Genomic surveillance for artemisinin resistance in Africa: moving beyond a candidate gene approach - PROJECT SUMMARY Artemisinin-based combination therapies (ACTs) are the first-line treatment for malaria in most endemic countries. Emergence of resistance to the artemisinin derivatives and key partner drugs in Southeast Asia raised fears that resistance could spread, or emerge independently, in sub-Saharan Africa, where the malaria burden is greatest. Such fears are being realized with reports of artemisinin-resistant Plasmodium falciparum in areas of East Africa, highlighting the need for proactive resistance surveillance. To date, surveillance for artemisinin resistance has focused on estimates of parasite clearance following treatment with ACTs in the context of drug efficacy studies or genotyping of mutations in the gene encoding Kelch13 (K13). Mutations in K13 are sufficient to cause parasite resistance to artemisinins; however, multiple studies have indicated that artemisinin resistance is multigenic, involving several altered biological processes, and is not always K13-mediated. Likewise, estimates of delayed parasite clearance, the hallmark of artemisinin resistance in Southeast Asia, are confounded by host immunity in high malaria transmission settings of Africa. In the proposed work, we aim to evaluate a genomic surveillance approach that involves sampling of parasite populations over time following ACT implementation to identify mutations under selection in functional pathways implicated in artemisinin resistance. We hypothesize that alteration of specific biological functions, rather than mutation of specific genes, is important for parasite resistance to artemisinins. We will first identify parasite loci under selection over time in four endemic countries and perform analyses to identify enriched functions among genes under selection (Aim 1). Altered functional profiles associated with artemisinin resistance on different genetic backgrounds will be validated using P. falciparum genetic crosses, and specific loci under selection in Mali will be validated for their role in artemisinin resistance using transcriptomic analyses and forward-genetic screens (Aim 2). We will then use amplicon sequencing to assess population-level and within-host dynamics of selected alleles in Mali to estimate selection coefficients and parasite clearance rates to inform the design of temporal sampling and prioritization strategies for future genomic surveillance studies (Aim 3). We anticipate that the proposed selection-based approach will identify parasite adaptation to drug pressure earlier in the evolutionary timeline of emerging resistance before it manifests clinically. Likewise, we expect that the reduced cost of sequencing and increased bioinformatics capabilities in low-and-middle-income countries will make genomic surveillance a tractable option for resistance surveillance.
