, Volume 8, Issue 3, pp 410–421 | Cite as

The biological interpretation of metabolomic data can be misled by the extraction method used

  • Xavier Duportet
  • Raphael Bastos Mereschi Aggio
  • Sónia Carneiro
  • Silas Granato Villas-Bôas
Original Article


The field of metabolomics is getting more and more popular and a wide range of different sample preparation procedures are in use by different laboratories. Chemical extraction methods using one or more organic solvents as the extraction agent are the most commonly used approach to extract intracellular metabolites and generate metabolite profiles. Metabolite profiles are the scaffold supporting the biological interpretation in metabolomics. Therefore, we aimed to address the following fundamental question: can we obtain similar metabolomic results and, consequently, reach the same biological interpretation by using different protocols for extraction of intracellular metabolites? We have used four different methods for extraction of intracellular metabolites using four different microbial cell types (Gram negative bacterium, Gram positive bacterium, yeast, and a filamentous fungus). All the quenched samples were pooled together before extraction, and, therefore, they were identical. After extraction and GC–MS analysis of metabolites, we did not only detect different numbers of compounds depending on the extraction method used and regardless of the cell type tested, but we also obtained distinct metabolite levels for the compounds commonly detected by all methods (P-value < 0.001). These differences between methods resulted in contradictory biological interpretation regarding the activity of different metabolic pathways. Therefore, our results show that different solvent-based extraction methods can yield significantly different metabolite profiles, which impact substantially in the biological interpretation of metabolomics data. Thus, development of alternative extraction protocols and, most importantly, standardization of sample preparation methods for metabolomics should be seriously pursued by the scientific community.


Metabolite extraction Metabolic fingerprint Metabolite profiling Metabolome Metabolomics Mass spectrometry 


  1. Aggio, R. B. M., Ruggiero, K., & Villas-Bôas, S. G. (2010). Pathway Activity Profiling (PAPi): From the metabolite profile to the metabolic pathway activity. Bioinformatics, 26, 2969–2976.PubMedCrossRefGoogle Scholar
  2. Asiago, V. M., Alvarado, L. Z., Shanaiah, N., Gowda, G. A. N., Owusu-Sarfo, K., Ballas, R. A., et al. (2010). Early detection of recurrent breast cancer using metabolite profiling. Cancer Research, 70, 8309–8318.PubMedCrossRefGoogle Scholar
  3. Baker, M. (2011). Metabolomics: From small molecules to big ideas. Nature Methods, 8, 117–121.CrossRefGoogle Scholar
  4. Bennett, B. D., Yuan, J., Kimball, E. H., & Rabinowitz, J. D. (2008). Absolute quantitation of intracellular metabolite concentrations by an isotope ratio-based approach. Nature Protocols, 3, 1299–1311.PubMedCrossRefGoogle Scholar
  5. Canelas, A. B., Pierick, A. T., Ras, C., Seifar, R. M., van Dam, J. C., van Gulik, W. M., et al. (2009). Quantitative evaluation of intracellular metabolite extraction techniques for yeast metabolomics. Analytical Chemistry, 81, 7379–7389.PubMedCrossRefGoogle Scholar
  6. Clark, W., & Christopher, K. (2000). An Introduction to DNA: Spectrophotometry, degradation, and the ‘Frankengel’ experiment. In S. J. Karcher (Ed.), Tested studies for laboratory reaching (Vol. 22, pp. 81–99). Edmonton, Canada: Association for Biology Laboratory Education, University of Alberta.Google Scholar
  7. Dietmair, S., Timmins, N. E., Gray, P. P., Nielsen, L. K., & Kromer, J. O. (2010). Towards quantitative metabolomics of mammalian cells: Development of a metabolite extraction protocol. Analytical Biochemistry, 404, 155–164.PubMedCrossRefGoogle Scholar
  8. Dunn, W. B., Broadhurst, D. I., Atherton, H. J., Goodacre, R., & Griffin, J. L. (2011). Systems level studies of mammalian metabolomes: The roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chemical Society Reviews, 40, 387–426.PubMedCrossRefGoogle Scholar
  9. El Rammouz, R., Letisse, F., & Durand, S. (2010). Analysis of skeletal muscle metabolome: Evaluation of extraction methods for targeted metabolite quantification using liquid chromatography tandem mass spectrometry. Analytical Biochemistry, 398, 169–177.PubMedCrossRefGoogle Scholar
  10. Ershov, B. G. (1998). Radiation-chemical degradation of cellulose and other polysaccharides. Russian Chemical Reviews, 67, 315–334.CrossRefGoogle Scholar
  11. Faijes, M., Mars, A. E., & Smid, E. J. (2007). Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum. Microbial Cell Factories, 6, 27–34.PubMedCrossRefGoogle Scholar
  12. Goldstone, D. C., Villas-Bôas, S. G., Till, M., Kelly, W. J., Attwood, G. T., & Arcus, V. L. (2009). Structural and functional characterization of a promiscuous feruloyl esterase (Est1E) from the rumen bacterium Butyrivibrio proteoclasticus. Proteins, 78, 1457–1469.Google Scholar
  13. Gonzalez, B., Francois, J., & Renaud, M. (1997). A rapid and reliable method for metabolite extraction in yeast using boiling buffered ethanol. Yeast, 13, 1347–1355.PubMedCrossRefGoogle Scholar
  14. Gromova, M., & Roby, C. (2010). Toward Arabidopsis thaliana hydrophilic metabolome: Assessment of extraction methods and quantitative 1H NMR. Phys Plant, 140, 111–127.CrossRefGoogle Scholar
  15. Han, K. K., Richard, C., & Biserte, G. (1983). Current developments in chemical cleavage of proteins. International Journal of Biochemistry, 15, 875–884.CrossRefGoogle Scholar
  16. Hirai, M. Y., Sawada, Y., Kanaya, S., Kuromori, T., Kobayashi, M., Klausnitzer, R., et al. (2010). Toward genome-wide metabolotyping and elucidation of metabolic system: Metabolic profiling of large-scale bioresources. Journal of Plant Research, 123, 291–298.PubMedCrossRefGoogle Scholar
  17. Kell, D. B., Brown, M., Davey, H. M., Dunn, W. B., Spasic, I., & Oliver, S. G. (2005). Metabolic footprinting and systems biology: The medium is the message. Nature Reviews in Microbiology, 3, 557–565.CrossRefGoogle Scholar
  18. Liu, J. Y., Li, N., Yang, J., Li, N., Qiu, H., Ai, D., et al. (2010). Metabolic profiling of murine plasma reveals an unexpected biomarker in rofecoxib-mediated cardiovascular events. Proceedings of the National Academy of Science USA, 107, 17017–17022.CrossRefGoogle Scholar
  19. Maharjan, R. P., & Ferenci, T. (2003). Global metabolite analysis: the influence of extraction methodology on metabolome profiles of Escherichia coli. Analytical Biochemistry, 313, 145–154.PubMedCrossRefGoogle Scholar
  20. Marcus, F. (1985). Preferential cleavage at aspartyl-prolyl peptide bonds in dilute acid. International Journal of Peptide and Protein Research, 25, 542–546.PubMedCrossRefGoogle Scholar
  21. Mas, S., Villas-Bôas, S. G., Hansen, M. E., Åkesson, M., & Nielsen, N. (2007). A comparison of direct infusion MS and GC–MS for metabolic footprinting of yeast mutants. Biotechnology and Bioengineering, 96, 1014–1022.PubMedCrossRefGoogle Scholar
  22. Nishiumi, S., Shinohara, M., Ikeda, A., Yoshie, T., Hatano, N., Kakuyama, S., et al. (2010). Serum metabolomics as a novel diagnostic approach for pancreatic cancer. Metabolomics, 6, 518–528.CrossRefGoogle Scholar
  23. Oliyai, C., & Borchardt, R. T. (1993). Chemical pathways of peptide degradation.4. Pathways, kinetics, and mechanism of degradation of an aspartyl residue in a model hexapeptide. Pharmaceutical Research, 10, 95–102.PubMedCrossRefGoogle Scholar
  24. Rabinowitz, J. D., & Kimball, E. (2007). Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Analytical Chemistry, 79, 6167–6173.PubMedCrossRefGoogle Scholar
  25. Shin, M. H., Lee, D. Y., Liu, K. H., Fiehn, O., & Kim, K. H. (2010). Evaluation of sampling and extraction methodologies for the global metabolic profiling of Saccharophagus degradans. Analytical Chemistry, 82, 6660–6666.PubMedCrossRefGoogle Scholar
  26. Smart, K. F., Aggio, R. B. M., Van Houtte, J. R., & Villas-Bôas, S. G. (2010). Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography–mass spectrometry. Nature Protocols, 5, 1709–1729.PubMedCrossRefGoogle Scholar
  27. van Gulik, W. M. (2010). Fast sampling for quantitative microbial metabolomics. Current Opinion in Biotechnology, 21, 27–34.PubMedCrossRefGoogle Scholar
  28. Villas-Bôas, S. G. (2007). Sampling and sample preparation. In S. G. Villas-Bôas, U. Roessner, M. E. Hansen, J. Smedsgaard, & J. Nielsen (Eds.), Metabolome analysis—an introduction (pp. 39–82). New Jersey, USA: Wiley.CrossRefGoogle Scholar
  29. Villas-Bôas, S. G., & Bruheim, P. (2007). Cold glycerol–saline: The promising quenching solution for accurate intracellular metabolite analysis of microbial cells. Analytical Biochemistry, 370, 87–97.PubMedCrossRefGoogle Scholar
  30. Villas-Bôas, S. G., Højer-Pedersen, J., Åkesson, M., Smedsgaard, J., & Nielsen, J. (2005a). Global metabolite analysis of yeast: Evaluation of sample preparation methods. Yeasts, 22, 1155–1169.CrossRefGoogle Scholar
  31. Villas-Bôas, S. G., Koulman, A., & Lane, G. A. (2007). Method standardization. In J. Nielsen & M. C. Jewett (Eds.), Topics in current genetics: Metabolomics (Vol. 18, pp. 11–52). Heidelberg: Springer.Google Scholar
  32. Villas-Bôas, S. G., Mas, S., Åkesson, M., Smedsgaard, J., & Nielsen, J. (2005b). Mass spectrometry in metabolome analysis. Mass Spectrometry Reviews, 24, 613–646.PubMedCrossRefGoogle Scholar
  33. Villas-Bôas, S. G., Moon, C. D., Noel, S., Hussein, H., Kelly, W. J., Cao, M., et al. (2008). Phenotypic characterization of transposon-inserted mutants of Clostridium proteoclasticum B316T using extracellular metabolomics. Journal of Biotechnology, 134, 55–63.PubMedCrossRefGoogle Scholar
  34. Winder, C. L., Dunn, W. B., Schuler, S., Broadhurst, D., Jarvis, R., Stephens, G. M., et al. (2008). Global metabolic profiling of Escherichia coli cultures: An evaluation of methods for quenching and extraction of intracellular metabolites. Analytical Chemistry, 80, 2939–2948.PubMedCrossRefGoogle Scholar
  35. Wu, T., Zivanovic, S., Hayes, D. G., & Weiss, J. (2008). Efficient reduction of chitosan molecular weight by high-intensity ultrasound: Underlying mechanism and effect of process parameters. Journal of Agriculture and Food Chemistry, 56, 5112–5119.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Xavier Duportet
    • 1
    • 2
  • Raphael Bastos Mereschi Aggio
    • 1
  • Sónia Carneiro
    • 1
    • 3
  • Silas Granato Villas-Bôas
    • 1
  1. 1.Centre for Microbial InnovationSchool of Biological Sciences, The University of AucklandAucklandNew Zealand
  2. 2.AgroParisTechParisFrance
  3. 3.Institute for Biotechnology and Bioengineering (IBB), Centre of Biological EngineeringUniversity of MinhoBragaPortugal

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