Metabolomics

, Volume 8, Issue 1, pp 8–18 | Cite as

Birmingham Metabolite Library: a publicly accessible database of 1-D 1H and 2-D 1H J-resolved NMR spectra of authentic metabolite standards (BML-NMR)

  • Christian Ludwig
  • John M. Easton
  • Alessia Lodi
  • Stefano Tiziani
  • Susan E. Manzoor
  • Andrew D. Southam
  • Jonathan J. Byrne
  • Lisa M. Bishop
  • Shan He
  • Theodoros N. Arvanitis
  • Ulrich L. Günther
  • Mark R. Viant
Original Article

Abstract

Public databases of NMR spectra of low molecular weight metabolites must be constructed to remove the major bottleneck of metabolite identification and quantification in the analysis of metabolomics data. Two-dimensional (2-D) 1H J-resolved spectroscopy represents a popular alternative to 1-D NMR methods, resolving the highly overlapped signals characteristic of complex metabolite mixtures across two frequency dimensions. Here we report the design, measurement and curation of, primarily, a database of 2-D J-resolved NMR spectra. Metabolites were selected based upon their importance within metabolic pathways and their detection potential by NMR, and prepared for analysis at pH 6.6, 7.0 and 7.4. Sixteen NMR spectra were recorded for each metabolite using a 500 MHz spectrometer, including 1-D and 2-D J-resolved spectra, different water suppression methods and different acquisition parameters. Some metabolites were removed due to limited solubility, poor NMR signal quality or contamination, and the final dataset comprised of 3328 NMR spectra arising from 208 metabolite standards. These data are housed in a purpose-built MySQL database (Birmingham Metabolite Library; BML-NMR) containing over 100 separate tables and allowing the efficient storage of raw free-induction-decays (FIDs), 1-D and 2-D NMR spectra and associated metadata. The database is compliant with the Metabolomics Standards Initiative (MSI) endorsed reporting requirements, with some necessary amendments. Library data can be accessed freely and searched through a custom written web interface (www.bml-nmr.org). FIDs, NMR spectra and associated metadata can be downloaded according to a newly implemented MSI-compatible XML schema.

Keywords

Metabolite database Metabolomics database Metabolic pathway Downloadable 

Supplementary material

11306_2011_347_MOESM1_ESM.zip (76 kb)
Supplementary material 1 (ZIP 76 kb)

References

  1. Aue, W. P., Karhan, J., & Ernst, R. R. (1976). Homonuclear broad-band decoupling and 2-dimensional J-resolved NMR spectroscopy. Journal of Chemical Physics, 64, 4226–4227.CrossRefGoogle Scholar
  2. Braun, S., Kalinowski, H. O., & Berger, S. (1998). 150 and more basic NMR experiments. Weinheim: Wiley VCH.Google Scholar
  3. Cui, Q., Lewis, I. A., Hegeman, A. D., et al. (2008). Metabolite identification via the Madison Metabolomics Consortium Database. Nature Biotechnology, 26, 162–164.PubMedCrossRefGoogle Scholar
  4. Fiehn, O., Robertson, D., Griffin, J., et al. (2007). The metabolomics standards initiative (MSI). Metabolomics, 3, 175–178.CrossRefGoogle Scholar
  5. Foxall, P. J. D., Parkinson, J. A., Sadler, I. H., Lindon, J. C., & Nicholson, J. K. (1993). Analysis of biological fluids using 600 MHz proton NMR spectroscopy—application of homonuclear 2-dimensional J-resolved spectroscopy to urine and blood plasma for spectral simplification and assignment. Journal of Pharmaceutical and Biomedical, 11, 21–31.CrossRefGoogle Scholar
  6. Hines, A., Oladiran, G. S., Bignell, J. P., Stentiford, G. D., & Viant, M. R. (2007). Direct sampling of organisms from the field and knowledge of their phenotype: Key recommendations for environmental metabolomics. Environmental Science and Technology, 41, 3375–3381.PubMedCrossRefGoogle Scholar
  7. Hwang, T. L., & Shaka, A. J. (1995). Water suppression that works—excitation sculpting using arbitrary wave-forms and pulsed-field gradients. Journal of Magnetic Resonance, Series A, 112, 275–279.CrossRefGoogle Scholar
  8. Kanehisa, M., Goto, S., Hattori, M., et al. (2006). From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Research, 34, D354–D357.PubMedCrossRefGoogle Scholar
  9. Ludwig, C., & Viant, M. R. (2010). Two-dimensional J-resolved NMR spectroscopy: Review of a key methodology in the metabolomics toolbox. Phytochemical Analysis, 21, 22–32.PubMedCrossRefGoogle Scholar
  10. Lutz, N. W., Maillet, S., Nicoli, F., Viout, P., & Cozzone, P. J. (1998). Further assignment of resonances in H-1 NMR spectra of cerebrospinal fluid (CSF). FEBS Letters, 425, 345–351.PubMedCrossRefGoogle Scholar
  11. Moore, G. J., & Sillerud, L. O. (1994). The pH-dependence of chemical-shift and spin–spin coupling for citrate. Journal of Magnetic Resonance Series B, 103, 87–88.PubMedCrossRefGoogle Scholar
  12. Nicholson, J. K., Foxall, P. J. D., Spraul, M., Farrant, R. D., & Lindon, J. C. (1995). 750 MHz H-1 and H-1-C-13 NMR spectroscopy of human blood plasma. Analytical Chemistry, 67, 793–811.PubMedCrossRefGoogle Scholar
  13. Parsons, H. M., Ludwig, C., Günther, U. L., & Viant, M. R. (2007). Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation. BMC Bioinformatics, 8, 234.PubMedCrossRefGoogle Scholar
  14. Parsons, H. M., Ludwig, C., & Viant, M. R. (2009). Line-shape analysis of J-resolved NMR spectra: Application to metabolomics and quantification of intensity errors from signal processing and high signal congestion. Magnetic Resonance in Chemistry, 47, S86–S95.PubMedCrossRefGoogle Scholar
  15. Pence, H. E., & Williams, A. (2010). ChemSpider: An online chemical information resource. Journal of Chemical Education, 87, 1123–1124.CrossRefGoogle Scholar
  16. Rubtsov, D. V., Jenkins, H., Ludwig, C., et al. (2007). Proposed reporting requirements for the description of NMR-based metabolomics experiments. Metabolomics, 3, 223–229.CrossRefGoogle Scholar
  17. Sumner, L. W., Amberg, A., Barrett, D., et al. (2007). Proposed minimum reporting standards for chemical analysis. Metabolomics, 3, 211–221.CrossRefGoogle Scholar
  18. Thrippleton, M. J., Edden, R. A. E., & Keeler, J. (2005). Suppression of strong coupling artefacts in J-spectra. Journal of Magnetic Resonance, 174, 97–109.PubMedCrossRefGoogle Scholar
  19. Tiziani, S., Lodi, A., Ludwig, C., Parsons, H. M., & Viant, M. R. (2008). Effects of the application of different window functions and projection methods on processing of H-1J-resolved nuclear magnetic resonance spectra for metabolomics. Analytica Chimica Acta, 610, 80–88.PubMedCrossRefGoogle Scholar
  20. Viant, M. R. (2003). Improved methods for the acquisition and interpretation of NMR metabolomic data. Biochemical and Biophysics Research Communication, 310, 943–948.CrossRefGoogle Scholar
  21. Wang, Y. L., Bollard, M. E., Keun, H., et al. (2003). Spectral editing and pattern recognition methods applied to high-resolution magic-angle spinning H-1 nuclear magnetic resonance spectroscopy of liver tissues. Analytical Biochemistry, 323, 26–32.PubMedCrossRefGoogle Scholar
  22. Wishart, D. S., Tzur, D., Knox, C., et al. (2007). HMDB: The human metabolome database. Nucleic Acids Research, 35, D521–D526.PubMedCrossRefGoogle Scholar
  23. Xi, Y. X., de Ropp, J. S., Viant, M. R., Woodruff, D. L., & Yu, P. (2006). Automated screening for metabolites in complex mixtures using 2D COSY NMR spectroscopy. Metabolomics, 2, 221–233.CrossRefGoogle Scholar
  24. Yang, W. J., Wang, Y. W., Zhou, Q. F., & Tang, H. R. (2008). Analysis of human urine metabolites using SPE and NMR spectroscopy. Science in China Series B: Chemistry, 51, 218–225.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Christian Ludwig
    • 1
  • John M. Easton
    • 2
  • Alessia Lodi
    • 1
  • Stefano Tiziani
    • 1
  • Susan E. Manzoor
    • 3
  • Andrew D. Southam
    • 3
  • Jonathan J. Byrne
    • 4
  • Lisa M. Bishop
    • 4
  • Shan He
    • 5
  • Theodoros N. Arvanitis
    • 2
  • Ulrich L. Günther
    • 1
  • Mark R. Viant
    • 3
    • 4
  1. 1.The Henry Wellcome Building for Biomolecular NMR Spectroscopy, School of Cancer SciencesUniversity of BirminghamBirminghamUK
  2. 2.School of Electronic, Electrical & Computer EngineeringUniversity of BirminghamBirminghamUK
  3. 3.School of BiosciencesUniversity of BirminghamBirminghamUK
  4. 4.NERC Biomolecular Analysis Facility—Metabolomics Node (NBAF-B)University of BirminghamBirminghamUK
  5. 5.School of Computer ScienceUniversity of BirminghamBirminghamUK

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