Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-05-22T10:56:52.750Z Has data issue: false hasContentIssue false
  • English
  • Français

Metabolomics: an emerging post-genomic tool for nutrition

Published online by Cambridge University Press:  09 March 2007

Phillip D. Whitfield ,
Alexander J. German  and
Peter-John M. Noble
Phillip D. Whitfield*
Affiliation:
Department of Veterinary Preclinical Sciences, Faculty of Veterinary Science, University of Liverpool, Crown Street, Liverpool L69 7ZJ, UK
Alexander J. German
Affiliation:
Small Animal Teaching Hospital, Faculty of Veterinary Science, University of Liverpool, Crown Street, Liverpool L69 7ZJ, UK
Peter-John M. Noble
Affiliation:
Small Animal Teaching Hospital, Faculty of Veterinary Science, University of Liverpool, Crown Street, Liverpool L69 7ZJ, UK
*
*Corresponding author: Dr P. D. Whitfield, fax +44 151 794 4243, email pdw01@liv.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The post-genomic era has been driven by the development of technologies that allow the function of cells and whole organisms to be explored at the molecular level. Metabolomics is concerned with the measurement of global sets of low-molecular-weight metabolites. Metabolite profiles of body fluids or tissues can be regarded as important indicators of physiological or pathological states. Such profiles may provide a more comprehensive view of cellular control mechanisms in man and animals, and raise the possibility of identifying surrogate markers of disease. Metabolomic approaches use analytical techniques such as NMR spectroscopy and MS to measure populations of low-molecular-weight metabolites in biological samples. Advanced statistical and bioinformatic tools are then employed to maximise the recovery of information and interpret the large datasets that are generated. Metabolomics has already been used to study toxicological mechanisms and disease processes and offers enormous potential as a means of investigating the complex relationship between nutrition and metabolism. Examples include the metabolism of dietary substrates, drug-induced disturbances of lipid metabolites in type 2 diabetes mellitus and the therapeutic effects of vitamin supplementation in the treatment of chronic metabolic disorders.

Keywords

MetabolomicsMetabonomicsMetabolite profiling
Type
Horizons in Nutritional Science
Information
British Journal of Nutrition , Volume 92 , Issue 4 , October 2004 , pp. 549 - 555
Copyright
Copyright © The Nutrition Society 2004

References

Aharoni, A, Ric, de, Vos, CH, Verhoeven, HA, Maliepaard, CA, Kruppa, G, Bino, R & Goodenowe, DB (2002) Non-targeted metabolome analysis by use of Fourier transform ion cyclotron mass spectrometry. OMICS 6, 217–234.Google Scholar
Allen, J, Davey, HM, Broadhurst, D, Heald, JK, Rowland, JJ, Oliver, SG & Kell, DB (2003) High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nat Biotechnol 21, 692–696.Google Scholar
Beckwith-Hall, BM, Nicholson, JK, Nicholls, A, Nicholls, AW, Foxall, PJ, Lindon, JC, Connor, SC, Abdi, M, Connelly, J & Holmes, E (1998) Nuclear magnetic resonance spectroscopic and principal components analysis investigations into biochemical effects of three hepatotoxins. Chem Res Toxicol 11, 260–272.Google Scholar
Brindle, JT, Antti, H & Holmes, E (2002) Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1 H-NMR-based metabonomics. Nat Med 8, 1439–1444.Google Scholar
Clayton, PT (2001) Applications of mass spectrometry in the study of inborn errors of metabolism. J Inherit Metab Dis 24, 139–150.Google Scholar
Elliott, R & Ong, TJ (2002) Nutritional genomics. BMJ 324, 1438–1442.CrossRefGoogle ScholarPubMed
Fiehn, O (2002) Metabolomics – the link between genotypes and phenotypes. Plant Mol Biol 48, 155–171.Google Scholar
Fiehn, O, Kloska, S & Altmannn, T (2001) Integrated studies on plant biology using multiparallel techniques. Curr Opin Biotechnol 12, 82–86.Google Scholar
Fiehn, O, Kopka, J, Dormann, P, Altmann, T, Trethewey, RN & Willmitzer, L (2000 a) Metabolite profiling for plant functional genomics. Nat Biotechnol 18, 1157–1161.Google Scholar
Fiehn, O, Kopka, J, Trethewey, RN & Willmitzer, L (2000 b) Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal Chem 72, 3573–3580.Google Scholar
Gavaghan, CL, Holmes, E, Lenz, E, Wilson, ID & Nicholson, JK (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.Google Scholar
German, JB, Roberts, MA & Watkins, SM (2003 a) Genomics and metabolomics as markers for the interaction of diet and health: lessons from lipids. J Nutr 133, 2078S–2083S.Google Scholar
German, JB, Roberts, MA & Watkins, SM (2003 b) Personal metabolomics as a next generation nutritional assessment. J Nutr 133, 4260–4266.Google Scholar
Glassbrook, N & Ryals, J (2001) A systemic approach to biochemical profiling. Curr Opin Plant Biol 4, 186–190.Google Scholar
Go, VL, Butrum, RR & Wong, DA (2003) Diet, nutrition and cancer prevention: the postgenomic era. J Nutr 133, 3830S–3836S.CrossRefGoogle ScholarPubMed
Goodacre, R, Vaidyanathan, S, Dunn, WB, Harrigan, GG & Kell, DB (2004) Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol 22, 245–252.Google Scholar
Griffin, JL (2004) Metabonomics: NMR spectroscopy and pattern recognition analysis of body fluids and tissues for characterisation of xenobiotic toxicity and disease diagnosis. Curr Opin Chem Biol 7, 648–654.CrossRefGoogle Scholar
Griffin, JL, Muller, D, Woograsingh, R, Jowatt, V, Hindmarsh, A, Nicholson, JK & Martin, JE (2002) Vitamin E deficiency and metabolic deficits in neuronal ceroid lipofuscinosis described by bioinformatics. Physiol Genomics 11, 195–203.Google Scholar
Griffiths, JR, McSheehy, PM, Robinson, SP, Troy, H, Chung, YL, Leek, RD, Williams, KJ, Stratford, IJ, Harris, AL & Stubbs, M (2002) Metabolic changes detected by in vivo magnetic resonance studies of HEPA-1 wild-type tumors and tumors deficient in hypoxia-inducible factor-1β (HIF-1β): evidence of an anabolic role for the HIF-1 pathway. Cancer Res 62, 688–695.Google Scholar
Griffiths, JR & Stubbs, M (2003) Opportunities for studying cancer by metabolomics: preliminary observations on tumors deficient in hypoxia-inducible factor 1. Adv Enzyme Regul 43, 67–76.CrossRefGoogle ScholarPubMed
Han, X & Gross, RW (2003) Global analyses of cellular lipidomes directly from crude extracts of biological samples by ESI mass spectrometry: a bridge to lipidomics. J Lipid Res 44, 1071–1079.Google Scholar
Hellerstein, MK (2003) In vivo measurement of fluxes through metabolic pathways: the missing link in functional genomics and pharmaceutical research. Annu Rev Nutr 23, 379–402.Google Scholar
Hellerstein, MK (2004) New stable isotope-mass spectrometric techniques for measuring fluxes through intact metabolic pathways in mammalian systems: introduction of moving pictures into functional genomics and biochemical phenotyping. Metab Eng 6, 85–100.CrossRefGoogle ScholarPubMed
Holmes, E & Antti, H (2002) Chemometric contributions to the evolution of metabonomics: mathematical solutions to characterising and interpreting complex biological NMR spectra. Analyst 127, 1549–1557.CrossRefGoogle Scholar
Idborg-Bjorkman, H, Edlund, PO, Kvalheim, OM, Schuppe-Koistinen, I & Jacobsson, SP (2003) Screening of biomarkers in rat urine using LC/electrospray ionisation-MS and two-way data analysis. Anal Chem 75, 4784–4792.CrossRefGoogle Scholar
Jonsson, P, Gullberg, J, Nordstrom, A, Kusano, M, Kowalczyk, M, Sjostrom, M & Moritz, T (2004) A strategy for identifying differences in large series of metabolomic samples analyzed by GC/MS. Anal Chem 76, 1738–1745.Google Scholar
Kell, DB (2004) Metabolomics and systems biology: making sense of the soup. Curr Opin Microbiol 7, 296–307.Google Scholar
Kuiper, HA, Kleter, GA, Noteborn, HP & Kok, EJ (2001) Assessment of the food safety issues relating to genetically modified foods. Plant J 27, 503–528.Google Scholar
Lamers, RJ, DeGroot, J, Spies-Faber, EJ (2003) Identification of disease- and nutrient-related metabolic fingerprints in osteoarthritic guinea pigs. J Nutr 133, 1776–1780.Google Scholar
Lenz, EM, Bright, J, Knight, R, Wilson, ID & Major, H (2004) Cyclosporin A-induced changes in endogenous metabolites in rat urine: a metabonomic investigation using high field 1H NMR spectroscopy, HPLC-TOF/MS and chemometrics. J Pharm Biomed Anal 35, 599–608.Google Scholar
Lindon, JC, Holmes, E & Nicholson, JK (2003 a) So what's the deal with metabonomics?. Anal Chem 75, 384A–391A.Google Scholar
Lindon, JC, Nicholson, JK & Holmes, E (2003 b) The role of metabonomics in toxicology and its evaluation by the COMET project. Toxicol Appl Pharmacol 187, 137–146.Google Scholar
Mendes, P (2002) Emerging bioinformatics for the metabolome. Brief Bioinform 3, 134–145.Google Scholar
Milner, JA (2003) Incorporating basic nutrition science into health interventions for cancer prevention. J Nutr 133, 3820S–3826S.Google Scholar
Nicholls, AW, Holmes, E, Lindon, JC, Shockcor, JP, Farrant, RD, Haselden, JN, Damment, SJ, Waterfield, CJ & Nicholson, JK (2001) Metabonomic investigations into hydrazine toxicity in the rat. Chem Res Toxicol 14, 975–987.Google Scholar
Nicholson, JK, Connelly, J, Lindon, JC & Holmes, E (2002) Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 1, 153–161.Google Scholar
Nicholson, JK, Lindon, JC & Holmes, E (1999) ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 1181–1189.Google Scholar
Nicholson, JK & Wilson, ID (2003) Understanding ‘global’ systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discov 2, 668–676.Google Scholar
Ordovas, JM & Mooser, V (2004) Nutrigenomics and nutrigenetics. Curr Opin Lipidol 15, 101–108.Google Scholar
Pham-Tuan, H, Kashavelis, L, Daykin, CA & Janssen, HG (2003) Method development in high-performance liquid chromatography for high throughput profiling and metabonomic studies of biofluid samples. J Chromatogr 789, 283–301.Google Scholar
Plumb, RS, Stumpf, CL, Gorenstein, MV, Castro-Perez, JM, Dear, GJ, Anthony, M, Sweatman, BC, Connor, SC & Haselden, JN (2002) Metabonomics: the use of electrospray mass spectrometry coupled to reversed-phase liquid chromatography shows potential for the screening of rat urine in drug development. Rapid Commun Mass Spectrom 16, 1991–1996.Google Scholar
Plumb, RS, Stumpf, CL, Granger, JH, Castro-Perez, J, Haselden, JN & Dear, GJ (2003) 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.Google Scholar
Raamsdonk, LM, Teusink, B & Broadhurst, D (2001) A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat Biotechnol 19, 45–50.Google Scholar
Rashed, MS (2001) Clinical applications of tandem mass spectrometry: ten years of diagnosis and screening for inherited metabolic diseases. J Chromatogr 758, 27–48.Google Scholar
Reo, NV (2002) NMR-based metabolomics. Drug Chem Toxicol 25, 375–382.Google Scholar
Roessner, U, Luedemann, A, Brust, D, Fiehn, O, Linke, T, Willmitzer, L & Fernie, A (2001) Metabolite profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11–29.CrossRefGoogle ScholarPubMed
Shockcor, JP & Holmes, E (2002) Metabonomic applications in toxicity screening and disease diagnosis. Curr Top Med Chem 2, 35–51.CrossRefGoogle ScholarPubMed
Solanky, KS, Bailey, NJ, Beckwith-Hall, BM, Davis, A, Bingham, S, Holmes, E, Nicholson, JK & Cassidy, A (2003) Application of biofluid 1 H nuclear magnetic resonance-based metabonomic techniques for the analysis of the biochemical effects of dietary isoflavones on human plasma profile. Anal Biochem 323, 197–204.Google Scholar
Su, X, Han, X, Yang, J, Mancuso, DJ, Chen, J, Bickel, PE & Gross, RW (2004) Sequential ordered fatty acid α oxidation and Δ9 desaturation are major determinants of lipid storage and utilization in differentiating adipocytes. Biochemistry 43, 5033–5044.Google Scholar
Sumner, LW, Mendes, P & Dixon, RA (2003) Plant metabolomics: large-scale phytochemistry in the functional genomics era. Phytochemistry 62, 817–836.CrossRefGoogle ScholarPubMed
Teague, C, Holmes, E, Maibaum, E, Nicholson, J, Tang, H, Chan, Q, Elliott, P & Wilson, I (2004) Ethyl glucoside in human urine following dietary exposure: detection by 1 H NMR spectroscopy as a result of metabonomic screening in humans. Analyst 129, 259–264.Google Scholar
Trethewey, RN (2004) Metabolite profiling as an aid to metabolic engineering in plants. Curr Opin Plant Biol 7, 196–201.Google Scholar
van Ommen, B (2004) Nutrigenomics: exploiting systems biology in the nutrition and health area. Nutrition 20, 4–8.Google Scholar
Waters, NJ, Holmes, E, Waterfield, CJ, Farrant, RD & Nicholson, JK (2002) NMR and pattern recognition studies on liver extracts and in livers from rats treated with alpha-naphthylisothiocyanate. Biochem Pharmacol 64, 67–77.Google Scholar
Watkins, SM & German, JB (2002) Toward the implantation of metabolomic assessments of human health and nutrition. Curr Opin Biotechnol 13, 512–516.Google Scholar
Watkins, SM, Hammock, BD, Newman, JW & German, JB (2001) Individual metabolism should guide agriculture towards foods for improved health and nutrition. Am J Clin Nutr 74, 283–286.Google Scholar
Watkins, SM, Reifsnyder, PR, Pan, HJ, German, JB & Leiter, EH (2002) Lipid metabolome-wide effects of the PPARγ agonist rosiglitazone. J Lipid Res 43, 1809–1817.Google Scholar
Weckwerth, W (2003) Metabolomics in systems biology. Annu Rev Plant Biol 54, 669–689.Google Scholar
Weckwerth, W & Fiehn, O (2002) Can we discover novel pathways using metabolomic analysis?. Curr Opin Biotechnol 13, 156–160.Google Scholar
Weckwerth, W, Loureiro, ME, Wenzel, K & Fiehn, O (2004) Differential metabolic networks unravel the effects of silent plant phenotypes. Proc Natl Acad Sci USA 101, 7809–7814.Google Scholar