alexa Soybean glycinin G1 acidic chain shares IgE epitopes with peanut allergen Ara h 3.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Beardslee TA, Zeece MG, Sarath G, Markwell JP

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Abstract BACKGROUND: The identification of IgE epitopes for proteins is the first step in understanding the interaction of allergens with the immune system. Proteins from the legume family have shown in vitro cross-reactivity in IgE-binding assays, but this cross-reactivity is rarely clinically significant. Resolution of this discrepancy requires IgE epitope mapping of legume family protein allergens. METHODS: We constructed six fusion proteins representing overlapping regions of soybean glycinin G1 acidic chain. These fusion proteins were used in immunoblotting and a novel sandwich ELISA with pooled sera from soy-allergic individuals to reveal a common IgE-binding region. This region was the focus for IgE epitope mapping using overlapping synthetic peptides. RESULTS: Data from the fusion protein experiments revealed an IgE-binding region consisting of residues F192-I265. Analysis of the overlapping synthetic peptides to this region indicated that IgE epitopes to glycinin G1 acidic chain consist of residues G217-V235 and G253-I265. The epitopes identified for glycinin G1 acidic chain are homologous to IgE epitopes previously identified for the peanut allergen Ara h 3 [1]. However, residues identified by alanine scanning in the peanut epitopes as being important for IgE binding are different in the natural soybean epitopes. CONCLUSIONS: The IgE epitopes identified for glycinin G1 acidic chain apparently represent an allergenic region of several legume family seed storage proteins. Our findings indicate that the identification of IgE epitopes and structural analysis of legume family proteins will provide valuable information to the study of food allergies. Copyright 2000 S. Karger AG, Basel This article was published in Int Arch Allergy Immunol and referenced in Journal of Data Mining in Genomics & Proteomics

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