Skip to main content

Advertisement

Springer Nature Link
Log in

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography–mass spectrometry

  • Review
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography–mass spectrometry (LC–MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

Abbreviations

ADP:

Adenosine diphosphate

AMP:

Adenosine monophosphate

ATP:

Adenosine triphosphate

CHO:

Chinese hamster ovary cells

CSF:

Cerebrospinal fluid

DBS:

Dried blood spot or dried biofluid spot

EDTA:

Ethylenediaminetetraacetic acid

ESI:

Electrospray ionization

GC–MS:

Gas chromatography–mass spectrometry

HILIC:

Hydrophilic interaction chromatography

HPLC:

High-performance liquid chromatography

HUSERMET:

Human serum metabolome project

LC–MS:

Liquid chromatography–mass spectrometry

NAD:

Nicotinamide adenine dinucleotide

NADH:

Reduced nicotinamide adenine dinucleotide

NMR:

Nuclear magnetic resonance

PBS:

Phosphate-buffered saline

PCA:

Principal-component analysis

RSD:

Relative standard deviation

SPE:

Solid-phase extraction

SPME:

Solid-phase microextraction

TFC:

Turbulent-flow chromatography

UHPLC:

Ultra-high-performance liquid chromatography

References

  1. Ceglarek U, Leichtle A, Brügel M et al (2009) Challenges and developments in tandem mass spectrometry based clinical metabolomics. Mol Cell Endocrinol 301:266

    Article  CAS  Google Scholar 

  2. Griffiths WJ, Wang Y (2009) Mass spectrometry: from proteomics to metabolomics and lipidomics. Chem Soc Rev 38:1882

    Article  CAS  Google Scholar 

  3. Theodoridis G, Gika HG, Wilson ID (2008) LC–MS-based methodology for global metabolite profiling in metabonomics/metabolomics. Trends Anal Chem 27:251

    Article  CAS  Google Scholar 

  4. Villas-Bôas SG, Mas S, Åkesson M et al (2005) Mass spectrometry in metabolome analysis. Mass Spectrom Rev 24:613

    Article  CAS  Google Scholar 

  5. Bruce SJ, Tavazzi I, Parisod V et al (2009) Investigation of human blood plasma sample preparation for performing metabolomics using ultrahigh performance liquid chromatography/mass spectrometry. Anal Chem 81:3285

    Article  CAS  Google Scholar 

  6. Ryan D, Robards K (2006) Metabolomics: the greatest omics of them all? Anal Chem 78:7954

    Article  CAS  Google Scholar 

  7. Nielsen J, Oliver S (2005) The next wave in metabolome analysis. Trends Biotechnol 23:544

    Article  CAS  Google Scholar 

  8. Dunn WB, Ellis DI (2005) Metabolomics: current analytical platforms and methodologies. Trends Anal Chem 24:285

    Article  CAS  Google Scholar 

  9. Koulman A, Lane GA, Harrison SJ et al (2009) From differentiating metabolites to biomarkers. Anal Bioanal Chem 394:663

    Article  CAS  Google Scholar 

  10. Griffin JL (2006) Understanding mouse models of disease through metabolomics. Curr Opin Chem Biol 10:309

    Article  CAS  Google Scholar 

  11. Griffin JL, Kauppinen RA (2007) Tumour metabolomics in animal models of human cancer. J Proteome Res 6:498

    Article  CAS  Google Scholar 

  12. Robertson DG, Reily MD, Baker JD (2007) Metabonomics in pharmaceutical discovery and development. J Proteome Res 6:526

    Article  CAS  Google Scholar 

  13. Lee SH, Woo HM, Jung BH et al (2007) Metabolomic approach to evaluate the toxicological effects of nonylphenol with rat urine. Anal Chem 79:6102

    Article  CAS  Google Scholar 

  14. Orešič M (2009) Metabolomics, a novel tool for studies of nutrition, metabolism and lipid dysfunction. Nutrition, Metabolism and Cardiovascular Diseases 19:816

    Google Scholar 

  15. Rezzi S, Ramadan Z, Fay LB et al (2007) Nutritional metabonomics: applications and perspectives. J Proteome Res 6:513

    Article  CAS  Google Scholar 

  16. Idborg-Bjorkman H, Edlund P, Kvalheim OM et al (2003) Screening of biomarkers in rat urine using LC/electrospray ionization-MS and two-way data analysis. Anal Chem 75:4784

    Article  CAS  Google Scholar 

  17. Chen C, Gonzalez FJ, Idle JR (2007) LC–MS-based metabolomics in drug metabolism. Drug Metab Rev 39:581

    Article  CAS  Google Scholar 

  18. Buchholz A, Takors R, Wandrey C (2001) Quantification of intracellular metabolites in escherichia coli K12 using liquid chromatographic-electrospray ionization tandem mass spectrometric techniques. Anal Biochem 295:129

    Article  CAS  Google Scholar 

  19. Koulman A, Cao M, Faville M et al (2009) Semi-quantitative and structural metabolic phenotyping by direct infusion ion trap mass spectrometry and its application in genetical metabolomics. Rapid Commun Mass Spectrom 23:2253

    Article  CAS  Google Scholar 

  20. Novotny MV, Soini HA, Mechref Y (2008) Biochemical individuality reflected in chromatographic, electrophoretic and mass-spectrometric profiles. J Chromatogr B 866:26

    Article  CAS  Google Scholar 

  21. Theodoridis GA, Gika HG, Want EJ et al (2012) Liquid chromatography–mass spectrometry based global metabolite profiling: A review. Anal Chim Acta 711:7

    Article  CAS  Google Scholar 

  22. Moco S, Vervoort J, Moco S et al (2007) Metabolomics technologies and metabolite identification. Trends Anal Chem 26:855

    Article  CAS  Google Scholar 

  23. Dunn WB, Bailey NJC, Johnson HE (2005) Measuring the metabolome: current analytical technologies. Analyst (Cambridge, United Kingdom) 130:606

  24. Psychogios N, Hau DD, Peng J et al (2011) The human serum metabolome. PLoS ONE 6:e16957. doi:10.1371/journal.pone.0016957

  25. Boudonck KJ, Mitchell MW, Német L et al (2009) Discovery of metabolomics biomarkers for early detection of nephrotoxicity. Toxicol Pathol 37:280

    Article  CAS  Google Scholar 

  26. Lawton KA, Berger A, Mitchell M et al (2008) Analysis of the adult human plasma metabolome. Pharmacogenomics 9:383

    Article  CAS  Google Scholar 

  27. Büscher JM, Czernik D, Ewald JC et al (2009) Cross-platform comparison of methods for quantitative metabolomics of primary metabolism. Anal Chem 81:2135

    Article  CAS  Google Scholar 

  28. Sreekumar A, Poisson LM, Rajendiran TM et al (2009) Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 457:910

    Article  CAS  Google Scholar 

  29. Álvarez-Sánchez B, Priego-Capote F, Luque de Castro MD (2010) Metabolomics analysis I. Selection of biological samples and practical aspects preceding sample preparation. Trends Anal Chem 29:111

    Google Scholar 

  30. Álvarez-Sánchez B, Priego-Capote F, Luque de Castro MD (2010) Metabolomics analysis II. Preparation of biological samples prior to detection. Trends Anal Chem 29:120

    Google Scholar 

  31. Gika H, Theodoridis G (2011) Sample preparation prior to the LC–MS-based metabolomics/metabonomics of blood-derived samples. Bioanalysis 3:1647

    Article  CAS  Google Scholar 

  32. Teahan O, Gamble S, Holmes E et al (2006) Impact of analytical bias in metabonomic studies of human blood serum and plasma. Anal Chem 78:4307

    Article  CAS  Google Scholar 

  33. Canelas AB, Ten Pierick A, Ras C et al (2009) Quantitative evaluation of intracellular metabolite extraction techniques for yeast metabolomics. Anal Chem 81:7379

    Article  CAS  Google Scholar 

  34. Duportet X, Aggio RBM, Carneiro S et al (2011) The biological interpretation of metabolomic data can be misled by the extraction method used. Metabolomics. doi:10.1007/s11306-011-0324-1

  35. Rammouz RE, Létisse F, Durand S et al (2010) Analysis of skeletal muscle metabolome: evaluation of extraction methods for targeted metabolite quantification using liquid chromatography tandem mass spectrometry. Anal Biochem 398:169

    Article  CAS  Google Scholar 

  36. Bolten CJ, Kiefer P, Letisse F et al (2007) Sampling for metabolome analysis of microorganisms. Anal Chem 79:3843

    Article  CAS  Google Scholar 

  37. Sun G, Yang K, Zhao Z et al (2007) Shotgun metabolomics approach for the analysis of negatively charged water-soluble cellular metabolites from mouse heart tissue. Anal Chem 79:6629

    Article  CAS  Google Scholar 

  38. Deprez S, Sweatman BC, Connor SC et al (2002) Optimisation of collection, storage and preparation of rat plasma for 1H NMR spectroscopic analysis in toxicology studies to determine inherent variation in biochemical profiles. J Pharm Biomed Anal 30:1297

    Article  CAS  Google Scholar 

  39. Rosenling T, Slim CL, Christin C et al (2009) The effect of preanalytical factors on stability of the proteome and selected metabolites in Cerebrospinal Fluid (CSF). J Proteome Res 8:5511

    Article  CAS  Google Scholar 

  40. 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

    Article  CAS  Google Scholar 

  41. van de Merbel NC (2008) Quantitative determination of endogenous compounds in biological samples using chromatographic techniques. Trends Anal Chem 27:924

    Article  CAS  Google Scholar 

  42. Lorenz MA, Burant CF, Kennedy RT (2011) Reducing time and increasing sensitivity in sample preparation for adherent mammalian cell metabolomics. Anal Chem 83:3406

    Article  CAS  Google Scholar 

  43. Kimball E, Rabinowitz JD (2006) Identifying decomposition products in extracts of cellular metabolites. Anal Biochem 358:273

    Article  CAS  Google Scholar 

  44. Vuckovic D, De Lannoy I, Gien B et al (2011) In vivo solid-phase microextraction: capturing the elusive portion of metabolome. Angew Chem Int Ed 50:5344

    Article  CAS  Google Scholar 

  45. Vuckovic D, Gien B, de Lannoy I et al (2011) In vivo solid-phase microextraction for single rodent pharmacokinetics studies of carbamazepine and carbamazpine-10,11-epoxide in mice. J Chromatogr A 1218:3367

    Article  CAS  Google Scholar 

  46. t'Kindt R, Morreel K, Deforce D et al (2009) Joint GC–MS and LC–MS platforms for comprehensive plant metabolomics: repeatability and sample pre-treatment. J Chromatogr B 877:3572

    Article  CAS  Google Scholar 

  47. Bernini P, Bertini I, Luchinat C et al (2011) Standard operating procedures for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR 49:231

    Article  CAS  Google Scholar 

  48. Denery JR, Nunes AAK, Dickerson TJ (2011) Characterization of differences between blood sample matrices in untargeted metabolomics. Anal Chem 83:1040

    Article  CAS  Google Scholar 

  49. Dunn WB, Broadhurst D, Begley P et al (2011) Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nat Protoc 6:1060

    Article  CAS  Google Scholar 

  50. Wedge DC, Allwood JW, Dunn W et al (2011) Is serum or plasma more appropriate for intersubject comparisons in metabolomic studies? An assessment in patients with small-cell lung cancer. Anal Chem 83:6689

    CAS  Google Scholar 

  51. Yu Z, Kastenmüller G, He Y et al (2011) Differences between human plasma and serum metabolite profiles. PLoS ONE 6(7):e21230. doi:10.1371/journal.pone.0021230

  52. Brauer R, Leichtle AB, Fiedler GM et al (2011) Preanalytical standardization of amino acid and acylcarnitine metabolite profiling in human blood using tandem mass spectrometry. Metabolomics 7:344

    Article  CAS  Google Scholar 

  53. Pereira H, Martin JF, Joly C et al (2010) Development and validation of a UPLC/MS method for a nutritional metabolomic study of human plasma. Metabolomics 6:207

    Google Scholar 

  54. Bando K, Kawahara R, Kunimatsu T et al (2010) Influences of biofluid sample collection and handling procedures on GC–MS based metabolomic studies. J Biosci Bioeng 110:491

    Article  CAS  Google Scholar 

  55. Vuckovic D, Pawliszyn J (2011) Systematic evaluation of solid-phase microextraction coatings for untargeted metabolomic profiling of biological fluids by liquid chromatography-mass spectrometry. Anal Chem 83:1944

    Article  CAS  Google Scholar 

  56. Bruce SJ, Jonsson P, Antti H et al (2008) Evaluation of a protocol for metabolic profiling studies on human blood plasma by combined ultra-performance liquid chromatography/mass spectrometry: From extraction to data analysis. Anal Biochem 372:237

    Article  CAS  Google Scholar 

  57. Tuck MK, Chan DW, Chia D et al (2009) Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group. J Proteome Res 8:113

    Article  CAS  Google Scholar 

  58. Chang MS, Ji Q, Zhang J et al (2007) Historical review of sample preparation for chromatographic bioanalysis: Pros and cons. Drug Dev Res 68:107

    Article  CAS  Google Scholar 

  59. Gika HG, Macpherson E, Theodoridis GA et al (2008) Evaluation of the repeatability of ultra-performance liquid chromatography–TOF-MS for global metabolic profiling of human urine samples. J Chromatogr B 871:299

    Article  CAS  Google Scholar 

  60. Want EJ, Wilson ID, Gika H et al (2010) Global metabolic profiling procedures for urine using UPLC–MS. Nat Protoc 5:1005

    Article  CAS  Google Scholar 

  61. Wishart DS, Lewis MJ, Morrissey JA et al (2008) The human cerebrospinal fluid metabolome. J Chromatogr B 871:164

    Article  CAS  Google Scholar 

  62. Stoop MP, Coulier L, Rosenling T et al (2010) Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples. Mol Cell Proteomics 9:2063

    Article  CAS  Google Scholar 

  63. Crews B, Wikoff WR, Patti GJ et al (2009) Variability analysis of human plasma and cerebral spinal fluid reveals statistical significance of changes in mass spectrometry-based metabolomics data. Anal Chem 81:8538

    Article  CAS  Google Scholar 

  64. 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: Anal Tech Biomed Life Sci 785:263

    Article  CAS  Google Scholar 

  65. Want EJ, O'Maille G, Smith CA et al (2006) Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Anal Chem 78:743

    Article  CAS  Google Scholar 

  66. Michopoulos F, Lai L, Gika H et al (2009) UPLC–MS-based analysis of human plasma for metabonomics using solvent precipitation or solid phase extraction. J Proteome Res 8:2114

    Article  CAS  Google Scholar 

  67. Zelena E, Dunn WB, Broadhurst D et al (2009) Development of a robust and repeatable UPLC - MS method for the long-term metabolomic study of human serum. Anal Chem 81:1357

    Article  CAS  Google Scholar 

  68. Pesek JJ, Matyska MT, Loo JA et al (2009) Analysis of hydrophilic metabolites in physiological fluids by HPLC–MS using a silica hydride-based stationary phase. J Sep Sci 32:2200

    Article  CAS  Google Scholar 

  69. Courant F, Pinel G, Bichon E et al (2009) Development of a metabolomic approach based on liquid chromatography-high resolution mass spectrometry to screen for clenbuterol abuse in calves. Analyst 134:1637

    Article  CAS  Google Scholar 

  70. Khin TM, Uehara T, Aoshima K et al (2009) Polar anionic metabolome analysis by nano-LC/MS with a metal chelating agent. Anal Chem 81:7766

    Article  CAS  Google Scholar 

  71. Graça G, Duarte IF, Goodfellow BJ et al (2008) Metabolite profiling of human amniotic fluid by hyphenated nuclear magnetic resonance spectroscopy. Anal Chem 80:6085

    Article  CAS  Google Scholar 

  72. Darghouth D, Koehl B, Madalinski G et al (2011) Pathophysiology of sickle cell disease is mirrored by the red blood cell metabolome. Blood 117:e57

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  74. Lee R, Britz-McKibbin P (2009) Differential rates of glutathione oxidation for assessment of cellular redox status and antioxidant capacity by capillary electrophoresis-mass spectrometry: an elusive biomarker of oxidative stress. Anal Chem 81:7047

    Article  CAS  Google Scholar 

  75. Rezzi S, Vera FA, Martin F-J et al (2008) Automated SPE-RP-HPLC fractionation of biofluids combined to off-line NMR spectroscopy for biomarker identification in metabonomics. J Chromatogr B: Anal Tech Biomed Life Sci 871:271

    Article  CAS  Google Scholar 

  76. Giavalisco P, Hummel J, Lisec J et al (2008) High-resolution direct infusion-based mass spectrometry in combination with whole 13C metabolome isotope labeling allows unambiguous assignment of chemical sum formulas. Anal Chem 80:9417

    Article  CAS  Google Scholar 

  77. Cubbon S, Bradbury T, Wilson J et al (2007) Hydrophilic interaction chromatography for mass spectrometric metabonomic studies of urine. Anal Chem 79:8911

    Article  CAS  Google Scholar 

  78. Evans AM, DeHaven CD, Barrett T et al (2009) Integrated, nontargeted ultrahigh performance liquid chromatography/ electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal Chem 81:6656

    Article  CAS  Google Scholar 

  79. Yin P, Zhao X, Li Q et al (2006) Metabonomics study of intestinal fistulas based on ultraperformance liquid chromatography coupled with Q-TOF mass spectrometry (UPLC/Q-TOF MS). J Proteome Res 5:2135

    Article  CAS  Google Scholar 

  80. Wikoff WR, Anfora AT, Liu J et al (2009) Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc Natl Acad Sci U S A 106:3698

    Google Scholar 

  81. Minami Y, Kasukawa T, Kakazu Y et al (2009) Measurement of internal body time by blood metabolomics. Proc Natl Acad Sci U S A 106:9890

    Google Scholar 

  82. Sheikh KD, Khanna S, Byers SW et al (2011) Small molecule metabolite extraction strategy for improving LC/MS detection of cancer cell metabolome. J Biomol techniques: JBT 22:1

    Google Scholar 

  83. Dunn WB, Broadhurst D, Brown M et al (2008) Metabolic profiling of serum using Ultra Performance Liquid Chromatography and the LTQ-Orbitrap mass spectrometry system. J Chromatogr B 871:288

    Article  CAS  Google Scholar 

  84. Geier FM, Want EJ, Leroi AM et al (2011) Cross-platform comparison of Caenorhabditis elegans tissue extraction strategies for comprehensive metabolome coverage. Anal Chem 83:3730

    Article  CAS  Google Scholar 

  85. Dunn WB, Brown M, Worton SA et al (2011) The metabolome of human placental tissue: investigation of first trimester tissue and changes related to preeclampsia in late pregnancy. Metabolomics:1. doi:10.1007/s11306-011-0348-6

  86. Williams J, Wood J, Pandarinathan L et al (2007) Quantitative method for the profiling of the endocannabinoid metabolome by LC-atmospheric pressure chemical ionization-MS. Anal Chem 79:5582

    Article  CAS  Google Scholar 

  87. Masson P, Spagou K, Nicholson JK et al (2011) Technical and biological variation in UPLC–MS-based untargeted metabolic profiling of liver extracts: application in an experimental toxicity study on galactosamine. Anal Chem 83:1116

    Article  CAS  Google Scholar 

  88. Masson P, Alves AC, Ebbels TMD et al (2010) Optimization and evaluation of metabolite extraction protocols for untargeted metabolic profiling of liver samples by UPLC–MS. Anal Chem 82:7779

    Article  CAS  Google Scholar 

  89. Čuperlović-Culf M, Da B, Culf AS et al (2010) Cell culture metabolomics: applications and future directions. Drug Discov Today 15:610

    Article  CAS  Google Scholar 

  90. Croixmarie V, Umbdenstock T, Cloarec O et al (2009) Integrated comparison of drug-related and drug-induced ultra performance liquid chromatography/mass spectrometry metabonomic profiles using human hepatocyte cultures. Anal Chem 81:6061

    Article  CAS  Google Scholar 

  91. Coulier L, Bas R, Jespersen S et al (2006) Simultaneous quantitative analysis of metabolites using ion-pair liquid chromatography-electrospray ionization mass spectrometry. Anal Chem 78:6573

    Article  CAS  Google Scholar 

  92. Sellick CA, Hansen R, Maqsood AR et al (2009) Effective quenching processes for physiologically valid metabolite profiling of suspension cultured mammalian cells. Anal Chem 81:174

    Article  CAS  Google Scholar 

  93. Shin MH, Lee DY, Liu K et al (2010) Evaluation of sampling and extraction methodologies for the global metabolic profiling of Saccharophagus degradans. Anal Chem 82:6660

    Article  CAS  Google Scholar 

  94. Dietmair S, Timmins NE, Gray PP et al (2010) Towards quantitative metabolomics of mammalian cells: development of a metabolite extraction protocol. Anal Biochem 404:155

    Article  CAS  Google Scholar 

  95. Teng Q, Huang W, Collette TW et al (2009) A direct cell quenching method for cell-culture based metabolomics. Metabolomics 5:199

    Article  CAS  Google Scholar 

  96. Price KE, Larive CK, Lunte CE (2009) Tissue-targeted metabonomics: biological considerations and application to doxorubicin-induced hepatic oxidative stress. Metabolomics 5:219

    Article  CAS  Google Scholar 

  97. Price KE, Lunte CE, Larive CK (2008) Development of tissue-targeted metabonomics. Part 1. Analytical considerations. J Pharm Biomed Anal 46:737

    Article  CAS  Google Scholar 

  98. Wibom C, Surowiec I, Mörén L et al (2010) Metabolomic patterns in glioblastoma and changes during radiotherapy: a clinical microdialysis study. J Proteome Res 9:2909

    Article  CAS  Google Scholar 

  99. Hrydziuszko O, Silva MA, Perera MTPR et al (2010) Application of metabolomics to investigate the process of human orthotopic liver transplantation: a proof-of-principle study. OMICS A J Integrative Biol 14:143

    Article  CAS  Google Scholar 

  100. Vuckovic D, Risticevic S, Pawliszyn J (2011) In vivo solid-phase microextraction in metabolomics: opportunities for the direct investigation of biological systems. Angew Chem Int Ed 50:5618

    Article  CAS  Google Scholar 

  101. Ouyang G, Vuckovic D, Pawliszyn J (2011) Nondestructive sampling of living systems using in vivo solid-phase microextraction. Chem Rev 111:2784

    Article  CAS  Google Scholar 

  102. Lord HL, Zhang X, Musteata FM et al (2011) In vivo solid-phase microextraction for monitoring intravenous concentrations of drugs and metabolites. Nat Protoc 6:896

    Article  CAS  Google Scholar 

  103. Lord HL, Grant RP, Walles M et al (2003) Development and evaluation of a solid-phase microextraction probe for in vivo pharmacokinetic studies. Anal Chem 75:5103

    Article  CAS  Google Scholar 

  104. Michopoulos F, Edge AM, Theodoridis G et al (2010) Application of turbulent-flow chromatography to the metabonomic analysis of human plasma: comparison with protein precipitation. J Sep Sci 33:1472

    Article  CAS  Google Scholar 

  105. Kong ST, Lin H, Ching J et al (2011) Evaluation of dried blood spots as sample matrix for gas chromatography/mass spectrometry based metabolomic profiling. Anal Chem 83:4314

    Article  CAS  Google Scholar 

  106. Wilson I (2011) Global metabolic profiling (metabonomics/metabolomics) using dried blood spots: advantages and pitfalls. Bioanalysis 3:2255

    Article  CAS  Google Scholar 

  107. Michopoulos F, Theodoridis G, Smith CJ et al (2010) Metabolite profiles from dried biofluid spots for metabonomic studies using UPLC combined with oaToF-MS. J Proteome Res 9:3328

    Article  CAS  Google Scholar 

  108. O’Mara M, Hudson-Curtis B, Olson K et al (2012) The effect of hematocrit and punch location on assay bias during quantitative bioanalysis of dried blood spot samples. Bioanalysis 4:2335

    Google Scholar 

  109. Michopoulos F, Theodoridis G, Smith CJ et al (2011) Metabolite profiles from dried blood spots for metabonomic studies using UPLC combined with orthogonal acceleration ToF-MS: effects of different papers and sample storage stability. Bioanalysis 3:2757

    Google Scholar 

  110. Stahnke H, Kittlaus S, Kempe G et al (2012) Reduction of matrix effects in LC-ESI-MS by dilution of the sample extracts: how much dilution is needed. Anal Chem 84:1474

    Google Scholar 

  111. Lafaye A, Labarre J, Tabet J et al (2005) Liquid chromatography–mass spectrometry and 15N metabolic labeling for quantitative metabolic profiling. Anal Chem 77:2026

    Article  CAS  Google Scholar 

  112. Giavalisco P, Köhl K, Hummel J et al (2009) 13C isotope-labeled metabolomes allowing for improved compound annotation and relative quantification in liquid chromatography–mass spectrometry-based metabolomic research. Anal Chem 81:6546

    Article  CAS  Google Scholar 

  113. Vuckovic D, Shirey R, Chen Y et al (2009) In vitro evaluation of new biocompatible coatings for solid-phase microextraction: implications for drug analysis and in vivo sampling applications. Anal Chim Acta 638:175

    Article  CAS  Google Scholar 

  114. Guo K, Peng J, Zhou R et al (2011) Ion-pairing reversed-phase liquid chromatography fractionation in combination with isotope labeling reversed-phase liquid chromatography–mass spectrometry for comprehensive metabolome profiling. J Chromatogr A 1218:3689

    Article  CAS  Google Scholar 

  115. Lindon JC, Nicholson JK, Holmes E et al (2005) Summary recommendations for standardization and reporting of metabolic analyses. Nat Biotechnol 23:833

    Article  CAS  Google Scholar 

  116. Sangster T, Major H, Plumb R et al (2006) A pragmatic and readily implemented quality control strategy for HPLC–MS and GC–MS-based metabonomic analysis. Analyst 131:1075

    Article  CAS  Google Scholar 

  117. Smilde AK, Van Der Werf MJ, Schaller J et al (2009) Characterizing the precision of mass-spectrometry-based metabolic profiling platforms. Analyst 134:2281

    Article  CAS  Google Scholar 

  118. Koek MM, Jellema RH, van der Greef J et al (2011) Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives. Metabolomics 7:307

    Article  CAS  Google Scholar 

  119. Chen C, Krausz KW, Shah YM et al (2009) Serum metabolomics reveals irreversible inhibition of fatty acid β-oxidation through the suppression of PPARα activation as a contributing mechanism of acetaminophen-induced hepatotoxicity. Chem Res Toxicol 22:699

    Article  CAS  Google Scholar 

  120. Qiu Y, Cai G, Su M et al (2009) Serum metabolite profiling of human colorectal cancer using GC-TOFMS and UPLC-QTOFMS. J Proteome Res 8:4844

    Article  CAS  Google Scholar 

  121. Want EJ, Nordström A, Morita H et al (2007) From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics. J Proteome Res 6:459

    Article  CAS  Google Scholar 

  122. Nordstrom A, Want E, Northen T et al (2008) Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics. Anal Chem 80:421

    Article  CAS  Google Scholar 

  123. Gao P, Lu C, Zhang F et al (2008) Integrated GC–MS and LC–MS plasma metabonomics analysis of ankylosing spondylitis. Analyst 133:1214

    Article  CAS  Google Scholar 

  124. Koulman A, Woffendin G, Narayana VK et al (2009) High-resolution extracted ion chromatography, a new tool for metabolomics and lipidomics using a second-generation Orbitrap mass spectrometer. Rapid Commun Mass Spectrom 23:1411

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street Room 940, Toronto, M5S 3E1, Canada

    Dajana Vuckovic

Authors
  1. Dajana Vuckovic
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Dajana Vuckovic.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Vuckovic, D. Current trends and challenges in sample preparation for global metabolomics using liquid chromatography–mass spectrometry. Anal Bioanal Chem 403, 1523–1548 (2012). https://doi.org/10.1007/s00216-012-6039-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-012-6039-y

Keywords