Local and dynamic regulation of neuronal glycolysis in vivo.

Energy metabolism supports neuronal function. While it is well established that changes in energy metabolism underpin brain plasticity and function, less is known about how individual neurons modulate their metabolic states to meet varying energy demands. This is because most approaches used to examine metabolism in living organisms lack the resolution to visualize energy metabolism within individual circuits, cells, or subcellular regions. Here, we adapted a biosensor for glycolysis, HYlight, for use in Caenorhabditis elegans to image dynamic changes in glycolysis within individual neurons and in vivo. We determined that neurons cell-autonomously perform glycolysis and modulate glycolytic states upon energy stress. By examining glycolysis in specific neurons, we documented a neuronal energy landscape comprising three general observations: 1) glycolytic states in neurons are diverse across individual cell types; 2) for a given condition, glycolytic states within individual neurons are reproducible across animals; and 3) for varying conditions of energy stress, glycolytic states are plastic and adapt to energy demands. Through genetic analyses, we uncovered roles for regulatory enzymes and mitochondrial localization in the cellular and subcellular dynamic regulation of glycolysis. Our study demonstrates the use of a single-cell glycolytic biosensor to examine how energy metabolism is distributed across cells and coupled to dynamic states of neuronal function and uncovers unique relationships between neuronal identities and metabolic landscapes in vivo.

Local and dynamic regulation of neuronal glycolysis in vivo.

Energy metabolism supports neuronal function. While it is well established that changes in energy metabolism underpin brain plasticity and function, less is known about how individual neurons modulate their metabolic states to meet varying energy demands. This is because most approaches used to examine metabolism in living organisms lack the resolution to visualize energy metabolism within individual circuits, cells, or subcellular regions. Here we adapted a biosensor for glycolysis, HYlight, for use in C. elegans to image dynamic changes in glycolysis within individual neurons and in vivo. We determined that neurons perform glycolysis cell-autonomously, and modulate glycolytic states upon energy stress. By examining glycolysis in specific neurons, we documented a neuronal energy landscape comprising three general observations: 1) glycolytic states in neurons are diverse across individual cell types; 2) for a given condition, glycolytic states within individual neurons are reproducible across animals; and 3) for varying conditions of energy stress, glycolytic states are plastic and adapt to energy demands. Through genetic analyses, we uncovered roles for regulatory enzymes and mitochondrial localization in the cellular and subcellular dynamic regulation of glycolysis. Our study demonstrates the use of a single-cell glycolytic biosensor to examine how energy metabolism is distributed across cells and coupled to dynamic states of neuronal function, and uncovers new relationships between neuronal identities and metabolic landscapes in vivo.

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 ß-cell glycolytic heterogeneity and dynamics.

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.

Pharmacological bypass of NAD+ salvage pathway protects neurons from chemotherapy-induced degeneration.

Axon degeneration, a hallmark of chemotherapy-induced peripheral neuropathy (CIPN), is thought to be caused by a loss of the essential metabolite nicotinamide adenine dinucleotide (NAD+) via the prodegenerative protein SARM1. Some studies challenge this notion, however, and suggest that an aberrant increase in a direct precursor of NAD+, nicotinamide mononucleotide (NMN), rather than loss of NAD+, is responsible. In support of this idea, blocking NMN accumulation in neurons by expressing a bacterial NMN deamidase protected axons from degeneration. We hypothesized that protection could similarly be achieved by reducing NMN production pharmacologically. To achieve this, we took advantage of an alternative pathway for NAD+ generation that goes through the intermediate nicotinic acid mononucleotide (NAMN), rather than NMN. We discovered that nicotinic acid riboside (NAR), a precursor of NAMN, administered in combination with FK866, an inhibitor of the enzyme nicotinamide phosphoribosyltransferase that produces NMN, protected dorsal root ganglion (DRG) axons against vincristine-induced degeneration as well as NMN deamidase. Introducing a different bacterial enzyme that converts NAMN to NMN reversed this protection. Collectively, our data indicate that maintaining NAD+ is not sufficient to protect DRG neurons from vincristine-induced axon degeneration, and elevating NMN, by itself, is not sufficient to cause degeneration. Nonetheless, the combination of FK866 and NAR, which bypasses NMN formation, may provide a therapeutic strategy for neuroprotection.