Sensitive and modular amplicon sequencing of Plasmodium falciparum diversity and resistance for research and public health.
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Aranda-Díaz Andrés, Vickers Eric Neubauer, Murie Kathryn, Palmer Brian, Hathaway Nicholas, Gerlovina Inna, Boene Simone, Garcia-Ulloa Manuel, Cisteró Pau, Katairo Thomas, Semakuba Francis Ddumba, Nsengimaana Bienvenu, Gwarinda Hazel, García-Fernández Carla, Louie William, Esayas Endashaw, Da Silva Clemente, Datta Debayan, Kiyaga Shahiid, Wiringilimaana Innocent, Fekele Sindew Mekasha, Bennett Adam, Smith Jennifer L, Gadisa Endalamaw, Parr Jonathan B, Conrad Melissa, Raman Jaishree, Tukwasibwe Stephen, Ssewanyana Isaac, Rovira-Vallbona Eduard, Tato Cristina M, Briggs Jessica, Mayor Alfredo, Greenhouse Bryan
Аннотация
METHODS: We developed, characterized, and implemented MAD4HatTeR, an amplicon sequencing panel based on Multiplex Amplicons for Drug, Diagnostic, Diversity, and Differentiation Haplotypes using Targeted Resequencing, along with a bioinformatic pipeline for data analysis. Additionally, we introduce an analytical approach to detect gene duplications and deletions from amplicon sequencing data. Laboratory control and field samples were used to demonstrate the panel's high sensitivity and robustness.
RESULTS: MAD4HatTeR targets 165 highly diverse loci, focusing on multiallelic microhaplotypes, key markers for drug and diagnostic resistance (including duplications and deletions), and csp and potential vaccine targets. The panel can also detect non-falciparum Plasmodium species. MAD4HatTeR successfully generated data from low-parasite-density dried blood spot and mosquito midgut samples, and detected minor alleles at within-sample allele frequencies as low as 1% with high specificity in high-parasite-density dried blood spot samples. Gene deletions and duplications were reliably detected in mono- and polyclonal controls. Data generated by MAD4HatTeR were highly reproducible across multiple laboratories.
CONCLUSIONS: The successful implementation of MAD4HatTeR in five laboratories, including three in malaria-endemic African countries, showcases its feasibility and reproducibility in diverse settings. MAD4HatTeR is thus a powerful tool for research and a robust resource for malaria public health surveillance and control.