BackgroundThe emergence of Plasmodium knowlesi in humans, which is in many cases misdiagnosed by microscopy as Plasmodium malariae due to the morphological similarity has contributed to the needs of detection and differentiation of malaria parasites. At present, nested PCR targeted on Plasmodium ssrRNA genes has been described as the most sensitive and specific method for Plasmodium detection. However, this method is costly and requires trained personnel for its implementation. Loop-mediated isothermal amplification (LAMP), a novel nucleic acid amplification method was developed for the clinical detection of P. knowlesi. The sensitivity and specificity of LAMP was evaluated in comparison to the results obtained via microscopic examination and nested PCR.MethodsLAMP assay was developed based on P. knowlesi genetic material targeting the apical membrane antigen-1 (AMA-1) gene. The method uses six primers that recognize eight regions of the target DNA and it amplifies DNA within an hour under isothermal conditions (65°C) in a water-bath.ResultsLAMP is highly sensitive with the detection limit as low as ten copies for AMA-1. LAMP detected malaria parasites in all confirm cases (n = 13) of P. knowlesi infection (sensitivity, 100%) and none of the negative samples (specificity, 100%) within an hour. LAMP demonstrated higher sensitivity compared to nested PCR by successfully detecting a sample with very low parasitaemia (< 0.01%).ConclusionWith continuous efforts in the optimization of this assay, LAMP may provide a simple and reliable test for detecting P. knowlesi malaria parasites in areas where malaria is prevalent.

BackgroundAmebiasis caused by Entamoeba histolytica is the third leading cause of death worldwide. This pathogenic amoeba is morphologically indistinguishable from E. dispar and E. moshkovskii, the non-pathogenic species. Polymerase chain reaction is the current method of choice approved by World Health Organization. Real-time PCR is another attractive molecular method for diagnosis of infectious diseases as post-PCR analyses are eliminated and turnaround times are shorter. The present work aimed to compare the results of Entamoeba species identification using the real-time assay against the established nested PCR method.MethodsIn this study, a total of 334 human faecal samples were collected from different Orang Asli settlements. Faecal samples were processed by direct wet smear and formalin ethyl acetate concentration methods followed by iodine staining and was microscopically examined for Entamoeba species and other intestinal parasites. Microscopically positive samples were then subject to nested PCR and real-time PCR.ResultsThe overall prevalence of Entamoeba infection was 19.5% (65/334). SK Posh Piah recorded highest Entamoeba prevalence (63.3%) while Kampung Kemensah had the lowest prevalence (3.7%) of Entamoeba. Microscopically positive samples were then tested by real-time PCR and nested PCR for the presence of Entamoeba histolytica, Entamoeba dispar, and Entamoeba moshkovskii infection. Real-time PCR showed higher Entamoeba detection (86.2%) compared to nested PCR (80%), although the McNemar test value showed no significant difference between the two methods (p = 0.221).ConclusionsThis study is the first in Malaysia to report the use of real-time PCR in identifying and differentiating the three Entamoeba infections. It is also proven to be more effective compared to the conventional nested PCR molecular method.

Abstract. In this study, three molecular assays (real-time multiplex polymerase chain reaction [PCR], merozoite surface antigen gene [MSP]-multiplex PCR, and the PlasmoNex Multiplex PCR Kit) have been developed for diagnosis of Plasmodium species. In total, 52 microscopy-positive and 20 malaria-negative samples were used in this study. We found that real-time multiplex PCR was the most sensitive for detecting P. falciparum and P. knowlesi. The MSPmultiplex PCR assay and the PlasmoNex Multiplex PCR Kit were equally sensitive for diagnosing P. knowlesi infection, whereas the PlasmoNex Multiplex PCR Kit and real-time multiplex PCR showed similar sensitivity for detecting P. vivax. The three molecular assays displayed 100% specificity for detecting malaria samples. We observed no significant differences between MSP-multiplex PCR and the PlasmoNex multiplex PCR kit (McNemar's test: P = 0.1489). However, significant differences were observed comparing real-time multiplex PCR with the PlasmoNex Multiplex PCR Kit (McNemar's test: P = 0.0044) or real-time multiplex PCR with MSP-multiplex PCR (McNemar's test: P = 0.0012).

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The emergence of potentially life-threatening zoonotic malaria caused by Plasmodium knowlesi nearly two decades ago has continued to challenge Malaysia healthcare. With a total of 376 P. knowlesi infections notified in 2008, the number increased to 2,609 cases in 2020 nationwide. Numerous studies have been conducted in Malaysian Borneo to determine the association between environmental factors and knowlesi malaria transmission. However, there is still a lack of understanding of the environmental influence on knowlesi malaria transmission in Peninsular Malaysia. Therefore, our study aimed to investigate the ecological distribution of human P. knowlesi malaria in relation to environmental factors in Peninsular Malaysia. A total of 2,873 records of human P. knowlesi infections in Peninsular Malaysia from 1st January 2011 to 31st December 2019 were collated from the Ministry of Health Malaysia and geolocated. Three machine learning-based models, maximum entropy (MaxEnt), extreme gradient boosting (XGBoost), and ensemble modeling approach, were applied to predict the spatial variation of P. knowlesi disease risk. Multiple environmental parameters including climate factors, landscape characteristics, and anthropogenic factors were included as predictors in both predictive models. Subsequently, an ensemble model was developed based on the output of both MaxEnt and XGBoost. Comparison between models indicated that the XGBoost has higher performance as compared to MaxEnt and ensemble model, with AUCROC values of 0.933 ± 0.002 and 0.854 ± 0.007 for train and test datasets, respectively. Key environmental covariates affecting human P. knowlesi occurrence were distance to the coastline, elevation, tree cover, annual precipitation, tree loss, and distance to the forest. Our models indicated that the disease risk areas were mainly distributed in low elevation (75–345 m above mean sea level) areas along the Titiwangsa mountain range and inland central-northern region of Peninsular Malaysia. The high-resolution risk map of human knowlesi malaria constructed in this study can be further utilized for multi-pronged interventions targeting community at-risk, macaque populations, and mosquito vectors.