• Journal Article

Surveillance for sulfadoxine-pyrimethamine resistant malaria parasites in the Lake and Southern Zones, Tanzania, using pooling and next-generation sequencing

Citation

Ngondi, J. M., Ishengoma, D. S., Doctor, S. M., Thwai, K. L., Keeler, C., Mkude, S., ... Gutman, J. (2017). Surveillance for sulfadoxine-pyrimethamine resistant malaria parasites in the Lake and Southern Zones, Tanzania, using pooling and next-generation sequencing. Malaria Journal, 16(1), 236. [236]. DOI: 10.1186/s12936-017-1886-9

Abstract

Background: Malaria in pregnancy (MiP) remains a major public health challenge in areas of high malaria transmission. Intermittent preventive treatment in pregnancy (IPTp) with sulfadoxine-pyrimethamine (SP) is recommended to prevent the adverse consequences of MiP. The effectiveness of SP for IPTp may be reduced in areas where the dhps581 mutation (a key marker of high level SP resistance) is found; this mutation was previously reported to be common in the Tanga Region of northern Tanzania, but there are limited data from other areas. The frequency of molecular markers of SP resistance was investigated in malaria parasites from febrile patients at health centres (HC) in seven regions comprising the Lake and Southern Zones of mainland Tanzania as part of the ongoing efforts to generate national-wide data of SP resistance.

Methods: A cross-sectional survey was conducted in the outpatient departments of 14 HCs in seven regions from April to June, 2015. 1750 dried blood spot (DBS) samples were collected (117 to 160 per facility) from consenting patients with positive rapid diagnostic tests for malaria, and no recent (within past 2 months) exposure to SP or related drugs. DNA was extracted from the DBS, pooled by HC, and underwent pooled targeted amplicon deep sequencing to yield estimates of mutated parasite allele frequency at each locus of interest.

Results: The dhps540 mutation was common across all 14 sites, ranging from 55 to 98.4% of sequences obtained. Frequency of the dhps581 mutation ranged from 0 to 2.4%, except at Kayanga HC (Kagera Region, Lake Zone) where 24.9% of sequences obtained were mutated. The dhfr164 mutation was detected only at Kanyanga HC (0.06%).

Conclusion: By pooling DNA extracts, the allele frequency of mutations in 14 sites could be directly determined on a single deep-sequencing run. The dhps540 mutant was very common at all locations. Surprisingly, the dhps581 was common at one health center, but rare in all the others, suggesting that there is geographic micro-heterogeneity in mutant distribution and that accurate surveillance requires inclusion of multiple sites. A better understanding of the effect of the dhps581 mutant on the efficacy of IPTp-SP is needed.