OLIVe: A Genetically Encoded Fluorescent Biosensor for Quantitative Imaging of Branched-Chain Amino Acid Levels inside Single Living Cells

Decoding the nexus: branched-chain amino acids and their connection with sleep, circadian rhythms, and cardiometabolic health

The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and, either directly or indirectly, overall body health, encompassing metabolic and cardiovascular well-being. Given the heightened metabolic activity of the brain, there exists a considerable demand for nutrients in comparison to other organs. Among these, the branched-chain amino acids, comprising leucine, isoleucine, and valine, display distinctive significance, from their contribution to protein structure to their involvement in overall metabolism, especially in cerebral processes. Among the first amino acids that are released into circulation post-food intake, branched-chain amino acids assume a pivotal role in the regulation of protein synthesis, modulating insulin secretion and the amino acid sensing pathway of target of rapamycin. Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors, competing for a shared transporter. Beyond their involvement in protein synthesis, these amino acids contribute to the metabolic cycles of γ-aminobutyric acid and glutamate, as well as energy metabolism. Notably, they impact GABAergic neurons and the excitation/inhibition balance. The rhythmicity of branched-chain amino acids in plasma concentrations, observed over a 24-hour cycle and conserved in rodent models, is under circadian clock control. The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood. Disturbed sleep, obesity, diabetes, and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics. The mechanisms driving these effects are currently the focal point of ongoing research efforts, since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies. In this context, the Drosophila model, though underutilized, holds promise in shedding new light on these mechanisms. Initial findings indicate its potential to introduce novel concepts, particularly in elucidating the intricate connections between the circadian clock, sleep/wake, and metabolism. Consequently, the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle. They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health, paving the way for potential therapeutic interventions.

NeIle, a Genetically Encoded Indicator for Branched-Chain Amino Acids Based on mNeonGreen Fluorescent Protein and LIVBP Protein

Branched-chain amino acids (BCAAs) play an important role in the functioning of mammalian cells and the central nervous system. However, available genetically encoded indicators for BCAAs are based on Förster resonance energy transfer and have a limited dynamic range. We developed a single fluorescent protein-based sensor for BCAAs, called NeIle, which is composed of circularly permutated mNeonGreen protein inserted into the leucine-isoleucine-valine binding protein (LIVBP) from Escherichia coli bacteria. In solution, the NeIle indicator displayed a positive fluorescence response to adding isoleucine, leucine, and valin amino acids with high ΔF/F dynamic ranges of 27-, 19-, and 11-fold and the corresponding affinity values of 5.0, 2.9, and 75 mM, respectively. The spectral and biochemical properties of the NeIle indicator were characterized in solution. We characterized the brightness of the NeIle indicator in living mammalian cells, including cultured neurons. Using the NeIle indicator, we successfully visualized the dynamics of isoleucine transients in different organelles of mammalian cells. We obtained and analyzed the X-ray crystal structure of the NeIle indicator in an isoleucine-bound state. Structure-guided directed mutagenesis of the NeIle indicator revealed the basis of its fluorescence response and selectivity to isoleucine.

Antioxidant properties of α-amino acids: a density functional theory viewpoint

The antioxidant properties of 21 proteinogenic amino acids (AAs) and 3,4-dioxophenylanine (DOPA) have been studied in implicit water using density functional theory (DFT). All the calculations have been performed according to three oxidation mechanisms: (1) hydrogen-atom transfer (HAT); (2) single electron transfer followed by proton transfer (SET-PT); and (3) sequential proton-loss electron transfer (SPLET). As a result, five AAs with the highest antioxidant capacity have been established: DOPA, selenocysteine (Sec), tyrosine (Tyr), cysteine (Cys), and tryptophan (Trp). Also, global reactivity in terms of hardness/softness has been evaluated, as well as Fukui indices of local reactivity. Trp has been determined as the most reactive molecule, whereas selenium atom of Sec has been established as the most reactive atom. All the findings are in agreement with the recent literature on both experimental and theoretical studies of amino acids antioxidant activity. However, to the best of my knowledge, the calculations for one electron redox reactions of zwitterionic amino acids in implicit water have been performed for the first time.

Non-invasive single cell aptasensing in live cells and animals

We report a genetically encoded aptamer biosensor platform for non-invasive measurement of drug distribution in cells and animals. We combined the high specificity of aptamer molecular recognition with the easy-to-detect properties of fluorescent proteins. We generated six encoded aptasensors, showcasing the platform versatility. The biosensors display high sensitivity and specificity for detecting their specific drug target over related analogs. We show dose dependent response of biosensor performance reaching saturating drug uptake levels in individual live cells. We designed our platform for integration into animal genomes; thus, we incorporated aptamer biosensors into zebrafish, an important model vertebrate. The biosensors enabled non-invasive drug biodistribution imaging in whole animals across different timepoints. To our knowledge, this is the first example of an aptamer biosensor-expressing transgenic vertebrate that is carried through generations. As such, our encoded platform addresses the need for non-invasive whole animal biosensing ideal for pharmacokinetic-pharmacodynamic analyses that can be expanded to other organisms and to detect diverse molecules of interest.

The alanyl-tRNA synthetase AARS1 moonlights as a lactyltransferase to promote YAP signaling in gastric cancer

Lactylation has been recently identified as a new type of posttranslational modification occurring widely on lysine residues of both histone and nonhistone proteins. The acetyltransferase p300 is thought to mediate protein lactylation, yet the cellular concentration of the proposed lactyl-donor, lactyl-coenzyme A, is about 1,000 times lower than that of acetyl-CoA, raising the question of whether p300 is a genuine lactyltransferase. Here, we report that alanyl-tRNA synthetase 1 (AARS1) moonlights as a bona fide lactyltransferase that directly uses lactate and ATP to catalyze protein lactylation. Among the candidate substrates, we focused on the Hippo pathway, which has a well-established role in tumorigenesis. Specifically, AARS1 was found to sense intracellular lactate and translocate into the nucleus to lactylate and activate the YAP-TEAD complex; and AARS1 itself was identified as a Hippo target gene that forms a positive-feedback loop with YAP-TEAD to promote gastric cancer (GC) cell proliferation. Consistently, the expression of AARS1 was found to be upregulated in GC, and elevated AARS1 expression was found to be associated with poor prognosis for patients with GC. Collectively, this work found AARS1 with lactyltransferase activity in vitro and in vivo and revealed how the metabolite lactate is translated into a signal of cell proliferation.

A Turn-On Fluorescent Amino Acid Sensor Reveals Chloroquine's Effect on Cellular Amino Acids via Inhibiting Cathepsin L

Maintaining homeostasis of metabolites such as amino acids is critical for cell survival. Dysfunction of nutrient balance can result in human diseases such as diabetes. Much remains to be discovered about how cells transport, store, and utilize amino acids due to limited research tools. Here we developed a novel, pan-amino acid fluorescent turn-on sensor, NS560. It detects 18 of the 20 proteogenic amino acids and can be visualized in mammalian cells. Using NS560, we identified amino acids pools in lysosomes, late endosomes, and surrounding the rough endoplasmic reticulum. Interestingly, we observed amino acid accumulation in large cellular foci after treatment with chloroquine, but not with other autophagy inhibitors. Using a biotinylated photo-cross-linking chloroquine analog and chemical proteomics, we identified Cathepsin L (CTSL) as the chloroquine target leading to the amino acid accumulation phenotype. This study establishes NS560 as a useful tool to study amino acid regulation, identifies new mechanisms of action of chloroquine, and demonstrates the importance of CTSL regulation of lysosomes.

Genetically encoded biosensors for microbial synthetic biology: From conceptual frameworks to practical applications

Genetically encoded biosensors are the vital components of synthetic biology and metabolic engineering, as they are regarded as powerful devices for the dynamic control of genotype metabolism and evolution/screening of desirable phenotypes. This review summarized the recent advances in the construction and applications of different genetically encoded biosensors, including fluorescent protein-based biosensors, nucleic acid-based biosensors, allosteric transcription factor-based biosensors and two-component system-based biosensors. First, the construction frameworks of these biosensors were outlined. Then, the recent progress of biosensor applications in creating versatile microbial cell factories for the bioproduction of high-value chemicals was summarized. Finally, the challenges and prospects for constructing robust and sophisticated biosensors were discussed. This review provided theoretical guidance for constructing genetically encoded biosensors to create desirable microbial cell factories for sustainable bioproduction.

Electrodetection of Small Molecules by Conformation-Mediated Signal Enhancement

Electrochemical biosensors allow the rapid, selective, and sensitive transduction of critical biological parameters into measurable signals. However, current electrochemical biosensors often fail to selectively and sensitively detect small molecules because of their small size and low molecular complexity. We have developed an electrochemical biosensing platform that harnesses the analyte-dependent conformational change of highly selective solute-binding proteins to amplify the redox signal generated by analyte binding. Using this platform, we constructed and characterized two biosensors that can sense leucine and glycine, respectively. We show that these biosensors can selectively and sensitively detect their targets over a wide range of concentrations-up to 7 orders of magnitude-and that the selectivity of these sensors can be readily altered by switching the bioreceptor's binding domain. Our work represents a new paradigm for the design of a family of modular electrochemical biosensors, where access to electrode surfaces can be controlled by protein conformational changes.

Genetically encoded tools for measuring and manipulating metabolism

Over the past few years, we have seen an explosion of novel genetically encoded tools for measuring and manipulating metabolism in live cells and animals. Here, we will review the genetically encoded tools that are available, describe how these tools can be used and outline areas where future development is needed in this fast-paced field. We will focus on tools for direct measurement and manipulation of metabolites. Metabolites are master regulators of metabolism and physiology through their action on metabolic enzymes, signaling enzymes, ion channels and transcription factors, among others. We hope that this Perspective will encourage more people to use these novel reagents or even join this exciting new field to develop novel tools for measuring and manipulating metabolism.

Noisy metabolism can promote microbial cross-feeding

Cross-feeding, the exchange of nutrients between organisms, is ubiquitous in microbial communities. Despite its importance in natural and engineered microbial systems, our understanding of how inter-species cross-feeding arises is incomplete, with existing theories limited to specific scenarios. Here, we introduce a novel theory for the emergence of such cross-feeding, which we term noise-averaging cooperation (NAC). NAC is based on the idea that, due to their small size, bacteria are prone to noisy regulation of metabolism which limits their growth rate. To compensate, related bacteria can share metabolites with each other to ‘average out’ noise and improve their collective growth. According to the Black Queen Hypothesis, this metabolite sharing among kin, a form of ‘leakage’, then allows for the evolution of metabolic interdependencies among species including de novo speciation via gene deletions. We first characterize NAC in a simple ecological model of cell metabolism, showing that metabolite leakage can in principle substantially increase growth rate in a community context. Next, we develop a generalized framework for estimating the potential benefits of NAC among real bacteria. Using single-cell protein abundance data, we predict that bacteria suffer from substantial noise-driven growth inefficiencies, and may therefore benefit from NAC. We then discuss potential evolutionary pathways for the emergence of NAC. Finally, we review existing evidence for NAC and outline potential experimental approaches to detect NAC in microbial communities.

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."

Biosensor for branched-chain amino acid metabolism in yeast and applications in isobutanol and isopentanol production

Branched-chain amino acid (BCAA) metabolism fulfills numerous physiological roles and can be harnessed to produce valuable chemicals. However, the lack of eukaryotic biosensors specific for BCAA-derived products has limited the ability to develop high-throughput screens for strain engineering and metabolic studies. Here, we harness the transcriptional regulator Leu3p from Saccharomyces cerevisiae to develop a genetically encoded biosensor for BCAA metabolism. In one configuration, we use the biosensor to monitor yeast production of isobutanol, an alcohol derived from valine degradation. Small modifications allow us to redeploy Leu3p in another biosensor configuration that monitors production of the leucine-derived alcohol, isopentanol. These biosensor configurations are effective at isolating high-producing strains and identifying enzymes with enhanced activity from screens for branched-chain higher alcohol (BCHA) biosynthesis in mitochondria as well as cytosol. Furthermore, this biosensor has the potential to assist in metabolic studies involving BCAA pathways, and offers a blueprint to develop biosensors for other products derived from BCAA metabolism.

There are a lack of eukaryotic biosensors specific for branched-chain amino acid (BCAA)-derived products. Here the authors report a genetically encoded biosensor for BCAA metabolism based on the Leu3p transcriptional regulator; they use this to monitor yeast production of isobutanol and isopentanol.

Host and microbiota metabolic signals in aging and longevity

Aging is an inevitable biochemical process that adversely affects personal health and poses ever-increasing challenges to society. Recent research has revealed the crucial role of metabolism in regulating aging and longevity. During diverse metabolic processes, the host organism and their symbiotic partners-the microbiota-produce thousands of chemical products (metabolites). Emerging studies have uncovered specific metabolites that act as signaling molecules to actively regulate longevity. Here we review the latest progress in understanding the molecular mechanisms by which metabolites from the host and/or microbiota promote longevity. We also highlight state-of-the-art technologies for discovering, profiling and imaging aging- and longevity-regulating metabolites and for deciphering the molecular basis of their actions. The broad application of these technologies in aging research, together with future advances, will foster the systematic discovery of aging- and longevity-regulating metabolites and their signaling pathways. These metabolite signals should provide promising targets for developing new interventions to promote longevity and healthy aging.

The Role of Amino Acids in Neurotransmission and Fluorescent Tools for Their Detection

Neurotransmission between neurons, which can occur over the span of a few milliseconds, relies on the controlled release of small molecule neurotransmitters, many of which are amino acids. Fluorescence imaging provides the necessary speed to follow these events and has emerged as a powerful technique for investigating neurotransmission. In this review, we highlight some of the roles of the 20 canonical amino acids, GABA and β-alanine in neurotransmission. We also discuss available fluorescence-based probes for amino acids that have been shown to be compatible for live cell imaging, namely those based on synthetic dyes, nanostructures (quantum dots and nanotubes), and genetically encoded components. We aim to provide tool developers with information that may guide future engineering efforts and tool users with information regarding existing indicators to facilitate studies of amino acid dynamics.