Advances in Astrocyte Computational Models: From Metabolic Reconstructions to Multi-omic Approaches

Structural and molecular characterization of astrocyte and vasculature connectivity in the mouse hippocampus and cortex

The relation of astrocytic endfeet to the vasculature plays a key functional role in the neuro-glia-vasculature unit. We characterize the spatial organization of astrocytes and the structural aspects that facilitate their involvement in molecular exchanges. Using double transgenic mice, we performed co-immunostaining, confocal microscopy, and three-dimensional digital segmentation to investigate the biophysical and molecular organization of astrocytes and their intricate endfoot network at the micrometer level in the isocortex and hippocampus. The results showed that hippocampal astrocytes had smaller territories, reduced endfoot dimensions, and fewer contacts with blood vessels compared with those in the isocortex. Additionally, we found that both connexins 43 and 30 have a higher density in the endfoot and the former is overexpressed relative to the latter. However, due to the limitations of the method, further studies are needed to determine the exact localization on the endfoot. The quantitative information obtained in this study will be useful for modeling the interactions of astrocytes with the vasculature.

Enzymatic Metabolic Switches of Astrocyte Response to Lipotoxicity as Potential Therapeutic Targets for Nervous System Diseases

Astrocytes play a pivotal role in maintaining brain homeostasis. Recent research has highlighted the significance of palmitic acid (PA) in triggering pro-inflammatory pathways contributing to neurotoxicity. Furthermore, Genomic-scale metabolic models and control theory have revealed that metabolic switches (MSs) are metabolic pathway regulators by potentially exacerbating neurotoxicity, thereby offering promising therapeutic targets. Herein, we characterized these enzymatic MSs in silico as potential therapeutic targets, employing protein-protein and drug-protein interaction networks alongside structural characterization techniques. Our findings indicate that five MSs (P00558, P04406, Q08426, P09110, and O76062) were functionally linked to nervous system drug targets and may be indirectly regulated by specific neurological drugs, some of which exhibit polypharmacological potential (e.g., Trifluperidol, Trifluoperazine, Disulfiram, and Haloperidol). Furthermore, four MSs (P00558, P04406, Q08426, and P09110) feature ligand-binding or allosteric cavities with druggable potential. Our results advocate for a focused exploration of P00558 (phosphoglycerate kinase 1), P04406 (glyceraldehyde-3-phosphate dehydrogenase), Q08426 (peroxisomal bifunctional enzyme, enoyl-CoA hydratase, and 3-hydroxyacyl CoA dehydrogenase), P09110 (peroxisomal 3-ketoacyl-CoA thiolase), and O76062 (Delta(14)-sterol reductase) as promising targets for the development or repurposing of pharmacological compounds, which could have the potential to modulate lipotoxic-altered metabolic pathways, offering new avenues for the treatment of related human diseases such as neurological diseases.

Astrocytes: new evidence, new models, new roles

Astrocytes have been in the limelight of active research for about 3 decades now. Over this period, ideas about their function and role in the nervous system have evolved from simple assistance in energy supply and homeostasis maintenance to a complex informational and metabolic hub that integrates data on local neuronal activity, sensory and arousal context, and orchestrates many crucial processes in the brain. Rapid progress in experimental techniques and data analysis produces a growing body of data, which can be used as a foundation for formulation of new hypotheses, building new refined mathematical models, and ultimately should lead to a new level of understanding of the contribution of astrocytes to the cognitive tasks performed by the brain. Here, we highlight recent progress in astrocyte research, which we believe expands our understanding of how low-level signaling at a cellular level builds up to processes at the level of the whole brain and animal behavior. We start our review with revisiting data on the role of noradrenaline-mediated astrocytic signaling in locomotion, arousal, sensory integration, memory, and sleep. We then briefly review astrocyte contribution to the regulation of cerebral blood flow regulation, which is followed by a discussion of biophysical mechanisms underlying astrocyte effects on different brain processes. The experimental section is closed by an overview of recent experimental techniques available for modulation and visualization of astrocyte dynamics. We then evaluate how the new data can be potentially incorporated into the new mathematical models or where and how it already has been done. Finally, we discuss an interesting prospect that astrocytes may be key players in important processes such as the switching between sleep and wakefulness and the removal of toxic metabolites from the brain milieu.

Parameter Inference for an Astrocyte Model using Machine Learning Approaches

Astrocytes are the largest subset of glial cells and perform structural, metabolic, and regulatory functions. They are directly involved in the communication at neuronal synapses and the maintenance of brain homeostasis. Several disorders, such as Alzheimer's, epilepsy, and schizophrenia, have been associated with astrocyte dysfunction. Computational models on various spatial levels have been proposed to aid in the understanding and research of astrocytes. The difficulty of computational astrocyte models is to fastly and precisely infer parameters. Physics informed neural networks (PINNs) use the underlying physics to infer parameters and, if necessary, dynamics that can not be observed. We have applied PINNs to estimate parameters for a computational model of an astrocytic compartment. The addition of two techniques helped with the gradient pathologies of the PINNS, the dynamic weighting of various loss components and the addition of Transformers. To overcome the issue that the neural network only learned the time dependence but did not know about eventual changes of the input stimulation to the astrocyte model, we followed an adaptation of PINNs from control theory (PINCs). In the end, we were able to infer parameters from artificial, noisy data, with stable results for the computational astrocyte model.

Analysis of Network Models with Neuron-Astrocyte Interactions

Neural networks, composed of many neurons and governed by complex interactions between them, are a widely accepted formalism for modeling and exploring global dynamics and emergent properties in brain systems. In the past decades, experimental evidence of computationally relevant neuron-astrocyte interactions, as well as the astrocytic modulation of global neural dynamics, have accumulated. These findings motivated advances in computational glioscience and inspired several models integrating mechanisms of neuron-astrocyte interactions into the standard neural network formalism. These models were developed to study, for example, synchronization, information transfer, synaptic plasticity, and hyperexcitability, as well as classification tasks and hardware implementations. We here focus on network models of at least two neurons interacting bidirectionally with at least two astrocytes that include explicitly modeled astrocytic calcium dynamics. In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to better integrate them in data-driven computational models. Broadening the discussion about theoretical approaches and expanding the computational tools is necessary to better understand astrocytes' roles in brain functions.

In silico analysis of metabolic effects of bipolar disorder on prefrontal cortex identified altered GABA, glutamate-glutamine cycle, energy metabolism and amino acid synthesis pathways

Bipolar disorder (BP) is a lifelong psychiatric condition, which often disrupts the daily life of the patients. It is characterized by unstable and periodic mood changes, which cause patients to display unusual shifts in mood, energy, activity levels, concentration and the ability to carry out day-to-day tasks. BP is a major psychiatric condition, and it is still undertreated. The causes and neural mechanisms of bipolar disorder are unclear, and diagnosis is still mostly based on psychiatric examination, furthermore the unstable character of the disorder makes diagnosis challenging. Identification of the molecular mechanisms underlying the disease may improve the diagnosis and treatment rates. Single nucleotide polymorphisms (SNP) and transcriptome profiles of patients were studied along with signalling pathways that are thought to be associated with bipolar disorder. Here, we present a computational approach that uses publicly available transcriptome data from bipolar disorder patients and healthy controls. Along with statistical analyses, data are integrated with a genome-scale metabolic model and protein-protein interaction network. Healthy individuals and bipolar disorder patients are compared based on their metabolic profiles. We hypothesize that energy metabolism alterations in bipolar disorder relate to perturbations in amino-acid metabolism and neuron-astrocyte exchange reactions. Due to changes in amino acid metabolism, neurotransmitters and their secretion from neurons and metabolic exchange pathways between neurons and astrocytes such as the glutamine-glutamate cycle are also altered. Changes in negatively charged (-1) KIV and KMV molecules are also observed, and it indicates that charge balance in the brain is highly altered in bipolar disorder. Due to this fact, we also hypothesize that positively charged lithium ions may stabilize the disturbed charge balance in neurons in addition to its effects on neurotransmission. To the best of our knowledge, our approach is unique as it is the first study using genome-scale metabolic models in neuropsychiatric research.

Astrocytic Glutamatergic Transmission and Its Implications in Neurodegenerative Disorders

Several neurodegenerative disorders involve impaired neurotransmission, and glutamatergic neurotransmission sets a prototypical example. Glutamate is a predominant excitatory neurotransmitter where the astrocytes play a pivotal role in maintaining the extracellular levels through release and uptake mechanisms. Astrocytes modulate calcium-mediated excitability and release several neurotransmitters and neuromodulators, including glutamate, and significantly modulate neurotransmission. Accumulating evidence supports the concept of excitotoxicity caused by astrocytic glutamatergic release in pathological conditions. Thus, the current review highlights different vesicular and non-vesicular mechanisms of astrocytic glutamate release and their implication in neurodegenerative diseases. As in presynaptic neurons, the vesicular release of astrocytic glutamate is also primarily meditated by calcium-mediated exocytosis. V-ATPase is crucial in the acidification and maintenance of the gradient that facilitates the vesicular storage of glutamate. Along with these, several other components, such as cystine/glutamate antiporter, hemichannels, BEST-1, TREK-1, purinergic receptors and so forth, also contribute to glutamate release under physiological and pathological conditions. Events of hampered glutamate uptake could promote inflamed astrocytes to trigger repetitive release of glutamate. This could be favorable towards the development and worsening of neurodegenerative diseases. Therefore, across neurodegenerative diseases, we review the relations between defective glutamatergic signaling and astrocytic vesicular and non-vesicular events in glutamate homeostasis. The optimum regulation of astrocytic glutamatergic transmission could pave the way for the management of these diseases and add to their therapeutic value.

Negative regulation of melatonin secretion by melatonin receptors in ovine pinealocytes

Melatonin (MLT) is a biological modulator of circadian and seasonal rhythms and reproduction. The photoperiodic information is detected by retinal photoreceptors and transmitted through nerve transmissions to the pineal gland, where MLT is synthesized and secreted at night into the blood. MLT interacts with two G protein-coupled receptors, MT1 and MT2. The aim of our work was to provide evidence for the presence of MLT receptors in the ovine pineal gland and define their involvement on melatonin secretion. For the first time, we identified the expression of MLT receptors with the specific 2-[125I]-MLT agonistic radioligand in ovin pinealocytes. The values of Kd and Bmax are 2.24 ± 1.1 nM and 20 ± 6.8 fmol/mg. MLT receptors are functional and inhibit cAMP production and activate ERK1/2 through pertussis toxin-sensitive Gi/o proteins. The MLT receptor antagonist/ inverse agonist luzindole increased cAMP production (189 ± 30%) and MLT secretion (866 ± 13%). The effect of luzindole on MLT secretion was additive with the effect of well-described activators of this pathway such as the β-adrenergic agonist isoproterenol and the α-adrenergic agonist phenylephrine. Co-incubation of all three compounds increased MLT secretion by 1236 ± 199%. These results suggest that MLT receptors are involved in the negative regulation of the synthesis of its own ligand in pinealocytes. While adrenergic receptors promote MLT secretion, MLT receptors mitigate this effect to limit the quantity of MLT secreted by the pineal gland.