Disease progression in Plasmodium knowlesi malaria is linked to variation in invasion gene family members

Abstract

Emerging pathogens undermine initiatives to control the global health impact of infectious diseases. Zoonotic malaria is no exception. Plasmodium knowlesi, a malaria parasite of Southeast Asian macaques, has entered the human population. P. knowlesi, like Plasmodium falciparum, can reach high parasitaemia in human infections, and the World Health Organization guidelines for severe malaria list hyperparasitaemia among the measures of severe malaria in both infections. Not all patients with P. knowlesi infections develop hyperparasitaemia, and it is important to determine why. Between isolate variability in erythrocyte invasion, efficiency seems key. Here we investigate the idea that particular alleles of two P. knowlesi erythrocyte invasion genes, P. knowlesi normocyte binding protein Pknbpxa and Pknbpxb, influence parasitaemia and human disease progression. Pknbpxa and Pknbpxb reference DNA sequences were generated from five geographically and temporally distinct P. knowlesi patient isolates. Polymorphic regions of each gene (approximately 800 bp) were identified by haplotyping 147 patient isolates at each locus. Parasitaemia in the study cohort was associated with markers of disease severity including liver and renal dysfunction, haemoglobin, platelets and lactate, (r = ≥ 0.34, p = <0.0001 for all). Seventy-five and 51 Pknbpxa and Pknbpxb haplotypes were resolved in 138 (94%) and 134 (92%) patient isolates respectively. The haplotypes formed twelve Pknbpxa and two Pknbpxb allelic groups. Patients infected with parasites with particular Pknbpxa and Pknbpxb alleles within the groups had significantly higher parasitaemia and other markers of disease severity. Our study strongly suggests that P. knowlesi invasion gene variants contribute to parasite virulence. We focused on two invasion genes, and we anticipate that additional virulent loci will be identified in pathogen genome-wide studies. The multiple sustained entries of this diverse pathogen into the human population must give cause for concern to malaria elimination strategists in the Southeast Asian region.

Figure 1. P. knowlesi Pknbpxa organisation and diversity.

Schematic representation of Pknbpxa 9578 bp. (A) Exon 1 and the intron (solid line) are followed by exon II begining at nucleotide 389 (EU867791). Pknbpxa cysteine residues at codon positions 181,239,283,311 and 315 that are implicated in erythrocyte binding, Meyer, et al., , were within the haplotyping fragment and conserved in all patient isolates. (B)A fragment from nucleotide 389–8889 (8501bp) was amplified and sequenced in five reference isoates. Synonymous (short vertical lines) and non-synonymous (long vertical lines)mutations are marked. (C) Graphical representation of a sliding window plot of nucleotide diversity per site. Diversity (π) was calculated using DnaSP v5.10 with window length 400 bp and step size 25 bp. Maximum diversity (π = 0.024) was observed between nucleotide positions 389 and 1388 (hatched line).

Figure 2. P. knowlesi Pknbpxb organisation and diversity.

Schematic representation of Pknbpxb 9571 bp. (A) Exon 1 and the intron (solid line) are followed by exon II beginning at nucleotide 346 (EU867792). Pknbpxb cysteine residues at codon positions 193,254,298,326 and 332 that are implicated in erythrocyte binding, Meyer et al., , were not within the haplotyping fragment but were conserved in the five patient reference isolates. (B) A fragment from nucleotide1 to 3448 was amplified in five reference isolates. Synonymous (short vertical lines) and non-synonymous (long vertical lines)mutations are marked. (C) Graphical representation of a sliding window plot of nucleotide diversity per site. Diversity (π) was calculated using DnaSP v5.10 with window length 400 bp and step size 25 bp. Maximum diversity (π = 0.0056) was observed between nucleotide positions 2275 to 3156 (hatched line).

Figure 3. Pknbpxa minimum spanning haplotype network.

(A) 75 haplotypes were resolved in 138 patient isolates coloured nodes. Isolates in the KH273 dimorphic group are in green and those in the KH195 dimorphism in blue. Each node represents one haplotype and the size of the coloured nodes is relative to the frequency. The frequency number is given for all nodes with a frequency >1. Intermediary gray nodes represent missing haplotypes required to connect two different haplotypes. (B) Haplotypes with Pkbnpxa group 6 allele iii (913C) that had increased markers of disease severity are shown in yellow. P. knowlesi isolates with this mutation appear in 2 clusters within the KH195 dimorphism. (C) Haplotypes with Pknbpxa group 8 982 alleles are shown: 982T allele i (KH273 green); 982G allele ii (KH195 blue); 982C allele iii (KH195 pink). Group 8 alleles ii and iii had increased markers of disease severity when compared with allele i. There is one main cluster of 982C (pink) haplotypes with 5 additional and apparently un-connected to the main cluster that appear on the edges of the network. 982C (pink) haplotypes all occur in the KH195 dimorphic group (4a blue). Note that the boxed nodes also contain Pknbpxa 913C (4b). Haplotypes were generated using Arlequin v3.5.1.2 and the network drawn with Gephi v0.8.2 with manual editing to add the missing haplotypes. Haplotype groups were mapped onto the minimum spanning network by applying the analysis of molecular variance (AMOVA).

Figure 4. Pknbpxb minimum spanning haplotype network.

(A) 51 haplotypes were resolved in 134 patient isolates (Blue). Each node represents one haplotype and the size of the coloured nodes is relative to the frequency. The frequency number is given for all nodes with a frequency >1. Intermediary gray nodes represent missing haplotypes required to connect two different haplotypes. (B) Pknbpxb haplotype group 1. Haplotypes with allele ii Pkbnpxb2638A, lower haemoglobin and higher axillary temperature, are shown in brown radiating from a high frequency haplotype (f = 18). (C) Pknbpxb group 2 haplotypes, alleles i (blue), ii (green) appeared as discrete clusters Allele iii (pink) had increased markers of disease severity and formed 2 clusters. Four isolates were excluded and appear as larger grey nodes. Haplotypes with alleles ii and iii cluster together. Alleles shared with Pknbpxb group 1 are boxed. Haplotypes were generated using Arlequin v3.5.1.2 and the network drawn with Gephi v0.8.2 and manual edited to add the missing haplotypes markers. Haplotype groups were mapped onto the minimum spanning network by applying the analysis of molecular variance (AMOVA).

Figure 5. Linkage disequilibrium (LD), Pknbpxa and Pknbpxb.

The LD matrix was inferred with Haploview (Barrett et al, 2005) and an in-house script for data input in the X chromosome format suitable for haploid data. Pknbpxa alleles are to the left of the blue line and Pknbpxb to the right. The intensity of shading reflects the strength of linkage in the correlation between pairs of loci (r²), black being strong r² >0.8. Linkage between the two genes was detected between Pknbpxa positions 810 and 1105 marked1 and 2 respectively and Pknbpxb positions 2403 and 3110 marked 3 and 4 respectively. Linkage between these sites is shown as red triangles where D'>0.99 and LOD>2 but with otherwise low r² values.