PII Protein-Derived FRET Sensors for Quantification and Live-Cell Imaging of 2-Oxoglutarate

Unravelling molecular dynamics in living cells: Fluorescent protein biosensors for cell biology

Genetically encoded, fluorescent protein (FP)-based Förster resonance energy transfer (FRET) biosensors are microscopy imaging tools tailored for the precise monitoring and detection of molecular dynamics within subcellular microenvironments. They are characterised by their ability to provide an outstanding combination of spatial and temporal resolutions in live-cell microscopy. In this review, we begin by tracing back on the historical development of genetically encoded FP labelling for detection in live cells, which lead us to the development of early biosensors and finally to the engineering of single-chain FRET-based biosensors that have become the state-of-the-art today. Ultimately, this review delves into the fundamental principles of FRET and the design strategies underpinning FRET-based biosensors, discusses their diverse applications and addresses the distinct challenges associated with their implementation. We place particular emphasis on single-chain FRET biosensors for the Rho family of guanosine triphosphate hydrolases (GTPases), pointing to their historical role in driving our understanding of the molecular dynamics of this important class of signalling proteins and revealing the intricate relationships and regulatory mechanisms that comprise Rho GTPase biology in living cells.

Branched-chain amino acid transaminase 1 regulates glioblastoma cell plasticity and contributes to immunosuppression

BACKGROUND

Glioblastoma is the most common malignant brain tumor in adults. Cellular plasticity and the poorly differentiated features result in a fast relapse of the tumors following treatment. Moreover, the immunosuppressive microenvironment proved to be a major obstacle to immunotherapeutic approaches. Branched-chain amino acid transaminase 1 (BCAT1) was shown to drive the growth of glioblastoma and other cancers;however, its oncogenic mechanism remains poorly understood.

METHODS

Using human tumor data, cell line models and orthotopic immuno-competent and -deficient mouse models, we investigated the phenotypic and mechanistic effects of BCAT1 on glioblastoma cell state and immunomodulation.

RESULTS

Here, we show that BCAT1 is crucial for maintaining the poorly differentiated state of glioblastoma cells and that its low expression correlates with a more differentiated glioblastoma phenotype. Furthermore, orthotopic tumor injection into immunocompetent mice demonstrated that the brain microenvironment is sufficient to induce differentiation of Bcat1-KO tumors in vivo. We link the transition to a differentiated cell state to the increased activity of ten-eleven translocation demethylases and the hypomethylation and activation of neuronal differentiation genes. In addition, the knockout of Bcat1 attenuated immunosuppression, allowing for an extensive infiltration of CD8+ cytotoxic T-cells and complete abrogation of tumor growth. Further analysis in immunodeficient mice revealed that both tumor cell differentiation and immunomodulation following BCAT1-KO contribute to the long-term suppression of tumor growth.

CONCLUSIONS

Our study unveils BCAT1's pivotal role in promoting glioblastoma growth by inhibiting tumor cell differentiation and sustaining an immunosuppressive milieu. These findings offer a novel therapeutic avenue for targeting glioblastoma through the inhibition of BCAT1.

Dynamic fluctuations in a bacterial metabolic network

The operation of the central metabolism is typically assumed to be deterministic, but dynamics and high connectivity of the metabolic network make it potentially prone to generating fluctuations. However, time-resolved measurements of metabolite levels in individual cells that are required to characterize such fluctuations remained a challenge, particularly in small bacterial cells. Here we use single-cell metabolite measurements based on Förster resonance energy transfer, combined with computer simulations, to explore the real-time dynamics of the metabolic network of Escherichia coli. We observe that steplike exposure of starved E. coli to glycolytic carbon sources elicits large periodic fluctuations in the intracellular concentration of pyruvate in individual cells. These fluctuations are consistent with predicted oscillatory dynamics of E. coli metabolic network, and they are primarily controlled by biochemical reactions around the pyruvate node. Our results further indicate that fluctuations in glycolysis propagate to other cellular processes, possibly leading to temporal heterogeneity of cellular states within a population.

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.

Imaging Approaches for the Study of Metabolism in Real Time Using Genetically Encoded Reporters

Metabolism comprises of two axes in order to serve homeostasis: anabolism and catabolism. Both axes are interbranched with the so-called bioenergetics aspect of metabolism. There is a plethora of analytical biochemical methods to monitor metabolites and reactions in lysates, yet there is a rising need to monitor, quantify and elucidate in real time the spatiotemporal orchestration of complex biochemical reactions in living systems and furthermore to analyze the metabolic effect of chemical compounds that are destined for the clinic. The ongoing technological burst in the field of imaging creates opportunities to establish new tools that will allow investigators to monitor dynamics of biochemical reactions and kinetics of metabolites at a resolution that ranges from subcellular organelle to whole system for some key metabolites. This article provides a mini review of available toolkits to achieve this goal but also presents a perspective on the open space that can be exploited to develop novel methodologies that will merge classic biochemistry of metabolism with advanced imaging. In other words, a perspective of "watching metabolism in real time."

Measurement of the nuclear concentration of α-ketoglutarate during adipocyte differentiation by using a fluorescence resonance energy transfer-based biosensor with nuclear localization signals

α-Ketoglutarate (α-KG) also known as 2-oxoglutarate (2-OG) is an intermediate metabolite in the tricarboxylic acid (TCA) cycle and is also produced by the deamination of glutamate. It is an indispensable cofactor for a series of 2-oxoglutarate-dependent oxygenases including epigenetic modifiers such as ten-eleven translocation DNA demethylases (TETs) and JmjC domain-containing histone demethylases (JMJDs). Since these epigenetic enzymes target genomic DNA and histone in the nucleus, the nuclear concentration of α-KG would affect the levels of transcription by modulating the activity of the epigenetic enzymes. Thus, it is of great interest to measure the nuclear concentration of α-KG to elucidate the regulatory mechanism of these enzymes. Here, we report a novel fluorescence resonance energy transfer (FRET)-based biosensor with multiple nuclear localization signals (NLSs) to measure the nuclear concentration of α-KG. The probe contains the α-KG-binding GAF domain of NifA protein from Azotobacter vinelandii fused with EYFP and ECFP. Treatment of 3T3-L1 preadipocytes expressing this probe with either dimethyl-2-oxoglutarate (dimethyl-2-OG), a cell-permeable 2-OG derivative, or citrate elicited time- and dose-dependent changes in the FRET ratio, proving that this probe functions as an α-KG sensor. Measurement of the nuclear α-KG levels in the 3T3-L1 cells stably expressing the probe during adipocyte differentiation revealed that the nuclear concentration of α-KG increased in the early stage of differentiation and remained high thereafter. Thus, this nuclear-localized α-KG probe is a powerful tool for real-time monitoring of α-KG concentrations with subcellular resolution in living cells and is useful for elucidating the regulatory mechanisms of epigenetic enzymes.

High-Throughput Screening Reveals New Glutaminase Inhibitor Molecules

The glutaminase (GLS) enzyme hydrolyzes glutamine into glutamate, an important anaplerotic source for the tricarboxylic acid cycle in rapidly growing cancer cells under the Warburg effect. Glutamine-derived α-ketoglutarate is also an important cofactor of chromatin-modifying enzymes, and through epigenetic changes, it keeps cancer cells in an undifferentiated state. Moreover, glutamate is an important neurotransmitter, and deregulated glutaminase activity in the nervous system underlies several neurological disorders. Given the proven importance of glutaminase for critical diseases, we describe the development of a new coupled enzyme-based fluorescent glutaminase activity assay formatted for 384-well plates for high-throughput screening (HTS) of glutaminase inhibitors. We applied the new methodology to screen a ∼30,000-compound library to search for GLS inhibitors. The HTS assay identified 11 glutaminase inhibitors as hits that were characterized by in silico, biochemical, and glutaminase-based cellular assays. A structure-activity relationship study on the most promising hit (C9) allowed the discovery of a derivative, C9.22, with enhanced in vitro and cellular glutaminase-inhibiting activity. In summary, we discovered a new glutaminase inhibitor with an innovative structural scaffold and described the molecular determinants of its activity.

Astrocyte-neuron metabolic cooperation shapes brain activity

The brain has almost no energy reserve, but its activity coordinates organismal function, a burden that requires precise coupling between neurotransmission and energy metabolism. Deciphering how the brain accomplishes this complex task is crucial to understand central facets of human physiology and disease mechanisms. Each type of neural cell displays a peculiar metabolic signature, forcing the intercellular exchange of metabolites that serve as both energy precursors and paracrine signals. The paradigm of this biological feature is the astrocyte-neuron couple, in which the glycolytic metabolism of astrocytes contrasts with the mitochondrial oxidative activity of neurons. Astrocytes generate abundant mitochondrial reactive oxygen species and shuttle to neurons glycolytically derived metabolites, such as L-lactate and L-serine, which sustain energy needs, conserve redox status, and modulate neurotransmitter-receptor activity. Conversely, early disruption of this metabolic cooperation may contribute to the initiation or progression of several neurological diseases, thus requiring innovative therapies to preserve brain energetics.

Heterogeneous Expression of Nuclear Encoded Mitochondrial Genes Distinguishes Inhibitory and Excitatory Neurons

Mitochondrial composition varies by organ and their constituent cell types. This mitochondrial diversity likely determines variations in mitochondrial function. However, the heterogeneity of mitochondria in the brain remains underexplored despite the large diversity of cell types in neuronal tissue. Here, we used molecular systems biology tools to address whether mitochondrial composition varies by brain region and neuronal cell type in mice. We reasoned that proteomics and transcriptomics of microdissected brain regions combined with analysis of single-cell mRNA sequencing (scRNAseq) could reveal the extent of mitochondrial compositional diversity. We selected nuclear encoded gene products forming complexes of fixed stoichiometry, such as the respiratory chain complexes and the mitochondrial ribosome, as well as molecules likely to perform their function as monomers, such as the family of SLC25 transporters. We found that the proteome encompassing these nuclear-encoded mitochondrial genes and obtained from microdissected brain tissue segregated the hippocampus, striatum, and cortex from each other. Nuclear-encoded mitochondrial transcripts could only segregate cell types and brain regions when the analysis was performed at the single-cell level. In fact, single-cell mitochondrial transcriptomes were able to distinguish glutamatergic and distinct types of GABAergic neurons from one another. Within these cell categories, unique SLC25A transporters were able to identify distinct cell subpopulations. Our results demonstrate heterogeneous mitochondrial composition across brain regions and cell types. We postulate that mitochondrial heterogeneity influences regional and cell type-specific mechanisms in health and disease.

Split NanoLuc technology allows quantitation of interactions between PII protein and its receptors with unprecedented sensitivity and reveals transient interactions

PII proteins constitute a widespread signal transduction superfamily in the prokaryotic world. The canonical PII signal proteins sense metabolic state of the cells by binding the metabolite molecules ATP, ADP and 2-oxoglutarate. Depending on bound effector molecule, PII proteins interact with and modulate the activity of multiple target proteins. To investigate the complexity of interactions of PII with target proteins, analytical methods that do not disrupt the native cellular context are required. To this purpose, split luciferase proteins have been used to develop a novel complementation reporter called NanoLuc Binary Technology (NanoBiT). The luciferase NanoLuc is divided in two subunits: a 18 kDa polypeptide termed "Large BiT" and a 1.3 kDa peptide termed "Small BiT", which only weakly associate. When fused to proteins of interest, they reconstitute an active luciferase when the proteins of interest interact. Therefore, we set out to develop a new NanoBiT sensor based on the interaction of PII protein from Synechocystis sp. PCC6803 with PII-interacting protein X (PipX) and N-acetyl-L-glutamate kinase (NAGK). The novel NanoBiT sensor showed unprecedented sensitivity, which made it possible to detect even weak and transient interactions between PII variants and their interacting partners, thereby shedding new light in PII signalling processes.

Carbon/nitrogen homeostasis control in cyanobacteria

Carbon/nitrogen (C/N) balance sensing is a key requirement for the maintenance of cellular homeostasis. Therefore, cyanobacteria have evolved a sophisticated signal transduction network targeting the metabolite 2-oxoglutarate (2-OG), the carbon skeleton for nitrogen assimilation. It serves as a status reporter for the cellular C/N balance that is sensed by transcription factors NtcA and NdhR and the versatile PII-signaling protein. The PII protein acts as a multitasking signal-integrating regulator, combining the 2-OG signal with the energy state of the cell through adenyl-nucleotide binding. Depending on these integrated signals, PII orchestrates metabolic activities in response to environmental changes through binding to various targets. In addition to 2-OG, other status reporter metabolites have recently been discovered, mainly indicating the carbon status of the cells. One of them is cAMP, which is sensed by the PII-like protein SbtB. The present review focuses, with a main emphasis on unicellular model strains Synechoccus elongatus and Synechocystis sp. PCC 6803, on the physiological framework of these complex regulatory loops, the tight linkage to metabolism and the molecular mechanisms governing the signaling processes.

Fluorescent Biosensors for Neuronal Metabolism and the Challenges of Quantitation

Over the past decade, genetically encoded fluorescent biosensors that report metabolic changes have become valuable tools for understanding brain metabolism. These sensors have been targeted to specific brain regions and cell types in different organisms to track multiple metabolic processes at single cell (and subcellular) resolution. Here, we review genetically encoded biosensors used to study metabolism in the brain. We particularly focus on the principles needed to use these sensors quantitatively while avoiding false inferences from variations in sensor fluorescence that arise from differences in expression level or environmental influences such as pH or temperature.

Functional and structural characterization of PII-like protein CutA does not support involvement in heavy metal tolerance and hints at a small-molecule carrying/signaling role

The PII-like protein CutA is annotated as being involved in Cu²⁺ tolerance, based on analysis of Escherichia coli mutants. However, the precise cellular function of CutA remains unclear. Our bioinformatic analysis reveals that CutA proteins are universally distributed across all domains of life. Based on sequence-based clustering, we chose representative cyanobacterial CutA proteins for physiological, biochemical, and structural characterization and examined their involvement in heavy metal tolerance, by generating CutA mutants in filamentous Nostoc sp. and in unicellular Synechococcus elongatus. However, we were unable to find any involvement of cyanobacterial CutA in metal tolerance under various conditions. This prompted us to re-examine experimentally the role of CutA in protecting E. coli from Cu²⁺ . Since we found no effect on copper tolerance, we conclude that CutA plays a different role that is not involved in metal protection. We resolved high-resolution CutA structures from Nostoc and S. elongatus. Similarly to their counterpart from E. coli and to canonical PII proteins, cyanobacterial CutA proteins are trimeric in solution and in crystal structure; however, no binding affinity for small signaling molecules or for Cu²⁺ could be detected. The clefts between the CutA subunits, corresponding to the binding pockets of PII proteins, are formed by conserved aromatic and charged residues, suggesting a conserved binding/signaling function for CutA. In fact, we find binding of organic Bis-Tris/MES molecules in CutA crystal structures, revealing a strong tendency of these pockets to accommodate cargo. This highlights the need to search for the potential physiological ligands and for their signaling functions upon binding to CutA. DATABASES: Structural data are available in Protein Data Bank (PDB) under the accession numbers 6GDU, 6GDV, 6GDW, 6GDX, 6T76, and 6T7E.

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.

Tuning the in vitro sensing and signaling properties of cyanobacterial PII protein by mutation of key residues

PII proteins comprise an ancient superfamily of signal transduction proteins, widely distributed among all domains of life. In general, PII proteins measure and integrate the current carbon/nitrogen/energy status of the cell through interdependent binding of ATP, ADP and 2-oxogluterate. In response to effector molecule binding, PII proteins interact with various PII-receptors to tune central carbon- and nitrogen metabolism. In cyanobacteria, PII regulates, among others, the key enzyme for nitrogen-storage, N-acetyl-glutamate kinase (NAGK), and the co-activator of the global nitrogen-trascription factor NtcA, the PII-interacting protein-X (PipX). One of the remarkable PII variants from Synechococcus elongatus PCC 7942 that yielded mechanistic insights in PII-NAGK interaction, is the NAGK-superactivating variant I86N. Here we studied its interaction with PipX. Another critical residue is Lys58, forming a salt-bridge with 2-oxoglutarate in a PII-ATP-2-oxoglutarate complex. Here, we show that Lys58 of PII protein is a key residue for mediating PII interactions. The K58N mutation not only causes the loss of 2-oxogluterate binding but also strongly impairs binding of ADP, NAGK and PipX. Remarkably, the exchange of the nearby Leu56 to Lys in the K58N variant partially compensates for the loss of K58. This study demonstrates the potential of creating custom tailored PII variants to modulate metabolism.

Nano-Sampling and Reporter Tools to Study Metabolic Regulation in Zebrafish

In the past years, evidence has emerged that hallmarks of human metabolic disorders can be recapitulated in zebrafish using genetic, pharmacological or dietary interventions. An advantage of modeling metabolic diseases in zebrafish compared to other "lower organisms" is the presence of a vertebrate body plan providing the possibility to study the tissue-intrinsic processes preceding the loss of metabolic homeostasis. While the small size of zebrafish is advantageous in many aspects, it also has shortcomings such as the difficulty to obtain sufficient amounts for biochemical analyses in response to metabolic challenges. A workshop at the European Zebrafish Principal Investigator meeting in Trento, Italy, was dedicated to discuss the advantages and disadvantages of zebrafish to study metabolic disorders. This perspective article by the participants highlights strategies to achieve improved tissue-resolution for read-outs using "nano-sampling" approaches for metabolomics as well as live imaging of zebrafish expressing fluorescent reporter tools that inform on cellular or subcellular metabolic processes. We provide several examples, including the use of reporter tools to study the heterogeneity of pancreatic beta-cells within their tissue environment. While limitations exist, we believe that with the advent of new technologies and more labs developing methods that can be applied to minimal amounts of tissue or single cells, zebrafish will further increase their utility to study energy metabolism.

Carbon/Nitrogen Metabolic Balance: Lessons from Cyanobacteria

Carbon and nitrogen are the two most abundant nutrient elements for all living organisms, and their metabolism is tightly coupled. What are the signaling mechanisms that cells use to sense and control the carbon/nitrogen (C/N) metabolic balance following environmental changes? Based on studies in cyanobacteria, it was found that 2-phosphoglycolate derived from the oxygenase activity of Rubisco (ribulose-1,5-bisphosphate carboxylase/oxygenase) and 2-oxoglutarate from the Krebs cycle act as the carbon- and nitrogen-starvation signals, respectively, and their concentration ratio likely reflects the status of the C/N metabolic balance. We will present and discuss the regulatory principles underlying the signaling mechanisms, which are likely to be conserved in other photosynthetic organisms. These concepts may also contribute to developments in the field of biofuel engineering or improvements in crop productivity.

Biosensors-Based In Vivo Quantification of 2-Oxoglutarate in Cyanobacteria and Proteobacteria

2-oxoglutarate (α-ketoglutarate; 2-OG) is an intermediate of the Krebs cycle, and constitutes the carbon skeleton for nitrogen assimilation and the synthesis of a variety of compounds. In addition to being an important metabolite, 2-OG is a signaling molecule with a broad regulatory repertoire in a variety of organisms, including plants, animals, and bacteria. Although challenging, measuring the levels and variations of metabolic signals in vivo is critical to better understand how cells control specific processes. To measure cellular 2-OG concentrations and dynamics, we designed a set of biosensors based on the fluorescence resonance energy transfer (FRET) technology that can be used in vivo in different organisms. For this purpose, we took advantage of the conformational changes of two cyanobacterial proteins induced by 2-OG binding. We show that these biosensors responded immediately and specifically to different 2-OG levels, and hence allowed to measure 2-OG variations in function of environmental modifications in the proteobacterium Escherichia coli and in the cyanobacterium Anabaena sp. PCC 7120. Our results pave the way to study 2-OG dynamics at the cellular level in uni- and multi-cellular organisms.