Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry

Nature Protocols volume 2, pages 778–791 (2007)Cite this article

Abstract

Untargeted metabolomics aims to gather information on as many metabolites as possible in biological systems by taking into account all information present in the data sets. Here we describe a detailed protocol for large-scale untargeted metabolomics of plant tissues, based on reversed phase liquid chromatography coupled to high-resolution mass spectrometry (LC-QTOF MS) of aqueous methanol extracts. Dedicated software, MetAlign, is used for automated baseline correction and alignment of all extracted mass peaks across all samples, producing detailed information on the relative abundance of thousands of mass signals representing hundreds of metabolites. Subsequent statistics and bioinformatics tools can be used to provide a detailed view on the differences and similarities between (groups of) samples or to link metabolomics data to other systems biology information, genetic markers and/or specific quality parameters. The complete procedure from metabolite extraction to assembly of a data matrix with aligned mass signal intensities takes about 6 days for 50 samples.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: LC-QTOF MS profiling of crude extracts from three different plant species.
Figure 2: Schematic overview of experimental setup and data flow for untargeted LC-QTOF MS-based metabolomics of plant materials.
Figure 3: Interface of MetAlign software used for untargeted processing of LC-QTOF MS data files.
Figure 4: Timing of standard procedure of untargeted LC-MS analyses, based on 50 Arabidopsis seedling samples and LC-MS analysis time of 1 h.
Figure 5: Stability of the LC-QTOF MS system during 240 h continuous analyses of crude plant extracts (ESI negative mode).
Figure 6: Correlation between conventional LC-PDA analysis and untargeted LC-MS-based metabolomics with regard to detection of the flavonoid rutin (for identification, see Fig.1f).
Figure 7: Hierarchical clustering (Pearson correlation) of 180 A. thaliana genotypes consisting of a recombinant inbred line (RIL) population and their parents, based on untargeted metabolomics data.

Similar content being viewed by others

References

  1. Bino, R.J. et al. Potential of metabolomics as a functional genomics tool. Trends Plant. Sci. 9, 418–425 (2004).

    Article  CAS  Google Scholar 

  2. Hall, R.D. Plant metabolomics: from holistic hope, to hype, to hot topic. New Phytol. 169, 453–468 (2006).

    Article  CAS  Google Scholar 

  3. Jenkins, H. et al. A proposed framework for the description of plant metabolomics experiments and their results. Nat. Biotechnol. 22, 1601–1606 (2004).

    Article  CAS  Google Scholar 

  4. Sumner, L.W., Mendes, P. & Dixon, R.A. Plant metabolomics: large-scale phytochemistry in the functional genomics era. Phytochemistry 62, 817–836 (2003).

    Article  CAS  Google Scholar 

  5. Dixon, R.A. et al. Applications of metabolomics in agriculture. J. Agric. Food Chem. 54, 8984–8994 (2006).

    Article  CAS  Google Scholar 

  6. Trethewey, R.N. Metabolite profiling as an aid to metabolic engineering in plants. Curr. Opin. Plant Biol. 7, 196–201 (2004).

    Article  CAS  Google Scholar 

  7. Saito, K., Dixon, R. & Willmitzer, L. Plant Metabolomics (Springer Verlag, Heidelberg, Germany, 2006).

    Book  Google Scholar 

  8. Vaidyanathan, S., Harrigan, G.G., Goodacre, R. (eds.) Metabolome Analyses: Strategies for Systems Biology (Springer, New York, 2005).

  9. Van der Greef, J., Stroobant, P. & Van der Heijden, R. The role of analytical sciences in medical systems biology. Curr. Opin. Chem. Biol. 8, 559–565 (2004).

    Article  CAS  Google Scholar 

  10. Fernie, A.R. Metabolome characterization in plant system analysis. Funct. Plant Biol. 30, 111–120 (2003).

    Article  CAS  Google Scholar 

  11. Fiehn, O. et al. Metabolite profiling for plant functional genomics. Nat. Biotechnol. 18, 1157–1161 (2000).

    Article  CAS  Google Scholar 

  12. Lisec, J., Schauer, N., Kopka, J., Willmitzer, L. & Fernie, A.R. Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protoc. 1, 1–10 (2006).

    Article  Google Scholar 

  13. Roessner, U. et al. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11–29 (2001).

    Article  CAS  Google Scholar 

  14. Roessner, U., Willmitzer, L. & Fernie, A.R. Metabolic profiling and biochemical phenotyping of plant systems. Plant Cell Rep. 21, 189–196 (2002).

    Article  CAS  Google Scholar 

  15. Schauer, N. et al. GC-MS libraries for the rapid identification of metabolites in complex biological samples. FEBS Lett. 579, 1332–1337 (2005).

    Article  CAS  Google Scholar 

  16. Fiehn, O. et al. Metabolite profiling for plant functional genomics. Nat. Biotechnol. 18, 1157–1161 (2000).

    Article  CAS  Google Scholar 

  17. Aharoni, A. et al. Nontargeted metabolome analysis by use of Fourier transform ion cyclotron mass spectrometry. Omics 6, 217–234 (2002).

    Article  CAS  Google Scholar 

  18. Hirai, M.Y. et al. Elucidation of gene-to-gene and metabolite-to-gene networks in Arabidopsis by integration of metabolomics and transcriptomics. J. Biol. Chem. 280, 25590–25595 (2005).

    Article  CAS  Google Scholar 

  19. Overy, S.A. et al. Application of metabolite profiling to the identification of traits in a population of tomato introgression lines. J. Exp. Bot. 56, 287–296 (2005).

    Article  CAS  Google Scholar 

  20. Goodacre, R., York, E.V., Heald, J.K. & Scott, J.M. Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry. Phytochemistry 62, 859–863 (2003).

    Article  CAS  Google Scholar 

  21. Jander, G. et al. Application of a high-throughput HPLC-MS/MS assay to Arabidopsis mutant screening; evidence that threonine aldolase plays a role in seed nutritional quality. Plant J. 39, 465–475 (2004).

    Article  CAS  Google Scholar 

  22. Moco, S. et al. A liquid chromatography-mass spectrometry-based metabolome database for tomato. Plant Physiol. 141, 1205–1218 (2006).

    Article  CAS  Google Scholar 

  23. Tolstikov, V.V., Lommen, A., Nakanishi, K., Tanaka, N. & Fiehn, O. Monolithic silica-based capillary reversed-phase liquid chromatography/electrospray mass spectrometry for plant metabolomics. Anal. Chem. 75, 6737–6740 (2003).

    Article  CAS  Google Scholar 

  24. von Roepenack-Lahaye, E. et al. Profiling of Arabidopsis secondary metabolites by capillary liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry. Plant Physiol. 134, 548–559 (2004).

    Article  CAS  Google Scholar 

  25. Vorst, O. et al. A non-directed approach to the differential analysis of multiple LC-MS-derived metabolic profiles. Metabolomics 1, 169–180 (2005).

    Article  CAS  Google Scholar 

  26. Rischer, H. et al. Gene-to-metabolite networks for terpenoid indole alkaloid biosynthesis in Catharanthus roseus cells. Proc. Natl. Acad. Sci. USA 103, 5614–5619 (2006).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  28. Le Gall, G., Colquhoun, I.J., Davis, A.L., Collins, G.J. & Verhoeyen, M.E. Metabolite profiling of tomato (Lycopersicon esculentum) using 1H NMR spectroscopy as a tool to detect potential unintended effects following a genetic modification. J. Agric. Food Chem. 51, 2447–2456 (2003).

    Article  CAS  Google Scholar 

  29. Ward, J.L., Harris, C., Lewis, J. & Beale, M.H. Assessment of H-1 NMR spectroscopy and multivariate analysis as a technique for metabolite fingerprinting of Arabidopsis thaliana . Phytochemistry 62, 949–957 (2003).

    Article  CAS  Google Scholar 

  30. Huhman, D.V. & Sumner, L.W. Metabolic profiling of saponins in Medicago sativa and Medicago truncatula using HPLC coupled to an electrospray ion-trap mass spectrometer. Phytochemistry 59, 347–360 (2002).

    Article  CAS  Google Scholar 

  31. Breitling, R., Pitt, A.R. & Barrett, M.P. Precision mapping of the metabolome. Trends Biotechnol. 24, 543–548 (2006).

    Article  CAS  Google Scholar 

  32. Verhoeven, H.A., de Vos, C.H., Bino, R.J. & Hall, R.D. Plant metabolomics strategies based upon quadrupole time of flight mass spectrometry (QTOF-MS). in Plant Metabolomics—Biotechnology and Forestry Vol. 57, pp. 33–48 (eds. Saito, K., Dixon, R.A. & Willmitzer, L.) (Springer-Verlag, Berlin, Heidelberg, 2006).

    Chapter  Google Scholar 

  33. Beekwilder, J., Jonker, H., Meesters, P., Hall, R.F., van der Meer, I.M. & de Vos, C.H.R. Antioxidants in raspberry: on-line analysis links antioxidant activity to a diversity of individual metabolites. J. Agric. Food Chem. 53, 3313–3320 (2005).

    Article  CAS  Google Scholar 

  34. Hall, R.D., de Vos, C.H.R., Verhoeven, H.A. & Bino, R.J. Metabolomics for the assessment of functional diversity and quality traits in plants. in Metabolome Analyses-Strategies for Systems Biology (eds. Vaidyanathan, S., Harrigan, G.G. & Goodacre, R.) (Springer, New York, 2005).

    Google Scholar 

  35. Kopka, J. et al. GMD@CSB.DB: the Golm Metabolome Database. Bioinformatics 21, 1635–1638 (2005).

    Article  CAS  Google Scholar 

  36. Tolstikov, V.V. & Fiehn, O. Analysis of highly polar compounds of plant origin: combination of hydrophilic interaction chromatography and electrospray ion mass trap spectrometry. Anal. Biochem. 301, 298–307 (2002).

    Article  CAS  Google Scholar 

  37. Peterman, S.M., Duczak, N., Kalgutkar, A.S., Lame, M.E. & Soglia, J.R. Application of a linear ion trap/orbitrap mass spectrometer in metabolite characterization studies: examination of the human liver microsomal metabolism of the non-tricyclic anti-depressant nefazodone using data-dependent accurate mass measurements. J. Am. Soc. Mass Spectrom. 17, 363–375 (2006).

    Article  CAS  Google Scholar 

  38. Exarchou, V., Godejohann, M., van Beek, T.A., Gerothanassis, I.P. & Vervoort, J. LC-UV-solid-phase extraction-NMR-MS combined with a cryogenic flow probe and its application to the identification of compounds present in Greek oregano. Anal. Chem. 75, 6288–6294 (2003).

    Article  CAS  Google Scholar 

  39. Wilson, I.D. & Brinkman, U.A.T. Hyphenation and hypernation––the practice and prospects of multiple hyphenation. J. Chromatogr. A 1000, 325–356 (2003).

    Article  CAS  Google Scholar 

  40. Wolfender, J.L., Ndjoko, K. & Hostettmann, K. Liquid chromatography with ultraviolet absorbance-mass spectrometric detection and with nuclear magnetic resonance spectroscopy: a powerful combination for the on-line structural investigation of plant metabolites. J. Chromatogr. A 1000, 437–455 (2003).

    Article  CAS  Google Scholar 

  41. Nordström, A., O'Maille, G., Qin, C. & Siuzdak, G. Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum. Anal. Chem. 78, 3289–3295 (2006).

    Article  Google Scholar 

  42. Laaksonen, R. et al. A systems biology strategy reveals biological pathways and plasma biomarker candidates for potentially toxic statin-induced changes in muscle. PLoS ONE e97 (2006).

  43. Keurentjes, J.J.B. et al. The genetics of plant metabolism. Nat. Genet. 38, 842–849 (2006).

    Article  CAS  Google Scholar 

  44. Bino, R.J. et al. The light-hyperresponsive high pigment-2dg mutation of tomato: alterations in the fruit metabolome. New Phytol. 166, 427–438 (2005).

    Article  CAS  Google Scholar 

  45. Smith, C.A., Want, E.J., O'Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006).

    Article  CAS  Google Scholar 

  46. Katajamaa, M. & Oresic, M. Processing software for differential analysis of LC/MS profile data. BMC Bioinformatics 6, 179.1–179.12 (2005).

    Article  Google Scholar 

  47. Idborg, H., Zamani, L., Edlund, P., Schuppe-Koistinen, I. & Jacobsson, S.P. Metabolic fingerprinting of rat urine by LC/MS. Part 2. Data pretreatment methods for handling of complex data. J. Chromatogr. B 828, 14–20 (2005).

    Article  CAS  Google Scholar 

  48. Fu, J., Swertz, M.A., Keurentjes, J.J.B. & Jansen, R.C. MetaNetwork: a computational protocol for the genetic study of metabolic networks. Nat. Protoc. (in the press) DOI: 10.1038/nprot.2007.96 (2007).

  49. Tikunov, Y. et al. A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles. Plant Physiol. 139, 1125–1137 (2005).

    Article  CAS  Google Scholar 

  50. Wolff, J.C., Eckers, C., Sage, A.B., Giles, K. & Bateman, R. Accurate mass liquid chromatography/mass spectrometry on quadrupole orthogonal acceleration time-of-flight mass analyzers using switching between separate sample and reference sprays. 2. Applications using the dual-electrospray ion source. Anal. Chem. 73, 2605–2612 (2001).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The preparation of this paper and the work described herein was made possible through funding from the Centre for BioSystems Genomics (which is part of the Netherlands Genomics Initiative and The Netherlands Organisation for Scientific Research), Plant Research International (PRI) and the EU project META-PHOR (Food-CT-2006-03622). We thank Harry Jonker and Bert Schipper (PRI) and Jeroen Jansen (NIOO, Heteren, The Netherlands) for their excellent help in sample preparation and LC-PDA-QTOF MS analyses.

Author information

Author notes

  1. Ric CH De Vos, Sofia Moco and Arjen Lommen: These authors contributed equally to this work.

Authors and Affiliations

  1. Plant Research International, Wageningen University and Research Centre (Wageningen-UR), PO Box 16, 6700 AA, Wageningen, The Netherlands

    Ric CH De Vos, Sofia Moco, Arjen Lommen, Raoul J Bino & Robert D Hall

  2. Centre for BioSystems Genomics, PO Box 98, Wageningen, The Netherlands

    Ric CH De Vos, Sofia Moco, Arjen Lommen, Joost JB Keurentjes, Raoul J Bino & Robert D Hall

  3. Laboratory of Biochemistry, Wageningen-UR, The Netherlands

    Sofia Moco

  4. RIKILT, Institute for Food Safety, Wageningen-UR, The Netherlands

    Arjen Lommen

  5. Laboratory of Plant Physiology, Wageningen-UR, The Netherlands

    Joost JB Keurentjes & Raoul J Bino

  6. Laboratory of Plant Genetics, Wageningen-UR, The Netherlands

    Joost JB Keurentjes

Authors
  1. Ric CH De Vos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sofia Moco
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Arjen Lommen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Joost JB Keurentjes
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Raoul J Bino
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Robert D Hall
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ric CH De Vos.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

De Vos, R., Moco, S., Lommen, A. et al. Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nat Protoc 2, 778–791 (2007). https://doi.org/10.1038/nprot.2007.95

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2007.95

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing