Abstract
GM risk assessments are crucial for determination and prevention of potential adverse effects through early detection and proper evaluation of intended and potential unintended changes in molecular breeding. In this context, the concept of ‘substantial equivalence’ has been suggested for the safety tests of GM products for many years. This study evaluated differences between four types of Glycine max crops; transgenic soybean, its non-transgenic counterpart, gamma induced soybean mutant and its parental line, at proteomic level in context of substantial equivalence. The results revealed the ratio of differentially expressed protein spots to total protein spots in mutants compared to their parental line was 50.7%. This ratio was 41.2% in transgenic plants compared to their counterparts. Scatter plot analysis presented those mutant plants showed a wider spread than transgenic plants in terms of distribution of proteins. It was determined that up-regulated proteins in mutant plants have various biological roles in processes such as development, stress response, photorespiration and ribosomal subunit assembly. In transgenic plants, upregulated proteins were shown to have diverse biological roles in processes such as ribosomal subunit assembly, electron transport, amino acid and nucleic acid metabolism and cell wall biogenesis. Although debate on the potential unintended effects focuses on GM organisms, our results point out that the plants that gained new characteristics by various breeding methods should be characterized in all aspects case-by-case.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abe A, Kosugi S, Yoshida K et al (2012) Genome sequencing reveals agronomically important loci in rice using mutmap. Nat Biotechnol 30(2):174–178. https://doi.org/10.1038/nbt.2095
Anai T (2012) Potential of a mutant-based reverse genetic approach for functional genomics and molecular breeding in soybean. Breed Sci 61:462–467. https://doi.org/10.1270/jsbbs.61.462
Anderson EJ, Ali ML, Beavis WD et al (2019) Soybean [Glycine max (L.) Merr.] breeding: history, improvement, production and future opportunities, advances in plant breeding strategies: legumes. In: Khayri J, Jain S, Johnson D (eds) Advances in plant breeding strategies: legumes, 1st edn. Springer, Cham, pp 431–516
Arase S, Hase Y, Abe J et al (2011) Optimization of ion-beam irradiation for mutagenesis in soybean: effects on plant growth and production of visibly altered mutants. Plant Biotech 28(3):323–329. https://doi.org/10.5511/plantbiotechnology.11.0111a
Ayan A, Meriç S, Gümüş T, Atak Ç (2022) Current strategies and future of mutation breeding in soybean improvement. In: Ohyama T, Takahashi Y, Ohtake N, Sato T, Tanabata S (eds) Soybean–recent advances in research and applications. IntechOpen. https://doi.org/10.5772/intechopen.104796
Bado S, Forster BP, Nielen S et al (2015) Plant mutation breeding: current progress and future assessment. Plant Breed Rev 39:23–88. https://doi.org/10.1002/9781119107743.ch02
Balsamo GM, Cangahuala-Inocente GC, Bertoldo JB et al (2011) Proteomic analysis of four Brazilian MON810 maize varieties and their four non-genetically-modified isogenic varieties. J Agric Food Chem 59:11553–11559. https://doi.org/10.1021/jf202635r
Barbosa HS, Arruda SCC, Azevedo RA, Arruda MAZ (2012) New insights on proteomics of transgenic soybean seeds: evaluation of differential expressions of enzymes and proteins. Anal Bioanal Chem 402:299–314. https://doi.org/10.1007/s00216-011-5409-1
Barros E, Lezar S, Anttonen MJ et al (2010) Comparison of two GM maize varieties with a near-isogenic non-GM variety using transcriptomics, proteomics and metabolomics. Plant Biotechnol J 8:436–451. https://doi.org/10.1111/j.1467-7652.2009.00487.x
Batista R, Saibo N, Lourenço T, Oliveira MM (2008) Microarray analyses reveal that plant mutagenesis may induce more transcriptomic changes than transgene insertion. Proc Natl Acad Sci U S A 105:3640–3645. https://doi.org/10.1073/pnas.0707881105
Bolon Y-T, Haun WJ, Xu WW et al (2011) Phenotypic and genomic analyses of a fast neutron mutant population resource in soybean. Plant Physiol 156:240–253. https://doi.org/10.1104/pp.110.170811
Brandão 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. https://doi.org/10.1016/j.jprot.2010.01.009
Çelik Ö, Ayan A, Meriç S, Atak Ç (2021) Comparison of tolerance related proteomic profiles of two drought tolerant tomato mutants improved by gamma radiation. J Biotechnol 330:35–44. https://doi.org/10.1016/j.jbiotec.2021.02.012
Davies H (2010) A role for “omics” technologies in food safety assessment. Food Control 21:1601–1610. https://doi.org/10.1016/j.foodcont.2009.03.002
de Campos BK, Galazzi RM, dos Santos BM et al (2020) Comparison of generational effect on proteins and metabolites in non-transgenic and transgenic soybean seeds through the insertion of the cp4-EPSPS gene assessed by omics-based platforms. Ecotoxicol Environ Saf 202:110918. https://doi.org/10.1016/j.ecoenv.2020.110918
EFSA (2011) Guidance for risk assessment of food and feed from genetically modified plants. EFSA J 9(5):2150
Esnault MA, Legue F, Chenal C (2010) Ionizing radiation: advances in plant response. Environ Exp Bot 68(3):231–237. https://doi.org/10.1016/j.envexpbot.2010.01.007
Gady AL, Hermans FW, Van de Wal MH et al (2009) Implementation of two high through-put techniques in a novel application: detecting point mutations in large EMS mutated plant populations. Plant Methods 5:13. https://doi.org/10.1186/1746-4811-5-13
Ghaffari A, Gharechahi J, Nakhoda B, Salekdeh GH (2014) Physiology and proteome responses of two contrasting rice mutants and their wild type parent under salt stress conditions at the vegetative stage. J Plant Physiol 171:31–44. https://doi.org/10.1016/j.jplph.2013.07.014
Gong CY, Li Q, Yu HT et al (2012) Proteomics insight into the biological safety of transgenic modification of rice as compared with conventional genetic breeding and spontaneous genotypic variation. J Proteome Res. https://doi.org/10.1021/pr300148w
Hoagland DR and Arnon DI (1950) The water-culture method for growing plants without soil. circular california agricultural experiment station 347(2nd edit)
Hunter MC, Smith RG, Schipanski ME et al (2017) Agriculture in 2050: recalibrating targets for sustainable intensification. Bioscience 67(4):386–391
IAEA (2020) Mutant variety database. In: Jt. FAO/IAEA. https://mvd.iaea.org/#!Search. Accessed 16 April 2022
ISAAA (2018) Global status of commercialized biotech/GM crops İn: 2018: Biotech crops continue to help meet the challenges of ıncreased population and climate change, Brief No: 54
Islam N, Krishnan HB, Natarajan S (2020) Proteomic profiling of fast neutron-induced soybean mutant unveiled pathways associated with increased seed protein content. J Proteome Res 19:3936–3944. https://doi.org/10.1021/acs.jproteome.0c00160
Karthika R, Subba Lakshmi B (2006) Effect of gamma rays and EMS on two varieties of soybean. Asian J Plant Sci. https://doi.org/10.3923/ajps.2006.721.724
Khan MH, Tyagi SD, Dar ZA (2013) Screening of soybean (Glycine Max (L.) Merrill) genotypes for resistance to rust, yellow mosaic and pod shattering. In: El-Shemy H (ed) Soybean–pest resistance. InTech. https://doi.org/10.5772/54697
Kim DG, Lyu JI, Kim JM et al (2022) Identification of loci governing agronomic traits and mutation hotspots via a gbs-based genome-wide association study in a soybean mutant diversity pool. Int J Mol Sci 23(18):10441. https://doi.org/10.3390/ijms231810441
Kohli A, Miro B, Twyman RM (2010) Transgene integration, expression and stability in plants: strategies for improvements. In: Kole C, Michler CH, Abbott AG, Hall TC (eds) Transgenic crop plants, 1st edn. Springer, Berlin, Heidelberg, pp 201–237
Ladics GS, Bartholomaeus A, Bregitzer P et al (2015) Genetic basis and detection of unintended effects in genetically modified crop plants. Transgenic Res 24:587–603. https://doi.org/10.1007/s11248-015-9867-7
Laemmli UK (1970) Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 227:680–685. https://doi.org/10.1038/227680a0
Lakhssassi N, Zhou Z, Liu S et al (2017) Characterization of the FAD2 gene family in soybean reveals the limitations of gel-based TILLING in genes with high copy number. Front Plant Sci 8:324
Lee KJ, Kim JB, Kim SH et al (2011) Alteration of seed storage protein composition in soybean [Glycine max (L.) Merrill] mutant lines induced by γ-irradiation mutagenesis. J Agric Food Chem 59:12405–12410. https://doi.org/10.1021/jf202809j
Lee S, Van K, Sung M et al (2019) Genome-wide association study of seed protein, oil and amino acid contents in soybean from maturity groups I to IV. Theor Appl Genet 132:1639–1659. https://doi.org/10.1007/s00122-019-03304-5
Li X, Lassner M, Zhang Y (2002) Deleteagene: a fast neutron deletion mutagenesis-based gene knockout system for plants. Comp Funct Genomics 3(2):158–160. https://doi.org/10.1002/cfg.148
Liu Y, Zhang YX, Song SQ et al (2015) A proteomic analysis of seeds from Bt-transgenic brassica napus and hybrids with wild B. juncea. Sci Rep 5:1–13. https://doi.org/10.1038/srep15480
Liu W, Xu W, Li L et al (2018) iTRAQ-based quantitative tissue proteomic analysis of differentially expressed proteins (DEPs) in non-transgenic and transgenic soybean seeds. Sci Rep 8:1–10. https://doi.org/10.1038/s41598-018-35996-y
Liu S, Ge F, Huang W et al (2019) Effective identification of soybean candidate genes involved in resistance to soybean cyst nematode via direct whole genome re-sequencing of two segregating mutants. Theor Appl Genet 132(9):2677–2687. https://doi.org/10.1007/s00122-019-03381-6
Liu W, Li L, Zhang Z et al (2020) iTRAQ-based quantitative proteomic analysis of transgenic and non-transgenic maize seeds. J Food Compos Anal 92:103564. https://doi.org/10.1016/j.jfca.2020.103564
Liu W, Chen H, Li L et al (2021) Proteomic analysis of the seeds of transgenic rice lines and the corresponding nongenetically modified isogenic variety. J Sci Food Agric 101:1869–1878. https://doi.org/10.1002/jsfa.10802
Luo J, Ning T, Sun Y et al (2009) Proteomic analysis of rice endosperm cells in response to expression of hGM-CSF. J Proteome Res 8:829–837. https://doi.org/10.1021/pr8002968
Mandaci M, Ćakir Ö, Turgut-Kara N et al (2015) Detection of genetically modified organisms in soy products sold in turkish market. Food Sci Technol 34:717–722. https://doi.org/10.1590/1678-457X.6441
Méchin V, Damerval C, Zivy M (2007) Total protein extraction with TCA-acetone. Methods Mol Biol 355:1–8. https://doi.org/10.1385/1-59745-227-0:1
Meriç S, Çakir Ö, Turgut-Kara N, Ari Ş (2014) Detection of genetically modified maize and soybean in feed samples. Genet Mol Res 13:1160–1168. https://doi.org/10.4238/2014.February.25.2
Mesnage R, Agapito-Tenfen SZ, Vilperte V et al (2016) An integrated multi-omics analysis of the NK603 Roundup-tolerant GM maize reveals metabolism disturbances caused by the transformation process. Sci Rep 6:37855. https://doi.org/10.1038/srep37855
Mudibu J, Nkongolo KKC, Kalonji-Mbuyi A, Kizungu RV (2012) Effect of gamma irradiation on morpho-agronomic characteristics of soybeans (Glycine max L.). Am J Plant Sci 3:331–337. https://doi.org/10.4236/ajps.2012.33039
Nobre DAC, Sediyama CS, Macedo WR et al (2019) Gamma radiation to produce soybean mutants for better plant performance and chemical composition of seeds. Emirates J Food Agric 31:511–520
OECD (1993) Safety evaluation of foods derived by modern biotechnology: concepts and principles. OECD Publishing, Paris
OECD (2006) An introduction to the food feed safety consensus documents of the task force Series on. OECD Environment, Health and Safety Publications, Paris
Oladosu Y, Rafii MY, Abdullah N et al (2016) Principle and application of plant mutagenesis in crop improvement: a review. Biotechnol Biotechnol Equip 30:1–16
Popovska M, Popovski B, Gjamovski V (2017) Primary effects of gamma radiation (cz137) on the morphology of leaves at some sweet cherry varieties. JAFES 71(2):148–154
Raina A, Laskar R, Khursheed S et al (2016) Role of mutation breeding in crop improvement- past, present and future. Asian Res J Agric 2(2):1–13
Ricroch AE, Bergé JB, Kuntz M (2011) Evaluation of genetically engineered crops using transcriptomic, proteomic, and metabolomic profiling techniques. Plant Physiol 155:1752–1761. https://doi.org/10.1104/pp.111.173609
Rigola D, van Oeveren J, Janssen A (2009) High-throughput detection of induced mutations and natural variation using keypoint technology. PLoS ONE 4(3):e4761. https://doi.org/10.1371/journal.pone.0004761
Ronald PC (2014) Lab to farm: applying research on plant genetics and genomics to crop ımprovement. PLoS Biol 12:e1001878. https://doi.org/10.1371/journal.pbio.1001878
Roychowdhury R, Tah J (2013) Mutagenesis-a potential approach for crop improvement. In: Hakeem K, Ahmad P, Ozturk M (eds) Crop improvement: new approaches and modern techniques, 1st edn. Springer, Boston, pp 149–187
Shevchenko A, Tomas H, Havli J et al (2006) In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nat Protoc 1:2856–2860. https://doi.org/10.1038/nprot.2006.468
Shu QY, Forster BP, Nakagawa H (2012) Principles and applications of plant mutation breeding. CABI, Wallingford
SoyStats (2019) 2019 Soy highlights |. http://soystats.com/2019-highlights/. Accessed 3 Jun 2021
Takagi H, Tamiru M, Abe A et al (2015) MutMap accelerates breeding of a salt-tolerant rice cultivar. Nat Biotechnol 33(5):445–449. https://doi.org/10.1038/nbt.3188
Tan Y, Tong Z, Yang Q et al (2017) Proteomic analysis of phytase transgenic and non-transgenic maize seeds. Sci Rep 7:1–11. https://doi.org/10.1038/s41598-017-09557-8
Tsuda M, Kaga A, Anai T et al (2015) Construction of a high-density mutant library in soybean and development of a mutant retrieval method using amplicon sequencing. BMC Genom 16:1014. https://doi.org/10.1186/s12864-015-2079-y
Vidal N, Barbosa H, Jacob S, Arruda M (2015) Comparative study of transgenic and non-transgenic maize (Zea mays) flours commercialized in Brazil, focussing on proteomic analyses. Food Chem 180:288–294. https://doi.org/10.1016/j.foodchem.2015.02.051
Wang L, Wang X, Jin X et al (2015) Comparative proteomics of Bt-transgenic and non-transgenic cotton leaves. Proteome Sci 13:15. https://doi.org/10.1186/s12953-015-0071-8
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 7:1850–1861. https://doi.org/10.1021/pr0705082
Acknowledgements
We thank the Depertmant of Molecular Biology and Genetics, Istanbul Kültür University for providing mutant seeds. We also thank DEKART Proteomics laboratory at Kocaeli University Medical School (http://laboratuar.kocaeli.edu.tr/dekart/) for MALDI-TOF/TOF MS analysis.
Funding
This work was supported by the Scientific Research Projects Coordination Unit (BAP) of Istanbul University, [Project No 25627].
Author information
Authors and Affiliations
Contributions
Methodology: [SM, ÇA, ŞA], Investigation: [SM, AA], Visualization: [SM, ŞA], Software: [SM], Writing: [SM, AA, ÇA, ŞA], Supervision: [ŞA], Validation: [SM, ŞA].
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no known competing financial or non-financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Meriç, S., Ayan, A., Atak, Ç. et al. Profile-based proteomic investigation of unintended effects on transgenic and gamma radiation induced mutant soybean plants. Genet Resour Crop Evol 70, 2077–2095 (2023). https://doi.org/10.1007/s10722-023-01560-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10722-023-01560-5