Presentation description

Malaria affects millions of individuals annually and is caused by Plasmodium parasites. P. falciparum is responsible for most malaria deaths, but many of this parasite's proteins have not been experimentally characterized. In areas of high transmission, individuals are often co-infected by genetically diverse parasites at the same time, yet the effect of competitive interactions on disease outcome and evolution is poorly understood. In this study, we aimed to identify proteins that may be involved in competitive or cooperative interactions between coinfecting parasites. To do this, we used a dataset of genome-wide genetic variation from parasites sampled in Cameroon, where many infections are polyclonal. For each variant in a coding region, we compared the allele frequency to the observed proportion of mixed genotypes. We identified genetic variants where the two alleles were present together in the same infection less often than expected given the allele frequency as candidates that may have competitive interactions. We also looked for the converse pattern, where alleles were found more often together given the allele frequency as these may represent cooperation between strains carrying the different alleles. This approach provides a way to look for different types of interactions between malaria parasites. By understanding the function of these genes and interactions between alleles, we hope to gain insight into how parasites are exploiting each other. This could reveal new mechanisms that could be utilized to limit parasite infections and improve disease outcomes.