Standardizing GC-MS metabolomics

被引：181

作者：

Kanani, Harin ^{[2
]}

Chrysanthopoulos, Panagiotis K. ^{[1
,3
]}

Klapa, Maria I. ^{[1
,2
]}

机构：

[1] Fdn Res & Technol Hellas, Inst Chem Engn & High Temp Chem Proc, Metab Engn & Syst Biol Lab, GR-26504 Patras, Greece

[2] Univ Maryland, Dept Chem & Biomol Engn, Metab Engn & Syst Biol Lab, College Pk, MD 20742 USA

[3] Univ Patras, Dept Biol, Div Genet & Cell & Dev Biol, GR-26500 Patras, Greece

来源：

JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES | 2008年 / 871卷 / 02期

关键词：

quantitative systems biology; high-throughput "omic" techniques; data correction and normalization; data validation; derivatization biases; TMS-derivatives; methoximation; metabolite extraction;

D O I：

10.1016/j.jchromb.2008.04.049

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Metabolomics being the most recently introduced "omic" analytical platform is currently at its development phase. For the metabolomics to be broadly deployed to biological and clinical research and practice, issues regarding data validation and reproducibility need to be resolved. Gas chromatography-mass spectrometry (GC-MS) will remain integral part of the metabolomics laboratory. In this paper, the sources of biases in GC-MS metabolomics are discussed and experimental evidence for their Occurrence and impact on the final results is provided. When available, methods to correct or account for these biases are presented towards the standardization of a systematic methodology for quantitative GC-MS metabolomics. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：191 / 201

页数：11

共 60 条

[1] Recent methodology in the phytochemical analysis of ginseng [J].

Angelova, Nadezhda ;

Kong, Hong-Wei ;

Van Der Heijden, Rob ;

Yang, Shih-Ying ;

Choi, Young Hae ;

Kim, Hye Kyong ;

Wang, Mei ;

Hankemeier, Thomas ;

Van Der Greef, Jan ;

Xu, Guowang ;

Verpoorte, Rob .

PHYTOCHEMICAL ANALYSIS, 2008, 19 (01) :2-16

[2] Metabolome analysis:: the potential of in vivo labeling with stable isotopes for metabolite profiling [J].

Birkemeyer, C ;

Luedemann, A ;

Wagner, C ;

Erban, A ;

Kopka, J .

TRENDS IN BIOTECHNOLOGY, 2005, 23 (01) :28-33

[3] Predicting interactions from mechanistic information: Can omic data validate theories? [J].

Borgert, Christopher J. .

TOXICOLOGY AND APPLIED PHARMACOLOGY, 2007, 223 (02) :114-120

[4] Growth stage-based phenotypic analysis of arabidopsis:: A model for high throughput functional genomics in plants [J].

Boyes, DC ;

Zayed, AM ;

Ascenzi, R ;

McCaskill, AJ ;

Hoffman, NE ;

Davis, KR ;

Görlach, J .

PLANT CELL, 2001, 13 (07) :1499-1510

[5] Metabolomics: quantification of intracellular metabolite dynamics [J].

Buchholz, A ;

Hurlebaus, J ;

Wandrey, C ;

Takors, R .

BIOMOLECULAR ENGINEERING, 2002, 19 (01) :5-15

[6] Engineering central metabolism in crop species: learning the system [J].

Carrari, F ;

Urbanczyk-Wochniak, E ;

Willmitzer, L ;

Fernie, AR .

METABOLIC ENGINEERING, 2003, 5 (03) :191-200

[7] Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops [J].

Catchpole, GS ;

Beckmann, M ;

Enot, DP ;

Mondhe, M ;

Zywicki, B ;

Taylor, J ;

Hardy, N ;

Smith, A ;

King, RD ;

Kell, DB ;

Fiehn, O ;

Draper, J .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2005, 102 (40) :14458-14462

[8] Metabolomics: Available results, current research projects in breast cancer, and future applications [J].

Claudino, Wederson Marcos ;

Quattrone, Alessandro ;

Biganzoli, Laura ;

Pestrin, Marta ;

Bertini, Ivano ;

Di Leo, Angelo .

JOURNAL OF CLINICAL ONCOLOGY, 2007, 25 (19) :2840-2846

[9]

Colon L. A., 2004, MODERN PRACTICE GAS, P277, DOI DOI 10.1002/0471651141

[10]

DILEO A, 2007, ANN ONCOL S, P12

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