Brain-Type Glycogen Phosphorylase Is Crucial for Astrocytic Glycogen Accumulation in Chronic Social Defeat Stress-Induced Depression in Mice

A comprehensive analysis of the differential expression in the hippocampus of depression induced by gut microbiota compared to traditional stress

Depression, which is a disease of heterogeneous etiology, is characterized by high disability and mortality rates. Gut microbiota are associated with the development of depression. To further explore any differences in the mechanisms of depression induced by gut microbiota and traditional stresses, as well as facilitate the development of microbiota-based interventions, a fecal microbiota transplantation (FMT) depression model was made. This was achieved by transplanting feces from major depressive disorder (MDD) patients into germ-free mice. Second, the mechanisms of the depression induced by gut microbiota were analyzed in comparison with those of the depression caused by different forms of stress. It turned out that mice exhibited depressive-like behavior after FMT. Then, PCR array analysis was performed on the hippocampus of the depressed mice to identify differentially expressed genes (DEGs). The KEGG analysis revealed that the pathways of depression induced by gut microbes are closely associated with immuno-inflammation. To determine the pathogenic pathways of physiological stress and psychological stress-induced depression, raw data was extracted from several databases and KEGG analysis was performed. The results from the analysis revealed that the mechanisms of depression induced by physiological and psychological stress are closely related to the regulation of neurotransmitters and energy metabolism. Interestingly, the immunoinflammatory response was distinct across different etiologies that induced depression. The findings showed that gut microbiota dysbiosis-induced depression was mainly associated with adaptive immunity, while physiological stress-induced depression was more linked to innate immunity. This study compared the pathogenesis of depression caused by gut microbiota dysbiosis, and physiological and psychological stress. We explored new intervention methods for depression and laid the foundation for precise treatment.

Brain-Type Glycogen Phosphorylase (PYGB) in the Pathologies of Diseases: A Systematic Review

Glycogen metabolism is a form of crucial metabolic reprogramming in cells. PYGB, the brain-type glycogen phosphorylase (GP), serves as the rate-limiting enzyme of glycogen catabolism. Evidence is mounting for the association of PYGB with diverse human diseases. This review covers the advancements in PYGB research across a range of diseases, including cancer, cardiovascular diseases, metabolic diseases, nervous system diseases, and other diseases, providing a succinct overview of how PYGB functions as a critical factor in both physiological and pathological processes. We present the latest progress in PYGB in the diagnosis and treatment of various diseases and discuss the current limitations and future prospects of this novel and promising target.

Sex-Dimorphic Glucocorticoid Receptor Regulation of Hypothalamic Primary Astrocyte Glycogen Metabolism: Interaction with Norepinephrine

Astrocyte glycogen is a critical metabolic variable that impacts hypothalamic control of glucostasis. Glucocorticoid hormones regulate peripheral glycogen, but their effects on hypothalamic glycogen are not known. A hypothalamic astrocyte primary culture model was used to investigate the premise that glucocorticoids impose sex-dimorphic independent and interactive control of glycogen metabolic enzyme protein expression and glycogen accumulation. The glucocorticoid receptor (GR) agonist dexamethasone (DEX) down-regulated glycogen synthase (GS), glycogen phosphorylase (GP)-brain type (GPbb), and GP-muscle type (GPmm) proteins in glucose-supplied male astrocytes, but enhanced these profiles in female. The catecholamine neurotransmitter norepinephrine (NE) did not alter these proteins, but amplified DEX inhibition of GS and GPbb in male or abolished GR stimulation of GPmm in female. In both sexes, DEX and NE individually increased glycogen content, but DEX attenuated the magnitude of noradrenergic stimulation. Glucoprivation suppressed GS, GPbb, and GPmm in male, but not female astrocytes, and elevated or diminished glycogen in these sexes, respectively. Glucose-deprived astrocytes exhibit GR-dependent induced glycogen accumulation in both sexes, and corresponding loss (male) or attenuation (female) of noradrenergic-dependent glycogen build-up. Current evidence for GR augmentation of hypothalamic astrocyte glycogen content in each sex, yet divergent effects on glycogen enzyme proteins infers that glucocorticoids may elicit opposite adjustments in glycogen turnover in each sex. Results document GR modulation of NE stimulation of glycogen accumulation in the presence (male and female) or absence (female) of glucose. Outcomes provide novel proof that astrocyte energy status influences the magnitude of GR and NE signal effects on glycogen mass.

Behavioral state-dependent oscillatory activity in prefrontal cortex induced by chronic social defeat stress

Chronic stress contributes to the onset and exacerbation of major depressive disorder (MDD) through the oscillatory activity in the prefrontal cortex (PFC). However, the oscillations on which chronic social stress converges to yield the behavioral state of social avoidance are largely unknown. Here, we use a chronic social defeat stress model and in vivo electrophysiological recordings to uncover a novel neurophysiological measure that predicts the social behavioral state in stressed animals. First, in this study, we find that chronic social defeat stress model induces depression-like behaviors (anhedonia and social avoidance). Second, we find statistically significant differences in PFC oscillatory activity across different frequency ranges in social behavioral state, and the oscillatory activity correlates with stress-induced behavioral state. Finally, we show that the social behavioral states are accurately decoded from the oscillatory activity based on machine learning. Together, these results demonstrate that naturally occurring differences in PFC oscillation underlie the social behavioral state that accompanies the emergence of stress-induced behavioral dysfunction.