Getting the most out of parasitic helminth transcriptomes using HelmDB: implications for biology and biotechnology

Mangiola, Stefano, Young, Neil D., Korhonen, Pasi, Mondal, Alinda, Scheerlinck, Jean-Pierre, Sternberg, Paul W., Cantacessi, Cinzia, Hall, Ross S., Jex, Aaron R., and Gasser, Robin B. (2013) Getting the most out of parasitic helminth transcriptomes using HelmDB: implications for biology and biotechnology. Biotechnology Advances, 31 (8). pp. 1109-1119.

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Compounded by a massive global food shortage, many parasitic diseases have a devastating, long-term impact on animal and human health and welfare worldwide. Parasitic helminths (worms) affect the health of billions of animals. Unlocking the systems biology of these neglected pathogens will underpin the design of new and improved interventions against them. Currently, the functional annotation of genomic and transcriptomic sequence data for socio-economically important parasitic worms relies almost exclusively on comparative bioinformatic analyses using model organism- and other databases. However, many genes and gene products of parasitic helminths (often > 50%) cannot be annotated using this approach, because they are specific to parasites and/or do not have identifiable homologs in other organisms for which sequence data are available. This inability to fully annotate transcriptomes and predicted proteomes is a major challenge and constrains our understanding of the biology of parasites, interactions with their hosts and of parasitism and the pathogenesis of disease on a molecular level. In the present article, we compiled transcriptomic data sets of key, socioeconomically important parasitic helminths, and constructed and validated a curated database, called HelmDB ( We demonstrate how this database can be used effectively for the improvement of functional annotation by employing data integration and clustering. Importantly, HelmDB provides a practical and user-friendly toolkit for sequence browsing and comparative analyses among divergent helminth groups (including nematodes and trematodes), and should be readily adaptable and applicable to a wide range of other organisms. This web-based, integrative database should assist 'systems biology' studies of parasitic helminths and the discovery and prioritization of novel drug and vaccine targets. This focus provides a pathway toward developing new and improved approaches for the treatment and control of parasitic diseases, with the potential for important biotechnological outcomes.

Item ID: 26414
Item Type: Article (Research - C1)
ISSN: 1873-1899
Keywords: parasitic helminths (nematode and trematode); systems biology; transcriptomics; annotation-improvement; genomics; bioinformatics
Date Deposited: 15 Apr 2013 01:15
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1103 Clinical Sciences > 110309 Infectious Diseases @ 30%
06 BIOLOGICAL SCIENCES > 0604 Genetics > 060408 Genomics @ 60%
08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080301 Bioinformatics Software @ 10%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 60%
97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 30%
97 EXPANDING KNOWLEDGE > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences @ 10%
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