Metabolic profiling and identification of the genetic varieties and agricultural origin of Cnidium officinale and Ligusticum chuanxiong

Journal of Bioscience and Bioengineering

Volumn 114, Issue 1, 2012, Pages 86-91

  Kobayashi, Shizu ^a   Nagasawa, Saki ^a   Yamamoto, Yutaka ^b   Donghyo, Kang ^b   Bamba, Takeshi ^b   Fukusaki, Eiichiro ^a  

^a OSAKA UNIVERSITY   (Japan)

^b Tochimoto Tenkaido CoLtd   (Japan)

Author keywords

Cnidium officinale; Gas chromatography mass spectrometry (GC MS); Ligusticum chuanxiong; Metabolite profiling; Metabolomics

Indexed keywords

CNIDIUM OFFICINALE; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; LIGUSTICUM CHUANXIONG; METABOLITE PROFILING; METABOLOMICS;

DISCRIMINANT ANALYSIS; GAS CHROMATOGRAPHY; METABOLITES; QUALITY CONTROL;

CULTIVATION;

ARTICLE; CLASSIFICATION; CNIDIUM; CNIDIUM OFFICINALE; DISCRIMINANT ANALYSIS; GENETIC VARIABILITY; LIGUSTICUM CHUANXIONG; MASS FRAGMENTOGRAPHY; METABOLOMICS; PLANT GENETICS;

CNIDIUM; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; GENETIC VARIATION; LIGUSTICUM; METABOLOME;

CNIDIUM OFFICINALE; LIGUSTICUM CHUANXIONG;

EID: 84862761107     PISSN: 13891723     EISSN: 13474421     Source Type: Journal    
DOI: 10.1016/j.jbiosc.2012.02.015     Document Type: Article

References (26)

1. Society of Japanese Pharmacopoeia: The Japanese pharmacopoeia XVI official monographs, p. 1531. The Minister of Health, Labour and Welfare, Tokyo (2011) (in Japanese).
2. Aoyagi M., Anetai M., Shibata T., Hatakeyama Y. Preparation and chemical evaluation of Cnidii Rhizoma (Part III) effect of blanching conditions on contents of ferulic acid and adenosine. Rep. Hokkaido Inst. Public Health 2002, 52:81-82. (in Japanese).
3. Chervenak M. China: moving towards innovation in pharma. Drug Discov. Today 2005, 10:1127-1130.
4. World Health Organization WHO guidelines on good agricultural and collection practices (GACP) for medicinal plants, p.1 2003, WHO, Geneva.
5. Zhu S., Fushimi H., Han G., Tsuchida T., Uno T., Takano A., Komatsu K. Molecular identification of "Chuanxiong" by nucleotide sequence and multiplex single base extension analysis on chloroplast trnK gene. Biol. Pharm. Bull. 2007, 30:527-531.
6. Yip P.Y., Chau C.H., Mak C.Y., Kwan H.S. DNA methods for identification of Chinese medicinal materials. Chin. Med. 2007, 2:9.
7. Sanchez J.J., Endicott P. Developing multiplexed SNP assays with special reference to degraded DNA templates. Nat. Protoc. 2006, 1:1370-1378.
8. Yi T., Leung K.S., Lu G.H., Zhang H. Comparative analysis of Ligusticum chuanxiong and related umbelliferous medicinal plants by high performance liquid chromatography-electrospray ionization mass spectrometry. Planta Med. 2007, 73:392-398.
9. Lu G.H., Chan K., Liang Y.Z., Leung K., Chan C.L., Jiang Z.H., Zhao Z.Z. Development of high-performance liquid chromatographic fingerprints for distinguishing Chinese Angelica from related umbelliferae herbs. J. Chromatogr. A 2005, 1073:383-392.
10. Jeong J.B., Ju S.Y., Park J.H., Lee J.R., Yun K.W., Kwon S.T., Lim J.H., Chung G.Y., Jeong H.J. Antioxidant activity in essential oils of Cnidium officinale makino and Ligusticum chuanxiong Hort and their inhibitory effects on DNA damage and apoptosis induced by ultraviolet B in mammalian cell. Cancer Epidemiol. 2009, 33:41-46.
11. Weckwerth W., Morgenthal K. Metabolomics: from pattern recognition to biological interpretation. Drug Discov. Today 2005, 10:1551-1558.
12. Wiklund S., Johansson E., Sjostrom L., Mellerowicz E.J., Edlund U., Shockcor J.P., Gottfies J., Moritz T., Trygg J. Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem. 2008, 80:115-122.
13. Shirai, K.: Standard dictionary of Chinese medicine, vol. 3, p. 1495. Shogakukan, Tokyo (1998) (in Japanese).
14. Lommen A. MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing. Anal. Chem. 2009, 81:3079-3086.
15. Katajamaa M., Miettinen J., Oresic M. MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics 2006, 22:634-636.
16. Styczynski M.P., Moxley J.F., Tong L.V., Walther J.L., Jensen K.L., Stephanopoulos G.N. Systematic identification of conserved metabolites in GC/MS data for metabolomics and biomarker discovery. Anal. Chem. 2007, 79:966-973.
17. Tugawa H., Tsujimoto Y., Arita M., Bamba T., Fukusaki E. GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA). BMC Bioinformatics 2011, 12:131.
18. Rantalainen M., Cloarec O., Ebbels T.M., Lundstet T., Nicholson J.K., Holmes E., Trygg J. Piecewise multivariate modelling of sequential metabolic profiling data. BMC Bioinformatics 2008, 9:105.
19. Ran X., Ma L., Peng C., Zhang H., Qin L.P. Ligusticum chuanxiong Hort: a review of chemistry and pharmacology. Pharm. Biol. 2011, 49:1180-1189.
20. Eriksson L., Johansson E., Kettaneh-Wold N., Wold S. Muti- and megavariate data analysis. Principles and applications, p. 107 2001, 107. Umetrics AB, Umea, Sweden.
21. Sieber M., Hoffmann D., Adler M., Vaidya V.S., Clement M., Bonventre J.V., Zidek N., Rached E., Amberg A., Callanan J.J., Dekant W., Mally A. Comparative analysis of novel noninvasive renal biomarkers and metabonomic changes in a rat model of gentamicin nephrotoxicity. Toxicol. Sci. 2009, 109:336-349.
22. Llorach R., Garrido I., Urpi-Sarda M., Tulipani S., Andres-Lacueva C. Metabolomics study of human urinary metabolome modifications after intake of almond (Prunus dulcis (Mill.) D. A. Webb) skin polyphenols research articles. J. Proteome Res. 2010, 9:5859-5867.
23. Tianniam S., Tarachiwin L., Bamba T., Kobayashi A., Fukusaki E. 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. J. Biosci. Bioeng. 2008, 105:655-659.
24. 1H NMR-based metabolic fingerprinting. J. Pharm. Biomed. Anal. 2008, 48:42-48.
25. Dai H., Xiao C., Liu H., Hao F., Tang H. Combined NMR and LC-DAD-MS analysis reveals comprehensive metabonomic variations for three phenotypic cultivars of Salvia Miltiorrhiza Bunge. J. Proteome Res. 2010, 9:1565-1578.
26. 1H NMR and UPLC-MS analyses. J. Agric. Food Chem. 2011, 59:8806-8815.