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Real-time fluorescence loop-mediated isothermal amplification assays for detection of zoonotic malaria Plasmodium parasites

Lai MY, Abdullah ML, Lau YL

Acta Trop, 2024 May 11;255:107249.
PMID: 38740319 DOI: 10.1016/j.actatropica.2024.107249

BACKGROUND: Natural human infections by Plasmodium cynomolgi and P. inui have been reported recently and gain the substantial attention from Southeast Asian countries. Zoonotic transmission of non-human malaria parasites to humans from macaque monkeys occurred through the bites of the infected mosquitoes. The objective of this study is to establish real-time fluorescence loop-mediated isothermal amplification (LAMP) assays for the detection of zoonotic malaria parasites by combining real-time fluorescent technology with the isothermal amplification technique.
METHODS: By using 18S rRNA as the target gene, the primers for P. cynomolgi, P. coatneyi and P. inui were newly designed in the present study. Four novel real-time fluorescence LAMP assays were developed for the detection of P. cynomolgi, P. coatneyi, P. inui and P. knowlesi. The entire amplification process was completed in 60 min, with the assays performed at 65 °C. By using SYTO-9 as the nucleic acid intercalating dye, the reaction was monitored via real-time fluorescence signal.
RESULTS: There was no observed cross-reactivity among the primers from different species. All 70 field-collected monkey samples were successfully amplified by real-time fluorescence LAMP assays. The detection limit for P. cynomolgi, P. coatneyi and P. knowlesi was 5 × 109 copies/µL. Meanwhile, the detection limit of P. inui was 5 × 1010 copies/µL.
CONCLUSION: This is the first report of the detection of four zoonotic malaria parasites by real-time fluorescence LAMP approaches. It is an effective, rapid and simple-to-use technique. This presented platform exhibits considerable potential as an alternative detection for zoonotic malaria parasites.
Fulltext A review of the genus Rusa in the indo-malayan archipelago and conservation efforts

Ali NANG, Abdullah ML, Nor SAM, Pau TM, Kulaimi NAM, Naim DM

Saudi J Biol Sci, 2021 Jan;28(1):10-26.
PMID: 33424278 DOI: 10.1016/j.sjbs.2020.08.024

Genus Rusa, belonging to the deer family Cervidae is native to the Indo-Malaya Archipelago (IMA). However, detailed information on the Rusa genus in the IMA is limited. This review provides comprehensive information on the Rusa genus in the IMA including, threats and conservation efforts. There are four species of deer in Rusa genus, which is Sambar deer (Rusa unicolor), Javan deer (Rusa timorensis), Visayan spotted deer (Rusa alfredi) and Philippine deer (Rusa marianna). Despite their wide distribution in the South Asian and Southeast Asian regions, they are under serious threats. Some conservation efforts that are being done to protect and conserve them among others are; (1) facilities protection, (2) habitat enrichment programme, (3) Ex-situ conservation, (4) legislations, and (5) captive breeding. Conservation through genetics is also an important step in conserving these species. Recommendations for conservation of the genus are also discussed; 1. maintenance of ecosystem. 2. more effective monitoring system on the existing protected area. 3. ex-situ conservation, and 4. habitat monitoring.
Genetic polymorphism and clustering of the Plasmodium cynomolgi Duffy binding protein 1 region II of recent macaque isolates from Peninsular Malaysia

Latif ENM, Noordin NR, Shahari S, Amir A, Lau YL, Cheong FW, et al.

Parasitol Res, 2024 Jan 19;123(1):105.
PMID: 38240877 DOI: 10.1007/s00436-024-08125-0

Plasmodium cynomolgi is a simian malaria parasite that has been increasingly infecting humans. It is naturally present in the long-tailed and pig-tailed macaques in Southeast Asia. The P. cynomolgi Duffy binding protein 1 region II [PcDBP1(II)] plays an essential role in the invasion of the parasite into host erythrocytes. This study investigated the genetic polymorphism, natural selection and haplotype clustering of PcDBP1(II) from wild macaque isolates in Peninsular Malaysia. The genomic DNA of 50 P. cynomolgi isolates was extracted from the macaque blood samples. Their PcDBP1(II) gene was amplified using a semi-nested PCR, cloned into a plasmid vector and subsequently sequenced. The polymorphism, natural selection and haplotypes of PcDBP1(II) were analysed using MEGA X and DnaSP ver.6.12.03 programmes. The analyses revealed high genetic polymorphism of PcDBP1(II) (π = 0.026 ± 0.004; Hd = 0.996 ± 0.001), and it was under purifying (negative) selection. A total of 106 haplotypes of PcDBP1(II) were identified. Phylogenetic and haplotype analyses revealed two groups of PcDBP1(II). Amino acid length polymorphism was observed between the groups, which may lead to possible phenotypic difference between them.
Fulltext The prevalence of simian malaria in wild long-tailed macaques throughout Peninsular Malaysia

Shahari S, Bin Abdullah ML, Binti Isman Rohimly AA, Binti Ashrat N, Amir A, Atroosh WMM, et al.

Sci Rep, 2024 Mar 12;14(1):6023.
PMID: 38472278 DOI: 10.1038/s41598-024-54981-2

The parasite Plasmodium knowlesi has been the sole cause of malaria in Malaysia from 2018 to 2022. The persistence of this zoonotic species has hampered Malaysia's progress towards achieving the malaria-free status awarded by the World Health Organisation (WHO). Due to the zoonotic nature of P. knowlesi infections, it is important to study the prevalence of the parasite in the macaque host, the long-tailed macaque (Macaca fascicularis). Apart from P. knowlesi, the long-tailed macaque is also able to harbour Plasmodium cynomolgi, Plasmodium inui, Plasmodium caotneyi and Plasmodium fieldi. Here we report the prevalence of the 5 simian malaria parasites in the wild long-tailed macaque population in 12 out of the 13 states in Peninsular Malaysia using a nested PCR approach targeting the 18s ribosomal RNA (18s rRNA) gene. It was found that all five Plasmodium species were widely distributed throughout Peninsular Malaysia except for states with major cities such as Kuala Lumpur and Putrajaya. Of note, Pahang reported a malaria prevalence of 100% in the long-tailed macaque population, identifying it as a potential hotspot for zoonotic transmission. Overall, this study shows the distribution of the 5 simian malaria parasite species throughout Peninsular Malaysia, the data of which could be used to guide future malaria control interventions to target zoonotic malaria.
Natural Plasmodium infection in wild macaques of three states in peninsular Malaysia

Amir A, Shahari S, Liew JWK, de Silva JR, Khan MB, Lai MY, et al.

Acta Trop, 2020 Nov;211:105596.
PMID: 32589995 DOI: 10.1016/j.actatropica.2020.105596

Zoonotic cases of Plasmodium knowlesi account for most malaria cases in Malaysia, and humans infected with P. cynomolgi, another parasite of macaques have recently been reported in Sarawak. To date the epidemiology of malaria in its natural Macaca reservoir hosts remains little investigated. In this study we surveyed the prevalence of simian malaria in wild macaques of three states in Peninsular Malaysia, namely Pahang, Perak and Johor using blood samples from 103 wild macaques (collected by the Department of Wildlife and National Parks Peninsular Malaysia) subjected to microscopic examination and nested PCR targeting the Plasmodium small subunit ribosomal RNA gene. As expected, PCR analysis yielded significantly higher prevalence (64/103) as compared to microscopic examination (27/103). No relationship between the age and/or sex of the macaques with the parasitaemia and the Plasmodium species infecting the macaques could be identified. Wild macaques in Pahang had the highest prevalence of Plasmodium parasites (89.7%), followed by those of Perak (69.2%) and Johor (28.9%). Plasmodium inui and P. cynomolgi were the two most prevalent species infecting the macaques from all three states. Half of the macaques (33/64) harboured two or more Plasmodium species. These data provide a baseline survey, which should be extended by further longitudinal investigations that should be associated with studies on the bionomics of the anopheline vectors. This information will allow an accurate evaluation of the risk of zoonotic transmission to humans, and to elaborate effective strategies to control simian malaria.
Seroprevalence of Pteropine orthoreovirus in humans remain similar after nearly two decades (2001-2002 vs. 2017) in Tioman Island, Malaysia

Leong WJ, Quek XF, Tan HY, Wong KM, Muhammad HS, Mohamed NA, et al.

J Med Virol, 2022 02;94(2):771-775.
PMID: 34708881 DOI: 10.1002/jmv.27422

Pteropine orthoreovirus (PRV) is an emerging zoonotic respiratory virus that can be transmitted from bats to humans. In Malaysia, aside from PRV2P (Pulau virus) being isolated from Pteropus hypomelanus sampled in Tioman Island, PRV3M (Melaka virus), PRV4K (Kampar virus), and PRV7S (Sikamat virus) were all isolated from samples of patients who reported having a disease spectrum from acute respiratory distress to influenza-like illness and sometimes even with enteric symptoms such as diarrhea and abdominal pain. Screening of sera collected from human volunteers on Tioman Island in 2001-2002 demonstrated that 12.8% (14/109) were positive for PRV2P and PRV3M. Taking all these together, we aim to investigate the serological prevalence of PRV (including PRV4K and PRV7S) among Tioman Island inhabitants again with the assumption that the seroprevalence rate will remain nearly similar to the above reported if human exposure to bats is still happening in the island. Using sera collected from human volunteers on the same island in 2017, we demonstrated seroprevalence of 17.8% (28/157) against PRV2P and PRV3M, respectively. Seropositivity of 11.4% among Tioman Island inhabitants against PRV4K and PRV7S, respectively, was described in this study. In addition, the seroprevalence of 89.5% (17/19), 73.6% (14/19), 63.0% (12/19), and 73.6% (14/19) against PRV2P, PRV3M, PRV4K, and PRV7S, respectively, were observed among pteropid bats in the island. We revealed that the seroprevalence of PRV among island inhabitants remains nearly similar after nearly two decades, suggesting that potential spill-over events in bat-human interface areas in the Tioman Island. We are unclear whether such spillover was directly from bats to humans, as suspected for the PRV3M human cases, or from an intermediate host(s) yet to be identified. There is a high possibility of the viruses circulating among the bats as demonstrated by high seroprevalence against PRV in the bats.
Fulltext Developing forecasting model for future pandemic applications based on COVID-19 data 2020-2022

Wan Mohamad Nawi WIA, K Abdul Hamid AA, Lola MS, Zakaria S, Aruchunan E, Gobithaasan RU, et al.

PLoS One, 2023;18(5):e0285407.
PMID: 37172040 DOI: 10.1371/journal.pone.0285407

Improving forecasting particularly time series forecasting accuracy, efficiency and precisely become crucial for the authorities to forecast, monitor, and prevent the COVID-19 cases so that its spread can be controlled more effectively. However, the results obtained from prediction models are inaccurate, imprecise as well as inefficient due to linear and non-linear patterns exist in the data set, respectively. Therefore, to produce more accurate and efficient COVID-19 prediction value that is closer to the true COVID-19 value, a hybrid approach has been implemented. Thus, aims of this study is (1) to propose a hybrid ARIMA-SVM model to produce better forecasting results. (2) to investigate in terms of the performance of the proposed models and percentage improvement against ARIMA and SVM models. statistical measurements such as MSE, RMSE, MAE, and MAPE then conducted to verify that the proposed models are better than ARIMA and SVM models. Empirical results with three real datasets of well-known cases of COVID-19 in Malaysia show that, compared to the ARIMA and SVM models, the proposed model generates the smallest MSE, RMSE, MAE and MAPE values for the training and testing datasets, means that the predicted value from the proposed model is closer to the actual value. These results prove that the proposed model can generate estimated values more accurately and efficiently. As compared to ARIMA and SVM, our proposed models perform much better in terms of error reduction percentages for all datasets. This is demonstrated by the maximum scores of 73.12%, 74.6%, 90.38%, and 68.99% in the MAE, MAPE, MSE, and RMSE, respectively. Therefore, the proposed model can be the best and effective way to improve prediction performance with a higher level of accuracy and efficiency in predicting cases of COVID-19.