Visualisation and analysis of proteomic data from the procyclic form of Trypanosoma brucei

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Abstract
We have undertaken a large scale study of the proteins expressed in the procyclic form of the parasite Trypanosoma brucei, which causes African sleeping sickness, using 2‐DE and MS. The complete data set encompasses over 2000 identifications, of which 770 are distinct proteins. We have discovered that multiple protein isoforms appear to be common in T. brucei, as most proteins have been matched to more than one gel spot. We have developed visualisation software to investigate the differences between isoforms, based on the information from the results of database searches with MS data. We are able to highlight instances where PTMs are the most likely cause of variant forms. In other cases, spots that appear reproducibly across replicates contain fragments of proteins, arising either as experimental artefacts or as part of protein degradation. We are also able to classify clusters of gel spots into different groups based on the pattern of peptides that have been matched from MS data. The entire data set is stored within a relational database system that allows complex queries (http://www.gla.ac.uk/functionalgenomics). Using specific proteins as examples, we demonstrate how the visualisation software and the database query facilities can be used.