The microbiome of the tsetse

Background: The tsetse fly is an important vector of tropical disease as it is the host for the parasite, Trypanosoma brucei, that causes African sleeping sickness. The completion of the genome sequence of the tsetse earlier this year has moved studies into the post-genomic era with new opportunities to decrease the burden of sleeping sickness. One significantly underexplored area is the role of the tsetse microbiome, which contains 3 recognised symbiotic bacteria, Wigglesworthia glossinidia, Sodalis glossunidius and Wolbachia sp., which are thought to play varying roles in nutrient provisioning, parasite transmission and causing reproductive abnormalities.
Objectives: In this project the student will use a combination of computational and microbiological techniques to define the function of the tsetse microbiome. Building on our extensive experience and significant unpublished data in whole-genome metabolic modelling in this area, the student will extend this work to define the metabolic function of Wigglesworthia and Sodalis, including recent breakthroughs in the successful laboratory culturing of Sodalis and enhanced growth using metabolic additions predicted by the in silico model.

Novelty: The combination of computational and experimental methods being used in this project is highly innovative and brings together the microbiological and metabolic expertise of the primary supervisor, Dr. Thomas, with the modelling and mathematical/computational expertise of the co-supervisor Dr. Wood.
Timeliness: The project benefits from the completion of the tsetse genome sequence in 2014. Through on ongoing project with Dr. Alistair Darby (Liverpool School of Tropical Medicine) we will have access to extensive transcriptomic, metabolomic and proteomic data from Sodalis that will be incorporated in York into SodalisBASE, a new bespoke database being developed in the TF in late 2014. Other new synthetic biology approaches being used in the Thomas lab would also allow the heterologous expression of key symbiont proteins to test key metabolic predictions.