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

Allosteric modulation of fluorescence revealed by hydrogen bond dynamics in a genetically encoded maltose biosensor

Genetically encoded fluorescent biosensors (GEFBs) proved to be reliable tracers for many metabolites and cellular processes. In the simplest case, a fluorescent protein (FP) is genetically fused to a sensing protein which undergoes a conformational change upon ligand binding. This drives a rearrangement in the chromophore environment and changes the spectral properties of the FP. Structural determinants of successful biosensors are revealed only in hindsight when the crystal structures of both ligand-bound and ligand-free forms are available. This makes the development of new biosensors for desired analytes a long trial-and-error process. In the current study, we conducted μs-long all atom molecular dynamics (MD) simulations of a maltose biosensor in both the apo (dark) and holo (bright) forms. We performed detailed hydrogen bond occupancy analyses to shed light on the mechanism of ligand induced conformational change in the sensor protein and its allosteric effect on the chromophore environment. We find that two strong indicators for distinguishing bright and dark states of biosensors are due to substantial changes in hydrogen bond dynamics in the system and solvent accessibility of the chromophore.

Molecular handcraft of a well-folded protein chimera

Modular assembly is a compelling pathway to create new proteins, a concept supported by protein engineering and millennia of evolution. Natural evolution provided a repository of building blocks, known as domains, which trace back to even shorter segments that underwent numerous 'copy-paste' processes culminating in the scaffolds we see today. Utilizing the subdomain-database Fuzzle, we constructed a fold-chimera by integrating a flavodoxin-like fragment into a periplasmic binding protein. This chimera is well-folded and a crystal structure reveals stable interfaces between the fragments. These findings demonstrate the adaptability of α/β-proteins and offer a stepping stone for optimization. By emphasizing the practicality of fragment databases, our work pioneers new pathways in protein engineering. Ultimately, the results substantiate the conjecture that periplasmic binding proteins originated from a flavodoxin-like ancestor.

Computational design of Periplasmic binding protein biosensors guided by molecular dynamics

Periplasmic binding proteins (PBPs) are bacterial proteins commonly used as scaffolds for substrate-detecting biosensors. In these biosensors, effector proteins (for example fluorescent proteins) are inserted into a PBP such that the effector protein's output changes upon PBP-substate binding. The insertion site is often determined by comparison of PBP apo/holo crystal structures, but random insertion libraries have shown that this can miss the best sites. Here, we present a PBP biosensor design method based on residue contact analysis from molecular dynamics. This computational method identifies the best previously known insertion sites in the maltose binding PBP, and suggests further previously unknown sites. We experimentally characterise fluorescent protein insertions at these new sites, finding they too give functional biosensors. Furthermore, our method is sufficiently flexible to both suggest insertion sites compatible with a variety of effector proteins, and be applied to binding proteins beyond PBPs.

iATPSnFR2: A high-dynamic-range fluorescent sensor for monitoring intracellular ATP

We developed a significantly improved genetically encoded quantitative adenosine triphosphate (ATP) sensor to provide real-time dynamics of ATP levels in subcellular compartments. iATPSnFR2 is a variant of iATPSnFR1, a previously developed sensor that has circularly permuted superfolder green fluorescent protein (GFP) inserted between the ATP-binding helices of the ε-subunit of a bacterial F0-F1 ATPase. Optimizing the linkers joining the two domains resulted in a ~fivefold to sixfold improvement in the dynamic range compared to the previous-generation sensor, with excellent discrimination against other analytes, and affinity variants varying from 4 µM to 500 µM. A chimeric version of this sensor fused to either the HaloTag protein or a suitable spectrally separated fluorescent protein provides an optional ratiometric readout allowing comparisons of ATP across cellular regions. Subcellular targeting the sensor to nerve terminals reveals previously uncharacterized single-synapse metabolic signatures, while targeting to the mitochondrial matrix allowed direct quantitative probing of oxidative phosphorylation dynamics.

A Bright Future? A Perspective on Class C GPCR Based Genetically Encoded Biosensors

One of the major challenges in molecular neuroscience today is to accurately monitor neurotransmitters, neuromodulators, peptides, and various other biomolecules in the brain with high temporal and spatial resolution. Only a comprehensive understanding of neuromodulator dynamics, their release probability, and spatial distribution will unravel their ultimate role in cognition and behavior. This Perspective offers an overview of potential design strategies for class C GPCR-based biosensors. It briefly highlights current applications of GPCR-based biosensors, with a primary focus on class C GPCRs and their unique structural characteristics compared with other GPCR subfamilies. The discussion offers insights into plausible future design approaches for biosensor development targeting members of this specific GPCR subfamily. It is important to note that, at this stage, we are contemplating possibilities rather than presenting a concrete guide, as the pipeline is still under development.

Illuminating the brain-genetically encoded single wavelength fluorescent biosensors to unravel neurotransmitter dynamics

Understanding how neuronal networks generate complex behavior is one of the major goals of Neuroscience. Neurotransmitter and Neuromodulators are crucial for information flow between neurons and understanding their dynamics is the key to unravel their role in behavior. To understand how the brain transmits information and how brain states arise, it is essential to visualize the dynamics of neurotransmitters, neuromodulators and neurochemicals. In the last five years, an increasing number of single-wavelength biosensors either based on periplasmic binding proteins (PBPs) or on G-protein-coupled receptors (GPCR) have been published that are able to detect neurotransmitter release in vitro and in vivo with high spatial and temporal resolution. Here we review and discuss recent progress in the development of these sensors, their limitations and future directions.

The conformational landscape of human transthyretin revealed by cryo-EM

Transthyretin (TTR) is a natively tetrameric thyroxine transporter found in blood and cerebrospinal fluid whose misfolding and aggregation causes transthyretin amyloidosis. A rational drug design campaign identified the small molecule tafamidis (Vyndaqel/Vyndamax) as an effective stabilizer of the native TTR fold, and this aggregation inhibitor is regulatory agency-approved for the treatment of TTR amyloidosis. Despite 50 years of structural studies on TTR and this triumph of structure-based drug design, there remains a notable dearth of structural information available to understand ligand binding allostery and amyloidogenic TTR unfolding intermediates. We used single-particle cryo-electron microscopy (cryo-EM) to investigate the conformational landscape of this 55 kiloDalton tetramer in the absence and presence of one or two ligands, revealing inherent asymmetries in the tetrameric architecture and previously unobserved conformational states. These findings provide critical mechanistic insights into negatively cooperative ligand binding and the structural pathways responsible for TTR amyloidogenesis. This study underscores the capacity of cryo-EM to provide new insights into protein structures that have been historically considered too small to visualize and to identify pharmacological targets suppressed by the confines of the crystal lattice, opening uncharted territory in structure-based drug design.

Monitoring Intracellular IP6 with a Genetically Encoded Fluorescence Biosensor

Inositol hexakisphosphate (IP6), a naturally occurring metabolite of inositol with specific functions in different organelles or tissues, participates in numerous physiological processes and plays a key role in mammalian metabolic regulation. However, current IP6 detection methods, i.e., high-performance liquid chromatography and gel electrophoresis, require sample destruction and lack spatiotemporal resolution. Here, we construct and characterize a genetically encoded fluorescence biosensor named HIPSer that enables ratiometric quantitative IP6 detection in HEK293T cells and subcellular compartments. We demonstrate that HIPSer has a high sensitivity and relative selectivity for IP6 in vitro. We also provide proof-of-concept evidence that HIPSer can monitor IP6 levels in real time in HEK293T cells and can be targeted for IP6 detection in the nucleus of HEK293T cells. Moreover, HIPSer could also detect changes in IP6 content induced by chemical inhibition of IP6-metabolizing enzymes in HEK293T cells. Thus, HIPSer achieves spatiotemporally precise detection of fluctuations in endogenous IP6 in live cells and provides a versatile tool for mechanistic investigations of inositol phosphate functions in metabolism and signaling.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

A genetically-encoded biosensor for direct detection of perfluorooctanoic acid

Determination of per- and polyfluoroalkyl substances (PFAS) in drinking water at the low levels set by regulatory officials has been a major focus for sensor developing researchers. However, it is becoming more apparent that detection of these contaminants in soils, foods and consumer products is relevant and necessary at part per billion and even part per million levels. Here, a fluorescent biosensor for the rapid detection of PFOA was engineered based on human liver fatty acid binding protein (hLFABP). By conjugating circularly permuted green fluorescent protein (cp.GFP) to a split hLFABP construct, the biosensor was able to detect perfluorooctanoic acid PFOA in PBS as well as environmental water samples with LODs of 236 and 330 ppb respectively. Furthermore, E. coli cells cytosolically expressing the protein-based sensor were demonstrated to quickly detect PFOA, demonstrating feasibility of whole-cell sensing. Overall, this work demonstrates a platform technology utilizing a circularly permuted GFP and split hLFABP conjugate as a label-free optical biosensor for PFOA.

Fluorescent proteins and genetically encoded biosensors

The genetically encoded fluorescent sensors convert chemical and physical signals into light. They are powerful tools for the visualisation of physiological processes in living cells and freely moving animals. The fluorescent protein is the reporter module of a genetically encoded biosensor. In this study, we first review the history of the fluorescent protein in full emission spectra on a structural basis. Then, we discuss the design of the genetically encoded biosensor. Finally, we briefly review several major types of genetically encoded biosensors that are currently widely used based on their design and molecular targets, which may be useful for the future design of fluorescent biosensors.

Single-Fluorophore Indicator to Explore Cellular and Sub-cellular Lactate Dynamics

Lactate is an energy substrate and an intercellular signal, which can be monitored in intact cells with the genetically encoded FRET indicator Laconic. However, the structural complexity, need for sophisticated equipment, and relatively small fluorescent change limit the use of FRET indicators for subcellular targeting and development of high-throughput screening methodologies. Using the bacterial periplasmic binding protein TTHA0766 from Thermus thermophilus, we have now developed a single-fluorophore indicator for lactate, CanlonicSF. This indicator exhibits a maximal fluorescence change of 200% and a K_D of ∼300 μM. The fluorescence is not affected by other monocarboxylates. The lactate indicator was not significantly affected by Ca²⁺ at the physiological concentrations prevailing in the cytosol, endoplasmic reticulum, and extracellular space, but was affected by Ca²⁺ in the low micromolar range. Targeting the indicator to the endoplasmic reticulum revealed for the first time sub-cellular lactate dynamics. Its improved lactate-induced fluorescence response permitted the development of a multiwell plate assay to screen for inhibitors of the monocarboxylate transporters MCTs, a pharmaceutical target for cancer and inflammation. The functionality of the indicator in living tissue was demonstrated in the brain of Drosophila melanogaster larvae. CanlonicSF is well suited to explore lactate dynamics with sub-cellular resolution in intact systems.

A high-performance genetically encoded fluorescent indicator for in vivo cAMP imaging

cAMP is a key second messenger that regulates diverse cellular functions including neural plasticity. However, the spatiotemporal dynamics of intracellular cAMP in intact organisms are largely unknown due to low sensitivity and/or brightness of current genetically encoded fluorescent cAMP indicators. Here, we report the development of the new circularly permuted GFP (cpGFP)-based cAMP indicator G-Flamp1, which exhibits a large fluorescence increase (a maximum ΔF/F₀ of 1100% in HEK293T cells), decent brightness, appropriate affinity (a K_d of 2.17 μM) and fast response kinetics (an association and dissociation half-time of 0.20 and 0.087 s, respectively). Furthermore, the crystal structure of the cAMP-bound G-Flamp1 reveals one linker connecting the cAMP-binding domain to cpGFP adopts a distorted β-strand conformation that may serve as a fluorescence modulation switch. We demonstrate that G-Flamp1 enables sensitive monitoring of endogenous cAMP signals in brain regions that are implicated in learning and motor control in living organisms such as fruit flies and mice.

Monitoring glycolytic dynamics in single cells using a fluorescent biosensor for fructose 1,6-bisphosphate

Cellular metabolism is regulated over space and time to ensure that energy production is efficiently matched with consumption. Fluorescent biosensors are useful tools for studying metabolism as they enable real-time detection of metabolite abundance with single-cell resolution. For monitoring glycolysis, the intermediate fructose 1,6-bisphosphate (FBP) is a particularly informative signal as its concentration is strongly correlated with flux through the whole pathway. Using GFP insertion into the ligand-binding domain of the Bacillus subtilis transcriptional regulator CggR, we developed a fluorescent biosensor for FBP termed HYlight. We demonstrate that HYlight can reliably report the real-time dynamics of glycolysis in living cells and tissues, driven by various metabolic or pharmacological perturbations, alone or in combination with other physiologically relevant signals. Using this sensor, we uncovered previously unknown aspects of β-cell glycolytic heterogeneity and dynamics.

Circularized fluorescent nanodiscs for probing protein-lipid interactions

Protein–lipid interactions are vital for numerous transmembrane signaling pathways. However, simple tools to characterize these interactions remain scarce and are much needed to advance our understanding of signal transduction across lipid bilayers. To tackle this challenge, we herein engineer nanodisc as a robust fluorescent sensor for reporting membrane biochemical reactions. We circularize nanodiscs via split GFP and thereby create an intensity-based fluorescent sensor (isenND) for detecting membrane binding and remodeling events. We show that isenND responds robustly and specifically to the action of a diverse array of membrane-interacting proteins and peptides, ranging from synaptotagmin and synuclein involved in neurotransmission to viral fusion peptides of HIV-1 and SARS-CoV-2. Together, isenND can serve as a versatile biochemical reagent useful for basic and translational research of membrane biology.

A fluorescent probe for detecting membrane protein binding and remodeling events is presented, which relies on split-GFP technology to generate circularized nanodiscs useful in membrane protein biophysics and structural biology.

Advances in the Computational Design of Small-Molecule-Controlled Protein-Based Circuits for Synthetic Biology

Synthetic biology approaches living systems with an engineering perspective and promises to deliver solutions to global challenges in healthcare and sustainability. A critical component is the design of biomolecular circuits with programmable input-output behaviors. Such circuits typically rely on a sensor module that recognizes molecular inputs, which is coupled to a functional output via protein-level circuits or regulating the expression of a target gene. While gene expression outputs can be customized relatively easily by exchanging the target genes, sensing new inputs is a major limitation. There is a limited repertoire of sensors found in nature, and there are often difficulties with interfacing them with engineered circuits. Computational protein design could be a key enabling technology to address these challenges, as it allows for the engineering of modular and tunable sensors that can be tailored to the circuit's application. In this article, we review recent computational approaches to design protein-based sensors for small-molecule inputs with particular focus on those based on the widely used Rosetta software suite. Furthermore, we review mechanisms that have been harnessed to couple ligand inputs to functional outputs. Based on recent literature, we illustrate how the combination of protein design and synthetic biology enables new sensors for diverse applications ranging from biomedicine to metabolic engineering. We conclude with a perspective on how strategies to address frontiers in protein design and cellular circuit design may enable the next generation of sense-response networks, which may increasingly be assembled from de novo components to display diverse and engineerable input-output behaviors.

Construction of a highly selective and sensitive carbohydrate-detecting biosensor utilizing Computational Identification of Non-disruptive Conjugation sites (CINC) for flexible and streamlined biosensor design

Fluorescently-labeled solute-binding proteins that alter their fluorescence output in response to ligand binding have been utilized as biosensors for a variety of applications. Coupling protein ligand binding to altered fluorescence output often requires trial and error-based testing of both multiple labeling positions and fluorophores to produce a functional biosensor with the desired properties. This approach is laborious and can lead to reduced ligand binding affinity or altered ligand specificity. Here we report the Computational Identification of Non-disruptive Conjugation sites (CINC) for streamlined identification of fluorophore conjugation sites. By exploiting the structural dynamics properties of proteins, CINC identifies positions where conjugation of a fluorophore results in a fluorescence change upon ligand binding without disrupting protein function. We show that a CINC-developed maltooligosaccharide (MOS)-detecting biosensor is capable of rapid (k_on = 20 μM^-1s^-1), sensitive (sub-μM K_D) and selective MOS detection. The MOS-detecting biosensor is modular with respect to the spectroscopic properties and demonstrates portability to detecting MOS released via α-amylase-catalyzed depolymerization of starch using both a stopped-flow and a microplate reader assay. Our MOS-detecting biosensor represents a first-in-class probe whose design was guided by changes in localized dynamics of individual amino acid positions, supporting expansion of the CINC pipeline as an indispensable tool for a wide range of protein engineering applications.

Visualizing physiological parameters in cells and tissues using genetically encoded indicators for metabolites

The study of metabolism is undergoing a renaissance. Since the year 2002, over 50 genetically-encoded fluorescent indicators (GEFIs) have been introduced, capable of monitoring metabolites with high spatial/temporal resolution using fluorescence microscopy. Indicators are fusion proteins that change their fluorescence upon binding a specific metabolite. There are indicators for sugars, monocarboxylates, Krebs cycle intermediates, amino acids, cofactors, and energy nucleotides. They permit monitoring relative levels, concentrations, and fluxes in living systems. At a minimum they report relative levels and, in some cases, absolute concentrations may be obtained by performing ad hoc calibration protocols. Proper data collection, processing, and interpretation are critical to take full advantage of these new tools. This review offers a survey of the metabolic indicators that have been validated in mammalian systems. Minimally invasive, these indicators have been instrumental for the purposes of confirmation, rebuttal and discovery. We envision that this powerful technology will foster metabolic physiology.

Development of a Real-Time Pectic Oligosaccharide-Detecting Biosensor Using the Rapid and Flexible Computational Identification of Non-Disruptive Conjugation Sites (CINC) Biosensor Design Platform

Fluorescently labeled, solute-binding proteins that change their fluorescent output in response to ligand binding are frequently used as biosensors for a wide range of applications. We have previously developed a "Computational Identification of Non-disruptive Conjugation sites" (CINC) approach, an in silico pipeline utilizing molecular dynamics simulations for the rapid design and construction of novel protein-fluorophore conjugate-type biosensors. Here, we report an improved in silico scoring algorithm for use in CINC and its use in the construction of an oligogalacturonide-detecting biosensor set. Using both 4,5-unsaturated and saturated oligogalacturonides, we demonstrate that signal transmission from the ligand-binding pocket of the starting protein scaffold to the CINC-selected reporter positions is effective for multiple different ligands. The utility of an oligogalacturonide-detecting biosensor is shown in Carbohydrate Active Enzyme (CAZyme) activity assays, where the biosensor is used to follow product release upon polygalacturonic acid (PGA) depolymerization in real time. The oligogalacturonide-detecting biosensor set represents a novel enabling tool integral to our rapidly expanding platform for biosensor-based carbohydrate detection, and moving forward, the CINC pipeline will continue to enable the rational design of biomolecular tools to detect additional chemically distinct oligosaccharides and other solutes.

Genetically encoded photo-switchable molecular sensors for optoacoustic and super-resolution imaging

Reversibly photo-switchable proteins are essential for many super-resolution fluorescence microscopic and optoacoustic imaging methods. However, they have yet to be used as sensors that measure the distribution of specific analytes at the nanoscale or in the tissues of live animals. Here we constructed the prototype of a photo-switchable Ca²⁺ sensor based on GCaMP5G that can be switched with 405/488-nm light and describe its molecular mechanisms at the structural level, including the importance of the interaction of the core barrel structure of the fluorescent protein with the Ca²⁺ receptor moiety. We demonstrate super-resolution imaging of Ca²⁺ concentration in cultured cells and optoacoustic Ca²⁺ imaging in implanted tumor cells in mice under controlled Ca²⁺ conditions. Finally, we show the generalizability of the concept by constructing examples of photo-switching maltose and dopamine sensors based on periplasmatic binding protein and G-protein-coupled receptor-based sensors.

Fine-tuning spermidine binding modes in the putrescine binding protein PotF

A profound understanding of the molecular interactions between receptors and ligands is important throughout diverse research, such as protein design, drug discovery, or neuroscience. What determines specificity and how do proteins discriminate against similar ligands? In this study, we analyzed factors that determine binding in two homologs belonging to the well-known superfamily of periplasmic binding proteins, PotF and PotD. Building on a previously designed construct, modes of polyamine binding were swapped. This change of specificity was approached by analyzing local differences in the binding pocket as well as overall conformational changes in the protein. Throughout the study, protein variants were generated and characterized structurally and thermodynamically, leading to a specificity swap and improvement in affinity. This dataset not only enriches our knowledge applicable to rational protein design but also our results can further lay groundwork for engineering of specific biosensors as well as help to explain the adaptability of pathogenic bacteria.

A Novel Assay Allowing Drug Self-Administration, Extinction, and Reinstatement Testing in Head-Restrained Mice

Multiphoton microscopy is one of several new technologies providing unprecedented insight into the activity dynamics and function of neural circuits. Unfortunately, some of these technologies require experimentation in head-restrained animals, limiting the behavioral repertoire that can be integrated and studied. This issue is especially evident in drug addiction research, as no laboratories have coupled multiphoton microscopy with simultaneous intravenous drug self-administration, a behavioral paradigm that has predictive validity for treatment outcomes and abuse liability. Here, we describe a new experimental assay wherein head-restrained mice will press an active lever, but not inactive lever, for intravenous delivery of heroin or cocaine. Similar to freely moving animals, we find that lever pressing is suppressed through daily extinction training and subsequently reinstated through the presentation of relapse-provoking triggers (drug-associative cues, the drug itself, and stressors). Finally, we show that head-restrained mice will show similar patterns of behavior for oral delivery of a sucrose reward, a common control used for drug self-administration experiments. Overall, these data demonstrate the feasibility of combining drug self-administration experiments with technologies that require head-restraint, such as multiphoton imaging. The assay described could be replicated by interested labs with readily available materials to aid in identifying the neural underpinnings of substance use disorder.

Designs, applications, and limitations of genetically encoded fluorescent sensors to explore plant biology

The understanding of signaling and metabolic processes in multicellular organisms requires knowledge of the spatial dynamics of small molecules and the activities of enzymes, transporters, and other proteins in vivo, as well as biophysical parameters inside cells and across tissues. The cellular distribution of receptors, ligands, and activation state must be integrated with information about the cellular distribution of metabolites in relation to metabolic fluxes and signaling dynamics in order to achieve the promise of in vivo biochemistry. Genetically encoded sensors are engineered fluorescent proteins that have been developed for a wide range of small molecules, such as ions and metabolites, or to report biophysical processes, such as transmembrane voltage or tension. First steps have been taken to monitor the activity of transporters in vivo. Advancements in imaging technologies and specimen handling and stimulation have enabled researchers in plant sciences to implement sensor technologies in intact plants. Here, we provide a brief history of the development of genetically encoded sensors and an overview of the types of sensors available for quantifying and visualizing ion and metabolite distribution and dynamics. We further discuss the pros and cons of specific sensor designs, imaging systems, and sample manipulations, provide advice on the choice of technology, and give an outlook into future developments.

A Sort-Seq Approach to the Development of Single Fluorescent Protein Biosensors

Motivated by the growing importance of single fluorescent protein biosensors (SFPBs) in biological research and the difficulty in rationally engineering these tools, we sought to increase the rate at which SFPB designs can be optimized. SFPBs generally consist of three components: a circularly permuted fluorescent protein, a ligand-binding domain, and linkers connecting the two domains. In the absence of predictive methods for biosensor engineering, most designs combining these three components will fail to produce allosteric coupling between ligand binding and fluorescence emission. While methods to construct diverse libraries with variation in the site of GFP insertion and linker sequences have been developed, the remaining bottleneck is the ability to test these libraries for functional biosensors. We address this challenge by applying a massively parallel assay termed "sort-seq," which combines binned fluorescence-activated cell sorting, next-generation sequencing, and maximum likelihood estimation to quantify the brightness and dynamic range for many biosensor variants in parallel. We applied this method to two common biosensor optimization tasks: the choice of insertion site and optimization of linker sequences. The sort-seq assay applied to a maltose-binding protein domain-insertion library not only identified previously described high-dynamic-range variants but also discovered new functional insertion sites with diverse properties. A sort-seq assay performed on a pyruvate biosensor linker library expressed in mammalian cell culture identified linker variants with substantially improved dynamic range. Machine learning models trained on the resulting data can predict dynamic range from linker sequences. This high-throughput approach will accelerate the design and optimization of SFPBs, expanding the biosensor toolbox.

Neurochemical Signaling of Reward and Aversion to Ventral Tegmental Area Glutamate Neurons

Ventral tegmental area (VTA) glutamate neurons signal and participate in reward and aversion-based behaviors. However, the neurochemical mechanisms that underlie how these neurons contribute to motivated behaviors is unknown. We used a combination of optical sensors to identify how distinct neurochemical inputs to VTA glutamate neurons participate in motivated behavior within female and male transgenic mice. Activity of glutamate inputs to VTA glutamate neurons increased for both reward-predicting and aversion-predicting cues and aversive outcomes, but subpopulations of glutamate inputs were increased or decreased by reward. For both reward and aversion-based cues and outcomes, activity of GABA inputs to VTA glutamate neurons mostly decreased. GCaMP recordings showed overall population increases in VTA glutamate neuron intracellular calcium during reward and aversion-based cues and outcomes. Electrophysiological recordings of VTA VGluT2 neurons showed that glutamate receptor activation increases firing while loss of excitation via glutamate receptor blockade decreases firing. GABA-A receptor activation decreased VTA glutamate neuron firing but GABA-A receptor blockade did not significantly change VTA glutamate neuron firing. Electrophysiological recordings in coordination with our sensor data suggest that glutamate inputs strongly regulate VTA glutamate neuron participation in diverse motivated behaviors.SIGNIFICANCE STATEMENT Glutamate and GABA are the primary excitatory and inhibitory neurotransmitters of the nervous system. However, identifying how these neurotransmitters regulate motivated behavior has remained challenging because of a lack of tools (1) capable of measuring neurotransmission at the temporal scale of motivated behaviors and (2) capable of capturing chemical signaling onto genetically-distinct neuronal populations. We have overcome these obstacles by implementing genetically-encoded fluorescent indicators to monitor both glutamate and GABA input dynamics exclusively to ventral tegmental area (VTA) glutamate neurons during reward and aversion-based behaviors. We identify that glutamate and GABA inputs to VTA glutamate neurons differentially and dynamically signal reward and aversion-based cues and outcomes. This research provides foundational evidence that links distinct neurotransmitters to motivated behaviors regulated by VTA glutamate neurons.

In vivo glucose imaging in multiple model organisms with an engineered single-wavelength sensor

Glucose is arguably the most important molecule in metabolism, and its dysregulation underlies diabetes. We describe a family of single-wavelength genetically encoded glucose sensors with a high signal-to-noise ratio, fast kinetics, and affinities varying over four orders of magnitude (1 μM to 10 mM). The sensors allow mechanistic characterization of glucose transporters expressed in cultured cells with high spatial and temporal resolution. Imaging of neuron/glia co-cultures revealed ∼3-fold faster glucose changes in astrocytes. In larval Drosophila central nervous system explants, intracellular neuronal glucose fluxes suggested a rostro-caudal transport pathway in the ventral nerve cord neuropil. In zebrafish, expected glucose-related physiological sequelae of insulin and epinephrine treatments were directly visualized. Additionally, spontaneous muscle twitches induced glucose uptake in muscle, and sensory and pharmacological perturbations produced large changes in the brain. These sensors will enable rapid, high-resolution imaging of glucose influx, efflux, and metabolism in behaving animals.

A Ratiometric Fluorescent Biosensor Reveals Dynamic Regulation of Long-Chain Fatty Acyl-CoA Esters Metabolism

Despite increasing awareness of the biological impacts of long-chain fatty acyl-CoA esters (LCACoAs), our knowledge about the subcellular distribution and regulatory functions of these acyl-CoA molecules is limited by a lack of methods for detecting LCACoAs in living cells. Here, we report development of a genetically encoded fluorescent sensor that enables ratiometric quantification of LCACoAs in living cells and subcellular compartments. We demonstrate how this FadR-cpYFP fusion "LACSer sensor" undergoes LCACoA-induced conformational changes reflected in easily detectable fluorescence responses, and show proof-of-concept for real-time monitoring of LCACoAs in human cells. Subsequently, we applied LACSer in scientific studies investigating how disruption of ACSL enzymes differentially reduces cytosolic and mitochondrial LCACoA levels, and show how genetic disruption of an acyl-CoA binding protein (ACBP) alters mitochondrial accumulation of LCACoAs.

A fast, high-affinity fluorescent serotonin biosensor engineered from a tick lipocalin

Serotonin (5-HT) is an important signaling monoamine and neurotransmitter. We report structure-guided engineering of a green fluorescent, genetically encoded serotonin sensor (G-GESS) from a 5-HT-binding lipocalin in the soft tick Argas monolakensis. G-GESS shows fast response kinetics and high affinity, specificity, brightness and photostability. We used G-GESS to image 5-HT dynamics in cultured cells, brain slices and behaving mice.

Structure- and mechanism-guided design of single fluorescent protein-based biosensors

Intensiometric genetically encoded biosensors, based on allosteric modulation of the fluorescence of a single fluorescent protein, are powerful tools for enabling imaging of neural activities and other cellular biochemical events. The archetypical example of such biosensors is the GCaMP series of Ca²⁺ biosensors, which have been steadily improved over the past two decades and are now indispensable tools for neuroscience. However, no other biosensors have reached levels of performance, or had revolutionary impacts within specific disciplines, comparable to that of the Ca²⁺ biosensors. Of the many reasons why this has been the case, a critical one has been a general black-box view of biosensor structure and mechanism. With this Perspective, we aim to summarize what is known about biosensor structure and mechanisms and, based on this foundation, provide guidelines to accelerate the development of a broader range of biosensors with performance comparable to that of the GCaMP series.

A comprehensive binding study illustrates ligand recognition in the periplasmic binding protein PotF

Periplasmic binding proteins (PBPs) are ubiquitous receptors in gram-negative bacteria. They sense solutes and play key roles in nutrient uptake. Escherichia coli's putrescine receptor PotF has been reported to bind putrescine and spermidine. We reveal that several similar biogenic polyamines are recognized by PotF. Using isothermal titration calorimetry paired with X-ray crystallography of the different complexes, we unveil PotF's binding modes in detail. The binding site for PBPs is located between two lobes that undergo a large conformational change upon ligand recognition. Hence, analyzing the influence of ligands on complex formation is crucial. Therefore, we solved crystal structures of an open and closed apo state and used them as a basis for molecular dynamics simulations. In addition, we accessed structural behavior in solution for all complexes by ¹H-¹⁵N HSQC NMR spectroscopy. This combined analysis provides a robust framework for understanding ligand binding for future developments in drug design and protein engineering.

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively.

Imaging Neurotransmitter and Neuromodulator Dynamics In Vivo with Genetically Encoded Indicators

The actions of neuromodulation are thought to mediate the ability of the mammalian brain to dynamically adjust its functional state in response to changes in the environment. Altered neurotransmitter (NT) and neuromodulator (NM) signaling is central to the pathogenesis or treatment of many human neurological and psychiatric disorders, including Parkinson's disease, schizophrenia, depression, and addiction. To reveal the precise mechanisms by which these neurochemicals regulate healthy and diseased neural circuitry, one needs to measure their spatiotemporal dynamics in the living brain with great precision. Here, we discuss recent development, optimization, and applications of optical approaches to measure the spatial and temporal profiles of NT and NM release in the brain using genetically encoded sensors for in vivo studies.

A Fluorescence Resonance Energy Transfer-Based Analytical Tool for Nitrate Quantification in Living Cells

Nitrate (NO₃ ^-) is a critical source of nitrogen (N) available to microorganisms and plants. Nitrate sensing activates signaling pathways in the plant system that impinges upon, developmental, molecular, metabolic, and physiological responses locally, and globally. To sustain, the high crop productivity and high nutritional value along with the sustainable environment, the study of rate-controlling steps of a metabolic network of N assimilation through fluxomics becomes an attractive strategy. To monitor the flux of nitrate, we developed a non-invasive genetically encoded fluorescence resonance energy transfer (FRET)-based tool named "FLIP-NT" that monitors the real-time uptake of nitrate in the living cells. The developed nanosensor is suitable for real-time monitoring of nitrate flux in living cells at subcellular compartments with high spatio-temporal resolution. The developed FLIP-NT nanosensor was not affected by the pH change and have specificity for nitrate with an affinity constant (K _d) of ∼5 μM. A series of affinity mutants have also been generated to expand the physiological detection range of the sensor protein with varying K _d values. It has been found that this sensor successfully detects the dynamics of nitrate fluctuations in bacteria and yeast, without the disruption of cellular organization. This FLIP-NT nanosensor could be a very important tool that will help us to advance the understanding of nitrate signaling.

A Split Methyl Halide Transferase AND Gate That Reports by Synthesizing an Indicator Gas

Monitoring microbial reactions in highly opaque or autofluorescent environments like soils, seawater, and wastewater remains challenging. To develop a simple approach for observing post-translational reactions within microbes situated in environmental matrices, we designed a methyl halide transferase (MHT) fragment complementation assay that reports by synthesizing an indicator gas. We show that backbone fission within regions of high sequence variability in the Rossmann domain yields split MHT (sMHT) AND gates whose fragments cooperatively associate to synthesize CH₃Br. Additionally, we identify a sMHT whose fragments require fusion to pairs of interacting partner proteins for maximal activity. We also show that sMHT fragments fused to FKBP12 and the FKBP-rapamycin binding domain of mTOR display significantly enhanced CH₃Br production in the presence of rapamycin. This gas production is reversed in the presence of the competitive inhibitor of FKBP12/FKPB dimerization, indicating that sMHT is a reversible reporter of post-translational reactions. This sMHT represents the first genetic AND gate that reports on protein-protein interactions via an indicator gas. Because indicator gases can be measured in the headspaces of complex environmental samples, this assay should be useful for monitoring the dynamics of diverse molecular interactions within microbes situated in hard-to-image marine and terrestrial matrices.

129Xe NMR-Protein Sensor Reveals Cellular Ribose Concentration

Dysregulation of cellular ribose uptake can be indicative of metabolic abnormalities or tumorigenesis. However, analytical methods are currently limited for quantifying ribose concentration in complex biological samples. Here, we utilize the highly specific recognition of ribose by ribose-binding protein (RBP) to develop a single-protein ribose sensor detectable via a sensitive NMR technique known as hyperpolarized 129Xe chemical exchange saturation transfer (hyper-CEST). We demonstrate that RBP, with a tunable ribose-binding site and further engineered to bind xenon, enables the quantitation of ribose over a wide concentration range (nM to mM). Ribose binding induces the RBP "closed" conformation, which slows Xe exchange to a rate detectable by hyper-CEST. Such detection is remarkably specific for ribose, with the minimal background signal from endogenous sugars of similar size and structure, for example, glucose or ribose-6-phosphate. Ribose concentration was measured for mammalian cell lysate and serum, which led to estimates of low-mM ribose in a HeLa cell line. This highlights the potential for using genetically encoded periplasmic binding proteins such as RBP to measure metabolites in different biological fluids, tissues, and physiologic states.

Rational Design of Novel Fluorescent Enzyme Biosensors for Direct Detection of Strigolactones

Strigolactones are plant hormones and rhizosphere signaling molecules with key roles in plant development, mycorrhizal fungal symbioses, and plant parasitism. Currently, sensitive, specific, and high-throughput methods of detecting strigolactones are limited. Here, we developed genetically encoded fluorescent strigolactone biosensors based on the strigolactone receptors DAD2 from Petunia hybrida, and HTL7 from Striga hermonthica. The biosensors were constructed via domain insertion of circularly permuted GFP. The biosensors exhibited loss of cpGFP fluorescence in vitro upon treatment with the strigolactones 5-deoxystrigol and orobanchol, or the strigolactone analogue rac-GR24, and the ShHTL7 biosensor also responded to a specific antagonist. To overcome biosensor sensitivity to changes in expression level and protein degradation, an additional strigolactone-insensitive fluorophore, LSSmOrange, was included as an internal normalization control. Other plant hormones and karrikins resulted in no fluorescence change, demonstrating that the biosensors report on compounds that specifically bind the SL receptors. The DAD2 biosensor likewise responded to strigolactones in an in vivo protoplast system, and retained strigolactone hydrolysis activity. These biosensors have applications in high-throughput screening for agrochemical compounds, and may also have utility in understanding strigolactone mediated signaling in plants.

Imaging voltage and brain chemistry with genetically encoded sensors and modulators

Neurons and glia are functionally organized into circuits and higher-order structures that allow the precise information processing required for complex behaviors. To better understand the structure and function of the brain, we must understand synaptic connectivity, action potential generation and propagation, as well as well-orchestrated molecular signaling. Recently, dramatically improved sensors for voltage, intracellular calcium, and neurotransmitters/modulators, combined with advanced microscopy provide new opportunities for in vivo dissection of cellular and circuit activity in awake, behaving animals. This review focuses on the current trends in genetically encoded sensors for molecules and cellular events and their potential applicability to the study of nervous system in health and disease.

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.

Target-responsive vasoactive probes for ultrasensitive molecular imaging

The ability to monitor molecules volumetrically throughout the body could provide valuable biomarkers for studies of healthy function and disease, but noninvasive detection of molecular targets in living subjects often suffers from poor sensitivity or selectivity. Here we describe a family of potent imaging probes that can be activated by molecules of interest in deep tissue, providing a basis for mapping nanomolar-scale analytes without the radiation or heavy metal content associated with traditional molecular imaging agents. The probes are reversibly caged vasodilators that induce responses detectable by hemodynamic imaging; they are constructed by combining vasoactive peptides with synthetic chemical appendages and protein blocking domains. We use this architecture to create ultrasensitive biotin-responsive imaging agents, which we apply for wide-field mapping of targets in rat brains using functional magnetic resonance imaging. We also adapt the sensor design for detecting the neurotransmitter dopamine, illustrating versatility of this approach for addressing biologically important molecules.

A Bright and Colorful Future for G-Protein Coupled Receptor Sensors

Neurochemicals have a large impact on brain states and animal behavior but are notoriously hard to detect accurately in the living brain. Recently developed genetically encoded sensors obtained from engineering a circularly permuted green fluorescent protein into G-protein coupled receptors (GPCR) provided a vital boost to neuroscience, by innovating the way we monitor neural communication. These new probes are becoming widely successful due to their flexible combination with state of the art optogenetic tools and in vivo imaging techniques, mainly fiber photometry and 2-photon microscopy, to dissect dynamic changes in brain chemicals with unprecedented spatial and temporal resolution. Here, we highlight current approaches and challenges as well as novel insights in the process of GPCR sensor development, and discuss possible future directions of the field.

Recent advances in the use of genetically encodable optical tools to elicit and monitor signaling events

Cells rely on a complex network of spatiotemporally regulated signaling activities to effectively transduce information from extracellular cues to intracellular machinery. To probe this activity architecture, researchers have developed an extensive molecular tool kit of fluorescent biosensors and optogenetic actuators capable of monitoring and manipulating various signaling activities with high spatiotemporal precision. The goal of this review is to provide readers with an overview of basic concepts and recent advances in the development and application of genetically encodable biosensors and optogenetic tools for understanding signaling activity.

Circularly Permuted Fluorescent Protein-Based Indicators: History, Principles, and Classification

Genetically encoded biosensors based on fluorescent proteins (FPs) are a reliable tool for studying the various biological processes in living systems. The circular permutation of single FPs led to the development of an extensive class of biosensors that allow the monitoring of many intracellular events. In circularly permuted FPs (cpFPs), the original N- and C-termini are fused using a peptide linker, while new termini are formed near the chromophore. Such a structure imparts greater mobility to the FP than that of the native variant, allowing greater lability of the spectral characteristics. One of the common principles of creating genetically encoded biosensors is based on the integration of a cpFP into a flexible region of a sensory domain or between two interacting domains, which are selected according to certain characteristics. Conformational rearrangements of the sensory domain associated with ligand interaction or changes in the cellular parameter are transferred to the cpFP, changing the chromophore environment. In this review, we highlight the basic principles of such sensors, the history of their creation, and a complete classification of the available biosensors.

Risk-Based Bioengineering Strategies for Reliable Bacterial Vaccine Production

Design of a reliable process for bacterial antigen production requires understanding of and control over critical process parameters. Current methods for process design use extensive screening experiments for determining ranges of critical process parameters yet fail to give clear insights into how they influence antigen potency. To address this gap, we propose to apply constraint-based, genome-scale metabolic models to reduce the need of experimental screening for strain selection and to optimize strains based on model driven iterative Design-Build-Test-Learn (DBTL) cycles. Application of these systematic methods has not only increased the understanding of how metabolic network properties influence antigen potency, but also allows identification of novel critical process parameters that need to be controlled to achieve high process reliability.

Development and structural characterization of an engineered multi-copper oxidase reporter of protein-protein interactions

Protein–protein interactions (PPIs) are ubiquitous in almost all biological processes and are often corrupted in diseased states. A detailed understanding of PPIs is therefore key to understanding cellular physiology and can yield attractive therapeutic targets. Here, we describe the development and structural characterization of novel Escherichia coli CueO multi-copper oxidase variants engineered to recapitulate protein–protein interactions with commensurate modulation of their enzymatic activities. The fully integrated single-protein sensors were developed through modular grafting of ligand-specific peptides into a highly compliant and flexible methionine-rich loop of CueO. Sensitive detection of diverse ligand classes exemplified by antibodies, an E3 ligase, MDM2 proto-oncogene (MDM2), and protease (SplB from Staphylococcus aureus) was achieved in a simple mix and measure homogeneous format with visually observable colorimetric readouts. Therapeutic antagonism of MDM2 by small molecules and peptides in clinical development for treatment of cancer patients was assayed using the MDM2-binding CueO enzyme. Structural characterization of the free and MDM2-bound CueO variant provided functional insight into signal-transducing mechanisms of the engineered enzymes and highlighted the robustness of CueO as a stable and compliant scaffold for multiple applications.

A genetically encoded single-wavelength sensor for imaging cytosolic and cell surface ATP

Adenosine 5' triphosphate (ATP) is a universal intracellular energy source and an evolutionarily ancient, ubiquitous extracellular signal in diverse species. Here, we report the generation and characterization of single-wavelength genetically encoded fluorescent sensors (iATPSnFRs) for imaging extracellular and cytosolic ATP from insertion of circularly permuted superfolder GFP into the epsilon subunit of F0F1-ATPase from Bacillus PS3. On the cell surface and within the cytosol, iATPSnFR1.0 responds to relevant ATP concentrations (30 μM to 3 mM) with fast increases in fluorescence. iATPSnFRs can be genetically targeted to specific cell types and sub-cellular compartments, imaged with standard light microscopes, do not respond to other nucleotides and nucleosides, and when fused with a red fluorescent protein function as ratiometric indicators. After careful consideration of their modest pH sensitivity, iATPSnFRs represent promising reagents for imaging ATP in the extracellular space and within cells during a variety of settings, and for further application-specific refinements.