Emerging new strategies for successful metabolite identification in metabolomics

Bioanalysis

Volumn 8, Issue 6, 2016, Pages 557-573

  Bingol, Kerem ^a   Bruschweiler Li, Lei ^b   Li, Dawei ^b   Zhang, Bo ^b   Xie, Mouzhe ^b   Brüschweiler, Rafael ^b  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^b OHIO STATE UNIVERSITY   (United States)

Author keywords

complex mixture analysis; metabolite databases; metabolomics; MS of metabolite mixtures; nanoparticle assisted metabolomics; NMR of metabolite mixtures; paramagnetic relaxation enhancement

Indexed keywords

DATA BASE; METABOLITE; METABOLOMICS; NUCLEAR MAGNETIC RESONANCE; FACTUAL DATABASE; MASS SPECTROMETRY; METABOLISM; METABOLOME; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY;

DEHYDROCHOLIC ACID; DRUG; TRIMETHYLAMMONIUM SALT DERIVATIVE;

DATABASES, FACTUAL; MAGNETIC RESONANCE SPECTROSCOPY; MASS SPECTROMETRY; METABOLOME; METABOLOMICS; PHARMACEUTICAL PREPARATIONS; TRIMETHYL AMMONIUM COMPOUNDS;

EID: 84960347323     PISSN: 17576180     EISSN: 17576199     Source Type: Journal    
DOI: 10.4155/bio-2015-0004     Document Type: Review

References (92)

1. Nicholson JK, Wilson ID. Understanding 'global' systems biology: metabonomics and the continuum of metabolism. Nat. Rev. Drug Discov. 2, 668-676 (2003).
2. Nicholson JK, Holmes E, Lindon JC, Wilson ID. The challenges of modeling mammalian biocomplexity. Nat. Biotechnol. 22, 1268-1274 (2004).
3. Fiehn O. Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp. Funct. Genomics 2, 155-168 (2001).
4. Nicholson JK, Connelly J, Lindon JC, Holmes E. Metabonomics: a platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov. 1, 153-161 (2002).
5. Fan TW, Lane AN. NMR-based stable isotope resolved metabolomics in systems biochemistry. J. Biomol. NMR 49, 267-280 (2011).
6. Raamsdonk LM, Teusink B, Broadhurst D et al. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat. Biotechnol. 19, 45-50 (2001).
7. Holmes E, Wilson ID, Nicholson JK. Metabolic phenotyping in health and disease. Cell 134, 714-717 (2008).
8. Powers R. The current state of drug discovery and a potential role for NMR metabolomics. J. Med. Chem. 57, 5860-5870 (2014).
9. Scalbert A, Brennan L, Manach C et al. The food metabolome: a window over dietary exposure. Am. J. Clin. Nutr. 99, 1286-1308 (2014).
10. Nicholson JK, Lindon JC. Systems biology: metabonomics. Nature 455, 1054-1056 (2008).
11. Dunn WB, Broadhurst DI, Atherton HJ, Goodacre R, Griffin JL. Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem. Soc. Rev. 40, 387-426 (2011).
12. Palmnas MS, Vogel HJ. The future of NMR metabolomics in cancer therapy: towards personalizing treatment and developing targeted drugs? Metabolites 3, 373-396 (2013).
13. Emwas AH, Luchinat C, Turano P et al. Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review. Metabolomics 11, 872-894 (2015).
14. Beckonert O, Keun HC, Ebbels TM et al. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat. Protoc. 2, 2692-2703 (2007).
15. Kim HK, Choi YH, Verpoorte R. NMR-based metabolomic analysis of plants. Nat. Protoc. 5, 536-549 (2010).
16. Dona AC, Jimenez B, Schafer H et al. Precision highthroughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping. Anal. Chem. 86, 9887-9894 (2014).
17. Brindle JT, Antti H, Holmes E et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat. Med. 8, 1439-1444 (2002).
18. Gowda GA, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Rev. Mol. Diagn. 8, 617-633 (2008).
19. Duarte IF, Diaz SO, Gil AM. NMR metabolomics of human blood and urine in disease research. J. Pharm. Biomed. Anal. 93, 17-26 (2014).
20. Clayton TA, Lindon JC, Cloarec O et al. Pharmacometabonomic phenotyping and personalized drug treatment. Nature 440, 1073-1077 (2006).
21. Ramautar R, Berger R, Van Der Greef J, Hankemeier T. Human metabolomics: strategies to understand biology. Curr. Opin. Chem. Biol. 17, 841-846 (2013).
22. Nicholson JK, Holmes E, Kinross JM, Darzi AW, Takats Z, Lindon JC. Metabolic phenotyping in clinical and surgical environments. Nature 491, 384-392 (2012).
23. Lindon JC, Nicholson JK. The emergent role of metabolic phenotyping in dynamic patient stratification. Expert Opin. Drug Metab. Toxicol. 10, 915-919 (2014).
24. Bingol K, Brüschweiler R. Two elephants in the room: new hybrid nuclear magnetic resonance and mass spectrometry approaches for metabolomics. Curr. Opin. Clin. Nutr. Metab. Care 18, 471-477 (2015).
25. Gowda GA, Raftery D. Can NMR solve some significant challenges in metabolomics. J. Magn. Reson. 260, 144-160 (2015).
26. Bingol K, Salinas RK, Brüschweiler R. Higher-rank correlation NMR spectra with spectral moment filtering. J. Phys. Chem. Lett. 1, 1086-1089 (2010).
27. Bingol K, Brüschweiler R. Deconvolution of chemical mixtures with high complexity by NMR consensus trace clustering. Anal. Chem. 83, 7412-7417 (2011).
28. Hubert J, Nuzillard JM, Purson S et al. Identification of natural metabolites in mixture: a pattern recognition strategy based on 13C NMR. Anal. Chem. 86, 2955-2962 (2014).
29. Wishart DS. Advances in metabolite identification. Bioanalysis 3, 1769-1782 (2011).
30. Halabalaki M, Vougogiannopoulou K, Mikros E, Skaltsounis AL. Recent advances and new strategies in the NMR-based identification of natural products. Curr. Opin. Biotechnol. 25, 1-7 (2014).
31. Bingol K, Zhang F, Bruschweiler-Li L, Brüschweiler R. TOCCATA: a customized carbon total correlation spectroscopy NMR metabolomics database. Anal. Chem. 84, 9395-9401 (2012).
32. Bingol K, Bruschweiler-Li L, Li DW, Brüschweiler R. Customized metabolomics database for the analysis of NMR 1H-1H TOCSY and 13C-1H HSQC-TOCSY spectra of complex mixtures. Anal. Chem. 86, 5494-5501 (2014).
33. Bingol K, Li DW, Bruschweiler-Li L et al. Unified and isomer-specific NMR metabolomics database for the accurate analysis of 13C-1H HSQC spectra. ACS Chem. Biol. 10, 452-459 (2015).
34. Ellinger JJ, Chylla RA, Ulrich EL, Markley JL. Databases and software for NMR-based metabolomics. Curr. Metabol. 1, 28-40 (2013).
35. Alonso A, Marsal S, Julia A. Analytical methods in untargeted metabolomics: state of the art in 2015. Front. Bioeng. Biotechnol. 3, 23 (2015).
36. Qiu F, Mcalpine JB, Lankin DC et al. 2D NMR barcoding and differential analysis of complex mixtures for chemical identification: the Actaea triterpenes. Anal. Chem. 86, 3964-3972 (2014).
37. Clendinen CS, Pasquel C, Ajredini R, Edison AS. 13C NMR metabolomics: INADEQUATE network analysis. Anal. Chem. 87, 5698-5706 (2015).
38. Pan Z, Raftery D. Comparing and combining NMR spectroscopy and mass spectrometry in metabolomics. Anal. Bioanal. Chem. 387, 525-527 (2007).
39. Crockford DJ, Holmes E, Lindon JC et al. Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies. Anal. Chem. 78, 363-371 (2006).
40. 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, 539-549 (2007).
41. Crockford DJ, Maher AD, Ahmadi KR et al. 1H NMR and UPLC-MS(E) statistical heterospectroscopy: characterization of drug metabolites (xenometabolome) in epidemiological studies. Anal. Chem. 80, 6835-6844 (2008).
42. Fan TW, Lorkiewicz PK, Sellers K, Moseley HN, Higashi RM, Lane AN. Stable isotope-resolved metabolomics and applications for drug development. Pharmacol. Ther. 133, 366-391 (2012).
43. Clendinen CS, Stupp GS, Ajredini R, Lee-Mcmullen B, Beecher C, Edison AS. An overview of methods using 13C for improved compound identification in metabolomics and natural products. Front. Plant Sci. 6, 611 (2015).
44. Marshall DD, Lei S, Worley B et al. Combining DI-ESI-MS and NMR datasets for metabolic profiling. Metabolomics 11, 391-402 (2015).
45. Dame ZT, Aziat F, Mandal R et al. The human saliva metabolome. Metabolomics 11, 1864-1883 (2015).
46. Holmes E, Loo RL, Stamler J et al. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature 453, 396-400 (2008).
47. Suhre K, Wallaschofski H, Raffler J et al. A genome-wide association study of metabolic traits in human urine. Nat. Genet. 43, 565-569 (2011).
48. Clendinen CS, Lee-Mcmullen B, Williams CM et al. 13C NMR metabolomics: applications at natural abundance. Anal. Chem. 86, 9242-9250 (2014).
49. Bingol K, Brüschweiler R. Multidimensional approaches to NMR-based metabolomics. Anal. Chem. 86, 47-57 (2014).
50. Bingol K, Zhang F, Bruschweiler-Li L, Brüschweiler R. Quantitative analysis of metabolic mixtures by twodimensional 13C constant-time TOCSY NMR spectroscopy. Anal. Chem. 85, 6414-6420 (2013).
51. Bodenhausen G, Ruben DJ. Natural abundance N-15 NMR by enhanced heteronuclear spectroscopy. Chem. Phys. Lett. 69, 185-189 (1980).
52. Braunschweiler L, Ernst RR. Coherence transfer by isotropic mixing - application to proton correlation spectroscopy. J. Magn. Reson. 53, 521-528 (1983).
53. Saric J, Wang Y, Li J et al. Species variation in the fecal metabolome gives insight into differential gastrointestinal function. J. Proteome Res. 7, 352-360 (2008).
54. Misawa T, Date Y, Kikuchi J. Human metabolic, mineral, and microbiota fluctuations across daily nutritional intake visualized by a data-driven approach. J. Proteome Res. 14, 1526-1534 (2015).
55. Gronwald W, Klein MS, Zeltner R et al. Detection of autosomal dominant polycystic kidney disease by NMR spectroscopic fingerprinting of urine. Kidney Int. 79, 1244-1253 (2011).
56. Guennec AL, Giraudeau P, Caldarelli S. Evaluation of fast 2D NMR for metabolomics. Anal. Chem. 86, 5946-5954 (2014).
57. Wen H, An YJ, Xu WJ, Kang KW, Park S. Real-time monitoring of cancer cell metabolism and effects of an anticancer agent using 2D in-cell NMR spectroscopy. Angew. Chem. Int. Ed. 54, 5374-5377 (2015).
58. Motta A, Paris D, Melck D. Monitoring real-time metabolism of living cells by fast two-dimensional NMR spectroscopy. Anal. Chem. 82, 2405-2411 (2010).
59. Martineau E, Giraudeau P, Tea I, Akoka S. Fast and precise quantitative analysis of metabolic mixtures by 2D 1H INADEQUATE NMR. J. Pharm. Biomed. Anal. 54, 252-257 (2011).
60. COLMAR 13C-TOCCATA: a Carbon TOCSY NMR Metabolomics Database. http://spin.ccic.ohio-state.edu/index.php/toccata/index
61. COLMAR 1H(13C)-TOCCATA: Customized Metabolomics Database for the Analysis of NMR 1H-1H TOCSY and 13C- 1H HSQC-TOCSY Spectra of Complex Mixtures. http://spin.ccic.ohio-state.edu/index.php/toccata2/index
62. COLMAR 13C-1H HSQC Query. http://spin.ccic.ohio-state.edu/index.php/hsqc/index
63. Ulrich EL, Akutsu H, Doreleijers JF et al. BioMagResBank. Nucleic Acids Res. 36, D402-D408 (2008).
64. Biological Magnetic Resonance Data Bank. www.bmrb.wisc.edu
65. Wishart DS, Jewison T, Guo AC et al. HMDB 3.0-The Human Metabolome Database in 2013. Nucleic Acids Res. 41, D801-D807 (2013).
66. The Human Metabolome Database. www.hmdb.ca
67. Kikuchi J, Tsuboi Y, Komatsu K, Gomi M, Chikayama E, Date Y. SpinCouple: development of a web tool for analyzing metabolite mixtures via two-dimensional J-resolved NMR database. Anal. Chem. 88, 659-665 (2016).
68. SpinCouple. http://emar.riken.jp/spincpl
69. Aue WP, Karhan J, Ernst RR. Homonuclear broad-band decoupling and 2-dimensional J-resolved NMR-spectroscopy. J. Chem. Phys. 64, 4226-4227 (1976).
70. Birmingham Metabolite Library. www.bml-nmr.org
71. Ludwig C, Easton JM, Lodi A et al. Birmingham Metabolite Library: a publicly accessible database of 1D 1H and 2D 1H J-resolved NMR spectra of authentic metabolite standards (BML-NMR). Metabolomics 8, 8-18 (2012).
72. Fonville JM, Maher AD, Coen M, Holmes E, Lindon JC, Nicholson JK. Evaluation of full-resolution J-resolved 1H NMR projections of biofluids for metabonomics information retrieval and biomarker identification. Anal. Chem. 82, 1811-1821 (2010).
73. Psychogios N, Hau DD, Peng J et al. The human serum metabolome. PLoS ONE 6, e16957 (2011).
74. Bouatra S, Aziat F, Mandal R et al. The human urine metabolome. PLoS ONE 8, e73076 (2013).
75. Bingol K, Brüschweiler R. NMR/MS Translator for the enhanced simultaneous analysis of metabolomics mixtures by NMR spectroscopy and mass spectrometry: application to human urine. J. Proteome Res. 14, 2642-2648 (2015).
76. Bingol K, Bruschweiler-Li L, Yu C, Somogyi A, Zhang F, Brüschweiler R. Metabolomics beyond spectroscopic databases: a combined MS/NMR strategy for the rapid identification of new metabolites in complex mixtures. Anal. Chem. 87, 3864-3870 (2015).
77. Madison Metabolomics Consortium Database. http://mmcd.nmrfam.wisc.edu
78. Cui Q, Lewis IA, Hegeman AD et al. Metabolite identification via the Madison Metabolomics Consortium Database. Nat. Biotechnol. 26, 162-164 (2008).
79. COLMAR. http://spin.ccic.ohio-state.edu/index.php/colmar
80. Koehn FE, Carter GT. The evolving role of natural products in drug discovery. Nat. Rev. Drug Discov. 4, 206-220 (2005).
81. Bingol K, Zhang F, Bruschweiler-Li L, Brüschweiler R. Carbon backbone topology of the metabolome of a cell. J. Am. Chem. Soc. 134, 9006-9011 (2012).
82. ChemSpider. www.chemspider.com
83. Pence HE, Williams A. ChemSpider: an online chemical information resource. J. Chem. Educ. 87, 1123-1124 (2010).
84. Scripps Center for Metabolomics. https://metlin.scripps.edu/index.php
85. Zhu ZJ, Schultz AW, Wang J et al. Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database. Nat.Protocols 8, 451-460 (2013).
86. Willoughby PH, Jansma MJ, Hoye TR. A guide to smallmolecule structure assignment through computation of 1H and 13C NMR chemical shifts. Nat. Protoc. 9, 643-660 (2014).
87. Tayyari F, Gowda GA, Gu H, Raftery D. 15N-cholaminea smart isotope tag for combining NMR- and MS-based metabolite profiling. Anal. Chem. 85, 8715-8721 (2013).
88. Lane AN, Arumugam S, Lorkiewicz PK et al. Chemoselective detection and discrimination of carbonylcontaining compounds in metabolite mixtures by 1H-detected 15N nuclear magnetic resonance. Magn. Reson. Chem. 53, 337-343 (2015).
89. Fernandez-Megia E, Correa J, Novoa-Carballal R, Riguera R. Paramagnetic NMR relaxation in polymeric matrixes: sensitivity enhancement and selective suppression of embedded species (1H and 13C PSR filter). J. Am. Chem. Soc. 129, 15164-15173 (2007).
90. Correa J, Pinto LF, Riguera R, Fernandez-Megia E. Predicting PSR filters by transverse relaxation enhancements. Anal. Chem. 87, 760-767 (2015).
91. Gowda GAN, Raftery D. Quantitating metabolites in protein precipitated serum using NMR spectroscopy. Anal. Chem. 86, 5433-5440 (2014).
92. Zhang B, Xie M, Bruschweiler-Li L, Bingol K, Brüschweiler R. Use of charged nanoparticles in NMR-based metabolomics for spectral simplification and improved metabolite identification. Anal. Chem. 87, 7211-7217 (2015).