Skip to main content
SpringerLink
Log in

Fundamentals of Mass Spectrometry-Based Metabolomics

  • Conference paper
  • First Online:
Toxic Chemical and Biological Agents

  • 603 Accesses

Abstract

Metabolomics involves the study of a complex and diverse array of compounds that can be thought of as the ultimate end products of the complex systems that are characteristic of molecular biology. The compounds that constitute the metabolome are small in size relative to the genome and proteome and include amino acids, carbohydrates, organic acids, lipids, and nucleotides with a mass less than 1800 Da. Understanding the role of these metabolites and the way in which changes in these important molecules impact biological processes has great potential to improve public health through better understanding of disease mechanisms. A comprehensive understanding of the metabolome will ultimately lead to better candidate biomarkers and drug targets enabling improvements in patient care. Metabolomics experiments can be divided primarily into two experimental strategies: targeted and untargeted. This monograph details these two approaches and the specific considerations for sample preparation, analytical separations, instrumental considerations, and data analysis that are required in the practice of these important technologies. Furthermore, selected applications of targeted and untargeted experiments are showcased to demonstrate the role of metabolomics as part of multi-omics studies and how metabolites can be spatially mapped in biological systems using imaging mass spectrometry.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ryan D, Robards K (2006) Metabolomics: the greatest omics of them all?. https://doi.org/10.1021/AC0614341

  2. Ren J-L, Zhang A-H, Kong L, Wang X-J (2018) Advances in mass spectrometry-based metabolomics for investigation of metabolites. RSC Adv 8(40):22335–22350. https://doi.org/10.1039/C8RA01574K

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Guo S, Tian J, Zhu B, Yang S, Yu K, Zhao Z (2018) Trends in metabolomics research: A Scientometric analysis (1992–2017). Curr Sci 114(11)

    Google Scholar 

  4. Markley JL, Brüschweiler R, Edison AS, Eghbalnia HR, Powers R, Raftery D, Wishart DS (2017) The future of NMR-based metabolomics. Curr Opin Biotechnol 43:34–40. https://doi.org/10.1016/J.COPBIO.2016.08.001

    Article  CAS  PubMed  Google Scholar 

  5. Papadimitropoulos M-EP, Vasilopoulou CG, Maga-Nteve C, Klapa MI (2018) Untargeted GC-MS metabolomics. Humana Press, New York, pp 133–147. https://doi.org/10.1007/978-1-4939-7643-0_9

    Book  Google Scholar 

  6. Zhou B, Xiao JF, Tuli L, Ressom HW (2012) LC-MS-based metabolomics. Mol BioSyst 8(2):470. https://doi.org/10.1039/C1MB05350G

    Article  CAS  PubMed  Google Scholar 

  7. Dueñas ME, Larson EA, Lee YJ (2019) Toward mass spectrometry imaging in the metabolomics scale: increasing metabolic coverage through multiple on-tissue chemical modifications. Front Plant Sci 10(860). https://doi.org/10.3389/fpls.2019.00860

  8. Emwas A-H, Roy R, McKay RT, Tenori L, Saccenti E, Gowda GAN, Raftery D, Alahmari F, Jaremko L, Jaremko M et al (2019) NMR spectroscopy for metabolomics research. Meta 9(7):123. https://doi.org/10.3390/metabo9070123

    Article  CAS  Google Scholar 

  9. Schrimpe-Rutledge AC, Codreanu SG, Sherrod SD, McLean JA (2016) Untargeted metabolomics strategies—challenges and emerging directions. J Am Soc Mass Spectrom 27(12):1897–1905. https://doi.org/10.1007/s13361-016-1469-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Gray WR (1967) Dansyl Chloride Procedure. Methods Enzymol 11(C):139–151. https://doi.org/10.1016/S0076-6879(67)11014-8

    Article  CAS  Google Scholar 

  11. Vinayavekhin N, Saghatelian A Untargeted metabolomics. In: Current protocols in molecular biology. Wiley, Hoboken, p 2010. https://doi.org/10.1002/0471142727.mb3001s90

  12. Enders JR, McIntire GL (2015) A dilute-and-shoot LC-MS method for quantitating opioids in Oral fluid. J Anal Toxicol 39(8):662–667. https://doi.org/10.1093/jat/bkv087

    Article  CAS  PubMed  Google Scholar 

  13. Ser Z, Liu X, Tang NN, Locasale JW (2015) Extraction parameters for metabolomics from cultured cells. Anal Biochem 475:22–28. https://doi.org/10.1016/j.ab.2015.01.003

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Boyd RK (1993) Quantitative trace analysis by combined chromatography and mass spectrometry using external and internal standards. Rapid Commun Mass Spectrom:257–271. https://doi.org/10.1002/rcm.1290070402

  15. Roberts LD, Souza AL, Gerszten RE, Clish CB Targeted Metabolomics. Curr Protoc Mol Biol 2012:1. (SUPPL.98. https://doi.org/10.1002/0471142727.mb3002s98

  16. Dunn WB, Ellis DI (2005) Metabolomics: current analytical platforms and methodologies. TrAC Trends Anal Chem 24(4):285–294. https://doi.org/10.1016/j.trac.2004.11.021

    Article  CAS  Google Scholar 

  17. Cajka T, Fiehn O (2014) Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry. TrAC Trends Anal Chem:192–206. https://doi.org/10.1016/j.trac.2014.04.017

  18. Jiang L, He L, Fountoulakis M (2004) Comparison of protein precipitation methods for sample preparation prior to proteomic analysis. J Chromatogr A 1023(2):317–320. https://doi.org/10.1016/j.chroma.2003.10.029

    Article  CAS  PubMed  Google Scholar 

  19. Folch J, Lees M, Sloane GH (2019) A simple method for the isolation and purification of total Lipides from animal tissues* Downloaded From; 2019

    Google Scholar 

  20. Bligh EG, Dyer WJ A rapid method of total lipid extraction and purification

    Google Scholar 

  21. Gutierrez DB, Gant-Branum RL, Romer CE, Farrow MA, Allen JL, Dahal N, Nei YW, Codreanu SG, Jordan AT, Palmer LD et al (2018) An integrated, high-throughput strategy for Multiomic systems level analysis. J Proteome Res 17(10):3396–3408. https://doi.org/10.1021/acs.jproteome.8b00302

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Gertsman I, Barshop BA (2018) Promises and pitfalls of untargeted metabolomics. J Inherit Metab Dis:355–366. https://doi.org/10.1007/s10545-017-0130-7

  23. Broadhurst D, Goodacre R, Reinke SN, Kuligowski J, Wilson ID, Lewis MR, Dunn WB (2018) Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical Metabolomic studies. Metabolomics. https://doi.org/10.1007/s11306-018-1367-3

  24. Haijes HA, van der Ham M, Gerrits J, van Hasselt PM, Prinsen HCMT, de Sain-van der Velden MGM, Verhoeven-Duif NM, Jans JJM (2019) Direct-infusion based metabolomics unveils biochemical profiles of inborn errors of metabolism in cerebrospinal fluid. Mol Genet Metab 127(1):51–57. https://doi.org/10.1016/J.YMGME.2019.03.005

    Article  CAS  PubMed  Google Scholar 

  25. Norris JL, Caprioli RM Analysis of tissue specimens by matrix-assisted laser desorption/ ionization imaging mass spectrometry in biological and clinical research. https://doi.org/10.1021/cr3004295

  26. Jandera P (2005) Liquid chromatography | normal phase. In: Encyclopedia of analytical science. Elsevier, pp 142–152. https://doi.org/10.1016/b0-12-369397-7/00324-1

  27. Scott RPW (2000) Chromatography: Liquid | mechanisms: normal phase. In: Encyclopedia of separation science. Elsevier, pp 706–711. https://doi.org/10.1016/b0-12-226770-2/00301-x

  28. Jiang P, Lucy CA (2016) Coupling normal phase liquid chromatography with electrospray ionization mass spectrometry: strategies and applications. Anal Methods:6478–6488. https://doi.org/10.1039/c6ay01419d

  29. Abbott SR (1980) Practical aspects of normal-phase chromatography. J Chromatogr Sci 18(10):540–550. https://doi.org/10.1093/chromsci/18.10.540

    Article  CAS  PubMed  Google Scholar 

  30. Patti GJ, Yanes O, Siuzdak GI (2012) Metabolomics: the apogee of the omics trilogy. Nat Rev Mol Cell Biol:263–269. https://doi.org/10.1038/nrm3314

  31. Dettmer K, Aronov PA, Hammock BD Mass spectrometry-based metabolomics. Mass Spectrom Rev 26(1):51–78. https://doi.org/10.1002/mas.20108

  32. Patterson RE, Ducrocq AJ, McDougall DJ, Garrett TJ, Yost RA (2015) Comparison of blood plasma sample preparation methods for combined LC-MS lipidomics and metabolomics. J Chromatogr B Anal Technol Biomed Life Sci 1002:260–266. https://doi.org/10.1016/j.jchromb.2015.08.018

    Article  CAS  Google Scholar 

  33. Cutillas P (2005) Principles of nanoflow liquid chromatography and applications to proteomics. Curr Nanosci 1(1):65–71. https://doi.org/10.2174/1573413052953093

    Article  CAS  Google Scholar 

  34. Alpert AJ (1990) Hydrophilic-interaction chromatography for the separation of peptides, nucleic acids and other polar compounds. J Chromatogr A 499(C):177–196. https://doi.org/10.1016/S0021-9673(00)96972-3

    Article  CAS  Google Scholar 

  35. Simon R, Enjalbert Q, Biarc J, Lemoine J, Salvador A (2012) Evaluation of Hydrophilic Interaction Chromatography (HILIC) versus C18 reversed-phase chromatography for targeted quantification of peptides by mass spectrometry. J Chromatogr A 1264:31–39. https://doi.org/10.1016/j.chroma.2012.09.059

    Article  CAS  PubMed  Google Scholar 

  36. Naser FJ, Mahieu NG, Wang L, Spalding JL, Johnson SL, Patti GJ (2018) Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome. Anal Bioanal Chem 410(4):1287–1297. https://doi.org/10.1007/s00216-017-0768-x

    Article  CAS  PubMed  Google Scholar 

  37. Martin AJP, Synge RLM (1941) A new form of chromatogram employing two liquid phases. Biochem J 35(12):1358–1368

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Roessner U, Wagner C, Kopka J, Tretheway RN, Willmitzer L (2001) Simultaneous analysis of metabolites in tuber by gas chromatography-mass spectrometry. Plant J 23:1

    Google Scholar 

  39. Castrillo JI, Hayes A, Mohammed S, Gaskell SJ, Oliver SG (2003) An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry. Phytochemistry 62:929–937

    Article  CAS  PubMed  Google Scholar 

  40. Halket JM, Waterman D, Przyborowska AM, Patel RKP, Fraser PD, Bramley PM (2005) Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS. J Exp Bot 56(410):219–243. https://doi.org/10.1093/jxb/eri069

    Article  CAS  PubMed  Google Scholar 

  41. Jonsson P, Johansson AI, Gullberg J, Trygg J, A J, Grung B, Marklund S, Sjöström M, Antti H, Moritz T (2005) High-throughput data analysis for detecting and identifying differences between samples in GC/MS-based metabolomic analyses. Anal Chem 77(17):5635–5642. https://doi.org/10.1021/ac050601e

    Article  CAS  PubMed  Google Scholar 

  42. Monnig CA, Kennedy RT (2014) Capillary electrophoresis. Food Toxic Anal Tech Strateg Dev 1997(12):561–597. https://doi.org/10.1021/acs.analchem.5b04125

    Article  CAS  Google Scholar 

  43. Ewing AG, Wallingford RA, Olefirowicz TM (1989) Capillary electrophoresis. Anal Chem 61(4):292A–303A. https://doi.org/10.1021/ac00179a002

    Article  CAS  PubMed  Google Scholar 

  44. VanOrman BB, Liversidge GG, McIntire GL, Olefirowicz TM, Ewing AG (1990) Effects of buffer composition on electroosmotic flow in capillary electrophoresis. J Microcolumn Sep 2(4):176–180. https://doi.org/10.1002/mcs.1220020404

    Article  CAS  Google Scholar 

  45. Olivares JA, Nguyen NT, Yonker CR, Smith RD (1987) On-line mass spectrometric detection for capillary zone electrophoresis. Anal Chem 59(8):1230–1232. https://doi.org/10.1021/ac00135a034

    Article  CAS  Google Scholar 

  46. Soga T, Ohashi Y, Ueno Y, Naraoka H, Tomita M, Nishioka T (2003) Quantitative metabolome analysis using capillary electrophoresis mass spectrometry. J Proteome Res 2(5):488–494. https://doi.org/10.1021/pr034020m

    Article  CAS  PubMed  Google Scholar 

  47. Nowak PM, Woźniakiewicz M, Gładysz M, Janus M, Kościelniak P (2017) Improving repeatability of capillary electrophoresis—a critical comparison of ten different capillary inner surfaces and three criteria of peak identification. Anal Bioanal Chem 409(18):4383–4393. https://doi.org/10.1007/s00216-017-0382-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Dwivedi P, Wu P, Klopsch SJ, Puzon GJ, Xun L, Hill HH (2008) Metabolic profiling by Ion Mobility Mass Spectrometry (IMMS). Metabolomics 4(1):63–80. https://doi.org/10.1007/s11306-007-0093-z

    Article  CAS  Google Scholar 

  49. Miller RA, Eiceman GA, Nazarov EG, King AT (2000) Novel micromachined high-field asymmetric waveform-ion mobility spectrometer. Sensors Actuators B Chem 67(3):300–306. https://doi.org/10.1016/S0925-4005(00)00535-9

    Article  CAS  Google Scholar 

  50. Kanu AB, Dwivedi P, Tam M, Matz L, Hill HH (2008) Ion mobility-mass spectrometry. J Mass Spectrom 43(1):1–22. https://doi.org/10.1002/jms.1383

    Article  CAS  PubMed  Google Scholar 

  51. Berm EJJ, Paardekooper J, Brummel-Mulder E, Hak E, Wilffert B, Maring JG (2015) A simple dried blood Spot method for therapeutic drug monitoring of the tricyclic antidepressants amitriptyline, nortriptyline, imipramine, clomipramine, and their active metabolites using LC-MS/MS. Talanta 134:165–172. https://doi.org/10.1016/j.talanta.2014.10.041

    Article  CAS  PubMed  Google Scholar 

  52. Tautenhahn R, Bottcher C, Neumann S (2008) Highly sensitive feature detection for high resolution LC/MS. BMC Bioinf 9. https://doi.org/10.1186/1471-2105-9-504

  53. Zhang X, Quinn K, Cruickshank-Quinn C, Reisdorph R, Reisdorph N (2018) The application of ion mobility mass spectrometry to metabolomics. Curr Opin Chem Biol:60–66. https://doi.org/10.1016/j.cbpa.2017.11.001

  54. Picache JA, Rose BS, Balinski A, Leaptrot KL, Sherrod SD, May JC, McLean JA (2019) Collision cross section compendium to annotate and predict multi-Omic compound identities. Chem Sci 10(4):983–993. https://doi.org/10.1039/c8sc04396e

    Article  CAS  PubMed  Google Scholar 

  55. Xiao JF, Zhou B, Ressom HW (2012) Metabolite identification and quantitation in LC-MS/MS-based metabolomics. TrAC Trends Anal Chem:1–14. https://doi.org/10.1016/j.trac.2011.08.009

  56. Yost RA, Enke CG (1978) Selected ion fragmentation with a tandem quadrupole mass spectrometer. J Am Chem Soc 100(7):2274–2275. https://doi.org/10.1021/ja00475a072

    Article  CAS  Google Scholar 

  57. Matraszek-Zuchowska I, Wozniak B, Posyniak A (2016) Comparison of the multiple reaction monitoring and enhanced product ion scan modes for confirmation of stilbenes in bovine urine samples using LC–MS/MS QTRAP® system. Chromatographia 79(15–16):1003–1012. https://doi.org/10.1007/s10337-016-3121-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hopfgartner G, Varesio E, Tschäppät V, Grivet C, Bourgogne E, Leuthold LA (2004) Triple quadrupole linear ion trap mass spectrometer for the analysis of small molecules and macromolecules. J Mass Spectrom 39(8):845–855. https://doi.org/10.1002/jms.659

    Article  CAS  PubMed  Google Scholar 

  59. Zhou J, Yin Y (2016) Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry. Analyst 141(23):6362–6373. https://doi.org/10.1039/c6an01753c

    Article  CAS  PubMed  Google Scholar 

  60. Bateman NW, Goulding SP, Shulman NJ, Gadok AK, Szumlinski KK, MacCoss MJ, Wu CC (2014) Maximizing peptide identification events in proteomic workflows using Data-Dependent Acquisition (DDA). Mol Cell Proteomics 13(1):329–338. https://doi.org/10.1074/mcp.M112.026500

    Article  CAS  PubMed  Google Scholar 

  61. Mullard G, Allwood JW, Weber R, Brown M, Begley P, Hollywood KA, Jones M, Unwin RD, Bishop PN, Cooper GJS et al (2015) A new strategy for MS/MS data acquisition applying multiple data dependent experiments on orbitrap mass spectrometers in non-targeted metabolomic applications. Metabolomics 11(5):1068–1080. https://doi.org/10.1007/s11306-014-0763-6

    Article  CAS  Google Scholar 

  62. Schwudke D, Liebisch G, Herzog R, Schmitz G, Shevchenko A (2007) Shotgun lipidomics by tandem mass spectrometry under data-dependent acquisition control. Methods Enzymol:175–191. https://doi.org/10.1016/S0076-6879(07)33010-3

  63. Doerr A (2014) DIA mass spectrometry. Nat Methods 2014:121

    Google Scholar 

  64. Venable JD, Dong MQ, Wohlschlegel J, Dillin A, Yates JR (2004) Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat Methods 1(1):39–45. https://doi.org/10.1038/nmeth705

    Article  CAS  PubMed  Google Scholar 

  65. Bilbao A, Varesio E, Luban J, Strambio-De-Castillia C, Hopfgartner G, Müller M, Lisacek F (2015) Processing strategies and software solutions for data-independent acquisition in mass spectrometry. Proteomics 15(5–6):964–980. https://doi.org/10.1002/pmic.201400323

    Article  CAS  PubMed  Google Scholar 

  66. Kondrat RW, McClusky GA, Cooks RG (1978) Multiple reaction monitoring in mass spectrometry/mass spectrometry for direct analysis of complex mixtures. Anal Chem 50(14):2017–2021. https://doi.org/10.1021/ac50036a020

    Article  CAS  Google Scholar 

  67. Rathahao-Paris E, Alves S, Junot C, Tabet JC (2016) High resolution mass spectrometry for structural identification of metabolites in metabolomics. Metabolomics:1–15. https://doi.org/10.1007/s11306-015-0882-8

  68. Michalski A, Damoc E, Lange O, Denisov E, Nolting D, Müller M, Viner R, Schwartz J, Remes P, Belford M et al (2012) Ultra high resolution linear ion trap orbitrap mass spectrometer (Orbitrap elite) facilitates top down LC MS/MS and versatile peptide fragmentation modes. Mol Cell Proteomics 11(3). https://doi.org/10.1074/mcp.O111.013698

  69. Ghaste M, Mistrik R, Shulaev V (2016) Applications of Fourier transform ion cyclotron resonance (FT-ICR) and Orbitrap based high resolution mass spectrometry in metabolomics and Lipidomics. Int J Mol Sci. https://doi.org/10.3390/ijms17060816

  70. Mahieu NG, Patti GJ (2017) Systems-level annotation of a metabolomics data set reduces 25 000 features to fewer than 1000 unique metabolites. Anal Chem 89(19):10397–10406. https://doi.org/10.1021/acs.analchem.7b02380

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Blaženović I, Kind T, Ji J, Fiehn O (2018) Software tools and approaches for compound identification of LC-MS/MS data in metabolomics. Meta 8(2):31. https://doi.org/10.3390/metabo8020031

    Article  CAS  Google Scholar 

  72. LCQuan. Thermo Fisher Scientific: Hemel Hempstead, Hetfordshire, UK

    Google Scholar 

  73. Depke T, Franke R, Brönstrup M (2017) Clustering of MS2 spectra using unsupervised methods to aid the identification of secondary metabolites from Pseudomonas Aeruginosa. J Chromatogr B 1071:19–28. https://doi.org/10.1016/j.jchromb.2017.06.002

    Article  CAS  Google Scholar 

  74. MassHunter. Agilent: Santa Clara, CA, USA

    Google Scholar 

  75. Profile Analysis. Bruker

    Google Scholar 

  76. SIEVE. Thermo Fisher Scientific

    Google Scholar 

  77. Progenesis. Waters, Milford, MA, USA

    Google Scholar 

  78. Tautenhahn R, Patti GJ, Rinehart D, Siuzdak G (2012) XCMS online: A web-based platform to process untargeted metabolomic data. Anal Chem 84(11):5035–5039. https://doi.org/10.1021/ac300698c

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Tsugawa H, Cajka T, Kind T, Ma Y, Higgins B, Ikeda K, Kanazawa M, VanderGheynst J, Fiehn O, Arita M (2015) MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat Methods 12(6):523–526. https://doi.org/10.1038/nmeth.3393

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Katajamaa M, Miettinen J, Oresic M (2006) MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics 22(5):634–636. https://doi.org/10.1093/bioinformatics/btk039

    Article  CAS  PubMed  Google Scholar 

  81. MassBank of North America(2019). https://mona.fiehnlab.ucdavis.edu/. Accessed Sep 12, 2019

  82. Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, Ázquez-Fresno RV, Sajed T, Johnson D, Li C, Karu N et al (2018) HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res 46. https://doi.org/10.1093/nar/gkx1089

  83. NIST Standard Reference Database 1A v17|NIST (2019). https://www.nist.gov/srd/nist-standard-reference-database-1a-v17. Accessed Sep 12, 2019

  84. Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, Ojima Y, Tanaka K, Tanaka S, Aoshima K et al (2010) MassBank: A public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45(7):703–714. https://doi.org/10.1002/jms.1777

    Article  CAS  PubMed  Google Scholar 

  85. Jeffryes JG, Colastani RL, Elbadawi-Sidhu M, Kind T, Niehaus TD, Broadbelt LJ, Hanson AD, Fiehn O, Tyo KEJ, Henry CS (2015) MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics. J Cheminform 7(1):44. https://doi.org/10.1186/s13321-015-0087-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. mzCloud – Statistics (2019). https://www.mzcloud.org/Stats. Accessed Sep 12, 2019

  87. Huang X, Chen Y-J, Cho K, Nikolskiy I, Crawford PA, Patti GJX (2014) 13CMS: global tracking of isotopic labels in untargeted metabolomics. Anal Chem 86(3):1632–1639. https://doi.org/10.1021/ac403384n

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T et al (2007) KEGG for linking genomes to life and the environment. Nucleic Acids Res 36(Database):D480–D484. https://doi.org/10.1093/nar/gkm882

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Karp PD, Riley M, Paley SM, Pellegrini-Toole A (2002) The MetaCyc database. Nucleic Acids Res 30(1):59–61. https://doi.org/10.1093/nar/30.1.59

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Pico AR, Kelder T, van Iersel MP, Hanspers K, Conklin BR, Evelo C (2008) WikiPathways: pathway editing for the people. PLoS Biol 6(7):e184. https://doi.org/10.1371/journal.pbio.0060184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Kleinridders A, Ferris HA, Reyzer ML, Rath M, Soto M, Manier ML, Spraggins J, Yang Z, Stanton RC, Caprioli RM et al (2018) Regional differences in brain glucose metabolism determined by imaging mass spectrometry. Mol Metab 12:113–121. https://doi.org/10.1016/j.molmet.2018.03.013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Aue WP, Bartholdi E, Ernst RR (1976) Two-dimensional spectroscopy. Application to nuclear magnetic resonance. J Chem Phys 64(5):2229–2246. https://doi.org/10.1063/1.432450

    Article  CAS  Google Scholar 

  93. Martineau E, Dumez JN, Giraudeau P (2019., No. February, 1–14) Fast quantitative 2D NMR for metabolomics and lipidomics: a tutorial. Magn Reson Chem. https://doi.org/10.1002/mrc.4899

Download references

Author information

Authors and Affiliations

  1. Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA

    Emilio S. Rivera, Marissa A. Jones, Emma R. Guiberson & Jeremy L. Norris

  2. Department of Biochemistry, Vanderbilt University, Nashville, TN, USA

    Emilio S. Rivera & Jeremy L. Norris

  3. Department of Chemistry, Vanderbilt University, Nashville, TN, USA

    Marissa A. Jones & Emma R. Guiberson

Authors
  1. Emilio S. Rivera
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marissa A. Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Emma R. Guiberson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jeremy L. Norris
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Chemistry and Chemical Technology, University of Calabria, Arcavacata di Rende, Italy

    Giovanni Sindona

  2. Special Projects Science Branch, Fisheries and Oceans Canada, St. John’s, NL, Canada

    Joseph H. Banoub

  3. Department of Pharmacy, Health and Nurture Science, University of Calabria, Rende, Italy

    Maria Luisa Di Gioia

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature B.V.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Rivera, E.S., Jones, M.A., Guiberson, E.R., Norris, J.L. (2020). Fundamentals of Mass Spectrometry-Based Metabolomics. In: Sindona, G., Banoub, J.H., Di Gioia, M.L. (eds) Toxic Chemical and Biological Agents. NATO Science for Peace and Security Series A: Chemistry and Biology. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-2041-8_4

Download citation

Publish with us

Policies and ethics

Search

Navigation