Evaluating potential risks of food allergy of novel food sources based on comparison of proteins predicted from genomes and compared to www.AllergenOnline.org. (January 2021)

• Record Type: Journal Article
• Authors: Abdelmoteleb, Mohamed; Zhang, Chi; Furey, Brian; Kozubal, Mark; Griffiths, Hywel; Champeaud, Marion; Goodman, Richard E.
• Is Part Of: Food and chemical toxicology. Volume 147(2021)
• Publication Date: 2021-01
• Subjects: Chlorella -- Galdieria -- Fusarium -- Bioinformatics -- Proteins -- Allergy -- Cross-reactivity -- Genome; AA amino acid -- AOL AllergenOnline -- BLAST FASTA sequence search tool -- NCBI National Center for Biotechnology Information; Toxicology -- Periodicals; Food poisoning -- Periodicals; Food Poisoning -- Periodicals; Toxicology -- Periodicals; Toxicologie -- Périodiques; Intoxications alimentaires -- Périodiques; Food poisoning; Toxicology; Periodicals; Electronic journals; 615.9
• DOI: 10.1016/j.fct.2020.111888
• Languages: English
• ISSNs: 0278-6915

Abstract

Abstract: Potential proteins from three novel food sources ( Chlorella variabilis, Galdieria sulphuraria, and Fusarium strain flavolapis) were predicted from genomic sequences and were evaluated for potential risks of allergic cross-reactivity by comparing the predicted amino acid sequences against the allergens in the www.AllergenOnline.org (AOL) database. The preliminary analysis used CODEX Alimentarius limits of >35% identity over 80 amino acids to evaluate the predicted proteins which include many evolutionarily conserved proteins. Regulators might expect clinical serum IgE tests based on identity matches above the criteria if the proteins were introduced in genetically engineered crops. Some regulators have the same expectations for proteins in novel foods. To address the inequality of extensively conserved sequences, we compared the predicted proteins from curated genomes of 23 highly diverse allergenic species from animals, plants and arthropods as well as humans to AOL sequences and compiled identities. Identity matches greater than CODEX limits (>35% ID over 80 AA) are common for many proteins that are conserved through extensive evolution but are not predictive of published allergy risks based on observed taxonomic cross-reactivity. Therefore, we recommend changes in the allergen databases or methods of identifying matches for risk evaluation of new food sources. Our results provide critical data for redefining allergens in AOL or for providing guidance on more predictive sequence identity matches for risk assessment of possible risks of food allergy. Highlights: Predicting risks of food allergy focuses on possible IgE cross-reactivity. Allergenic foods contain few clinically important allergen types. Comparing proteins by sequences can identify possible cross-reactivity. Allergy databases include many evolutionarily conserved proteins of little risk. CODEX predictions are designed for single proteins, whole genomes and proteomes are challenging.