GABA Metabolism and Transport: Effects on Synaptic Efficacy

GABAergic inhibition is an important regulator of excitability in neuronal networks. In addition, inhibitory synaptic signals contribute crucially to the organization of spatiotemporal patterns of network activity, especially during coherent oscillations. In order to maintain stable network states, the release of GABA by interneurons must be plastic in timing and amount. This homeostatic regulation is achieved by several pre- and postsynaptic mechanisms and is triggered by various activity-dependent local signals such as excitatory input or ambient levels of neurotransmitters. Here, we review findings on the availability of GABA for release at presynaptic terminals of interneurons. Presynaptic GABA content seems to be an important determinant of inhibitory efficacy and can be differentially regulated by changing synthesis, transport, and degradation of GABA or related molecules. We will discuss the functional impact of such regulations on neuronal network patterns and, finally, point towards pharmacological approaches targeting these processes

GABA Metabolism and Transport: Effects on Synaptic Efficacy

GABAergic inhibition is an important regulator of excitability in neuronal networks. In addition, inhibitory synaptic signals contribute crucially to the organization of spatiotemporal patterns of network activity, especially during coherent oscillations. In order to maintain stable network states, the release of GABA by interneurons must be plastic in timing and amount. This homeostatic regulation is achieved by several pre-and postsynaptic mechanisms and is triggered by various activity-dependent local signals such as excitatory input or ambient levels of neurotransmitters. Here, we review findings on the availability of GABA for release at presynaptic terminals of interneurons. Presynaptic GABA content seems to be an important determinant of inhibitory efficacy and can be differentially regulated by changing synthesis, transport, and degradation of GABA or related molecules. We will discuss the functional impact of such regulations on neuronal network patterns and, finally, point towards pharmacological approaches targeting these processes

Subtype-specific differentiation of cardiac pacemaker cell clusters from human induced pluripotent stem cells

Background: Human induced pluripotent stem cells (hiPSC) harbor the potential to differentiate into diverse cardiac cell types. Previous experimental efforts were primarily directed at the generation of hiPSC-derived cells with ventricular cardiomyocyte characteristics. Aiming at a straightforward approach for pacemaker cell modeling and replacement, we sought to selectively differentiate cells with nodal-type properties. Methods: hiPSC were differentiated into spontaneously beating clusters by co-culturing with visceral endoderm-like cells in a serum-free medium. Subsequent culturing in a specified fetal bovine serum (FBS)-enriched cell medium produced a pacemaker-type phenotype that was studied in detail using quantitative real-time polymerase chain reaction (qRT-PCR), immunocytochemistry, and patch-clamp electrophysiology. Further investigations comprised pharmacological stimulations and co-culturing with neonatal cardiomyocytes. Results: hiPSC co-cultured in a serum-free medium with the visceral endoderm-like cell line END-2 produced spontaneously beating clusters after 10–12 days of culture. The pacemaker-specific genes HCN4, TBX3, and TBX18 were abundantly expressed at this early developmental stage, while levels of sarcomeric gene products remained low. We observed that working-type cardiomyogenic differentiation can be suppressed by transfer of early clusters into a FBS-enriched cell medium immediately after beating onset. After 6 weeks under these conditions, sinoatrial node (SAN) hallmark genes remained at high levels, while working-type myocardial transcripts (NKX2.5, TBX5) were low. Clusters were characterized by regular activity and robust beating rates (70–90 beats/min) and were triggered by spontaneous Ca2+ transients recapitulating calcium clock properties of genuine pacemaker cells. They were responsive to adrenergic/cholinergic stimulation and able to pace neonatal rat ventricular myocytes in co-culture experiments. Action potential (AP) measurements of cells individualized from clusters exhibited nodal-type (63.4%) and atrial-type (36.6%) AP morphologies, while ventricular AP configurations were not observed. Conclusion: We provide a novel culture media-based, transgene-free approach for targeted generation of hiPSC-derived pacemaker-type cells that grow in clusters and offer the potential for disease modeling, drug testing, and individualized cell-based replacement therapy of the SAN

Neuronal Expression of Glucosylceramide Synthase in Central Nervous System Regulates Body Weight and Energy Homeostasis

Abstract Hypothalamic neurons are main regulators of energy homeostasis. Neuronal function essentially depends on plasma membrane-located gangliosides. The present work demonstrates that hypothalamic integration of metabolic signals requires neuronal expression of glucosylceramide synthase (GCS; UDP-glucose:ceramide glucosyltransferase). As a major mechanism of central nervous system (CNS) metabolic control, we demonstrate that GCS-derived gangliosides interacting with leptin receptors (ObR) in the neuronal membrane modulate leptin-stimulated formation of signaling metabolites in hypothalamic neurons. Furthermore, ganglioside-depleted hypothalamic neurons fail to adapt their activity (c-Fos) in response to alterations in peripheral energy signals. Consequently, mice with inducible forebrain neuron-specific deletion of the UDP-glucose:ceramide glucosyltransferase gene (Ugcg) display obesity, hypothermia, and lower sympathetic activity. Recombinant adeno-associated virus (rAAV)-mediated Ugcg delivery to the arcuate nucleus (Arc) significantly ameliorated obesity, specifying gangliosides as seminal components for hypothalamic regulation of body energy homeostasis

Fast Homeostatic Plasticity of Inhibition via Activity-Dependent Vesicular Filling

Synaptic activity in the central nervous system undergoes rapid state-dependent changes, requiring constant adaptation of the homeostasis between excitation and inhibition. The underlying mechanisms are, however, largely unclear. Chronic changes in network activity result in enhanced production of the inhibitory transmitter GABA, indicating that presynaptic GABA content is a variable parameter for homeostatic plasticity. Here we tested whether such changes in inhibitory transmitter content do also occur at the fast time scale required to ensure inhibition-excitation-homeostasis in dynamic cortical networks. We found that intense stimulation of afferent fibers in the CA1 region of mouse hippocampal slices yielded a rapid and lasting increase in quantal size of miniature inhibitory postsynaptic currents. This potentiation was mediated by the uptake of GABA and glutamate into presynaptic endings of inhibitory interneurons (the latter serving as precursor for the synthesis of GABA). Thus, enhanced release of inhibitory and excitatory transmitters from active networks leads to enhanced presynaptic GABA content. Thereby, inhibitory efficacy follows local neuronal activity, constituting a negative feedback loop and providing a mechanism for rapid homeostatic scaling in cortical circuits

Neuronal Oscillations Enhance Stimulus Discrimination by Ensuring Action Potential Precision

Although oscillations in membrane potential are a prominent feature of sensory, motor, and cognitive function, their precise role in signal processing remains elusive. Here we show, using a combination of in vivo, in vitro, and theoretical approaches, that both synaptically and intrinsically generated membrane potential oscillations dramatically improve action potential (AP) precision by removing the membrane potential variance associated with jitter-accumulating trains of APs. This increased AP precision occurred irrespective of cell type and—at oscillation frequencies ranging from 3 to 65 Hz—permitted accurate discernment of up to 1,000 different stimuli. At low oscillation frequencies, stimulus discrimination showed a clear phase dependence whereby inputs arriving during the trough and the early rising phase of an oscillation cycle were most robustly discriminated. Thus, by ensuring AP precision, membrane potential oscillations dramatically enhance the discriminatory capabilities of individual neurons and networks of cells and provide one attractive explanation for their abundance in neurophysiological systems

Neuronal oscillations in cortical networks.

Clocks tick, bridges and skyscrapers vibrate, neuronal networks oscillate. Are neuronal oscillations an inevitable by-product, similar to bridge vibrations, or an essential part of the brain's design? Mammalian cortical neurons form behavior-dependent oscillating networks of various sizes, which span five orders of magnitude in frequency. These oscillations are phylogenetically preserved, suggesting that they are functionally relevant. Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information. T he first human electroencephalographic (EEG) pattern described was an 8 to 12 Hz rhythm, the alpha waves of Berger (1), followed by a barrage of intensive clinical and basic research. From scalp recordings, investigators identified various other oscillatory patterns that were particularly obvious during rest and sleep. However, the scalp EEG during conscious, waking behavior demonstrated lowamplitude, "desynchronized" patterns. This apparent inverse relation between cognitive activity and brain rhythms was further emphasized by the dominance of oscillations in anesthesia and epilepsy, states associated with loss of consciousness (2). Therefore, the motivation to relate these "idling" or even harmful rhythms to complex cognitive brain operations was diminished. The recent resurgence of interest in neuronal oscillations is a result of several parallel developments. Whereas in the past we simply watched oscillations, we have recently begun creating them under controlled situations A System of Brain Oscillators Neuronal networks in the mammalian forebrain demonstrate several oscillatory bands covering frequencies from approximately 0.05 Hz to 500 Hz The power density of EEG or local field potential is inversely proportional to frequency (f ) in the mammalian cortex (27) These relations between anatomical architecture and oscillatory patterns allow brain operations to be carried out simultaneously at multiple temporal and spatial scales (32). Assembly Synchronization by Oscillation Integration of information requires "synchrony" of the convergent inputs. Synchrony is define