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. 2019 Feb 27;97(1):41–47. doi: 10.3184/003685014X13898807933527

Nutrimetabonomics: Nutritional Applications of Metabolic Profiling

Jonathan R Swann 1,, Sandrine P Claus 1,
PMCID: PMC10365364  PMID: 24800468

Abstract

An individual's metabolic phenotype, and ultimately health, is significantly influenced by complex interactions between their genes and the diet. Studying these associations and their downstream biochemical consequences has proven extremely challenging using traditional hypothesis-led strategies. Metabonomics, a systems biology approach, allows the global metabolic response of biological systems to stimuli to be characterised. Through the application of this approach to nutritional-based research, nutrimetabonomics, the biochemical response to dietary inputs is being investigated at greater levels of resolution. This has allowed novel insights to be gained regarding intricate diet-gene interactions and their consequences for health and disease. In this review, we present some of the latest research exploring how nutrimetabonomics can assist in the elucidation of novel biomarkers of dietary behaviour and provide new perspectives on diet-health relationships. The use of this approach to study the metabolic interplay between the gut microbiota and the host is also explored.

Keywords: nutrimetabonomics, nutrition, gut microbiota, metabolic profiling

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References

  • 1.Wild C.P. (2005) Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol. Biomarkers Prev., 14, 1847–1850. [DOI] [PubMed] [Google Scholar]
  • 2.Claus S.P., and Swann J.R. (2013) Nutrimetabonomics: applications for nutritional sciences, with specific reference to gut microbial interactions. Ann. Rev. Food Sci. Technol., 4, 381–399. [DOI] [PubMed] [Google Scholar]
  • 3.Heinzmann S.S., Brown I.J., Chan Q. et al. (2010) Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption. Am. J. Clin. Nutr., 92, 436–443. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Lloyd A.J., Beckmann M., Favé G., Mathers J.C., and Draper J. (2011) Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption. Br. J. Nutr., 106, 812–824. [DOI] [PubMed] [Google Scholar]
  • 5.Pujos-Guillot E., Hubert J., Martin J.-F. et al. (2013) Mass Spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study. J. Proteome Res., 12, 1645–1659. [DOI] [PubMed] [Google Scholar]
  • 6.Edmands W.M.B., Beckonert O.P., Stella C. et al. (2011) Identification of human urinary biomarkers of cruciferous vegetable consumption by metabonomic profiling. J. Proteome Res., 10, 4513–4521. [DOI] [PubMed] [Google Scholar]
  • 7.Holmes E., Loo R.-L., and Stamler J. et al. (2008) Human metabolic phenotype diversity and its association with diet and blood pressure. Nature, 453, 396–401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Lloyd A.J., Favé G., Beckmann M. et al. (2011) Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods. Am. J. Clin. Nutr., 94, 981–991. [DOI] [PubMed] [Google Scholar]
  • 9.Rezzi S., Ramadan Z., Fay L.B., and Kochhar S. (2007) Nutritional metabonomics: applications and perspectives. J. Proteome Res., 6, 513–525. [DOI] [PubMed] [Google Scholar]
  • 10.Lankinen M., Schwab U., Erkkilä A. et al. (2009) Fatty fish intake decreases lipids related to inflammation and insulin signaling–a lipidomics approach. PLoS one, 4, e5258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Fardet A., Canlet C., Gottardi G. et al. (2007) Whole-grain and refined wheat flours show distinct metabolic profiles in rats as assessed by a 1H NMR-based metabonomic approach. J. Nutr., 137, 923–929. [DOI] [PubMed] [Google Scholar]
  • 12.Stella C., Beckwith-Hall B., Cloarec O. et al. (2006) Susceptibility of human metabolic phenotypes to dietary modulation. J. Proteome Res., 5, 2780–2788. [DOI] [PubMed] [Google Scholar]
  • 13.Wang Y., Tang H., Nicholson J.K., Hylands P.J., Sampson J., and Holmes E. (2005) A metabonomic strategy for the detection of the metabolic effects of chamomile (Matricaria recutita L.) ingestion. J. Agric. Food Chem., 53, 191–196. [DOI] [PubMed] [Google Scholar]
  • 14.Van Dorsten F.A., Daykin C.A., Mulder T.P.J., Van Duynhoven J.P.M. (2006) Metabonomics approach to determine metabolic differences between green tea and black tea consumption. J. Agric. Food Chem., 54, 6929–6938. [DOI] [PubMed] [Google Scholar]
  • 15.Daykin C.A., Van Duynhoven J.P.M., Groenewegen A., Dachtler M., Van Amelsvoort J.M.M., and Mulder T.P.J. (2005) Nuclear magnetic resonance spectroscopic based studies of the metabolism of black tea polyphenols in humans. J. Agric. Food Chem., 53, 1428–1434. [DOI] [PubMed] [Google Scholar]
  • 16.Solanky K.S., Bailey N.J.C., Beckwith-Hall B.M. et al. (2003) Application of biofluid 1H nuclear magnetic resonance-based metabonomic techniques for the analysis of the biochemical effects of dietary isoflavones on human plasma profile. Anal. Biochem., 323, 197–204. [DOI] [PubMed] [Google Scholar]
  • 17.Merrifield C.A., Lewis M.C., Claus S.P. et al. (2012) Weaning diet induces sustained metabolic phenotype shift in the pig and influences host response to Bifidobacterium lactis NCC2818. Gut., 62, 842–851. [DOI] [PubMed] [Google Scholar]
  • 18.Swann J.R., Tuohy K.M., Lindfors P. et al. (2011) Variation in antibiotic-induced microbial recolonisation impacts on the host metabolic phenotypes of rats. J. Proteome Res., 10, 3590–3603. [DOI] [PubMed] [Google Scholar]
  • 19.Claus S.P., Ellero S.L., Berger B. et al. (2011) Colonisation-induced host-gut microbial metabolic interaction. MBio., 2, 2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Swann J.R., Want E.J., Geier F.M. et al. (2011) Systemic gut microbial modulation of bile acid metabolism in host tissue compartments. Proc. Natl. Acad. Sci., 108, Suppl 1, 4523–4530. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Kok M.G.M., Ruijken M.M.A., Swann J.R., Wilson I.D., Somsen G.W., and Jong G.J. (2013) Anionic metabolic profiling of urine from antibiotic-treated rats by capillary electrophoresis–mass spectrometry. Anal. Bioanal. Chem., 405, 2585–2594. [DOI] [PubMed] [Google Scholar]
  • 22.Lees H.J., Swann J.R., Wilson I.D., Nicholson J.K., and Holmes E. (2013) Hippurate: The Natural History of a Mammalian–Microbial Cometabolite. J. Proteome Res., 12, 1527–1546. [DOI] [PubMed] [Google Scholar]
  • 23.Turnbaugh P.J., Ley R.E., Hamady M., Fraser-Liggett C.M., Knight R., and Gordon J.I. (2007) The human microbiome project. Nature, 449, 804–810. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Smith M.I., Yatsunenko T., Manary M.J. et al. (2013) Gut microbiomes of Malawian Twin pairs discordant for Kwashiorkor. Science, 339, 548–554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Boulangé C.L., Claus S.P., Chou C.J. et al. (2013) Early metabolic adaptation in C57BL/6 mice resistant to high fat diet induced weight gain involves an activation of mitochondrial oxidative pathways. J. Proteome Res., 12, 1956–1968. [DOI] [PubMed] [Google Scholar]
  • 26.Dewulf E.M., Cani P.D., Claus S.P. et al. (2012) Insight into the prebiotic concept: lessons from an exploratory, double blind intervention study with inulin-type fructans in obese women. Gut, doi:10.1136/gutjnl-2012-303304. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Calvani R., Miccheli A., Capuani G. et al. (2010) Gut microbiome-derived metabolites characterise a peculiar obese urinary metabotype. Int. J. Obes. (Lond.), 34, 1095–1098. [DOI] [PubMed] [Google Scholar]
  • 28.Zuppi C., Messana I., Forni F. et al. (1997) 1H NMR spectra of normal urines: reference ranges of the major metabolites. Clin. Chim. Acta, 265, 85–97. [DOI] [PubMed] [Google Scholar]
  • 29.Arora T., Loo R.-L., Anastasovska J. et al. (2012) Differential effects of two fermentable carbohydrates on central appetite regulation and body composition. PLoS one, 7, e43263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Nicholson J.K., and Wilson I.D. (2003) Understanding “global” systems biology: metabonomics and the continuum of metabolism. Nat. Rev. Drug Discov., 2, 668–676. [DOI] [PubMed] [Google Scholar]
  • 31.Nicholson J., Lindon J., and Holmes E. (1999) “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 29, 1181–1189. [DOI] [PubMed] [Google Scholar]

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