Malaria parasite and vector genomics: transmission, pathology, and therapeutics

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Malaria exerts the largest burden on global health of any disease caused by a eukaryotic parasite, and is responsible for approximately 600,000 deaths a year. Recent gains have been made in controlling malaria, but the proclivity for malaria parasites and their Anopheline mosquito vectors to evolve resistance to drugs and insecticides means that tools are needed to preserve the efficacy of existing therapeutics and control measures, and that investment in basic research is necessary to keep development pipelines stocked with new candidate drugs, vaccines, and insecticides. We propose to advance these efforts by coupling innovative applications of genomic technologies with key questions in the fields of malaria transmission, pathogenesis, and therapeutics. Our projects were specifically designed to leverage resources and expertise not commonly found outside of genome sequencing centers, and involve collaborations with leading investigators in the field. We will employ 16S sequencing, whole genome shotgun sequencing, and GWAS to test a hypothesis that mosquito innate immune genes play a role in shaping mosquito microbiome communities, which have been demonstrated to affect vectorial capacity (Aim 1). We will employ extremely sensitive single-cell transcriptomic profiling to bridge a key knowledge gap in the cues that cause P. falciparum parasites to commit to sexual differentiation, which is essential for transmission (Aim 2). We will create de novo assemblies of unprecedented quality to explore the heretofore uncharacterized genomic dark matter' of Plasmodium subtelomeres, where important antigenic gene families mediating pathogenesis reside and evolve (Aim 3). Finally, we will employ hybrid selection to enrich and sequence Plasmodium DNA from a critical 10 year longitudinal collection of clinical malaria samples from northwestern Thailand, a region where resistance to the current first line drug therapy (artemesinin) has recently arisen (Aim 4). We hypothesize that changes in allele frequency associated with resistance will be detectable in a longitudinal selection screen. The work we propose will not only push the frontier of malaria genomics into bold new territories, but generate empirical and analytical approaches applicable to a broad range of diseases.