Plant Metabolomics by GC-MS and Differential Analysis

  • Joel L. Shuman
  • Diego F. Cortes
  • Jenny M. Armenta
  • Revonda M. Pokrzywa
  • Pedro Mendes
  • Vladimir Shulaev
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 678)

Abstract

Metabolomics is a new genomics approach that aims at measuring all or a subset of metabolites in the cell. Several approaches to plant metabolomics are currently used in plant research. These include targeted analysis, metabolite profiling, and metabolic fingerprinting. Metabolic fingerprinting, unlike metabolite profiling, does not aim at separating or identifying all the metabolites present in the sample, but rather generates a fingerprint that characterizes a specific metabolic state of the plant system under investigation. This chapter describes the implementation of metabolic fingerprinting approach using gas chromatography coupled to mass spectrometry (GC-MS) and discriminant function analysis combined with genetic algorithm (GA-DFA). This approach enables the identification of specific metabolites that are biologically relevant, and which may go undetected if direct infusion-based fingerprinting approaches were used due to the sample complexity and matrix suppression effects.

Key words

Arabidopsis Plant metabolomics Polar metabolite Extraction Derivatization GC-MS Metabolic fingerprinting Metabolite profiling Targeted analysis Bioinformatics GA-DFA Genetic algorithm Discriminant function analysis 

Notes

Acknowledgments

This work was funded by National Science Foundation grant 03122857 as part of the Arabidopsis 2010 Project.

References

  1. 1.
    Shulaev, V. (2006) Metabolomics technology and bioinformatics. Brief. Bioinform. 7, 128–139.PubMedCrossRefGoogle Scholar
  2. 2.
    Rizhsky, L., Liang, H., Shuman, J., Shulaev, V., Davletova, S., et al. (2004) When defense pathways collide. The response of Arabidopsis to a combination of drought and heat stress. Plant Physiol. 134, 1683–1696.PubMedCrossRefGoogle Scholar
  3. 3.
    Roessner, U., Wagner, C., Kopka, J., Trethewey, R. N., Willmitzer, L. (2000) Simultaneous analysis of metabolites in potato tuber by gas chromatography-mass spectrometry. Plant J. 23, 131–142.PubMedCrossRefGoogle Scholar
  4. 4.
    Krishnan, P., Kruger, N. J., Ratcliffe, R. G. (2005) Metabolite fingerprinting and profiling in plants using NMR. J. Exp. Bot. 56, 255–265.PubMedCrossRefGoogle Scholar
  5. 5.
    Goodacre, R., York, E. V., Heald, J. K., Scott, I. M. (2003) Chemometric discrimination of unfractionated plant extracts analyzed by electrospray mass spectrometry. Phytochemistry 62, 859–863.PubMedCrossRefGoogle Scholar
  6. 6.
    Johnson, H. E., Broadhurst, D., Goodacre, R., Smith, A. R. (2003) Metabolic fingerprinting of salt-stressed tomatoes. Phytochemistry 62, 919–928.PubMedCrossRefGoogle Scholar
  7. 7.
    Shulaev, V., Cortes, D., Miller, G., Mittler, R. (2008) Metabolomics for plant stress response. Physiol. Plant. 132, 199–208.PubMedCrossRefGoogle Scholar
  8. 8.
    Kováts, E. (1958) Gas-chromatographische charakterisierung organischer verbindungen. Teil 1: retentionsindices aliphatischer halogenide, alkohole, aldehyde und ketone. Helv. Chim. Acta 41, 1915–1932.CrossRefGoogle Scholar
  9. 9.
    Jarvis, R.M. and Goodacre, R. (2005) Genetic algorithm optimization for pre-processing and variable selection of spectroscopic data. Bioinformatics 21, 860–868.PubMedCrossRefGoogle Scholar
  10. 10.
    Mendes, P. (2006) Available from: http://mendes.vbi.vt.edu/tiki-index.php?page=ometer.
  11. 11.
    Schweer, H. (1982) Gas chromatography–mass spectrometry of aldoses as O-methoxime, O-2-methyl-2-propoxime and O-n-butoxime pertrifluoroacetyl derivatives on OV-225 with methylpropane as ionization agent: II. Hexoses. J. Chrom. A 236, 361–367.CrossRefGoogle Scholar
  12. 12.
    Henriques, I. D., Aga, D. S., Mendes, P., O’Connor, S. K., Love, N. G. (2007) Metabolic footprinting: a new approach to identify physiological changes in complex microbial communities upon exposure to toxic chemicals. Environ. Sci. Technol. 41, 3945–3951.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Joel L. Shuman
    • 1
  • Diego F. Cortes
    • 1
  • Jenny M. Armenta
    • 1
  • Revonda M. Pokrzywa
    • 1
  • Pedro Mendes
    • 1
    • 2
    • 3
  • Vladimir Shulaev
    • 4
    • 3
  1. 1.Virginia Bioinformatics InstituteVirginia TechBlacksburgUSA
  2. 2.School of Computer ScienceUniversity of ManchesterManchesterUK
  3. 3.Department of Cancer BiologyWake Forest University School of MedicineWinston-SalemUSA
  4. 4.Department of HorticultureVirginia Bioinformatics Institute, Virginia TechBlacksburgUSA

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