Skip to main content

Metabonomics: Analytical Techniques and Associated Chemometrics at a Glance

  • Protocol
  • First Online:
Metabonomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1277))

Abstract

Without any prior knowledge, it can be an overwhelming task to get an overview of and insight into the field of metabonomics. This chapter introduces the concept of metabonomics, the most commonly applied techniques, and the inevitably indispensable multivariate statistical analyses in an easily digestible yet comprehensive manner.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

References

  1. Williams RJ (1951) Individual metabolic patterns and human disease: an exploratory study utilizing predominantly paper chromatographic methods. Biochem Inst Stud (Texas Univ Publ) 4:7–20

    Google Scholar 

  2. Horning EC, Horning MG (1970) Metabolic profiles: chromatographic methods for isolation and characterization of a variety of metabolites in man. Methods Med Res 12:369–371

    CAS  PubMed  Google Scholar 

  3. Hoult DI, Busby SJ, Gadian DG et al (1974) Observation of tissue metabolites using 31P nuclear magnetic resonance. Nature 252:285–287

    Article  CAS  PubMed  Google Scholar 

  4. Gartland KP, Sanins SM, Nicholson JK et al (1990) Pattern recognition analysis of high resolution 1H NMR spectra of urine. A nonlinear mapping approach to the classification of toxicological data. NMR Biomed 3:166–172

    Article  CAS  PubMed  Google Scholar 

  5. Gartland KP, Beddell CR, Lindon JC et al (1991) Application of pattern recognition methods to the analysis and classification of toxicological data derived from proton nuclear magnetic resonance spectroscopy of urine. Mol Pharmacol 39:629–642

    CAS  PubMed  Google Scholar 

  6. 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

    Article  CAS  PubMed  Google Scholar 

  7. Oliver SG, Winson MK, Kell DB et al (1998) Systematic functional analysis of the yeast genome. Trends Biotechnol 16:373–378

    Article  CAS  PubMed  Google Scholar 

  8. Pearson H (2007) Meet the human metabolome. Nature 446:8

    Article  CAS  PubMed  Google Scholar 

  9. Wishart DS, Jewison T, Guo AC et al (2013) HMDB 3.0–The human metabolome database in 2013. Nucleic Acids Res 41:D801–D807

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  10. Haug K, Salek RM, Conesa P et al (2013) MetaboLights–an open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res 41:D781–D786

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Fiehn O, Robertson D, Griffin J et al (2007) The metabolomics standards initiative (MSI). Metabolomics 3:175–178

    Article  CAS  Google Scholar 

  12. Emwas A-HM, Salek RM, Griffin JL et al (2013) NMR-based metabolomics in human disease diagnosis: applications, limitations, and recommendations. Metabolomics 9:1048–1072

    Article  CAS  Google Scholar 

  13. Gika HG, Theodoridis GA, Plumb RS et al (2014) Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics. J Pharm Biomed Anal 87:12–25

    Article  CAS  PubMed  Google Scholar 

  14. Cauchi M, Fowler DP, Walton C et al (2014) Application of gas chromatography mass spectrometry (GC–MS) in conjunction with multivariate classification for the diagnosis of gastrointestinal diseases. Metabolomics. doi:10.1007/s11306-014-0650-1

    Google Scholar 

  15. Wang X, Li K, Adams E et al (2013) Capillary electrophoresis-mass spectrometry in metabolomics: the potential for driving drug discovery and development. Curr Drug Metab 14:807–813

    Article  CAS  PubMed  Google Scholar 

  16. Bjerrum JT, Nielsen OH, Wang YL et al (2008) Technology insight: metabonomics in gastroenterology-basic principles and potential clinical applications. Nat Clin Pract Gastroenterol Hepatol 5:332–343

    Article  PubMed  Google Scholar 

  17. Bjerrum JT, Wang Y, Hao F et al (2014) Metabonomics of human fecal extracts characterize ulcerative colitis, Crohn’s disease and healthy individuals. Metabolomics. doi:10.1007/s11306-014-0677-3

    Google Scholar 

  18. Bjerrum JT, Rantalainen M, Wang Y et al (2014) Integration of transcriptomics and metabonomics: improving diagnostics, biomarker identification and phenotyping in ulcerative colitis. Metabolomics 10:280–290

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Bjerrum JT, Nielsen OH, Hao F et al (2010) Metabonomics in ulcerative colitis: diagnostics, biomarker identification, and insight into the pathophysiology. J Proteome Res 9:954–962

    Article  CAS  PubMed  Google Scholar 

  20. Creek DJ, Dunn WB, Fiehn O et al (2014) Metabolite identification: are you sure? And how do your peers gauge your confidence? Metabolomics. doi:10.1007/s11306-014-0656-8

    Google Scholar 

  21. Ramirez T, Daneshian M, Kamp H et al (2013) Metabolomics in toxicology and preclinical research. ALTEX 30:209–225

    Article  PubMed Central  PubMed  Google Scholar 

  22. Roux A, Lison D, Junot C et al (2011) Applications of liquid chromatography coupled to mass spectrometry-based metabolomics in clinical chemistry and toxicology: a review. Clin Biochem 44:119–135

    Article  CAS  PubMed  Google Scholar 

  23. Macomber RS (1998) A complete introduction to modern NMR spectroscopy. Wiley, New York

    Google Scholar 

  24. Huang Y, Cai S, Zhang Z et al (2014) High-resolution two-dimensional J-resolved NMR spectroscopy for biological systems. Biophys J 106:2061–2070

    Article  CAS  PubMed  Google Scholar 

  25. Glanzer S, Zangger K (2014) Directly decoupled diffusion-ordered NMR spectroscopy for the analysis of compound mixtures. Chemistry. doi:10.1002/chem.201402920

    PubMed  Google Scholar 

  26. Xi Y, de Ropp JS, Viant MR et al (2006) Automated screening for metabolites in complex mixtures using 2D COSY NMR spectroscopy. Metabolomics 2:221–233

    Article  CAS  Google Scholar 

  27. Sandusky P, Raftery D (2005) Use of selective TOCSY NMR experiments for quantifying minor components in complex mixtures: application to the metabonomics of amino acids in honey. Anal Chem 77:2455–2463

    Article  CAS  PubMed  Google Scholar 

  28. Meier S, Beeren SR (2014) Simultaneous determination of binding constants for multiple carbohydrate hosts in complex mixtures. J Am Chem Soc 136(32):11284–12847

    Article  CAS  PubMed  Google Scholar 

  29. Parella T, Espinosa JF (2013) Long-range proton-carbon coupling constants: NMR methods and applications. Prog Nucl Magn Reson Spectrosc 73:17–55

    Article  CAS  PubMed  Google Scholar 

  30. Furrer J (2012) A comprehensive discussion of HMBC pulse sequences. 2. Some useful variants. Concepts Magn Reson 40:146–169

    Article  Google Scholar 

  31. Furrer J (2012) A comprehensive discussion of hmbc pulse sequences, part 1: the classical HMBC. Concepts Magn Reson 40:101–127

    Article  Google Scholar 

  32. Jeannerat D, Furrer J (2012) NMR experiments for the analysis of mixtures: beyond 1D 1H spectra. Comb Chem High Throughput Screen 15:15–35

    Article  CAS  PubMed  Google Scholar 

  33. Gruetter R, Weisdorf SA, Rajanayagan V et al (1998) Resolution improvements in in vivo 1H NMR spectra with increased magnetic field strength. J Magn Reson 135:260–264

    Article  CAS  PubMed  Google Scholar 

  34. Grimes JH, O’Connell TM (2011) The application of micro-coil NMR probe technology to metabolomics of urine and serum. J Biomol NMR 49:297–305

    Article  CAS  PubMed  Google Scholar 

  35. Keun HC, Ebbels TMD, Antti H et al (2002) Analytical reproducibility in (1)H NMR-based metabonomic urinalysis. Chem Res Toxicol 15:1380–1386

    Article  CAS  PubMed  Google Scholar 

  36. Borgan E, Sitter B, Lingjærde OC et al (2010) Merging transcriptomics and metabolomics–advances in breast cancer profiling. BMC Cancer 10628

    Google Scholar 

  37. Bhardwaj C, Hanley L (2014) Ion sources for mass spectrometric identification and imaging of molecular species. Nat Prod Rep 31:756–767

    Article  CAS  PubMed  Google Scholar 

  38. Forcisi S, Moritz F, Kanawati B et al (2013) Liquid chromatography-mass spectrometry in metabolomics research: mass analyzers in ultra high pressure liquid chromatography coupling. J Chromatogr A 1292:51–65

    Article  CAS  PubMed  Google Scholar 

  39. Becker S, Kortz L, Helmschrodt C et al (2012) LC-MS-based metabolomics in the clinical laboratory. J Chromatogr B Analyt Technol Biomed Life Sci 883–884:68–75

    Article  PubMed  Google Scholar 

  40. Denoroy L, Zimmer L, Renaud B et al (2013) Ultra high performance liquid chromatography as a tool for the discovery and the analysis of biomarkers of diseases: a review. J Chromatogr B Analyt Technol Biomed Life Sci 927:37–53

    Article  CAS  PubMed  Google Scholar 

  41. Tsugawa H, Bamba T, Shinohara M et al (2011) Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis. J Biosci Bioeng 112:292–298

    Article  CAS  PubMed  Google Scholar 

  42. Volpi N, Maccari F (2013) Capillary electrophoresis of biomolecules. Springer, New York

    Book  Google Scholar 

  43. Eriksson L, Andersson PL, Johansson E et al (2006) Megavariate analysis of environmental QSAR data. Part I–a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD). Mol Divers 10:169–186

    Article  CAS  PubMed  Google Scholar 

  44. Bylesjö M, Rantalainen M, Cloarec O et al (2006) OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification. J Chemometrics 20:341–351

    Article  Google Scholar 

  45. Trygg J, Wold S (2002) Orthogonal projections to latent structures (O-PLS). J Chemometrics 16:119–128

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jacob T. Bjerrum .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this protocol

Cite this protocol

Bjerrum, J.T. (2015). Metabonomics: Analytical Techniques and Associated Chemometrics at a Glance. In: Bjerrum, J. (eds) Metabonomics. Methods in Molecular Biology, vol 1277. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2377-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2377-9_1

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-2376-2

  • Online ISBN: 978-1-4939-2377-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics