Spatially resolved fluorescence lifetime mapping of enzyme kinetics in living cells

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Abstract

Summary

Traditional cuvette-based enzyme studies lack spatial information and do not allow real-time monitoring of the effects of modulating enzyme functions in vivo. In order to probe the realistic timescales of steric modifications in enzyme–substrate complexes and functional binding–unbinding kinetics in living cells without losing spatial information, it is imperative to develop sensitive imaging strategies that can report enzyme kinetics in real time over a wide dynamic range of timescales. Here we present a multi-photon excitation-based, ultra-fast photon detection using a streak camera and Laguerre expansion-based fast deconvolution approach for achieving high spatio-temporal resolution in monitoring real-time enzyme kinetics in single cells. In particular, we report spatially resolved, nanosecond-scale fluorescence dynamics associated with binding–unbinding kinetics of endogenous metabolic co-factor nicotinamide adenine dinucleotide with enzymes in intact living cells. By monitoring real-time kinetics of NAD(P)H–enzyme kinetics in primary hepatocytes isolated from young and aged mouse models, we observed that the mechanism of inhibition of mitochondrial respiration at complex I site is mediated by redistribution of free and protein-bound nicotinamide adenine dinucleotide pools and that this equilibrium redistribution is affected by age-related modifications in mitochondrial function. We describe unique advantages of Laguerre deconvolution algorithm in comparison with conventional lifetime analysis approaches. Non-invasive monitoring of metabolic dysfunctions in intact animal models is an attractive strategy for gaining insight into the dynamics of tissue metabolism in health and in various metabolic syndromes such as cancer, diabetes and aging-induced metabolic dysfunctions. Besides the example demonstrated above, we envisage that the proposed method can find applications in a variety of other situations where intensity-based approaches fall short owing to spectroscopic artefacts.

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