We use cookies to improve your experience. By continuing to browse this site, you accept our cookie policy.×
Research Article

Systematic evaluation of serum and plasma collection on the endogenous metabolome

    Zhi Zhou

    State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China

    ,
    Yanhua Chen

    *Author for correspondence:

    E-mail Address: chenyanhua@imm.ac.cn

    State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China

    ,
    Jiuming He

    State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China

    ,
    Jing Xu

    State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China

    ,
    Ruiping Zhang

    State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China

    ,
    Yan Mao

    Xinjiang Institute of Materia Medica, Urumqi 830004, China

    &
    Zeper Abliz

    State Key Laboratory of Bioactive Substance & Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100050, China

    Minzu University of China, Beijing 100081, P. R. China

    Published Online:https://doi.org/10.4155/bio-2016-0078

    Aim: In metabolomics research, the use of different blood collection methods may influence endogenous metabolites. Materials & methods: Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants. Results: Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma.

    Papers of special note have been highlighted as: • of interest; •• of considerable interest

    References

    • 1 Xu J, Chen Y, Zhang R et al. Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers. Mol. Cell. Proteomics 12(5), 1306–1318 (2013).
    • 2 Pan Z, Gu H, Talaty N et al. Principal component analysis of urine metabolites detected by NMR and DESI–MS in patients with inborn errors of metabolism. Anal. Bioanal. Chem. 387(2), 539–549 (2007).
    • 3 Fava F, Lovegrove JA, Gitau R et al. The gut microbiota and lipid metabolism: implications for human health and coronary heart disease. Curr. Med. Chem. 13(25), 3005–3021 (2006).
    • 4 Donald GR, Michael DR, J DB. Metabonomics in pharmaceutical discovery and development. J. Proteome Res. 6(2), 526–539 (2007).
    • 5 Schnackenberg LK, Beger RD. Monitoring the health to disease continuum with global metabolic profiling and systems biology. Pharmacogenomics 7(7), 1077–1086 (2006).
    • 6 Rezzi S, Ramadan Z, Martin FP. Human metabolic phenotypes link directly to specific dietary preferences in healthy individuals. J. Proteome Res. 6(11), 4469–4477 (2007).
    • 7 Issaq HJ, Xiao Z, Veenstra TD. Serum and plasma proteomics. Chem. Rev. 107(8), 3601–3620 (2007).
    • 8 Kronenberg F, Trenkwalder E, Kronenberg MF, König P, Utermann G, Dieplinger H. Influence of hematocrit on the measurement of lipoproteins demonstrated by an example of lipoprotein(a). Kidney Int. 54, 1385–1389 (1998).
    • 9 Tripisciano C, Leistner A, Linsberger I, Leistner A, Falkenhagen D, Weber V. Effect of anticoagulation with citrate versus heparin on the adsorption of coagulation factors to blood purification resins with different charge. Biomacromolecules 13(2), 484–488 (2012).
    • 10 Yu Z, Kastenmüller G, He Y et al. Differences between human plasma and serum profiles. PLoS ONE 6(7), e21230 (2011).
    • 11 Barri T, Dragsted LO. UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: effect of experimental artefacts and anticoagulant. Anal. Chim. Acta 768, 118–128 (2013). •• Compared the differences on metabolomes of serum, heparin plasma, EDTA plasma and citrate plasma based on MS.
    • 12 Skov K, Hadrup N, Smedsgaard J, Frandsen H. LC–MS analysis of the plasma metabolome – a novel sample preparation strategy. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. doi:10.1016/j.jchromb.2014.11.033 (2015) (Epub ahead of print).
    • 13 Basu D, Kulkarni R. Overview of blood components and their preparation. Indian J. Anaesth. 58(5), 529–537 (2014).
    • 14 Michopoulos F, Lai L, Gika H, Theodoridis G, Wilson I. UPLC–MS-based analysis of human plasma for metabonomics using solvent precipitation or solid phase extraction. J. Proteome Res. 8(4), 2114–2121 (2009).
    • 15 Tulipani S, Llorach R, Urpi-Sarda M, Andres-Lacueva C. Comparative analysis of sample preparation methods to handle the complexity of the blood fluid metabolome: when less is more. Anal. Chem. 85(1), 341–348 (2013).
    • 16 Yang W, Chen Y, Xi C et al. Liquid chromatography-tandem mass spectrometry-based plasma metabonomics delineate the effect of metabolites’ stability on reliability of potential biomarkers. Anal. Chem. 85(5), 2606–2610 (2013).
    • 17 Yan R, Colantonio D, Wong PY, Chen Y. Suitability of Becton Dickinson Vacutainer rapid serum tube for collecting and storing blood samples for antibiotic and anticonvulsant drug monitoring. J. Clin. Pathol. 67(9), 807–810 (2014).
    • 18 Gislefoss RE, Grimsrud TK, Mørkrid L. Stability of selected serum hormones and lipids after long-term storage in the Janus Serum Bank. Clin. Biochem. 48(6), 364–369 (2015).
    • 19 Tammen H, Schulte I, Hess R et al. Peptidomic analysis of human blood specimens: comparison between plasma specimens and serum by differential peptide display. Proteomics 5(13), 3414–3422 (2005).
    • 20 Hsieh SY, Chen RK, Pan YH, Lee HL. Systematical evaluation of the effects of sample collection procedures on low-molecular-weight serum/plasma proteome profiling. Proteomics 6(10), 3189–3198 (2006).
    • 21 Ladenson JH, Tsai LM, Michael JM, Kessler G, Joist JH. Serum versus heparinized plasma for eighteen common chemistry tests: is serum the appropriate specimen? Am. J. Clin. Pathol. 62(4), 545–552 (1974).
    • 22 Miles RR, Roberts RF, Putnam AR, Roberts WL. Comparison of serum and heparinized plasma samples for measurement of chemistry. Clin. Chem. 50(9), 1704–1706 (2004).
    • 23 Liu L, Aa J, Wang G et al. Differences in metabolite profile between blood plasma and serum. Anal. Biochem. 406(2), 105–112 (2010).
    • 24 Drake SK, Bowen RA, Remaley AT, Hortin GL. Potential interferences from blood collection tubes in mass spectrometric analyses of serum polypeptides. Clin. Chem. 50(12), 2398–2401 (2004). • The authors found that polymer gel in a serum collection tube will shed in samples and be detected as peaks with a constant m/z interval.
    • 25 Pereira H, Martin JF, Joly C, Sébédio JL, Pujos-Guillot E. Development and validation of a UPLC/MS method for a nutritional metabolomic study of human plasma. Metabolomics 6(2), 207–218 (2010).
    • 26 Bando K, Kawahara R, Kunimatsu T et al. Influences of biofluid sample collection and handling procedures on GC–MS based metabolomic studies. J. Biosci. Bioeng. 110(4), 491–499 (2010).
    • 27 Vuckovic D, Pawliszyn J. Systematic evaluation of solid-phase microextraction coatings for untargeted metabolomic profiling of biological fluids by liquid chromatography–mass spectrometry. Anal. Chem. 83(6), 1944–1954 (2011).
    • 28 Brown M, Dunn WB, Dobson P et al. Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. Analyst 134(7), 1322–1332 (2009).
    • 29 Teahan O, Gamble S, Holmes E et al. Impact of analytical bias in metabonomic studies of human blood serum and plasma. Anal. Chem. 78(13), 4307–4318 (2006). • Compared the metabolomics profiling between serum and heparin plasma based on NMR spectroscopy. Further, the authors investigate the effect of serum clot condition and freeze–thawing circle.
    • 30 Teerlink T, Nijveldt RJ, de Jong S, van Leeuwen PA. Determination of arginine, asymmetric dimethylarginine and symmetric dimethylarginine in human plasma and other biological samples by high-performance liquid chromatography. Anal. Biochem. 303(2), 131–137 (2002).
    • 31 Bruce SJ, Jonsson P, Antti H et al. 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(2), 237–249 (2008).
    • 32 Gika HG, Theodoridis GA, Wingate JE, Wilson ID. Within-day reproducibility of an HPLC–MS-based method for metabonomic analysis: application to human urine. J. Proteome Res. 6(8), 3291–3303 (2007).
    • 33 Kamleh MA, Ebbels TM, Spagou K, Masson P, Want EJ. Optimizing the use of quality control samples for signal drift correction in large-scale urine metabolic profiling studies. Anal. Chem. 84(6), 2670–2677 (2012).
    • 34 van den Berg RA, Hoefsloot HC, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling and transformations: improving the biological information content of metabolomics data. BMC Genomics 7, 142–155 (2006).
    • 35 Sumner LW, Amberg A, Barrett D et al. Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 3(3), 211–221 (2007).
    • 36 Yin P, Peter A, Franken H et al. Preanalytical aspects and sample quality assessment in metabolomics studies of human blood. Clin. Chem. 59(5), 833–845 (2013).
    • 37 Banks RE, Stanley AJ, Cairns DA et al. Influences of blood sample processing on low-molecular-weight proteome identified by surface-enhanced laser desorption/ionization mass spectrometry. Clin. Chem. 51(9), 1637–1649 (2005).
    • 38 Bowen RA, Chan Y, Cohen J et al. Effect of blood collection tubes on total triiodothyronine and other laboratory assays. Clin. Chem. 51(2), 424–433 (2005).
    • 39 Karppi J, Akerman KK, Parviainen M. Suitability of collection tubes with separator gels for collecting and storing blood samples for therapeutic drug monitoring (TDM). Clin. Chem. Lab. Med. 38(4), 313–320 (2000).
    • 40 Jørgenrud B, Jäntti S, Mattila I et al. The influence of sample collection methodology and sample preprocessing on the blood metabolic profile. Bioanalysis 7(8), 991–1006 (2015). •• Investigated the differences among serum, citrate plasma and EDTA plasma on polar metabolites and lipids by GC × GC–TOF MS and ultra HPLC–TOF MS, respectively.
    • 41 Mei H, Hsieh Y, Nardo C et al. Investigation of matrix effects in bioanalytical high performance liquid chromatography/tandem mass spectrometric assays: application to drug discovery. Rapid Commun. Mass Spectrom. 17(1), 97–103 (2003).
    • 42 Hsu FF, Turk J. Characterization of phosphatidylethanolamine as a lithiated adduct by triple quadrupole tandem mass spectrometry with electrospray ionization. J. Am. Soc. Mass Spectrom. 35(5), 595–606 (2000).
    • 43 Hsu FF, Turk J. Structural characterization of triacylglycerols as lithiated adducts by electrospray ionization mass spectrometry using low-energy collisionally activated dissociation on a triple stage quadrupole instrument. J. Am. Soc. Mass Spectrom. 10(7), 587–599 (1999).
    • 44 Cubero Herrera L, Ramaley L, Potvin MA et al. A method for determining regioisomer abundances of polyunsaturated triacylglycerols in omega-3 enriched fish oils using reversed-phase liquid chromatography and triple-stage mass spectrometry. Food Chem. 139(1–4), 655–662 (2013).