Microsatellites reveal high polymorphism and high potential for use in anti-malarial efficacy studies in areas with different transmission intensities in mainland Tanzania

Abstract

Abstract Background Tanzania is currently implementing therapeutic efficacy studies (TES) in areas of varying malaria transmission intensities as per the World Health Organization (WHO) recommendations. In TES, distinguishing reinfection from recrudescence is critical for the determination of anti-malarial efficacy. Recently, the WHO recommended genotyping polymorphic coding genes, merozoite surface proteins 1 and 2 (msp1 and msp2), and replacing the glutamate-rich protein (glurp) gene with one of the highly polymorphic microsatellites in Plasmodium falciparum to adjust the efficacy of antimalarials in TES. This study assessed the polymorphisms of six neutral microsatellite markers and their potential use in TES, which is routinely performed in Tanzania. Methods Plasmodium falciparum samples were obtained from four TES sentinel sites, Kibaha (Pwani), Mkuzi (Tanga), Mlimba (Morogoro) and Ujiji (Kigoma), between April and September 2016. Parasite genomic DNA was extracted from dried blood spots on filter papers using commercial kits. Genotyping was done using six microsatellites (Poly-α, PfPK2, TA1, C3M69, C2M34 and M2490) by capillary method, and the data were analysed to determine the extent of their polymorphisms and genetic diversity at the four sites. Results Overall, 83 (88.3%) of the 94 samples were successfully genotyped (with positive results for ≥ 50.0% of the markers), and > 50.0% of the samples (range = 47.6–59.1%) were polyclonal, with a mean multiplicity of infection (MOI) ranging from 1.68 to 1.88 among the four sites. There was high genetic diversity but limited variability among the four sites based on mean allelic richness (RS = 7.48, range = 7.27–8.03, for an adjusted minimum sample size of 18 per site) and mean expected heterozygosity (He = 0.83, range = 0.80–0.85). Cluster analysis of haplotypes using STRUCTURE, principal component analysis, and pairwise genetic differentiation (FST) did not reveal population structure or clustering of parasites according to geographic origin. Of the six markers, Poly-α was the most polymorphic, followed by C2M34, TA1 and C3M69, while M2490 was the least polymorphic. Conclusion Microsatellite genotyping revealed high polyclonality and genetic diversity but no significant population structure. Poly-α, C2M34, TA1 and C3M69 were the most polymorphic markers, and Poly-α alone or with any of the other three markers could be adopted for use in TES in Tanzania.