Kennedy Kassaza1,2, Anna C Long3, Jennifer M McDaniels3, Mharlove Andre3, Wasswa Fredrickson2, Dan Nyehangane1, Patrick Orikiriza1, Darwin J Operario4, Joel Bazira2, Juliet A Mwanga-Amumpaire1,5, Christopher C Moore4, Jennifer L Guler6,7, Yap Boum8,9. 1. Epicentre Mbarara Research Centre, Mbarara, Uganda. 2. Department of Microbiology, Mbarara University of Science and Technology, Mbarara, Uganda. 3. Department of Biology, University of Virginia, Box 400328, 22904, Charlottesville, VA, USA. 4. Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, 22904, USA. 5. Department of Pediatrics and Child Health, Mbarara University of Science and Technology, Mbarara, Uganda. 6. Department of Biology, University of Virginia, Box 400328, 22904, Charlottesville, VA, USA. jlg5fw@virginia.edu. 7. Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, VA, 22904, USA. jlg5fw@virginia.edu. 8. Epicentre Mbarara Research Centre, Mbarara, Uganda. yap.boum@epicentre.msf.org. 9. Department of Microbiology, Mbarara University of Science and Technology, Mbarara, Uganda. yap.boum@epicentre.msf.org.
Abstract
BACKGROUND: Chloroquine (CQ) resistance is conferred by mutations in the Plasmodium falciparum CQ resistance transporter (pfcrt). Following CQ withdrawal for anti-malarial treatment, studies across malaria-endemic countries have shown a range of responses. In some areas, CQ sensitive parasites re-emerge, and in others, mutant haplotypes persist. Active surveillance of resistance mutations in clinical parasites is essential to inform treatment regimens; this effort requires fast, reliable, and cost-effective methods that work on a variety of sample types with reagents accessible in malaria-endemic countries. METHODS: Quantitative PCR followed by High-Resolution Melt (HRM) analysis was performed in a field setting to assess pfcrt mutations in two groups of clinical samples from Southwestern Uganda. Group 1 samples (119 in total) were collected in 2010 as predominantly Giemsa-stained slides; Group 2 samples (125 in total) were collected in 2015 as blood spots on filter paper. The Rotor-Gene Q instrument was utilized to assess the impact of different PCR-HRM reagent mixes and the detection of mixed haplotypes present in the clinical samples. Finally, the prevalence of the wild type (CVMNK) and resistant pfcrt haplotypes (CVIET and SVMNT) was evaluated in this understudied Southwestern region of Uganda. RESULTS: The sample source (i.e. Giemsa-stained slides or blood spots) and type of LCGreen-based reagent mixes did not impact the success of PCR-HRM. The detection limit of 10- 5 ng and the ability to identify mixed haplotypes as low as 10 % was similar to other HRM platforms. The CVIET haplotype predominated in the clinical samples (66 %, 162/244); however, there was a large regional variation between the sample groups (94 % CVIET in Group 1 and 44 % CVIET in Group 2). CONCLUSIONS: The HRM-based method exhibits the flexibility required to conduct reliable assessment of resistance alleles from various sample types generated during the clinical management of malaria. Large regional variations in CQ resistance haplotypes across Southwestern Uganda emphasizes the need for continued local parasite genotype assessment to inform anti-malarial treatment policies.
BACKGROUND:Chloroquine (CQ) resistance is conferred by mutations in the Plasmodium falciparum CQ resistance transporter (pfcrt). Following CQ withdrawal for anti-malarial treatment, studies across malaria-endemic countries have shown a range of responses. In some areas, CQ sensitive parasites re-emerge, and in others, mutant haplotypes persist. Active surveillance of resistance mutations in clinical parasites is essential to inform treatment regimens; this effort requires fast, reliable, and cost-effective methods that work on a variety of sample types with reagents accessible in malaria-endemic countries. METHODS: Quantitative PCR followed by High-Resolution Melt (HRM) analysis was performed in a field setting to assess pfcrt mutations in two groups of clinical samples from Southwestern Uganda. Group 1 samples (119 in total) were collected in 2010 as predominantly Giemsa-stained slides; Group 2 samples (125 in total) were collected in 2015 as blood spots on filter paper. The Rotor-Gene Q instrument was utilized to assess the impact of different PCR-HRM reagent mixes and the detection of mixed haplotypes present in the clinical samples. Finally, the prevalence of the wild type (CVMNK) and resistant pfcrt haplotypes (CVIET and SVMNT) was evaluated in this understudied Southwestern region of Uganda. RESULTS: The sample source (i.e. Giemsa-stained slides or blood spots) and type of LCGreen-based reagent mixes did not impact the success of PCR-HRM. The detection limit of 10- 5 ng and the ability to identify mixed haplotypes as low as 10 % was similar to other HRM platforms. The CVIET haplotype predominated in the clinical samples (66 %, 162/244); however, there was a large regional variation between the sample groups (94 % CVIET in Group 1 and 44 % CVIET in Group 2). CONCLUSIONS: The HRM-based method exhibits the flexibility required to conduct reliable assessment of resistance alleles from various sample types generated during the clinical management of malaria. Large regional variations in CQ resistance haplotypes across Southwestern Uganda emphasizes the need for continued local parasite genotype assessment to inform anti-malarial treatment policies.
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