Functional Genomics pp 377-398

Part of the Methods in Molecular Biology book series (MIMB, volume 815)

Metabolome Analysis of Gram-Positive Bacteria such as Staphylococcus aureus by GC-MS and LC-MS

  • Manuel Liebeke
  • Kirsten Dörries
  • Hanna Meyer
  • Michael Lalk
Protocol

Abstract

The field of metabolomics has become increasingly important in the context of functional genomics. Together with other ”omics“ data, the investigation of the metabolome is an essential part of systems biology. Beside the analysis of human and animal biofluids, the investigation of the microbial physiology by methods of metabolomics has gained increased attention. For example, the analysis of metabolic processes during growth or virulence factor expression is crucially important to understand pathogenesis of bacteria. Common bioanalytical techniques for metabolome analysis include liquid and gas chromatographic methods coupled to mass spectrometry (LC-MS and GC-MS) and spectroscopic approaches such as NMR. In order to achieve metabolome data representing the physiological status of a microorganism, well-verified protocols for sampling and analysis are necessary. This chapter presents a detailed protocol for metabolome analysis of the Gram-positive bacterium Staphylococcus aureus. A detailed manual for cell sampling and metabolite extraction is given, followed by the description of the analytical procedures GC-MS and LC-MS. The advantages and limitations of each experimental setup are discussed. Here, a guideline specified for S. aureus metabolomics and information for important protocol steps are presented, to avoid common pitfalls in microbial metabolome analysis.

Key words

Metabolomics Liquid chromatography Gas chromatography Mass spectrometry Bacteria Staphylococcus aureus Energy charge Protocol Sampling Ion-pairing 

References

  1. 1.
    Fiehn O, (2002) Metabolomics – the link between genotypes and phenotypes. Plant Mol Biol 48, 155–171.PubMedCrossRefGoogle Scholar
  2. 2.
    Oliver SG, Winson MK, Kell DB, and Baganz F (1998) Systematic functional analysis of the yeast genome. Trends in biotechnology 16, 373–378.PubMedCrossRefGoogle Scholar
  3. 3.
    Bennett BD, Kimball EH, Gao M, Osterhout R, Van Dien SJ, and Rabinowitz JD (2009) Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli. Nat Chem Biol 5, 593–599.PubMedCrossRefGoogle Scholar
  4. 4.
    Brauer MJ, Yuan J, Bennett BD, Lu WY, Kimball E, Botstein D, and Rabinowitz JD (2006) Conservation of the metabolomic response to starvation across two divergent microbes. P Natl Acad Sci USA 103, 19302–19307.CrossRefGoogle Scholar
  5. 5.
    Zamboni N, and Sauer U (2009) Novel biological insights through metabolomics and 13C-flux analysis. Curr Opin Microbiol 12, 553–558.PubMedCrossRefGoogle Scholar
  6. 6.
    Nakahigashi K, Toya Y, Ishii N, Soga T, Hasegawa M, Watanabe H, Takai Y, Honma M, Mori H, and Tomita M (2009) Systematic phenome analysis of Escherichia coli multiple-knockout mutants reveals hidden reactions in central carbon metabolism. Mol Syst Biol 5, 306.PubMedCrossRefGoogle Scholar
  7. 7.
    Mashego MR, Rumbold K, De Mey M, Vandamme E, Soetaert W, and Heijnen JJ (2007) Microbial metabolomics: past, present and future methodologies. Biotechnol Lett 29, 1–16.PubMedCrossRefGoogle Scholar
  8. 8.
    Durot M, Bourguignon PY, and Schachter V (2009) Genome-scale models of bacterial metabolism: reconstruction and applications. FEMS Microbiol Rev 33, 164–190.PubMedCrossRefGoogle Scholar
  9. 9.
    Bolten CJ, Kiefer P, Letisse F, Portais JC, and Wittmann C (2007) Sampling for metabolome analysis of microorganisms. Anal Chem 79, 3843–3849.PubMedCrossRefGoogle Scholar
  10. 10.
    Meyer H, Liebeke M, and Lalk M (2010) A protocol for the investigation of the intracellular Staphylococcus aureus metabolome. Anal Biochem 401, 250–259.PubMedCrossRefGoogle Scholar
  11. 11.
    Donat S, Streker K, Schirmeister T, Rakette S, Stehle T, Liebeke M, Lalk M, and Ohlsen K (2009) Transcriptome and functional analysis of the eukaryotic-type serine/threonine kinase PknB in Staphylococcus aureus. J Bacteriol 191, 4056–4069.PubMedCrossRefGoogle Scholar
  12. 12.
    Liebeke M, Meyer H, Donat S, Ohlsen K, and Lalk M (2010) A metabolomic view of Staphylococcus aureus and its serine/threonine kinase and phosphatase deletion mutants: involvement in cell wall biosynthesis. Chem Biol 17, 820–830.PubMedCrossRefGoogle Scholar
  13. 13.
    Winder CL, Dunn WB, Schuler S, Broadhurst D, Jarvis R, Stephens GM, and Goodacre R (2008) Global metabolic profiling of Escherichia coli cultures: an evaluation of methods for quenching and extraction of intracellular metabolites. Anal Chem 80, 2939–2948.PubMedCrossRefGoogle Scholar
  14. 14.
    Lisec J, Schauer N, Kopka J, Willmitzer L, and Fernie AR (2006) Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat Protoc 1, 387–396.PubMedCrossRefGoogle Scholar
  15. 15.
    Want EJ, Coen M, Masson P, Keun HC, Pearce JT, Reily MD, Robertson DG, Rohde CM, Holmes E, Lindon JC, Plumb RS, and Nicholson JK (2010) Ultra performance liquid chromatography-mass spectrometry profiling of bile acid metabolites in biofluids: application to experimental toxicology studies. Anal Chem 82, 5282–5289.PubMedCrossRefGoogle Scholar
  16. 16.
    Villas-Boas SG, Mas S, Akesson M, Smedsgaard J, and Nielsen J (2005) Mass spectrometry in metabolome analysis. Mass Spectrom Rev 24, 613–646.PubMedCrossRefGoogle Scholar
  17. 17.
    Cubbon S, Antonio C, Wilson J, and Thomas-Oates J (2010) Metabolomic applications of HILIC-LC-MS. Mass Spectrom Rev 29, 671–684.PubMedCrossRefGoogle Scholar
  18. 18.
    Allwood JW, and Goodacre R (2009) An introduction to liquid chromatography-mass spectrometry instrumentation applied in plant metabolomic analyses. Phytochem Anal 21, 33–47.CrossRefGoogle Scholar
  19. 19.
    Bajad SU, Lu W, Kimball EH, Yuan J, Peterson C, and Rabinowitz JD (2006) Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry. J Chromatogr A 1125, 76–88.PubMedCrossRefGoogle Scholar
  20. 20.
    Buescher JM, Moco S, Sauer U, and Zamboni N (2010) Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. Anal Chem 82, 4403–4412.PubMedCrossRefGoogle Scholar
  21. 21.
    Roessner U, Luedemann A, Brust D, Fiehn O, Linke T, Willmitzer L, and Fernie A (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13, 11–29.PubMedCrossRefGoogle Scholar
  22. 22.
    Roessner-Tunali U, Urbanczyk-Wochniak E, Czechowski T, Kolbe A, Willmitzer L, and Fernie AR (2003) De novo amino acid biosynthesis in potato tubers is regulated by sucrose levels. Plant Physiol 133, 683–692.PubMedCrossRefGoogle Scholar
  23. 23.
    Sangster T, Major H, Plumb R, Wilson AJ, and Wilson ID (2006) A pragmatic and readily implemented quality control strategy for HPLC-MS and GC-MS-based metabonomic analysis. Analyst 131, 1075–1078.PubMedCrossRefGoogle Scholar
  24. 24.
    Wu L, Mashego MR, van Dam JC, Proell AM, Vinke JL., Ras C, van Winden WA, van Gulik W M, and Heijnen JJ (2005) Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards. Anal Biochem 336, 164–171.PubMedCrossRefGoogle Scholar
  25. 25.
    Bennett BD, Yuan J, Kimball EH, and Rabinowitz JD (2008) Absolute quantitation of intracellular metabolite concentrations by an isotope ratio-based approach. Nat Protoc 3, 1299–1311.PubMedCrossRefGoogle Scholar
  26. 26.
    Pluskal T, Nakamura T, Villar-Briones A, and Yanagida M Metabolic profiling of the fission yeast S. pombe: quantification of compounds under different temperatures and genetic perturbation. Mol Biosyst 6, 182–198.Google Scholar
  27. 27.
    Liebeke M, Brozel VS, Hecker M, and Lalk M (2009) Chemical characterization of soil extract as growth media for the ecophysiological study of bacteria. Appl Microbiol Biotechnol 83, 161–173.PubMedCrossRefGoogle Scholar
  28. 28.
    Benton HP, Wong DM, Trauger SA, and Siuzdak G (2008) XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization. Anal Chem 80, 6382–6389.PubMedCrossRefGoogle Scholar
  29. 29.
    Lommen A (2009) MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing. Anal Chem 81, 3079–3086.PubMedCrossRefGoogle Scholar
  30. 30.
    Bunk B, Kucklick M, Jonas R, Munch R, Schobert M, Jahn D, and Hiller K (2006) MetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data. Bioinformatics 22, 2962–2965.PubMedCrossRefGoogle Scholar
  31. 31.
    Luedemann A, Strassburg K, Erban A, and Kopka J (2008) TagFinder for the quantitative analysis of gas chromatography–mass spectrometry (GC–MS)-based metabolite profiling experiments. Bioinformatics 24, 732–737.PubMedCrossRefGoogle Scholar
  32. 32.
    Trygg J, Holmes E, and Lundstedt T (2007) Chemometrics in metabonomics. J Proteome Res 6, 469–479.PubMedCrossRefGoogle Scholar
  33. 33.
    Lai L, Michopoulos F, Gika H, Theodoridis G, Wilkinson RW, Odedra R, Wingate J, Bonner R, Tate S, and Wilson ID (2010) Methodological considerations in the development of HPLC-MS methods for the analysis of rodent plasma for metabonomic studies. Mol Biosyst 6, 108–120.PubMedCrossRefGoogle Scholar
  34. 34.
    Burton L, Ivosev G, Tate S, Impey G, Wingate J, and Bonner R (2008) Instrumental and experimental effects in LC-MS-based metabolomics. J Chromatogr B 871, 227–235.CrossRefGoogle Scholar
  35. 35.
    Hummel J, Strehmel N, Selbig J, Walther D, and Kopka J (2010) Decision tree supported substructure prediction of metabolites from GC-MS profiles. Metabolomics 6, 322–333.PubMedCrossRefGoogle Scholar
  36. 36.
    Smith CA, Want EJ, O’Maille G, Abagyan R, and Siuzdak G (2006) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78, 779–787.PubMedCrossRefGoogle Scholar
  37. 37.
    Katajamaa M, Miettinen J, and Oresic M (2006) MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics 22, 634–636.PubMedCrossRefGoogle Scholar
  38. 38.
    Sumner LW, Urbanczyk-Wochniak E, and Broeckling CD (2007) Metabolomics data analysis, visualization, and integration. Methods Mol Biol 406, 409–436.PubMedCrossRefGoogle Scholar
  39. 39.
    Smith CA, O’Maille G, Want EJ, Qin C, Trauger SA, Brandon TR, Custodio DE, Abagyan R, and Siuzdak G (2005) METLIN: a metabolite mass spectral database. Ther Drug Monit 27, 747–751.PubMedCrossRefGoogle Scholar
  40. 40.
    Ulrich EL, Akutsu H, Doreleijers JF, Harano Y, Ioannidis YE, Lin J, Livny M, Mading S, Maziuk D, Miller Z, Nakatani E, Schulte CF, Tolmie DE, Kent Wenger R, Yao H, and Markley JL (2008) BioMagResBank. Nucleic Acids Res 36, D402–408.PubMedCrossRefGoogle Scholar
  41. 41.
    Wishart, DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, Hau DD, Psychogios N, Dong E, Bouatra S, Mandal R, et al. (2009) HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37, D603–610.PubMedCrossRefGoogle Scholar
  42. 42.
    Atkinson DE (1968) The energy charge of the adenylate pool as a regulatory parameter. Interaction with feedback modifiers. Biochemistry-Us 7, 4030–4034.Google Scholar
  43. 43.
    Steuer R, Morgenthal K, Weckwerth W, and Selbig J (2007) A gentle guide to the analysis of metabolomic data. Methods Mol Biol 358, 105–126.PubMedCrossRefGoogle Scholar
  44. 44.
    Gehlenborg N, O’Donoghue SI, Baliga NS, Goesmann A, Hibbs MA, Kitano H, Kohlbacher O, Neuweger H, Schneider R, Tenenbaum D, and Gavin AC (2010) Visualization of omics data for systems biology. Nat Methods 7, S56–68.PubMedCrossRefGoogle Scholar
  45. 45.
    Scholz M, and Selbig J (2007) Visualization and analysis of molecular data. Methods Mol Biol 358, 87–104.PubMedCrossRefGoogle Scholar
  46. 46.
    Bligh EG, and Dyer WJ (1959) A rapid method of total lipid extraction and purification. Can J Biochem Physiol 37, 911–917.PubMedCrossRefGoogle Scholar
  47. 47.
    Kouremenos KA, Harynuk JJ, Winniford WL, Morrison PD, and Marriott PJ (2010) One-pot microwave derivatization of target compounds relevant to metabolomics with comprehensive two-dimensional gas chromatography. J Chromatogr B 878, 1761–1770.CrossRefGoogle Scholar
  48. 48.
    Liebeke M, Wunder A, and Lalk M (2010) A rapid microwave-assisted derivatization of bacterial metabolome samples for GC/MS analysis. Anal Biochem 401, 312–314.PubMedCrossRefGoogle Scholar
  49. 49.
    Coulier L, Bas R, Jespersen S, Verheij E, van der Werf MJ, and Hankemeier T (2006) Simultaneous quantitative analysis of metabolites using ion-pair liquid chromatography-electrospray ionization mass spectrometry. Anal Chem 78, 6573–6582.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Manuel Liebeke
    • 1
  • Kirsten Dörries
    • 2
  • Hanna Meyer
    • 3
  • Michael Lalk
    • 3
  1. 1.Biomolecular Medicine, Department of Surgery and CancerFaculty of Medicine, Imperial College LondonLondonUK
  2. 2.Institute of PharmacyErnst-Moritz-Arndt-University GreifswaldGreifswaldGermany
  3. 3.Institute of Pharmacy, Interfaculty Institute for Genetics and Functional GenomicsUniversity of GreifswaldGreifswaldGermany

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