Proteomics analyses of herbicide-tolerant genetically modified, conventionally, and organically farmed soybean seeds

The present study compared genetically modified (GM) crops with crops from different farming practices using high-resolution tandem mass spectrometry (HR-MS) and proteomics bioinformatics tools. In a previously pub-lished study, a number of significant differences regarding nutritional and elemental composition between a selection of GM, non-GM conventionally farmed, and organic soybeans have been found. In the present study, the proteome-level equivalence of the same samples was assessed using HR-MS. Direct comparison of tandem mass spectra and bottom-up proteomics bioinformatics indicated that proteomes of all samples investigated were very similar overall, with only a few distinct protein expression clusters obtained for GM and organic samples. Standard bottom-up proteome analyses identified 1025 soy proteins; of these 39 were found to be differentially expressed (p < 0.01) between GM, non-GM conventionally farmed, and organically farmed soybeans. Subsequent bioinformatics analyses of these proteins highlighted several potentially affected biochemical pathways that could contribute to the compositional differences reported earlier. In addition, protein markers separating conventionally, and organically farmed soybean seeds were found and peptide markers for the detection of GM soy in food and feed samples are described. Taken together, the data presented here shows that HR-MS based proteomics approaches can be used for the detection of transgenic events in food and feed grade soy, the dif-ferentiation of organically and conventionally farmed plants, and provide mechanistic explanations of effects observed on the phenotypic level of GM plants. HR-MS and proteomic bioinformatics thus should be considered key tools when developing molecular panel approaches for detection and safety assessments of novel crop va-rieties destined for use in feed and food.

Automated summary

The present study used HR-MS and proteomics bioinformatics to compare GM crops with crops from different farming practices. The results showed significant differences in nutritional and elemental composition between GM, non-GM conventionally farmed, and organic soybeans. Proteomic analysis revealed overall similarity but distinct protein expression clusters for GM and organic samples. Bioinformatics analysis highlighted affected biochemical pathways and identified protein and peptide markers for differentiating conventionally and organically farmed soybeans, as well as detecting GM soy in food and feed samples.