Food allergy—towards predictive testing for novel foods

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Abstract
The risks associated with IgE-mediated food allergy highlight the need for methods to screen for potential food allergens. Clinical and immunological tests are available for the diagnosis of food allergy to known food allergens, but this does not extend to the evaluation, or prediction of allergenicity in novel foods. This category includes foods produced using novel processes, genetically modified (GM) foods, and foods that might be used as alternatives to traditional foods. Through the collation and analysis of the protein sequences of known allergens and their epitopes, it is possible to identify related groups which correlate with observed clinical cross-reactivities. 3-D modelling extends the use of sequence data and can be used to display eptiopes on the surface of a molecule. Experimental models support sequence analysis and 3-D modelling. Observed crossreactivities can be examined by Western blots prepared from native 2-D gels of a whole food preparation (e.g. hazelnut, peanut), and common proteins identified. IgEs to novel proteins can be raised in Brown Norway rat (a high IgE responder strain), and the proteins tested in simulated digest to determine epitope stability. Using the CSL serum bank, epitope binding can be examined through the ability of an allergen to cross-link the high affinity IgE receptor and thereby release mediators using in vitro cell-based models. This range of methods, in combination with data mining, provides a variety of screening options for testing the potential of a novel food to be allergenic, which does not involve prior exposure to the consumer.

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