 discrepancy is likely due to the fact that not all glycinin forms were quantified including glycinin subunit 5 (Gly G5). A previous report on soybean allergens using the same quantitation technology reported substantially lower levels of these storage proteins (Houston et al., 2010). However, the values for that study were for peptide concentrations not proteins which required correction to intact protein molecular mass as listed in the methods. Alternative methods, such as protein ELISA, were not commercially available for the individual allergens in this study.
The levels of allergens have been previously reported to vary between non-GM varieties. For example, in a study of non-GM soybean varieties involving skin reactivity and in vitro IgE binding of 10 soybean cultivars, Codina et al. (2003) reported up to sixfold differences in IgE binding potencies, while Sten et al. (2004) reported wide variation in IgE binding to different varieties of the same species of non-GM crops. To investigate an allergen’s natural variation in expression, Xu et al. (2007) evaluated 16 soybean varieties and showed relative variation in allergens, such as Gly m 5 and Gly m Bd 30K, between wild and cultivated non-GM soybean varieties. Houston et al. (2010) quantified soybean allergens in 20 non-GM varieties and observed anywhere from statistically insignificant changes in expression for some allergens to as much as 10-fold for glycinin G3 (a Gly m 6 isoform) when comparing two different varieties.
These examples give an indication of variation in the allergen levels of various non-GM soybean brought about by breeding. Further research is needed to establish a “baseline” of allergen levels from a composite of both the genetic and even broader environmental factors. Toward this goal, we report here a comparison of genetic versus environmental variation in the expression of eight soybean allergens. While the genetic variation in this study was limited (i.e., early, edible ancestors of soybean were not studied), the environmental component was vast – spanning three agriculturally relevant climate zones (4–6) covering a large range of North America. The results indicate a greater influence of environment on allergen variation, although this was dependent upon the allergen in question, suggesting that protein function is the determining factor in a “genetic versus environmental” discussion. At this point in time, it is apparent that currently one cannot simply speculate or predict how allergens will respond to either a changing genetic background or environment.
While scientifically interesting, this does not directly address the concerns of regulatory safety. The current human health safety evaluation of GM food crops involves an evaluation of endogenous allergen levels using serum IgE screening when its’ non-GM equivalent is a commonly allergenic food (e.g., soybean; Holzhauser et al., 2008; Thomas et al., 2008). Given the natural variation in levels of endogenous allergens of available non-GM food crops due to differences in: (1) the genetics of commercial varieties (Houston et al., 2010) and (2) the interactions of those varieties with the environment (i.e., temperature, moisture, nutrients, plant pathogens, insect loads; Sancho et al., 2006a,b; Goodman et al., 2008; Doerrer et al., 2010), it is evident that we are only beginning to understand the contextual importance of natural variation in allergen assessment. It is important to note that no safety associated information is gained by performing endogenous allergen comparison studies on GM soybean if the analysis isn’t compared to non-GM soybean levels (i.e., natural variability) already in the food supply. With antibody-based assays that monitor allergen expression, it is necessary to monitor each of these non-GM reference varieties along with the GM line, simply because the assays are either relative or non-specific. The AQUA™-MRM approach employed here does not have these limitations and could conceivably allow for direct monitoring of only the GM line, once sufficient reference data hav