Integration of omics analyses into GMO risk assessment in Europe: a case study from soybean field trials

Abstract

In Europe, genetically modified organisms (GMOs) are subject to an authorization process including a mandatory risk assessment. According to the respective guidance by the European Food Safety Authority (EFSA), one of the pillars of this GMO risk assessment is a comparative analysis of the compositional and agronomic characteristics. This targeted approach has been criticized for its limitations, as it only considers pre-determined compounds, being insufficient to assess a comprehensive range of relevant compounds, including toxins and anti-nutrients, on a case-specific basis. Strategies based on advanced untargeted omics technologies have been proposed as a potential broader approach to be implemented into the initial step of the risk assessment framework. Here, we provide an example of a step-by-step omics analysis based on systems biology approach to fit into the context of European GMO regulation. We have performed field trial experiments with genetically modified (GM) Intacta™ Roundup Ready™ 2 Pro soybean containing both cry1Ac and cp4epsps transgenic inserts and analyzed its proteomic profile against the non-GM counterpart and reference varieties. Based on EFSA’s comparative endpoint-by-endpoint approach, the proteomics analysis revealed six proteins from the GMO outside the 99% tolerance intervals of reference varieties (RVs) in the equivalence test. Interestingly, from the near-isogenic (non-GM) comparator we found as many as ten proteins to be outside of the said RVs’ equivalence limits. According to EFSA’s statistical guidelines, differences found in metabolite abundance between a GMO and its non-GM comparator would not be considered biologically relevant as all compounds of concern remained within the equivalence limits of commercial RVs. By assessing the proteomic and metabolomic data through our proposed systems biology approach, we found 70 proteins, and the metabolite xylobiose as differentially expressed between the GMO and its non-GM comparator. Biological relevance of such results was revealed through a functional biological network analysis, where we found alterations in several metabolic pathways related to protein synthesis and protein processing. Moreover, the allergenicity analysis identified 43 proteins with allergenic potential being differentially expressed in the GM soybean variety. Our results demonstrate that implementation of advanced untargeted omics technologies in the risk assessment of GMOs will enable early and holistic assessment of possible adverse effects. The proposed approach can provide a better understanding of the specific unintended effects of the genetic modification on the plant’s metabolism, the involved biological networks, and their interactions, and allows to formulate and investigate dedicated risk hypotheses in the first place. We draw conclusions on a detailed comparison with the comparative assessment according to EFSA and provide scientific arguments and examples on how the current comparative approach is not fit for purpose.