Imaging approach for monitoring cellular metabolites and ions using genetically encoded biosensors

Effects of fluorescent protein tdTomato on mouse retina

Fluorescent proteins (FPs) have been widely used to investigate cellular and molecular interactions and trace biological events in many applications. Some of the FPs have been demonstrated to cause undesirable cellular damage by light-induced ROS production in vivo or in vitro. However, it remains unknown if one of the most popular FPs, tdTomato, has similar effects in neuronal cells. In this study, we discovered that tdTomato expression led to unexpected retinal dysfunction and ultrastructural defects in the transgenic mouse retina. The retinal dysfunction mainly manifested in the reduced photopic electroretinogram (ERG) responses and decreased contrast sensitivity in visual acuity, caused by mitochondrial damages characterized with cellular redistribution, morphological modifications and molecular profiling alterations. Taken together, our findings for the first time demonstrated the retinal dysfunction and ultrastructural defects in the retinas of tdTomato-transgenic mice, calling for a more careful design and interpretation of experiments involved in FPs.

Oxidative stress monitoring in iPSC-derived motor neurons using genetically encoded biosensors of H2O2

Oxidative stress plays an important role in the development of neurodegenerative diseases, being either the initiator or part of a pathological cascade that leads to the neuron’s death. Genetically encoded biosensors of oxidative stress demonstrated their general functionality and overall safety in various systems. However, there is still insufficient data regarding their use in the research of disease-related phenotypes in relevant model systems, such as human cells. Here, we establish an approach for monitoring the redox state of live motor neurons with SOD1 mutations associated with amyotrophic lateral sclerosis. Using CRISPR/Cas9, we insert genetically encoded biosensors of cytoplasmic and mitochondrial H₂O₂ in the genome of induced pluripotent stem cell (iPSC) lines. We demonstrate that the biosensors remain functional in motor neurons derived from these iPSCs and reflect the differences in the stationary redox state of the neurons with different genotypes. Moreover, we show that the biosensors respond to alterations in motor neuron oxidation caused by either environmental changes or cellular stress. Thus, the obtained platform is suitable for cell-based research of neurodegenerative mechanisms.

Novel computational and experimental approaches for investigating the thermodynamics of metabolic networks

Thermodynamic analysis of metabolic networks has emerged as a useful new tool for pathway design and metabolic engineering. Understanding the relationship between the thermodynamic driving force of biochemical reactions and metabolic flux has generated new insights regarding the design principles of microbial carbon metabolism. This review summarizes the various lessons that can be obtained from the thermodynamic analysis of metabolic pathways, illustrates concepts of computational thermodynamic tools, and highlights recent applications of thermodynamic analysis to pathway design in industrially relevant microbes.

Subcellular metabolomics: Isolation, measurement, and applications

Metabolomics, a technique that profiles global small molecules in biological samples, has been a pivotal tool for disease diagnosis and mechanism research. The sample type in metabolomics covers a wide range, including a variety of body fluids, tissues, and cells. However, little attention was paid to the smaller, relatively independent partition systems in cells, namely the organelles. The organelles are specific compartments/places where diverse metabolic activities are happening in an orderly manner. Metabolic disorders of organelles were found to occur in various pathological conditions such as inherited metabolic diseases, diabetes, cancer, and neurodegenerative diseases. However, at the cellular level, the metabolic outcomes of organelles and cytoplasm are superimposed interactively, making it difficult to describe the changes in subcellular compartments. Therefore, characterizing the metabolic pool in the compartmentalized system is of great significance for understanding the role of organelles in physiological functions and diseases. So far, there are very few research articles or reviews related to subcellular metabolomics. In this review, subcellular fractionation and metabolite analysis methods, as well as the application of subcellular metabolomics in the physiological and pathological studies are systematically reviewed, as a practical reference to promote the continued advancement in subcellular metabolomics.

Lighting Up Live-Cell and In Vivo Central Carbon Metabolism with Genetically Encoded Fluorescent Sensors

As the core component of cell metabolism, central carbon metabolism, consisting of glycolysis, the pentose phosphate pathway, and the tricarboxylic acid cycle converts nutrients into metabolic precursors for biomass and energy to sustain the life of virtually all extant species. The metabolite levels or distributions in central carbon metabolism often change dynamically with cell fates, development, and disease progression. However, traditional biochemical methods require cell lysis, making it challenging to obtain spatiotemporal information about metabolites in living cells and in vivo. Genetically encoded fluorescent sensors allow the rapid, sensitive, specific, and real-time readout of metabolite dynamics in living organisms, thereby offering the potential to fill the gap in current techniques. In this review, we introduce recent progress made in the development of genetically encoded fluorescent sensors for central carbon metabolism and discuss their advantages, disadvantages, and applications. Moreover, several future directions of metabolite sensors are also proposed.

Genetically Encoded Ratiometric RNA-Based Sensors for Quantitative Imaging of Small Molecules in Living Cells

Precisely determining the intracellular concentrations of metabolites and signaling molecules is critical in studying cell biology. Fluorogenic RNA-based sensors have emerged to detect various targets in living cells. However, it is still challenging to apply these genetically encoded sensors to quantify the cellular concentrations and distributions of targets. Herein, using a pair of orthogonal fluorogenic RNA aptamers, DNB and Broccoli, we engineered a modular sensor system to apply the DNB-to-Broccoli fluorescence ratio to quantify the cell-to-cell variations of target concentrations. These ratiometric sensors can be broadly applied for live-cell imaging and quantification of metabolites, signaling molecules, and other synthetic compounds.

Detection of Low-Abundance Metabolites in Live Cells Using an RNA Integrator

Genetically encoded biosensors are useful tools for detecting the presence and levels of diverse biomolecules in living cells. However, low-abundance targets are difficult to detect because they are often unable to bind and activate enough biosensors to detect using standard microscopic imaging approaches. Here we describe a type of RNA-based biosensor, an RNA integrator, which enables detection of low-abundance targets in vitro and in living cells. The RNA integrator is an RNA sequence comprising a ribozyme and an unfolded form of the fluorogenic aptamer Broccoli. Upon binding its target, the ribozyme undergoes cleavage and releases Broccoli, which subsequently folds and becomes fluorescent. Importantly, each target molecule can bind and induce cleavage of multiple copies of the integrator sensor, resulting in an amplified signal. We show that this approach can be generalized to numerous different ribozyme types for the detection of various small molecules.

Circularly Permuted Fluorogenic Proteins for the Design of Modular Biosensors

Fluorescent reporters are essential components for the design of optical biosensors that are able to image intracellular analytes in living cells. Herein, we describe the development of circularly permuted variants of Fluorescence-Activating and absorption-Shifting Tag (FAST) and demonstrate their potential as reporting module in biosensors. Circularly permutated FAST (cpFAST) variants allow one to condition the binding and activation of a fluorogenic ligand (and thus fluorescence) to analyte recognition by coupling them with analyte-binding domains. We demonstrated their use for biosensor design by generating multicolor plug-and-play fluorogenic biosensors for imaging the intracellular levels of Ca²⁺ in living mammalian cells in real time.

Role of green fluorescent proteins and their variants in development of FRET-based sensors

Since the last decade, a lot of advancement has been made to understand biological processes involving complex intracellular pathways. The major challenge faced was monitoring and trafficking of metabolites in real time. Although a range of quantitative and imaging techniques have been developed so far, the discovery of green fluorescent proteins (GFPs) has revolutionized the advancement in the field of metabolomics. GFPs and their variants have enabled researchers to 'paint' a wide range of biological molecules. Fluorescence resonance energy transfer (FRET)-based genetically encoded sensors is a promising technology to decipher the real-time monitoring of the cellular events inside living cells. GFPs and their variants, due to their intrinsic fluorescence properties, are extensively being used nowadays in cell-based assays. This review focuses on structure and function of GFP and its derivatives, mechanism emission and their use in the development of FRET-based sensors for metabolites.

Sugar flux and signaling in plant-microbe interactions

Plant breeders have developed crop plants that are resistant to pests, but the continual evolution of pathogens creates the need to iteratively develop new control strategies. Molecular tools have allowed us to gain deep insights into disease responses, allowing for more efficient, rational engineering of crops that are more robust or resistant to a greater number of pathogen variants. Here we describe the roles of SWEET and STP transporters, membrane proteins that mediate transport of sugars across the plasma membrane. We discuss how these transporters may enhance or restrict disease through controlling the level of nutrients provided to pathogens and whether the transporters play a role in sugar signaling for disease resistance. This review indicates open questions that require further research and proposes the use of genome editing technologies for engineering disease resistance.

Visualization of Nicotine Adenine Dinucleotide Redox Homeostasis with Genetically Encoded Fluorescent Sensors

SIGNIFICANCE

Beyond their roles as redox currency in living organisms, pyridine dinucleotides (NAD⁺/NADH and NADP⁺/NADPH) are also precursors or cosubstrates of great significance in various physiologic and pathologic processes. Recent Advances: For many years, it was challenging to develop methodologies for monitoring pyridine dinucleotides in situ or in vivo. Recent advances in fluorescent protein-based sensors provide a rapid, sensitive, specific, and real-time readout of pyridine dinucleotide dynamics in single cells or in vivo, thereby opening a new era of pyridine dinucleotide bioimaging. In this article, we summarize the developments in genetically encoded fluorescent sensors for NAD⁺/NADH and NADP⁺/NADPH redox states, as well as their applications in life sciences and drug discovery. The strengths and weaknesses of individual sensors are also discussed.

CRITICAL ISSUES

These sensors have the advantages of being specific and organelle targetable, enabling real-time monitoring and subcellular-level quantification of targeted molecules in living cells and in vivo.

FUTURE DIRECTIONS

NAD⁺/NADH and NADP⁺/NADPH have distinct functions in metabolic and redox regulation, and thus, a comprehensive evaluation of metabolic and redox states must be multiplexed with a combination of various metabolite sensors in a single cell. Antioxid. Redox Signal. 28, 213-229.

Label-free, simultaneous quantification of starch, protein and triacylglycerol in single microalgal cells

BACKGROUND

Current approaches for quantification of major energy-storage forms in microalgae, including starch, protein and lipids, generally require cell cultivation to collect biomass followed by tedious and time-consuming analytical procedures. Thus, label-free, non-destructive and simultaneous quantification of such macromolecules at single-cell resolution is highly desirable in microalgal feedstock development and bioprocess control.

RESULTS

Here, we established a method based on single-cell Raman spectra (SCRS) that simultaneously quantifies the contents of starch, protein, triacylglycerol (TAG) and lipid unsaturation degree in individual Chlamydomonas reinhardtii cells. Measurement accuracy for the contents based on full SCRS spectrum each reached 96.86-99.24%, all significantly higher than single peak-based models. However, accuracy and reliability of measurement are dependent on the number of cells sampled, thus a formal mathematical framework was proposed and validated to rationally define "minimal sampling depth" for a given state of cellular population. Furthermore, a barcode consisting of 13 marker Raman peaks was proposed to characterize the temporal dynamics of these energy-storage products, which revealed that the average contents of starch and TAG increased, while their heterogeneity indices decreased, with those of protein being exactly the opposite. Finally, our method is widely applicable, as measurements among cells from liquid suspension culture, wet paste and frozen dried powder all exhibited excellent consistency.

CONCLUSIONS

When sampled at proper depth, SCRS can serve as a quantitative and generally applicable tool for characterization and screening of strains and bioprocesses based on the profile of energy-storage macromolecules and their among-cell heterogeneity.

A Toolbox of Genetically Encoded FRET-Based Biosensors for Rapid l-Lysine Analysis

Background: The fast development of microbial production strains for basic and fine chemicals is increasingly carried out in small scale cultivation systems to allow for higher throughput. Such parallelized systems create a need for new rapid online detection systems to quantify the respective target compound. In this regard, biosensors, especially genetically encoded Förster resonance energy transfer (FRET)-based biosensors, offer tremendous opportunities. As a proof-of-concept, we have created a toolbox of FRET-based biosensors for the ratiometric determination of l-lysine in fermentation broth. Methods: The sensor toolbox was constructed based on a sensor that consists of an optimized central lysine-/arginine-/ornithine-binding protein (LAO-BP) flanked by two fluorescent proteins (enhanced cyan fluorescent protein (ECFP), Citrine). Further sensor variants with altered affinity and sensitivity were obtained by circular permutation of the binding protein as well as the introduction of flexible and rigid linkers between the fluorescent proteins and the LAO-BP, respectively. Results: The sensor prototype was applied to monitor the extracellular l-lysine concentration of the l-lysine producing Corynebacterium glutamicum (C. glutamicum) strain DM1933 in a BioLector^® microscale cultivation device. The results matched well with data obtained by HPLC analysis and the Ninhydrin assay, demonstrating the high potential of FRET-based biosensors for high-throughput microbial bioprocess optimization.

The Signaling State of Orange Carotenoid Protein

Orange carotenoid protein (OCP) is the photoactive protein that is responsible for high light tolerance in cyanobacteria. We studied the kinetics of the OCP photocycle by monitoring changes in its absorption spectrum, intrinsic fluorescence, and fluorescence of the Nile red dye bound to OCP. It was demonstrated that all of these three methods provide the same kinetic parameters of the photocycle, namely, the kinetics of OCP relaxation in darkness was biexponential with a ratio of two components equal to 2:1 independently of temperature. Whereas the changes of the absorption spectrum of OCP characterize the geometry and environment of its chromophore, the intrinsic fluorescence of OCP reveals changes in its tertiary structure, and the fluorescence properties of Nile red indicate the exposure of hydrophobic surface areas of OCP to the solvent following the photocycle. The results of molecular-dynamics studies indicated the presence of two metastable conformations of 3'-hydroxyechinenone, which is consistent with characteristic changes in the Raman spectra. We conclude that rotation of the β-ionylidene ring in the C-terminal domain of OCP could be one of the first conformational rearrangements that occur during photoactivation. The obtained results suggest that the photoactivated form of OCP represents a molten globule-like state that is characterized by increased mobility of tertiary structure elements and solvent accessibility.

Development of novel FP-based probes for live-cell imaging of nitric oxide dynamics

Nitric oxide () is a free radical with a wide range of biological effects, but practically impossible to visualize in single cells. Here we report the development of novel multicoloured fluorescent quenching-based probes by fusing a bacteria-derived -binding domain close to distinct fluorescent protein variants. These genetically encoded probes, referred to as geNOps, provide a selective, specific and real-time read-out of cellular dynamics and, hence, open a new era of bioimaging. The combination of geNOps with a Ca(2+) sensor allowed us to visualize and Ca(2+) signals simultaneously in single endothelial cells. Moreover, targeting of the probes was used to detect signals within mitochondria. The geNOps are useful new tools to further investigate and understand the complex patterns of signalling on the single (sub)cellular level.

Compartment-specific metabolomics for CHO reveals that ATP pools in mitochondria are much lower than in cytosol

Mammalian cells show a compartmented metabolism. Getting access to subcellular metabolite pools is of high interest to understand the cells' metabolomic state. Therefore a protocol is developed and applied for monitoring compartment-specific metabolite and nucleotide pool sizes in Chinese hamster ovary (CHO) cells. The approach consists of a subtracting filtering method separating cytosolic components from physically intact mitochondrial compartments. The internal standards glucose-6-phosphate and cis-aconitate were chosen to quantify cytosolic secession and mitochondrial membrane integrity. Extracts of related fractions were studied by liquid chromatography-isotope dilution mass spectrometry for the absolute quantification of a subset of glycolytic and tricarboxylic acid cycle intermediates together with the adenylate nucleotides ATP, ADP and AMP. The application of the protocol revealed highly dynamic changes in the related pool sizes as a function of distinct cultivation periods of IgG1 producing CHO cells. Mitochondrial and cytosolic pool dynamics were in agreement with anticipated metabolite pools of independent studies. The analysis of adenosine phosphate levels unraveled significantly higher ATP levels in the cytosol leading to the hypothesis that mitochondria predominantly serve for fueling ATP into the cytosol where it is tightly controlled at physiological adenylate energy charges about 0.9.

Exploring metabolic pathways and regulation through functional chemoproteomic and metabolomic platforms

Genome sequencing efforts have revealed a strikingly large number of uncharacterized genes, including poorly or uncharacterized metabolic enzymes, metabolites, and metabolic networks that operate in normal physiology, and those enzymes and pathways that may be rewired under pathological conditions. Although deciphering the functions of the uncharacterized metabolic genome is a challenging prospect, it also presents an opportunity for identifying novel metabolic nodes that may be important in disease therapy. In this review, we will discuss the chemoproteomic and metabolomic platforms used in identifying, characterizing, and targeting nodal metabolic pathways important in physiology and disease, describing an integrated workflow for functional mapping of metabolic enzymes.

Profiling metabolic states with genetically encoded fluorescent biosensors for NADH

NADH and its oxidized form, NAD(+), play central roles in energy metabolism and are ideal indicators of cellular metabolic states. In this review, we will introduce recent progress made in the developing of a series of genetically encoded NADH sensors, which offer the potential to fill the gap in currently used techniques of endogenous NAD(P)H fluorescence imaging. These sensors are bright, specific and organelles targetable, allowing real-time tracking and quantification of intracellular NADH levels in different subcellular compartments. The individual strengths and weaknesses of these sensors when applied to the study of metabolic states profiling will be also discussed.

Microfluidic platforms for plant cells studies

Conventional methods of plant cell analysis rely on growing plant cells in soil pots or agarose plates, followed by screening the plant phenotypes in traditional greenhouses and growth chambers. These methods are usually costly, need a large number of experiments, suffer from low spatial resolution and disorderly growth behavior of plant cells, with lack of ability to locally and accurately manipulate the plant cells. Microfluidic platforms take advantage of miniaturization for handling small volume of liquids and providing a closed environment, with the purpose of in vitro single cell analysis and characterizing cell response to external cues. These platforms have shown their ability for high-throughput cellular analysis with increased accuracy of experiments, reduced cost and experimental times, versatility in design, ability for large-scale and combinatorial screening, and integration with other miniaturized sensors. Despite extensive research on animal cells within microfluidic environments for high-throughput sorting, manipulation and phenotyping studies, the application of microfluidics for plant cells studies has not been accomplished yet. Novel devices such as RootChip, RootArray, TipChip, and PlantChip developed for plant cells analysis, with high spatial resolution on a micrometer scale mimicking the internal microenvironment of plant cells, offering preliminary results on the capability of microfluidics to conquer the constraints of conventional methods. These devices have been used to study different aspects of plant cell biology such as gene expression, cell biomechanics, cellular mechanism of growth, cell division, and cells fusion. This review emphasizes the advantages of current microfluidic systems for plant science studies, and discusses future prospects of microfluidic platforms for characterizing plant cells response to diverse external cues.

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.

Quantitative imaging approaches for small-molecule measurements using FRET sensors in plants

Cellular metabolites and ions can exhibit very specific spatiotemporal dynamics that are very challenging to monitor using extraction-based methods. Genetically encoded Föster resonance energy transfer sensors afford a powerful method of measuring these dynamics in situ and hence are now widely used in order to decode information communicated through the dynamics of cellular metabolites and ions. This methodology involves (1) the development of a suitable sensor, (2) genetic engineering of the sensor for its expression in the tissue of interest, and (3) measurement and characterization of the cellular metabolites and ions using optical imaging. This chapter describes the measurement aspects. We describe the imaging setup, sample preparation from leaf discs and root cells, performance of a perfusion experiment, and quantification of metabolite and ion concentrations from the imaging data. We also describe post-experiment analysis including estimation of sensor efficiency and spectral bleedthrough.

Development of a multiplexed microfluidic platform for the automated cultivation of embryonic stem cells

We present a multiplexed platform for a microfabricated stem cell culture device. The modular platform contains all the components to control stem cell culture conditions in an automated fashion. It does not require an incubator during perfusion culture and can be mounted on the stage of an inverted fluorescence microscope for high-frequency imaging of stem cell cultures. A pressure-driven pump provides control over the medium flow rate and offers switching of the flow rates. Flow rates of the pump are characterized for different pressure settings, and a linear correlation between the applied pressure and the flow rate in the cell culture devices is shown. In addition, the pump operates with two culture medium reservoirs, thus enabling the switching of the culture medium on-the-fly during a cell culture experiment. Also, with our platform, the culture medium reservoirs are cooled to prevent medium degradation during long-term experiments. Media temperature is then adjusted to a higher controlled temperature before entering the microfabricated cell culture device. Furthermore, the temperature is regulated in the microfabricated culture devices themselves. Preliminary culture experiments are demonstrated using mouse embryonic stem cells.

Visualization of synaptic inhibition with an optogenetic sensor developed by cell-free protein engineering automation

We describe an engineered fluorescent optogenetic sensor, SuperClomeleon, that robustly detects inhibitory synaptic activity in single, cultured mouse neurons by reporting intracellular chloride changes produced by exogenous GABA or inhibitory synaptic activity. Using a cell-free protein engineering automation methodology that bypasses gene cloning, we iteratively constructed, produced, and assayed hundreds of mutations in binding-site residues to identify improvements in Clomeleon, a first-generation, suboptimal sensor. Structural analysis revealed that these improvements involve halide contacts and distant side chain rearrangements. The development of optogenetic sensors that respond to neural activity enables cellular tracking of neural activity using optical, rather than electrophysiological, signals. Construction of such sensors using in vitro protein engineering establishes a powerful approach for developing new probes for brain imaging.

An objective function exploiting suboptimal solutions in metabolic networks

Background

Flux Balance Analysis is a theoretically elegant, computationally efficient, genome-scale approach to predicting biochemical reaction fluxes. Yet FBA models exhibit persistent mathematical degeneracy that generally limits their predictive power.

Results

We propose a novel objective function for cellular metabolism that accounts for and exploits degeneracy in the metabolic network to improve flux predictions. In our model, regulation drives metabolism toward a region of flux space that allows nearly optimal growth. Metabolic mutants deviate minimally from this region, a function represented mathematically as a convex cone. Near-optimal flux configurations within this region are considered equally plausible and not subject to further optimizing regulation. Consistent with relaxed regulation near optimality, we find that the size of the near-optimal region predicts flux variability under experimental perturbation.

Conclusion

Accounting for suboptimal solutions can improve the predictive power of metabolic FBA models. Because fluctuations of enzyme and metabolite levels are inevitable, tolerance for suboptimality may support a functionally robust metabolic network.

In vivo biochemistry: applications for small molecule biosensors in plant biology

Revolutionary new technologies, namely in the areas of DNA sequencing and molecular imaging, continue to impact new discoveries in plant science and beyond. For decades we have been able to determine properties of enzymes, receptors and transporters in vitro or in heterologous systems, and more recently been able to analyze their regulation at the transcriptional level, to use GFP reporters for obtaining insights into cellular and subcellular localization, and tp measure ion and metabolite levels with unprecedented precision using mass spectrometry. However, we lack key information on the location and dynamics of the substrates of enzymes, receptors and transporters, and on the regulation of these proteins in their cellular environment. Such information can now be obtained by transitioning from in vitro to in vivo biochemistry using biosensors. Genetically encoded fluorescent protein-based sensors for ion and metabolite dynamics provide highly resolved spatial and temporal information, and are complemented by sensors for pH, redox, voltage, and tension. They serve as powerful tools for identifying missing processes (e.g., glucose transport across ER membranes), components (e.g., SWEET sugar transporters for cellular sugar efflux), and signaling networks (e.g., from systematic screening of mutants that affect sugar transport or cytosolic and vacuolar pH). Combined with the knowledge of properties of enzymes and transporters and their interactions with the regulatory machinery, biosensors promise to be key diagnostic tools for systems and synthetic biology.

An optimized fluorescent probe for visualizing glutamate neurotransmission

We describe an intensity-based glutamate-sensing fluorescent reporter (iGluSnFR) with signal-to-noise ratio and kinetics appropriate for in vivo imaging. We engineered iGluSnFR in vitro to maximize its fluorescence change, and we validated its utility for visualizing glutamate release by neurons and astrocytes in increasingly intact neurological systems. In hippocampal culture, iGluSnFR detected single field stimulus-evoked glutamate release events. In pyramidal neurons in acute brain slices, glutamate uncaging at single spines showed that iGluSnFR responds robustly and specifically to glutamate in situ, and responses correlate with voltage changes. In mouse retina, iGluSnFR-expressing neurons showed intact light-evoked excitatory currents, and the sensor revealed tonic glutamate signaling in response to light stimuli. In worms, glutamate signals preceded and predicted postsynaptic calcium transients. In zebrafish, iGluSnFR revealed spatial organization of direction-selective synaptic activity in the optic tectum. Finally, in mouse forelimb motor cortex, iGluSnFR expression in layer V pyramidal neurons revealed task-dependent single-spine activity during running.

Perspectives for using genetically encoded fluorescent biosensors in plants

Genetically encoded fluorescent biosensors have long proven to be excellent tools for quantitative live imaging, but sensor applications in plants have been lacking behind those in mammalian systems with respect to the variety of sensors and tissue types used. How can this be improved, and what can be expected for the use of genetically encoded fluorescent biosensors in plants in the future? In this review, we present a table of successful physiological experiments in plant tissue using fluorescent biosensors, and draw some conclusions about the specific challenges plant cell biologists are faced with and some of the ways they have been overcome so far.

From measurement to implementation of metabolic fluxes

The intracellular reaction rates (fluxes) are the ultimate outcome of the activities of the complete inventory (from DNA to metabolite) and in their sum determine the cellular phenotype. The genotype-phenotype relationship is fundamental in such different fields as cancer research and biotechnology. Here, we summarize the developments in determining metabolic fluxes, inferring major pathways from the DNA-sequence, estimating optimal flux distributions, and how these flux distributions can be achieved in vivo. The technical advances to intervene with the many levels of the cellular architecture allow the implementation of new strategies in for example Metabolic Engineering.

Time-lapse fluorescence imaging of Arabidopsis root growth with rapid manipulation of the root environment using the RootChip

The root functions as the physical anchor of the plant and is the organ responsible for uptake of water and mineral nutrients such as nitrogen, phosphorus, sulfate and trace elements that plants acquire from the soil. If we want to develop sustainable approaches to producing high crop yield, we need to better understand how the root develops, takes up a wide spectrum of nutrients, and interacts with symbiotic and pathogenic organisms. To accomplish these goals, we need to be able to explore roots in microscopic detail over time periods ranging from minutes to days. We developed the RootChip, a polydimethylsiloxane (PDMS)- based microfluidic device, which allows us to grow and image roots from Arabidopsis seedlings while avoiding any physical stress to roots during preparation for imaging(1) (Figure 1). The device contains a bifurcated channel structure featuring micromechanical valves to guide the fluid flow from solution inlets to each of the eight observation chambers(2). This perfusion system allows the root microenvironment to be controlled and modified with precision and speed. The volume of the chambers is approximately 400 nl, thus requiring only minimal amounts of test solution. Here we provide a detailed protocol for studying root biology on the RootChip using imaging-based approaches with real time resolution. Roots can be analyzed over several days using time lapse microscopy. Roots can be perfused with nutrient solutions or inhibitors, and up to eight seedlings can be analyzed in parallel. This system has the potential for a wide range of applications, including analysis of root growth in the presence or absence of chemicals, fluorescence-based analysis of gene expression, and the analysis of biosensors, e.g. FRET nanosensors(3).

In vivo quantification of cell coupling in plants with different phloem-loading strategies

Uptake of photoassimilates into the leaf phloem is the key step in carbon partitioning and phloem transport. Symplasmic and apoplasmic loading strategies have been defined in different plant taxa based on the abundance of plasmodesmata between mesophyll and phloem. For apoplasmic loading to occur, an absence of plasmodesmata is a sufficient but not a necessary criterion, as passage of molecules through plasmodesmata might well be blocked or restricted. Here, we present a noninvasive, whole-plant approach to test symplasmic coupling and quantify the intercellular flux of small molecules using photoactivation microscopy. Quantification of coupling between all cells along the prephloem pathways of the apoplasmic loader Vicia faba and Nicotiana tabacum showed, to our knowledge for the first time in vivo, that small solutes like sucrose can diffuse through plasmodesmata up to the phloem sieve element companion cell complex (SECCC). As expected, the SECCC was found to be symplasmically isolated for small solutes. In contrast, the prephloem pathway of the symplasmic loader Cucurbita maxima was found to be well coupled with the SECCC. Phloem loading in gymnosperms is not well understood, due to a profoundly different leaf anatomy and a scarcity of molecular data compared with angiosperms. A cell-coupling analysis for Pinus sylvestris showed high symplasmic coupling along the entire prephloem pathway, comprising at least seven cell border interfaces between mesophyll and sieve elements. Cell coupling together with measurements of leaf sap osmolality indicate a passive symplasmic loading type. Similarities and differences of this loading type with that of angiosperm trees are discussed.

Getting the whole picture: combining throughput with content in microscopy

The increasing availability and performance of automated scientific equipment in the past decades have brought about a revolution in the biological sciences. The ease with which data can now be generated has led to a new culture of high-throughput science, in which new types of biological questions can be asked and tackled in a systematic and unbiased manner. High-throughput microscopy, also often referred to as high-content screening (HCS), allows acquisition of systematic data at the single-cell level. Moreover, it allows the visualization of an enormous array of cellular features and provides tools to quantify a large number of parameters for each cell. These features make HCS a powerful method to create data that is rich and biologically meaningful without compromising systematic capabilities. In this Commentary, we will discuss recent work, which has used HCS, to demonstrate the diversity of applications and technological solutions that are evolving in this field. Such advances are placing HCS methodologies at the frontier of high-throughput science and enable scientists to combine throughput with content to address a variety of cell biological questions.

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.

Protein-protein interactions in plants

The study of protein-protein interactions (PPIs) is essential to uncover unknown functions of proteins at the molecular level and to gain insight into complex cellular networks. Affinity purification and mass spectrometry (AP-MS), yeast two-hybrid, imaging approaches and numerous diverse databases have been developed as strategies to analyze PPIs. The past decade has seen an increase in the number of identified proteins with the development of MS and large-scale proteome analyses. Consequently, the false-positive protein identification rate has also increased. Therefore, the general consensus is to confirm PPI data using one or more independent approaches for an accurate evaluation. Furthermore, identifying minor PPIs is fundamental for understanding the functions of transient interactions and low-abundance proteins. Besides establishing PPI methodologies, we are now seeing the development of new methods and/or improvements in existing methods, which involve identifying minor proteins by MS, multidimensional protein identification technology or OFFGEL electrophoresis analyses, one-shot analysis with a long column or filter-aided sample preparation methods. These advanced techniques should allow thousands of proteins to be identified, whereas in-depth proteomic methods should permit the identification of transient binding or PPIs with weak affinity. Here, the current status of PPI analysis is reviewed and some advanced techniques are discussed briefly along with future challenges for plant proteomics.

A genetically encoded, high-signal-to-noise maltose sensor

We describe the generation of a family of high-signal-to-noise single-wavelength genetically encoded indicators for maltose. This was achieved by insertion of circularly permuted fluorescent proteins into a bacterial periplasmic binding protein (PBP), Escherichia coli maltodextrin-binding protein, resulting in a four-color family of maltose indicators. The sensors were iteratively optimized to have sufficient brightness and maltose-dependent fluorescence increases for imaging, under both one- and two-photon illumination. We demonstrate that maltose affinity of the sensors can be tuned in a fashion largely independent of the fluorescent readout mechanism. Using literature mutations, the binding specificity could be altered to moderate sucrose preference, but with a significant loss of affinity. We use the soluble sensors in individual E. coli bacteria to observe rapid maltose transport across the plasma membrane, and membrane fusion versions of the sensors on mammalian cells to visualize the addition of maltose to extracellular media. The PBP superfamily includes scaffolds specific for a number of analytes whose visualization would be critical to the reverse engineering of complex systems such as neural networks, biosynthetic pathways, and signal transduction cascades. We expect the methodology outlined here to be useful in the development of indicators for many such analytes.

A comprehensive concept of optogenetics

Fundamental questions that neuroscientists have previously approached with classical biochemical and electrophysiological techniques can now be addressed using optogenetics. The term optogenetics reflects the key program of this emerging field, namely, combining optical and genetic techniques. With the already impressively successful application of light-driven actuator proteins such as microbial opsins to interact with intact neural circuits, optogenetics rose to a key technology over the past few years. While spearheaded by tools to control membrane voltage, the more general concept of optogenetics includes the use of a variety of genetically encoded probes for physiological parameters ranging from membrane voltage and calcium concentration to metabolism. Here, we provide a comprehensive overview of the state of the art in this rapidly growing discipline and attempt to sketch some of its future prospects and challenges.

Quantitative imaging with fluorescent biosensors

Molecular activities are highly dynamic and can occur locally in subcellular domains or compartments. Neighboring cells in the same tissue can exist in different states. Therefore, quantitative information on the cellular and subcellular dynamics of ions, signaling molecules, and metabolites is critical for functional understanding of organisms. Mass spectrometry is generally used for monitoring ions and metabolites; however, its temporal and spatial resolution are limited. Fluorescent proteins have revolutionized many areas of biology-e.g., fluorescent proteins can report on gene expression or protein localization in real time-yet promoter-based reporters are often slow to report physiologically relevant changes such as calcium oscillations. Therefore, novel tools are required that can be deployed in specific cells and targeted to subcellular compartments in order to quantify target molecule dynamics directly. We require tools that can measure enzyme activities, protein dynamics, and biophysical processes (e.g., membrane potential or molecular tension) with subcellular resolution. Today, we have an extensive suite of tools at our disposal to address these challenges, including translocation sensors, fluorescence-intensity sensors, and Förster resonance energy transfer sensors. This review summarizes sensor design principles, provides a database of sensors for more than 70 different analytes/processes, and gives examples of applications in quantitative live cell imaging.

The RootChip: an integrated microfluidic chip for plant science

Studying development and physiology of growing roots is challenging due to limitations regarding cellular and subcellular analysis under controlled environmental conditions. We describe a microfluidic chip platform, called RootChip, that integrates live-cell imaging of growth and metabolism of Arabidopsis thaliana roots with rapid modulation of environmental conditions. The RootChip has separate chambers for individual regulation of the microenvironment of multiple roots from multiple seedlings in parallel. We demonstrate the utility of The RootChip by monitoring time-resolved growth and cytosolic sugar levels at subcellular resolution in plants by a genetically encoded fluorescence sensor for glucose and galactose. The RootChip can be modified for use with roots from other plant species by adapting the chamber geometry and facilitates the systematic analysis of root growth and metabolism from multiple seedlings, paving the way for large-scale phenotyping of root metabolism and signaling.

Microfluidics for single cell analysis

Substantial evidence shows that the heterogeneity of individual cells within a genetically identical population can be critical to their chance of survival. Methods that use average responses from a population often mask the difference from individual cells. To fully understand cell-to-cell variability, a complete analysis of an individual cell, from its live state to cell lysates, is essential. Highly sensitive detection of multiple components and high throughput analysis of a large number of individual cells remain the key challenges to realise this aim. In this context, microfluidics and lab-on-a-chip technology have emerged as the most promising avenue to address these challenges. In this review, we will focus on the recent development in microfluidics that are aimed at total single cell analysis on chip, that is, from an individual live cell to its gene and proteins. We also discuss the opportunities that microfluidic based single cell analysis can bring into the drug discovery process.