Rapid multiplexed nanopore amplicon sequencing to distinguish Plasmodium falciparum recrudescence from new infection in antimalarial drug trials

Evaluation of antimalarial drug efficacy against Plasmodium falciparum requires molecular correction to distinguish recrudescence from new infections by comparing parasite genotypes before treatment and in recurrent infections. We aimed to assess the utility of nanopore sequencing in providing rapid corrected drug efficacy estimates, particularly in patients from high-transmission settings where polyclonal infections are common. We optimized a multiplexed AmpSeq panel targeting six microhaplotypes to achieve high and uniform coverage. The assay's sensitivity and specificity for detecting minority clones in polyclonal infections and its reproducibility were evaluated using a range of mixtures of four P. falciparum laboratory strains at defined ratios. Genetic diversity across the microhaplotype markers was assessed using 20 paired patient samples from a clinical trial. A custom bioinformatics workflow was used to infer haplotypes from polyclonal infections, including minority clones, applying rigorous cutoff criteria for accurate haplotype calling. The nanopore AmpSeq assay provided uniform and high read coverage across all six microhaplotype markers in both laboratory strain mixtures and patient samples. It demonstrated high sensitivity in detecting minority clones (as low as 1:100:100:100 in the 3D7:K1:HB3:FCB1 strain mixtures), high specificity (false-positive haplotypes < 0.01%), and robust reproducibility (intra-assay: 98%; inter-assay: 97%). The markers exhibited high genetic diversity (highest for cpmp with H_E=0.99 and 28 unique haplotypes). Across the paired patient samples, the assay consistently distinguished recrudescence from new infections in 17/20 cases (85%) for all six markers. Our study demonstrates the feasibility and robustness of nanopore AmpSeq for distinguishing recrudescence from new infections in paired samples from clinical drug trials, offering a promising tool to obtain rapid corrected estimates of drug failure.