Journal of Biomolecular NMR

, Volume 49, Issue 3–4, pp 307–323 | Cite as

Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra

  • Pascal Mercier
  • Michael J. Lewis
  • David Chang
  • David Baker
  • David S. Wishart
Article

Abstract

Nuclear magnetic resonance (NMR) and Mass Spectroscopy (MS) are the two most common spectroscopic analytical techniques employed in metabolomics. The large spectral datasets generated by NMR and MS are often analyzed using data reduction techniques like Principal Component Analysis (PCA). Although rapid, these methods are susceptible to solvent and matrix effects, high rates of false positives, lack of reproducibility and limited data transferability from one platform to the next. Given these limitations, a growing trend in both NMR and MS-based metabolomics is towards targeted profiling or “quantitative” metabolomics, wherein compounds are identified and quantified via spectral fitting prior to any statistical analysis. Despite the obvious advantages of this method, targeted profiling is hindered by the time required to perform manual or computer-assisted spectral fitting. In an effort to increase data analysis throughput for NMR-based metabolomics, we have developed an automatic method for identifying and quantifying metabolites in one-dimensional (1D) proton NMR spectra. This new algorithm is capable of using carefully constructed reference spectra and optimizing thousands of variables to reconstruct experimental NMR spectra of biofluids using rules and concepts derived from physical chemistry and NMR theory. The automated profiling program has been tested against spectra of synthetic mixtures as well as biological spectra of urine, serum and cerebral spinal fluid (CSF). Our results indicate that the algorithm can correctly identify compounds with high fidelity in each biofluid sample (except for urine). Furthermore, the metabolite concentrations exhibit a very high correlation with both simulated and manually-detected values.

Keywords

Metabolomics Nuclear magnetic resonance Targeted profiling Automated targeted spectral profiling 

References

  1. Aich P, Potter AA, Griebel PJ (2009) Modern approaches to understanding stress and disease susceptibility: a review with special emphasis on respiratory disease. Int J Gen Med 2:19–32Google Scholar
  2. Altman DG, Bland JM (1994) Diagnostic tests 1: sensitivity and specificity. BMJ 308:1552CrossRefGoogle Scholar
  3. Beckonert O, Coen M, Keun HC, Wang Y, Ebbels TM, Holmes E, Lindon JC, Nicholson JK (2010) High-resolution magic-angle-spinning NMR spectroscopy for metabolic profiling of intact tissues. Nat Protoc 5:1019–1032CrossRefGoogle Scholar
  4. 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 81:9188–9193CrossRefGoogle Scholar
  5. Bezabeh T, Somorjai RL, Smith ICP (2009) MR metabolomics of fecal extracts: applications in the study of bowel diseases. Magn Reson Chem 47:S54–S61CrossRefGoogle Scholar
  6. Cevallos-Cevallos JM, Reyes-De-Corcuera JI, Etxeberria E, Danyluk MD, Rodrick GE (2009) Metabolomic analysis in food science: a review. Trends Food Sci Tech 20:557–566Google Scholar
  7. Chang D, Banack CD, Shah SL (2007a) Robust baseline correction algorithm for signal dense NMR spectra. J Magn Reson 187:288–292ADSCrossRefGoogle Scholar
  8. Chang D, Weljie A, Newton J (2007b) Leveraging latent information in NMR spectra for robust predictive models. Pac Symp Biocomput 115–126Google Scholar
  9. Chen C, Gonzalez FJ, Idle JR (2007a) LC-MS-based metabolomics in drug metabolism. Drug Metab Rev 39:581–597CrossRefGoogle Scholar
  10. Chen DJ, Lee CY, Park CH, Mendes P (2007b) Parallelizing simulated annealing algorithms based on high-performance computer. J Global Optim 39:261–289MATHCrossRefGoogle Scholar
  11. Chenomx Nmr Suite (2010) Chenomx Inc., Edmonton, AB, Canada. http://www.chenomx.com
  12. Cui Q, Lewis IA, Hegeman AD, Anderson ME, Li J, Schulte CF, Westler WM, Eghbalnia HR, Sussman MR, Markley JL (2008) Metabolite identification via the Madison Metabolomics Consortium Database. Nat Biotechnol 26:162–164CrossRefGoogle Scholar
  13. Fonville JM, Maher AD, Coen M, Holmes E, Lindon JC, Nicholson JK (2010) Evaluation of full-resolution J-resolved 1H NMR projections of biofluids for metabonomics information retrieval and biomarker identification. Anal Chem 82:1811–1821CrossRefGoogle Scholar
  14. Frassineti C, Ghelli S, Gans P, Sabatini A, Moruzzi MS, Vacca A (1995) Nuclear magnetic resonance as a tool for determining protonation constants of natural polyprotic bases in solution. Anal Biochem 231:374–382CrossRefGoogle Scholar
  15. Griffin JL, Kauppinen RA (2007) Tumour metabolomics in animal models of human cancer. J Proteome Res 6:498–505CrossRefGoogle Scholar
  16. Hall RD, Brouwer ID, Fitzgerald MA (2008) Plant metabolomics and its potential application for human nutrition. Physiol Plant 132:162–175Google Scholar
  17. Kaddurah-Daouk R, Kristal BS, Weinshilboum RM (2008) Metabolomics: a global biochemical approach to drug response and disease. Annu Rev Pharmacol Toxicol 48:653–683CrossRefGoogle Scholar
  18. Keun HC (2006) Metabonomic modeling of drug toxicity. Pharmacol Ther 109:92–106CrossRefGoogle Scholar
  19. Kim YS, Maruvada P, Milner JA (2008) Metabolomics in biomarker discovery: future uses for cancer prevention. Futur Oncol 4:93–102CrossRefGoogle Scholar
  20. Kim K, Aronov P, Zakharkin SO, Anderson D, Perroud B, Thompson IM, Weiss RH (2009) Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Mol Cell Proteomics 8:558–570CrossRefGoogle Scholar
  21. Kimura T, Noguchi Y, Shikata N, Takahashi M (2009) Plasma amino acid analysis for diagnosis and amino acid-based metabolic networks. Curr Opin Clin Nutr Metab Care 12:49–53CrossRefGoogle Scholar
  22. Kristal BS, Shurubor Y, Marur V (2007) Projection-based informatics approaches to serum/plasma metabolomics data: applications to biomarkers for caloric intake in rats. Faseb J 21:A310–A310Google Scholar
  23. Li H, Jiang Y, He FC (2008) Recent development of metabonomics and its applications in clinical research. Yi Chuan 30:389–399CrossRefGoogle Scholar
  24. Lindon JC, Nicholson JK (2008) Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics. Annu Rev Anal Chem 1:45–69CrossRefGoogle Scholar
  25. Lindon JC, Nicholson JK, Holmes E (2007) The handbook of metabonomics and metabolomics, 1st edn. Elsevier, AmsterdamGoogle Scholar
  26. Markley JL, Anderson ME, Cui Q, Eghbalnia HR, Lewis IA, Hegeman AD, Li J, Schulte CF, Sussman MR, Westler WM, Ulrich EL, Zolnai Z (2007) New bioinformatics resources for metabolomics. Pac Symp Biocomput 157–168Google Scholar
  27. Milgram E, Nordstrom A (2009) Asms metabolomics workshop survey. http://fiehnlab.ucdavis.edu/staff/kind/Metabolomics-Survey-2009/
  28. Moore JG, Sillerud OL (1994) The pH dependence of chemical shift and spin-spin coupling for citrate. J Magn Res B 103:87–88 Google Scholar
  29. Morris GA, Barjat H, Home TJ (1997) Reference deconvolution methods. Prog Nucl Mag Res Sp 31:197–257Google Scholar
  30. Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A (2010) Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell BiolGoogle Scholar
  31. Odunsi K (2007) Cancer diagnostics using 1H-NMR-based metabonomics. Ernst Schering Found Symp Proc 4:205–226Google Scholar
  32. Poullet JB, Sima DM, Simonetti AW, De Neuter B, Vanhamme L, Lemmerling P, Van Huffel S (2007) An automated quantitation of short echo time MRS spectra in an open source software environment: AQSES. NMR Biomed 20:493–504CrossRefGoogle Scholar
  33. Poullet JB, Sima DM, Van Huffel S (2008) MRS signal quantitation: a review of time- and frequency-domain methods. J Magn Reson 195:134–144ADSCrossRefGoogle Scholar
  34. Quinones MP, Kaddurah-Daouk R (2009) Metabolomics tools for identifying biomarkers for neuropsychiatric diseases. Neurobiol Dis 35:165–176CrossRefGoogle Scholar
  35. Scalbert A, Brennan L, Fiehn O, Hankemeier T, Kristal BS, van Ommen B, Pujos-Guillot E, Verheij E, Wishart D, Wopereis S (2009) Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics 5:435–458CrossRefGoogle Scholar
  36. Schiffmann R, Waldek S, Benigni A, Auray-Blais C (2010) Biomarkers of Fabry disease nephropathy. Clin J Am Soc Nephrol 5:360–364CrossRefGoogle Scholar
  37. Serkova NJ, Niemann CU (2006) Pattern recognition and biomarker validation using quantitative 1H-NMR-based metabolomics. Expert Rev Mol Diagn 6:717–731CrossRefGoogle Scholar
  38. Sima DM, Van Huffel S (2006) Regularized semiparametric model identification with application to nuclear magnetic resonance signal quantification with unknown macromolecular base-line. J Roy Stat Soc B 68:383–409MATHCrossRefGoogle Scholar
  39. Sinclair AJ, Viant MR, Ball AK, Burdon MA, Walker EA, Stewart PM, Rauz S, Young SP (2010) NMR-based metabolomic analysis of cerebrospinal fluid and serum in neurological diseases—a diagnostic tool? NMR Biomed 23:123–132Google Scholar
  40. Spratlin JL, Serkova NJ, Eckhardt SG (2009) Clinical applications of metabolomics in oncology: a review. Clin Cancer Res 15:431–440CrossRefGoogle Scholar
  41. Staab JM, O’Connell TM, Gomez SM (2010) Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS). BMC Bioinform 11:123CrossRefGoogle Scholar
  42. Stein SE, Scott DR (1994) Optimization and testing of mass-spectral library search algorithms for compoud identification. J Am Soc Mass Spectr 5:859–866CrossRefGoogle Scholar
  43. Tainsky MA (2009) Genomic and proteomic biomarkers for cancer: a multitude of opportunities. Biochim Biophys Acta 1796:176–193Google Scholar
  44. Tiziani S, Lopes V, Gunther UL (2009) Early stage diagnosis of oral cancer using 1H NMR-based metabolomics. Neoplasia 11:269–276Google Scholar
  45. Van Der Graaf M, Heerschap A (1996) Effect of cation binding on the proton chemical shifts and the spin-spin coupling constant of citrate. J Magn Res B 112:58–62Google Scholar
  46. Vangala S, Tonelli A (2007) Biomarkers, metabonomics, and drug development: can inborn errors of metabolism help in understanding drug toxicity? AAPS J 9:E284–E297CrossRefGoogle Scholar
  47. 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 NMR spectra for improved metabolic biomarker recovery. Anal Chem 81:56–66CrossRefGoogle Scholar
  48. Waterman CL, Kian-Kai C, Griffin JL (2010) Metabolomic strategies to study lipotoxicity in cardiovascular disease. Biochim Biophys Acta 1801:230–234Google Scholar
  49. Weiss RH, Kim K, Tolstikov V (2008) Use of urinary metabolomics to identify biomarkers for kidney cancer. Cancer Biomark 4:167–167Google Scholar
  50. Weljie AM, Newton J, Mercier P, Carlson E, Slupsky CM (2006) Targeted profiling: quantitative analysis of 1H NMR metabolomics data. Anal Chem 78:4430–4442CrossRefGoogle Scholar
  51. Wishart DS (2008a) Applications of metabolomics in drug discovery and development. Drugs R&d 9:307–322CrossRefGoogle Scholar
  52. Wishart DS (2008b) Metabolomics: applications to food science and nutrition research. Trends Food Sci Tech 19:482–493CrossRefGoogle Scholar
  53. Wishart DS (2008c) Quantitative metabolomics using NMR. Trac-trend Anal Chem 27:228–237CrossRefGoogle Scholar
  54. Wishart DS, Lewis MJ, Morrissey JA, Flegel MD, Jeroncic K, Xiong Y, Cheng D, Eisner R, Gautam B, Tzur D, Sawhney S, Bamforth F, Greiner R, Li L (2008) The human cerebrospinal fluid metabolome. J Chromatogr B Analyt Technol Biomed Life Sci 871:164–173CrossRefGoogle Scholar
  55. Wolfender JL, Glauser G, Boccard J, Rudaz S (2009) MS-based plant metabolomic approaches for biomarker discovery. Nat Prod Commun 4:1417–1430Google Scholar
  56. Woo HM, Kim KM, Choi MH, Jung BH, Lee J, Kong G, Nam SJ, Kim S, Bai SW, Chung BC (2009) Mass spectrometry based metabolomic approaches in urinary biomarker study of women’s cancers. Clin Chim Acta 400:63–69CrossRefGoogle Scholar
  57. Xi Y, Rocke DM (2008) Baseline correction for NMR spectroscopic metabolomics data analysis. BMC Bioinform 9:324CrossRefGoogle Scholar
  58. Xia JG, Bjorndahl TC, Tang P, Wishart DS (2008) MetaboMiner—semi-automated identification of metabolites from 2D NMR spectra of complex biofluids. Bmc Bioinform 9:ARTN 507Google Scholar
  59. Young SP, Wallace GR (2009) Metabolomic analysis of human disease and its application to the eye. J Ocul Biol Dis Infor 2:235–242CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Pascal Mercier
    • 1
  • Michael J. Lewis
    • 1
  • David Chang
    • 1
    • 4
  • David Baker
    • 3
  • David S. Wishart
    • 2
  1. 1.Chenomx IncEdmontonCanada
  2. 2.Department of Computing Science and Biological SciencesUniversity of AlbertaEdmontonCanada
  3. 3.Pfizer IncGrotonUSA
  4. 4.Director of Products and ServicesEdmontonCanada

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