Characterization of GMO or glyphosate effects on the composition of maize grain and maize-based diet for rat feeding
In addition to classical targeted biochemical analyses, metabolomic analyses seem pertinent to reveal expected as well as unexpected compositional differences between plant genetically modified organisms (GMO) and non-GMO samples. Data previously published in the existing literature led to divergent conclusions on the effect of maize transgenes on grain compositional changes and feeding effects. Therefore, a new study examining field-grown harvested products and feeds derived from them remains useful.
Our aim was to use a metabolomics approach to characterize grain and grain-based diet compositional changes for two GMO events, one involving Bacillus thuringiensis toxin to provide insect resistance and the other one conferring herbicide tolerance by detoxification of glyphosate. We also investigated the potential compositional modifications induced by the use of a glyphosate-based herbicide on the transgenic line conferring glyphosate tolerance.
The majority of statistically significant differences in grain composition, evidenced by the use of 1H-NMR profiling of polar extracts and LC-ESI-QTOF-MS profiling of semi-polar extracts, could be attributed to the combined effect of genotype and environment. In comparison, transgene and glyphosate effects remained limited in grain for the compound families studied. Some but not all compositional changes observed in grain were also detected in grain-based diets formulated for rats.
Only part of the data previously published in the existing literature on maize grains of plants with the same GMO events could be reproduced in our experiment. All spectra have been deposited in a repository freely accessible to the public. Our grain and diet characterization opened the way for an in depth study of the effects of these diets on rat health.
KeywordsMaize Metabolomics GMO Grain Rat diet
Liquid chromatography electrospray-ionization time-of-flight mass spectrometry
Nuclear magnetic resonance
Principal component analysis
We thank Drs Pablo Steinberg, Ralf Wilhelm and Joachim Schiemann (G-TwYST, EC project) for having shared the maize production and preliminary targeted analyses of the grains, and Dr Maria Pla (IRTA Mas Badia Field Station) and the farmers involved in maize culture, harvest and drying for providing the grain samples cultivated in Spain. We are grateful to the members of the scientific council of RiskOGM program for their follow-up and advice.
We thank the French Ministry of Ecological and Solidarity Transition (RiskOGM program) for the financial support of the GMO90+ research project, and MetaboHUB (ANR-11-INBS-0010) and PHENOME (ANR-11-INBS-0012) projects for financing.
Compliance with ethical standards
Conflict of interest
Conflicts of interest of the principal investigators are declared on the public RiskOGM programme website (http://recherche-riskogm.fr/en/page/partners-pdis).
The GMO plant samples followed dedicated laboratory procedures concerning their identification and destruction. Although this article is related to a project involving animals (Study approved by French Ethical Committee CETEA), it does not contain any study with animals performed by any of the authors.
- Bakan, B., Melcion, D., Richard-Molard, D., & Cahagnier, B. (2002). Fungal growth and Fusarium mycotoxin content in isogenic traditional maize and genetically modified maize grown in France and Spain. Journal of Agricultural and Food Chemistry, 50(4), 728–731. https://doi.org/10.1021/jf0108258.CrossRefPubMedGoogle Scholar
- Baker, J. M., Hawkins, N. D., Ward, J. L., Lovegrove, A., Napier, J. A., Shewry, P. R., et al. (2006). A metabolomic study of substantial equivalence of field-grown genetically modified wheat. Plant Biotechnology Journal, 4(4), 381–392. https://doi.org/10.1111/j.1467-7652.2006.00197.x.CrossRefPubMedGoogle Scholar
- Benevenuto, R. F., Agapito-Tenfen, S. Z., Vilperte, V., Wikmark, O.-G., van Rensburg, P. J., & Nodari, R. O. (2017). Molecular responses of genetically modified maize to abiotic stresses as determined through proteomic and metabolomic analyses. PLoS ONE, 12(2), e0173069. https://doi.org/10.1371/journal.pone.0173069.CrossRefPubMedPubMedCentralGoogle Scholar
- Biais, B., Allwood, J. W., Deborde, C., Xu, Y., Maucourt, M., Beauvoit, B., et al. (2009). 1H NMR, GC-EI-TOFMS, and data set correlation for fruit metabolomics: Application to spatial metabolite analysis in melon. Analytical Chemistry, 81(8), 2884–2894. https://doi.org/10.1021/ac9001996.CrossRefPubMedGoogle Scholar
- Bowers, E., Hellmich, R., & Munkvold, G. (2014). Comparison of fumonisin contamination using HPLC and ELISA methods in Bt and near-isogenic maize hybrids infested with european corn borer or western bean cutworm. Journal of Agricultural and Food Chemistry, 62(27), 6463–6472. https://doi.org/10.1021/jf5011897.CrossRefPubMedGoogle Scholar
- Catchpole, G. S., Beckmann, M., Enot, D. P., Mondhe, M., Zywicki, B., Taylor, J., et al. (2005). Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proceedings of the National Academy of Sciences of the United States of America, 102(40), 14458–14462. https://doi.org/10.1073/pnas.0503955102.CrossRefPubMedPubMedCentralGoogle Scholar
- Graham, S. F., Hollis, J. H., Migaud, M., & Browne, R. A. (2009). Analysis of betaine and choline contents of aleurone, bran, and flour fractions of wheat (Triticum aestivum L.) using 1H nuclear magnetic resonance (NMR) spectroscopy. Journal of Agricultural and Food Chemistry, 57(5), 1948–1951. https://doi.org/10.1021/jf802885m.CrossRefPubMedGoogle Scholar
- Hall, R. D. (2011). Plant metabolomics in a nutshell: Potential and future challenges. In R. D. Hall (Ed.), Biology of plant metabolomics (Vol. 43, pp. 1–24). Oxford: Wiley-Blackwell.Google Scholar
- Harrigan, G. G., Venkatesh, T. V., Leibman, M., Blankenship, J., Perez, T., Halls, S., et al. (2016). Evaluation of metabolomics profiles of grain from maize hybrids derived from near-isogenic GM positive and negative segregant inbreds demonstrates that observed differences cannot be attributed unequivocally to the GM trait. Metabolomics, 12(5), 82. https://doi.org/10.1007/s11306-016-1017-6.CrossRefPubMedPubMedCentralGoogle Scholar
- Hetherington, P. R., Reynolds, T. L., Marshall, G., & Kirkwood, R. C. (1999). The absorption, translocation and distribution of the herbicide glyphosate in maize expressing the CP-4 transgene. Journal of Experimental Botany, 50(339), 1567–1576. https://doi.org/10.1093/jxb/50.339.1567.CrossRefGoogle Scholar
- Kumar, V., Rani, A., Goyal, L., Dixit, A. K., Manjaya, J., Dev, J., et al. (2010). Sucrose and raffinose family oligosaccharides (RFOs) in soybean seeds as influenced by genotype and growing location. Journal of Agricultural and Food Chemistry, 58(8), 5081–5085. https://doi.org/10.1021/jf903141s.CrossRefPubMedGoogle Scholar
- Le Gall, G., Colquhoun, I. J., Davis, A. L., Collins, G. J., & Verhoeyen, M. E. (2003). Metabolite profiling of tomato (Lycopersicon esculentum) using 1H NMR spectroscopy as a tool to detect potential unintended effects following a genetic modification. Journal of Agricultural and Food Chemistry, 51(9), 2447–2456. https://doi.org/10.1021/jf0259967.CrossRefPubMedGoogle Scholar
- Leon, C., Rodriguez-Meizoso, I., Lucio, M., Garcia-Cañas, V., Ibañez, E., Schmitt-Kopplin, P., et al. (2009). Metabolomics of transgenic maize combining Fourier transform-ion cyclotron resonance-mass spectrometry, capillary electrophoresis-mass spectrometry and pressurized liquid extraction. Journal of Chromatography A, 1216(43), 7314–7323. https://doi.org/10.1016/j.chroma.2009.04.092.CrossRefPubMedGoogle Scholar
- Levandi, T., Leon, C., Kaljurand, M., Garcia-Cañas, V., & Cifuentes, A. (2008). Capillary electrophoresis time-of-flight mass spectrometry for comparative metabolomics of transgenic versus conventional maize. Analytical Chemistry, 80(16), 6329–6335. https://doi.org/10.1021/ac8006329.CrossRefPubMedGoogle Scholar
- Manetti, C., Bianchetti, C., Casciani, L., Castro, C., Di Cocco, M. E., Miccheli, A., et al. (2006). A metabonomic study of transgenic maize (Zea mays) seeds revealed variations in osmolytes and branched amino acids. Journal of Experimental Botany, 57(11), 2613–2625. https://doi.org/10.1093/jxb/erl025.CrossRefPubMedGoogle Scholar
- Mesnage, R., Agapito-Tenfen, S. Z., Vilperte, V., Renney, G., Ward, M., Séralini, G.-E., et al. (2016). An integrated multi-omics analysis of the NK603 Roundup-tolerant GM maize reveals metabolism disturbances caused by the transformation process. Scientific Reports, 6, 37855. https://doi.org/10.1038/srep37855.CrossRefPubMedPubMedCentralGoogle Scholar
- Moing, A., Maucourt, M., Renaud, C., Gaudillere, M., Brouquisse, R., Lebouteiller, B., et al. (2004). Quantitative metabolic profiling by 1-dimensional 1H-NMR analyses: Application to plant genetics and functional genomics. Functional Plant Biology, 31(9), 889–902. https://doi.org/10.1071/FP04066.CrossRefGoogle Scholar
- Mounet, F., Lemaire-Chamley, M., Maucourt, M., Cabasson, C., Giraudel, J.-L., Deborde, C., et al. (2007). Quantitative metabolic profiles of tomato flesh and seeds during fruit development: Complementary analysis with ANN and PCA. Metabolomics, 3(3), 273–288. https://doi.org/10.1007/s11306-007-0059-1.CrossRefGoogle Scholar
- Onkokesung, N., Gaquerel, E., Kotkar, H., Kaur, H., Baldwin, I. T., & Galis, I. (2012). MYB8 Controls inducible phenolamide levels by activating three novel hydroxycinnamoyl-coenzyme A:polyamine transferases in Nicotiana attenuata. Plant Physiology, 158(1), 389–407. https://doi.org/10.1104/pp.111.187229.CrossRefPubMedGoogle Scholar
- Ridley, W. P., Sidhu, R. S., Pyla, P. D., Nemeth, M. A., Breeze, M. L., & Astwood, J. D. (2002). Comparison of the nutritional profile of glyphosate-tolerant corn event NK603 with that of conventional corn (Zea mays L.). Journal of Agricultural and Food Chemistry, 50(25), 7235–7243. https://doi.org/10.1021/jf0205662.CrossRefPubMedGoogle Scholar
- Schmidt, K., Döhring, J., Kohl, C., Pla, M., Kok, E. J., Glandorf, D. C. M., et al. (2016). Proposed criteria for the evaluation of the scientific quality of mandatory rat and mouse feeding trials with whole food/feed derived from genetically modified plants. Archives of toxicology, 90(9), 2287–2291. https://doi.org/10.1007/s00204-016-1762-3.CrossRefPubMedPubMedCentralGoogle Scholar
- Skogerson, K., Harrigan, G. G., Reynolds, T. L., Halls, S. C., Ruebelt, M., Iandolino, A., et al. (2010). Impact of genetics and environment on the metabolite composition of maize grain. Journal of Agricultural and Food Chemistry, 58(6), 3600–3610. https://doi.org/10.1021/jf903705y.CrossRefPubMedGoogle Scholar
- Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R., & Siuzdak, G. (2006). XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Analytical Chemistry, 78(3), 779–787. https://doi.org/10.1021/ac051437y.CrossRefPubMedGoogle Scholar
- t’Kindt, R., Morreel, K., Deforce, D., Boerjan, W., & Van Bocxlaer, J. (2009). Joint GC–MS and LC–MS platforms for comprehensive plant metabolomics: Repeatability and sample pre-treatment. Journal of Chromatography B, 877(29), 3572–3580. https://doi.org/10.1016/j.jchromb.2009.08.041.CrossRefGoogle Scholar
- Tang, W., Hazebroek, J., Zhong, C., Harp, T., Vlahakis, C., Baumhover, B., et al. (2017). Effect of genetics, environment, and phenotype on the metabolome of maize hybrids using GC/MS and LC/MS. Journal of Agricultural and Food Chemistry, 65(25), 5215–5225. https://doi.org/10.1021/acs.jafc.7b00456.CrossRefPubMedGoogle Scholar
- Venkatesh, T. V., Chassy, A. W., Fiehn, O., Flint-Garcia, S., Zeng, Q., Skogerson, K., et al. (2016). Metabolomic assessment of key maize resources: GC-MS and NMR Profiling of grain from B73 hybrids of the Nested Association Mapping (NAM) Founders and of geographically diverse landraces. Journal of Agricultural and Food Chemistry, 64(10), 2162–2172. https://doi.org/10.1021/acs.jafc.5b04901.CrossRefPubMedGoogle Scholar
- Watson, S. A. (2003). Description, development, structure and composition of the corn kernel. In P. J. White & L. A. Johnson (Eds.), Corn: Chemistry and technology, Second Edition (pp. 69–106). St Paul, MN: AACC.Google Scholar
- Wusirika, R., Bohn, M., Lai, J., & Kole, C. (Eds.). (2014). Genetics, genomics and breeding of maize. Boca Raton, FL: CRC Press.Google Scholar