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ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Food Processing and Sensory Quality Research » Research » Publications at this Location » Publication #350818

Research Project: Reducing Peanut and Tree Nut Allergy

Location: Food Processing and Sensory Quality Research

Title: Distinguishing allergens from non-allergenic homologues using Physical–Chemical Property (PCP) motifs

item LU, WENZHE - University Of Texas Medical Branch
item NEGI, SURENDRA - University Of Texas Medical Branch
item SCHEIN, CATHERINE - University Of Texas Medical Branch
item Maleki, Soheila
item Hurlburt, Barry
item BRAUN, WERNER - University Of Texas Medical Branch

Submitted to: Molecular Immunology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/27/2018
Publication Date: 4/6/2018
Citation: Lu, W., Negi, S.S., Schein, C.H., Maleki, S.J., Hurlburt, B.K., Braun, W. 2018. Distinguishing allergens from non-allergenic homologues using Physical–Chemical Property (PCP) motifs. Molecular Immunology. 99:1-8.

Interpretive Summary: We have developed a novel method to evaluate the potential aller-genicity of query sequences using allergen-specific motifs for major allergens in the top 17 Pfam. The scoring method is able to distinguish non-allergenic and allergenic sequences in these fami-lies. The motifs overlap with experimentally known IgE epitopes for peptides from peanut and other allergens, as illustrated by peptide microarray data presented here. The allergenicity scores for pectate lyase allergens and their homologous non-allergenic sequences from the human microbiome in PF00544 show a clear separation consistent with the hypothesis that proteins of resident microbes are tolerated. Scores for individual allergen sequences against motifs derived for allergens related to Bet v 1 correlated well with experimental data on their cross-reactivity. The ability of the method to predict likely IgE epitopes and cross reactivities can be improved in the future by combining the linear motifs with prediction methods for conformational IgE epitopes and those determining cross-reactive surface patches of allergens.

Technical Abstract: Motivation: Quantitative guidelines to distinguish allergenic proteins from related, but non-allergenic ones are urgently needed for regulatory agencies, biotech companies and physicians. Cataloguing the SDAP database has indicated that allergenic proteins populate a relatively small number of protein families (PFAM). However, these families also contain non-allergens, thus new methods are needed to discriminate allergenic proteins within those families. Methods: Physical–Chemical Properties (PCP)-motifs that distinguished known allergens were determined for several highly populated PFAM. Published data was used to determine the correla-tion between our motifs and experimentally determined IgE epitopes. In addition, peptides contain-ing differential scoring motifs in the peanut allergen Ara h 5 were synthesized on a microarray, and shown to bind IgE from a patient allergic to peanut. Results: A novel scoring method based on PCP-motifs that characterize known allergenic proteins was validated for several families that are highly populated by allergenic proteins. The combined motif score distinguished sequences previously determined to be allergenic from non-allergenic homologues. The method also showed a good correlation to the experimentally determined cross-reactions among the birch pollen allergen Bet v 1 and related fruit and nut allergens. Further, we demonstrated that peptides of Ara h 5 containing selective motifs coincide with experimentally de-termined IgE epitopes. The motifs also discriminated pectate lyases in the human microbiome from allergens related to mountain cedar Jun a 1. As the similar microbiome proteins lacked key motifs characteristic of the known allergens, we predict that these should not be allergenic. Software Availability: The PCPMer software is available at Contact: