Enlightening brain energy metabolism.

Brain tissue metabolism is distributed across several cell types and subcellular compartments, which activate at different times and with different temporal patterns. The introduction of genetically-encoded fluorescent indicators that are imaged using time-lapse microscopy has opened the possibility of studying brain metabolism at cellular and sub-cellular levels. There are indicators for sugars, monocarboxylates, Krebs cycle intermediates, amino acids, cofactors, and energy nucleotides, which inform about relative levels, concentrations and fluxes. This review offers a brief survey of the metabolic indicators that have been validated in brain cells, with some illustrative examples from the literature. Whereas only a small fraction of the metabolome is currently accessible to fluorescent probes, there are grounds to be optimistic about coming developments and the application of these tools to the study of brain disease.

Visualizing physiological parameters in cells and tissues using genetically encoded indicators for metabolites.

The study of metabolism is undergoing a renaissance. Since the year 2002, over 50 genetically-encoded fluorescent indicators (GEFIs) have been introduced, capable of monitoring metabolites with high spatial/temporal resolution using fluorescence microscopy. Indicators are fusion proteins that change their fluorescence upon binding a specific metabolite. There are indicators for sugars, monocarboxylates, Krebs cycle intermediates, amino acids, cofactors, and energy nucleotides. They permit monitoring relative levels, concentrations, and fluxes in living systems. At a minimum they report relative levels and, in some cases, absolute concentrations may be obtained by performing ad hoc calibration protocols. Proper data collection, processing, and interpretation are critical to take full advantage of these new tools. This review offers a survey of the metabolic indicators that have been validated in mammalian systems. Minimally invasive, these indicators have been instrumental for the purposes of confirmation, rebuttal and discovery. We envision that this powerful technology will foster metabolic physiology.