, Volume 2, Issue 4, pp 221–233 | Cite as

Automated screening for metabolites in complex mixtures using 2D COSY NMR spectroscopy

  • Yuanxin Xi
  • Jeffrey S. de Ropp
  • Mark R. Viant
  • David L. Woodruff
  • Ping Yu


One of the greatest challenges in metabolomics is the rapid and unambiguous identification and quantification of metabolites in a biological sample. Although one-dimensional (1D) proton nuclear magnetic resonance (NMR) spectra can be acquired rapidly, they are complicated by severe peak overlap that can significantly hinder the automated identification and quantification of metabolites. Furthermore, it is currently not reasonable to assume that NMR spectra of pure metabolites are available a priori for every metabolite in a biological sample. In this paper we develop and report on tests of methods that assist in the automatic identification of metabolites using proton two-dimensional (2D) correlation spectroscopy (COSY) NMR. Given a database of 2D COSY spectra for the metabolites of interest, our methods provide a list sorted by a heuristic likelihood of the metabolites present in a sample that has been analyzed using 2D COSY NMR. Our models attempt to correct the displacement of the peaks that can occur from one sample to the next, due to pH, temperature and matrix effects, using a statistical and chemical model. The correction of one peak can result in an implied correction of others due to spin–spin coupling. Furthermore, these displacements are not independent: they depend on the relative position of functional groups in the molecule. We report experimental results using defined mixtures of amino acids as well as real complex biological samples that demonstrate that our methods can be very effective at automatically and rapidly identifying metabolites.


metabolomics metabolite identification 2D COSY NMR pH 



This publication was made possible in part by grant number 5 P42 ES04699 from the National Institute of Environmental Health Sciences, NIH. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS, NIH. MRV thanks the Natural Environment Research Council, UK, for the award of an Advanced Fellowship (NER/J/S/2002/00618). The authors are indebted to Chenomx for the use of their NMR Suite software.


  1. Aue W.P., Bartholdi E., Ernst R.R. (1975) Two-dimensional spectroscopy. Application to nuclear magnetic resonance. J. Chem. Phys. 64:2229–2246CrossRefGoogle Scholar
  2. Croasmun W.R., Carlson R.M.K. (Eds) (1994). Two-Dimensional NMR Spectroscopy, 2nd Ed. VCH Publishers, Inc. New YorkGoogle Scholar
  3. Dancea F., Gunther U.L. (2005). Automated protein NMR structure determination using wavelet de-noised NOESY spectra. J. Biomol. NMR 33:139–152PubMedCrossRefGoogle Scholar
  4. Dunn W.B. and Ellis D.I. (2005) Metabolomics: Current analytical platforms and methodologies. Trends Anal. Chem. 24:285–294CrossRefGoogle Scholar
  5. Fan W.M.T. (1996) Metabolite profiling by one- and two-dimensional NMR analysis of complex mixtures. Prog. Nucl. Magn. Reson. 28:161–219Google Scholar
  6. Forshed J., Schuppe-Koistinen I., Jacobsson S.P. (2003) Peak alignment of NMR signals by means of a genetic algorithm. Anal. Chim. Acta 487:189–199CrossRefGoogle Scholar
  7. Griffin J.L. (2003) Metabonomics: NMR spectroscopy and pattern recognition analysis of body fluids and tissues for characterisation of xenobiotic toxicity and disease diagnosis. Curr. Opin. Chem. Biol. 7:648–654PubMedCrossRefGoogle Scholar
  8. Holmes E., Nicholls A.W., Lindon J.C., Connor S.C., Connelly J.C., Haselden J.N., Damment S.J.P., Spraul M., Neidig P., Nicholson J.K. (2000) Chemometric Models for Toxicity Classification Based on NMR Spectra of Biofluids. Chem. Res. Toxicol. 13:471–478PubMedCrossRefGoogle Scholar
  9. Hurd R.E. (1990) Gradient-enhanced spectroscopy. J. Magn. Reson. 87:422–428Google Scholar
  10. Jardetzky, O. and Roberts, G.C.K. (1981) NMR in Molecular Biology. Academic Press, Inc., Orlando, Florida, Chapter 5Google Scholar
  11. Kell D.B. (2004) Metabolomics and systems biology: making sense of the soup. Curr. Opin. Microbiol. 7:296–307PubMedCrossRefGoogle Scholar
  12. Lee G.-C., Woodruff D.L. (2004) Beam search for peak alignment of NMR signals. Anal. Chim. Acta 513:413–416CrossRefGoogle Scholar
  13. Lindon J.C., Nicholson J.K., Holmes E., Everett J.R. (2000) Metabonomics: Metabolic processes studied by NMR spectroscopy of biofluids. Concept Magn. Reson. 12:289–320CrossRefGoogle Scholar
  14. Lindon J.C., Holmes E., Nicholson J.K. (2004). Toxicological applications of magnetic resonance. Prog. Nucl. Magn. Reson. Spect. 45:109–143CrossRefGoogle Scholar
  15. Mannina L., Cristinzio M., Sobolev A.P., Ragni P., Segre A. (2004) High-field nuclear magnetic resonance (NMR) study of truffles (Tuber aestivum vittadini). J. Ag. Food Chem. 52:7988–7996CrossRefGoogle Scholar
  16. Moore G.J., Sillerud L.O. (1994) The pH Dependence of Chemical Shift and Spin–Spin Coupling for Citrate, J. Magn. Reson. B 103:87–88CrossRefGoogle Scholar
  17. Nicholson J.K. Connelly J., Lindon J.C., Holmes E. (2002) Metabonomics: A platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov. 1:153–161PubMedCrossRefGoogle Scholar
  18. 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. 77:2455–2463PubMedCrossRefGoogle Scholar
  19. Sobolev A.P., Brosio E., Gianferri R., Segre A.L. (2005) Metabolic profile of lettuce leaves by high-field NMR spectra. Magn. Reson. Chem. 43:625–638PubMedCrossRefGoogle Scholar
  20. Stoyanova R., Nicholls A.W., Nicholson J.K., Lindon J.C., Brown T.R. (2004) Automatic alignment of individual peaks in large high-resolution spectral data set. J. Magn. Reson. 170:329–355PubMedCrossRefGoogle Scholar
  21. Tang H.R., Wang Y.L., Nicholson J.K., Lindon J.C. (2004) Use of relaxation-edited one-dimensional and two dimensional nuclear magnetic resonance spectroscopy to improve detection of small metabolites in blood plasma. Anal. Biochem. 325:260–272PubMedCrossRefGoogle Scholar
  22. Viant M.R. (2003) Improved methods for the acquisition and interpretation of NMR metabolomic data. Biochem. Biophys. Res. Comm. 310:943–948PubMedCrossRefGoogle Scholar
  23. Viant M.R., Rosenblum E.S., Tjeerdema R.S. (2003) NMR-based metabolomics: A powerful approach for characterizing the effects of environmental stressors on organism health. Environ. Sci. Technol. 37:4982–4989PubMedCrossRefGoogle Scholar
  24. Wan, X., Xu, D., Slupsky, C. M., and Lin, G. (2003) Automated NMR Resonance Assignments, Proceedings of the Computational Systems Bioinformatics (CSB’03), IEEEGoogle Scholar
  25. Wuthrich K. (1976) NMR in Biological Research: Peptides and Proteins. North-Holland Publishing Company, AmsterdamGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  • Yuanxin Xi
    • 1
  • Jeffrey S. de Ropp
    • 2
  • Mark R. Viant
    • 3
  • David L. Woodruff
    • 4
  • Ping Yu
    • 2
  1. 1.Department of Applied ScienceUniversity of CaliforniaDavisUSA
  2. 2.NMR FacilityUniversity of CaliforniaDavisUSA
  3. 3.School of BiosciencesThe University of BirminghamEdgbastonUK
  4. 4.Institute for Data Analysis and Visualization and Graduate School of ManagementUniversity of CaliforniaDavisUSA

Personalised recommendations