Interactive Metabolomics: Development of a Tool to Study Changes in Metabolome-Macromolecule Dynamics

Investigation into the biochemical effects of a disease, or treatment with a particular medication, commonly involves the compositional analysis of body fluids and in particular, blood plasma. However, blood plasma is an extremely complex and heterogeneous biological fluid whose components undergo a variety of possible interactions including, amongst others, the binding and interaction of many small compounds (including drugs) with larger molecules, such as proteins. Whilst many studies have been carried out to look at the effects of drug-protein binding, which is recognized as an important phenomenon, little is actually known about the biochemical consequences of interactions between proteins and the body's own biochemicals. Therefore information intrinsically encoded in these interactions is to a large extent ignored. In fact, from a measurement science perspective, the presence of these interactions is often considered a troublesome interference which makes the analysis of blood plasma non-trivial and which must be removed prior to accurate quantitative analysis of endogenous compounds in a sample. However, if we are to fully characterize the metabolic status of an individual, it is unlikely that 'simple' quantification of plasma components is enough and gaining a fuller understanding of these interactions is therefore of critical importance.In order to achieve this aim, the project will build on results from a previous feasibility study and will develop a tool which will allow rapid profiles to be generated showing differences between samples based on how the components of the sample interact with each other. Nuclear Magnetic Resonance (NMR) spectroscopy is a very powerful technique able to detect interactions of this type in whole blood plasma, with minimal disturbance to the sample. This can be achieved by setting up the NMR spectrometer to simultaneously monitor the diffusion rate of all the NMR-visible molecules present in the biological sample. The diffusion rate of a molecule is directly proportional to its size and therefore when a small compound interacts with a larger molecule such as a protein, the observed diffusion rate of the small compound will be slower than if there is no interaction. By measuring diffusion rate by NMR, an estimation of the degree of interaction can be made for either small biochemicals generated by the body or drugs. The proposed work will focus on the application of this technique to probe changes in diffusion rates of all components of a complex heterogeneous biofluid such as blood plasma, simultaneously, in a single experiment and without pre-selection of the interactions of interest. In order to relate differences in measured diffusion rates, and hence also interactions between components in the sample, to disease-status, drug treatment or drug toxicity, statistical pattern recognition approaches will be used to interrogate the resultant diffusion-based blood plasma profiles.