Cryptic Diversity and Demographic Expansion of Plasmodium knowlesi Malaria Vectors in Malaysia

Although Malaysia is considered free of human malaria, there has been a growing number of Plasmodium knowlesi cases. This alarming trend highlighted the need for our understanding of this parasite and its associated vectors, especially considering the role of genetic diversity in the adaptation and evolution among vectors in endemic areas, which is currently a significant knowledge gap in their fundamental biology. Thus, this study aimed to investigate the genetic diversity of Anopheles balabacensis, Anopheles cracens, Anopheles introlatus, and Anopheles latens—the vectors for P. knowlesi malaria in Malaysia. Based on cytochrome c oxidase 1 (CO1) and internal transcribed spacer 2 (ITS2) markers, the genealogic networks of An. latens showed a separation of the haplotypes between Peninsular Malaysia and Malaysia Borneo, forming two distinct clusters. Additionally, the genetic distances between these clusters were high (2.3–5.2% for CO1) and (2.3–4.7% for ITS2), indicating the likely presence of two distinct species or cryptic species within An. latens. In contrast, no distinct clusters were observed in An. cracens, An. balabacensis, or An. introlatus, implying a lack of pronounced genetic differentiation among their populations. It is worth noting that there were varying levels of polymorphism observed across the different subpopulations, highlighting some levels of genetic variation within these mosquito species. Nevertheless, further analyses revealed that all four species have undergone demographic expansion, suggesting population growth and potential range expansion for these vectors in this regio

Spatial analyses of Plasmodium knowlesi vectors with reference to control interventions in Malaysia

Background Malaria parasites such as Plasmodium knowlesi, P. inui, and P. cynomolgi are spread from macaques to humans through the Leucosphyrus Group of Anopheles mosquitoes. It is crucial to know the distribution of these vectors to implement efective control measures for malaria elimination. Plasmodium knowlesi is the most predominant zoonotic malaria parasite infecting humans in Malaysia. Methods Vector data from various sources were used to create distribution maps from 1957 to 2021. A predictive statistical model utilizing logistic regression was developed using signifcant environmental factors. Interpolation maps were created using the inverse distance weighted (IDW) method and overlaid with the corresponding environmental variables. Results Based on the IDW analysis, high vector abundances were found in the southwestern part of Sarawak, the northern region of Pahang and the northwestern part of Sabah. However, most parts of Johor, Sabah, Perlis, Penang, Kelantan and Terengganu had low vector abundance. The accuracy test indicated that the model predicted sampling and non-sampling areas with 75.3% overall accuracy. The selected environmental variables were entered into the regression model based on their signifcant values. In addition to the presence of water bodies, elevation, temperature, forest loss and forest cover were included in the fnal model since these were signifcantly correlated. Anopheles mosquitoes were mainly distributed in Peninsular Malaysia (Titiwangsa range, central and northern parts), Sabah (Kudat, West Coast, Interior and Tawau division) and Sarawak (Kapit, Miri, and Limbang). The predicted Anopheles mosquito density was lower in the southern part of Peninsular Malaysia, the Sandakan Division of Sabah and the western region of Sarawak. Conclusion The study ofers insight into the distribution of the Leucosphyrus Group of Anopheles mosquitoes in Malaysia. Additionally, the accompanying predictive vector map correlates well with cases of P. knowlesi malaria. This research is crucial in informing and supporting future eforts by healthcare professionals to develop efective malaria control interventions

Plasmodium knowlesi infecting humans in Southeast Asia: What's next?

Plasmodium knowlesi, a simian malaria parasite, has been in the limelight since a large focus of human P. knowlesi infection was reported from Sarawak (Malaysian Borneo) in 2004. Although this infection is transmitted across Southeast Asia, the largest number of cases has been reported from Malaysia. The increasing number of knowlesi malaria cases has been attributed to the use of molecular tools for detection, but environmental changes including deforestation likely play a major role by increasing human exposure to vector mosquitoes, which coexist with the macaque host. In addition, with the reduction in human malaria transmission in Southeast Asia, it is possible that human populations are at a greater risk of P. knowlesi infection due to diminishing cross-species immunity. Furthermore, the possibility of increasing exposure of humans to other simian Plasmodium parasites such as Plasmodium cynomolgi and Plasmodium inui should not be ignored. We here review the current status of these parasites in humans, macaques, and mosquitoes to support necessary reorientation of malaria control and elimination in the affected areas

Correction: Pramasivan et al. Multiplex PCR Assay for the Identification of Four Species of the Anopheles Leucosphyrus Sub-Group in Malaysia. Insects 2022, 13, 195

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Gender beyond male and female: Occurrence of a gynandromorph in the Japanese encephalitis vector Culex sitiens (Diptera: Culicidae)

A gynandromorph of Culex sitiens Wiedemann (Diptera: Culicidae) was attracted to a human during a mosquito surveillance programme conducted in Kuala Lipis, Pahang, Malaysia on July 20, 2019. Gynandromorphism was observed in antennae, maxillary palps, legs and wings of the specimen, with distinct male characters on the left and female characters on the right, though the left maxillary palp is slightly shorter than the proboscis of a typical male. The abdomen, however, displays well-developed male genitalia. This study represents the first report of oblique gynandromorphism in Cx. sitiens, one of the vectors of Japanese encephalitis in Asia. © 2019 Elsevier B.V