Although Plasmodium vivax parasites are the predominant cause of malaria outside of sub-Saharan Africa, they not always prioritised by elimination programmes. P. vivax is resilient and poses challenges through its ability to re-emerge from dormancy in the human liver. With observed growing drug-resistance and the increasing reports of life-threatening infections, new tools to inform elimination efforts are needed. In order to halt transmission, we need to better understand the dynamics of transmission, the movement of parasites, and the reservoirs of infection in order to design targeted interventions. The use of molecular genetics and epidemiology for tracking and studying malaria parasite populations has been applied successfully in P. falciparum species and here we sought to develop a molecular genetic tool for P. vivax. By assembling the largest set of P. vivax whole genome sequences (n = 433) spanning 17 countries, and applying a machine learning approach, we created a 71 SNP barcode with high predictive ability to identify geographic origin (91.4%). Further, due to the inclusion of markers for within population variability, the barcode may also distinguish local transmission networks. By using P. vivax data from a low-transmission setting in Malaysia, we demonstrate the potential ability to infer outbreak events. By characterising the barcoding SNP genotypes in P. vivax DNA sourced from UK travellers (n = 132) to ten malaria endemic countries predominantly not used in the barcode construction, we correctly predicted the geographic region of infection origin. Overall, the 71 SNP barcode outperforms previously published genotyping methods and when rolled-out within new portable platforms, is likely to be an invaluable tool for informing targeted interventions towards elimination of this resilient human malaria.
The macaque parasite Plasmodium knowlesi is a significant concern in Malaysia where cases of human infection are increasing. Parasites infecting humans originate from genetically distinct subpopulations associated with the long-tailed (Macaca fascicularis (Mf)) or pig-tailed macaques (Macaca nemestrina (Mn)). We used a new high-quality reference genome to re-evaluate previously described subpopulations among human and macaque isolates from Malaysian-Borneo and Peninsular-Malaysia. Nuclear genomes were dimorphic, as expected, but new evidence of chromosomal-segment exchanges between subpopulations was found. A large segment on chromosome 8 originating from the Mn subpopulation and containing genes encoding proteins expressed in mosquito-borne parasite stages, was found in Mf genotypes. By contrast, non-recombining organelle genomes partitioned into 3 deeply branched lineages, unlinked with nuclear genomic dimorphism. Subpopulations which diverged in isolation have re-connected, possibly due to deforestation and disruption of wild macaque habitats. The resulting genomic mosaics reveal traits selected by host-vector-parasite interactions in a setting of ecological transition.
Sabah, Malaysia, has amongst the highest burden of human Plasmodium knowlesi infection in the world, associated with increasing encroachment on the parasite's macaque host habitat. However, the genomic make-up of P. knowlesi in Sabah was previously poorly understood. To inform on local patterns of transmission and putative adaptive drivers, we conduct population-level genetic analyses of P. knowlesi human infections using 52 new whole genomes from Sabah, Malaysia, in combination with publicly available data. We identify the emergence of distinct geographical subpopulations within the macaque-associated clusters using identity-by-descent-based connectivity analysis. Secondly, we report on introgression events between the clusters, which may be linked to differentiation of the subpopulations, and that overlap genes critical for survival in human and mosquito hosts. Using village-level locations from P. knowlesi infections, we also identify associations between several introgressed regions and both intact forest perimeter-area ratio and mosquito vector habitat suitability. Our findings provide further evidence of the complex role of changing ecosystems and sympatric macaque hosts in Malaysia driving distinct genetic changes seen in P. knowlesi populations. Future expanded analyses of evolving P. knowlesi genetics and environmental drivers of transmission will be important to guide public health surveillance and control strategies.