Tracking the flow of malaria parasites and drug resistance within the DRC and across its borders
This project will leverage high-throughput genotyping of parasites using a state-of-the-art panel of molecular inversion probes (MIPs) for targeted sequencing of thousands of resistance and neutral loci across thousands of infections covering the entire Democratic Republic of Congo (DRC) and select areas in bordering countries. This will provide a map with an unprecedented scale and resolution to define the evolution and spread of antimalarial resistance mutations.
In this project, the research team will first develop a genotyping panel which should provide a high-resolution tool for studying all known drug resistance loci and general parasite population structure in this and other settings. Applying this to well-annotated samples from across the DRC and bordering countries, they will define the prevalence of drug resistance mutations and define them based on their genetic haplotypes which act as a unique fingerprints. Then, they will map these drug resistance haplotypes and study their spread and spatial associations and further examine their epidemiologic associations and interactions. Onto this detailed spatial map, they will examine specific locales of interest for temporal changes.
These focal regions in the DRC represent diverse ecologic and demographic features that likely impact resistance spread and evolution including areas with minimal health care infrastructure and ongoing regions of conflict.
The final work will be to apply more sophisticated models to the rich sequence data in order to estimate the flow of parasites and resistance mutations within and between the DRC. This includes the development of new population structure models (MALECOT) incorporating parasite infections that have multiple strains allowing for a better understanding of the full dataset as in polyclonal infections are often the majority in endemic African countries. This model should be broadly applicable to other studies of malaria or infections with mixed strains. They will also leverage spatially explicit models to define general parasite flow in both relative and absolute terms comparing and contrasting to the flow of resistant parasites.
This work will provide the patterns of general gene flow and barriers on the spread of specific drug resistance alleles and haplotypes. In summary, not only will this project enhance our understanding of malaria landscape genetics and the evolution and spread of antimalarial resistance, it will provide tools and analysis framework for improving public health interventions that will directly inform the DRC National Malaria Control Program.
Malaria remains endemic in sub-Saharan Africa in large part due to continued evolution and spread of drug resistance which undermines ongoing large-scale control and elimination efforts.