Real-time metabolic analysis of living cancer cells with correlated cellular spectro-microscopy

In recent years, major efforts have been devoted to the application of microscopy with mid-infrared light to the study of living cells and tissue. Despite this interest, infrared (IR) microscopy has not realized its full potential in the molecular characterization of living systems. This is partly due to the fact that current approaches for data mining and analysis of IR absorption spectra have not evolved comparably to measurement technology and are not up to the interpretation of the complex spectra of living systems such as cells and tissue. In this work we show that the use of two-dimensional correlation spectroscopy coupled to IR absorption spectro-microscopy allows us to extract the spectral components of individual metabolites from time-resolved IR spectra of living cells. We call this method correlated cellular spectro-microscopy, and we implement it in the study of the glycolytic metabolism of cancer cells. We show that the method can detect intermediates of the glycolytic pathway, quantify their rate of formation, and correlate this with variations in pH, all in a single measurement. We propose the method as a useful tool for the quantitative description of metabolic processes in living cells and for the validation of drug candidates aimed at suppressing glycolysis in cancer cells.