Barcoding Genetically Distinct Plasmodium falciparum Strains for Comparative Assessment of Fitness and Antimalarial Drug Resistance.

The repeated emergence of antimalarial drug resistance in Plasmodium falciparum, including to the current frontline antimalarial artemisinin, is a perennial problem for malaria control. Next-generation sequencing has greatly accelerated the identification of polymorphisms in resistance-associated genes but has also highlighted the need for more sensitive and accurate laboratory tools to profile current and future antimalarials and to quantify the impact of drug resistance acquisition on parasite fitness. The interplay of fitness and drug response is of fundamental importance in understanding why particular genetic backgrounds are better at driving the evolution of drug resistance in natural populations, but the impact of parasite fitness landscapes on the epidemiology of drug resistance has typically been laborious to accurately quantify in the lab, with assays being limited in accuracy and throughput. Here we present a scalable method to profile fitness and drug response of genetically distinct P. falciparum strains with well-described sensitivities to several antimalarials. We leverage CRISPR/Cas9 genome-editing and barcode sequencing to track unique barcodes integrated into a nonessential gene (). We validate this approach in multiplex competitive growth assays of three strains with distinct geographical origins. Furthermore, we demonstrate that this method can be a powerful approach for tracking artemisinin response as it can identify an artemisinin resistant strain within a mix of multiple parasite lines, suggesting an approach for scaling the laborious ring-stage survival assay across libraries of barcoded parasite lines. Overall, we present a novel high-throughput method for multiplexed competitive growth assays to evaluate parasite fitness and drug response. The complex interplay between antimalarial resistance and parasite fitness has important implications for understanding the development and spread of drug resistance alleles and the impact of genetic background on transmission. One limitation with current methodologies to measure parasite fitness is the ability to scale this beyond simple head-to-head competition experiments between a wildtype control line and test line, with a need for a scalable approach that allows tracking of parasite growth in complex mixtures. In our study, we have used CRISPR editing to insert unique DNA barcodes into a safe-harbor genomic locus to tag multiple parasite strains and use next-generation sequencing to read out strain dynamics. We observe inherent fitness differences between the strains, as well as sensitive modulation of responses to challenge with clinically relevant antimalarials, including artemisinin.