Systematic Genetic Identification of Resistance Determinants and Fitness Modifiers in Malaria Parasites

About This Grant

PROJECT SUMMARY Globally, approximately 282 million incidences and 610,000 fatalities were attributed to malaria in 2024 (World Malaria Report, 2025). The recent increase in cases highlights the urgent need for a more comprehensive understanding of the etiological agent of the disease. The protozoan parasite responsible for causing malaria, Plasmodium falciparum, remains the most prevalent and lethal species among the Plasmodium genera. Malaria persistence can be partly attributed to the growing resistance of the Plasmodium parasite to currently available antimalarial drugs (World Malaria Report, 2025). An additional factor to the difficulty of eradication efforts is the highly competitive nature of Plasmodium falciparum populations in Africa, where the emergence and spread of drug resistance pose significant challenges to malaria control1–4. I propose conducting bulk segregant analyses (BSAs), both with and without artemisinin (ART) pressure, with sample collection at multiple time points. Previous BSAs under drug pressure have successfully uncovered key mutations such as pfCRT for chloroquine (CQ) resistance and pfK13 for ART resistance5,6. However, these methodologies required careful refinement and are still being optimized for other drugs, such as piperaquine (PPQ). Based on my preliminary data and prior in vivo pooled assays, I hypothesize that competitive dynamics and resistance mechanisms interact in ways that complicate resistance detection and parasite population structure under temporary selective pressure7–9. Combining genetically diverse parasites in pooled assays can confound the detection of resistance when drug sensitivity varies among the population. In such cases, the resistant parasite can only be detected through genetic sequencing and tracking the most abundant parasite. Furthermore, competition among parasites plays a significant role in population dynamics. More fit parasites, even if drug-sensitive, may outcompete resistant parasites and dominate the population after treatment. Interestingly, moderately resistant and moderately fit parasites may emerge as dominant when no parasites exhibit both high fitness and high resistance. Utilizing the experimental structure of a competitive growth assay in a genetic cross will assess fitness-resistance trade-offs by monitoring allelic shifts under both treated and untreated conditions. These experiments will provide insights into how genetic architecture influences competitive outcomes and facilitates the spread of resistant parasites. This work aligns with global malaria control efforts by providing critical data on the evolutionary dynamics of resistance, informing surveillance strategies, and guiding intervention policies.