The concept of metabolite profiling has been around for several decades, but only recent technical innovations have allowed metabolite profiling to be carried out on a large scale — with respect to both the number of metabolites measured and the number of experiments carried out. As a result, the power of metabolite profiling as a technology platform for diagnostics, and the research areas of gene-function analysis and systems biology, is now beginning to be fully realized.
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Harrigan, G. G. & Goodacre, R. (eds). Metabolic Profiling: Its Role in Biomarker Discovery and Gene Functional Analysis (Kluwer Academic, Boston, 2003).
Fiehn, O. Metabolomics. The link between genotype and phenotype. Plant Mol. Biol. 48, 155–171 (2002).
Kell, D. B. Metabolomics and systems biology: making sense of the soup. Curr. Opin. Microbiol. 7, 296–307 (2004).
Roessner, U. et al. Metabolite profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11–29 (2001).
Fiehn, O. et al. Metabolite profiling for plant functional genomics. Nature Biotech. 18, 1157–1161 (2000).
Halket, J. M. et al. 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 (2003).
Aharoni, A. et al. Terpenoid metabolism in wild type and transgenic Arabidopsis plants. Plant Cell 15, 2866–2884 (2003).
Swart, P. J. et al. HPLC-UV atmospheric-pressure ionisation mass-spectrometric determination of the dopamine-D2 agonist N-0923 and its major metabolites after oxidative metabolism by rat liver, monkey liver and human liver microsomes. Toxicology Methods 3, 279–290 (1993).
Matuszewski, B. K., Constanzer, M. L. & Chavez-Eng, C. M. Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLC-MS/MS. Anal. Chem. 75, 3019–3030 (2003).
Plumb, R. S. et al. Use of liquid chromatography/time-of-flight mass spectrometry and multivariate statistical analysis shows promise for the detection of drug metabolites in biological fluids. Rapid Commun. Mass Spectrom. 17, 2632–2638 (2003).
Watkins, S. M. & German, J. B. Metabolomics and biochemical profiling in drug discovery and development. Curr. Opin. Mol. Ther. 4, 224–228 (2002).
Aharoni, A. et al. Nontargeted metabolome analysis by use of Fourier transform ion cyclotron mass spectrometry. OMICS 6, 217–234 (2002).
Soga, T. et al. Quantitative metabolome analysis using capillary electrophoresis mass spectrometry. J. Proteome Res. 2, 488–494 (2003).
Nobeli, I., Krissinel, E. B. & Thornton, J. M. B. A structure-based anatomy of the E. coli metabolome. J. Mol. Biol. 334, 697–719 (2003).
Hall, R. et al. Plant metabolomics: the missing link in functional genomics strategies. Plant Cell 14, 1437–1440 (2002).
Roessner-Tunali, U. et al. Metabolic profiling of transgenic tomato plants overexpressing hexokinase reveals that the influence of hexose phosphorylation diminishes during fruit development. Plant Physiol. 133, 84–99 (2003).
Walles, M. et al. Verapamil drug metabolism studies by automated in-tube solid phase microextraction. J. Pharma. Biomed. Anal. 30, 307–319 (2002).
Kok, E. J. & Kuiper, H. A. Comparative safety assessment for biotech crops. Trends Biotech. 21, 438–444 (2003).
Sauter, H., Lauer, M. & Fritsch, H. Metabolite profiling of plants — a new diagnostic technique. Abstr. Pap. Am. Chem. Soc. 195, 129 (1988).
Allen, J. et al. High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nature Biotech. 21, 692–696 (2003).
Brindle, J. T. et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nature Med. 8, 1439–1444 (2002).
Huhman, D. V. & Sumner, L. W. Metabolic profiling of saponins in Medicago sativa and Medicago trunculata using HPLC coupled to an electrospray ion-trap mass spectrometer. Phytochemistry 59, 347–360 (2002).
Kose, F., Weckwerth, W., Linke, T. & Fiehn, O. Visualizing plant metabolomic correlation networks using clique-metabolite matrices. Bioinformatics 17, 1198–1208 (2001).
Aranibar, N., Singh, B. K., Stockton, G. W. & Ott, K. H. Automated mode-of-action detection by metabolic profiling. Biochem. Biophys. Res. Commun. 286, 150–155 (2001).
Quackenbush, J. Computational analysis of microarray data. Nature Rev. Genet. 2, 418–427 (2001).
Griffin, J. L. et al. NMR spectroscopy based metabonomic studies on the comparative biochemistry of the kidney and urine of the bank vole (Clethrionomys glareolus), wood mouse (Apodemus sylvaticus), white toothed shrew (Crocidura suaveolens) and the laboratory rat. Comp. Biochem. Physiol. B 127, 357–367 (2000).
Kaderbhai, N. N., Broadhurst, D. I., Ellis, D. I., Goodacre, R. & Kell, D. B. Functional genomics via metabolic footprinting: monitoring metabolite secretion by Escherichia coli tryptophan metabolism mutants using FT-IR and direct injection electrospray mass spectrometry. Comp. Funct. Genomics 4, 376–391 (2003).
Rashed, M. S. et al. Screening blood spots for inborn errors of metabolism by electrospray tandem mass spectrometry with a microplate batch process and a computer algorithm from automated flagging of abnormal profiles. Clin. Chem. 43, 1129–1141 (1997).
Martzen, M. R. et al. A biochemical genomics approach for identifying genes by the activity of their products. Science 286, 1153–1155 (1999).
Trethewey, R. N., Krotzky, A. J. & Willmitzer, L. Metabolic profiling: a Rosetta stone for genomics? Curr. Opin. Plant Biol. 2, 83–85 (1999).
Raamsdonk, L. M. et al. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nature Biotech. 19, 45–50 (2001).
Fehr, M., Lalonde, S., Lager, I., Wolff, M. W. & Frommer, W. B. In vivo imaging of the dynamics of glucose uptake in the cytosol of COS-7 cells by fluorescent nanosensors. J. Biol. Chem. 278, 19127–19133 (2003).
Barabasi, A. L. & Oltvai, Z. N. Network biology: understanding the cell's functional organisation. Nature Rev. Genet. 5, 101–113 (2004).
Wagner, A. & Fell, D. A. The small world inside large metabolic networks. Proc. R. Soc. Lond. B 268, 1803–1810 (2001).
Kamath, R. S. et al. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 421, 231–237 (2003).
Kacser, H. & Burns, J. A. The control of flux. Symposia Soc. Exp. Biol. 28, 65–104 (1974).
Fernie, A. R. et al. Metabolic profiling at the genome level. Plant Animal Genome Abstr. XI, W307 (2003).
Kitano, H. Perspectives on systems biology. New Generation Comput. 18, 199–216 (2000).
Ideker, T., Galitski, T. & Hood, L. A new approach to decoding life: systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343–372 (2001).
Edwards, J. S., Ibarra, R. U. & Palsson, B. O. In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nature Biotech. 19, 125–130 (1999).
Baliga, N. S. et al. Coordinate regulation of energy transduction modules in Halobacterium sp. analyzed by a global systems approach. Proc. Natl Acad. Sci. USA 99, 14913–14918 (2002).
Davidson, E. H. et al. A genomic regulatory network for development. Science 295, 1669–1678 (2002).
Nicholson, J. K. & Wilson, I. D. Understanding 'global' systems biology: metabonomics and the continuum of metabolism. Nature Rev. Drug Discov. 2, 668–676 (2003).
Weckwerth, W. Metabolomics in systems biology. Annu. Rev. Plant Biol. 54, 669–689 (2003).
Urbanczyk-Wochniak, E. et al. Parallel analysis of transcript and metabolic profiles: a new approach in systems biology. EMBO Reports 4, 989–993 (2003).
Askenazi, M. et al. Integrating transcriptional and metabolite profiles to direct the engineering of Iovastatin-producing fungal strains. Nature Biotech. 21, 150–156 (2003).
Gygi, S. P. et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nature Biotech. 17, 994–999 (1999).
Stein, S. E. An integrated method for spectrum extraction and compound identification from GC/MS data. J. Am. Soc. Mass Spectrom. 10, 770–781 (1999).
Wagner, C., Sefkow, M. & Kopka, J. Construction and application of a mass spectral and retention time index database generated from plant GC/EI-TOF-MS metabolite profiles. Phytochemistry 62, 887–900 (2003).
Frenzel, T., Miller, A. & Engel, K. H. A methodology for automated comparative analysis of metabolite profiling data. Eur. Food Res. Technol. 216, 335–342 (2003).
Duran, A. L., Yang, J., Wang, L. & Sumner, L. W. Metabolomics spectral formatting, alignment and conversion tools (MSFACTs). Bioinformatics 19, 2283–2293 (2003).
Waisim, M., Hassan, M. S. & Brereton, R. G. Evaluation of chemometric methods for determining the number and position of components in high-performance liquid chromatography detected by diode array detector by diode array detector and on-flow 1H nuclear magnetic resonance spectroscopy. Analyst 128, 1082–1090 (2003).
Lindon, J. C. HPLC-NMR-MS: past, present and future. Drug Discov. Today 8, 1021–1022 (2003).
Meiler, J. & Will, M. Genius: a genetic algorithm for automated structure elucidation from 13C NMR spectra. J. Am. Chem. Soc. 124, 1868–1870 (2002).
The authors thank O. Schmitz for assistance in the preparation of figure 2. Software used in the preparation of figure 2 was provided by OmniViz Inc.
The authors declare no competing financial interests.
The application of statistical and computer methods to data analysis in chemistry and related scientific fields.
The smallest taxonomic subdivision of an ecospecies, which consists of populations that have adapted to a particular set of environmental conditions.
- ELECTROSPRAY IONIZATION
To analyse compounds effectively by mass spectrometry, they must be ionized in the gas phase. Electrospray is the most widely used atmospheric-pressure ionization technique for the sensitive, comprehensive analysis of polar and ionic compounds. Using electrospray, a strong electric field is applied to the liquid sample stream, which is then nebulized and desolvated with the assistance of a high-temperature gas flow to produce gas-phase ions.
- HIERARCHICAL CLUSTER ANALYSIS
An agglomerative statistical method that finds clusters of observations within a data set. It allows the grouping of individuals on the basis of the similarity in their properties.
- ION SUPPRESSION
The common term that is given to a range of phenomena that can occur during the ionization of complex mixtures. An important component of this is the competition between co-eluting compounds for ionization energy, which can lead to varying degrees of ionization of any individual compounds.
- PRINCIPAL COMPONENT ANALYSIS
A statistical tool in which an orthogonal coordinate system, with axes that are ordered in terms of the amount of variance in a dataset, is produced. This allows the separation of individuals on the basis of differences in their properties and can also be used to evaluate the properties that contribute the most to these separations.
- QUADRUPOLE TECHNOLOGY
A quadrupole mass filter consists of four parallel metal rods. Two opposite rods have a DC voltage and the other two have an AC voltage. The applied voltages affect the trajectory of ions that travel down the flight path that is centred between the four rods, such that only ions of a certain mass-to-charge ratio pass through the quadrupole filter and all other ions are thrown out of their original path. A mass spectrum is obtained by monitoring the ions that pass through the quadrupole filter as the voltages on the rods are varied.
- SUBSTANTIAL EQUIVALENCE TESTING
The concept of substantial equivalence embodies the idea that organisms that are used as foods or as food sources can serve as a basis for comparison when assessing the safety of human consumption of a food or food component that has been modified or is new.
- SUPERVISED GROUPING APPROACH
A method that requires training with known data sets in which the types of groups expected are predefined before being applied to experimental data.
- UNSUPERVISED GROUPING APPROACH
A method that does not require training with known data sets and that generates groups on the basis of the data structure in the experimental data.
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Fernie, A., Trethewey, R., Krotzky, A. et al. Metabolite profiling: from diagnostics to systems biology. Nat Rev Mol Cell Biol 5, 763–769 (2004). https://doi.org/10.1038/nrm1451
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