Population genetic analysis of Plasmodium knowlesi reveals differential selection and exchange events between Borneo and Peninsular sub-populations

Abstract

The zoonotic Plasmodium knowlesi parasite is a growing public health concern in Southeast Asia, especially in Malaysia, where elimination of P. falciparum and P. vivax malaria has been the focus of control efforts. Understanding of the genetic diversity of P. knowlesi parasites can provide insights into its evolution, population structure, diagnostics, transmission dynamics, and the emergence of drug resistance. Previous work has revealed that P. knowlesi fall into three main sub-populations distinguished by a combination of geographical location and macaque host (Macaca fascicularis and M. nemestrina). It has been shown that Malaysian Borneo groups display profound heterogeneity with long regions of high or low divergence resulting in mosaic patterns between sub-populations, with some evidence of chromosomal-segment exchanges. However, the genetic structure of non-Borneo sub-populations is less clear. By gathering one of the largest collections of P. knowlesi whole-genome sequencing data, we studied structural genomic changes across sub-populations, with the analysis revealing differences in Borneo clusters linked to mosquito-related stages of the parasite cycle, in contrast to differences in host-related stages for the Peninsular group. Our work identifies new genetic exchange events, including introgressions between Malaysian Peninsular and M. nemestrina-associated clusters on various chromosomes, including in parasite invasion genes (DBP$$\beta$$ β , NBPX$$\alpha$$ α and NBPX$$\beta$$ β ), and important proteins expressed in the vertebrate parasite stages. Recombination events appear to have occurred between the Peninsular and M. fascicularis-associated groups, including in the DBP$$\beta$$ β and DBP$$\gamma$$ γ invasion associated genes. Overall, our work finds that genetic exchange events have occurred among the recognised contemporary groups of P. knowlesi parasites during their evolutionary history, leading to apparent mosaicism between these sub-populations. These findings generate new hypotheses relevant to parasite evolutionary biology and P. knowlesi epidemiology, which can inform malaria control approaches to containing the impact of zoonotic malaria on human communities.

Limited Polymorphism in the Dihydrofolate Reductase (dhfr) and dihydropteroate synthase genes (dhps) of Plasmodium knowlesi isolate from Thailand

“…Similar to the previous report ( Diez Benavente et al., 2017 ), the pkdhps tree in this study created sample clusters based on its natural hosts M. fascicularis (Mf-Pk) and M. nemestrina (Mn-Pk). However, the four Mf-Pk samples found in the Mn-Pk taxa and three of the four isolates reported genetic exchange between host-associated clusters at chromosomes 5, 8, and 11 but not at the pkdhps gene on chromosome 14 ( Turkiewicz et al., 2023 ). Thus, this observation would not be a result of the parasite's genetic introgression, but rather due to the information provided by the partial gene analysis, which may be insufficient to distinguish between the two clusters.…”

Genomic epidemiology ofPlasmodium knowlesireveals putative genetic drivers of adaptation in Malaysia

“…This includes the oocyst capsule protein (PKA1H_080026000), CPW-WPC family protein (PKA1H_080026200) and the microneme-associated antigen (PKA1H_080031400). The inclusion of the new Sabah isolates expands the distribution of the introgression event associated with the oocyst-expressed cap380 gene, previously only observed in Betong, Sarawak (15,18). The oocyst capsule protein is essential for the maturation of ookinete into oocyst in P. berghei and is assumed to assist in immune evasion in mosquito hosts (27).…”

“…Large-scale, collaborative efforts to produce publicly available population-level whole genome data for Plasmodium species of interest, have produced over 20,000 P. falciparum (12) and ~1,800 P. vivax (13) genomes. In contrast, P. knowlesi currently has fewer than 200 whole genomes available from a limited geographic distribution (14,15,16,17,18). Only 16 reported P. knowlesi genomes are described from the state of Sabah in East Malaysia, despite this area representing among the highest reported number of P. knowlesi cases and disease burden globally to date (19).…”

Rapid profiling of Plasmodium parasites from genome sequences to assist malaria control

“…Using the mitochondrial genome has the advantage of ~ 20 more copies than the nuclear genome in cells [8]. In addition, we included a set of established markers (n = 137) that differentiate geographical regions for P. falciparum (61; Eastern, Western and Horn of Africa, Southeast Asia, South America, Oceania), P. vivax (56; East Africa, South Asia, Southeast Asia, Southern Southeast Asia, South America) and P. knowlesi (20; Non-Borneo (Peninsular); Borneo -Macaca fascularis (Borneo-Mf ), Borneo -Macaca nemestrina (Borneo-Mn)) [8,17,19,20] (Table 2). In brief, these barcoding markers have been previously determined using the population differentiation F ST statistic, and identifying scores of one, which indicate that the SNP allele is fixed in the region of interest and not present outside that location.…”

“…However, recently a selective whole genome amplification (SWGA) strategy has been used to sequence P. falciparum [15], P. vivax [2,16], P. knowlesi [17] and P. malariae [18] genomes from non-filtered blood and from dried blood spots of clinical samples, leading to the characterisation of single nucleotide polymorphisms (SNPs) and insertions and deletions (indels) for population genomic analyses. More generally, genomic diversity studies using WGS from P. falciparum, P. knowlesi and P. vivax endemic field isolates have provided significant insights into the structure and ancestry of the geographical-based parasite populations, intra-and inter-population genomic diversity, and led to the development of molecular barcodes to determine the geographical source of infections [8,17,[19][20][21]. Furthermore, population genetic analyses have identified genomic regions under selective pressure, some in drug resistance-associated genes [2,15,[22][23][24].…”