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Data handling for interactive metabolomics: tools for studying the dynamics of metabolome-macromolecule interactions

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Abstract

All published metabolomics studies investigate changes in either absolute or relative quantities of metabolites. However, blood plasma, one of the most commonly studied biofluids for metabolomics applications, is a complex, heterogeneous mixture of lipoproteins, proteins, small organic molecules and ions which together undergo a variety of possible molecular interactions including metal complexation, chemical exchange processes, micellular compartmentation of metabolites, enzyme-mediated biotransformations and small-molecule-macromolecule binding. In particular, many low molecular weight (MW) compounds (including drugs) can exist both ‘free’ in solution and bound to proteins or within organised aggregates of macromolecules. To study the effects of e.g. disease on these interactions we suggest that new approaches are needed. We have developed a technique termed ‘interactive metabolomics’ or i-metabolomics. i-metabolomics can be defined as: “The study of interactions between low MW biochemicals and macromolecules in heterogeneous biosamples such as blood plasma, without pre-selection of the components of interest”. Standard 1D NMR experiments commonly used in metabolomics allow metabolite concentration differences between samples to be investigated because the intensity of each peak depends on the concentration of the compound in question. On the other hand, the instrument can be set-up to measure molecular interactions by monitoring the diffusion coefficients of molecules. According to the Stokes–Einstein equation, the diffusion coefficient of a molecule is inversely proportional to its effective size, as represented by the hydrodynamic radius. Therefore, when low MW compounds are non-covalently bound to proteins, the observed diffusion coefficient for the compound will be intermediate between those of its free and bound forms. By measuring diffusion by NMR, the degree of protein binding can be estimated for either low MW endogenous biochemicals or xenobiotics. This type of experiment is referred to as either Diffusion-Ordered Spectroscopy (DOSY) or Diffusion-Edited Spectroscopy, depending on the type of post-acquisition data processing applied to the spectra. Results presented in this paper demonstrate approaches for the non-selective modelling of metabolite-macromolecule interactions (i-metabolomics), whilst additionally highlighting some of the all too frequently ignored issues associated with interpretation of data derived from profiling of blood plasma.

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Acknowledgments

The authors would like to thank Dr. Jonathan Byrne (School of Pharmacy, University of Nottingham, now School of Biosciences, University of Birmingham) for his contribution to the early stages of this project, Angela Savage (School of Pharmacy, University of Nottingham) for technical assistance during this work. Professor Gareth Morris and Dr. Matteis Nilsson (University of Manchester) are also gratefully acknowledged for fruitful discussions on the initial set up of the diffusion experiments. Finally, the EPSRC are thanked for funding of the work (EPSRC Grant number EP/F014767/1).

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  1. Florian Wulfert

    Present address: Department of Biosciences, Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield, S1 1WB, UK

Authors and Affiliations

  1. Division of Molecular and Cellular Science, School of Pharmacy, University of Nottingham, Nottingham, NG7 2RD, UK

    Clare A. Daykin & Florian Wulfert

  2. Department of Food Science, Faculty of Life Sciences, University of Copenhagen, 1958, Frederiksberg C, Denmark

    Rasmus Bro

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Correspondence to Clare A. Daykin.

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Daykin, C.A., Bro, R. & Wulfert, F. Data handling for interactive metabolomics: tools for studying the dynamics of metabolome-macromolecule interactions. Metabolomics 8 (Suppl 1), 52–63 (2012). https://doi.org/10.1007/s11306-011-0359-3

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