Proteomic and Bioinformatic Analyses for the Identification of Proteins With Low Allergenic Potential for Hazard Assessment. (23rd March 2019)
- Record Type:
- Journal Article
- Title:
- Proteomic and Bioinformatic Analyses for the Identification of Proteins With Low Allergenic Potential for Hazard Assessment. (23rd March 2019)
- Main Title:
- Proteomic and Bioinformatic Analyses for the Identification of Proteins With Low Allergenic Potential for Hazard Assessment
- Authors:
- Krutz, Nora L
Winget, Jason
Ryan, Cindy A
Wimalasena, Rohan
Maurer-Stroh, Sebastian
Dearman, Rebecca J
Kimber, Ian
Gerberick, G Frank - Abstract:
- Abstract: Use of botanicals and natural substances in consumer products has increased in recent years. Such extracts can contain protein that may theoretically represent a potential risk of IgE-mediated allergy. No method has yet been generally accepted or validated for assessment of the allergenic potential of proteins. For development of suitable methods datasets of allergenic and nonallergenic (or low allergenic) proteins are required that can serve, respectively, as positive and negative controls. However, data are unavailable on proteins that lack or have low allergenic potential. Here, low allergenic potential proteins are identified based on the assumption that proteins with established human exposure, but with a lack of an association with allergy, possess low allergenic potential. Proteins were extracted from sources considered to have less allergenic potential (corn, potato, spinach, rice, and tomato) as well as higher allergenic potential (wheat) regarding common allergenic foods. Proteins were identified and semi-quantified by label-free proteomic analysis conducted using mass spectrometry. Predicted allergenicity was determined using AllerCatPro (https://allercatpro.bii.a-star.edu.sg/ ). In summary, 9077 proteins were identified and semi-quantified from 6 protein sources. Within the top 10% of the most abundant proteins identified, 178 characterized proteins were found to have no evidence for allergenicity predicted by AllerCatPro and were considered to have lowAbstract: Use of botanicals and natural substances in consumer products has increased in recent years. Such extracts can contain protein that may theoretically represent a potential risk of IgE-mediated allergy. No method has yet been generally accepted or validated for assessment of the allergenic potential of proteins. For development of suitable methods datasets of allergenic and nonallergenic (or low allergenic) proteins are required that can serve, respectively, as positive and negative controls. However, data are unavailable on proteins that lack or have low allergenic potential. Here, low allergenic potential proteins are identified based on the assumption that proteins with established human exposure, but with a lack of an association with allergy, possess low allergenic potential. Proteins were extracted from sources considered to have less allergenic potential (corn, potato, spinach, rice, and tomato) as well as higher allergenic potential (wheat) regarding common allergenic foods. Proteins were identified and semi-quantified by label-free proteomic analysis conducted using mass spectrometry. Predicted allergenicity was determined using AllerCatPro (https://allercatpro.bii.a-star.edu.sg/ ). In summary, 9077 proteins were identified and semi-quantified from 6 protein sources. Within the top 10% of the most abundant proteins identified, 178 characterized proteins were found to have no evidence for allergenicity predicted by AllerCatPro and were considered to have low allergenic potential. This panel of low allergenic potential proteins provides a pragmatic approach to aid the development of alternative methods for robust testing strategies to distinguish between proteins of high and low allergenic potential to assess the risk of proteins from natural or botanical sources. … (more)
- Is Part Of:
- Toxicological sciences. Volume 170:Number 1(2019)
- Journal:
- Toxicological sciences
- Issue:
- Volume 170:Number 1(2019)
- Issue Display:
- Volume 170, Issue 1 (2019)
- Year:
- 2019
- Volume:
- 170
- Issue:
- 1
- Issue Sort Value:
- 2019-0170-0001-0000
- Page Start:
- 210
- Page End:
- 222
- Publication Date:
- 2019-03-23
- Subjects:
- Type I allergy -- risk assessment -- label-free proteomic analysis -- in silico prediction model -- AllerCatPro
Toxicology -- Periodicals
Toxicology -- Periodicals
Toxicology
Periodicals
615.9 - Journal URLs:
- http://www.sciencedirect.com/science/journal/10966080 ↗
http://toxsci.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/toxsci/kfz078 ↗
- Languages:
- English
- ISSNs:
- 1096-6080
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8873.031900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25150.xml