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

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

Laboratory markers of disease severity in Plasmodium knowlesi infection: a case control study

This study was funded by the Medical Research Council (MRC) UK; Grant number G0801971, and the London School of Hygiene and Tropical Medicine (Trust Funds award)Background: Plasmodium knowlesi malaria causes severe disease in up to 10% of cases in Malaysian Borneo and has a mortality rate of 1 - 2%. However, laboratory markers with the ability to identify patients at risk of developing complications have not yet been assessed as they have for other species of Plasmodium. Methods: A case control study was undertaken in two hospitals in Sarikei and Sibu, Malaysian Borneo. One hundred and ten patients with uncomplicated (n = 93) and severe (n = 17) P. knowlesi malaria were studied. Standardized pigment-containing neutrophil (PCN) count, parasite density and platelet counts were determined and analysed by logistic regression and receiver operating characteristic (ROC) analysis. Results: The PCN count was strongly associated with risk of disease severity. Patients with high parasite density (>= 35,000/mu l) or with thrombocytopaenia (= 35,000/mu l or >= 1% or a platelet count <= 45,000/mu l can be regarded at risk of developing complications and should be managed according to current WHO guidelines for the treatment of severe malaria.Publisher PDFPeer reviewe

Burkholderia pseudomallei Isolates from Sarawak Malaysian Borneo Are Predominantly Susceptible to Aminoglycosides and Macrolides

Melioidosis is a potentially fatal disease caused by the saprophytic bacterium Burkholderia pseudomallei. Resistance to gentamicin is generally a hallmark of B. pseudomallei, and gentamicin is a selective agent in media used for diagnosis of melioidosis. In this study, we determined the prevalence and mechanism of gentamicin susceptibility found in B. pseudomallei isolates from Sarawak, Malaysian Borneo. We performed multilocus sequence typing and antibiotic susceptibility testing on 44 B. pseudomallei clinical isolates from melioidosis patients in Sarawak district hospitals. Whole-genome sequencing was used to identify the mechanism of gentamicin susceptibility. A novel allelic-specific PCR was designed to differentiate gentamicin-sensitive isolates from wild-type B. pseudomallei. A reversion assay was performed to confirm the involvement of this mechanism in gentamicin susceptibility. A substantial proportion (86%) of B. pseudomallei clinical isolates in Sarawak, Malaysian Borneo, were found to be susceptible to the aminoglycoside gentamicin, a rare occurrence in other regions where B. pseudomallei is endemic. Gentamicin sensitivity was restricted to genetically related strains belonging to sequence type 881 or its single-locus variant, sequence type 997. Whole-genome sequencing identified a novel nonsynonymous mutation within amrB, encoding an essential component of the AmrAB-OprA multidrug efflux pump. We confirmed the role of this mutation in conferring aminoglycoside and macrolide sensitivity by reversion of this mutation to the wild-type sequence. Our study demonstrates that alternative B. pseudomallei selective media without gentamicin are needed for accurate melioidosis laboratory diagnosis in Sarawak. This finding may also have implications for environmental sampling of other locations to test for B. pseudomallei endemicity

Linkage disequilibrium (LD), <i>Pknbpxa</i> and <i>Pknbpxb</i>.

<p>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. <i>Pknbpxa</i> alleles are to the left of the blue line and <i>Pknbpxb</i> 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 <i>Pknbpxa</i> positions 810 and 1105 marked1 and 2 respectively and <i>Pknbpxb</i> 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.</p

<i>P. knowlesi Pknbpxb</i> organisation and diversity.

<p>Schematic representation of <i>Pknbpxb</i> 9571 bp. (<b>A</b>) 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 <i>et al</i>., <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003086#pntd.0003086-Bei1" target="_blank">[23]</a>, were not within the haplotyping fragment but were conserved in the five patient reference isolates. (<b>B</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. (<b>C</b>) Graphical representation of a sliding window plot of nucleotide diversity per site. Diversity (<b>π</b>) was calculated using DnaSP v5.10 with window length 400 bp and step size 25 bp. Maximum diversity (<b>π</b> = 0.0056) was observed between nucleotide positions 2275 to 3156 (hatched line).</p

<i>P. knowlesi Pknbpxa</i> organisation and diversity.

<p>Schematic representation of <i>Pknbpxa</i> 9578 bp. (<b>A</b>) 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, <i>et al.</i>, <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0003086#pntd.0003086-Bei1" target="_blank">[23]</a>, were within the haplotyping fragment and conserved in all patient isolates. (<b>B</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. (<b>C</b>) Graphical representation of a sliding window plot of nucleotide diversity per site. Diversity (<b>π</b>) was calculated using DnaSP v5.10 with window length 400 bp and step size 25 bp. Maximum diversity (<b>π</b> = 0.024) was observed between nucleotide positions 389 and 1388 (hatched line).</p

<i>Pknbpxa</i> and <i>Pknbpxb</i> reference and haplotyping sequence diversity.

<p>n = number of sequences sampled; BP = number of sites analyzed (all within coding region and there were no gaps); SNP = number of polymorphic sites; NS = number of non-synonymous substitutions; S = number of synonymous substitutions; <b>π</b> = average pairwise nucleotide diversity calculated using Jukes-Cantor correction with standard deviation in parenthesis calculated using DnaSP v 5.10.01; d = nucleotide diversity calculated using Tamura's three-parameter model with standard error in parentheses calculated using MEGA v 5.05</p

<i>Pknbpxb </i>minimum spanning haplotype network.

<p>(<b>A</b>) 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>B</b>) <i>Pknbpxb</i> haplotype group 1. Haplotypes with allele ii <i>Pkbnpxb</i>2638A, lower haemoglobin and higher axillary temperature, are shown in brown radiating from a high frequency haplotype (f = 18). (<b>C</b>) <i>Pknbpxb</i> 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 <i>Pknbpxb</i> 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).</p