GC-MS 기반 대사체학 기술을 응용한 참당귀의 산지비교분석
Comparative Analysis of Cultivation Region of Angelica gigas Using a GC-MS-Based Metabolomics Approach
2
조회
0
다운로드
5
인용
0
참고문헌
키워드
초록
Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, α-pinene, and β-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.
Abstract
Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, α-pinene, and β-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.
참고문헌 (23)
- Arbona V, "Plant phenotype demarcation using nontargeted LC-MS and GC-MS metabolite profiling", Journal of Agricultural and Food Chemistry, 57, pp.7338~7347 (2009)
- Bylesjo M, "OPLS discriminant analysis : Combining the strengths of PLS-DA and SIMCA classification", Journal of Chemometrics, 20, pp.341~351 (2006)
- Claudino WM, "Metabolomics in cancer : A bench-to-bedside intersection", Critical Reviews in Oncology, 2012, pp.84, 1~7
- Clevenger JF, "Apparatus for the determination of volatile oil", Journal of American Pharmaceutical Association, 17, pp.345~349 (1928)
- De Vos RCH, "Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry", Nature Protocols, 2, pp.778~791 (2007)
- "European pharmacopoeia technical guide for the elaboration of minographs" (2015)[URL]
- Fiehn O., "Metabolomics : The link between genotypes and phenotypes", Plant Molecular Biology, 48, pp.155~171 (2002)
- Fukusaki E, "Plant metabolomics : Potential for practical operation", Journal of Bioscience and Bioengineering, 100, pp.347~354 (2005)
- 홍영식, "영양 대사체학", 한국식품영양과학회지, 43(2), pp.179~186 (2014), 한국식품영양과학회
- Kanani H, "Standardizing GC-MS metabolomics", Journal of Chromatography B, 871, pp.191~201 (2008)
- Kende A, "Target list building for volatile metabolite profiling of fruit", Journal of Chromatography A, 1217, pp.6718~6723 (2010)
- Kim EJ, "Metabolite profiling of Angelica gigas from different geographical origins using 1H NMR and UPLC-MS analyses", Journal of Agricultural and Food Chemistry, 59, pp.8806~8815 (2011)
- Kim MR, "Determination of volatile flavor components in danggui cultivars by solvent free injection and hydrodistillation followed by gas chromatographic-mass spectrometric analysis", Journal of Chromatography A, 1116, pp.259~264 (2006)
- Lee DK, "Comparison of primary and secondary metabolites for suitability to discriminate the origins of Schisandra chinensis by GC", MS and LC, Food Chemistry, pp.2013, 141[DOI]
- 이혜원, "자생종과 재배종 고본의 성분함량 비교", 한국약용작물학회지, 16(3), pp.168~172 (2008), 한국약용작물학회
- Lindon JC, "Metabolomics in pharmaceutical R&D", Federation of European Biochemical Societies Journal, 274, pp.1140~1151 (2007)
- "NIST08 mass spectral library(NIST08/2008)" (2008)[URL]
- Özek G, "Gas chromatographic-mass spectrometric analysis of volatiles obtained by four different techniques from Salvia rosifolia Sm. and evaluation for biological activity", Journal of Chromatography A, 1217, pp.741~748 (2010)
- Tianniam S, "Metabolic profiling of Angelica acutiloba roots utilizing gas chromatography-time-of-flight-mass spectrometry for quality assessment based on cultivation area and cultivar via multivariate pattern recognition", Journal of Bioscience and Bioengineering, 105, pp.655~659 (2008)
- Westerhuis JA, "Multivariate paired data analysis : Multilevel PLSDA versus OPLSDA", Metabolomics, 6, pp.119~128 (2010)
- Wiklund S, "Visualization of GC", TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models, 2008, pp.80, 115~122
- 양승옥, "Comparative Analysis of Metabolites in Roots of Panax ginseng Obtained from Different Sowing Methods", 한국약용작물학회지, 22(1), pp.17~22 (2014), 한국약용작물학회[DOI]
- Zhang A, "Metabolomics: Towards understanding traditional Chinese medicine", Planta Medica, 76, pp.2026~2035 (2010)