Toxoplasma gondii is an obligate intracellular protozoan parasite that causes toxoplasmosis in humans. To date, little is known about T. gondii infection among the indigenous community, particularly in East Malaysia. This study was conducted to determine the status of T. gondii infection and to investigate associated risk factors among the indigenous community of Sarawak, East Malaysia. The sociodemographic data was obtained using a pretested questionnaire. A serological test was done to detect the presence of specific IgM and IgG antibodies against T. gondii in serum samples. A nested polymerase chain reaction (PCR) was used to determine acute infection among seropositive individuals. The overall seroprevalence of T. gondii infection was 50% (95% CI = 43.3 – 56.7). From this subset, 40.1%, 5.7%, and 4.2% were positive for anti-T. Gondii IgG antibodies, IgM, and both IgG and IgM, respectively. Four seropositive samples were amplified through PCR. None of the pregnant women tested positive for T. gondii infection based on the serological and PCR assays. A significant association was found between age, low monthly household income, unemployment, usage of untreated water and close contact with T. gondii seropositive cats. These results provide basic information on T. gondii infection and may be useful for policymakers to initiate prevention and control programs, especially amongst pregnant women and women of childbearing age in the indigenous community.

Malaria is the most common vector-borne parasitic disease in Malaysia and Thailand, especially in Malayan Borneo and along the Thailand border areas, but little is known about the genetic diversity of the parasite. Present study aims to investigate the genetic diversity of Plasmodium falciparum isolates in these two countries and eventually contributes to more effective malaria control strategies, particularly in vaccine and antimalarial treatment. One hundred and seventy three P. falciparum isolates were collected from Malaysia (n = 67) and Thailand (n = 106) and genotyped using nested PCR targeting the polymorphic region of MSP-1, block 2. Sequence analysis was conducted to investigate the allele diversity of the isolates. Three allelic families were identified in Malaysian and Thailand P. falciparum isolates, MAD20, K1 and RO33. Sequence analysis revealed that there were 5 different MAD20, 1 K1 and 2 different RO33 for Malaysian isolates. Thailand isolates exhibited greater polymorphism because there were 13 different MAD20, 6 different K1 and 2 different RO33 identified in this study. Multiclonal infections were observed for the isolates in both countries, however, low multiplicity of infection (MOI) was observed for Malaysian (1.1) and Thailand (1.2) isolates. Phylogenetic analysis showed that P. falciparum isolates of Malaysia and Thailand were clustered in the same group for all the allelic families. Population structure of P. falciparum isolates in Malaysia and Thailand exhibit extensive genetic polymorphism but showed high similarities as well as comparable MOI.

Plasmodium knowlesi is the most common zoonotic parasite associated with human malaria infection in Malaysia. Apical membrane antigen 1 (AMA1) protein in the parasite plays a critical role in parasite invasion into host cells. To date, there is no complete three-dimensional ectodomain structure of P. knowlesi AMA1 (PkAMA1) protein. The knowledge of a protein structure is important to understand the protein molecular functions. Three in silico servers with respective structure prediction methods were used in this study, i.e., SWISS-MODEL for homology modeling and Phyre2 for protein threading, which are template-based modeling, while I-TASSER for template-free ab initio modeling. Two query sequences were used in the study, i.e., native ectodomain of PkAMA1 strain H protein designated as PkAMA1-H and a modified PkAMA1 (mPkAMA1) protein sequence in adaptation for Pichia pastoris expression. The quality of each model was assessed by ProSA-web, QMEAN and SAVES v6.0 (ERRAT, Verify3D and Ramachandran plot) servers. Generated models were then superimposed with two models of Plasmodium AMA1 deposited in Protein Data Bank (PDB), i.e., PkAMA1 (4UV6.B) and Plasmodium vivax AMA1 (PvAMA1, 1W81) protein structures for similarity assessment, quantified by root-meansquare deviation (RMSD) value. SWISS-MODEL, Phyre2 and I-TASSER server generated two, one and five models, respectively. All models are of good quality according to ProSA-web assessment. Based on the average values of model quality assessment and superimposition, the models that recorded highest values for most parameters were selected as best predicted models, i.e., model 2 for both PkAMA1-H and mPkAMA1 from SWISS-MODEL as well as model 1 of PkAMA1-H and model 3 of mPkAMA1 from I-TASSER. Template-based method is useful if known template is available, but template-free method is more suitable if there is no known available template. Generated models can be used as guidance in further protein study that requires protein structural data, i.e., protein-protein interaction study.

Malaria caused by Plasmodium knowlesi species has become a public health concern, especially in Malaysia. Plasmodium knowlesi parasite which originates from the macaque species, infects human through the bite of the Anopheles mosquitoes. Research on malaria vaccine has been a continuous effort to eradicate the malaria infection, yet there is no vaccine against P. knowlesi malaria to date. Apical membrane antigen 1 (AMA1) is a unique surface protein of all apicomplexan parasites that plays a crucial role in parasite-host cell invasion and thus has been a long-standing malaria vaccine candidate. The selection of protective epitopes in silico has led to significant advances in the design of the vaccine. The present study aimed to employ bioinformatics tools to predict the potential immunogenic B- and T-cell epitopes in designing malaria vaccine targeting P. knowlesi AMA1 (PkAMA1). B-cell epitopes were predicted using four bioinformatics tools, i.e., BepiPred, ABCpred, BcePred, and IEDB servers whereas T-cell epitopes were predicted using two bioinformatics servers, i.e., NetMHCpan4.1 and NetMHCIIpan-4.0 targeting human major histocompatibility complex (MHC) class I and class II molecules, respectively. The antigenicity of the selected epitopes computed by both B- and T-cell predictors were further analyzed using the VaxiJen server. The results demonstrated that PkAMA1 protein encompasses multi antigenic regions that have the potential for the development of multi-epitope vaccine. Two B- and T-cell epitopes consensus regions, i.e., NSGIRIDLGEDAEVGNSKYRIPAGKCP (codons 28-54) and KTHAASFVIAEDQNTSY RHPAVYDEKNKT (codons 122-150) at domain I (DI) of PkAMA1 were reported. Advancement of bioinformatics in characterization of the target protein may facilitate vaccine development especially in vaccine design which is costly and cumbersome process. Thus, comprehensive B-cell and T-cell epitope prediction of PkAMA1 offers a promising pipeline for the development and design of multi-epitope vaccine against P. knowlesi.

Soil-transmitted helminth (STH) infections, mainly caused by Ascaris lumbricoides, Trichuris trichiura, and hookworms, are among the most common intestinal parasites that infect humans. The infections are widely distributed throughout tropical and subtropical countries, including Malaysia, particularly in underprivileged communities. Microscopic and culture techniques have been used as a gold standard for diagnostic techniques. However, these methods yield low sensitivity and specificity, laborious and time-consuming. Therefore, simple, rapid, and accurate alternative methods are needed for the simultaneous detection of STH infections. Although advanced technologies such as real-time multiplex PCR have been established, the use of this technique as a routine diagnostic is limited due to the high cost of the instrument. Therefore, a single-round multiplex conventional PCR assay for rapid detection of four STH species in the fecal sample was developed in this study. To perform the single-round multiplex PCR, each pair of species-specific primers was selected from target genes, including Ancylostoma duodenale (Internal Transcribed Spacer 2; accession No. AJ001594; 156 base pair), Necator americanus (ITS 2; accession No. AJ001599; 225 base pair), Ascaris lumbricoides (Internal Transcribed Spacer 1; accession No. AJ000895; 334 base pair) and Trichuris triciura (partial ITS 1, 5.8s rRNA and partial ITS 2; accession No. AM992981; 518 base pair). The results showed that the newly designed primers could detect the DNA of STH at low concentrations (0.001 ng/μl) with no cross-amplification with other species. This assay enables the differentiation of single infections as well as mixed infections. It could be used as an alternative and is a convenient method for the detection of STHs, especially for the differentiation of N. americanus and A. duodenale.

Diseases such as malaria, dengue, Zika and chikungunya remain endemic in many countries. Setting and deploying traps to capture the host/vector species are fundamental to understand their density and distributions. Human effort to manage the trap data accurately and timely is an exhaustive endeavour when the study area expands and period prolongs. One stop mobile app to manage and monitor the process of targeted species trapping, from field to laboratory level is still scarce. Toward this end, we developed a new mobile app named “PesTrapp” to acquire the vector density index based on the mobile updates of ovitraps and species information in field and laboratory. This study aimed to highlight the mobile app’s development and design, elucidate the practical user experiences of using the app and evaluate the preliminary user assessment of the mobile app. The mobile app was developed using mobile framework and database. User evaluation of the mobile app was based on the adjusted Mobile App Rating Scale and Standardized User Experience Percentile Rank Questionnaire. The process flows of system design and detailed screen layouts were described. The user experiences with and without the app in a project to study Aedes surveillance in six study sites in Selangor, Malaysia were elucidated. The overall mean user evaluation score of the mobile app was 4.0 out of 5 (SD=0.6), reflects its acceptability of the users. The PesTrapp, a one-stop solution, is anticipated to improve the entomological surveillance work processes. This new mobile app can contribute as a tool in the vector control countermeasure strategies.