Computational strategies for metabolite identification in metabolomics

Bioanalysis

Volumn 1, Issue 9, 2009, Pages 1579-1596

  Wishart, David S ^a,b  

^a UNIVERSITY OF ALBERTA   (Canada)

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; HUMAN; IMAGE PROCESSING; LIQUID CHROMATOGRAPHY; MASS FRAGMENTOGRAPHY; METABOLOMICS; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; REVIEW;

ANIMALS; CHROMATOGRAPHY, LIQUID; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE SPECTROSCOPY; METABOLOMICS;

EID: 78650725285     PISSN: 17576180     EISSN: 17576199     Source Type: Journal    
DOI: 10.4155/bio.09.138     Document Type: Review

References (105)

1. German JB, Hammock BD, Watkins SM: Metabolomics: building on a century of biochemistry to guide human health. Metabolomics 1(1), 3-9 (2005).
2. Wishart DS. Current progress in computational metabolomics. Brief Bioinform. 8(5), 279-293 (2007).
3. Trygg J, Holmes E, Lundstedt T. Chemometrics in metabonomics. J. Proteome Res. 6(2), 469-479 (2007).
4. Xiayan L, Legido-Quigley C. Advances in separation science applied to metabonomics. Electrophoresis 18, 3724-3736 (2008).
5. Issaq HJ, Abbott E, Veenstra TD. Utility of separation science in metabolomic studies. J. Sep. Sci. 31(11), 1936-1947 (2008).
6. Guo K, Li L. Differential 12C-/13C-isotope dansylation labeling and fast liquid chromatography/mass spectrometry for absolute and relative quantification of the metabolome. Anal. Chem. 81(10), 3919-3932 (2009).
7. Shriner RL, Hermann CKF, Morrill TC, Curtin DY, Fuson RC. The Systematic Identification of Organic Compounds (8th Edition). Wiley, NY, USA (2003).
8. Roy SM, Becker CH. Quantification of proteins and metabolites by mass spectrometry without isotopic labeling. Methods Mol. Biol. 359, 87-105 (2007).
9. Wishart DS, Lewis MJ, Morrissey JA et al. The human cerebrospinal fluid metabolome. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 871(2), 164-173 (2008).
10. Wishart DS. Quantitative metabolomics using NMR. Trends Anal. Chem. 27, 228-237 (2008).
11. Rumsfeld D. Press Briefing. 12 February 2002.
12. Fiehn O. Metabolomics: the link between genotypes and phenotypes. Plant Mol. Biol. 48, 155-171 (2002).
13. Dunn WB. Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes. Phys. Biol. 2008 5(1), 11001 (2008).
14. Coles SJ, Day NE, Murray-Rust P, Rzepa HS, Zhang Y. Enhancement of the chemical semantic web through the use of In ChI identifiers. Org. Biomol. Chem. 3(10), 1832-1834 (2005).
15. Wilson DM, Burlingame AL. Deuterium and carbon-13 tracer studies of ethanol metabolism in the rat by 2H, 1H-decoupled 13C nuclear magnetic resonance. Biochem. Biophys. Res. Commun. 56(3), 828-835 (1974).
16. Shulman RG, Rothman DL. 13C NMR of intermediary metabolism: implications for systemic physiology. Annu. Rev. Physiol. 63, 15-48 (2001).
17. Nicholson JK, Lindon JC, Holmes E. 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29(11), 1181-1189 (1999).
18. Reo NV. NMR-based metabolomics. Drug Chem. Toxicol. 25(4), 375-382 (2002).
19. Weljie AM, Newton J, Mercier P, Carlson E, Slupsky CM. Targeted profiling: quantitative analysis of 1H NMR metabolomics data. Anal. Chem. 78(13), 4430-4442 (2006).
20. Rossé G, Neidig P, Schröder H. Automated structure verification of small molecules libraries using 1D and 2D NMR techniques. Methods Mol. Biol. 201, 123-139 (2002).
21. Xia J, Bjorndahl TC, Tang P, Wishart DS. MetaboMiner - semi-automated identification of metabolites from 2D NMR spectra of complex biofluids. BMC Bioinformatics 9, 507 (2008).
22. Steinbeck C, Krause S, Kuhn S. NMRShiftDB - constructing a free chemicalinformation system with open-source components. J. Chem. Inf. Comput. Sci. 43(6), 1733-1739 (2003).
23. Wishart DS, Knox C, Guo AC et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 37(Database issue), D603-D610 (2009).
24. Ulrich EL, Akutsu H, Doreleijers JF et al. BioMagResBank. Nucleic Acids Res. 36(Database issue), D402-D408 (2008).
25. Akiyama K, Chikayama E, Yuasa H et al. PRIMe: a web site that assembles tools for metabolomics and transcriptomics. In Silico Biol. 8(3-4), 339-345 (2008).
26. Tanaka K, Budd MA, Efron ML, Isselbacher KJ. Isovaleric acidemia: a new genetic defect of leucine metabolism. Proc. Natl Acad. Sci. USA 56, 236-242 (1966).
27. Kuhara T. Gas chromatographic-mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism. Mass Spectrom. Rev. 24, 814-827 (2005).
28. Lisec J, Schauer N, Kopka J, Willmitzer L, Fernie AR. Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protoc. 1(1), 387-396 (2006).
29. Matsumoto I, Kuhara T. A new chemical diagnostic method for inborn errors of metabolism by mass spectrometry - rapid, practical and simultaneous urinary metabolites analysis. Mass Spectrom. Rev. 15, 43-57 (1996).
30. Halket JM, Waterman D, Przyborowska AM, Patel RKP, Fraser PD, Bramley PM. Chemical derivatization and mass spectral libraries in metabolite profiling by GC-MS and LC- MS/MS. J. Exp. Botany 56(410), 219-243 (2005).
31. A J, Trygg J, Gullberg J et al. Extraction and GC-MS analysis of the human blood plasma metabolome. Anal. Chem. 77, 8086-8094 (2005).
32. Stein SE. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spect. 10(8), 770-781 (1999).
33. Kovats E. Gas chromatographische Charakteriserung organischer Verbindungen. I. Retentions indices aliphatischer halogenide, alkohole, aldehyde und ketone. Helv. Chim. Acta 41, 1915-1932 (1958).
34. Draper J, Enot DP, Parker D et al. Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'. BMC Bioinformatics 10(1), 227 (2009).
35. Lu H, Liang Y, Dunn WB, Shen H, Kell DB. Comparative evaluation of software for deconvolution of metabolomics data based on GC-TOF-MS. Trends Anal. Chem. 27, 215-227 (2008).
36. Kopka J, Schauer N, Krueger S et al. GMD@CSB.DB: the Golm Metabolome Database. Bioinformatics 21(8), 1635-1638 (2005).
37. 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).
38. Skogerson K, Runnebaum R, Wohlgemuth G, de Ropp J, Heymann H, Fiehn O. Comparison of gas chromatography-coupled time-of-flight mass spectrometry and 1H nuclear magnetic resonance spectroscopy metabolite identification in white wines from a sensory study investigating wine body. J. Agric. Food Chem. (2009) (Epub ahead of print).
39. Henion J, Skrabalak D, Dewey E, Maylin G. Micro LC-MS in drug analysis and metabolism studies. Drug Metab. Rev. 14(5), 961-1003 (1983).
40. Rashed MS, Ozand PT, Bucknall MP, Little D. Diagnosis of inborn errors of metabolism from blood spots by acylcarnitines and amino acids profiling using automated electrospray tandem mass spectrometry. Pediatr. Res. 38(3), 324-331 (1995).
41. Taguchi R, Nishijima M, Shimizu T. Basic analytical systems for lipidomics by mass spectrometry in Japan. Meth. Enzymol. 432, 185-211 (2007).
42. Hopley C, Bristow T, Lubben A et al. Towards a universal product ion mass spectral library - reproducibility of product ion spectra across eleven different mass spectrometers. Rapid Commun. Mass Spectrom. 22(12), 1779-1786 (2008).
43. Oberacher H, Pavlic M, Libiseller K et al. On the inter-instrument and inter-laboratory transferability of a tandem mass spectral reference library: 1. Results of an Austrian multicenter study. J. Mass Spectrom. 44(4), 485-493 (2009).
44. Okuda S, Yamada T, Hamajima M et al. KEGG Atlas mapping for global analysis of metabolic pathways. Nucleic Acids Res. 36, W423-W426 (2008).
45. Wheeler DL, Barrett T, Benson DA et al. Database resources of the National Centre for Biotechnology Information. Nucleic Acids Res. 35, 5-12 (2007).
46. Shinbo Y, Nakamura Y, Altaf-Ul-Amin M et al. KNApSAcK: a comprehensive species-metabolite relationship database. Biotechnol. Agr. Forest 57, 166-181 (2006).
47. Sud M, Fahy E, Cotter D et al. LMSD: LIPID MAPS structure database. Nucleic Acids Res. 35, 527-532 (2007).
48. Smith CA, O'Maille G, Want EJ et al. METLIN: a metabolite mass spectral database. Ther. Drug Monit. 27(6), 747-751 (2005).
49. Kind T, Fiehn O. Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics 8, 105 (2007).
50. Böcker S, Letzel MC, Lipták Z, Pervukhin A. SIRIUS: decomposing isotope patterns for metabolite identification. Bioinformatics 25(2), 218-224 (2009).
51. Nakamura Y, Kanaya S, Sakurai N et al. A tool for high-throughput prediction of molecular formulas and identification of isotopic peaks from large scale mass spectrometry data. Plant Biotech. 25, 377-380 (2008).
52. Noury S, Silvi B, Gillespie RJ. Chemical bonding in hypervalent molecules: is the octet rule relevant? Inorg. Chemistry 411, 2164-2172 (2002).
53. Senior JK. Partition and their representative graphs. Am. J. Math. 73, 663-689 (1951).
54. Iijima Y, Nakamura Y, Ogata Y et al. Metabolite annotations based on the integration of mass spectral information. Plant J. 54(5), 949-962 (2008).
55. Sana TR, Roark JC, Li X, Waddell K, Fischer SM. Molecular formula and METLIN Personal Metabolite Database matching applied to the identification of compounds generated by LC/TOF-MS. J. Biomol. Tech. 19(4), 258-266 (2008).
56. Hill DW, Kertesz TM, Fontaine D, Friedman R, Grant DF. Mass spectral metabonomics beyond elemental formula: chemical database querying by matching experimental with computational fragmentation spectra. Anal. Chem. 80(14), 5574-5582 (2008).
57. Matsuda F, Yonekura-Sakakibara K, Niida R, Kuromori T, Shinozaki K, Saito K. MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites. Plant J. 57(3), 555-577 (2009).
58. Takahashi H, Kai K, Shinbo Y et al. Metabolomics approach for determining growth-specific metabolites based on fourier transform ion cyclotron resonance mass spectrometry. Anal. Bioanal. Chem. 391, 2769-2782 (2008).
59. Loftus N, Miseki K, Iida J, Gika HG, Theodoridis G, Wilson ID. Profiling and biomarker identification in plasma from different Zucker rat strains via high mass accuracy multistage mass spectrometric analysis using liquid chromatography/mass spectrometry with a quadrupole ion trap-time of flight mass spectrometer. Rapid Commun. Mass Spectrom. 22(16), 2547-2554 (2008).
60. Steinbeck C. Recent developments in automated structure elucidation of natural products. Nat. Prod. Rep. 21, 512-518 (2004).
61. Jaspars M. Computer assisted structure elucidation of natural products using two-dimensional NMR spectroscopy. Nat. Prod. Rep. 16, 241-248 (1999).
62. Lederberg J, Sutherland GL, Buchanan BG et al. Application of artificial intelligence to chemical inference. J. Am. Chem. Soc. 91, 2973-2976 (1968).
63. Kuhn S, Egertt B, Neumann S, Steinbeck C. Building blocks for automated elucidation of metabolites: machine learning methods for NMR prediction. BMC Bioinformatics 9, 400 (2008).
64. Korytko A, Schulz KP, Madison MS, Munk ME. HOUDINI: a new approach to computer-based structure generation. J. Chem. Inf. Comput. Sci. 43(5), 1434-1446 (2003).
65. Steinbeck C. SENECA: a platformindependent, distributed, and parallel system for computer-assisted structure elucidation in organic chemistry. J. Chem. Inf. Comput. Sci. 41(6), 1500-1507 (2001).
66. Junker J, Maier W, Lindel T, Köck M. Computer-assisted constitutional assignment of large molecules: COCON analysis of ascomycin. Org. Lett. 1(5), 737-740 (1999).
67. Elyashberg M, Blinov K, Molodtsov S, Smurnyy Y, Williams AJ, Churanova T. Computer-assisted methods for molecular elucidation: realizing a spectroscopist's dream. J. Cheminformatics 1(3) (2009).
68. Nassar AE, Adams PE. Metabolite characterization in drug discovery utilizing robotic liquid-handling, quadruple time-offlight mass spectrometry and in silico prediction. Curr. Drug Metab. 4(4), 259-271 (2003).
69. Pelander A, Tyrkkö E, Ojanperä I. In silico methods for predicting metabolism and mass fragmentation applied to quetiapine in liquid chromatography/time-of-flight mass spectrometry urine drug screening. Rapid Commun. Mass Spectrom. 23(4), 506-514 (2009).
70. Langowski J, Long A. Computer systems for the prediction of xenobiotic metabolism. Adv. Drug Deliv. Rev. 54, 407-415 (2002).
71. Darvas F. MetabolExpert, an expert system for predicting metabolism of substances. In: QSAR in Environmental Toxicology. Dordecht Riedel, Dordrecht, The Netherlands 71-81 (1987).
72. Ekins S, Andreyev S, Ryabov A et al. Computational prediction of human drug metabolism. Expert Opin. Drug Metab. Toxicol. 1(2), 303-324 (2005).
73. Greene N, Judson PN, Langowski JJ, Marchant CA. Knowledge-based expert systems for toxicity and metabolism prediction: DEREK, StAR and METEOR. SAR QSAR Environ. Res. 10, 299-314 (1999).
74. Hernández F, Grimalt S, Pozo OJ, Sancho JV. Use of ultra-high-pressure liquid chromatography-quadrupole time-of-flight MS to discover the presence of pesticide metabolites in food samples. J. Sep. Sci. 32(13), 2245-2261 (2009).
75. Human Metabolome Database www.hmdb.ca
76. NMRShiftDBwww.ebi.ac.uk/nmrshiftdb
77. Chenomx Inc. NMR Suite www.chenomx.com/software/software.php
78. Bruker BioSpin, AMIX program www.bruker-biospin.com/amix.html
79. MetaboMiner http://wishart.biology.ualberta.ca/metabominer
80. Natural Products 13C NMR Database http://c13.usal.es
81. Biological Magnetic Resonance Data Bank www.bmrb.wisc.edu/metabolomics/
82. Agilent Technologies www.chem.agilent.com
83. LECO www.leco.com
84. Manchester Metabolomics Database http://dbkgroup.org/MMD
85. AIST:RIO-DB spectral database for organic compounds http://riodb01.ibase. aist.go.jp/sdbs/cgi-bin/cre-index.cgi?lang=eng
86. Mass Bank www.massbank.jp
87. National Institute of Standards and Technology www.nist.gov
88. Bio-Rad www.bio-rad.com
89. Advanced Chemistry Development www.acdlabs.com
90. Thermo Scientific www.thermo.com
91. HighChem, Ltd www.highchem.com
92. AMDIS www.amdis.net
93. SpectralWorks www.spectralworks.com
94. Shimadzu www.shimadzu.com
95. Waters Corporation www.waters.com
96. Applied Biosystems www.appliedbiosystems.com
97. Bruker Daltonics www.bdal.de
98. Sierra Analytics www.massspec.com
99. Sirius http://bio.informatik.uni-jena.de/sirius
100. Metaboomics Fiehn Lab http://fiehnlab.ucdavis.edu/projects
101. PERCH Solutions, Ltd www.perchsolutions.com
102. WEbCocon http://cocon.nmr.de
103. Lhasa Limited www.lhasalimited.org
104. CompuDrug Inc. www.compudrug.com
105. GeneGo www.genego.com