4.7 Article

Describing the current status of Plasmodium falciparum population structure and drug resistance within mainland Tanzania using molecular inversion probes

期刊

MOLECULAR ECOLOGY
卷 30, 期 1, 页码 100-113

出版社

WILEY
DOI: 10.1111/mec.15706

关键词

drug resistance; isolation‐ by‐ distance; malaria; molecular inversion probes; Plasmodium falciparum; population structure; Tanzania

资金

  1. National Institutes of Health [R01AI121558, R01AI139520, K24AI134990]
  2. National Malaria Control Program/Ministry of Health
  3. MRC [MR/R015600/1] Funding Source: UKRI

向作者/读者索取更多资源

The study utilized high-throughput Plasmodium genomic data to analyze parasite population structure and geographic distribution of drug resistance mutations in Tanzania nationwide. The results indicated clear genetic separation between parasites from the northern and southern regions, with more drug resistance mutations found in the northern districts. The Malaria Indicator Survey data corresponded with genetic findings, providing insights into local genetic diversity and transmission patterns of malaria parasites.
High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programmes, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania countrywide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, approximately separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from nearby districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts (including two infections carrying pfk13-R561H), and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared.

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