Data

Potential allergens of the Pacific Oyster (Crassostrea gigas)

James Cook University
Lopata, Andreas ; Kamath, Sandip ; Nugraha, Roni
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.4225/28/588ebc2ca00e2&rft.title=Potential allergens of the Pacific Oyster (Crassostrea gigas)&rft.identifier=10.4225/28/588ebc2ca00e2&rft.publisher=James Cook University&rft.description=The increasing production and consumption of molluscs are associated with a rise in the prevalence of mollusc allergy worldwide, currently affecting 0.2% to 1.3% of the general population. However, the elucidation of mollusc allergens, crucial for better diagnostics, still lags behind other seafood groups such as fish and crustacean. Genomic data have previously been utilized for the improved identification of non-food allergens by performing similarity searches using the BLAST program. Based on the published genome of the Pacific oyster (Crassostrea gigas) we aimed to identify the repertoire of potential allergen using bioinformatics analysis and sought to validate allergenicity using a combination of immuno-chemical methods and proteomic analysis. A repertoire of 25,982 genome-derived proteomes of the Pacific oyster were aligned with 2117 allergen sequences resulting in over 800 protein homologues. Of those, 95 proteins were potentially cross-reactive allergens due to high identity with known allergens (>50% identity). Analysis of the transcriptomic data showed the proteins were differentially expressed across tissue of the oyster. &rft.creator=Lopata, Andreas &rft.creator=Kamath, Sandip &rft.creator=Nugraha, Roni &rft.date=2017&rft.relation=http://dx.doi.org/10.1111/imj.12869&rft.coverage=&rft_rights=Once access to the data has been obtained via negotiation with the data manager, use of the dataset is governed by the CC-BY-NC AU licence.&rft_rights=CC BY-NC: Attribution-Noncommercial 3.0 AU http://creativecommons.org/licenses/by-nc/3.0/au&rft_subject=food allergens&rft_subject=oyster&rft_subject=genomic&rft_subject=in-silico&rft_subject=immunoinformatics&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Non-Commercial Licence view details
CC-BY-NC

CC BY-NC: Attribution-Noncommercial 3.0 AU
http://creativecommons.org/licenses/by-nc/3.0/au

Once access to the data has been obtained via negotiation with the data manager, use of the dataset is governed by the CC-BY-NC AU licence.

Access:

Conditions apply view details

Conditional: Contact researchdata@jcu.edu.au to request access to this data.

Full description

The increasing production and consumption of molluscs are associated with a rise in the prevalence of mollusc allergy worldwide, currently affecting 0.2% to 1.3% of the general population. However, the elucidation of mollusc allergens, crucial for better diagnostics, still lags behind other seafood groups such as fish and crustacean. Genomic data have previously been utilized for the improved identification of non-food allergens by performing similarity searches using the BLAST program. Based on the published genome of the Pacific oyster (Crassostrea gigas) we aimed to identify the repertoire of potential allergen using bioinformatics analysis and sought to validate allergenicity using a combination of immuno-chemical methods and proteomic analysis. A repertoire of 25,982 genome-derived proteomes of the Pacific oyster were aligned with 2117 allergen sequences resulting in over 800 protein homologues. Of those, 95 proteins were potentially cross-reactive allergens due to high identity with known allergens (>50% identity). Analysis of the transcriptomic data showed the proteins were differentially expressed across tissue of the oyster.

Notes

This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)

Created: 2017-01-30

This dataset is part of a larger collection

Click to explore relationships graph
Subjects

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Identifiers
  • DOI : 10.4225/28/588EBC2CA00E2
  • Local : researchdata.jcu.edu.au//published/99a172a23c48f66d51a50bd0f7720c58
  • Local : 06dd1f377cbc62ea860a60c09651c572