Single cell analysis of metabolism using genetically-encoded fluorescent sensors

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DESCRIPTION Abstract: Metabolic pathways provide essential energy and building blocks for the function of all cells, and dysregulation of these pathways is a central feature of cancer, diabetes, and obesity, which kill or disable millions of Americans every year. The components of core metabolic pathways such as glycolysis have been very well understood for decades, but there are still major gaps in our understanding of their integrated behavior and regulation in the context of living cells. A major challenge to understanding normal metabolism and its dysregulation in human disease is that metabolic behavior can vary dramatically from cell to cell, and over time within a single cell. For example, metabolic state can differ radically between neighboring cell types in a tissue, creating a functional segregation that is important for overall tissue function, or between a single metastatic cancer cell and the surrounding normal cells. Such spatial differences as well as dynamic changes in metabolism within a single cell are invisible to the usual biochemical methods or even modern metabolomic methods, which require disruption of the living cell and homogenization of tissue. Fluorescent sensors of metabolism, engineered by combining fluorescent proteins with metabolite binding proteins, can address this challenge by enabling us to monitor key metabolites in real time, in single living cells, or in hundreds of cells in paralle. We recently piloted the development of novel sensors for two key metabolites (ATP and NADH), in order to address specific neurobiological questions about how metabolism influences neuronal ion channels and can reduce susceptibility to epileptic seizures. But our preliminary results with these sensors have underscored the general problem of cell heterogeneity as well as the need for a much larger toolkit of fluorescent metabolite sensors. We propose to develop a suite of novel sensors for key metabolites in order to address fundamental questions of cellular me