Peter Christensen1,2, Zbynek Bozdech3, Wanitda Watthanaworawit1, Laurent Rénia4,5, Benoît Malleret4,6, Clare Ling1,7, François Nosten1,7. 1. Shoklo Malaria Research Unit, Mahidol University, Maesot, Tak, 63110, Thailand. 2. Microbiology and Immunology, University of Otago, Dunedin, Otago, 9016, New Zealand. 3. School of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore. 4. Singapore Immunology Network, ASTAR, Singapore, 138648, Singapore. 5. ASTAR ID Labs, A*STAR, Singapore, 138648, Singapore. 6. Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117545, Singapore. 7. Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Abstract
Background: Targeted malaria elimination strategies require highly sensitive tests to detect low density malaria infections (LDMI). Commonly used methods for malaria diagnosis such as light microscopy and antigen-based rapid diagnostic tests (RDTs) are not sensitive enough for reliable identification of infections with parasitaemia below 200 parasites per milliliter of blood. While targeted malaria elimination efforts on the Thailand-Myanmar border have successfully used high sample volume ultrasensitive quantitative PCR (uPCR) to determine malaria prevalence, the necessity for venous collection and processing of large quantities of patient blood limits the widespread tractability of this method. Methods: Here we evaluated a real-time reverse transcription PCR (RT-qPCR) method that reduces the required sample volume compared to uPCR. To do this, 304 samples collected from an active case detection program in Kayin state, Myanmar were compared using uPCR and RT-qPCR. Results: Plasmodium spp. RT-qPCR confirmed 18 of 21 uPCR Plasmodium falciparum positives, while P. falciparum specific RT-qPCR confirmed 17 of the 21 uPCR P. falciparum positives. Combining both RT-qPCR results increased the sensitivity to 100% and specificity was 95.1%. Conclusion: Malaria detection in areas of low transmission and LDMI can benefit from the increased sensitivity of ribosomal RNA detection by RT-PCR, especially where sample volume is limited. Isolation of high quality RNA also allows for downstream analysis of malaria transcripts. Copyright:
Background: Targeted malaria elimination strategies require highly sensitive tests to detect low density malaria infections (LDMI). Commonly used methods for malaria diagnosis such as light microscopy and antigen-based rapid diagnostic tests (RDTs) are not sensitive enough for reliable identification of infections with parasitaemia below 200 parasites per milliliter of blood. While targeted malaria elimination efforts on the Thailand-Myanmar border have successfully used high sample volume ultrasensitive quantitative PCR (uPCR) to determine malaria prevalence, the necessity for venous collection and processing of large quantities of patient blood limits the widespread tractability of this method. Methods: Here we evaluated a real-time reverse transcription PCR (RT-qPCR) method that reduces the required sample volume compared to uPCR. To do this, 304 samples collected from an active case detection program in Kayin state, Myanmar were compared using uPCR and RT-qPCR. Results: Plasmodium spp. RT-qPCR confirmed 18 of 21 uPCR Plasmodium falciparum positives, while P. falciparum specific RT-qPCR confirmed 17 of the 21 uPCR P. falciparum positives. Combining both RT-qPCR results increased the sensitivity to 100% and specificity was 95.1%. Conclusion: Malaria detection in areas of low transmission and LDMI can benefit from the increased sensitivity of ribosomal RNA detection by RT-PCR, especially where sample volume is limited. Isolation of high quality RNA also allows for downstream analysis of malaria transcripts. Copyright:
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