Project description:Neurons utilize glucose to generate adenosine triphosphate (ATP) essential for their survival, excitability and synaptic signaling, as well as initiating changes in neuronal structure and function. Defects in oxidative metabolism and mitochondria functions are also associated with aging and diverse human neurological diseases1-4. While neurons are known to adapt their metabolism to meet the increased energy demands of complex behaviors such as learning and memory, the molecular underpinnings regulating this process remain poorly understood4-6. Here we show that the orphan nuclear receptor estrogen related receptor gamma (ERRγ) becomes highly expressed during retinoic-acid induced neurogenesis and is widely expressed in neuronal nuclei throughout the brain. Mechanistically, we show that ERRγ directly orchestrates the expression of networks of genes involved in mitochondrial oxidative phosphorylation and energy generation in neurons. The importance of this regulation is evidenced by decreased adaptive metabolic capacity in cultured neurons lacking ERRγ, and reduced long-term potentiation (LTP) in ERRγ-/- hippocampal slices. Notably, the defect in LTP was rescued by the metabolic intermediate pyruvate, functionally linking the ERRγ knockout metabolic phenotype and memory formation. Consistent with this notion, mice lacking neuronal ERRγ exhibit defects in spatial learning and memory. These findings implicate ERRγ in the metabolic adaptations required for long-term memory formation. We used microarray analysis to compare the genome-wide gene expression changes between wild type (WT) and ERRγ-/- P0 cerebral cortex as it contains mainly neuronal lineage at this stage compared to adult cortex.
Project description:Neurons utilize glucose to generate adenosine triphosphate (ATP) essential for their survival, excitability and synaptic signaling, as well as initiating changes in neuronal structure and function. Defects in oxidative metabolism and mitochondria functions are also associated with aging and diverse human neurological diseases1-4. While neurons are known to adapt their metabolism to meet the increased energy demands of complex behaviors such as learning and memory, the molecular underpinnings regulating this process remain poorly understood4-6. Here we show that the orphan nuclear receptor estrogen related receptor gamma (ERRγ) becomes highly expressed during retinoic-acid induced neurogenesis and is widely expressed in neuronal nuclei throughout the brain. Mechanistically, we show that ERRγ directly orchestrates the expression of networks of genes involved in mitochondrial oxidative phosphorylation and energy generation in neurons. The importance of this regulation is evidenced by decreased adaptive metabolic capacity in cultured neurons lacking ERRγ, and reduced long-term potentiation (LTP) in ERRγ-/- hippocampal slices. Notably, the defect in LTP was rescued by the metabolic intermediate pyruvate, functionally linking the ERRγ knockout metabolic phenotype and memory formation. Consistent with this notion, mice lacking neuronal ERRγ exhibit defects in spatial learning and memory. These findings implicate ERRγ in the metabolic adaptations required for long-term memory formation. We used ChIP-Seq analysis to determine the genome-wide binding of ERRγ in neurons derived from ES cells.
Project description:Neurons utilize glucose to generate adenosine triphosphate (ATP) essential for their survival, excitability and synaptic signaling, as well as initiating changes in neuronal structure and function. Defects in oxidative metabolism and mitochondria functions are also associated with aging and diverse human neurological diseases1-4. While neurons are known to adapt their metabolism to meet the increased energy demands of complex behaviors such as learning and memory, the molecular underpinnings regulating this process remain poorly understood4-6. Here we show that the orphan nuclear receptor estrogen related receptor gamma (ERRγ) becomes highly expressed during retinoic-acid induced neurogenesis and is widely expressed in neuronal nuclei throughout the brain. Mechanistically, we show that ERRγ directly orchestrates the expression of networks of genes involved in mitochondrial oxidative phosphorylation and energy generation in neurons. The importance of this regulation is evidenced by decreased adaptive metabolic capacity in cultured neurons lacking ERRγ, and reduced long-term potentiation (LTP) in ERRγ-/- hippocampal slices. Notably, the defect in LTP was rescued by the metabolic intermediate pyruvate, functionally linking the ERRγ knockout metabolic phenotype and memory formation. Consistent with this notion, mice lacking neuronal ERRγ exhibit defects in spatial learning and memory. These findings implicate ERRγ in the metabolic adaptations required for long-term memory formation.
Project description:Neurons utilize glucose to generate adenosine triphosphate (ATP) essential for their survival, excitability and synaptic signaling, as well as initiating changes in neuronal structure and function. Defects in oxidative metabolism and mitochondria functions are also associated with aging and diverse human neurological diseases1-4. While neurons are known to adapt their metabolism to meet the increased energy demands of complex behaviors such as learning and memory, the molecular underpinnings regulating this process remain poorly understood4-6. Here we show that the orphan nuclear receptor estrogen related receptor gamma (ERRγ) becomes highly expressed during retinoic-acid induced neurogenesis and is widely expressed in neuronal nuclei throughout the brain. Mechanistically, we show that ERRγ directly orchestrates the expression of networks of genes involved in mitochondrial oxidative phosphorylation and energy generation in neurons. The importance of this regulation is evidenced by decreased adaptive metabolic capacity in cultured neurons lacking ERRγ, and reduced long-term potentiation (LTP) in ERRγ-/- hippocampal slices. Notably, the defect in LTP was rescued by the metabolic intermediate pyruvate, functionally linking the ERRγ knockout metabolic phenotype and memory formation. Consistent with this notion, mice lacking neuronal ERRγ exhibit defects in spatial learning and memory. These findings implicate ERRγ in the metabolic adaptations required for long-term memory formation.
Project description:Intracellular Ca2+ signaling regulates diverse functions of the nervous system. Many of these neuronal functions, including learning and memory, are regulated by neuronal calcium sensor-1 (NCS-1). However, the pathways by which NCS-1 regulates these functions remain poorly understood. Consistent with the findings of previous reports, we revealed that NCS-1 deficient (Ncs1-/-) mice exhibit impaired spatial learning and memory function in the Morris water maze test, although there was little change in their exercise activity, as determined via treadmill-analysis. Expression of brain-derived neurotrophic factor (BDNF; a key regulator of memory function) and dopamine was significantly reduced in the Ncs1-/- mouse brain, without changes in the levels of glial cell-line derived neurotrophic factor or nerve growth factor. Although there were no gross structural abnormalities in the hippocampi of Ncs1-/- mice, electron microscopy analysis revealed that the density of large dense core vesicles in CA1 presynaptic neurons, which release BDNF and dopamine, was decreased. Phosphorylation of Ca2+/calmodulin-dependent protein kinase II-α (CaMKII-α, which is known to trigger long-term potentiation and increase BDNF levels, was significantly reduced in the Ncs1-/- mouse brain. Furthermore, high voltage electric potential stimulation, which increases the levels of BDNF and promotes spatial learning, significantly increased the levels of NCS-1 concomitant with phosphorylated CaMKII-α in the hippocampus; suggesting a close relationship between NCS-1 and CaMKII-α. Our findings indicate that NCS-1 may regulate spatial learning and memory function at least in part through activation of CaMKII-α signaling, which may directly or indirectly increase BDNF production.
Project description:Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.