The prevalence of food allergy is increasing worldwide. To protect sensitive consumers, it is imperative to identify the culprit allergens, characterize their molecular biochemistry, and develop reliable allergen detection methods.
A review of food allergy: https://doi.org/10.1146/annurev-food-041715-033308
A perspective on food allergen epitope mapping: https://doi.org/10.1021/acs.jafc.8b01967
Sialic acid and food allergy: https://doi.org/10.1080/10408398.2022.2136620
Protocols for allergen purification and linear IgE-binding epitope characterization
Allergen Detection
Given existing public health concerns for nut allergies, we have developed and validated monoclonal antibody-based enzyme-linked immunosorbent assays (ELISA) for detection of almond, pecan, and pistachio in foods.
ELISAs for almond: https://doi.org/10.1021/jf402851k, https://doi.org/10.1111/1750-3841.13829
ELISA for pistachio: https://doi.org/10.1021/acs.jafc.5b03066
ELISA for pecan: https://doi.org/10.1016/j.lwt.2019.108516
Protocols for ELISA validation: https://doi.org/10.1007/978-1-0716-3453-0_19
Allergen Characterization
We have found that amandin, a major storage protein and allergen in almond, is stable toward processing and storage, and can serve as a reliable target protein for robust detection of almond. We have reported IgE cross-reactivity between amandin and a homologous 11S legumin in mahaleb cherry seed, indicating the cherry seed is a potential cross-reactive food ingredient for almond-allergic patients. Besides almond, we have also studied how germination affect immunoreactivity of black gram and mung bean vicilin.
Effect of processing and food matrix on amandin immunoreactivity: high pressure processing, Maillard reaction, processing and storage, phenolic compounds,
Cross-reactivity with other Prunus seeds: Prunus spp., Prunus mahaleb
Effect of germination on vicilin immunoreactivity: https://doi.org/10.1016/j.lwt.2020.110217
Effect of temperature and pH on immunoreactivity of soy agglutinin: https://doi.org/10.1016/j.foodchem.2024.138376
Allergen Prediction
Using pretrained protein language models, we have developed robust models for allergenic protein/peptide prediction. The developed pLM4Alg models have achieved state-of-the-art performance. Moreover, pLM4Alg is the first model capable of handling prediction tasks involving residue-missed sequences and sequences containing nonstandard amino acid residues. To facilitate easy access, a user-friendly web server has been established.
