Varunjikar, M.S.Bøhn, T.Sanden, M.Belghit, I.Pineda Pampliega, JavierPalmblad, M.Broll, H.Braeuning, A.Rasinger, J.D.2025-01-232025-01-232023-04-18Varunjikar, Bøhn, Sanden, Belghit, Pineda-Pampliega, Palmblad, Broll, Braeuning, & Rasinger. (2023). Proteomics analyses of herbicide-tolerant genetically modified, conventionally, and organically farmed soybean seeds. Food Control, 151. https://doi.org/10.1016/J.FOODCONT.2023.1097950956-713510.1016/j.foodcont.2023.109795https://hdl.handle.net/20.500.14352/115719Funding was provided by the Institute of Marine Research (Program Ledelse Fiskeernæring, MultiOmics Tools project 15470) and by the German Federal Institute for Risk Assessment (project 51–004).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 published 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 differentiation 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 varieties destined for use in feed and food.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/journal article1873-7129https://www.sciencedirect.com/science/article/pii/S0956713523001950?via%3Dihubhttps://www.sciencedirect.com/science/article/pii/S0956713523001950?via%3Dihubopen access631.527633.34579.67575Glycine maxProteomicsBioinformaticsMass spectrometryTransgenic soyGenetic modificationGMO detectionGMO analysisFood controlFeed controlRisk assessmentTecnología de los alimentosAgriculturaGenéticaBiotecnología3309 Tecnología de Los Alimentos2302.90 Bioquímica de Alimentos2417.14 Genética Vegetal3103.11 Semillas3103.09 Cultivos de Plantas3103.07 Cultivos Forrajeros