Parasitic protozoa are a major cause of global infectious diseases and thus represent serious threats to public health. Among these are African trypanosomes, which are the causative agents of Human African trypanosomiasis (HAT, or sleeping sickness) and Animal African trypanosomiasis (AAT, or Nagana) in domesticated animals. Although HAT has been in decline for several years, its burden remains profound. The disease is 100% fatal if left untreated. However, treatment is expensive, challenging to administer in resource-limited settings, and parasite resistance to current chemotherapeutics is emerging. AAT remains a huge problem on the continent (for many of these same reasons described above for HAT) and has a devastating socioeconomic impact in afflicted regions. Acquiring a better understanding of tsetse and trypanosome biology is crucial in our efforts to reduce disease transmission through the fly and to develop novel preventative and therapeutic solutions for African trypanosomiases and related parasitic diseases. The Aksoy lab focuses on the molecular dialogue between tsetse and trypanosomes that determine the outcome of the infection process as interference in this process can block parasite transmission to the mammalian host. In addition, studies on tsetse’s endosymbionts, which are essential for fecundity and immunity, provide novel points of interference for vector control efforts. 

The Tschudi lab investigates the biology of trypanosomes with special emphasis on the developmental program that leads to the acquisition of infectivity. The Aksoy and Caccone labs have been working in Uganda and Kenya to understand the patterns of genomic connectivity of both vectors and parasites and associations between tsetse genotypes and trypanosome infections to guide control studies. They have also been applying comparative genomic approaches to understand the evolutionary origin of African trypanosomes and the genetic connectivity across strains from different named species. The Galvani lab analyzes these parameters using mathematical models to identify factors that influence the emergence of HAT epidemics.