunity identify a shared IgA pre-erythrocytic immunoproteome.

Knowledge of the Plasmodium falciparum antigens that comprise the human liver stage immunoproteome is important for pre-erythrocytic vaccine development, but, compared with the erythrocytic stage immunoproteome, more challenging to classify. Previous studies of P. falciparum antibody responses report IgG and rarely IgA responses. We assessed IgG and IgA antibody responses in adult sera collected during two controlled human malaria infection (CHMI) studies in malaria-naïve volunteers and in 1- to 6-year-old malaria-exposed Malian children on a 251 P. falciparum antigen protein microarray. IgG profiles in the two CHMI groups were equivalent and differed from Malian children. IgA profiles were robust in the CHMI groups and a subset of Malian children. We describe immunoproteome differences in naïve vs. exposed individuals and report pre-erythrocytic proteins recognized by the immune system. IgA responses detected in this study expand the list of pre-erythrocytic antigens for further characterization as potential vaccine candidates.

Malian adults maintain serologic responses to virulent PfEMP1s amid seasonal patterns of fluctuation.

Plasmodium falciparum erythrocyte membrane protein-1s (PfEMP1s), diverse malaria proteins expressed on the infected erythrocyte surface, play an important role in pathogenesis, mediating adhesion to host vascular endothelium. Antibodies to particular non-CD36-binding PfEMP1s are associated with protection against severe disease. We hypothesized that given lifelong P. falciparum exposure, Malian adults would have broad PfEMP1 serorecognition and high seroreactivity levels during follow-up, particularly to non-CD36-binding PfEMP1s such as those that attach to endothelial protein C receptor (EPCR) and intercellular adhesion molecule-1 (ICAM-1). Using a protein microarray, we determined serologic responses to 166 reference PfEMP1 fragments during a dry and subsequent malaria transmission season in Malian adults. Malian adult sera had PfEMP1 serologic responses throughout the year, with decreased reactivity to a small subset of PfEMP1 fragments during the dry season and increases in reactivity to a different subset of PfEMP1 fragments during the subsequent peak malaria transmission season, especially for intracellular PfEMP1 domains. For some individuals, PfEMP1 serologic responses increased after the dry season, suggesting antigenic switching during asymptomatic infection. Adults were more likely to experience variable serorecognition of CD36-binding PfEMP1s than non-CD36-binding PfEMP1s that bind EPCR or ICAM-1, which remained serorecognized throughout the year. Sustained seroreactivity to non-CD36-binding PfEMP1s throughout adulthood amid seasonal fluctuation patterns may reflect underlying protective severe malaria immunity and merits further investigation.

Integration of population and functional genomics to understand mechanisms of artemisinin resistance in Plasmodium falciparum.

Resistance to antimalarial drugs, and in particular to the artemisinin derivatives and their partner drugs, threatens recent progress toward regional malaria elimination and eventual global malaria eradication. Population-level studies utilizing whole-genome sequencing approaches have facilitated the identification of regions of the parasite genome associated with both clinical and in vitro drug-resistance phenotypes. However, the biological relevance of genes identified in these analyses and the establishment of a causal relationship between genotype and phenotype requires functional characterization. Here we examined data from population genomic and transcriptomic studies in the context of data generated from recent functional studies, using a new population genetic approach designed to identify potential favored mutations within the region of a selective sweep (iSAFE). We identified several genes functioning in pathways now known to be associated with artemisinin resistance that were supported in early population genomic studies, as well as potential new drug targets/pathways for further validation and consideration for treatment of artemisinin-resistant Plasmodium falciparum. In addition, we establish the utility of iSAFE in identifying positively-selected mutations in population genomic studies, potentially accelerating the time to functional validation of candidate genes.

Whole-genome analysis of Malawian Plasmodium falciparum isolates identifies possible targets of allele-specific immunity to clinical malaria.

Individuals acquire immunity to clinical malaria after repeated Plasmodium falciparum infections. Immunity to disease is thought to reflect the acquisition of a repertoire of responses to multiple alleles in diverse parasite antigens. In previous studies, we identified polymorphic sites within individual antigens that are associated with parasite immune evasion by examining antigen allele dynamics in individuals followed longitudinally. Here we expand this approach by analyzing genome-wide polymorphisms using whole genome sequence data from 140 parasite isolates representing malaria cases from a longitudinal study in Malawi and identify 25 genes that encode possible targets of naturally acquired immunity that should be validated immunologically and further characterized for their potential as vaccine candidates.