Whilst there is much current interest in the genome-wide analysis of cells at the level of transcription (to define the 'transcriptome') and translation (to define the 'proteome'), the third level of analysis, that of the 'metabolome', has been curiously unexplored to date. The term 'metabolome' refers to the entire complement of all the small molecular weight metabolites inside a cell suspension (or other sample) of interest. It is likely that measurement of the metabolome in different physiological states will in fact be much more discriminating for the purposes of functional genomics. Why should this be so?

As proven in the summation theorem of Metabolic Control Analysis (MCA), changes in the concentrations of individual enzymes tend to have little effect on particular metabolic fluxes (nor, indeed, on the phenotype under most laboratory conditions). However, in part because of the so-called connectivities of MCA, changes in individual enzyme concentrations can and do have substantial effects on metabolite concentrations, even when the changes in flux are negligible.

We have long pioneered the rapid analysis of metabolites at the whole-cell level, using methods such as Pyrolysis mass spectrometry, Fourier-Transfrom Infrared Spectrometry, Raman spectrometry, GC-MS, and most recently, LC-Electrospray and cap-LC-tandem-electrospray mass spectrometries. In combination with our established chemometrics methods, including artificial neural networks and genetic programming, these methods have been shown, in many publications, to be highly capable of discriminating closely related samples. Current work is directed to the development and exploitation of these and related methods for the purposes of functional genomics.


Here are some metabolome-related links:



Here are some of our recent metabolome publications:


Last updated: May 31, 2016 at 9:37 am