Proteome turnover in the bloodstream and procyclic forms of Trypanosoma brucei measured by quantitative proteomics

• Published in: Wellcome open research Vol. 4; p. 152
• Main Authors: Tinti, Michele, Güther, Maria Lucia S., Crozier, Thomas W. M., Lamond, Angus I., Ferguson, Michael A. J.
• Format: Journal Article
• Language: English
• Published: England Wellcome Trust Limited 2019; F1000 Research Limited; Wellcome
• Subjects: Biosynthesis; Cell culture; Cell cycle; Cell division; Data visualization; Gene expression; Isotopes; Life sciences; Parasites; Peptides; Proteins; Quality control; RNA polymerase; Writing; United Kingdom > UK; Trypanosoma; Procyclic; Bloodstream; Proteomics; Turnover
• ISSN: 2398-502X; 2398-502X
• DOI: 10.12688/wellcomeopenres.15421.1

Background : Cellular proteins vary significantly in both abundance and turnover rates. These parameters depend upon their rates of synthesis and degradation and it is useful to have access to data on protein turnover rates when, for example, designing genetic knock-down experiments or assessing the potential usefulness of covalent enzyme inhibitors. Little is known about the nature and regulation of protein turnover in Trypanosoma brucei , the etiological agent of human and animal African trypanosomiasis. Methods : To establish baseline data on T. brucei proteome turnover, a Stable Isotope Labelling with Amino acids in Cell culture (SILAC)-based mass spectrometry analysis was performed to reveal the synthesis and degradation profiles for thousands of proteins in the bloodstream and procyclic forms of this parasite. Results : This analysis revealed a slower average turnover rate of the procyclic form proteome relative to the bloodstream proteome. As expected, many of the proteins with the fastest turnover rates have functions in the cell cycle and in the regulation of cytokinesis in both bloodstream and procyclic forms. Moreover, the cellular localization of T. brucei proteins correlates with their turnover, with mitochondrial and glycosomal proteins exhibiting slower than average turnover rates. Conclusions : The intention of this study is to provide the trypanosome research community with a resource for protein turnover data for any protein or group of proteins. To this end, bioinformatic analyses of these data are made available via an open-access web resource with data visualization functions.