Transgenic Research

, Volume 20, Issue 4, pp 939–949 | Cite as

Proteomic analysis of MON810 and comparable non-GM maize varieties grown in agricultural fields

  • Anna Coll
  • Anna Nadal
  • Michel Rossignol
  • Pere Puigdomènech
  • Maria PlaEmail author
Brief Communication


Worldwide maize is the second major agricultural commodity and around one-fourth is currently biotech, with significant application of the insect resistant event MON810 particularly in the European Union. Grains are the major commercialized part of the plant, and can be harvested after maturity (for food and feed purposes) or at late milky-starchy stage (for forage uses, with the whole plant). We assessed possible proteomic unintended effects of the MON810 transgene using two-dimensional gel electrophoresis coupled to mass spectrometry. To keep in a realistic scenario we used plants grown in agricultural fields in a region where ~50% of maize was MON810, and analyzed grains at milky-starchy stage. In maize, differential transcripts and metabolites between GM and comparable non-GM varieties tend to be variety specific. Thus, we analyzed two variety pairs, DKC6575/Tietar and PR33P67/PR33P66 which are considered representative of Food and Agriculture Organization 700 and 600 varieties commercially grown in the region. MON810 and non-GM milky-starchy grains had virtually identical proteomic patterns, with a very small number of spots showing fold-variations in the 1-1.8 range. They were all variety specific and had divergent identities and functions. Although 2DE allows the analysis of a limited dataset our results support substantial equivalence between MON810 and comparable non-GM varieties.


Genetically Modified Organism (GMO) MON810 Proteome Two-dimensional gel electrophoresis (2DE) Mass spectrometry (MS) Unexpected effects Maize 



Two-dimensional gel electrophoresis


Certified reference material


European Union


Food and Agriculture Organization


Genetically Modified Organism


Mass spectrometry


Mass spectrometry protein sequence data base


Polymerase chain reaction


Vegetative eight-leaf stage


Days after flowering



We thank R. Collado (UdG), S. Irar (CRAG), D. Centeno and V. Rofidal (INRA) for technical support; and J. Serra (E.E.A. Mas Badia), E. Melé and J. Messeguer (CRAG) for valuable suggestions. This work was financially supported by the Spanish MEC project with ref. AGL2007-65903/AGR. AC received a studentship from the Generalitat de Catalunya (2005FI 00144).

Supplementary material

11248_2010_9453_MOESM1_ESM.doc (32 kb)
Supplementary material 1 (DOC 32 kb)
11248_2010_9453_MOESM2_ESM.doc (31 kb)
Supplementary material 2 (DOC 31 kb)


  1. Baker JM, Hawkins ND, Ward JL, Lovegrove A, Napier JA, Shewry PR, Beale MH (2006) A metabolomic study of substantial equivalence of field-grown genetically modified wheat. Plant Biotechnol J 4:381–392PubMedCrossRefGoogle Scholar
  2. Barros E, Lezar S, Anttonen MJ, Van Dijk JP, Rohlig RM, Kok EJ, Engel KH (2010) Comparison of two GM maize varieties with a near-isogenic non-GM variety using transcriptomics, proteomics and metabolomics. Plant Biotechnol J. doi:  10.1111/j.1467-7652.2009.00487.x
  3. Baudo MM, Lyons R, Powers S, Pastori GM, Edwards KJ, Holdsworth MJ, Shewry PR (2006) Transgenesis has less impact on the transcriptome of wheat grain than conventional breeding. Plant Biotechnol J 4:369–380PubMedCrossRefGoogle Scholar
  4. Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72:248–254PubMedCrossRefGoogle Scholar
  5. Brandao AR, Barbosa HS, Arruda MAZ (2010) Image analysis of two dimensional gel electrophoresis for comparative proteomics of transgenic and non-transgenic soybean seeds. J Proteomics 73:1433–1440PubMedCrossRefGoogle Scholar
  6. Catchpole GS, Beckmann M, Enot DP, Mondhe M, Zywicki B, Taylor J, Hardy N, Smith A, King RD, Kell DB, Fiehn O, Draper J (2005) Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc Natl Acad Sci USA 102:14458–14462PubMedCrossRefGoogle Scholar
  7. Cheng KC, Beaulieu J, Iquira E, Belzile FJ, Fortin MG, Stromvik MV (2008) Effect of transgenes on global gene expression in soybean is within the natural range of variation of conventional cultivars. J Agric Food Chem 56:3057–3067PubMedCrossRefGoogle Scholar
  8. Coll A, Nadal A, Palaudelmàs M, Messeguer J, Melé E, Puigdomènech P, Pla M (2008) Lack of repeatable differential expression patterns between MON810 and comparable commercial varieties of maize. Plant Mol Biol 68:105–117PubMedCrossRefGoogle Scholar
  9. Coll A, Nadal A, Collado R, Capellades G, Kubista M, Messeguer J, Pla M (2010) Natural variation explains most transcriptomic changes among maize plants of MON810 and comparable non-GM varieties subjected to two N-fertilization farming practices. Plant Mol Biol. doi: 10.1007/s11103-010-9624-5
  10. Corpillo D, Gardini G, Vaira AM, Basso M, Aime S, Accotto GP, Fasano M (2004) Proteomics as a tool to improve investigation of substantial equivalence in Genetically Modified Organisms: the case of a virus-resistant tomato. Proteomics 4:193–200PubMedCrossRefGoogle Scholar
  11. Dubouzet JG, Ishihara A, Matsuda F, Miyagawa H, Iwata H, Wakasa K (2007) Integrated metabolomic and transcriptomic analyses of high-tryptophan rice expressing a mutant anthranilate synthase alpha subunit. J Exp Bot 58:3309–3321PubMedCrossRefGoogle Scholar
  12. EFSA (2004) Guidance document of the Scientific Panel on Genetically Modified Organisms for the risk assessment of genetically modified plants and derived food and feed. EFSA Journal 99:1–94Google Scholar
  13. El Ouakfaoui S, Miki B (2005) The stability of the Arabidopsis transcriptome in transgenic plants expressing the marker genes nptII and uidA. Plant J 41:791–800PubMedCrossRefGoogle Scholar
  14. Gregersen PL, Brinch-Pedersen H, Holm PB (2005) A microarray-based comparative analysis of gene expression profiles during grain development in transgenic and wild type wheat. Transgenic Res 14:887–905PubMedCrossRefGoogle Scholar
  15. Hernández M, Pla M, Esteve T, Prat S, Puigdomènech P, Ferrando A (2003) A specific real-time quantitative PCR detection system for event MON810 in maize YieldGard based on the 3’-transgene integration sequence. Transgenic Res 12:179–189PubMedCrossRefGoogle Scholar
  16. Hernández M, Esteve T, Pla M (2005) Real-time PCR based methods for quantitative detection of barley, rice, sunflower and wheat. J Agric Food Chem 53:7003–7009PubMedCrossRefGoogle Scholar
  17. Holst-Jensen A, De Loose M, Van den Eede G (2006) Coherence between legal requirements and approaches for detection of Genetically Modified Organisms (GMOs) and their derived products. J Agric Food Chem 54:2799–2809PubMedCrossRefGoogle Scholar
  18. Ioset JR, Urbaniak B, Ndjoko-Ioset K, Wirth J, Martin F, Gruissem W, Hostettmann K, Sautter C (2007) Flavonoid profiling among wild type and related GM wheat varieties. Plant Mol Biol 65:645–654PubMedCrossRefGoogle Scholar
  19. James C (2010) Global Status of Commercialized Biotech/GM Crops: 2009. ISAAA Briefs 41. ISAAA, Ithaca, NYGoogle Scholar
  20. Khalf M, Goulet C, Vorster J, Brunelle F, Anguenot R, Fliss I, Michaud D (2010) Tubers from potato lines expressing a tomato Kunitz protease inhibitor are substantially equivalent to parental and transgenic controls. Plant Biotechnol J 8:155–169PubMedCrossRefGoogle Scholar
  21. Kristensen C, Morant M, Olsen CE, Ekstrom CT, Galbraith DW, Moller BL, Bak S (2005) Metabolic engineering of dhurrin in transgenic Arabidopsis plants with marginal inadvertent effects on the metabolome and transcriptome. Proc Natl Acad Sci U S A 102:1779–1784PubMedCrossRefGoogle Scholar
  22. La Paz JL, Vicient CM, Puigdomènech P, Pla M (2010) Characterization of polyadenylated cryIA(b) transcripts in maize MON810 commercial varieties. Anal Bioanal Chem 396:2125–2133PubMedCrossRefGoogle Scholar
  23. Lehesranta SJ, Davies HV, Shepherd LV, Nunan N, McNicol JW, Auriola S, Koistinen KM, Suomalainen S, Kokko HI, Karenlampi SO (2005) Comparison of tuber proteomes of potato varieties, landraces, and genetically modified lines. Plant Physiol 138:1690–1699PubMedCrossRefGoogle Scholar
  24. Levandi T, Leon C, Kaljurand M, Garcia-Canas V, Cifuentes A (2008) Capillary electrophoresis time-of-flight mass spectrometry for comparative metabolomics of transgenic versus conventional maize. Anal Chem 80:6329–6335PubMedCrossRefGoogle Scholar
  25. López A, Serra J, Capellades G, Betbesé JA, Salvia J (2009) Experimetnació de noves varietats de blat de moro per a gra. Indicacions per a la Campanya 2009. Dossier Tècnic 35:3–17Google Scholar
  26. Manetti C, Bianchetti C, Casciani L, Castro C, Di Cocco ME, Miccheli A, Motto M, Conti F (2006) A metabonomic study of transgenic maize (Zea mays) seeds revealed variations in osmolytes and branched amino acids. J Exp Bot 57:2613–2625PubMedCrossRefGoogle Scholar
  27. Miki B, Abdeen A, Manabe Y, MacDonald P (2009) Selectable marker genes and unintended changes to the plant transcriptome. Plant Biotechnol J 7:211–218PubMedCrossRefGoogle Scholar
  28. Natarajan S, Xu C, Caperna TJ, Garrett WM (2005) Comparison of protein solubilization methods suitable for proteomic analysis of soybean seed proteins. Anal Biochem 342:214–220PubMedCrossRefGoogle Scholar
  29. Neuhoff V, Arold N, Taube D, Ehrhardt W (1988) Improved staining of proteins in polyacrylamide gels including isoelectric focusing gels with clear background at nanogram sensitivity using Coomassie Brilliant Blue G-250 and R-250. Electrophoresis 9:255–262PubMedCrossRefGoogle Scholar
  30. Piccioni F, Capitani D, Zolla L, Mannina L (2009) NMR metabolic profiling of transgenic maize with the Cry1Ab gene. J Agric Food Chem 57:6041–6049PubMedCrossRefGoogle Scholar
  31. Ren Y, Lv J, Wang H, Li L, Peng Y, Qu LJ (2009) A comparative proteomics approach to detect unintended effects in transgenic Arabidopsis. J Genet Genomics 36:629–639PubMedCrossRefGoogle Scholar
  32. Rosati A, Bogani P, Santarlasci A, Buiatti M (2008) Characterisation of 3’ transgene insertion site and derived mRNAs in MON810 YieldGard maize. Plant Mol Biol 67:271–281PubMedCrossRefGoogle Scholar
  33. Ruebelt MC, Lipp M, Reynolds TL, Schmuke JJ, Astwood JD, DellaPenna D, Engel KH, Jany KD (2006) Application of two-dimensional gel electrophoresis to interrogate alterations in the proteome of gentically modified crops. 3. Assessing unintended effects. J Agric Food Chem 54:2169–2177PubMedCrossRefGoogle Scholar
  34. Van Dijk JP, Cankar K, Scheffer SJ, Beenen HG, Shepherd LV, Stewart D, Davies HV, Wilkockson SJ, Leifert C, Gruden K, Kok EJ (2009) Transcriptome analysis of potato tubers–effects of different agricultural practices. J Agric Food Chem 57:1612–1623PubMedCrossRefGoogle Scholar
  35. Zolla L, Rinalducci S, Antonioli P, Righetti PG (2008) Proteomics as a complementary tool for identifying unintended side effects occurring in transgenic maize seeds as a result of genetic modifications. J Proteome Res 7:1850–1861PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Anna Coll
    • 1
  • Anna Nadal
    • 1
  • Michel Rossignol
    • 2
  • Pere Puigdomènech
    • 3
  • Maria Pla
    • 1
    Email author
  1. 1.Institute for Food and Agricultural Technology (INTEA)University of GironaGironaSpain
  2. 2.National Institute for Agricultural Research (INRA), UR1199, LPFMontpellier Cedex 01France
  3. 3.Centre for Research in Agricultural Genomics, CSIC-IRTA-UABBarcelonaSpain

Personalised recommendations