Helminth secretome database (HSD)

a collection of helminth excretory/secretory proteins predicted from expressed sequence tags (ESTs)

Gagan Garg, Shoba Ranganathan*

*Corresponding author for this work

Research output: Contribution to journalConference paper

25 Citations (Scopus)
31 Downloads (Pure)

Abstract

Background: Helminths are important socio-economic organisms, responsible for causing major parasitic infections in humans, other animals and plants. These infections impose a significant public health and economic burden globally. Exceptionally, some helminth organisms like Caenorhabditis elegans are free-living in nature and serve as model organisms for studying parasitic infections. Excretory/secretory proteins play an important role in parasitic helminth infections which make these proteins attractive targets for therapeutic use. In the case of helminths, large volume of expressed sequence tags (ESTs) has been generated to understand parasitism at molecular level and for predicting excretory/secretory proteins for developing novel strategies to tackle parasitic infections. However, mostly predicted ES proteins are not available for further analysis and there is no repository available for such predicted ES proteins. Furthermore, predictions have, in the main, focussed on classical secretory pathways while it is well established that helminth parasites also utilise non-classical secretory pathways. Results: We developed a free Helminth Secretome Database (HSD), which serves as a repository for ES proteins predicted using classical and non-classical secretory pathways, from EST data for 78 helminth species (64 nematodes, 7 trematodes and 7 cestodes) ranging from parasitic to free-living organisms. Approximately 0.9 million ESTs compiled from the largest EST database, dbEST were cleaned, assembled and analysed by different computational tools in our bioinformatics pipeline and predicted ES proteins were submitted to HSD. Conclusion: We report the large-scale prediction and analysis of classically and non-classically secreted ES proteins from diverse helminth organisms. All the Unigenes (contigs and singletons) and excretory/secretory protein datasets generated from this analysis are freely available. A BLAST server is available at http://estexplorer.biolinfo. org/hsd, for checking the sequence similarity of new protein sequences against predicted helminth ES proteins.

Original languageEnglish
Article numberS8
Pages (from-to)1-11
Number of pages11
JournalBMC Genomics
Volume13
DOIs
Publication statusPublished - 2012
EventAsia Pacific Bioinformatics Network (APBioNet) Eleventh International Conference on Bioinformatics (InCoB2012) - Bangkok, Thailand
Duration: 3 Oct 20125 Oct 2012

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