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- Metabolic profiles of genetically modified potatoes using a combination of metabolite fingerprinting and multivariate analysis
- Hyun Soon Kim; Suk Weon Kim; Y S Park; Suk Yoon Kwon; Jang Ryol Liu; Hyouk Joung; Jae Heung Jeon
- Bibliographic Citation
- Biotechnology and Bioprocess Engineering, vol. 14, no. 6, pp. 738-747
- Publication Year
- Comprehensive metabolite fingerprinting of transgenic potatoes that constitutively express human beta amyloid, curdlan synthase (CRDS), and glycogen synthase (glgA); and of wild-type potatoes was carried out using FT-IR and 1H NMR spectroscopy in combination with multivariate analyses. Comparison of metabolic patterns between transgenic and wild-type potatoes revealed that there were neither quantitative nor qualitative differences in metabolites between transgenic potatoes expressing human beta amyloid, CRDS or glgA, and non-transformed control potatoes. However, there were metabolic differences between two control potato lines - one that was fresh and the other stored. After 1 week of storage, comprehensive metabolite patterns were significantly modified. Although the differences between CRDS and glgA transgenic and control potato lines were small, PCA analysis of FT-IR and 1H NMR spectral data identified two distinct control lines. These results suggest that the comprehensive metabolite changes in control potato lines, which occurred after 1 week of storage, were greater than the differences between CRDS and glgA transgenic and wild-type potato lines. Thus, the combination of FT-IR and 1H NMR spectral data and multivariate analysis was valuable for the detection of comprehensive differences in metabolic profiles between transgenic and non-transformed control plants, even though peak-signal overlap prevented assignment of pure compounds. The combination of FT-IR and 1H NMR spectral data and multivariate analysis is a simple and rapid method for evaluation of the metabolic equivalence of GM crops.
- 1H NMR spectroscopy; FT-IR spectroscopy; Genetically modified potatoes; Multivariate analysis; Principal component analysis (PCA)
- South Korea
- Appears in Collections:
- Division of Biomaterials Research > Plant Systems Engineering Research > 1. Journal Articles
Jeonbuk Branch Institute > Biological Resource Center > 1. Journal Articles
Division of Biomaterials Research > 1. Journal Articles
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