To investigate metabolic changes during cellular transformation, we used a 1 H NMR based metabolite–metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite–metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome.
Madhu, B., Narita, M., Jauhiainen, A., Menon, S., Stubbs, M., Tavaré, S., … Griffiths, J. R. (2015). Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression. Metabolomics, 11(6), 1848–1863. https://doi.org/10.1007/s11306-015-0838-z