Reverse transcription PCR to detect low density malaria infections
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 identificatio...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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2022
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| Online Access: | https://hdl.handle.net/10356/163572 |
| _version_ | 1811683866204700672 |
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| author | Christensen, Peter Bozdech, Zbynek Watthanaworawit, Wanitda Imwong, Mallika Rénia, Laurent Malleret, Benoît Ling, Clare Nosten, François |
| author2 | School of Biological Sciences |
| author_facet | School of Biological Sciences Christensen, Peter Bozdech, Zbynek Watthanaworawit, Wanitda Imwong, Mallika Rénia, Laurent Malleret, Benoît Ling, Clare Nosten, François |
| author_sort | Christensen, Peter |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T04:19:32Z |
| format | Journal Article |
| id | ntu-10356/163572 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:19:32Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1635722023-02-28T17:10:47Z Reverse transcription PCR to detect low density malaria infections Christensen, Peter Bozdech, Zbynek Watthanaworawit, Wanitda Imwong, Mallika Rénia, Laurent Malleret, Benoît Ling, Clare Nosten, François School of Biological Sciences Science::Biological sciences Science::Medicine Low Density Malaria Infection Plasmodium 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. Agency for Science, Technology and Research (A*STAR) Published version This study was supported by the Wellcome Trust through a strategic award “Eliminating malaria to counter artemisinin resistance” [101148, https://doi.org/10.35802/101148]. Funding was also obtained from the following sources; the Bill and Melinda Gates Foundation; The Singapore Immunology Network, A*STAR core fund; the NUHS start-up funding [NUHSRO/2018/006/SU/01]; NUHS seed fund [NUHSRO/2018/094/T1]; the Wellcome Trust Mahidol University Oxford Tropical Medicine Research Programme and the New Zealand HRC eASIA [17/678] project grant. 2022-12-09T07:39:21Z 2022-12-09T07:39:21Z 2022 Journal Article Christensen, P., Bozdech, Z., Watthanaworawit, W., Imwong, M., Rénia, L., Malleret, B., Ling, C. & Nosten, F. (2022). Reverse transcription PCR to detect low density malaria infections. Wellcome Open Research, 6, 39-. https://dx.doi.org/10.12688/wellcomeopenres.16564.3 2398-502X https://hdl.handle.net/10356/163572 10.12688/wellcomeopenres.16564.3 2-s2.0-85132600241 6 39 en NUHSRO/2018/006/SU/01 NUHSRO/2018/094/T1 Wellcome Open Research © 2022 Christensen P et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf |
| spellingShingle | Science::Biological sciences Science::Medicine Low Density Malaria Infection Plasmodium Christensen, Peter Bozdech, Zbynek Watthanaworawit, Wanitda Imwong, Mallika Rénia, Laurent Malleret, Benoît Ling, Clare Nosten, François Reverse transcription PCR to detect low density malaria infections |
| title | Reverse transcription PCR to detect low density malaria infections |
| title_full | Reverse transcription PCR to detect low density malaria infections |
| title_fullStr | Reverse transcription PCR to detect low density malaria infections |
| title_full_unstemmed | Reverse transcription PCR to detect low density malaria infections |
| title_short | Reverse transcription PCR to detect low density malaria infections |
| title_sort | reverse transcription pcr to detect low density malaria infections |
| topic | Science::Biological sciences Science::Medicine Low Density Malaria Infection Plasmodium |
| url | https://hdl.handle.net/10356/163572 |
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