NMR-Based Metabolomics: Monitoring Metabolic Response to Physical Exercise

  • Chapter
  • First Online:
A Practical Guide to Metabolomics Applications in Health and Disease

Part of the book series: Learning Materials in Biosciences ((LMB))

  • 314 Accesses

Abstract

In this section, the principles of nuclear magnetic resonance (NMR) based metabolomics as well as the metabolic changes during and after exercise will be outlined. Using a straightforward, non-invasive experiment with an amateur road cyclist as a test subject, we will illustrate how NMR-based metabolomics, related data analysis, and biochemical pathways can be integrated and interpreted.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Friebolin H, Becconsall JK. Basic one-and two-dimensional NMR spectroscopy. Wiley-VCH Weinheim. 2005;7

    Google Scholar 

  2. Bouatra S, Aziat F, Mandal R, Guo AC, Wilson MR, Knox C, Bjorndahl TC, Krishnamurthy R, Saleem F, Liu P, Dame ZT, Poelzer J, Huynh J, Yallou FS, Psychogios N, Dong E, Bogumil R, Roehring C, Wishart DS. The human urine metabolome. PLoS One. 2013;8(9):e73076.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. De Meyer T, Sinnaeve D, Van Gasse B, Tsiporkova E, Rietzschel ER, De Buyzere ML, Gillebert TC, Bekaert S, Martins JC, Van Criekinge W. NMR-based characterization of metabolic alterations in hypertension using an adaptive, intelligent binning algorithm. Anal Chem. 2008;80(10):3783–90.

    Article  PubMed  Google Scholar 

  4. Kostidis S, Addie RD, Morreau H, Mayboroda OA, Giera M. Quantitative NMR analysis of intra- and extracellular metabolism of mammalian cells: a tutorial. Anal Chim Acta. 2017;980:1–24.

    Article  CAS  PubMed  Google Scholar 

  5. Rosen Vollmar AK, Rattray NJW, Cai Y, Santos-Neto ÁJ, Deziel NC, Jukic AMZ, Johnson CH. Normalizing untargeted periconceptional urinary metabolomics data: a comparison of approaches. Meta. 2019;9(10):198.

    Google Scholar 

  6. Dieterle F, Ross A, Schlotterbeck G, Senn H. Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. Anal Chem. 2006;78(13):4281–90.

    Article  CAS  PubMed  Google Scholar 

  7. van den Berg RA, Hoefsloot HCJ, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics. 2006;7(1):142.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Murenu E, Kostidis S, Lahiri S, Geserich AS, Imhof A, Giera M, Michalakis S. Metabolic analysis of vitreous/lens and retina in wild type and retinal degeneration mice. Int J Mol Sci. 2021;22(5):2345.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Gandhi S, Chinnadurai V, Bhadra K, Gupta I, Kanwar RS. Urinary metabolic modulation in human participants residing in Siachen: a 1H NMR metabolomics approach. Sci Rep. 2022;12(1):9070.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;100(2):126–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Hawley JA, Hargreaves M, Joyner MJ, Zierath JR. Integrative biology of exercise. Cell. 2014;159(4):738–49.

    Article  CAS  PubMed  Google Scholar 

  12. Hargreaves M, Spriet LL. Skeletal muscle energy metabolism during exercise. Nat Metab. 2020;2(9):817–28.

    Article  CAS  PubMed  Google Scholar 

  13. McPherson PAC. Ketone bodies. In: Caballero B, Finglas PM, Toldrá F, editors. Encyclopedia of food and health. Oxford: Academic Press; 2016. p. 483–9.

    Chapter  Google Scholar 

  14. Pinckaers PJM, Churchward-Venne TA, Bailey D, van Loon LJC. Ketone bodies and exercise performance: the next magic bullet or merely hype? Sports Med. 2017;47(3):383–91.

    Article  PubMed  Google Scholar 

  15. Johnson RH, Walton JL, Krebs HA, Williamson DH. Post-exercise ketosis. Lancet. 1969;294(7635):1383–5.

    Article  Google Scholar 

  16. Dhatariya KK, Glaser NS, Codner E, Umpierrez GE. Diabetic ketoacidosis. Nat Rev Dis Primers. 2020;6(1):40.

    Article  PubMed  Google Scholar 

  17. Giacomoni F, Le Corguillé G, Monsoor M, Landi M, Pericard P, Pétéra M, Duperier C, Tremblay-Franco M, Martin J-F, Jacob D, Goulitquer S, Thévenot EA, Caron C. Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics. Bioinformatics (Oxford, England). 2015;31(9):1493–5.

    CAS  PubMed  Google Scholar 

  18. Goecks J, Nekrutenko A, Taylor J, The Galaxy T. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010;11(8):R86.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Verhoeven A, Giera M, Mayboroda OA. KIMBLE: a versatile visual NMR metabolomics workbench in KNIME. Anal Chim Acta. 2018;1044:66–76.

    Article  CAS  PubMed  Google Scholar 

  20. Berthold MR, Cebron N, Dill F, Gabriel TR, Kötter T, Meinl T, Ohl P, Sieb C, Thiel K, Wiswedel B. KNIME: The Konstanz information miner. In: Preisach C, Burkhardt H, Schmidt-Thieme L, Decker R, editors. Data analysis, machine learning and applications. Berlin, Heidelberg: Springer; 2008. p. 319–26.

    Chapter  Google Scholar 

  21. Chong J, Soufan O, Li C, Caraus I, Li S, Bourque G, Wishart DS, **a J. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res. 2018;46(W1):W486–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Madrid-Gambin F, Oller-Moreno S, Fernandez L, Bartova S, Giner MP, Joyce C, Ferraro F, Montoliu I, Moco S, Marco S. AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics. Bioinformatics (Oxford, England). 2020;36(9):2943–5.

    CAS  PubMed  Google Scholar 

  23. Liu G, Hinch B, Beavis AD. Mechanisms for the transport of α,ω-dicarboxylates through the mitochondrial inner membrane. J Biol Chem. 1996;271(41):25338–44.

    Article  CAS  PubMed  Google Scholar 

  24. Smith HG. The metabolism of azelaic acid. J Biol Chem. 1933;103(2):531–5.

    Article  CAS  Google Scholar 

  25. Mortensen PB. C6--C10-dicarboxylic aciduria in starved, fat-fed and diabetic rats receiving decanoic acid or medium-chain triacylglycerol. An in vivo measure of the rate of beta-oxidation of fatty acids. Biochim Biophys Acta. 1981;664(2):349–55.

    Article  CAS  PubMed  Google Scholar 

  26. Bergseth S, Poisson J-P, Bremer J. Metabolism of dicarboxylic acids in rat hepatocytes. Biochim Biophys Acta (BBA) – Lipids Lipid Metab. 1990;1042(2):182–7.

    Article  CAS  Google Scholar 

  27. Bharathi SS, Zhang Y, Gong Z, Muzumdar R, Goetzman ES. Role of mitochondrial acyl-CoA dehydrogenases in the metabolism of dicarboxylic fatty acids. Biochem Biophys Res Commun. 2020;527(1):162–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Mortensen PB. The possible antiketogenic and gluconeogenic effect of the ω-oxidation of fatty acids in rats. Biochim Biophys Acta (BBA) – Lipids Lipid Metab. 1980;620(2):177–85.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Aswin Verhoeven or Martin Giera .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Verhoeven, A., Derks, R.J., Giera, M. (2023). NMR-Based Metabolomics: Monitoring Metabolic Response to Physical Exercise. In: Ivanisevic, J., Giera, M. (eds) A Practical Guide to Metabolomics Applications in Health and Disease. Learning Materials in Biosciences. Springer, Cham. https://doi.org/10.1007/978-3-031-44256-8_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-44256-8_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-44255-1

  • Online ISBN: 978-3-031-44256-8

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Navigation