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Metabolite Identification in Complex Mixtures Using Nuclear Magnetic Resonance Spectroscopy

Reference work entry

Abstract

Metabolomics has become a major tool in the analysis of food samples and the investigation of the impact of food on human health. Food samples, and biofluids in which food-derived metabolites are found, are complex mixtures of metabolites. Metabolomics aims to capture the entire set of metabolites (small molecules) present in a sample, using methods such as mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy. However, identification of those metabolites remains a challenging task, and this chapter describes these challenges in relation to analysis of complex mixtures using nuclear NMR spectroscopy. Major challenges include the large diversity in metabolites, the problem of spectral overlap, and the lack of available reference spectra. The identification of known metabolites (structural confirmation) using a combination of NMR spectroscopy methods and the importance of spectral databases and emerging software tools for structural confirmation are presented. The importance of NMR spectroscopy in structural elucidation of novel metabolites is also described, with the contribution of mass spectrometry and hyphenated systems highlighted. Finally, the debate on reporting standards for metabolite identifications and annotations to facilitate data sharing and the emerging scoring systems to communicate confidence in metabolite identifications are discussed. Without comprehensive metabolite identification, biological interpretation of metabolomics results may be misleading or incomplete and so understanding of how metabolites are identified and the confidence in those identifications is crucial.

Keywords

1D-1H-NMR 2D-NMR Annotation Complex mixtures Databases Hyphenation Liquid chromatography (LC) Mass spectrometry (MS) Metabolite identification Molecular structure encoding texts (SMILES and InChI) Purification Reporting standards Software tools Solid phase extraction (SPE) Spectral matching Structural confirmation Structural elucidation 

Notes

Acknowledgments

Justin van der Hooft is supported by the Wellcome Trust (grant no. 105614/Z/14/Z). Naomi Rankin is supported by UPBEAT – The UPBEAT RCT mother-child study. Stratifying and treating obese pregnant women to prevent adverse pregnancy, perinatal and longer term outcomes – MRC (MR/L002477/1).

Glasgow Polyomics (including the NMR metabolomics facility) is supported by the Wellcome Trust (grant no. 105614/Z/14/Z). Our recent work in 1H-NMR metabolomics is supported by (i) the Chief Scientist Office, Scotland (CZB/4/613); (ii) The Wellcome Trust Institutional Strategic Support Fund (ISSF) (WT097821MF and 105614/z/14/z); (iii) The European Federation of Pharmaceutical Industries Associations (EFPIA) Innovative Medicines Initiative Joint Undertaking (EMIF) (grant number 115372); (iv) The European commission, under the Health Cooperation Work Programme of the 7th Framework Programme (Grant number 305507) under Heart “omics” in AGEing (HOMAGE); and (v) chest, heart and stroke Scotland (R13/A149).

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Authors and Affiliations

  1. 1.College of Medical, Veterinary and Life SciencesGlasgow Polyomics/University of GlasgowGlasgowUK
  2. 2.Institute of Cardiovascular and Medical Sciences (ICAMS), BHF Glasgow Cardiovascular Research Centre and Glasgow PolyomicsCollege of Medical, Veterinary and Life Sciences, University of GlasgowGlasgowUK

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