Malaria molecular surveillance in the Peruvian Amazon with a novel highly multiplexed Plasmodium falciparum Ampliseq assay

Molecular surveillance for malaria has great potential to support national malaria control programs (NMCPs). To bridge the gap between research and implementation, several applications (use cases) have been identified to align research, technology development, and public health efforts. For implementation at NMCPs, there is an urgent need for feasible and cost-effective tools. We designed a new highly-multiplexed deep sequencing assay (Pf AmpliSeq), compatible with benchtop sequencers, allowing for high accuracy sequencing at higher coverage and lower cost than WGS, targeting genomic regions of interest. The novelty of the assay is in its high number of targets multiplexed in one easy workflow, combining population genetic markers with 13 near full-length resistance genes, applicable for many different use cases. We provide a first proof-of-principle for hrp2 and hrp3 deletion detection using amplicon sequencing. Initial sequence data processing can be performed automatically, and subsequent variant analysis requires minimal bioinformatic skills using any tabulated data analysis program. The assay was validated with a retrospective sample collection (n = 254) from the Peruvian Amazon between 2003 and 2018. By combining phenotypic markers and a within-country 28-SNP-barcode, we were able to distinguish different lineages with multiple resistant ( dhfr/dhps/crt/mdr1 ) haplotypes and hrp2 and hrp3 deletions, increasing in recent years. We found no evidence suggesting the emergence of ART-resistance in Peru. These findings indicate a parasite population under drug pressure, but susceptible to current antimalarials, and demonstrates the added value of a highly multiplexed molecular tool to inform malaria strategies and surveillance systems. Importance While the power of next generation sequencing technologies to inform and guide malaria control programs has become broadly recognized, integration of genomic data for operational incorporation into malaria surveillance remains a challenge in most malaria endemic countries. The main obstacles include limited infrastructure and accessibility to high-throughput sequencing facilities and the need for local capacity to run in-country analysis of genomes at a large enough scale to be informative for surveillance. In addition, there is a lack of standardized laboratory protocols and automated analysis pipelines to generate reproducible and timely results useful for relevant stakeholders. With our standardized laboratory and bioinformatic workflow, malaria genetic surveillance data can be readily generated by surveillance researchers and malaria control programs in endemic countries, increasing ownership and ensuring timely results for informed decision and policy-making. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was funded by the Belgium Development Cooperation (DGD) under the Framework Agreement Program between DGD and ITM (FA4 Peru, 2017-2021) and the sample collections in 2018 were supported by VLIR-UOS (project PE2018TEA470A102; University of Antwerp). Funding for the sample collections lead by the U.S. Naval Medical Research Unit 6 (NAMRU-6) in 2011 and 2012 was provided by the Armed Forces Health Surveillance Division (AFHSD) and its Global Emerging Infections Surveillance and Response (GEIS) Section (P0144\_20\_N6_01, 2020-2021). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB of the Institute of Tropical Medicine Antwerp gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Sample meta data and drug resistant and hrp2 and hrp3 haplotypes, barcodes, lineages location, date, etc. is accessible at . Raw data (fastq), variant files (vcf), and scripts are available on request. All other data is included in the manuscript and supporting files.