Genetically encoded sensors for metabolites.

BACKGROUND: 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. METHODS: We therefore developed genetically encoded nanosensors for several metabolites to provide a basic set of tools for the determination of cytosolic and subcellular metabolite levels in real time by using fluorescence microscopy. RESULTS: Prototypes of these sensors were successfully used in vitro and also in vivo, i.e., to measure sugar levels in fungal and animal cells. CONCLUSIONS: One of the future goals will be to expand the set of sensors to a wider spectrum of substrates by using the natural spectrum of periplasmic binding proteins from bacteria and by computational design of proteins with altered binding pockets in conjunction with mutagenesis. This toolbox can then be applied for four-dimensional imaging of cells and tissues to elucidate the spatial and temporal distribution of metabolites as a discovery tool in functional genomics, as a tool for high-throughput, high-content screening for drugs, to test metabolic models, and to analyze the interplay of cells in a tissue or organ.     

Glutamine Flux Imaging Using Genetically Encoded Sensors

Genetically encoded sensors allow real-time monitoring of biological molecules at a subcellular resolution. A tremendous variety of such sensors for biological molecules became available in the past 15 years, some of which became indispensable tools that are used routinely in many laboratories.One of the exciting applications of genetically encoded sensors is the use of these sensors in investigating cellular transport processes. Properties of transporters such as kinetics and substrate specificities can be investigated at a cellular level, providing possibilities for cell-type specific analyses of transport activities. In this article, we will demonstrate how transporter dynamics can be observed using genetically encoded glutamine sensor as an example. Experimental design, technical details of the experimental settings, and considerations for post-experimental analyses will be discussed.     

Optical sensors for monitoring dynamic changes of intracellular metabolite levels in mammalian cells

Knowledge of the in vivo levels, distribution and flux of ions and metabolites is crucial to our understanding of physiology in both healthy and diseased states. The quantitative analysis of the dynamics of ions and metabolites with subcellular resolution in vivo poses a major challenge for the analysis of metabolic processes. Genetically encoded F?rster resonance energy transfer (FRET) sensors can be used for real-time in vivo detection of metabolites. FRET sensor proteins, for example, for glucose, can be targeted genetically to any cellular compartment, or even to subdomains (e.g., a membrane surface), by adding signal sequences or fusing the sensors to specific proteins. The sensors can be used for analyses in individual mammalian cells in culture, in tissue slices and in intact organisms. Applications include gene discovery, high-throughput drug screens or systematic analysis of regulatory networks affecting uptake, efflux and metabolism. Quantitative analyses obtained with the help of FRET sensors for glucose or other ions and metabolites provide valuable data for modeling of flux. Here we provide a detailed protocol for monitoring glucose levels in the cytosol of mammalian cell cultures through the use of FRET glucose sensors; moreover, the protocol can be used for other ions and metabolites and for analyses in other organisms, as has been successfully demonstrated in bacteria, yeast and even intact plants. The whole procedure typically takes ～4 d including seeding and transfection of mammalian cells; the FRET-based analysis of transfected cells takes ～5 h.     

Quantitative monitoring of 2-oxoglutarate in Escherichia coli cells by a fluorescence resonance energy transfer-based biosensor

2-Oxoglutarate (2OG) is a metabolite from the highly conserved Krebs cycle and not only plays a critical role in metabolism but also acts as a signaling molecule in a variety of organisms. Environmental inorganic nitrogen is reduced to ammonium by microorganisms, whose metabolic pathways involve the conversion of 2OG to glutamate and glutamine. Tracking of 2OG in real time would be useful for studies on cell metabolism and signal transduction. Here, we developed a genetically encoded 2OG biosensor based on fluorescent resonance energy transfer by inserting the functional 2OG-binding domain GAF of the NifA protein between the fluorescence resonance energy transfer (FRET) pair YFP/CFP. The dynamic range of the sensors is 100 μM to 10 mM, which appeared identical to the physiological range observed in E. coli. We optimized the peptide lengths of the binding domain to obtain a sensor with a maximal ratio change of 0.95 upon 2OG binding and demonstrated the feasibility of this sensor for the visualization of metabolites both in vitro and in vivo.     

Smad7: not only a regulator, but also a cross-talk mediator of TGF-β signalling

Over the past decade, we have learned that cellular processes, including signalling and metabolism, are highly compartmentalized, and that relevant changes in metabolic state can occur at sub-second timescales. Moreover, we have learned that individual cells in populations, or as part of a tissue, exist in different states. If we want to understand metabolic processes and signalling better, it will be necessary to measure biochemical and biophysical responses of individual cells with high temporal and spatial resolution. Fluorescence imaging has revolutionized all aspects of biology since it has the potential to provide information on the cellular and subcellular distribution of ions and metabolites with sub-second time resolution. In the present review we summarize recent progress in quantifying ions and metabolites in populations of yeast cells as well as in individual yeast cells with the help of quantitative fluorescent indicators, namely FRET metabolite sensors. We discuss the opportunities and potential pitfalls and the controls that help preclude misinterpretation.     

Imaging Cellular Inorganic Phosphate in Caenorhabditis elegans Using a Genetically Encoded FRET-Based Biosensor

Inorganic phosphate (Pi) has central roles in metabolism, cell signaling and energy conversion. The distribution of Pi to each cell and cellular compartment of an animal must be tightly coordinated with its dietary supply and with the varied metabolic demands of individual cells. An analytical method for monitoring Pi dynamics with spatial and temporal resolution is therefore needed to gain a comprehensive understanding of mechanisms governing the transport and recycling of this essential nutrient. Here we demonstrate the utility of a genetically encoded FRET-based Pi sensor to assess cellular Pi levels in the nematode Caenorhabditis elegans. The sensor was expressed in different cells and tissues of the animal, including head neurons, tail neurons, pharyngeal muscle, and the intestine. Cytosolic Pi concentrations were monitored using ratiometric imaging. Injection of phosphate buffer into intestinal cells confirmed that the sensor was responsive to changes in Pi concentration in vivo. Live Pi imaging revealed cell-specific and developmental stage-specific differences in cytosolic Pi concentrations. In addition, cellular Pi levels were perturbed by food deprivation and by exposure to the respiratory inhibitor cyanide. These results suggest that Pi concentration is a sensitive indicator of metabolic status. Moreover, we propose that live Pi imaging in C. elegans is a powerful approach to discern mechanisms that govern Pi distribution in individual cells and throughout an animal.     

Fluorescence lifetime-based pH mapping of tumors in vivo using genetically encoded sensor SypHerRed

Changes in intracellular pH (pHi) reflect metabolic states of cancer cells during tumor growth and dissemination. Therefore, monitoring of pHi is essential for understanding the metabolic mechanisms that support cancer progression. Genetically encoded fluorescent pH sensors have become irreplaceable tools for real-time tracking pH in particular subcellular compartments of living cells. However, ratiometric readout of most of the pH probes is poorly suitable to measure pH in thick samples ex vivo or tissues in vivo including solid tumors. Fluorescence lifetime imaging (FLIM) is a promising alternative to the conventional fluorescent microscopy. Here, we present a quantitative approach to map pHi in cancer cells and tumors in vivo, relying on fluorescence lifetime of a genetically encoded pH sensor SypHerRed. We demonstrate the utility of SypHerRed in visualizing pHi in cancer cell culture and in mouse tumor xenografts using fluorescence lifetime imaging microscopy and macroscopy. For the first time to our knowledge, the absolute pHi value is obtained for tumors in vivo by an optical technique. In addition, we demonstrate the possibility of simultaneous detection of pHi and endogenous fluorescence of metabolic cofactor NADH, which provides a complementary insight into metabolic aspects of cancer. Fluorescence lifetime-based readout and red-shifted spectra make pH sensor SypHerRed a promising instrument for multiparameter in vivo imaging applications.     

Quantitative imaging using genetically encoded sensors for small molecules in plants

Quantitative imaging in live cells is a powerful method for monitoring the dynamics of biomolecules at an excellent spatio-temporal resolution. Such an approach, initially limited to a small number of substrates for which specific dyes were available, has become possible for a large number of biomolecules due to the development of genetically encoded, protein-based sensors. These sensors, which can be introduced into live cells through a transgenic approach, offer the benefits of quantitative imaging, with an extra advantage of non-invasiveness. In the past decade there has been a drastic expansion in the number of biomolecules for which genetically encoded sensors are available, and the functional properties of existing sensors are being improved at a dramatic pace. A number of technical improvements have now made the application of genetically encoded sensors in plants rather straightforward, and some of the sensors such as calcium indicator proteins have become standard analytical tools in many plant laboratories. The use of a handful of probes has already revealed an amazing specificity of cellular biomolecule dynamics in plants, which leads us to believe that there are many more discoveries to be made using genetically encoded sensors. In this short review, we will summarize the progress made in the past 15?years in the development in genetically encoded sensors, and highlight significant discoveries made in plant biology.     

Combining mechanical and optical approaches to dissect cellular mechanobiology

Mechanical force modulates a wide array of cell physiological processes. Cells sense and respond to mechanical stimuli using a hierarchy of structural complexes spanning multiple length scales, including force-sensitive molecules and cytoskeletal networks. Understanding mechanotransduction, i.e., the process by which cells convert mechanical inputs into biochemical signals, has required the development of novel biophysical tools that allow for probing of cellular and subcellular components at requisite time, length, and force scales and technologies that track the spatio-temporal dynamics of relevant biomolecules. In this review, we begin by discussing the underlying principles and recent applications of atomic force microscopy, magnetic twisting cytometry, and traction force microscopy, three tools that have been widely used for measuring the mechanical properties of cells and for probing the molecular basis of cellular mechanotransduction. We then discuss how such tools can be combined with advanced fluorescence methods for imaging biochemical processes in living cells in the context of three specific problem spaces. We first focus on fluorescence resonance energy transfer, which has enabled imaging of intra- and inter-molecular interactions and enzymatic activity in real time based on conformational changes in sensor molecules. Next, we examine the use of fluorescence methods to probe force-dependent dynamics of focal adhesion proteins. Finally, we discuss the use of calcium ratiometric signaling to track fast mechanotransductive signaling dynamics. Together, these studies demonstrate how single-cell biomechanical tools can be effectively combined with molecular imaging technologies for elucidating mechanotransduction processes and identifying mechanosensitive proteins.     

Rational design of genetically encoded fluorescence resonance energy transfer-based sensors of cellular Cdc42 signaling

The temporal and spatial control of Rho GTPase signaling pathways is a central issue in understanding the molecular mechanisms that generate complex cellular movements. The Rho protein Cdc42 induces a significant conformational change in its downstream effector, the Wiskott-Aldrich syndrome protein (WASP). On the basis of this conformational change, we have created a series of single-molecule sensors for both active Cdc42 and Cdc42 guanine nucleotide exchange factors (GEFs) that utilize fluorescence resonance energy transfer (FRET) between cyan and yellow fluorescent proteins. In vitro, the Cdc42 sensors produce up to 3.2-fold FRET emission ratio changes upon binding active Cdc42. The GEF sensors yield up to 1.7-fold changes in FRET upon exchange of GDP for GTP. The GEF-catalyzed rate of nucleotide exchange for the GEF sensor is indistinguishable from that of wild-type Cdc42, but GAP-catalyzed nucleotide hydrolysis is slowed approximately 16-fold. In vivo, both sensors faithfully report on Cdc42 and/or Cdc42-GEF activity. These results establish the successful creation of rationally designed and genetically encoded tools that can be used to image the activity of biologically and medically important molecules in living systems.     

Shining light on signaling and metabolic networks by genetically encoded biosensors

Fluorescent labels have revolutionized cell biology. Signaling intermediates and metabolites can be measured in real time with subcellular spatial resolution. Most of these sensors are based on fluorescent proteins, and many report fluorescence resonance energy transfer. Because the biosensors are genetically encoded, a toolbox for addressing cell biological questions at the systems level is now available. Fluorescent biosensors are able to determine the localization of proteins and their dynamics, to reveal the cellular and subcellular localization of the respective interactions and activities, and to provide complementary data on the steady state levels of ions, metabolites, and signaling intermediates with high temporal and spatial resolution. They represent the basis for cell-based high-throughput assays that are necessary for a systems perspective on plant cell function.     

Recent progress in mass spectrometry for single-cell metabolomics

Metabolites are the end products of cellular vital activities and can reflect the state of cellular to a certain extent. Rapid change of metabolites and the low abundance of signature metabolites cause difficulties in single-cell detection, which is a great challenge in single-cell metabolomics analysis. Mass spectrometry (MS) is a powerful tool that uniquely suited to detect intracellular small-molecule metabolites and has shown good application in single-cell metabolite analysis. In this mini-review, we describe three types of emerging technologies for MS-based single-cell metabolic analysis in recent years, including nano-ESI-MS based single-cell metabolomics analysis, high-throughput analysis via flow cytometry, and cellular metabolic imaging analysis. These techniques provide a large amount of single-cell metabolic data, allowing the potential of MS in single-cell metabolic analysis is gradually being explored and is of great importance in disease and life science research.     

Elucidation and structural analysis of conserved pools for genome-scale metabolic reconstructions

In this article, we introduce metabolite concentration coupling analysis (MCCA) to study conservation relationships for metabolite concentrations in genome-scale metabolic networks. The analysis allows the global identification of subsets of metabolites whose concentrations are always coupled within common conserved pools. Also, the minimal conserved pool identification (MCPI) procedure is developed for elucidating conserved pools for targeted metabolites without computing the entire basis conservation relationships. The approaches are demonstrated on genome-scale metabolic reconstructions of Helicobacter pylori, Escherichia coli, and Saccharomyces cerevisiae. Despite significant differences in the size and complexity of the examined organism's models, we find that the concentrations of nearly all metabolites are coupled within a relatively small number of subsets. These correspond to the overall exchange of carbon molecules into and out of the networks, interconversion of energy and redox cofactors, and the transfer of nitrogen, sulfur, phosphate, coenzyme A, and acyl carrier protein moieties among metabolites. The presence of large conserved pools can be viewed as global biophysical barriers protecting cellular systems from stresses, maintaining coordinated interconversions between key metabolites, and providing an additional mode of global metabolic regulation. The developed approaches thus provide novel and versatile tools for elucidating coupling relationships between metabolite concentrations with implications in biotechnological and medical applications.     

Imaging molecular interactions in living cells

Hormones integrate the activities of their target cells through receptor-modulated cascades of protein interactions that ultimately lead to changes in cellular function. Understanding how the cell assembles these signaling protein complexes is critically important to unraveling disease processes, and to the design of therapeutic strategies. Recent advances in live-cell imaging technologies, combined with the use of genetically encoded fluorescent proteins, now allow the assembly of these signaling protein complexes to be tracked within the organized microenvironment of the living cell. Here, we review some of the recent developments in the application of imaging techniques to measure the dynamic behavior, colocalization, and spatial relationships between proteins in living cells. Where possible, we discuss the application of these different approaches in the context of hormone regulation of nuclear receptor localization, mobility, and interactions in different subcellular compartments. We discuss measurements that define the spatial relationships and dynamics between proteins in living cells including fluorescence colocalization, fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, fluorescence resonance energy transfer microscopy, and fluorescence lifetime imaging microscopy. These live-cell imaging tools provide an important complement to biochemical and structural biology studies, extending the analysis of protein-protein interactions, protein conformational changes, and the behavior of signaling molecules to their natural environment within the intact cell.     

Strigo-D2—a bio-sensor for monitoring spatio-temporal strigolactone signaling patterns in intact plants

Strigolactones (SLs) are a class of plant hormones that mediate biotic interactions and modulate developmental programs in response to endogenous and exogenous stimuli. However, a comprehensive view on the spatio-temporal pattern of SL signaling has not been established, and tools for a systematic in planta analysis do not exist. Here, we present Strigo-D2, a genetically encoded ratiometric SL signaling sensor that enables the examination of SL signaling distribution at cellular resolution and is capable of rapid response to altered SL levels in intact Arabidopsis (Arabidopsis thaliana) plants. By monitoring the abundance of a truncated and fluorescently labeled SUPPRESSOR OF MAX2 1-LIKE 6 (SMXL6) protein, a proteolytic target of the SL signaling machinery, we show that all cell types investigated have the capacity to respond to changes in SL levels but with very different dynamics. In particular, SL signaling is pronounced in vascular cells but low in guard cells and the meristematic region of the root. We also show that other hormones leave Strigo-D2 activity unchanged, indicating that initial SL signaling steps work in isolation from other hormonal signaling pathways. The specificity and spatio-temporal resolution of Strigo-D2 underline the value of the sensor for monitoring SL signaling in a broad range of biological contexts with highly instructive analytical depth.

Strigo-D2 is a genetically encoded sensor visualizing spatio-temporal patterns of strigolactone signaling levels in intact plants based on the activity ratio of two fluorescent marker proteins.     

Visualization of glutamine transporter activities in living cells using genetically encoded glutamine sensors

Glutamine plays a central role in the metabolism of critical biological molecules such as amino acids, proteins, neurotransmitters, and glutathione. Since glutamine metabolism is regulated through multiple enzymes and transporters, the cellular glutamine concentration is expected to be temporally dynamic. Moreover, differentiation in glutamine metabolism between cell types in the same tissue (e.g. neuronal and glial cells) is often crucial for the proper function of the tissue as a whole, yet assessing cell-type specific activities of transporters and enzymes in such heterogenic tissue by physical fractionation is extremely challenging. Therefore, a method of reporting glutamine dynamics at the cellular level is highly desirable. Genetically encoded sensors can be targeted to a specific cell type, hence addressing this knowledge gap. Here we report the development of F?ster Resonance Energy Transfer (FRET) glutamine sensors based on improved cyan and yellow fluorescent proteins, monomeric Teal Fluorescent Protein (mTFP)1 and venus. These sensors were found to be specific to glutamine, and stable to pH-changes within a physiological range. Using cos7 cells expressing the human glutamine transporter ASCT2 as a model, we demonstrate that the properties of the glutamine transporter can easily be analyzed with these sensors. The range of glutamine concentration change in a given cell can also be estimated using sensors with different affinities. Moreover, the mTFP1-venus FRET pair can be duplexed with another FRET pair, mAmetrine and tdTomato, opening up the possibility for real-time imaging of another molecule. These novel glutamine sensors will be useful tools to analyze specificities of glutamine metabolism at the single-cell level.     

Elimination of environmental sensitivity in a cameleon FRET-based calcium sensor via replacement of the acceptor with Venus

Genetically encoded sensors are becoming a powerful tool for investigating cellular signaling pathways and, potentially, signaling in vivo. Many sensors use changes in fluorescence resonance energy transfer (FRET) between donor and acceptor variants of GFP separated by a ligand binding domain sensitive to a particular signaling pathway. Accurate measurements require that sensors be insensitive to extraneous intracellular environmental factors. We have found that the responsiveness of the Ca(2+) sensor, cameleon YC6.1, varies linearly with the resting YFP/CFP emission ratio in the cell. However, cells expressing responsive or non-responsive sensor can easily be segregated by determining a resting YFP/CFP ratio cutoff for the sensor. This environmental sensitivity has been eliminated by replacing EYFP with Venus to produce a new cameleon we have designated VC6.1. Measurements show that VC6.1 has a greater dynamic range than YC6.1 and better environmental resistance. We also show that YC6.1 is inactivated by persistent activation of the IP(3) pathway following expression of constitutively active G(q), while VC6.1 is not. The stability of VC6.1 may make it well suited to studies utilizing mixed cell populations such as those encountered in vivo.