Needles in the EST Haystack: Large-Scale Identification and Analysis of Excretory-Secretory (ES) Proteins in Parasitic Nematodes Using Expressed Sequence Tags (ESTs)
Open Access
- 24 September 2008
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLoS Neglected Tropical Diseases
- Vol. 2 (9) , e301
- https://doi.org/10.1371/journal.pntd.0000301
Abstract
Parasitic nematodes of humans, other animals and plants continue to impose a significant public health and economic burden worldwide, due to the diseases they cause. Promising antiparasitic drug and vaccine candidates have been discovered from excreted or secreted (ES) proteins released from the parasite and exposed to the immune system of the host. Mining the entire expressed sequence tag (EST) data available from parasitic nematodes represents an approach to discover such ES targets. In this study, we predicted, using EST2Secretome, a novel, high-throughput, computational workflow system, 4,710 ES proteins from 452,134 ESTs derived from 39 different species of nematodes, parasitic in animals (including humans) or plants. In total, 2,632, 786, and 1,292 ES proteins were predicted for animal-, human-, and plant-parasitic nematodes. Subsequently, we systematically analysed ES proteins using computational methods. Of these 4,710 proteins, 2,490 (52.8%) had orthologues in Caenorhabditis elegans, whereas 621 (13.8%) appeared to be novel, currently having no significant match to any molecule available in public databases. Of the C. elegans homologues, 267 had strong “loss-of-function” phenotypes by RNA interference (RNAi) in this nematode. We could functionally classify 1,948 (41.3%) sequences using the Gene Ontology (GO) terms, establish pathway associations for 573 (12.2%) sequences using Kyoto Encyclopaedia of Genes and Genomes (KEGG), and identify protein interaction partners for 1,774 (37.6%) molecules. We also mapped 758 (16.1%) proteins to protein domains including the nematode-specific protein family “transthyretin-like” and “chromadorea ALT,” considered as vaccine candidates against filariasis in humans. We report the large-scale analysis of ES proteins inferred from EST data for a range of parasitic nematodes. This set of ES proteins provides an inventory of known and novel members of ES proteins as a foundation for studies focused on understanding the biology of parasitic nematodes and their interactions with their hosts, as well as for the development of novel drugs or vaccines for parasite intervention and control. Excretory-secretory (ES) proteins are an important class of proteins in many organisms, spanning from bacteria to human beings, and are potential drug targets for several diseases. In this study, we first developed a software platform, EST2Secretome, comprised of carefully selected computational tools to identify and analyse ES proteins from expressed sequence tags (ESTs). By employing EST2Secretome, we analysed 4,710 ES proteins derived from 0.5 million ESTs for 39 economically important and disease-causing parasites from the phylum Nematoda. Several known and novel ES proteins that were either parasite- or nematode-specific were discovered, focussing on those that are either absent from or very divergent from similar molecules in their animal or plant hosts. In addition, we found many nematode-specific protein families of domains “transthyretin-like” and “chromadorea ALT,” considered vaccine candidates for filariasis in humans. We report numerous C. elegans homologues with loss-of-function RNAi phenotypes essential for parasite survival and therefore potential targets for parasite intervention. Overall, by developing freely available software to analyse large-scale EST data, we enabled researchers working on parasites for neglected tropical diseases to select specific genes and/or proteins to carry out directed functional assays for demystifying the molecular complexities of host–parasite interactions in a cell.Keywords
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