Reverse transcription PCR to detect low density malaria infections

• Main Authors: Christensen, Peter, Bozdech, Zbynek, Watthanaworawit, Wanitda, Imwong, Mallika, Rénia, Laurent, Malleret, Benoît, Ling, Clare, Nosten, François
• Other Authors: School of Biological Sciences
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Biological sciences; Science::Medicine; Low Density Malaria Infection; Plasmodium
• Online Access: https://hdl.handle.net/10356/163572
• Institution: Nanyang Technological University

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.