Browse > Article
http://dx.doi.org/10.3839/jabc.2022.056

Comparative untargeted metabolomic analysis of Korean soybean four varieties (Glycine max (L.) Merr.) based on liquid chromatography mass spectrometry  

Eun-Ha Kim (Biosafety Division, National Institute of Agricultural Sciences)
Soo-Yun Park (Biosafety Division, National Institute of Agricultural Sciences)
Sang-Gu Lee (Biosafety Division, National Institute of Agricultural Sciences)
Hyoun-Min Park (Biosafety Division, National Institute of Agricultural Sciences)
Oh Suk Yu (Biosafety Division, National Institute of Agricultural Sciences)
Yun-Young Kang (Biosafety Division, National Institute of Agricultural Sciences)
Myeong Ji Kim (Biosafety Division, National Institute of Agricultural Sciences)
Jung-Won Jung (Biosafety Division, National Institute of Agricultural Sciences)
Seon-Woo Oh (Biosafety Division, National Institute of Agricultural Sciences)
Publication Information
Journal of Applied Biological Chemistry / v.65, no.4, 2022 , pp. 439-446 More about this Journal
Abstract
Soybean is a crop with high-quality of protein and oil, and it is one of the most widely used genetically modified (GM) crops in the world today. In South Korea, Kwangan is the most utilized variety as a parental line for GM soybean development. In this study, untargeted LC-MS metabolomic approaches were used to compare metabolite profiles of Kwangan and three other commercial varieties cultivated in Gunwi and Jeonju in 2020 year. Metabolomic studies revealed that the 4 soybean varieties were distinct based on the partial least squares-discriminant analysis (PLS-DA) score plots; 18 metabolites contributed to variety distinction, including phenylalanine, isoflavones, and fatty acids. All varieties were clearly differentiated by location on the PLS-DA score plot, indicating that the growing environment is also attributable to metabolite variability. In particular, isoflavones and linolenic acid levels in Kwangan were significantly lower and higher, respectively compared to those of the three varieties. It was discussed that it might need to include more diverse conventional varieties as comparators in regard to metabolic characteristics of Kwangan for the assessment of substantial equivalence biogenetically engineered soybeans in a Kwangan-variety background.
Keywords
Environment; LC-MS; Metabolite profiles; Soybean; Variety;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
연도 인용수 순위
1 ISAAA (2021) Pocket K No. 16: Biotech Crop Highlight in 2019. International Service for the Acquisition of Agri-biotech Applications. Updated May 2021 http://www.isaaa.org/kc 
2 Lee KJ, Park HJ, Yi BY, Lee KR, Kim MS, Woo HJ, Jin YM, Kwon SJ (2008) Development of herbicide tolerant soybean using Agrobacterium thumfaciens. J Plant Biotechnol 35: 69-74. doi: 10.5010/JPB.2008.35.1.069    DOI
3 Jeon EH, Chung Y-S (2009) Development of genetic transformation method of Korean soybean. J Plant Biotechnol 36: 344-351. doi: 10.5010/JPB.2009.36.4.344    DOI
4 Kim DG, Kantayos V, Kim DK, Park HG, Kim HH, Rha ES, Lee SC, Bae CH (2016) Plant regeneration by in vitro tissue culture in Korean soybean (Glycine max L.). Koren J Plant Res 29: 143-153. doi: 10.7732/kjpr.2016.29.1.143    DOI
5 Cho C, Kim D-Y, Choi M-S, Jin M, Seo M-S (2021) Efficient isolation and gene transfer of protoplast in Korean soybean (Glycine Max (L.) Merr.) cultivars. Korean J Breed Sci 53: 230-239. doi: 10.9787/KJBS.2021.53.3.230    DOI
6 Oh S-W, Kim E-H, Lee S-Y, Baek D-Y, Lee S-G. Kang H-J. Chung Y-S. Park S-K, Ryu T-H (2021) Compositional equivalence assessment of insect-resistant genetically modified rice using multiple statistical analyses. GM Crops & Food 12: 303-314. doi: 10.1080/21645698.2021.1893624    DOI
7 Christ B. Pluskai T, Aubry S, Weng JK (2018) Contribution of untargedted metabolomics for future assessment of biotech crops. Trends Plant Sci 24: 1047-1056. doi: 10.1016/j.tplants.2018.09.011    DOI
8 Fraser PD, Aharoni A, Hall RD, Huang S, Giovannoni JJ, Sonnewald U, Fernie AR (2020) Metabolomics should be deployed in the identification and characterization of gene-edited crips. Plant J 102: 897-902. doi: 10.1111/tpj.14679    DOI
9 Zhou J, Ma C, Xu H, Yuan K, Lu X, Zhu Z, Wu Y, Xu G (2009) Metabolic profiling of transgenic rice with cry1Ac and sck genes: an evaluation of unintended effects at metabolic level by using GC-FID and GC-MS. J Chromatogr B 877: 725-732. doi: 10.1016/j.jchromb.2009.01.040    DOI
10 Clarke JD, Alexander DC, Ward DP, Ryals JA, Mitchell MW, Wulff JE, Guo L (2013) Assessment of genetically modified soybean in relation to natural variation in the soybean seed metabolome. Scientific Rep 3: 6 
11 Wang XJ, Zhang X, Yang JT, Wang ZX (2018) Effect on transcriptome and metabolome of stacked transgenic maize containing insecticidal cry and glyphosate tolerance epsps genes. Plant J 93: 1007-1016. doi: 10.1111/tpj.13825    DOI
12 John KMM, Natarajan S, Luthria DL (2016) Metabolite changes in nine different soybean varieties grown under field and greenhouse conditions. Food Chem 211: 347-355. doi: 10.1016/j.foodchem.2016.05.055    DOI
13 Lee SJ, Yan W, Ahn JK, Chung IM (2003) Effects of year, site, genotype, and their interactions on various soybean isoflavones. Field Crops Res 81: 181-192. doi: 10.1016/S0378-4290(02)00220-4    DOI
14 Kim HJ, Cho HS, Pak JH, Kwon T, Lee J-H, Kim D-H, Lee DH, Kim C-G, Chung Y-S(2018) Confirmation of drought tolerance of ectopically expressed AtABF3 gene in soybean. Mol Cells 4: 413-422. doi: 10.14348/molcells.2018.2254    DOI
15 Seo M-S, Cho C, Jeong N, Sung S-K, Choi M-S, Jin M, Kim D-Y (2021) In vitro tissue culture frequency and transformation of various cultivars of soybean (Glycine max (L.) Merr.). Korean J Plant Res 34: 278-286. doi: 10.7732/kjpr.2021.34.4.278    DOI
16 Yeom WW, Kim HY, Lee K-R, Cho HS, Kim J-Y, Jung HW, Oh S-W, Jun SE, Kim HU, Chung Y-S (2020) Increased production of α-linolenic acid in soybean seeds by overexpressing of Lesquerella FAD3-1. Front Plant Sci 10: 1812. doi: 10.3389/fpls.2019.01812    DOI
17 Kim M-J, Kim JK, Kim HJ, Pak JH, Lee J-H, Kim D-H, Lee D-H, Choi HK, Ho WJ, Lee J-D, Chung Y-S, Ha S-H (2012) Genetic modification of the soybean to enhance the β-carotene content through seed-specific expression. Plos ONE 7: e48287. doi: 10.1371/journal.pone.0048287    DOI
18 Cho HS. Lee DH, Jung HW, Oh S-W. Kim HJ, Chung Y-S (2019) Evaluation of yield components from transgenic soybean overexpressing chromatin architecture-controlling ATPG8 and ATPG10 genes. Plant Breed Biotech 7: 34-41. doi: 10.9787/PBB.2019.7.1.34    DOI
19 Song JH, Shin GS, Kim HJ, Lee SB, Moon JY, Jeong JC, Choi H-K, Kim IA, Song HJ, Kim CY, Chung Y-S (2022) Mutation of GmIPK1 gene using CRISPR/Cas9 reduced phytic acid content in soybean seeds. Int J Mol Sci 23: 10583. doi: 10.3390/ijms231810583    DOI
20 OECD (1993) Safety evaluation of foods derived by modern biotechnology; Concepts and Principles. Organization of Economic Cooperation and Development (OECD), Paris, France 
21 Codex Alimentarius (2003) Guideline for the donduct of food safety assessment of foods derived from recombinant-DNA plants. CAC/GL45-2003, Geveva 
22 Kim HM, Jang EK, Gwak BS. Hwang TY, Yun GS, Hwang SG, Jeong HS, Kim HS (2018) Variation of isoflavone contents and classification using multivariate analysis in Korean soybean varieties released from 1913 to 2013. Korean J Breed Sci 50: 50-60. doi: 10.9787/KJBS.2018.50.1.50    DOI
23 Kim YJ, Park YJ, Oh S-D, Yoon JS, Kim JG, Seo J-S, Park J-H, Kim C-G, ParkS-Y, ParkS-K, Choi M-S, Kim JK (2022) Effects of genotype and environment on the nutrient and metabolic profiles of soybeans genetically modified with epidermal growth factor or thioredoxin compared with conventional soybeans. Ind Crops Prod 175: 114229. doi: 10.1016/j.indcrop.2021.114229    DOI
24 Gu S, Son Y, Park JY, Choi S-G, Lee M, Kim H-J (2019) Analysis of the seed metabolite profiles and antioxidant activity of perilla variation. Korean J Food Sci and Technol 51: 193-199. doi: 10.9721/KJFST.2019.51.3.193    DOI
25 Kudou S, Flenry Y, Welti D, Magnolato D, Uchida T, Kitamura K, Okubo K (1991) Malonyl isoflavone glycosides in soybean seeds (Glycine max Merrill). Agric Biol Chem 55: 2227-2233. doi: 10.1080/00021369.1991.10870966    DOI
26 Yoon H, Yi J, Desta K, Shin M-J, Lee Y, Lee S. Wang X, Choi Y-M, Lee S (2021) Yearly variation of isoflavone composition and yield-related traits of 35 Korean soybean germplasm. Korean J Breed Sci 53: 411-423. doi: 10.9787/KJBS.2021.53.4.411    DOI
27 Hemingway J, Eskandari M, Rajcan I (2015) Genetic and environmental effects on fatty acid composition in soybeans with potential use in the automotive industry. Crop Sci 55: 658-668. doi: 10.2135/cropsci2014.06.0425    DOI
28 Yoshiki Y, Kudou S, Okubo K (1998) Relationship between chemical structures and biological activities of triterpenoid saponins from soybean. Biosci Biotechnol Biochem 62: 2291-2299. doi: 10.1271/bbb.62.2291    DOI
29 Nam J-H, Jeong J-C, Yoon Y-H, Hong S-Y, Kim S-J, Jin Y-I, Jee S-N, Kim H-S, Ok H-C, Nho C-W, Pan C-H (2012) Comparison of soyasaponin group B contents in soybean seed by different cultivars and regional background. Korean J Plant Res 25: 394-400. doi: 10.7732/kjpr.2012.25.4.394    DOI
30 Berhow MA, Kong SB, Vermillion KE, Duval SM (2006) Complete quantification of group A and group B soyasaponins in soybeans. J Agric Food Chem 54: 2035-2044. doi: 10.1021/jf053072o    DOI
31 Seguin P, Chennupati P, Tremblay G, Liu W (2014) Crop management, genotypes, and environmental factors affect soyasaponin B concentration in soybean. J Agric Food Chem 62: 7160-7165. doi: 10.1021/jf500966t    DOI
32 Hong S-Y, Kim S-J, Sohn H-B, Kim Y-H, Cho K-S (2018) Comparison of isoflavone content in 43 soybean varieties adapted to highland cultivation areas. Korean J Breed Sci 50: 442-452. doi: 10.9787/KJBS.2018.50.4.442    DOI
33 Tsukamoto C, Shimada S, Igita K, Kudou S, Kokubun M, Okubo K, Kitamura K (1995) Factors affecting isoflavones content in soybean seeds: changes in isoflavones, saponins, and composition of fatty acids at different temperatures during seed development. J Agric Food Chem 43: 1184-1192. doi: 10.1021/jf00053a012    DOI
34 Lozovaya VV, Lygin AV, Ulanov AV, Nelson RL, Dayde J, Widholm JM (2005) Effect of temperature and soil moisture status during seed development on soybean seed isoflavone concentration and composition. Crop Sci 45: 1934-1940. doi: 10.2135/cropsci2004.0567    DOI
35 OECD (2012) Revised Consensus Document on Compositional Considerations for New Varieties of Soybean [Glycine max (L.) Merr]: Key Food and Feed Nutrients, Anti-nutrients, Toxicants and Allergens. Series on Harmonization of Regulatory Oversight in Biotechnology No. 25, OECD Publishing, Paris