Skip to main content
SpringerLink
Log in

Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

With unmatched mass resolution, mass accuracy, and exceptional detection sensitivity, Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) has the potential to be a powerful new technique for high-throughput metabolomic analysis. In this study, we examine the properties of an ultrahigh-field 12-Tesla (12T) FTICR-MS for the identification and absolute quantitation of human plasma metabolites, and for the untargeted metabolic fingerprinting of inbred-strain mouse serum by direct infusion (DI). Using internal mass calibration (mass error ≤1 ppm), we determined the rational elemental compositions (incorporating unlimited C, H, N and O, and a maximum of two S, three P, two Na, and one K per formula) of approximately 250 out of 570 metabolite features detected in a 3-min infusion analysis of aqueous extract of human plasma, and were able to identify more than 100 metabolites. Using isotopically-labeled internal standards, we were able to obtain excellent calibration curves for the absolute quantitation of choline with sub-pmol sensitivity, using 500 times less sample than previous LC/MS analyses. Under optimized serum dilution conditions, chemical compounds spiked into mouse serum as metabolite mimics showed a linear response over a 600-fold concentration range. DI/FTICR-MS analysis of serum from 26 mice from 2 inbred strains, with and without acute trichloroethylene (TCE) treatment, gave a relative standard deviation (RSD) of 4.5%. Finally, we extended this method to the metabolomic fingerprinting of serum samples from 49 mice from 5 inbred strains involved in an acute alcohol toxicity study, using both positive and negative electrospray ionization (ESI). Using these samples, we demonstrated the utility of this method for high-throughput metabolomics, with more than 400 metabolites profiled in only 24 h. Our experiments demonstrate that DI/FTICR-MS is well-suited for high-throughput metabolomic analysis.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Aharoni, A., Ric de Vos, C. H., Verhoeven, H. A., Maliepaard, C. A., Kruppa, G., Bino, R., Goodenowe, D. B. (2002). Nontargeted metabolome analysis by use of Fourier transform ion cyclotron mass spectrometry, Omics, 6(3), 217–234.

    Article  PubMed  CAS  Google Scholar 

  • Allen, J., Davey, H. M., Broadhurst, D., Heald, J. K., Rowland, J. J., Oliver, S. G., Kell, D. B. (2003). High-throughput classification of yeast mutants for functional genomics using metabolic footprinting, Nature Biotechnology, 21(6), 692–696.

    Article  PubMed  CAS  Google Scholar 

  • Belov, M. E., Anderson, G. A., Angell, N. H., Shen, Y., Tolic, N., Udseth, H. R., Smith, R. D. (2001). Dynamic range expansion applied to mass spectrometry based on data-dependent selective ion ejection in capillary liquid chromatography Fourier transform ion cyclotron resonance for enhanced proteome characterization, Analytical Chemistry, 73(21), 5052–5060.

    Article  PubMed  CAS  Google Scholar 

  • Brown, S. C., Kruppa, G., Dasseux, J. L. (2005). Metabolomics applications of FT-ICR mass spectrometry, Mass Spectrometry Reviews, 24(2), 223–231.

    Article  PubMed  CAS  Google Scholar 

  • Buchholz, A., Takors, R., Wandrey, C., (2001). Quantification of intracellular metabolites in Escherichia coli K12 using liquid chromatographic-electrospray ionization tandem mass spectrometric techniques, Analytical Biochemistry, 295(2), 129–137.

    Article  PubMed  CAS  Google Scholar 

  • De Vos, R. C., Moco, S., Lommen, A., Keurentjes, J. J., Bino, R. J., Hall, R. D. (2007). Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry, Nature Protocols, 2(4), 778–791.

    Article  PubMed  CAS  Google Scholar 

  • Denkert, C., Budczies, J., Kind, T., Weichert, W., Tablack, P., Sehouli, J., Niesporek, S., Konsgen, D., Dietel, M., Fiehn, O., (2006). Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors, Cancer Research, 66(22), 10795–10804.

    Article  PubMed  CAS  Google Scholar 

  • Dunn, W. B., Bailey, N. J., Johnson, H. E. (2005). Measuring the metabolome: Current analytical technologies, Analyst, 130(5), 606–625.

    Article  PubMed  CAS  Google Scholar 

  • Eisen, M. B., Spellman, P. T., Brown, P. O., Botstein, D., (1998). Cluster analysis and display of genome-wide expression patterns, Proceedings of the National Academy of Sciences, 95(25), 14863–14868.

    Article  CAS  Google Scholar 

  • Fahy, E., Sud, M., Cotter, D., Subramaniam, S., (2007). LIPID MAPS online tools for lipid research, Nucleic Acids Research, 35(Web Server issue), W606–W612.

    Article  PubMed  Google Scholar 

  • Fan, T. W., Lane, A. N., Higashi, R. M. (2004). The promise of metabolomics in cancer molecular therapeutics, Current Opinion in Molecular Therapeutics, 6(6), 584–592.

    PubMed  Google Scholar 

  • Fiehn, O., Kloska, S., Altmann, T., (2001). Integrated studies on plant biology using multiparallel techniques, Current Opinion in Biotechnology, 12(1), 82–86.

    Article  PubMed  CAS  Google Scholar 

  • Galinski, E. A. (1995). Osmoadaptation in bacteria, Advances in Microbial Physiology, 37, 272–328.

    Article  PubMed  CAS  Google Scholar 

  • Gamache, P. H., Meyer, D. F., Granger, M. C., Acworth, I. N. (2004). Metabolomic applications of electrochemistry/mass spectrometry, American Society for Mass Spectrometry, 15(12), 1717–1726.

    Article  CAS  Google Scholar 

  • Goodacre, R., Vaidyanathan, S., Dunn, W. B., Harrigan, G. G., Kell, D. B. (2004). Metabolomics by numbers: Acquiring and understanding global metabolite data, Trends in Biotechnology, 22(5), 245–252.

    Article  PubMed  CAS  Google Scholar 

  • Halket, J. M., Przyborowska, A., Stein, S. E., Mallard, W. G., Down, S., Chalmers, R. A. (1999). Deconvolution gas chromatography/mass spectrometry of urinary organic acids–potential for pattern recognition and automated identification of metabolic disorders, Rapid Communications in Mass Spectrometry, 13(4), 279–284.

    Article  PubMed  CAS  Google Scholar 

  • Hirai, M. Y., Yano, M., Goodenowe, D. B., Kanaya, S., Kimura, T., Awazuhara, M., Arita, M., Fujiwara, T., Saito, K., (2004). Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana, Proceedings of the National Academy of Sciences, 101(27), 10205–10210.

    Article  CAS  Google Scholar 

  • Hughey, C. A., Rodgers, R. P., Marshall, A. G. (2002). Resolution of 11,000 compositionally distinct components in a single electrospray ionization Fourier transform ion cyclotron resonance mass spectrum of crude oil, Analytical Chemistry, 74(16), 4145–4149.

    Article  PubMed  CAS  Google Scholar 

  • Jones, O. A., Spurgeon, D. J., Svendsen, C., Griffin, J. L. (2007). A metabolomics based approach to assessing the toxicity of the polyaromatic hydrocarbon pyrene to the earthworm Lumbricus rubellus. Chemosphere [Epub ahead of print].

  • Kind, T., Fiehn, O., (2006). Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm, BMC Bioinformatics, 7, 234.

    Article  PubMed  CAS  Google Scholar 

  • Kind, T., Fiehn, O., (2007). Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry, BMC Bioinformatics, 8, 105.

    Article  PubMed  CAS  Google Scholar 

  • Koc, H., Mar, M. H., Ranasinghe, A., Swenberg, J. A., Zeisel, S. H. (2002). Quantitation of choline and its metabolites in tissues and foods by liquid chromatography/electrospray ionization-isotope dilution mass spectrometry, Analytical Chemistry, 74(18), 4734–4740.

    Article  PubMed  CAS  Google Scholar 

  • Kolch, W., Mischak, H., Pitt, A. R. (2005). The molecular make-up of a tumour: Proteomics in cancer research, Clinical Science (London), 108(5), 369–383.

    CAS  Google Scholar 

  • Lee, S. H., Woo, H. M., Jung, B. H., Lee, J., Kwon, O. S., Pyo, H. S., Choi, M. H., Chung, B. C. (2007). Metabolomic approach to evaluate the toxicological effects of nonylphenol with rat urine, Analytical Chemistry, 79(16), 6102–6110.

    Article  PubMed  CAS  Google Scholar 

  • Marshall, A. G., Hendrickson, C. L., Shi, S. D. (2002). Scaling MS plateaus with high-resolution FT-ICRMS, Analytical Chemistry, 74(9), 252A–259A.

    Article  PubMed  CAS  Google Scholar 

  • Nakamura, Y., Kimura, A., Saga, H., Oikawa, A., Shinbo, Y., Kai, K., Sakurai, N., Suzuki, H., Kitayama, M., Shibata, D., Kanaya, S., & Ohta, D., (2007). Differential metabolomics unraveling light/dark regulation of metabolic activities in Arabidopsis cell culture. Planta, 227(1), 57–66.

    Article  PubMed  CAS  Google Scholar 

  • Neubauer, O., (1901). Archiv, Fur Experimentelle Pathologie und Pharmakologie, 46, 133–154.

    Article  Google Scholar 

  • Nicholson, J. K., Lindon, J. C., 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(11), 1181–1189.

    Article  PubMed  CAS  Google Scholar 

  • Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., Kanehisa, M., (1999). KEGG: Kyoto Encyclopedia of Genes and Genomes, Nucleic Acids Research, 27(1), 29–34.

    Article  PubMed  CAS  Google Scholar 

  • Ohta, D., Shibata, D., Kanaya, S., (2007). Metabolic profiling using Fourier-transform ion-cyclotron-resonance mass spectrometry, Analytical and Bioanalytical Chemistry, 389(5), 1469–1475.

    Article  PubMed  CAS  Google Scholar 

  • Plumb, R., Castro-Perez, J., Granger, J., Beattie, I., Joncour, K., Wright, A., (2004). Ultra-performance liquid chromatography coupled to quadrupole-orthogonal time-of-flight mass spectrometry. Rapid Communications in Mass Spectrometry, 18(19), 2331–2337.

    Article  PubMed  CAS  Google Scholar 

  • Pomfret, E. A., daCosta, K. A., Schurman, L. L., Zeisel, S. H. (1989). Measurement of choline and choline metabolite concentrations using high-pressure liquid chromatography and gas chromatography-mass spectrometry. Analytical Biochemistry, 180(1), 85–90.

    Article  PubMed  CAS  Google Scholar 

  • Saldanha, A. J. (2004). Java Treeview–extensible visualization of microarray data, Bioinformatics, 20(17), 3246–3248.

    Article  PubMed  CAS  Google Scholar 

  • Sato, S., Soga, T., Nishioka, T., Tomita, M., (2004). Simultaneous determination of the main metabolites in rice leaves using capillary electrophoresis mass spectrometry and capillary electrophoresis diode array detection, Plant Journal, 40(1), 151–163.

    Article  PubMed  CAS  Google Scholar 

  • Soga, T., Baran, R., Suematsu, M., Ueno, Y., Ikeda, S., Sakurakawa, T., Kakazu, Y., Ishikawa, T., Robert, M., Nishioka, T., Tomita, M., (2006). Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption, Journal of Biological Chemistry, 281(24), 16768–16776.

    Article  PubMed  CAS  Google Scholar 

  • Southam, A. D., Payne, T. G., Cooper, H. J., Arvanitis, T. N., Viant, M. R. (2007). Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray Fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method, Analytical Chemistry, 79(12), 4595–4602.

    Article  PubMed  CAS  Google Scholar 

  • Staack, R. F., Varesio, E., Hopfgartner, G., (2005). The combination of liquid chromatography/tandem mass spectrometry and chip-based infusion for improved screening and characterization of drug metabolites, Rapid Communications in Mass Spectrometry, 19(5), 618–626.

    Article  PubMed  CAS  Google Scholar 

  • Sud, M., Fahy, E., Cotter, D., Brown, A., Dennis, E. A., Glass, C. K., Merrill, A. H., Jr., Murphy, R. C., Raetz, C. R., Russell, D. W., Subramaniam, S., (2007). LMSD: LIPID MAPS structure database. Nucleic Acids Research, 35(Database issue), D527–D532.

    Article  PubMed  CAS  Google Scholar 

  • Tohge, T., Nishiyama, Y., Hirai, M. Y., Yano, M., Nakajima, J., Awazuhara, M., Inoue, E., Takahashi, H., Goodenowe, D. B., Kitayama, M., Noji, M., Yamazaki, M., Saito, K., (2005). Functional genomics by integrated analysis of metabolome and transcriptome of Arabidopsis plants over-expressing an MYB transcription factor, Plant Journal, 42(2), 218–235.

    Article  PubMed  CAS  Google Scholar 

  • Want, E. J., O’Maille, G., Smith, C. A., Brandon, T. R., Uritboonthai, W., Qin, C., Trauger, S. A., Siuzdak, G., (2006). Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry, Analytical Chemistry, 78(3), 743–752.

    Article  PubMed  CAS  Google Scholar 

  • Wikoff, W. R., Gangoiti, J. A., Barshop, B. A., Siuzdak, G., (2007). Metabolomics identifies perturbations in human disorders of propionate metabolism. Clinical Chemistry. [Epub ahead of print].

  • Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., Fung, C., Nikolai, L., Lewis, M., Coutouly, M. A., Forsythe, I., Tang, P., Shrivastava, S., Jeroncic, K., Stothard, P., Amegbey, G., Block, D., Hau, D. D., Wagner, J., Miniaci, J., Clements, M., Gebremedhin, M., Guo, N., Zhang, Y., Duggan, G. E., Macinnis, G. D., Weljie, A. M., Dowlatabadi, R., Bamforth, F., Clive, D., Greiner, R., Li, L., Marrie, T., Sykes, B. D., Vogel, H. J., Querengesser, L., (2007). HMDB: The human metabolome database. Nucleic Acids Research, 35 (Database issue), D521–D526.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Dr. David Robinette for his assistance with the preparation of the manuscript. This study was partially funded by a gift from an anonymous donor to support research in proteomics at UNC, by NIH grants P30 CA0-16086, 1S10RR16776, caBIG-ICR-07-20-01, R01 AA016258, and P30 Es010126, by collaboration with Bruker Daltonics, and by start-up funds from the University of Victoria. We also acknowledge the use of the 12-Tesla FTICR mass spectrometer at the UNC-Duke Michael Hooker Proteomics Center, NC (NIH 1-S10-RR019889-01 and NCBC 2005-IDG-1015) for some of these experiments.

Author information

Author notes

  1. Cameron O. Scarlett

    Present address: School of Pharmacy, University of Wisconsin, Madison, WI, USA

Authors and Affiliations

  1. University of Victoria – Genome BC Proteomics Centre, Vancouver Island Technology Park, #3101-4464 Markham St., Victoria, BC, Canada, V8Z 7X8

    Jun Han & Christoph H. Borchers

  2. Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina, Chapel Hill, NC, USA

    Jun Han & Ivan Rusyn

  3. Danell Consulting, Greenville, NC, USA

    Ryan M. Danell

  4. Bruker Daltonics Inc., Billerica, MA, USA

    Jayanti R. Patel, Dmitry R. Gumerov & J. Paul Speir

  5. Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC, United States

    Cameron O. Scarlett, Carol E. Parker & Christoph H. Borchers

  6. UNC-Duke Proteomics Center, University of North Carolina, Chapel Hill, NC, USA

    Cameron O. Scarlett, Carol E. Parker & Christoph H. Borchers

  7. Nutrition Research Institute, Department of Nutrition, School of Public Health, University of North Carolina, Chapel Hill, NC, USA

    Steven Zeisel

Authors
  1. Jun Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ryan M. Danell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jayanti R. Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dmitry R. Gumerov
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cameron O. Scarlett
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. J. Paul Speir
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Carol E. Parker
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ivan Rusyn
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Steven Zeisel
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Christoph H. Borchers
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christoph H. Borchers.

Electronic supplementary material

Below is the link to the electronic supplementary material.

11306_2008_104_MOESM1_ESM.doc

Rights and permissions

Reprints and permissions

About this article

Cite this article

Han, J., Danell, R.M., Patel, J.R. et al. Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry. Metabolomics 4, 128–140 (2008). https://doi.org/10.1007/s11306-008-0104-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11306-008-0104-8

Keywords

Search

Navigation