Neuronal energy use and brain evolution

Fine-Tuning Ferroptosis by Modulating GPX4 and Its Potential in Mitigating Neuronal Degeneration in Parkinson's Disease

The increasing prevalence of neurodegenerative diseases necessitates the development of novel approaches to study, diagnose, and treat these devastating disorders. Accordingly, there is a critical need to precisely address the gap in the biochemical and physiological mechanisms that underlie neurodegenerative diseases to promote advancements in therapeutic interventions. Parkinson's Disease (PD), the second most common neurodegenerative disorder after Alzheimer's, demands further research focused on unravelling the rather intricate molecular mechanisms that drive its progression upon different cell signaling cues. While alpha-synuclein aggregation and mitochondrial dysfunction are two cellular hallmarks of the molecular pathophysiology of PD, few drugs are currently in clinical trials for treatment of PD, which warrants further studies to identify new therapeutic molecular targets. Herein, we briefly highlight some of the reported roles of ferroptosis, a modality of cell death that is driven by iron-dependent phospholipid peroxidation, and its regulation by glutathione peroxidase 4 (GPX4). We discuss the interconnectedness between lipid peroxidation and GPX4 regulation in the context of molecular pathogenesis of PD.  Future studies are imperative in investigating the physiological role of ferroptosis and the translational impact of ferroptosis-specific modulators in studying PD biology.

Amyotrophic lateral sclerosis represents corticomotoneuronal system failure

Several decades have passed since the anterograde corticomotoneuronal hypothesis for amyotrophic lateral sclerosis (ALS) was proposed. The intervening years have witnessed its emergent support based on anatomical, pathological, physiological, neuroimaging, and molecular biological studies. The evolution of an extensive corticomotoneuronal system appears restricted to the human species, with ALS representing a uniquely human disease. While some, very select non-human primates have limited corticomotoneuronal projections, these tend to be absent in all other animals. From a general perspective, the early clinical features of ALS may be considered to reflect failure of the corticomotoneuronal system. The characteristic loss of skilled motor dexterity involving the limbs, and speech impairment through progressive bulbar dysfunction specifically involve those motor units having the strongest corticomotoneuronal projections. A similar explanation likely underlies the unique "split phenotypes" that have now been well characterized in ALS. Large Betz cells and other pyramidal corticomotoneuronal projecting neurons, with their extensive dendritic arborization, are particularly vulnerable to the elements of the ALS exposome such as aging, environmental stress and lifestyle changes. Progressive failure of the proteosome impairs nucleocytoplasmic shuffling and induces toxic but soluble TDP-43 to aggregate in corticomotoneurons. Betz cell failure is further accentuated through dysfunction of its profuse dendritic arborizations. Clarification of system specific genomes and neural networks will likely promote the initiation of precision medicine approaches directed to support the key structure that underlies the neurological manifestations of ALS, the corticomotoneuronal system.

Energetic diversity in retinal ganglion cells is modulated by neuronal activity and correlates with resilience to degeneration

Neuronal function requires high energy expenditure that is likely customized to meet specific signaling demands. However, little is known about diversity of metabolic homeostasis among divergently-functioning types of neurons. To this end, we examined retinal ganglion cells (RGCs), a population of closely related, yet electrophysiologically distinct excitatory projection neurons. Using in vivo 2-photon imaging to measure ATP with single cell resolution, we identified differential homeostatic energy maintenance in the RGC population that correspond to distinct RGC types. In the presence of circuit activity, the most active RGC type (Alpha RGCs), had lower homeostatic ATP levels than other types and exhibited the greatest magnitude of ATP decline when ATP synthesis was inhibited. By simultaneously manipulating circuit activity and mitochondrial function, we found that while oxidative phosphorylation was required to meet ATP demands during circuit activity, it was expendable to maintain resting ATP levels. We also examined ATP signatures associated with survival and injury response after axotomy and report a correlation between low homeostatic ATP and increased survival. In addition, we observed transient ATP increases in RGCs following axon injury. Together, these findings identify diversity of energy handling capabilities of dynamically active neurons with implications for neuronal resilience.

The metabolic costs of cognition

Cognition and behavior are emergent properties of brain systems that seek to maximize complex and adaptive behaviors while minimizing energy utilization. Different species reconcile this trade-off in different ways, but in humans the outcome is biased towards complex behaviors and hence relatively high energy use. However, even in energy-intensive brains, numerous parsimonious processes operate to optimize energy use. We review how this balance manifests in both homeostatic processes and task-associated cognition. We also consider the perturbations and disruptions of metabolism in neurocognitive diseases.

A framework for optimal control of oscillations and synchrony applied to non-linear models of neural population dynamics

We adapt non-linear optimal control theory (OCT) to control oscillations and network synchrony and apply it to models of neural population dynamics. OCT is a mathematical framework to compute an efficient stimulation for dynamical systems. In its standard formulation, it requires a well-defined reference trajectory as target state. This requirement, however, may be overly restrictive for oscillatory targets, where the exact trajectory shape might not be relevant. To overcome this limitation, we introduce three alternative cost functionals to target oscillations and synchrony without specification of a reference trajectory. We successfully apply these cost functionals to single-node and network models of neural populations, in which each node is described by either the Wilson-Cowan model or a biophysically realistic high-dimensional mean-field model of exponential integrate-and-fire neurons. We compute efficient control strategies for four different control tasks. First, we drive oscillations from a stable stationary state at a particular frequency. Second, we switch between stationary and oscillatory stable states and find a translational invariance of the state-switching control signals. Third, we switch between in-phase and out-of-phase oscillations in a two-node network, where all cost functionals lead to identical OC signals in the minimum-energy limit. Finally, we (de-) synchronize an (a-) synchronously oscillating six-node network. In this setup, for the desynchronization task, we find very different control strategies for the three cost functionals. The suggested methods represent a toolbox that enables to include oscillatory phenomena into the framework of non-linear OCT without specification of an exact reference trajectory. However, task-specific adjustments of the optimization parameters have to be performed to obtain informative results.

Neural Processing without O2 and Glucose Delivery: Lessons from the Pond to the Clinic

Neuronal activity requires a large amount of ATP, leading to a rapid collapse of brain function when aerobic respiration fails. Here, we summarize how rhythmic motor circuits in the brain stem of adult frogs, which normally have high metabolic demands, transform to produce proper output during severe hypoxia associated with emergence from hibernation. We suggest that general principles underlying plasticity in brain bioenergetics may be uncovered by studying nonmammalian models that face extreme environments, yielding new insights to combat neurological disorders involving dysfunctional energy metabolism.

Monitoring of activity-driven trafficking of endogenous synaptic proteins through proximity labeling

To enable transmission of information in the brain, synaptic vesicles fuse to presynaptic membranes, liberating their content and exposing transiently a myriad of vesicular transmembrane proteins. However, versatile methods for quantifying the synaptic translocation of endogenous proteins during neuronal activity remain unavailable, as the fast dynamics of synaptic vesicle cycling difficult specific isolation of trafficking proteins during such a transient surface exposure. Here, we developed a novel approach using synaptic cleft proximity labeling to capture and quantify activity-driven trafficking of endogenous synaptic proteins at the synapse. We show that accelerating cleft biotinylation times to match the fast dynamics of vesicle exocytosis allows capturing endogenous proteins transiently exposed at the synaptic surface during neural activity, enabling for the first time the study of the translocation of nearly every endogenous synaptic protein. As proof-of-concept, we further applied this technology to obtain direct evidence of the surface translocation of noncanonical trafficking proteins, such as ATG9A and NPTX1, which had been proposed to traffic during activity but for which direct proof had not yet been shown. The technological advancement presented here will facilitate future studies dissecting the molecular identity of proteins exocytosed at the synapse during activity, helping to define the molecular machinery that sustains neurotransmission in the mammalian brain.

Essential Role of Astrocytes in Learning and Memory

One of the most biologically relevant functions of astrocytes within the CNS is the regulation of synaptic transmission, i.e., the physiological basis for information transmission between neurons. Changes in the strength of synaptic connections are indeed thought to be the cellular basis of learning and memory. Importantly, astrocytes have been demonstrated to tightly regulate these processes via the release of several gliotransmitters linked to astrocytic calcium activity as well as astrocyte-neuron metabolic coupling. Therefore, astrocytes seem to be integrators of and actors upon learning- and memory-relevant information. In this review, we focus on the role of astrocytes in learning and memory processes. We delineate the recognized inputs and outputs of astrocytes and explore the influence of manipulating astrocytes on behaviour across diverse learning paradigms. We conclude that astrocytes influence learning and memory in various manners. Appropriate astrocytic Ca2+ dynamics are being increasingly identified as central contributors to memory formation and retrieval. In addition, astrocytes regulate brain rhythms essential for cognition, and astrocyte-neuron metabolic cooperation is required for memory consolidation.

Orchestrating Blood Flow in the Retina: Interpericyte Tunnelling Nanotube Communication

The retina transforms light into electrical signals, which are sent to the brain via the optic nerve to form our visual perception. This complex signal processing is performed by the retinal neuron and requires a significant amount of energy. Since neurons are unable to store energy, they must obtain glucose and oxygen from the bloodstream to produce energy to match metabolic needs. This process is called neurovascular coupling (NVC), and it is based on a precise mechanism that is not totally understood. The discovery of fine tubular processes termed tunnelling nanotubes (TNTs) set a new type of cell-to-cell communication. TNTs are extensions of the cellular membrane that allow the transfer of material between connected cells. Recently, they have been reported in the brain and retina of living mice, where they connect pericytes, which are vascular mural cells that regulate vessel diameter. Accordingly, these TNTs were termed interpericyte tunnelling nanotubes (IPTNTs), which showed a vital role in blood delivery and NVC. In this chapter, we review the involvement of TNTs in NVC and discuss their implications in retinal neurodegeneration.

Plasticity in the functional properties of NMDA receptors improves network stability during severe energy stress

Brain energy stress leads to neuronal hyperexcitability followed by a rapid loss of function and cell death. In contrast, the frog brainstem switches into a state of extreme metabolic resilience that allows them to maintain motor function during hypoxia as they emerge from hibernation. NMDA receptors (NMDARs) are Ca2+-permeable glutamate receptors that contribute to the loss of homeostasis during hypoxia. Therefore, we hypothesized that hibernation leads to plasticity that reduces the role of NMDARs within neural networks to improve function during energy stress. To test this, we assessed a circuit with a large involvement of NMDAR synapses, the brainstem respiratory network of female bullfrogs, Lithobates catesbeianus. Contrary to our expectations, hibernation did not alter the role of NMDARs in generating network output, nor did it affect the amplitude, kinetics, and hypoxia sensitivity of NMDAR currents. Instead, hibernation strongly reduced NMDAR Ca2+ permeability and enhanced desensitization during repetitive stimulation. Under severe hypoxia, the normal NMDAR profile caused network hyperexcitability within minutes, which was mitigated by blocking NMDARs. After hibernation, the modified complement of NMDARs protected against hyperexcitability, as disordered output did not occur for at least one hour in hypoxia. These findings uncover state-dependence in the plasticity of NMDARs, whereby multiple changes to receptor function improve neural performance during energy stress without interfering with its normal role during healthy activity.

Synaptic modifications transform neural networks to function without oxygen

BACKGROUND

Neural circuit function is highly sensitive to energetic limitations. Much like mammals, brain activity in American bullfrogs quickly fails in hypoxia. However, after emergence from overwintering, circuits transform to function for approximately 30-fold longer without oxygen using only anaerobic glycolysis for fuel, a unique trait among vertebrates considering the high cost of network activity. Here, we assessed neuronal functions that normally limit network output and identified components that undergo energetic plasticity to increase robustness in hypoxia.

RESULTS

In control animals, oxygen deprivation depressed excitatory synaptic drive within native circuits, which decreased postsynaptic firing to cause network failure within minutes. Assessments of evoked and spontaneous synaptic transmission showed that hypoxia impairs synaptic communication at pre- and postsynaptic loci. However, control neurons maintained membrane potentials and a capacity for firing during hypoxia, indicating that those processes do not limit network activity. After overwintering, synaptic transmission persisted in hypoxia to sustain motor function for at least 2 h.

CONCLUSIONS

Alterations that allow anaerobic metabolism to fuel synapses are critical for transforming a circuit to function without oxygen. Data from many vertebrate species indicate that anaerobic glycolysis cannot fuel active synapses due to the low ATP yield of this pathway. Thus, our results point to a unique strategy whereby synapses switch from oxidative to exclusively anaerobic glycolytic metabolism to preserve circuit function during prolonged energy limitations.

Astrocyte strategies in the energy-efficient brain

Astrocytes generate ATP through glycolysis and mitochondrion respiration, using glucose, lactate, fatty acids, amino acids, and ketone bodies as metabolic fuels. Astrocytic mitochondria also participate in neuronal redox homeostasis and neurotransmitter recycling. In this essay, we aim to integrate the multifaceted evidence about astrocyte bioenergetics at the cellular and systems levels, with a focus on mitochondrial oxidation. At the cellular level, the use of fatty acid β-oxidation and the existence of molecular switches for the selection of metabolic mode and fuels are examined. At the systems level, we discuss energy audits of astrocytes and how astrocytic Ca2+ signaling might contribute to the higher performance and lower energy consumption of the brain as compared to engineered circuits. We finish by examining the neural-circuit dysregulation and behavior impairment associated with alterations of astrocytic mitochondria. We conclude that astrocytes may contribute to brain energy efficiency by coupling energy, redox, and computational homeostasis in neural circuits.

Energy efficiency as a normative account for predictive coding

In this issue of Patterns, Ali et al. demonstrate that predictive coding emerges in an artificial neural network optimized to be energy efficient. The results offer an explanation for why brains may implement predictive coding.

Waste not, want not

When faced with limited resources, organisms evolve ways to conserve. In this editorial, Martin introduces a special issue devoted to economies in biology and highlights key issues, including some interesting examples of conservation and how fixed resource budgets force tradeoffs in life history traits.