Detection and characterisation of putative allergens in Anisakis food-borne parasites using advanced transcriptomic and bioinformatic technologies

Background: Food-borne nematodes of the genus Anisakis are responsible for a widerange of illnesses (= anisakiasis), from self-limiting gastrointestinal forms to severesystemic allergic reactions, which are often misdiagnosed and under-reported. In orderto enhance and refine current diagnostic tools for anisakiasis, knowledge of the wholespectrum of parasite molecules acting as potential allergens is necessary.Methodology/Principal Findings: In this study, we employ high-throughput (Illumina)sequencing and bioinformatics technologies to characterise the transcriptomes of twoAnisakis species, A. simplex and A. pegreffii, and mine these annotated datasets tocompile lists of potential allergens from these parasites. A total of ~65,000,000 readswere generated from cDNA libraries for each species, and assembled into ~34,000transcripts (= Unigenes); ~18,000 peptides were predicted from each cDNA library andclassified based on homology searches, protein motifs and gene ontology andbiological pathway mapping. Using comparative analyses with sequence data availablein public databases, 36 (A. simplex) and 29 (A. pegreffii) putative allergens wereidentified, 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 theresearch community with a curated dataset to use as a molecular resource for futureinvestigations of poorly known putative Anisakis allergens, using functional genomics,proteomics and immunological tools. Ultimately, an improved knowledge of thebiological functions of these molecules in the parasite, as well as of their immunogenicproperties, will assist the development of comprehensive, reliable and robustdiagnostic tools.