Article

Development and use of fluorescent nanosensors for metabolite imaging in living cells.

Carnegie Institution, Plant Biology, 260 Panama St., Stanford, CA 94305, USA.
Biochemical Society Transactions (Impact Factor: 3.24). 03/2005; 33(Pt 1):287-90. DOI: 10.1042/BST0330287
Source: PubMed

ABSTRACT To understand metabolic networks, fluxes and regulation, it is crucial to be able to determine the cellular and subcellular levels of metabolites. Methods such as PET and NMR imaging have provided us with the possibility of studying metabolic processes in living organisms. However, at present these technologies do not permit measuring at the subcellular level. The cameleon, a fluorescence resonance energy transfer (FRET)-based nanosensor uses the ability of the calcium-bound form of calmodulin to interact with calmodulin binding polypeptides to turn the corresponding dramatic conformational change into a change in resonance energy transfer between two fluorescent proteins attached to the fusion protein. The cameleon and its derivatives were successfully used to follow calcium changes in real time not only in isolated cells, but also in living organisms. To provide a set of tools for real-time measurements of metabolite levels with subcellular resolution, protein-based nanosensors for various metabolites were developed. The metabolite nanosensors consist of two variants of the green fluorescent protein fused to bacterial periplasmic binding proteins. Different from the cameleon, a conformational change in the binding protein is directly detected as a change in FRET efficiency. The prototypes are able to detect various carbohydrates such as ribose, glucose and maltose as purified proteins in vitro. The nanosensors can be expressed in yeast and in mammalian cell cultures and were used to determine carbohydrate homeostasis in living cells with subcellular resolution. One future goal is to expand the set of sensors to cover a wider spectrum of metabolites by using the natural spectrum of bacterial periplasmic binding proteins and by computational design of the binding pockets of the prototype sensors.

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