Flexible and cost-effective genomic surveillance of P. falciparum malaria with targeted nanopore sequencing

Abstract Genomic surveillance of Plasmodium falciparum malaria can provide policy-relevant information about antimalarial drug resistance, diagnostic test failure, and the evolution of vaccine targets. Yet the large and low complexity genome of P. falciparum complicates the development of genomic methods, while resource constraints in malaria endemic regions can limit their deployment. Here, we demonstrate an approach for targeted nanopore sequencing of P. falciparum from dried blood spots (DBS) that enables cost-effective genomic surveillance of malaria in low-resource settings. We release software that facilitates flexible design of amplicon sequencing panels and use this software to design two target panels for P. falciparum. The panels generate 3–4 kbp reads for eight and sixteen targets respectively, covering key drug-resistance associated genes, diagnostic test antigens, polymorphic markers and the vaccine target csp. We validate our approach on mock and field samples, demonstrating robust sequencing coverage, accurate variant calls within coding sequences, the ability to explore P. falciparum within-sample diversity and to detect deletions underlying rapid diagnostic test failure

Median confirmed population malaria incidence for the entire HFCA (total) or just those identified at the health facility (HF).

RFDA (blue) and RFTAT (orange) arms are shown.</p

Seropositivity for each health facility by trial arm and age for any of AMA-1, GLURP-R2, or MSP1-19 antigens in a post-only simple random sample.

Data are fitted using a loess smoother function and 95% confidence intervals (grey shaded area). RFTAT control (black) and RFDA intervention (red) arms are shown accordingly. (TIF)</p

Population seroprevalence of a selection of long- and short-term malaria antigens.

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Day 1 individuals recruited for RCD follow-ups on days 30 and 90 by age and gender.

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Seropositivity by trial arm and age for any of AMA-1, GLURP-R2, or MSP1-19 antigens in a post-only simple random sample.

Data are fitted using a loess smoother function and 95% confidence intervals. RFTAT control (orange) and RFDA intervention (blue) arms are shown accordingly. Plots for individual catchments are shown in S3 Fig.</p

CONSORT checklist.

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S1 Protocol -

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Number of individuals enrolled and treated in the CoRE study by arm.

Number of individuals enrolled and treated in the CoRE study by arm.</p

Sensitivity analyses assessing the effect of removal of an antigen or a health facility on outcome.

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