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Trypanosomatid parasites cause serious infections in humans and production losses in livestock. Due to the high divergence from other eukaryotes, such as humans and model organisms, the functional roles of many trypanosomatid proteins cannot be predicted by homology-based methods, rendering a significant portion of their proteins as uncharacterized. Recent technological advances have led to the availability of multiple systematic and genome-wide datasets on trypanosomatid parasites that are informative regarding the biological role(s) of their proteins. Here, we report TrypsNetDB (http://trypsNetDB.org), a web-based resource for the functional annotation of 16 different species/strains of trypanosomatid parasites. The database not only visualizes the network context of the queried protein(s) in an intuitive way but also examines the response of the represented network in more than 50 different biological contexts and its enrichment for various biological terms and pathways, protein sequence signatures, and potential RNA regulatory elements. The interactome core of the database, as of Jan 23, 2017, contains 101,187 interactions among 13,395 trypanosomatid proteins inferred from 97 genome-wide and focused studies on the interactome of these organisms., Author summary Methods to predict protein function based on sequences enable the rapid annotation of newly sequenced genomes. However, as most of these methods rely on homology-based approaches, non-conserved proteins in trypanosomatids remain elusive for annotation, rendering approximately half of the sequenced proteins uncharacterized. In this study, we developed a user friendly integrated database, TrypsNetDB, which fills multiple gaps in the field by depositing the current interactome knowledge on trypanosomatid proteins and combining this information with other available resources accompanied by related statistical analyses. The database allows automatic inter-species mapping of available data to better characterize the queried proteins in the species of interest. The database is built on fast and reliable ASP.Net framework and provides (i) a significant increase in the genome-wide functional annotation of trypanosomatid proteins, (ii) potential novel targets for therapeutics against trypanosomatids, and (iii) a robust methodology that can be adapted for the functional annotation of other non-model organisms.

The functions of the majority of trypanosomatid-specific proteins are unknown, hindering our understanding of the biology and pathogenesis of Trypanosomatida. While protein-protein interactions are highly informative about protein function, a global map of protein interactions and complexes is still lacking for these important human parasites. Here, benefiting from in-depth biochemical fractionation, we systematically interrogated the co-complex interactions of more than 3354 protein groups in procyclic life stage of Trypanosoma brucei, the protozoan parasite responsible for human African trypanosomiasis. Using a rigorous methodology, our analysis led to identification of 128 high-confidence complexes encompassing 716 protein groups, including 635 protein groups that lacked experimental annotation. These complexes correlate well with known pathways as well as for proteins co-expressed across the T. brucei life cycle, and provide potential functions for a large number of previously uncharacterized proteins. We validated the functions of several novel proteins associated with the RNA-editing machinery, identifying a candidate potentially involved in the mitochondrial post-transcriptional regulation of T. brucei. Our data provide an unprecedented view of the protein complex map of T. brucei, and serve as a reliable resource for further characterization of trypanosomatid proteins. The presented results in this study are available at: www.TrypsNetDB.org., Author Summary Due to high evolutionary divergence of trypanosomatid pathogens from other eukaryotes, accurate prediction of functional roles for most of their proteins is not feasible based on homology-based approaches. Although protein co-complex maps provide a compelling tool for the functional annotation of proteins, as subunits of a complex are expected to be involved in similar biological processes, the current knowledge about these maps is still rudimentary. Here, we systematically examined the protein co-complex membership of more than one third of T. brucei proteome using two orthogonal fractionation approaches. A high-confidence network of co-complex relationships predicts the network context of 866 proteins, including many hypothetical and experimentally unannotated proteins. To our knowledge, this study presents the largest proteomics-based interaction map of trypanosomatid parasites to date, providing a useful resource for formulating new biological hypothesises and further experimental leads.