Karen Deuschle

Construction and optimization of a family of genetically encoded metabolite sensors by semirational protein engineering

A family of genetically‐encoded metabolite sensors has been constructed using bacterial periplasmic binding proteins (PBPs) linearly fused to protein fluorophores. The ligand‐induced conformational change in a PBP allosterically regulates the relative distance and orientation of a fluorescence resonance energy transfer (FRET)‐compatible protein pair. Ligand binding is transduced into a macroscopic FRET observable, providing a reagent for in vitro and in vivo ligand‐measurement and visualization. Sensors with a higher FRET signal change are required to expand the dynamic range and allow visualization of subtle analyte changes under high noise conditions. Various observations suggest that factors other than inter‐fluorophore separation contribute to FRET transfer efficiency and the resulting ligand‐dependent spectral changes. Empirical and rational protein engineering leads to enhanced allosteric linkage between ligand binding and chromophore rearrangement; modifications predicted to decrease chromophore rotational averaging enhance the signal change, emphasizing the importance of the rotational freedom parameter κ2 to FRET efficiency. Tighter allosteric linkage of the PBP and the fluorophores by linker truncation or by insertion of chromophores into the binding protein at rationally designed sites gave rise to sensors with improved signal change. High‐response sensors were obtained with fluorescent proteins attached to the same binding PBP lobe, suggesting that indirect allosteric regulation during the hinge‐bending motion is sufficient to give rise to a FRET response. The optimization of sensors for glucose and glutamate, ligands of great clinical interest, provides a general framework for the manipulation of ligand‐dependent allosteric signal transduction mechanisms.

Rapid Metabolism of Glucose Detected with FRET Glucose Nanosensors in Epidermal Cells and Intact Roots of Arabidopsis RNA-Silencing Mutants

Genetically encoded glucose nanosensors have been used to measure steady state glucose levels in mammalian cytosol, nuclei, and endoplasmic reticulum. Unfortunately, the same nanosensors in Arabidopsis thaliana transformants manifested transgene silencing and undetectable fluorescence resonance energy transfer changes. Expressing nanosensors in sgs3 and rdr6 transgene silencing mutants eliminated silencing and resulted in high fluorescence levels. To measure glucose changes over a wide range (nanomolar to millimolar), nanosensors with higher signal-to-noise ratios were expressed in these mutants. Perfusion of leaf epidermis with glucose led to concentration-dependent ratio changes for nanosensors with in vitro Kd values of 600 μM (FLIPglu-600μΔ13) and 3.2 mM (FLIPglu-3.2mΔ13), but one with 170 nM Kd (FLIPglu-170nΔ13) showed no response. In intact roots, FLIPglu-3.2mΔ13 gave no response, whereas FLIPglu-600μΔ13, FLIPglu-2μΔ13, and FLIPglu-170nΔ13 all responded to glucose. These results demonstrate that cytosolic steady state glucose levels depend on external supply in both leaves and roots, but under the conditions tested they are lower in root versus epidermal and guard cells. Without photosynthesis and external supply, cytosolic glucose can decrease to <90 nM in root cells. Thus, observed gradients are steeper than expected, and steady state levels do not appear subject to tight homeostatic control. Nanosensor-expressing plants can be used to assess glucose flux differences between cells, invertase-mediated sucrose hydrolysis in vivo, delivery of assimilates to roots, and glucose flux in mutants affected in sugar transport, metabolism, and signaling.

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

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.

Genetically encoded sensors for metabolites

Metabolomics, i.e., the multiparallel analysis of metabolite changes occurring in a cell or an organism, has become feasible with the development of highly efficient mass spectroscopic technologies. Functional genomics as a standard tool helped to identify the function of many of the genes that encode important transporters and metabolic enzymes over the past few years. Advanced expression systems and analysis technologies made it possible to study the biochemical properties of the corresponding proteins in great detail. We begin to understand the biological functions of the gene products by systematic analysis of mutants using systematic PTGS/RNAi, knockout and TILLING approaches. However, one crucial set of data especially relevant in the case of multicellular organisms is lacking: the knowledge of the spatial and temporal profiles of metabolite levels at cellular and subcellular levels.

Genetically encoded sensors for ions and metabolites

Abstract Many of the genes encoding important trans porters and metabolic enzymes have been identified over the last ten years. Moreover it has been possible to study the biochemical properties of the corresponding proteins in great detail. It is expected that by 2,010 biochemical functions will have been assigned to many of the products of the approximately 30,000 Arabidopsis genes. We will get closer to understanding the biological function of the gene products by systematic analysis of mutants using knock-out and TILLING approaches. Metabolomics initiatives complement these approaches by providing insight into the changes in cellular ion and metabolite profiles in the mutants, thus giving information essential for the construction of cellular and whole plant models. However, one important dataset especially relevant to multicellular organisms is lacking: the knowledge of the spatial and temporal profiles of ions and metabolite levels at cellular and subcell ular levels. To address this issue, we have developed protein-based nanosensors for several metabolites, providing a set of tools for the determination of cytosolic and subcellular ion (e.g. iron and zinc) and metabolite levels in real time using fluorescence-based microscopy. The prototypes of these sensors were shown to function in vitro and also in vivo, i.e. in yeast and in mammalian cell cultures. One future goal is to expand the set of sensors to a wider spectrum of targets by using the natural spectrum of periplasmic binding proteins from bacteria and by computational design of proteins with altered binding pockets. Application of nanosensor technology to plant cells and tissues will help to elucidate the special and temporal distribution of ions and metabolites.