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Highly multiplexed ddPCR-amplicon sequencing reveals strong Plasmodium falciparum population structure and isolated populations amenable to local elimination efforts in Zanzibar

Holzschuh, A.; Lerch, A.; Gerlovina, I.; Fakih, B. S.; Al-Mafazy, A.-W.; Reaves, E. J.; Ali, A.; Abbas, F.; Ali, M. H.; Ali, M. A.; Hetzel, M. W.; Yukich, J. O.; Koepfli, C.

2023-01-06 genomics
10.1101/2023.01.05.522832 bioRxiv
Show abstract

Over the past 15 years, Zanzibar has made great strides towards malaria elimination; yet progress has stalled. Parasite genetic data of Plasmodium falciparum may inform strategies for malaria elimination by helping to identify contributory factors to parasite persistence. Here we elucidate fine-scale parasite population structure and infer relatedness and connectivity of infections using an identity-by-descent (IBD) approach. We sequenced 518 P. falciparum samples from 5 districts covering both main islands using a novel, highly multiplexed droplet digital PCR (ddPCR)-based amplicon deep sequencing method targeting 35 microhaplotypes and drug-resistance loci. Despite high genetic diversity, we observe strong fine-scale spatial and temporal structure of local parasite populations, including isolated populations on Pemba Island and genetically admixed populations on Unguja Island, providing evidence of ongoing local transmission. We observe a high proportion of highly related parasites in individuals living closer together, including between clinical index cases and the mostly asymptomatic cases surrounding them, consistent with isolation-by-distance. We identify a substantial fraction (2.9%) of related parasite pairs between Zanzibar, and mainland Tanzania and Kenya, consistent with recent importation. We identify haplotypes known to confer resistance to known antimalarials in all districts, including multidrug-resistant parasites, but most parasites remain sensitive to current first-line treatments. Our study provides a high-resolution view of parasite genetic structure across the Zanzibar archipelago and reveals actionable patterns, including isolated parasite populations, which may be prioritized for malaria elimination.

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