Skip to main content
SpringerLink
Log in

Metabolomics — the link between genotypes and phenotypes

  • Chapter
Functional Genomics

Abstract

Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms ‘transcriptome’ and ‘proteome’, the set of metabolites synthesized by a biological system constitute its ‘metabolome’. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Adams, R.F. 1974. Determination of amino acid profiles in biological samples by gas chromatography. J. Chromatogr. 95: 189–212.

    PubMed  CAS  Google Scholar 

  • Adams, M.A., Chen, Z.L., Landman, P. and Colmer, D. 1999. Simultaneous determination by capillary gas chromatography of organic acids, sugars, and sugar alcohols in plant tissue extracts as their trimethylsilyl derivatives. Anal. Biochem. 266: 77–84.

    PubMed  CAS  Google Scholar 

  • Albert, R., Jeong, H. and Barabási, A.-L. 2000. Error and attack tolerance of complex networks. Nature 406: 378–381.

    PubMed  CAS  Google Scholar 

  • Arabidopsis Genome Initiative. 2000. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408: 796–815.

    Google Scholar 

  • Arkin, A., Shen, P. and Ross, J. 1997. A test case of correlation metric construction of a reaction pathway from measurements. Science 277: 1275–1279.

    CAS  Google Scholar 

  • ap Rees, T. and Hill, S.A. 1994. Metabolic control analysis of plant metabolism. Plant Cell Envir. 17: 587–599.

    CAS  Google Scholar 

  • Beaudry, F., Le Blanc, J.C.Y., Coutu, M., Ramier, I., Moreau, J.P. and Brown N.K. 1999. Metabolite profiling study of propranolol in rat using LC/MS/MS analysis. Biomed. Chromatogr. 13: 363–369.

    PubMed  CAS  Google Scholar 

  • Becker, M.Y. and Rojas, I. 2001. A graph layout algorithm for drawing metabolic pathways. Bioinformatics 17: 461–467.

    PubMed  CAS  Google Scholar 

  • Benthin, B., Danz, H. and Hamburger, M. 1999. Pressurized liquid extraction of medicinal plants. J. Chromatogr. A 837: 211–219.

    PubMed  CAS  Google Scholar 

  • Bersini, H. and Calenbuhr, V. 1997. Frustrated chaos in biological networks. J. Theor. Biol. 188: 187–200.

    PubMed  CAS  Google Scholar 

  • Beuerle, T. and Schwab, W. 1999. Metabolic profile of linoleic acid stored in apples: formation of 13(R)-hydroxy-9(Z), 11(E)-octadecadienoic acid. Lipids 34: 375–380.

    PubMed  CAS  Google Scholar 

  • Bittner, M., Meltzer, P. and Trent, J. 1999. Data analysis and integration: of steps and arrows. Nature Genet. 22: 213–215.

    PubMed  CAS  Google Scholar 

  • Blanch, G.P., Caja, M.M., del Castillo, M.L.R., Santa-Maria, G. and Herraiz, M. 1999. Fractionation of plant extracts by supercritical fluid extraction and direct introduction in capillary gas chromatography using a programmable temperature vaporizer. J. Chromatogr. Sci. 37: 407–410.

    CAS  Google Scholar 

  • Bouchereau, A., Guénot, P. and Larher, F. 2000. Analysis of amines in plant materials. J. Chromatogr. B 747: 49–67.

    CAS  Google Scholar 

  • Brazma, A. and Vilo, J. 2000. Gene expression data analysis. FEBS Lett. 480: 17–24.

    PubMed  CAS  Google Scholar 

  • Bücher, T. and Rüssmann, W. 1963. Gleichgewicht und Ungleichgewicht im System der Glykolyse. Angew. Chem. 75: 881–948.

    Google Scholar 

  • Butte, A.J. and Kohane, I.S. 2000. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. Pac. Symp. Biocomput. 5: 427–439.

    Google Scholar 

  • Castioni, P., Christen, P. and Veuthey J.L. 1995. Supercritical fluid extraction of compounds from plant origin. Analusis 23: 95–106.

    CAS  Google Scholar 

  • Christensen, B. and Nielsen, J. 1999. Metabolic network analysis: a powerful tool in metabolic engineering. In: T. Scheper (Ed.) Advances in Biochemical Engineering and Biotechnology, Springer-Verlag, Berlin, pp. 210–231.

    Google Scholar 

  • Christensen, B. and Nielsen, J. 2000. Metabolic network analysis of Penicillium chysogenum using 13C-labelled glucose. Biotechnol. Bioeng. 68: 652–659.

    PubMed  CAS  Google Scholar 

  • Cornish-Bowden, A. and Cárdenas, M.L. 2000. From genome to cellular phenotype: a role for metabolic flux analysis? Nature Biotechnol. 18: 267–268.

    CAS  Google Scholar 

  • Cornish-Bowden, A. and Eisenthal, R. 2000. Computer simulations as a tool for studying metabolism and drug design. In: A.J. Cornish-Bowden and M.L. Cárdenas (Eds.) Technological and Medical Implications of Metabolic Control Analysis, Kluwer Academic Publishers, Dordrecht, Netherlands, pp. 165–172.

    Google Scholar 

  • Cornish-Bowden, A. and Hofmeyr, J.-H.S. 1994. Determination of control coefficients in intact metabolic systems. Biochem. J. 298: 367–375.

    PubMed  CAS  Google Scholar 

  • Dauner, M. and Sauer, U. 2000. GC-MS analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Progr. 16: 642–649.

    CAS  Google Scholar 

  • de Jongh, D.C., Radford, T., Hribar, J.D., Hanessian, S., Bieber, M., Dawson, G. and Sweeley, C.C. 1969. Analysis of trimethylsilyl derivatives of carbohydrates by gas chromatography and mass spectrometry. J. Am. Chem. Soc. 91: 1728–1740.

    Google Scholar 

  • Dieuaide-Noubhani, M., Raffard, G., Canioni, P., Pradett, A. and Raymond, P. 1995. Quantification of compartmented metabolic fluxes in maize root tips using isotope distribution from C-or 14C-labeled glucose. J. Biol. Chem. 22: 13147–13159.

    Google Scholar 

  • Edwards, J.S. and Palsson, B.O. 2000. The Escherichia coli MG 1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc. Natl. Acad. Sci. USA 97: 5528–5533.

    PubMed  CAS  Google Scholar 

  • Edwards, J.S., Ibarra, R.U. and Palsson, B.O. 2001. In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nature Biotechnol. 19: 125–130.

    CAS  Google Scholar 

  • Eisen, M.B., Spellmann, P.T., Brown, P.O. and Botstein, D. 1998. Cluster analysis & display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95: 14863–14868.

    PubMed  CAS  Google Scholar 

  • Farré, E.M., Tiessen, A., Roessner, U., Geigenberger, P., Trethewey, R.N. and Willmitzer, L. 2001. Analysis of the compartmentation of glycolytic intermediates, nucleotides, sugars, organic acids, amino acids and sugar alcohols in potato tubers using a non-aqueous fractionation method. Plant Physiol., in press.

    Google Scholar 

  • Fell, D.A. 1997. Understanding the control of metabolism. Snell (ed.) Portland Press, London. Portland Press Frontiers in metabolism 2: 301 pp.

    Google Scholar 

  • Fell, D.A., Wagner, A. 2000. The small world of metabolism. Nature Biotechnol. 18: 1121–1122.

    CAS  Google Scholar 

  • Fiehn, O., Kloska, K. and Altmann, T. 2001. Integrated studies on plant biology using multiparallel techniques. Curr. Opin. Biotechnol. 12: 82–86.

    PubMed  CAS  Google Scholar 

  • Fiehn, O., Kopka, J., Trethewey, R.N. and Willmitzer, L. 2000a. Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal. Chem. 72: 3573–3580.

    PubMed  CAS  Google Scholar 

  • Fiehn, O., Kopka, J., Dörmann, P., Altmann, T., Trethewey, R.N. and Willmitzer, L. 2000b. Metabolite profiling for plant functional genomics. Nature Biotechnol. 18: 1157–1161.

    CAS  Google Scholar 

  • Fraser, P.D., Pinto, M.E.S., Holloway, D.E. and Bramley, P.M. 2000. Application of high-performance liquid chromatography with photodiode array detection to the metabolic profiling of plant isoprenoids. Plant J. 24: 551–558.

    PubMed  CAS  Google Scholar 

  • Gámiz-Gracia, L. and de Castro, M.D.L. 2000. Continuous subcritical water extraction of medicinal plant essential oil: comparison with conventional techniques. Talanta 51:1179–1185.

    PubMed  Google Scholar 

  • Gavaghan, C.L., Holmes, E., Lenz, E., Wilson, I.D., Nicholson, J.K.. 2000. An NMR-based metabonomic approach to investigate the biochemical consequences of genetic strain differences: application to the C57BL10J and Alpk:ApfCD mouse. FEBS Lett. 484:169–174.

    PubMed  CAS  Google Scholar 

  • Gerhardt, R. and Heldt, H.W. 1984. Measurement of subcellular metabolite levels in leaves by fractionation of freeze-stopped material in nonaqueous media. Plant Physiol. 75: 542–547.

    PubMed  CAS  Google Scholar 

  • Giddings, G., Allison, G., Brooks, D. and Carter, A 2000. Transgenic plants as factories for biopharmaceuticals. Nature Biotechnol. 18: 1151–1155.

    CAS  Google Scholar 

  • Giersch, C. 1995. Determining elasticities from multiple measurements of flux rates and metabolite concentrations: application of the multiple modulation method to a reconstituted pathway. Eur. J. Biochem. 227: 194–201.

    PubMed  CAS  Google Scholar 

  • Giersch, C. 2000. Mathematical modelling of metabolism. Curr. Opin. Plant Biol. 2: 249–253.

    Google Scholar 

  • Gilbert, R.J., Goodacre, R., Woodward, A.M. and Kell, D.B. 1997. Genetic programming: a novel method for the quantitative analysis of pyrolysis mass spectral data. Anal. Chem. 69: 4381–4389.

    PubMed  CAS  Google Scholar 

  • Gilbert, R.J., Rowland, J.J. and Kell, D.B. 2000. Genomic computing: explanatory modelling for functional genomics. In: D. Whitley, D. Goldberg and E. Cantú-Paz (Eds.) Proceedings of the Genetic and Evolutionary Computation Conference, Morgan Kaufman, San Francisco, pp. 551–557.

    Google Scholar 

  • Gombert, A.K. and Nielsen, J. 1999. Mathematical modelling of metabolism. Curr. Opin. Biotechnol. 11: 180–186.

    Google Scholar 

  • Gonzalez, B., Francois, J. and Renaud, M. 1997. A rapid and reliable method for metabolite extraction in yeast using boiling buffered ethanol. Yeast 13: 1347–1356.

    PubMed  CAS  Google Scholar 

  • Goodacre, R., Shann, B., Gilbert, R.J., Timmings, E.M., McGovern, A.C., Alsberg, B.K., Kell, D.B. and Logan NA. 2000. Detection of the dipicolinic acid biomarker in Bacillus spores using Curiepoint pyrolysis mass spectrometry and Fourier transform infrared spectroscopy. Anal. Chem. 72: 119–127.

    PubMed  CAS  Google Scholar 

  • Goryanin, I., Hodgman, T.C. and Selkov, E. 1999. Mathematical simulation and analysis of cellular metabolism and regulation. Bioinformatics 15: 749–758.

    PubMed  CAS  Google Scholar 

  • Groen, A.K., van Roermund, C.W.T., Vervoorn, R.C. and Tager, J.M. 1986. Control of gluconeogenesis in rat liver cells: flux control coefficients of the enzymes in the gluconeogenic pathway in the absence and presence of glucagon. Biochem. J. 237: 379–389.

    PubMed  CAS  Google Scholar 

  • Gu, M., Kerwin, J.L., Watts, J.D. and Aebersold, R. 1997. Ceramide profiling of complex lipid mixtures by electrospray ionisation mass spectrometry. Anal. Biochem. 24: 347–356.

    Google Scholar 

  • Halket, J.M., Przyborowska, A., Stein, S.E., Mallard, W.G., Down, S. and Chalmers, R.A. 1999. Deconvolution gas chromatography mass spectrometry of urinary organic acids. Potential for pattern recognition and automated identification of metabolic disorders. Rapid Commun. Mass Spectrom. 13: 279–284.

    PubMed  CAS  Google Scholar 

  • Heinrich, R. and Rapoport, T.A. 1974. A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. Eur. J. Biochem. 42: 89–95.

    PubMed  CAS  Google Scholar 

  • Hofmeyr, J.-H.S. 1995. Metabolic regulation: a control analytic perspective. J. Bioenerget. Biomembr. 27: 479–490.

    CAS  Google Scholar 

  • Hofmeyr, J.-H.S. and Cornish-Bowden, A. 1995. Strategies for manipulating metabolic fluxes in biotechnology. Bioorg. Chem. 23: 439_449.

    Google Scholar 

  • Hofmeyr, J.-H.S., Cornish-Bowden, A. and Rohwer, J.M. 1993. Taking enzyme kinetics out of control; putting control into regulation. Eur. J. Biochem. 212: 833–837.

    PubMed  CAS  Google Scholar 

  • Jarvis, A.P. and Morgan, E.D. 1997. Isolation of plant products by supercritical fluid extraction. Phytochem. Anal. 8: 217–222.

    CAS  Google Scholar 

  • Jeong, H., Tombor, B., Albert, R., Oltvai, Z.N. and Barabási, A.-L. 2000. The large-scale organization of metabolic networks. Nature 407: 651–654.

    PubMed  CAS  Google Scholar 

  • Jellum, E., Kvittingen, E.A. and Stokke, O. 1988. Mass spectrometry in diagnosis of metabolic disorders. Biomed. Environ. Mass Spectrom. 16: 57–62.

    PubMed  CAS  Google Scholar 

  • Johansen, H.N., Glitso, V. and Knudsen, K.E.B. 1996. Influence of extraction solvent and temperature on the quantitative determination of oligosaccharides from plant materials by high performance liquid chromatography. J. Agric. Food Chem. 44: 1470–1474.

    CAS  Google Scholar 

  • Johnson, H.E., Gilbert, R.J., Winson, M.K., Goodacre, R., Smith, A.R., Rowland, J.J., Hall, M.A. and Kell, D.B. 2000. Explanatory analysis of the metabolome using genetic programming of simple, interpretable rules. Genet. Program Evolv. Mach. 1: 243–258.

    Google Scholar 

  • Kacser, H. and Burns, J.A.. 1973. The control of flux. Symp. Soc. Exp. Biol. 27: 65–105. Reprinted in 1995 in Biochem. Soc. Trans. 23: 341–366.

    PubMed  CAS  Google Scholar 

  • Katona, Z.F., Sass, P. and Molnár-Perl, I. 1999. Simultaneous determination of sugars, sugar alcohols, acids and amino acids in apricots by gas chromatography-mass spectrometry. J. Chromatogr. A 847: 91–102.

    CAS  Google Scholar 

  • KEGG. http://www.genome.ad.jp/kegg/

  • Kell, D.B. and Mendes, P. 2000. Snapshots of systems. In: A.J. Cornish-Bowden and M.L. Cardenas (Eds.) Technological and Medical Implications of Metabolic Control Analysis, Kluwer Academic Publishers, Dordrecht, Netherlands, pp. 3–25.

    Google Scholar 

  • Kholodenko, B.N., Schuster, S., Rohwer, J.M., Cascante, M. and Westerhoff, H.V. 1995. Composite control of cell function: metabolic pathways behaving as single control units. FEBS Lett. 368: 1–4.

    PubMed  CAS  Google Scholar 

  • Kim, K.-R., Park, H.-G., Paik, M.-J., Ryu, H.-S., Oh, K.S., Myung, S.-W. and Liebich, H.M. 1998. Gas chromatographic profiling of urinary organic acids from uterine myoma patients and cervical cancer patients. J. Chromatogr. B 712: 11–22.

    CAS  Google Scholar 

  • Kimura, H., Yamamoto, T. and Seiji, Y 1999. Automated metabolic profiling and interpretation of GC/MS data for organic academia screening: a personal computer-based system. Tohuku J. Exp. Med. 188: 317–344.

    CAS  Google Scholar 

  • Klapa, M.I., Park, S.M., Sinskey, A.J. and Stephanopoulos, G. 1999. Metabolite and isotopomer balancing in the analysis of metabolic cycles. I. Theory. Biotechnol. Bioeng. 62: 375–391.

    CAS  Google Scholar 

  • Kose, F., Weckwerth, W., Linke, T. and Fiehn, O. 2001. Visualising plant metabolomic correlation networks using clique-metabolite matrices. Bioinformatics, in press.

    Google Scholar 

  • Krauss, S. and Quant, PA. 1996. Regulation and control in complex, dynamic metabolic systems: experimental application of the top-down approaches of metabolic control analysis to fatty acid oxidation and ketogenesis. J. Theor. Biol. 182: 381–388.

    PubMed  CAS  Google Scholar 

  • Lim, H.K., Stellingwerf, S., Sisenwine, S. and Chan, K.W. 1999. Rapid drug metabolite profiling using fast liquid chromatography, automated multiple-stage mass spectrometry and receptor-binding. J. Chromatogr. A 831: 227–241.

    PubMed  CAS  Google Scholar 

  • Lukashin, A.V. and Fuchs, R. 2001. Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters. Bioinformatics 17: 405–414.

    PubMed  CAS  Google Scholar 

  • Mendes, P. and Kell, D.B. 1998. Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation. Bioinformatics 14: 869–883.

    PubMed  CAS  Google Scholar 

  • Möllney, M., Wiechert, W., Kownatzki, D. and de Graaf, A.A. 1999. Bidirectional reaction steps in metabolic networks. IV. Optimal design of isotopomer labelling experiments. Biotechnol. Bioeng. 66:86–103.

    PubMed  Google Scholar 

  • Namiesnik, J. and Gorecki, T. 2000. Sample preparation for chromatographic analysis of plant material. J. Plan. Chromatogr. 13: 404–413.

    CAS  Google Scholar 

  • Ning, C., Kuhara, T., Inoue, Y., Zhang, C.H., Matsumoto, M., Shinka, T., Furumoto, T., Yokota, K. and Matsumoto, I. 1996. Gas chromatographic mass spectrometric metabolic profiling of patients with fatal infantile mitochondrial myopathy with de Toni-Fanconi-Debre syndrome. Acta Paed. Japon. 38: 661–666.

    CAS  Google Scholar 

  • Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H. and Kanehisa, M. 1999. KEGG: Kyoto encyclopedia of genes and genomes. Nucl. Acids Res. 27: 29–34.

    PubMed  CAS  Google Scholar 

  • Oliver, S.G., Winson, M.K., Kell, D.B. and Baganz, R. 1998. Systematic functional analysis of the yeast genome. Trends Biotechnol. 16: 373–378.

    PubMed  CAS  Google Scholar 

  • Ong, E.-S., Woo, S.-O. and Yong, Y.-L. 2000. Pressurized liquid extraction of berberine and aristolochic acids in medicinal plants. J. Chromatogr. A 313: 57–64.

    Google Scholar 

  • Orth, H.C.J., Rentel, C. and Schmidt, PC. 1999. Isolation, purity analysis and stability of hyperforin as a standard material from Hypericum perforatum L. J. Pharm. Pharmcol. 51: 193–200.

    CAS  Google Scholar 

  • Park, S.M., Klapa, M.I., Sinskey, A.J. and Stephanopoulos, G. 1999. Metabolite and isotopomer balancing in the analysis of metabolic cycles. II. Applications. Biotechnol. Bioeng. 62: 392–401.

    CAS  Google Scholar 

  • Peng, S. and Jayallemand, C. 1991. Use of antioxidants in extraction of tannins from walnut plants. J. Chem. Ecol. 17: 887–895.

    CAS  Google Scholar 

  • Pfeiffer, T., Sánchez-Valdenebro, I., Nuno, J.C., Montero, F. and Schuster, S. 1999. Metatool: for studying metabolic networks. Bioinformatics 15: 251–257.

    PubMed  CAS  Google Scholar 

  • Poolman, M.G., Fell, D.A. and Thomas, S. 2000. Modelling photosynthesis and its control. J. Exp. Bot. 51: 319–328.

    PubMed  CAS  Google Scholar 

  • Poolman, M..G., Ölcer, H., Lloyd, J.C., Raines, C.A. and Fell, D.A. 2001. Computer modelling and experimental evidence for two steady-states in the photosynthetic Calvin cycle. Eur. J. Biochem. 368:2810–2816.

    Google Scholar 

  • Que, A.M., Palm, A., Baker, A.G. and Novotny, M.V. 2000. Steroid profiles determined by capillary electrochromatography, laser-induced fluorescence detection and electrospray-mass spectrometry. J. Chromatogr. A 887: 379–391.

    PubMed  CAS  Google Scholar 

  • Raamsdonk, L.M., Teusink, B., Broadhurst, D., Zhang, N., Hayes, A., Walsh, M.C., Berden, J.A., Brindle, K.M., Kell, D.B., Rowland, J.J., Westerhoff, H.V., van Dam, K. and Oliver, S.G. 2001. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nature Biotechnol. 19: 45–50.

    CAS  Google Scholar 

  • Raith, K., Zellmer, S., Lasch, J. and Neubert, R.H.H. 2000. Profiling of human stratum corneum ceramides by liquid chromatography-electrospray mass spectrometry. Anal. Chim. Acta 418: 167–173.

    CAS  Google Scholar 

  • Roberts, J.K.M. 2000. NMR adventures in the metabolic labyrinth within plants. Trends Plant Sci. 5: 30–34.

    PubMed  CAS  Google Scholar 

  • Robertson, D.G., Reily, M.D., Sigler, RE., Wells, D.F., Paterson, D.A. and Braden, T.K. 2000. Metabonomics: evaluation of nuclear magnetic resonance (NMR) and pattern recognition technology for rapid in vivo screening of liver and kidney toxicants. Toxicol. Sci. 57: 326–337.

    PubMed  CAS  Google Scholar 

  • Roessner, U., Luedemann, A., Brust, D., Fiehn, O., Linke, T., Willmitzer, L. and Fernie, A.R. 2001. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13: 11–29.

    PubMed  CAS  Google Scholar 

  • Roessner, U., Wagner, C., Kopka, J., Trethewey, R.N. and Willmitzer, L. 2000. Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry. Plant J. 23: 131–142.

    PubMed  CAS  Google Scholar 

  • Sargenti, S.R. and Vichnewski, W 2000. Sonication and liquid chromatography as a rapid technique for extraction and fractionation of plant material. Phytochem. Anal. 11: 69–73.

    CAS  Google Scholar 

  • Sauter, H., Lauer, M. and Fritsch, H. 1991. Metabolic profiling of plants: a new diagnostic technique. ACS Symp. Ser. 443: 288–299.

    CAS  Google Scholar 

  • Schmidt, K., Carlsen, M., Nielsen, J. and Villadsen, J. 1997. Modelling isotopomer distributions in biochemical networks using isotopomer mapping matrices. Biotechnol. Bioeng. 55: 831–840.

    PubMed  CAS  Google Scholar 

  • Schuster, S. 1999. Studies on the stoichiometric structure of enzymatic reaction systems. Theory Biosci. 118: 125–139.

    CAS  Google Scholar 

  • Schuster, S., Dandekar, T. and Fell, D.A. 1999. Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol. 17: 53–60.

    PubMed  CAS  Google Scholar 

  • Schuster, S., Fell, D.A. and Dandekar, T. 2000. A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nature Biotechnol. 18: 326–332.

    CAS  Google Scholar 

  • Shetty, H.U., Holloway, H.W. and Rapoport, S.I. 1995. Capillary gas chromatography combined with ion trap detection for quantitative profiling of polyols in cerebrospinal fluid and plasma. Anal. Biochem. 224: 279–285.

    PubMed  CAS  Google Scholar 

  • Smedsgaard, J. and Frisvad, J.C. 1996. Using direct electrospray mass spectrometry in taxonomy and secondary metabolite profiling of crude fungal extracts. J. Microbiol. Meth. 25: 5–17.

    CAS  Google Scholar 

  • Srere, P.A. 1985. The metabolon. Trends Biochem. Sci. 10: 109–110.

    Google Scholar 

  • Starmans, D.A.J. and Nijhuis, H.H. 1996. Extraction of secondary metabolites from plant material: a review. Trends Food Sci. Technol. 7: 191–197.

    CAS  Google Scholar 

  • Stein, S.E. 1999. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spectrom. 10: 770–781.

    CAS  Google Scholar 

  • Streeter J.G. and Strimbu C.E. 1998. Simultaneous extraction and derivatization of carbohydrates from green plant tissues for analysis by gas-liquid chromatography. Anal. Biochem. 259: 253–257.

    PubMed  CAS  Google Scholar 

  • Szyperski, T. 1998. 13C-NMR, MS and metabolic flux balancing in biotechnology research. Quant. Rev. Biophys. 31: 41–106.

    CAS  Google Scholar 

  • Tanaka, K., Hine, D.G., West-Dull, A. and Lynn, T.B. 1980a. Gas-chromatographic method of analysis of urinary organic acids. I. Retention indices of 155 metabolically important compounds. Clin. Chem. 26: 1839–1846.

    PubMed  CAS  Google Scholar 

  • Tanaka, K., West-Dull, A., Hine, D.G., Lynn, T.B. and Lowe, T. 1980b. Gas-chromatographic method of analysis of urinary organic acids. II. Description of the procedure, and its application to diagnosis of patients with organic acidurias. Clin. Chem. 26: 1847–1853.

    PubMed  CAS  Google Scholar 

  • Taylor, J., Goodacre, R., Wade, W.G., Rowland, J.J. and Kell, D.B. 1998. The deconvolution of pyrolysis mass spectra using genetic programming: application to the identification of some Eubacterium species. FEMS Microbiol. Lett. 160: 237–246.

    PubMed  CAS  Google Scholar 

  • Teusink, B., Baganz, F., Westerhoff, H.V. and Oliver, S.G. 1998. Metabolic control analysis as a tool in the elucidation of the function of novel genes. Meth. Microbiol. 26: 297–336.

    CAS  Google Scholar 

  • Thomas, S., Mooney, P.J.F., Burrell, M.M. and Fell, D.A. 1997. Metabolic control analysis of glycolysis in tuber tissue of potato (Solarium tuberosum): explanation for the low control coefficient of phosphofructokinase over respiratory flux. Biochem J. 332: 119–127.

    Google Scholar 

  • Trethewey, R.N., Geigenberger, P., Riedel, K., Hajurezaei, M.R., Sonnewald, U., Stitt, M., Riesmeier, J.W. and Willmitzer, L. 1998. Combined expression of glucokinase and invertase in potato tubers leads to a dramatic reduction in starch accumulation and a stimulation of glycolysis. Plant J. 15: 109–118.

    PubMed  CAS  Google Scholar 

  • Trethewey, R.N., Krotzky, A.J. and Willmitzer, L. 1999. Metabolic profiling: a Rosetta stone for genomics? Curr. Opin. Plant Biol. 2: 83–85.

    PubMed  CAS  Google Scholar 

  • Tweeddale, H., Notley-McRobb, L. and Ferenci, T. 1998. Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (’metabolome’) analysis. J. Bact. 180: 5109–5116.

    PubMed  CAS  Google Scholar 

  • Velot, C., Mixon, M.B., Teige, M. and Srere, P.A. 1997. Model of a quinary structure between Krebs TCA cycle enzymes: a model for the metabolon. Biochemistry 36: 14271–14276.

    PubMed  CAS  Google Scholar 

  • Vingron, M. and Hoheisel, J. 1999. Computational aspects of expression data. J. Mol. Med. 77: 3–7.

    PubMed  CAS  Google Scholar 

  • Warne, M.A., Lenz, E.M., Osborn, D., Weeks, J.M. and Nicholson, J.K. 2000. An NMR-based metabonomic investigation of the toxic effects of 3-trifluoromethyl-aniline on the earthworm Eisenia veneta. Biomarkers 5: 56–72.

    CAS  Google Scholar 

  • Wiechert, W. and de Graaf, A.A. 1997a. Bidirectional reaction steps in metabolic networks. I. Modeling and simulation of carbon isotope labelling experiments. Biotechnol. Bioeng. 55: 112–117.

    Google Scholar 

  • Wiechert, W., Siefke, C., de Graaf, A.A. and Marx, A. 1997b. Bidirectional reaction steps in metabolic networks. II. Flux estimation and statistical analysis. Biotechnol. Bioeng. 55: 118–135.

    CAS  Google Scholar 

  • Wiechert, W., Möllney, M., Isermann, N., Wurzel, M. and de Graaf, A.A. 1999. Bidirectional reaction steps in metabolic networks. III. Explicit solution and analysis of isotopomer systems. Biotechnol. Bioeng. 66: 69–85.

    PubMed  CAS  Google Scholar 

  • Wolfender, J.L., Rodriguez, S. and Hostettmann, K. 1998. Liquid chromatography coupled to mass spectrometry and nuclear magnetic resonance for the screening of plant constituents. J. Chromatogr. A 794: 299–316.

    CAS  Google Scholar 

  • World Health Organization. 2000. Safety aspects of genetically modified foods of plant origins. In: Report of a joint FAO/WHO expert consultation on foods derived from biotechnology, held in Geneva, Switzerland, 29 May–2 June 2000. World Health Organization, Geneva, pp. 1–35.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Max-Planck Institute of Molecular Plant Physiology, 14424, Potsdam, Germany

    Oliver Fiehn

Authors
  1. Oliver Fiehn
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. The Institute for Genomic Research, Rockville, MD, USA

    Chris Town

  2. Case Western Reserve University, Cleveland, OH, USA

    Chris Town

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Fiehn, O. (2002). Metabolomics — the link between genotypes and phenotypes. In: Town, C. (eds) Functional Genomics. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0448-0_11

Download citation

  • DOI: https://doi.org/10.1007/978-94-010-0448-0_11

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-3903-1

  • Online ISBN: 978-94-010-0448-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation