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. © 2016 Baird et al.

The Anisakis Transcriptome Provides a Resource for Fundamental and Applied Studies on Allergy-Causing Parasites.

OTRANTO, Domenico;Cantacessi, C.
2016-01-01

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. © 2016 Baird et al.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/168018
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