METHODS: Using the recently completed genome sequences from P. malariae, P. ovale and P. knowlesi, a set of 33 candidate cell surface and secreted blood-stage antigens was selected and expressed in a recombinant form using a mammalian expression system. These proteins were added to an existing panel of antigens from P. falciparum and P. vivax and the immunoreactivity of IgG, IgM and IgA immunoglobulins from individuals diagnosed with infections to each of the five different Plasmodium species was evaluated by ELISA. Logistic regression modelling was used to quantify the ability of the responses to determine prior exposure to the different Plasmodium species.
RESULTS: Using sera from European travellers with diagnosed Plasmodium infections, antigens showing species-specific immunoreactivity were identified to select a panel of 22 proteins from five Plasmodium species for serological profiling. The immunoreactivity to the antigens in the panel of sera taken from travellers and individuals living in malaria-endemic regions with diagnosed infections showed moderate power to predict infections by each species, including P. ovale, P. malariae and P. knowlesi. Using a larger set of patient samples and logistic regression modelling it was shown that exposure to P. knowlesi could be accurately detected (AUC = 91%) using an antigen panel consisting of the P. knowlesi orthologues of MSP10, P12 and P38.
CONCLUSIONS: Using the recent availability of genome sequences to all human-infective Plasmodium spp. parasites and a method of expressing Plasmodium proteins in a secreted functional form, an antigen panel has been compiled that will be useful to determine exposure to these parasites.
RESULTS: A noticeable variation between the RDT (Alltest Biotech, China) and nPCR results was observed, for RDT 78% (46/59) were P. falciparum positive, 6.8% (4/59) were co-infected with both P. falciparum and Plasmodium vivax, 15.3% (9/59) were negative by the RDT. However, when the nPCR was applied only 44.1% (26/59) and 55.9% (33/59) was P. falciparum positive and negative respectively. The pfhrp2 was further amplified form all nPCR positive samples. Only 17 DNA samples were positive from the 26 positive P. falciparum, interestingly, variation in band sizes was observed and further confirmed by DNA sequencing, and sequencing analysis revealed a high-level of genetic diversity of the pfhrp2 gene in the parasite population from the study area. However, despite extreme sequence variation, diversity of PfHRP2 does not appear to affect RDT performance.
RESULTS: In the erythrocyte-binding assay, binding level was determined by scoring the number of rosettes that were formed by erythrocytes surrounding transfected mammalian COS-7 cells which expressed PkDBPαII. The assay result revealed a significant difference in the binding level. The number of rosettes scored for Fya+/b+ was 1.64-fold higher than that of Fya+/b- (155.50 ± 34.32 and 94.75 ± 23.16 rosettes, respectively; t(6) = -2.935, P = 0.026).
CONCLUSIONS: The erythrocyte-binding assay provided a simple approach to quantitatively determine the binding level of PkDBPαII to the erythrocyte Duffy antigen. Using this assay, PkDBPαII was found to display higher binding to Fya+/b+ erythrocytes than to Fya+/b- erythrocytes.
METHODOLOGY/PRINCIPAL FINDINGS: Using in silico tools, we designed and expressed four novel P. knowlesi protein products to address the distinct lack of suitable serosurveillance tools: PkSERA3 antigens 1 and 2, PkSSP2/TRAP and PkTSERA2 antigen 1. Antibody prevalence to these antigens was determined by ELISA for three time-points post-treatment from a hospital-based clinical treatment trial in Sabah, East Malaysia (n = 97 individuals; 241 total samples for all time points). Higher responses were observed for the PkSERA3 antigen 2 (67%, 65/97) across all time-points (day 0: 36.9% 34/92; day 7: 63.8% 46/72; day 28: 58.4% 45/77) with significant differences between the clinical cases and controls (n = 55, mean plus 3 SD) (day 0 p<0.0001; day 7 p<0.0001; day 28 p<0.0001). Using boosted regression trees, we developed models to classify P. knowlesi exposure (cross-validated AUC 88.9%; IQR 86.1-91.3%) and identified the most predictive antibody responses.
CONCLUSIONS/SIGNIFICANCE: The PkSERA3 antigen 2 had the highest relative variable importance in all models. Further validation of these antigens is underway to determine the specificity of these tools in the context of multi-species infections at the population level.
METHODS: An indirect enzyme-linked immunosorbent assay (ELISA) was developed to evaluate the usefulness of USM.TOXO1 antigen for the detection of IgG antibodies against Toxoplasma gondii in human sera. Whereas the reactivity of the developed antigen against IgM antibody was evaluated by western blot and Dot enzyme immunoassay (dot-EIA) analysis.
RESULTS: The diagnostic performance of the new antigens in IgG ELISA was achieved at the maximum values of 85.43% and 81.25% for diagnostic sensitivity and specificity respectively. The USM.TOXO1 was also proven to be reactive with anti- T. gondii IgM antibody.
CONCLUSIONS: This finding makes the USM.TOXO1 antigen an attractive candidate for improving the toxoplasmosis serodiagnosis and demonstrates that multiepitope antigens could be a potential and promising diagnostic marker for the development of high sensitive and accurate assays.
METHODS: Blood samples were collected from P. knowlesi malaria patients within a period of 4 years (2008-2012). The pkmsp3 gene of the isolates was amplified via PCR, and subsequently cloned and sequenced. The full length pkmsp3 sequence was divided into Domain A and Domain B. Natural selection, genetic diversity, and haplotypes of pkmsp3 were analysed using MEGA6 and DnaSP ver. 5.10.00 programmes.
RESULTS: From 23 samples, 48 pkmsp3 sequences were successfully obtained. At the nucleotide level, 101 synonymous and 238 non-synonymous mutations were observed. Tests of neutrality were not significant for the full length, Domain A or Domain B sequences. However, the dN/dS ratio of Domain B indicates purifying selection for this domain. Analysis of the deduced amino acid sequences revealed 42 different haplotypes. Neighbour Joining phylogenetic tree and haplotype network analyses revealed that the haplotypes clustered into two distinct groups.
CONCLUSIONS: A moderate level of genetic diversity was observed in the pkmsp3 and only the C-terminal region (Domain B) appeared to be under purifying selection. The separation of the pkmsp3 into two haplotype groups provides further evidence of the existence of two distinct P. knowlesi types or lineages. Future studies should investigate the diversity of pkmsp3 among P. knowlesi isolates in North Borneo, where large numbers of human knowlesi malaria infection still occur.
METHODS: Blood samples from 78 knowlesi malaria patients were used. Forty-eight of the samples were from Peninsular Malaysia, and 30 were from Malaysia Borneo. The genomic DNA of the samples was extracted and used as template for the PCR amplification of the PkγRII. The PCR product was cloned and sequenced. The sequences obtained were analysed for genetic diversity and natural selection using MEGA6 and DnaSP (version 5.10.00) programmes. Genetic differentiation between the PkγRII of Peninsular Malaysia and North Borneo isolates was estimated using the Wright's FST fixation index in DnaSP (version 5.10.00). Haplotype analysis was carried out using the Median-Joining approach in NETWORK (version 4.6.1.3).
RESULTS: A total of 78 PkγRII sequences was obtained. Comparative analysis showed that the PkγRII have similar range of haplotype (Hd) and nucleotide diversity (π) with that of PkDBPαRII. Other similarities between PkγRII and PkDBPαRII include undergoing purifying (negative) selection, geographical clustering of haplotypes, and high inter-population genetic differentiation (FST index). The main differences between PkγRII and PkDBPαRII include length polymorphism and no departure from neutrality (as measured by Tajima's D statistics) in the PkγRII.
CONCLUSION: Despite the biological difference between PkγRII and PkDBPαRII, both generally have similar genetic diversity level, natural selection, geographical haplotype clustering and inter-population genetic differentiation index.