Oral Biology pp 79-105 | Cite as

NMR-Based Metabolomics of Oral Biofluids

  • Horst Joachim SchirraEmail author
  • Pauline J. Ford
Part of the Methods in Molecular Biology book series (MIMB, volume 1537)


NMR-based metabolomics is an established technique for characterizing the metabolite profile of biological fluids and investigating how metabolite profiles change in response to biological and/or clinical stimuli. Thus, NMR-based metabolomics has the potential to discover biomarkers for diagnosis, prognosis, and/or therapy of clinical conditions, as well as to unravel the physiology underlying clinical conditions. Here, we describe a detailed protocol for NMR-based metabolomics of oral biofluids, including sample collection, sample handling, NMR data acquisition, and processing. In addition, we give a general overview of the statistical analysis of the resulting metabolomic data.

Key words

Metabolomics Systems biology NMR spectroscopy Saliva Gingival crevicular fluid 



We gratefully acknowledge Dr Shaneen Leishman for assistance in refining the collection methods. We are grateful to Dr Emma Broughton and Dr Rachel Dunn for preparing and analyzing the saliva and GCF samples used for Fig. 2. NMR spectra for Fig. 2 were measured at the University of Queensland’s 900 MHz spectrometer, which is part of the Queensland NMR Network (QNN), and the authors acknowledge financial support provided by the Queensland State Government to the Queensland NMR Network facilities at The University of Queensland. We wish to thank Dr Gregory Pierens for critical reading of the manuscript and helpful advice.


  1. 1.
    Fiehn O (2002) Metabolomics—the link between genotypes and phenotypes. Plant Mol Biol 48:155–171CrossRefPubMedGoogle Scholar
  2. 2.
    Nicholson JK, Lindon JC, Holmes E (1999) “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29:1181–1189CrossRefPubMedGoogle Scholar
  3. 3.
    Aurich MK, Thiele I (2016)Computational modeling of human metabolism and its application to systems biomedicine. In: Schmitz U, Wolkenhauer O (eds) Systems medicine, pp 253-281Google Scholar
  4. 4.
    Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD (2009) Analytical and statistical approaches to metabolomics research. J Sep Sci 32:2183–2199CrossRefPubMedGoogle Scholar
  5. 5.
    Shepherd LVT, Fraser P, Stewart D (2011) Metabolomics: a second-generation platform for crop and food analysis. Bioanalysis 3:1143–1159CrossRefPubMedGoogle Scholar
  6. 6.
    Shulaev V (2006) Metabolomics technology and bioinformatics. Brief Bioinform 7:128–139CrossRefPubMedGoogle Scholar
  7. 7.
    Zhang AH, Sun H, Wang P, Han Y, Wang XJ (2012) Modern analytical techniques in metabolomics analysis. Analyst 137:293–300CrossRefPubMedGoogle Scholar
  8. 8.
    Gebregiworgis T, Powers R (2012) Application of NMR metabolomics to search for human disease biomarkers. Comb Chem High Throughput Screen 15:595–610CrossRefPubMedGoogle Scholar
  9. 9.
    Emwas AHM, Salek RM, Griffin JL, Merzaban J (2013) NMR-based metabolomics in human disease diagnosis: applications, limitations, and recommendations. Metabolomics 9:1048–1072CrossRefGoogle Scholar
  10. 10.
    Bertram HC, Eggers N, Eller N (2009) Potential of human saliva for nuclear magnetic resonance-based metabolomics and for health-related biomarker identification. Anal Chem 81:9188–9193CrossRefPubMedGoogle Scholar
  11. 11.
    Takeda I, Stretch C, Barnaby P, Bhatnager K, Rankin K, Fu H, Weljie A, Jha N, Slupsky C (2009) Understanding the human salivary metabolome. NMR Biomed 22:577–584CrossRefPubMedGoogle Scholar
  12. 12.
    Aimetti M, Cacciatore S, Graziano A, Tenori L (2012) Metabonomic analysis of saliva reveals generalized chronic periodontitis signature. Metabolomics 8:465–474CrossRefGoogle Scholar
  13. 13.
    Klukowska M, Goyal CR, Khambe D, Cannon M, Miner M, Gurich N, Circello B, Huggins T, Barker ML, Furnish C, Conde E, Hoke P, Haught C, Xie SC, White DJ (2015) Response of chronic gingivitis to hygiene therapy and experimental gingivitis. Clinical, microbiological and metabonomic changes. Am J Dent 28:273–284PubMedGoogle Scholar
  14. 14.
    Fidalgo TKS, Freitas-Fernandes LB, Angeli R, Muniz AMS, Gonsalves E, Santos R, Nadal J, Almeida FCL, Valente AP, Souza IPR (2013) Salivary metabolite signatures of children with and without dental caries lesions. Metabolomics 9:657–666CrossRefGoogle Scholar
  15. 15.
    Fidalgo TKS, Freitas-Fernandes LB, Almeida FCL, Valente AP, Souza IPR (2015) Longitudinal evaluation of salivary profile from children with dental caries before and after treatment. Metabolomics 11:583–593CrossRefGoogle Scholar
  16. 16.
    Lemanska A, Grootveld M, Silwood CJL, Brereton RG (2012) Chemometric variance analysis of 1H NMR metabolomics data on the effects of oral rinse on saliva. Metabolomics 8:S64–S80Google Scholar
  17. 17.
    Lloyd GR, Wongravee K, Silwood CJL, Grootveld M, Brereton RG (2009) Self Organising Maps for variable selection: application to human saliva analysed by nuclear magnetic resonance spectroscopy to investigate the effect of an oral healthcare product. Chemometr Intell Lab Syst 98:149–161CrossRefGoogle Scholar
  18. 18.
    Misawa T, Date Y, Kikuchi J (2015) Human metabolic, mineral, and microbiota fluctuations across daily nutritional intake visualized by a data-driven approach. J Proteome Res 14:1526–1534CrossRefPubMedGoogle Scholar
  19. 19.
    Walsh MC, Brennan L, Malthouse JPG, Roche HM, Gibney MJ (2006) Effect of acute dietary standardization on the urinary, plasma, and salivary metabolomic profiles of healthy humans. Am J Clin Nutr 84:531–539PubMedGoogle Scholar
  20. 20.
    Neyraud E, Tremblay-Franco M, Gregoire S, Berdeaux O, Canlet C (2013) Relationships between the metabolome and the fatty acid composition of human saliva; effects of stimulation. Metabolomics 9:213–222CrossRefGoogle Scholar
  21. 21.
    Mounayar R, Morzel M, Brignot H, Tremblay-Franco M, Canlet C, Lucchi G, Ducoroy P, Feron G, Neyraud E (2014) Nutri-metabolomics applied to taste perception phenotype: human subjects with high and low sensitivity to taste of fat differ in salivary response to oleic acid. OMICS J Integrat Biol 18:666–672Google Scholar
  22. 22.
    Mounayar R, Morzel M, Brignot H, Tremblay-Franco M, Canlet C, Lucchi G, Ducoroy P, Feron G, Neyraud E (2014) Salivary markers of taste sensitivity to oleic acid: a combined proteomics and metabolomics approach. Metabolomics 10:688–696CrossRefGoogle Scholar
  23. 23.
    Santone C, Dinallo V, Paci M, D'Ottavio S, Barbato G, Bernardini S (2014) Saliva metabolomics by NMR for the evaluation of sport performance. J Pharm Biomed Anal 88:441–446CrossRefPubMedGoogle Scholar
  24. 24.
    de Laurentiis G, Paris D, Melck D, Maniscalco M, Marsico S, Corso G, Motta A, Sofia M (2008) Metabonomic analysis of exhaled breath condensate in adults by nuclear magnetic resonance spectroscopy. Eur Respir J 32:1175–1183CrossRefPubMedGoogle Scholar
  25. 25.
    Beckonert O, Keun HC, Ebbels TMD, Bundy JG, Holmes E, Lindon JC, Nicholson JK (2007) Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc 2:2692–2703CrossRefPubMedGoogle Scholar
  26. 26.
    Dona AC, Jiménez B, Schäfer H, Humpfer E, Spraul M, Lewis MR, Pearce JTM, Holmes E, Lindon JC, Nicholson JK (2014) Precision high-throughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping. Anal Chem 86:9887–9894Google Scholar
  27. 27.
    Eliasson M, Rannar S, Trygg J (2011) From data processing to multivariate validation—essential steps in extracting interpretable information from metabolomics data. Curr Pharm Biotechnol 12:996–1004CrossRefPubMedGoogle Scholar
  28. 28.
    Roberts MJ, Schirra HJ, Lavin MF, Gardiner RA (2014) NMR-based metabolomics: global analysis of metabolites to address problems in prostate cancer. In: iConcept Press (ed) Cervical, breast and prostate cancer. iConcept Press, Tokwawan, Kowloon, Hong Kong, pp 1–43Google Scholar
  29. 29.
    Trygg J, Gullberg J, Johansson AI, Jonsson P, Moritz T (2006) Chemometrics in metabolomics—an introduction. In: Saito K, Dixon RA, Willmitzer L (eds) Plant metabolomics. pp 117–128Google Scholar
  30. 30.
    Griffiths GS (2003) Formation, collection and significance of gingival crevice fluid. Periodontology 2000(31):32–42CrossRefGoogle Scholar
  31. 31.
    Henson BS, Wong DT (2010) Collection, storage, and processing of saliva samples for downstream molecular applications. In: Seymour GJ, Cullinan MP, Heng NCK (eds) Oral biology: molecular techniques and applications, pp 21–30Google Scholar
  32. 32.
    Akoka S, Barantin L, Trierweiler M (1999) Concentration measurement by proton NMR using the ERETIC method. Anal Chem 71:2554–2557CrossRefPubMedGoogle Scholar
  33. 33.
    Silvestre V, Goupry S, Trierweiler M, Robins R, Akoka S (2001) Determination of substrate and product concentrations in lactic acid bacterial fermentations by proton NMR using the ERETIC method. Anal Chem 73:1862–1868CrossRefPubMedGoogle Scholar
  34. 34.
    Clos LJ, Jofre MF, Ellinger JJ, Westler WM, Markley JL (2013) NMRbot: Python scripts enable high-throughput data collection on current Bruker BioSpin NMR spectrometers. Metabolomics 9:558–563CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Euceda LR, Giskeødegård GF, Bathen TF (2015) Preprocessing of NMR metabolomics data. Scand J Clin Lab Investig 75:193–203Google Scholar
  36. 36.
    Davis RA, Charlton AJ, Godward J, Jones SA, Harrison M, Wilson JC (2007) Adaptive binning: an improved binning method for metabolomics data using the undecimated wavelet transform. Chemometr Intell Lab Syst 85:144–154CrossRefGoogle Scholar
  37. 37.
    Sousa SAA, Magalhaes A, Ferreira MMC (2013) Optimized bucketing for NMR spectra: three case studies. Chemometr Intell Lab Syst 122:93–102CrossRefGoogle Scholar
  38. 38.
    Wishart DS (2008) Quantitative metabolomics using NMR. TrAC Trends Anal Chem 27:228–237CrossRefGoogle Scholar
  39. 39.
    Kim SB, Wang Z, Hiremath B (2010) A Bayesian approach for the alignment of high-resolution NMR spectra. Ann Oper Res 174:19–32CrossRefGoogle Scholar
  40. 40.
    MacKinnon N, Ge W, Khan AP, Somashekar BS, Tripathi P, Siddiqui J, Wei JT, Chinnaiyan AM, Rajendiran TM, Ramamoorthy A (2012) Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation. Anal Chem 84:5372–5379CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Tomasi G, Savorani F, Engelsen SB (2011) icoshift: an effective tool for the alignment of chromatographic data. J Chromatogr A 1218:7832–7840CrossRefPubMedGoogle Scholar
  42. 42.
    Veselkov KA, Lindon JC, Ebbels TMD, Crockford D, Volynkin VV, Holmes E, Davies DB, Nicholson JK (2009) Recursive segment-wise peak alignment of biological 1H-1 NMR spectra for improved metabolic biomarker recovery. Anal Chem 81:56–66Google Scholar
  43. 43.
    Wang K, Barding GA, Larive CK (2015) Peak alignment of one-dimensional NMR spectra by means of an intensity fluctuation frequency difference (IFFD) segment-wise algorithm. Anal Meth 7:9673–9682CrossRefGoogle Scholar
  44. 44.
    Pearson K (1901) On lines and planes of closest fit to systems of points in space. Phil Mag 2:559–572CrossRefGoogle Scholar
  45. 45.
    Wold S, Ruhe A, Wold H, Dunn WJ (1984) The collinearity problem in linear-regression—the partial least-squares (PLS) approach to generalized inverses. SIAM J Sci Stat Comput 5:735–743CrossRefGoogle Scholar
  46. 46.
    Trygg J, Wold S (2002) Orthogonal projections to latent structures (O-PLS). J Chemometr 16:119–128CrossRefGoogle Scholar
  47. 47.
    Trygg J (2002) O2-PLS for qualitative and quantitative analysis in multivariate calibration. J Chemometr 16:283–293CrossRefGoogle Scholar
  48. 48.
    Trygg J, Wold S (2003) O2-PLS, a two-block (X-Y) latent variable regression (LVR) method with an integral OSC filter. J Chemometr 17:53–64CrossRefGoogle Scholar
  49. 49.
    Goodacre R, Broadhurst D, Smilde AK, Kristal BS, Baker JD, Beger R, Bessant C, Connor S, Calmani G, Craig A, Ebbels T, Kell DB, Manetti C, Newton J, Paternostro G, Somorjai R, Sjöström M, Trygg J, Wulfert F (2007) Proposed minimum reporting standards for data analysis in metabolomics. Metabolomics 3:231–241Google Scholar
  50. 50.
    Lindon JC, Nicholson JK, Holmes E, Keun HC, Craig A, Pearce JTM, Bruce SJ, Hardy N, Sansone SA, Antti H, Jonsson P, Daykin C, Navarange M, Beger RD, Verheij ER, Amberg A, Baunsgaard D, Cantor GH, Lehman-McKeeman L, Earll M, Wold S, Johansson E, Haselden JN, Kramer K, Thomas C, Lindberg J, Schuppe-Koistinen I, Wilson ID, Reily MD, Robertson DG, Senn H, Krotzky A, Kochhar S, Powell J, van der Ouderaa F, Plumb R, Schaefer H, Spraul M, Standard Metabolic Reporting Structures Working Group (2005) Summary recommendations for standardization and reporting of metabolic analyses. Nat Biotechnol 23:833–838CrossRefPubMedGoogle Scholar
  51. 51.
    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, Wenger RK, Yao HY, Markley JL (2008) BioMagResBank. Nucleic Acids Res 36:D402–D408CrossRefPubMedGoogle Scholar
  52. 52.
    Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu YF, Djoumbou Y, Mandal R, Aziat F, Dong E, Bouatra S, Sinelnikov I, Arndt D, Xia JG, Liu P, Yallou F, Bjorndahl T, Perez-Pineiro R, Eisner R, Allen F, Neveu V, Greiner R, Scalbert A (2013) HMDB 3.0-the human metabolome database in 2013. Nucleic Acids Res 41:D801–D807CrossRefPubMedGoogle Scholar
  53. 53.
    Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, Fung C, Nikolai L, Lewis M, Coutouly MA, Forsythe I, Tang P, Shrivastava S, Jeroncic K, Stothard P, Amegbey G, Block D, Hau DD, Wagner J, Miniaci J, Clements M, Gebremedhin M, Guo N, Zhang Y, Duggan GE, MacInnis GD, Weljie AM, Dowlatabadi R, Bamforth F, Clive D, Greiner R, Li L, Marrie T, Sykes BD, Vogel HJ, Querengesser L (2007) HMDB: the human metabolome database. Nucleic Acids Res 35:D521–D526CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Dame ZT, Aziat F, Mandal R, Krishnamurthy R, Bouatra S, Borzouie S, Guo AC, Sajed T, Deng L, Lin H, Liu P, Dong E, Wishart DS (2015) The human saliva metabolome. Metabolomics 11:1864–1883CrossRefGoogle Scholar
  55. 55.
    Cavanagh J, Fairbrother WJ, Palmer AG, Rance M, Skelton NJ (2007) Protein NMR spectroscopy: principles and practice, 2nd edn. Protein NMR Spectroscopy: Principles and Practice, pp 1–888Google Scholar
  56. 56.
    Frolkis A, Knox C, Lim E, Jewison T, Law V, Hau DD, Liu P, Gautam B, Ly S, Guo AC, Xia JG, Liang YJ, Shrivastava S, Wishart DS (2010) SMPDB: the small molecule pathway database. Nucleic Acids Res 38:D480–D487CrossRefPubMedGoogle Scholar
  57. 57.
    Aggio R, Ruggiero K, Villas-Bôas S (2009) Pathway activity profiling (papi): an integration system for metabolomics data. N Biotechnol 25:S334–S335Google Scholar
  58. 58.
    Aggio RBM, Ruggiero K, Villas-Bôas SG (2010) Pathway activity profiling (PAPi): from the metabolite profile to the metabolic pathway activity. Bioinformatics 26:2969–2976Google Scholar
  59. 59.
    Xia JG, Sinelnikov IV, Han B, Wishart DS (2015) MetaboAnalyst 3.0-making metabolomics more meaningful. Nucleic Acids Res 43:W251–W257CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Lenander-Lumikari M, Johansson I, Vilja P, Samaranayake LP (1995) Newer saliva collection methods and saliva composition: a study of two Salivette kits. Oral Dis 1:86–91CrossRefPubMedGoogle Scholar
  61. 61.
    Bylesjö M, Eriksson D, Kusano M, Moritz T, Trygg J (2007) Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data. Plant J 52:1181–1191Google Scholar
  62. 62.
    Bylesjö M, Nilsson R, Srivastava V, Grönlund A, Johansson AI, Jansson S, Karlsson J, Moritz T, Wingsle G, Trygg J (2009) Integrated analysis of transcript, protein and metabolite data to study lignin biosynthesis in hybrid aspen. J Proteome Res 8:199–210Google Scholar
  63. 63.
    Kirwan GM, Johansson E, Kleemann R, Verheij ER, Wheelock AM, Goto S, Trygg J, Wheelock CE (2012) Building multivariate systems biology models. Anal Chem 84:7064–7071CrossRefPubMedGoogle Scholar

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© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Centre for Advanced Imaging, The University of QueenslandBrisbaneAustralia
  2. 2.School of Dentistry, Oral Health CentreThe University of QueenslandHerstonAustralia

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