Selection of Tree Nut Allergen Peptide Markers: A Need for Improved Protein Sequence Databases
Weili Xiong1, Melinda A McFarland1, Cary Pirone1
1U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, 5001 Campus Dr, College Park, MD 20740.
Journal of AOAC International
|March 21, 2019
Summary
Supplementing protein databases with genomic data improves food allergen detection. This enhances the selection of peptide markers for accurate identification of tree nut allergens, aiding regulatory compliance.
Area of Science:
- Food science
- Proteomics
- Genomics
Background:
- Reliable food allergen detection is crucial for protecting allergic individuals and ensuring regulatory compliance.
- Mass spectrometry (MS)-based methods require robust peptide markers, but incomplete protein sequence data hinders analysis, especially for plant-based foods.
Purpose of the Study:
- To evaluate the effectiveness of incorporating translated genomic sequencing data into protein databases for food allergen analysis.
- To enhance the identification and selection of peptide markers for improved food allergen detection.
Main Methods:
- A parsimony-driven global proteomics workflow was employed.
- Data from reference tree nut ingredients were compiled and analyzed.
- Protein sequence databases were supplemented with translated genomic data, specifically for English walnut.
Main Results:
- Supplementing databases with genomic data improved the selection of candidate peptide markers.
- Enhanced marker selection facilitated better differentiation between closely related species.
- The approach demonstrated utility for improving allergen detection in tree nut ingredients.
Conclusions:
- Genomic-derived sequences are valuable for augmenting protein databases in food allergen research.
- Future database improvements and genomic data integration will support the development of harmonized LC-tandem MS methods for food allergen detection.
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