Development of an Oxford nanopore sequencing technology-based whole genome sequencing method for Plasmodium...

Whole genome sequencing (WGS) is critical for malaria molecular surveillance (MMS). While short-read platforms have been widely used for Plasmodium falciparum genomics; they have limitations in resolving repetitive regions and structural variation in this highly complex genome. Long-read technologies, such as those developed by Oxford nanopore technologies (ONT), offer complementary capabilities and may be particularly suitable for low-resource settings. We optimized an ONT-based WGS protocol for P. falciparum from DBS and whole blood samples. Laboratory strains (3D7, HB3, and Dd2) were mixed with whole blood to create mock infections and dried blood spots (DBS). DNA was extracted using Qiagen or Tween-Chelex 100, and parasite DNA was enriched using McrBC/MspJI digestion, NEBNext microbiome DNA enrichment Kit (NMDEK), and selective whole genome amplification (sWGA). Parasite and human DNA levels were quantified by multiplex qPCR. Sequencing was performed on ONT (R10.4.1 flow cell). The protocol was validated with? clinical samples from a therapeutic efficacy study. Tween-Chelex 100 had a higher DNA yield compared to Qiagen kit (2-4 Ct value difference), though Qiagen extractions gave longer reads (median 2791 vs. 2252 bp). NMDEK effectively depleted human DNA by increasing the Ct value of β-tubulin human gene by ~ 10 cycles, while sWGA increased parasite DNA. Combined enrichment yielded > 75% parasite DNA at 100 p/µl and > 90% genome coverage. WGS of mock and clinical samples achieved median read lengths > 2 kb, > 30× depth, and 99.8% accuracy. Whole blood outperformed DBS in depth and coverage. ONT WGS showed high concordance with Sanger sequencing and detected additional mutations and structural variants, including pfmdr1 and pfgch1 copy number variations. The optimized ONT-WGS protocol enabled accurate, high-coverage sequencing from whole blood and DBS. It provides a practical option for generating long-read data with relatively rapid turnaround and modest infrastructure requirements, supporting its application for MMS in malaria-endemic settings.