Proteomic analysis of protein complexes and cell cycle regulation in Trypanosoma brucei

摘要

is a unicellular trypanosomatid protozoan parasite and the etiological agent of sleeping sickness in sub-Saharan Africa. The trypanosomatid order also includes the parasites (Chagas disease) and (Leishmaniasis). Sleeping sickness is estimated to cause ~10,000 deaths per year and current treatments are expensive, difficult to administer and toxic. Although genomic sequencing of all three parasites has identified the coding sequences of these organisms, much is still unknown about protein function, with 64% of identified genes annotated as “hypothetical”, lacking obvious homology with proteins of known function. To further understand the unusual biology of this family of eukaryotes, this thesis aimed to provide evidence for protein function in in a high-throughput manner, utilising global proteomic analyses. This work has encompassed two main approaches: The global analysis of protein interactions and the analysis of proteome changes across the cell-cycle.To enable these approaches, I developed protocols for proteome wide analysis of protein complexes in , combining multiple forms of chromatography on ‘native’ lysates of cells to produce a proteome wide map of core, soluble protein complexes in this organism. I further performed preliminary studies to optimise in vivo formaldehyde crosslinking in in order to characterise membrane bound protein complexes.I also developed methodologies to produce large populations of procyclic cells highly enriched in different phases of the cell-cycle for proteomic analysis. In conjunction with the optimisation of methods for isobaric tag quantitation on Fusion mass spectrometers, I provide the first characterisation of protein regulation during cell division in at an unparalleled proteomic depth.Together, these datasets provide a wealth of information about the interaction and cell cycle regulation of many thousands of proteins in , and contributes greatly to the understanding of protein function in trypanosomatid organisms. I highlight the ability of these methods to predict novel protein complexes, predict interactions between “hypothetical” proteins with proteins of known function, and to identify “hypothetical” cell-cycle regulated proteins that are essential for growth of the parasite, that are a potentially interesting source for novel drug targets. Data visualisation tools to browse the data in a user-friendly format will further allow the trypanosmatid research community to mine these datasets to understand function of proteins of interest and continue to extract functional information from these datasets to extend our understanding of trypanosomatid biology.