The Horn of Africa harbors the largest reservoir of Plasmodium vivax in the continent. Most of sub-Saharan Africa has remained relatively vivax-free due to a high prevalence of the human Duffy-negative trait, but the emergence of strains able to invade Duffy-negative reticulocytes poses a major public health threat. We undertook the first population genomic investigation of P. vivax from the region, comparing the genomes of 24 Ethiopian isolates against data from Southeast Asia to identify important local adaptions. The prevalence of the Duffy binding protein amplification in Ethiopia was 79%, potentially reflecting adaptation to Duffy negativity. There was also evidence of selection in a region upstream of the chloroquine resistance transporter, a putative chloroquine-resistance determinant. Strong signals of selection were observed in genes involved in immune evasion and regulation of gene expression, highlighting the need for a multifaceted intervention approach to combat P. vivax in the region.
Plasmodium vivax is the most widespread and difficult to treat cause of human malaria. The development of vaccines against the blood stages of P. vivax remains a key objective for the control and elimination of vivax malaria. Erythrocyte binding-like (EBL) protein family members such as Duffy binding protein (PvDBP) are of critical importance to erythrocyte invasion and have been the major target for vivax malaria vaccine development. In this study, we focus on another member of EBL protein family, P. vivax erythrocyte binding protein (PvEBP). PvEBP was first identified in Cambodian (C127) field isolates and has subsequently been showed its preferences for binding reticulocytes which is directly inhibited by antibodies. We analysed PvEBP sequence from 316 vivax clinical isolates from eight countries including China (n = 4), Ethiopia (n = 24), Malaysia (n = 53), Myanmar (n = 10), Papua New Guinea (n = 16), Republic of Korea (n = 10), Thailand (n = 174), and Vietnam (n = 25). PvEBP gene exhibited four different phenotypic clusters based on the insertion/deletion (indels) variation. PvEBP-RII (179-479 aa.) showed highest polymorphism similar to other EBL family proteins in various Plasmodium species. Whereas even though PvEBP-RIII-V (480-690 aa.) was the most conserved domain, that showed strong neutral selection pressure for gene purifying with significant population expansion. Antigenicity of both of PvEBP-RII (16.1%) and PvEBP-RIII-V (21.5%) domains were comparatively lower than other P. vivax antigen which expected antigens associated with merozoite invasion. Total IgG recognition level of PvEBP-RII was stronger than PvEBP-RIII-V domain, whereas total IgG inducing level was stronger in PvEBP-RIII-V domain. These results suggest that PvEBP-RII is mainly recognized by natural IgG for innate protection, whereas PvEBP-RIII-V stimulates IgG production activity by B-cell for acquired immunity. Overall, the low antigenicity of both regions in patients with vivax malaria likely reflects genetic polymorphism for strong positive selection in PvEBP-RII and purifying selection in PvEBP-RIII-V domain. These observations pose challenging questions to the selection of EBP and point out the importance of immune pressure and polymorphism required for inclusion of PvEBP as a vaccine candidate.
This report describes the MalariaGEN Pv4 dataset, a new release of curated genome variation data on 1,895 samples of Plasmodium vivax collected at 88 worldwide locations between 2001 and 2017. It includes 1,370 new samples contributed by MalariaGEN and VivaxGEN partner studies in addition to previously published samples from these and other sources. We provide genotype calls at over 4.5 million variable positions including over 3 million single nucleotide polymorphisms (SNPs), as well as short indels and tandem duplications. This enlarged dataset highlights major compartments of parasite population structure, with clear differentiation between Africa, Latin America, Oceania, Western Asia and different parts of Southeast Asia. Each sample has been classified for drug resistance to sulfadoxine, pyrimethamine and mefloquine based on known markers at the dhfr, dhps and mdr1 loci. The prevalence of all of these resistance markers was much higher in Southeast Asia and Oceania than elsewhere. This open resource of analysis-ready genome variation data from the MalariaGEN and VivaxGEN networks is driven by our collective goal to advance research into the complex biology of P. vivax and to accelerate genomic surveillance for malaria control and elimination.
Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.