Background

Surveillance of Plasmodium parasites has been identified by the World Health Organization (WHO) as one of the essential pillars to move towards malaria elimination in its endemic areas (WHO, 2019). Molecular parasite genotyping tools can strengthen malaria surveillance systems by monitoring the emergence and spread of drug resistance, histidine rich protein 2 and 3 (hrp2 and hrp3) deletions, quantification of malaria importation risk, and characterization of changing transmission intensity. As molecular surveillance platforms transition from proof-of-concept research studies to operational incorporation into national malaria control programs (NMCPs), simple standardized laboratory protocols feasible on benchtop sequencers and automated analysis pipelines are necessary to generate reproducible results and decrease the time from sample collection to results, thereby ensuring rapid turnover of up-to-date reports for decision making and policy (WHO, 2016; MPA Committee, 2019). Various methods have been developed to investigate drug resistance markers, usually based on the amplification of loci of interest using PCR-based techniques, with amplicons detected in real time assays by amplicon sequencing (Taylor et al., 2013; Menard et al., 2016; Nsanzabana et al., 2018), or analyzed using restriction fragment length polymorphism (Eldin de Pecoulas et al., 1995; Duraisingh et al., 1998). In the past, population surveillance widely utilized genotyping tools targeting surface antigens by PCR to distinguish parasite clones (Falk et al., 2006; Koepfli et al., 2009), followed by panels of microsatellites (MS) that are not under evolutionary selection pressure and are, therefore, more suitable to inform population genetic changes (Anderson et al., 2000; Imwong et al., 2007; Karunaweera et al., 2008). More recently, genome-wide single nucleotide polymorphism (SNP) panels, capable of defining a molecular barcode to capture the diversity of parasite populations, have been developed and can be investigated with methods such as microarrays, real-time PCR, and deep sequencing (Daniels et al., 2008, 2013 and 2015; Neafsey et al., 2008; Baniecki et al., 2015; Koepfli and Mueller, 2017; Fola et al., 2020; Tessema et al., 2022). Surveys to detect these gene deletions rely on molecular methods based on PCR assays that classify deletions based on failure to amplify targets in the hrp2 and hrp3 exon region (and sometimes flanking genes).

Currently, there is no multifunctional tool that includes a combination of more than two types of markers (i.e., SNP-barcodes, drug resistance, etc.) to serve several use cases. In addition, the characterization of hrp2 and hrp3-deletions relies on PCR assays that classify deletions based on failure to amplify targets. The few existing tools that combine population markers with drug resistance target short regions around validated drug resistance SNPs, missing the potential to detect novel resistance-associated mutations. Furthermore, many SNP-panels were designed from genomes across the world and lack the resolution to study subtle patterns on a smaller geographical scale. Therefore, we have developed a targeted amplicon next-generation sequencing (NGS) assay for molecular surveillance of Plasmodium falciparum parasites that combines a specifically designed barcode for the target country, 13 full-length resistance-associated genes (Table 1), hrp2 and hrp3, and an apical membrane antigen 1 (ama1) microhaplotype region. The novelty of the assay is its high number of targets multiplexed in one easy workflow, using AmpliSeq deep sequencing technology (Illumina, 2018), and combining phenotypic markers with a 28-SNP barcode with in-country resolution to investigate parasite gene flow in Peru. The assay uses overlapping amplicons to cover large genes. The 28 SNP-barcode was designed with in-country resolution to monitor parasite strains circulating in Peru over space and time (Kattenberg et al., 2023). These SNPs were selected from a South American P. falciparum genome dataset selecting SNPs with a frequency of minor alleles below 0.35 and those that were not under selective pressure, prioritizing SNPs that differentiated the Peruvian samples from other parasite populations in the dataset. Noteworthy, the seq-based tool can be performed on routinely collected filter paper blood spots and can be easily adapted to different regions to investigate either regional trends or in-country epidemiological changes using different SNP-barcodes. The technology applies a multiplex PCR approach to amplify all genomic regions of interest in a rapid and easily standardizable procedure, and allows simultaneous amplification of a high number of targets at once, therefore having great potential for implementation into routine surveillance practice by NMCPs.

Table 1. Targeted genes of interest for drug resistance in the PF AmpliSeq assay

AMQ: amodiaquine; ART: artesunate; ATQ: atovaquone; CM: clindamycin; CQ: chloroquine; DHA: dihydroartemisinin; HF: halofantrine; LF: lumefantrine; MQ: mefloquine; PG: proguanil; PPQ: piperaquine; PYR: pyrimethamine; SULF: sulfadoxine; QN: quinine. *The list of drugs to which resistance has been observed is non-exhaustive. Validated mutations are listed in the WHO report on antimalarial drug efficacy, resistance, and response: 10 years of surveillance (2010–2019).