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Characterizing the genomic variation and population dynamics of Plasmodium falciparum malaria parasites in and around Lake Victoria, Kenya.

ABSTRACT: Characterising the genomic variation and population dynamics of Plasmodium falciparum parasites in high transmission regions of Sub-Saharan Africa is crucial to the long-term efficacy of regional malaria elimination campaigns and eradication. Whole-genome sequencing (WGS) technologies can contribute towards understanding the epidemiology and structural variation landscape of P. falciparum populations, including those within the Lake Victoria basin, a region of intense transmission. Here we provide a baseline assessment of the genomic diversity of P. falciparum isolates in the Lake region of Kenya, which has sparse genetic data. Lake region isolates are placed within the context of African-wide populations using Illumina WGS data and population genomic analyses. Our analysis revealed that P. falciparum isolates from Lake Victoria form a cluster within the East African parasite population. These isolates also appear to have distinct ancestral origins, containing genome-wide signatures from both Central and East African lineages. Known drug resistance biomarkers were observed at similar frequencies to those of East African parasite populations, including the S160N/T mutation in the pfap2mu gene, which has been associated with delayed clearance by artemisinin-based combination therapy. Overall, our work provides a first assessment of P. falciparum genetic diversity within the Lake Victoria basin, a region targeting malaria elimination.

SUBMITTER: Osborne A

PROVIDER: S-EPMC8494747 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:The transcriptome of Plasmodium falciparum clinical isolates varies according to strain, mosquito bites, disease severity and clinical history. Therefore, it remains a challenge to directly interpret the parasite's transcriptomic information into a more general biological signature in a natural human malaria infection. These confounding variations can be potentially overcome with parasites derived from controlled-human malaria infection (CHMI) studies. METHODS:We performed CHMI studies in healthy and immunologically naïve volunteers receiving the same P. falciparum strain ((Sanaria® PfSPZ Challenge (NF54)), but with different sporozoite dosage and route of infection. Parasites isolated from these volunteers at the day of patency were subjected to in vitro culture for several generations and synchronized ring-stage parasites were subjected to transcriptome profiling. FINDINGS:We observed clear deviations between CHMI-derived parasites from volunteer groups receiving different PfSPZ dose and route. CHMI-derived parasites and the pre-mosquito strain used for PfSPZ generation showed significant transcriptional variability for gene clusters associated with malaria pathogenesis, immune evasion and transmission. These transcriptional variation signature clusters were also observed in the transcriptome of P. falciparum isolates from acute clinical infections. INTERPRETATION:Our work identifies a previously unrecognized transcriptional pattern in malaria infections in a non-immune background. Significant transcriptome heterogeneity exits between parasites derived from human infections and the pre-mosquito strain, implying that the malaria parasites undergo a change in functional state to adapt to its host environment. Our work also highlights the potential use of transcriptomics data from CHMI study advance our understanding of malaria parasite adaptation and transmission in humans. FUND: This work is supported by German Israeli Foundation, German ministry for education and research, MOE Tier 1 from the Singapore Ministry of Education Academic Research Fund, Singapore Ministry of Health's National Medical Research Council, National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA and the German Centre for Infection Research (Deutsches Zentrum für Infektionsforschung-DZIF).

Project description:Whole-genome sequencing technologies are being increasingly applied to Plasmodium falciparum clinical isolates to identify genetic determinants of malaria pathogenesis. However, genome-wide discovery methods, such as haplotype scans for signatures of natural selection, are hindered by missing genotypes in sequence data. Poor correlation between single nucleotide polymorphisms (SNPs) in the P. falciparum genome complicates efforts to apply established missing-genotype imputation methods that leverage off patterns of linkage disequilibrium (LD). The accuracy of state-of-the-art, LD-based imputation methods (IMPUTE, Beagle) was assessed by measuring allelic r2 for 459 P. falciparum samples from malaria patients in 4 countries: Thailand, Cambodia, Gambia, and Malawi. In restricting our analysis to 86 k high-quality SNPs across the populations, we found that the complete-case analysis was restricted to 21k SNPs (24.5%), despite no single SNP having more than 10% missing genotypes. The accuracy of Beagle in filling in missing genotypes was consistently high across all populations (allelic r2, 0.87-0.96), but the performance of IMPUTE was mixed (allelic r2, 0.34-0.99) depending on reference haplotypes and population. Positive selection analysis using Beagle-imputed haplotypes identified loci involved in resistance to chloroquine (crt) in Thailand, Cambodia, and Gambia, sulfadoxine-pyrimethamine (dhfr, dhps) in Cambodia, and artemisinin (kelch13) in Cambodia. Tajima's D-based analysis identified genes under balancing selection that encode well-characterized vaccine candidates: apical merozoite antigen 1 (ama1) and merozoite surface protein 1 (msp1). In contrast, the complete-case analysis failed to identify any well-validated drug resistance or candidate vaccine loci, except kelch13. In a setting of low LD and modest levels of missing genotypes, using Beagle to impute P. falciparum genotypes is a viable strategy for conducting accurate large-scale population genetics and association analyses, and supporting global surveillance for drug resistance markers and candidate vaccine antigens.

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Characterizing the genomic variation and population dynamics of Plasmodium falciparum malaria parasites in and around Lake Victoria, Kenya.

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