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Gas Chromatography–Mass Spectrometry of Biofluids and Extracts

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Metabonomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1277))

Abstract

Gas chromatography–mass spectrometry (GC–MS) has been widely used in metabonomics analyses of biofluid samples. Biofluids provide a wealth of information about the metabolism of the whole body and from multiple regions of the body that can be used to study general health status and organ function. Blood serum and blood plasma, for example, can provide a comprehensive picture of the whole body, while urine can be used to monitor the function of the kidneys, and cerebrospinal fluid (CSF) will provide information about the status of the brain and central nervous system (CNS). Different methods have been developed for the extraction of metabolites from biofluids, these ranging from solvent extracts, acids, heat denaturation, and filtration. These methods vary widely in terms of efficiency of protein removal and in the number of metabolites extracted. Consequently, for all biofluid-based metabonomics studies, it is vital to optimize and standardize all steps of sample preparation, including initial extraction of metabolites. In this chapter, recommendations are made of the optimum experimental conditions for biofluid samples for GC–MS, with a particular focus on blood serum and plasma samples.

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References

  1. Allwood JW, Clarke A, Goodacre R et al (2010) Dual metabolomics: a novel approach to understanding plant-pathogen interactions. Phytochemistry 71:590–597

    PubMed  Google Scholar 

  2. Gidman EA, Stevens CJ, Goodacre R et al (2006) Using metabolic fingerprinting of plants for evaluating nitrogen deposition impacts on the landscape level. Glob Change Biol 12:1460–1465

    Google Scholar 

  3. Hollywood KA, Maatje M, Shadi IT et al (2010) Phenotypic profiling of keloid scars using FT-IR microspectroscopy reveals a unique spectral signature. Arch Dermatol Res 302:705–715

    PubMed  Google Scholar 

  4. Lloyd AJ, Allwood JW, Winder CL et al (2011) Metabolomic approaches reveal that cell wall modifications play a major role in ethylene-mediated resistance against Botrytis cinerea. Plant J 67:852–868

    CAS  PubMed  Google Scholar 

  5. Wang H, Hollywood K, Jarvis RM et al (2010) Phenotypic characterization of shewanella oneidensis MR-1 under aerobic and anaerobic growth conditions by using fourier transform infrared spectroscopy and high-performance liquid chromatography analyses. Appl Environ Microbiol 76:6266–6276

    PubMed Central  CAS  PubMed  Google Scholar 

  6. Ferreiro-Vera C, Priego-Capote F, Calderon-Santiago M et al (2013) Global metabolomic profiling of human serum from obese individuals by liquid chromatography-time-of-flight/mass spectrometry to evaluate the intake of breakfasts prepared with heated edible oils. Food Chem 141:1722–1731

    CAS  PubMed  Google Scholar 

  7. Shrestha B, Vertes A (2014) Relative quantitation in single-cell metabolomics by laser ablation electrospray mass spectrometry. Methods Mol Biol 1083:31–39

    PubMed  Google Scholar 

  8. Lee D-K, Yoon MH, Kang YP et al (2013) Comparison of primary and secondary metabolites for suitability to discriminate the origins of Schisandra chinensis by GC/MS and LC/MS. Food Chem 141:3931–3937

    CAS  PubMed  Google Scholar 

  9. Wang J, Chen L, Tian X et al (2013) Global metabolomic and network analysis of Escherichia coli responses to exogenous biofuels. J Proteome Res 12:5302–5312

    CAS  PubMed  Google Scholar 

  10. Styczynski MP, Moxley JF, Tong LV et al (2007) Systematic identification of conserved metabolites in GC/MS data for metabolomics and biomarker discovery. Anal Chem 79:966–973

    CAS  PubMed  Google Scholar 

  11. Zimmermann D, Hartmann M, Moyer MP et al (2007) Determination of volatile products of human colon cell line metabolism by GC/MS analysis. Metabolomics 3:13–17

    CAS  Google Scholar 

  12. Bouatra S, Aziat F, Mandal R et al (2013) The human urine metabolome. PLoS One 8:e73076

    PubMed Central  CAS  PubMed  Google Scholar 

  13. Brunetti C, George RM, Tattini M et al (2013) Metabolomics in plant environmental physiology. J Exp Bot 64:4011–4020

    CAS  PubMed  Google Scholar 

  14. Regal P, Seijas JA, Cepeda A et al (2013) Structure elucidation and HPLC-MS/MS determination of a potential biomarker for estradiol administration in cattle. Anal Bioanal Chem 405:9537–9546

    CAS  PubMed  Google Scholar 

  15. Al-Talla ZA, Akrawi SH, Emwas AHM (2011) Solid state NMR and bioequivalence comparison of the pharmacokinetic parameters of two formulations of clindamycin. Int J Clin Pharm Ther 49:469–476

    CAS  Google Scholar 

  16. Al-Talla ZA, Akrawi SH, Tolley LT et al (2011) Bioequivalence assessment of two formulations of ibuprofen. Drug Des Devel Ther 5:427–433

    PubMed Central  CAS  PubMed  Google Scholar 

  17. Gika HG, Theodoridis GA, Wingate JE et al (2007) Within-day reproducibility of an HPLC-MS-based method for metabonomic analysis: application to human urine. J Proteome Res 6:3291–3303

    CAS  PubMed  Google Scholar 

  18. Semmar N, Jay M, Nouira S (2007) A new approach to graphical and numerical analysis of links between plant chemotaxonomy and secondary metabolism from HPLC data smoothed by a simplex mixture design. Chemoecology 17:139–156

    CAS  Google Scholar 

  19. Emwas A-HMS, Reza M, Griffin JL, Merzaban J (2013) NMR-based metabolomics in human disease diagnosis: applications, limitations, and recommendations. Metabolomics 9:1048–1072

    CAS  Google Scholar 

  20. Cao M, Zhao L, Chen H et al (2012) NMR-based metabolomic analysis of human bladder cancer. Anal Sci 28:451–456

    CAS  PubMed  Google Scholar 

  21. Kokushi E, Uno S, Harada T et al (2012) 1H NMR-based metabolomics approach to assess toxicity of bunker a heavy oil to freshwater carp, Cyprinus carpio. Environ Toxicol 27:404–414

    CAS  PubMed  Google Scholar 

  22. Wang Z, Chen Z, Yang S et al (2012) H-1 NMR-based metabolomic analysis for identifying serum biomarkers to evaluate methotrexate treatment in patients with early rheumatoid arthritis. Exp Ther Med 4:165–171

    PubMed Central  CAS  PubMed  Google Scholar 

  23. Lindon JC, Holmes E, Nicholson JK (2007) Metabonomics in pharmaceutical R & D. FEBS J 274:1140–1151

    CAS  PubMed  Google Scholar 

  24. Serkova N, Fuller TF, Klawitter J et al (2005) H-1-NMR-based metabolic signatures of mild and severe ischemia/reperfusion injury in rat kidney transplants. Kidney Int 67:1142–1151

    CAS  PubMed  Google Scholar 

  25. Wishart DS (2008) Quantitative metabolomics using NMR. Trends Anal Chem 27:228–237

    CAS  Google Scholar 

  26. Bouhrara M, Ranga C, Fihri A et al (2013) Nitridated fibrous silica (KCC-1) as a sustainable solid base nanocatalyst. ACS Sustain Chem Eng 1:1192–1199

    CAS  Google Scholar 

  27. Bahuleyan BK, De SK, Sarath PU et al (2012) Effect of aluminium nitride on the properties of polyethylene obtained by in situ polymerization using Ni(II) diimine complex. Macromol Res 20:772–775

    CAS  Google Scholar 

  28. Emwas A-HM, Al-Talla ZA, Guo X et al (2013) Utilizing NMR and EPR spectroscopy to probe the role of copper in prion diseases. Magn Reson Chem 51:255–268

    CAS  PubMed  Google Scholar 

  29. Jackson MD, Moon J, Gotti E et al (2013) Material and elastic properties of Al-tobermorite in ancient roman seawater concrete. J Am Ceram Soc 96:2598–2606

    CAS  Google Scholar 

  30. Oommen JM, Hussain MM, Emwas A-HM et al (2010) Nuclear magnetic resonance study of nanoscale ionic materials. Electrochem Solid St Lett 13:K87–K88

    CAS  Google Scholar 

  31. Patil U, Fihri A, Emwas A-H et al (2012) Silicon oxynitrides of KCC-1, SBA-15 and MCM-41 for CO2 capture with excellent stability and regenerability. Chem Sci 3:2224–2229

    CAS  Google Scholar 

  32. Shidong C, Maltsev S, Emwas AH et al (2010) Solid-state NMR paramagnetic relaxation enhancement immersion depth studies in phospholipid bilayers. J Magn Reson 207:89–94

    Google Scholar 

  33. Abuhijleh AL, Abu Ali H, Emwas A-H (2009) Synthesis, spectral and structural characterization of dinuclear rhodium (II) complexes of the anticonvulsant drug valproate with theophylline and caffeine. J Organomet Chem 694:3590–3596

    CAS  Google Scholar 

  34. Sahloul N, Emwas A, Power W et al (2005) Ethyl acrylate-hydroxyethyl acrylate and hydroxyethyl acrylate-methacrylic acid: reactivity ratio estimation from cross-linked polymer using high resolution magic angle spinning spectroscopy. J Macromol Sci Pure Appl Chem A42:1369–1385

    CAS  Google Scholar 

  35. Nageeb A, Al-Tawashi A, Mohammad Emwas A-H et al (2013) Comparison of Artemisia annua bioactivities between traditional medicine and chemical extracts. Curr Bioact Compd 9:324–332

    PubMed Central  CAS  PubMed  Google Scholar 

  36. Jackson MD, Chae SR, Mulcahy SR et al (2013) Unlocking the secrets of Al-tobermorite in Roman seawater concrete. Am Mineral 98:1669–1687

    CAS  Google Scholar 

  37. Mroue KH, Emwas A-HM, Power WP (2010) Solid-state Al-27 nuclear magnetic resonance investigation of three aluminum-centered dyes. Can J Chem 88:111–123

    CAS  Google Scholar 

  38. Khan MT, Busch M, Molina VG et al (2014) How different is the composition of the fouling layer of wastewater reuse and seawater desalination RO membranes? Water Res 59:271–282

    CAS  PubMed  Google Scholar 

  39. Bharti SK, Behari A, Kapoor VK et al (2013) Magic angle spinning NMR spectroscopic metabolic profiling of gall bladder tissues for differentiating malignant from benign disease. Metabolomics 9:101–118

    CAS  Google Scholar 

  40. Jimenez B, Mirnezami R, Kinross J et al (2013) H-1 HR-MAS NMR spectroscopy of tumor-induced local metabolic “Field-Effects” enables colorectal cancer staging and prognostication. J Proteome Res 12:959–968

    CAS  PubMed  Google Scholar 

  41. Kim S, Lee S, Maeng YH et al (2013) Study of metabolic profiling changes in colorectal cancer tissues using 1D H-1 HR-MAS NMR spectroscopy. Bull Kor Chem Soc 34:1467–1472

    CAS  Google Scholar 

  42. Kumar V, Dwivedi DK, Jagannathan NR (2014) High-resolution NMR spectroscopy of human body fluids and tissues in relation to prostate cancer. NMR Biomed 27:80–89

    CAS  PubMed  Google Scholar 

  43. Tripathi P, Somashekar BS, Ponnusamy M et al (2013) HR-MAS NMR tissue metabolomic signatures cross-validated by mass spectrometry distinguish bladder cancer from benign disease. J Proteome Res 12:3519–3528

    PubMed Central  CAS  PubMed  Google Scholar 

  44. Kamal MS, Bahuleyan BK, Sohail OB et al (2013) Crystallization analysis fractionation of poly(ethylene-co-styrene) produced by metallocene catalysts. Polymer Bull 70:2645–2656

    CAS  Google Scholar 

  45. Kirchheim AP, Dal Molin DC, Fischer P et al (2011) Real-time high-resolution X-ray imaging and nuclear magnetic resonance study of the hydration of pure and Na-doped C3A in the presence of sulfates. Inorg Chem 50:1203–1212

    CAS  PubMed  Google Scholar 

  46. Atiqullah M, Winston MS, Bercaw JE et al (2012) Effects of a vanadium post-metallocene catalyst-induced polymer backbone inhomogeneity on UV oxidative degradation of the resulting polyethylene film. Polym Degrad Stab 97:1164–1177

    CAS  Google Scholar 

  47. Das SK, Xu S, Emwas A-H et al (2012) High energy lithium-oxygen batteries—transport barriers and thermodynamics. Energ Environ Sci 5:8927–8931

    CAS  Google Scholar 

  48. Blindauer CA, Emwas AH, Holy A et al (1997) Complex formation of the antiviral 9–2-(phosphonomethoxy)ethyl adenine (PMEA) and of its N1, N3, and N7 deaza derivatives with copper(II) in aqueous solution. Chem Eur J 3:1526–1536

    CAS  Google Scholar 

  49. Sze KH, Wu Q, Tse HS et al (2012) Dynamic nuclear polarization: new methodology and applications. In: Zhu G (ed) Nmr of proteins and small biomolecules. Topics in current chemistry, vol 326., pp 215–242

    Google Scholar 

  50. Tuerke M-T, Tkach I, Reese M et al (2010) Optimization of dynamic nuclear polarization experiments in aqueous solution at 15 MHz/9.7 GHz: a comparative study with DNP at 140 MHz/94 GHz. Phys Chem Chem Phys 12:5893–5901

    CAS  Google Scholar 

  51. Ludwig C, Marin-Montesinos I, Saunders MG et al (2010) Application of ex situ dynamic nuclear polarization in studying small molecules. Phys Chem Chem Phys 12:5868–5871

    CAS  PubMed  Google Scholar 

  52. Emwas AH, Saunders M, Ludwig C et al (2008) Determinants for optimal enhancement in ex situ DNP experiments. Appl Magn Reson 34:483–494

    CAS  Google Scholar 

  53. Raji M, Ma A, Emwas A-H (2013) Dehydrodimerization of pterostilbene during electrospray ionization mass spectrometry. Rapid Commun Mass Spectrom 27:1260–1266

    CAS  PubMed  Google Scholar 

  54. Lee SJ, Choi JY, Park S et al (2010) Determination of phospholipids in soybean (Glycine max (L.) Merr) cultivars by liquid chromatography-tandem mass spectrometry. J Food Compos Anal 23:314–318

    CAS  Google Scholar 

  55. Kumar MS, Pandita NS, Pal AK (2012) LC-MS/MS as a tool for identification of bioactive compounds in marine sponge Spongosorites halichondriodes. Toxicon 60:1135–1147

    CAS  PubMed  Google Scholar 

  56. Jin Y, Xiao Y-s, Zhang F-f et al (2008) Systematic screening and characterization of flavonoid glycosides in Carthamus tinctorius L. by liquid chromatography/UV diode-array detection/electrospray ionization tandem mass spectrometry. J Pharm Biomed Anal 46:418–430

    CAS  PubMed  Google Scholar 

  57. Cao X-w, Shen W-j, Zhu J et al (2013) A comparative study of the ionization modes in GC-MS multi-residue method for the determination of organochlorine pesticides and polychlorinated biphenyls in crayfish. Food Anal Meth 6:445–456

    Google Scholar 

  58. Nakamizo S, Sasayama T, Shinohara M et al (2013) GC/MS-based metabolomic analysis of cerebrospinal fluid (CSF) from glioma patients. J Neurooncol 113:65–74

    PubMed Central  CAS  PubMed  Google Scholar 

  59. Hu X, Li H, Tang P et al (2013) GC-MS-based metabolomics study of the responses to arachidonic acid in Blakeslea trispora. Fungal Genet Biol 57:33–41

    CAS  PubMed  Google Scholar 

  60. Emond P, Mavel S, Aidoud N et al (2013) GC-MS-based urine metabolic profiling of autism spectrum disorders. Anal Bioanal Chem 405:5291–5300

    CAS  PubMed  Google Scholar 

  61. Tsugawa H, Bamba T, Shinohara M et al (2011) Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis. J Biosci Bioeng 112:292–298

    CAS  PubMed  Google Scholar 

  62. Ooi M, Nishiumi S, Yoshie T et al (2011) GC/MS-based profiling of amino acids and TCA cycle-related molecules in ulcerative colitis. Inflamm Res 60:831–840

    CAS  PubMed  Google Scholar 

  63. Gao X, Zhao A, Zhou M et al (2011) GC/MS-based urinary metabolomics reveals systematic differences in metabolism and ethanol response between Sprague–Dawley and Wistar rats. Metabolomics 7:363–374

    CAS  Google Scholar 

  64. Cevallos-Cevallos JM, Garcia-Torres R, Etxeberria E et al (2011) GC-MS analysis of headspace and liquid extracts for metabolomic differentiation of citrus huanglongbing and zinc deficiency in leaves of ‘Valencia’ sweet orange from commercial groves. Phytochem Anal 22:236–246

    CAS  PubMed  Google Scholar 

  65. Zhang Q, Wang G-J, A J-Y (2009) Application of GC/MS-based metabonomic profiling in studying the lipid-regulating effects of Ginkgo biloba extract on diet-induced hyperlipidemia in rats. Acta Pharmacol Sin 30:1674–1687

    PubMed Central  CAS  PubMed  Google Scholar 

  66. Kuhara T, Ohse M, Inoue Y et al (2009) Urinary metabolic profile of phenylketonuria in patients receiving total parenteral nutrition and medication. Rapid Commun Mass Spectrom 23:3167–3172

    CAS  PubMed  Google Scholar 

  67. Cheng J, Che N, Li H et al (2013) Gas chromatography time-of-flight mass spectrometry-based metabolomic analysis of human macrophages infected by M-tuberculosis. Anal Lett 46:1922–1936

    CAS  Google Scholar 

  68. Kobayashi T, Nishiumi S, Ikeda A et al (2013) A novel serum metabolomics-based diagnostic approach to pancreatic cancer. Cancer Epidemiol Biomarkers Prev 22:571–579

    CAS  PubMed  Google Scholar 

  69. Phua LC, Koh PK, Cheah PY et al (2013) Global gas chromatography/time-of-flight mass spectrometry (GC/TOFMS)-based metabonomic profiling of lyophilized human feces. J Chromatogr B Analyt Technol Biomed Life Sci 937:103–113

    CAS  PubMed  Google Scholar 

  70. MacIntyre DA, Jimenez B, Jantus Lewintre E et al (2010) Serum metabolome analysis by H-1-NMR reveals differences between chronic lymphocytic leukaemia molecular subgroups. Leukemia 24:788–797

    CAS  PubMed  Google Scholar 

  71. Wen H, Yoo SS, Kang J et al (2010) A new NMR-based metabolomics approach for the diagnosis of biliary tract cancer. J Hepatol 52:228–233

    CAS  PubMed  Google Scholar 

  72. Huang S-M, Zuo X, Li JJE et al (2012) Metabolomics studies show dose-dependent toxicity induced by SiO2 nanoparticles in MRC-5 human fetal lung fibroblasts. Adv Healthc Mat 1:779–784

    CAS  Google Scholar 

  73. Viant MR (2009) Applications of metabolomics to the environmental sciences. Metabolomics 5:1–2

    CAS  Google Scholar 

  74. Fang Z-Z, Krausz KW, Tanaka N et al (2013) Metabolomics reveals trichloroacetate as a major contributor to trichloroethylene-induced metabolic alterations in mouse urine and serum. Arch Toxicol 87:1975–1987

    CAS  PubMed  Google Scholar 

  75. Teng Q, Ekman DR, Huang W et al (2013) Impacts of 17 alpha-ethynylestradiol exposure on metabolite profiles of zebrafish (Danio rerio) liver cells. Aquat Toxicol 130:184–191

    PubMed  Google Scholar 

  76. Wu H, Liu X, Zhang X et al (2013) Proteomic and metabolomic responses of clam Ruditapes philippinarum to arsenic exposure under different salinities. Aquat Toxicol 136:91–100

    PubMed  Google Scholar 

  77. Eiden-Plach A, Huy-Hoang N, Schneider U et al (2012) Alu Sx repeat-induced homozygous deletion of the StAR gene causes lipoid congenital adrenal hyperplasia. J Steroid Biochem Mol Biol 130:1–6

    CAS  PubMed  Google Scholar 

  78. Shiomi Y, Nishiumi S, Ooi M et al (2011) GCMS-based metabolomic study in mice with colitis induced by dextran sulfate sodium. Inflamm Bowel Dis 17:2261–2274

    PubMed  Google Scholar 

  79. van der Kloet FM, Tempels FWA, Ismail N et al (2012) Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study). Metabolomics 8:109–119

    PubMed Central  CAS  PubMed  Google Scholar 

  80. Gavaghan CL, Li JV, Hadfield ST et al (2011) Application of NMR-based metabolomics to the investigation of salt stress in maize (Zea mays). Phytochem Anal 22:214–224

    CAS  PubMed  Google Scholar 

  81. Laiakis EC, Hyduke DR, Fornace AJ Jr (2012) Comparison of mouse urinary metabolic profiles after exposure to the inflammatory stressors gamma radiation and lipopolysaccharide. Radiat Res 177:187–199

    PubMed Central  CAS  PubMed  Google Scholar 

  82. Liu X, Zhang L, You L et al (2011) Toxicological responses to acute mercury exposure for three species of Manila clam Ruditapes philippinarum by NMR-based metabolomics. Environ Toxicol Pharmacol 31:323–332

    PubMed  Google Scholar 

  83. Daykin CA, Foxall PJD, Connor SC et al (2002) The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by (1)H nuclear magnetic resonance spectroscopy. Anal Biochem 304:220–230

    CAS  PubMed  Google Scholar 

  84. de Graaf RA, Behar KL (2003) Quantitative H-1 NMR spectroscopy of blood plasma metabolites. Anal Chem 75:2100–2104

    PubMed  Google Scholar 

  85. Polson C, Sarkar P, Incledon B et al (2003) Optimization of protein precipitation based upon effectiveness of protein removal and ionization effect in liquid chromatography-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 785:263–275

    CAS  PubMed  Google Scholar 

  86. Zellner M, Winkler W, Hayden H et al (2005) Quantitative validation of different protein precipitation methods in proteome analysis of blood platelets. Electrophoresis 26:2481–2489

    CAS  PubMed  Google Scholar 

  87. Tiziani S, Emwas AH, Lodi A et al (2008) Optimized metabolite extraction from blood serum for H-1 nuclear magnetic resonance spectroscopy. Anal Biochem 377:16–23

    CAS  PubMed  Google Scholar 

  88. A J, Trygg J, Gullberg J et al (2005) Extraction and GC/MS analysis of the human blood plasma metabolome. Anal Chem 77:8086–8094

    CAS  PubMed  Google Scholar 

  89. Huang J-H, Xie H-L, Yan J et al (2013) Interpretation of type 2 diabetes mellitus relevant GC-MS metabolomics fingerprints by using random forests. Anal Meth 5:4883–4889

    CAS  Google Scholar 

  90. Aliferis KA, Jabaji S (2012) FT-ICR/MS and GC-EI/MS metabolomics networking unravels global potato sprout’s responses to rhizoctonia solani infection. PLoS One 7:1–13

    Google Scholar 

  91. Fancy S-A, Rumpel K (2008) GC-MS-based metabolomics. In: Wang F (ed) Methods in pharmacology and toxicology. Springer, New York, pp 317–340

    Google Scholar 

  92. Ku KM, Choi JN, Kim J et al (2010) Metabolomics analysis reveals the compositional differences of shade grown tea (Camellia sinensis L.). J Agric Food Chem 58:418–426

    CAS  PubMed  Google Scholar 

  93. Arbona V, Iglesias DJ, Talon M et al (2009) Plant phenotype demarcation using nontargeted LC-MS and GC-MS metabolite profiling. J Agric Food Chem 57:7338–7347

    CAS  PubMed  Google Scholar 

  94. Dettmer K, Aronov PA, Hammock BD (2007) Mass spectrometry-based metabolomics. Mass Spectrom Rev 26:51–78

    PubMed Central  CAS  PubMed  Google Scholar 

  95. Halket JM, Waterman D, Przyborowska AM et al (2005) Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS. J Exp Bot 56:219–243

    CAS  PubMed  Google Scholar 

  96. Little JL (1999) Artifacts in trimethylsilyl derivatization reactions and ways to avoid them. J Chromatogr A 844:1–22

    CAS  PubMed  Google Scholar 

  97. Birkemeyer C, Kolasa A, Kopka J (2003) Comprehensive chemical derivatization for gas chromatography–mass spectrometry-based multi-targeted profiling of the major phytohormones. J Chromatogr A 993:89–102

    CAS  PubMed  Google Scholar 

  98. Fiehn O, Kopka J, Trethewey RN et al (2000) Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal Chem 72:3573–3580

    CAS  PubMed  Google Scholar 

  99. Roessner-Tunali U, Liu JL, Leisse A et al (2004) Kinetics of labelling of organic and amino acids in potato tubers by gas chromatography–mass spectrometry following incubation in C-13 labelled isotopes. Plant J 39:668–679

    CAS  PubMed  Google Scholar 

  100. Colebatch G, Desbrosses G, Ott T et al (2004) Global changes in transcription orchestrate metabolic differentiation during symbiotic nitrogen fixation in Lotus japonicus. Plant J 39:487–512

    PubMed  Google Scholar 

  101. Jonsson P, Gullberg J, Nordstrom A et al (2004) A strategy for identifying differences in large series of metabolomic samples analyzed by GC/MS. Anal Chem 76:1738–1745

    CAS  PubMed  Google Scholar 

  102. Barding GA, Beni S, Fukao T et al (2013) Comparison of GC-MS and NMR for metabolite profiling of rice subjected to submergence stress. J Proteome Res 12:898–909

    CAS  PubMed  Google Scholar 

  103. Kim J, Choi JN, John KMM et al (2012) GC-TOF-MS- and CE-TOF-MS-based metabolic profiling of cheonggukjang (fast-fermented bean paste) during fermentation and its correlation with metabolic pathways. J Agric Food Chem 60:9746–9753

    CAS  PubMed  Google Scholar 

  104. Marcinowska R, Trygg J, Wolf-Watz H et al (2011) Optimization of a sample preparation method for the metabolomic analysis of clinically relevant bacteria. J Microbiol Methods 87:24–31

    CAS  PubMed  Google Scholar 

  105. Rosenling T, Stoop MP, Smolinska A et al (2011) The impact of delayed storage on the measured proteome and metabolome of human cerebrospinal fluid. Clin Chem 57:1703–1711

    CAS  PubMed  Google Scholar 

  106. Jiang W, Qiu Y, Ni Y et al (2010) An automated data analysis pipeline for GC-TOF-MS metabonomics studies. J Proteome Res 9:5974–5981

    CAS  PubMed  Google Scholar 

  107. Lu H, Gan D, Zhang Z et al (2011) Sample classification of GC-ToF-MS metabolomics data without the requirement for chromatographic deconvolution. Metabolomics 7:191–205

    CAS  Google Scholar 

  108. Chorell E, Moritz T, Branth S et al (2009) Predictive metabolomics evaluation of nutrition-modulated metabolic stress responses in human blood serum during the early recovery phase of strenuous physical exercise. J Proteome Res 8:2966–2977

    CAS  PubMed  Google Scholar 

  109. Dunn WB, Broadhurst D, Ellis DI et al (2008) A GC-TOF-MS study of the stability of serum and urine metabolomes during the UK Biobank sample collection and preparation protocols. Int J Epidemiol 37:23–30

    Google Scholar 

  110. Hummel J, Selbig J, Walther D et al (2007) The golm metabolome database: a database for GC-MS based metabolite profiling. In: Nielsen J, Jewett MC (eds) Topics in Current Genetics, vol 18., pp 75–95

    Google Scholar 

  111. Lu H, Dunn WB, Shen H et al (2008) Comparative evaluation of software for deconvolution of metabolomics data based on GC-TOF-MS. Trends Anal Chem 27:215–227

    CAS  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  113. Yu Z, Kastenmueller G, He Y et al (2011) Differences between human plasma and serum metabolite profiles. PLoS One 6:1–6

    Google Scholar 

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Acknowledgments

We would like to thank King Abdullah University of Science and Technology for financial support and Dr. Virginia Unkefer from KAUST and Dr. Christina Morris for their assistance and helpful editorial remarks.

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Correspondence to Abdul-Hamid M. Emwas .

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Emwas, AH.M., Al-Talla, Z.A., Yang, Y., Kharbatia, N.M. (2015). Gas Chromatography–Mass Spectrometry of Biofluids and Extracts. In: Bjerrum, J. (eds) Metabonomics. Methods in Molecular Biology, vol 1277. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2377-9_8

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  • DOI: https://doi.org/10.1007/978-1-4939-2377-9_8

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