4.7 Article

Drug-Resistance and Population Structure of Plasmodium falciparum Across the Democratic Republic of Congo Using High-Throughput Molecular Inversion Probes

Journal

JOURNAL OF INFECTIOUS DISEASES
Volume 218, Issue 6, Pages 946-955

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/infdis/jiy223

Keywords

Democratic Republic of the Congo; malaria; drug resistance; molecular inversion probe; targeted sequencing

Funding

  1. National Institutes of Health [R01AI107949-04, R21AI121465, K24AI134990, R01AI099473, T32GM107000]
  2. National Science Foundation [BCS-1339949]
  3. UK Medical Research Council [MR/N01507X/1]
  4. Royster Society
  5. Eunice Kennedy Shriver National Institute of Child Health and Development [P2C HD050924]
  6. Skills Development Fellowship - UK Medical Research Council (MRC)
  7. Skills Development Fellowship - UK Department for International Development (DFID) under the MRC/DFID Concordat agreement
  8. EDCTP2 program - European Union
  9. MRC [MR/N01507X/1, MR/R015600/1] Funding Source: UKRI

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A better understanding of the drivers of the spread of malaria parasites and drug resistance across space and time is needed. These drivers can be elucidated using genetic tools. Here, a novel molecular inversion probe (MIP) panel targeting all major drug-resistance mutations and a set of microsatellites was used to genotype Plasmodium falciparum infections of 552 children from the 2013-2014 Demographic and Health Survey conducted in the Democratic Republic of the Congo (DRC). Microsatellite-based analysis of population structure suggests that parasites within the DRC form a homogeneous population. In contrast, sulfadoxine-resistance markers in dihydropteroate synthase show marked spatial structure with ongoing spread of double and triple mutants compared with 2007. These findings suggest that parasites in the DRC remain panmictic despite rapidly spreading antimalarial-resistance mutations. Moreover, highly multiplexed targeted sequencing using MIPs emerges as a cost-effective method for elucidating pathogen genetics in complex infections in large cohorts.

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