Abstract
Background
Food-borne nematodes of the genus Anisakis are responsible for a wide range of illnesses (= anisakiasis), from self-limiting gastrointestinal forms to severe systemic allergic reactions, which are often misdiagnosed and under-reported. In order to enhance and refine current diagnostic tools for anisakiasis, knowledge of the whole spectrum of parasite molecules transcribed and expressed by this parasite, including those acting as potential allergens, is necessary.
Methodology/Principal Findings
In this study, we employ high-throughput (Illumina) sequencing and bioinformatics to characterise the transcriptomes of two Anisakis species, A. simplex and A. pegreffii, and utilize this resource to compile lists of potential allergens from these parasites. A total of ~65,000,000 reads were generated from cDNA libraries for each species, and assembled into ~34,000 transcripts (= Unigenes); ~18,000 peptides were predicted from each cDNA library and classified based on homology searches, protein motifs and gene ontology and biological pathway mapping. Using comparative analyses with sequence data available in public databases, 36 (A. simplex) and 29 (A. pegreffii) putative allergens were identified, including sequences encoding ‘novel’ Anisakis allergenic proteins (i.e. cyclophilins and ABA-1 domain containing proteins).
Conclusions/Significance
This study represents a first step towards providing the research community with a curated dataset to use as a molecular resource for future investigations of the biology of Anisakis, including molecules putatively acting as allergens, using functional genomics, proteomics and immunological tools. Ultimately, an improved knowledge of the biological functions of these molecules in the parasite, as well as of their immunogenic properties, will assist the development of comprehensive, reliable and robust diagnostic tools.
Nematodes within the genus Anisakis (i.e. A. simplex and A. pegreffii, also known as herring worms) are the causative agents of the fish-borne gastrointestinal illness known as ‘anisakiasis’, with infections resulting in symptoms ranging from mild gastric forms to severe allergic reactions leading to urticaria, gastrointestinal and/or respiratory signs and/or anaphylaxis (‘allergic anisakiasis’). Despite significant advances in knowledge of the pathobiology of allergic anisakiasis, thus far, the exact number and nature of parasite molecules acting as potential allergens are currently unknown; filling this gap is necessary to the development of robust and reliable diagnostics for allergic anisakiasis which, in turn, underpins the implementation of effective therapeutic strategies. Here, we use RNA-Seq and bioinformatics to sequence and annotate the transcriptomes of A. simplex and A. pegreffii, and, as an example application of these resources, mine this data to identify and characterise putative novel parasite allergens based on comparisons with known allergen sequence data from other parasites and other organisms.
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