Morphological plasticity of astroglia: Understanding synaptic microenvironment

Memory formation in the brain is thought to rely on the remodeling of synaptic connections which eventually results in neural network rewiring. This remodeling is likely to involve ultrathin astroglial protrusions which often occur in the immediate vicinity of excitatory synapses. The phenomenology, cellular mechanisms, and causal relationships of such astroglial restructuring remain, however, poorly understood. This is in large part because monitoring and probing of the underpinning molecular machinery on the scale of nanoscopic astroglial compartments remains a challenge. Here we briefly summarize the current knowledge regarding the cellular organisation of astroglia in the synaptic microenvironment and discuss molecular mechanisms potentially involved in use-dependent astroglial morphogenesis. We also discuss recent observations concerning morphological astroglial plasticity, the respective monitoring methods, and some of the newly emerging techniques that might help with conceptual advances in the area. GLIA 2015

The Nanoworld of the Tripartite Synapse: Insights from Super-Resolution Microscopy

Synaptic connections between individual nerve cells are fundamental to the process of information transfer and storage in the brain. Over the past decades a third key partner of the synaptic machinery has been unveiled: ultrathin processes of electrically passive astroglia which often surround pre- and postsynaptic structures. The recent advent of super-resolution (SR) microscopy has begun to uncover the dynamic nanoworld of synapses and their astroglial environment. Here we overview and discuss the current progress in our understanding of the synaptic nanoenvironment, as gleaned from the imaging methods that go beyond the diffraction limit of conventional light microscopy. We argue that such methods are essential to achieve a new level of comprehension pertinent to the principles of signal integration in the brain

Synaptic GABA release prevents GABA transporter type-1 reversal during excessive network activity.

GABA transporters control extracellular GABA, which regulates the key aspects of neuronal and network behaviour. A prevailing view is that modest neuronal depolarization results in GABA transporter type-1 (GAT-1) reversal causing non-vesicular GABA release into the extracellular space during intense network activity. This has important implications for GABA uptake-targeting therapies. Here we combined a realistic kinetic model of GAT-1 with experimental measurements of tonic GABAA receptor currents in ex vivo hippocampal slices to examine GAT-1 operation under varying network conditions. Our simulations predict that synaptic GABA release during network activity robustly prevents GAT-1 reversal. We test this in the 0 Mg(2+) model of epileptiform discharges using slices from healthy and chronically epileptic rats and find that epileptiform activity is associated with increased synaptic GABA release and is not accompanied by GAT-1 reversal. We conclude that sustained efflux of GABA through GAT-1 is unlikely to occur during physiological or pathological network activity

Efficient integration of synaptic events by NMDA receptors in three-dimensional neuropil

Sustained activation of NMDA receptors (NMDARs) plays an important role in controlling activity of neural circuits in the brain. However, whether this activation reflects the ambient level of excitatory neurotransmitter glutamate in brain tissue or whether it depends mainly on local synaptic discharges remains poorly understood. To shed light on the underlying biophysics here we developed and explored a detailed Monte Carlo model of a realistic three-dimensional neuropil fragment containing 54 excitatory synapses. To trace individual molecules and their individual receptor interactions on this scale, we have designed and implemented a dedicated computer cluster and the appropriate software environment. Our simulations have suggested that sparse synaptic discharges are 20-30 times more efficient than nonsynaptic (stationary, leaky) supply of glutamate in controlling sustained NMDAR occupancy in the brain. This mechanism could explain how the brain circuits provide substantial background activation of NMDARs while maintaining a negligible ambient glutamate level in the extracellular space. Thus the background NMDAR occupancy, rather than the background glutamate level, is likely to reflect the ongoing activity in local excitatory networks

Optical monitoring of glutamate release at multiple synapses in situ detects changes following LTP induction

Information processing and memory formation in the brain relies on release of the main excitatory neurotransmitter glutamate from presynaptic axonal specialisations. The classical Hebbian paradigm of synaptic memory, long-term potentiation (LTP) of transmission, has been widely associated with an increase in the postsynaptic receptor current. Whether and to what degree LTP induction also enhances presynaptic glutamate release has been the subject of debate. Here, we took advantage of the recently developed genetically encoded optical sensors of glutamate (iGluSnFR) to monitor its release at CA3-CA1 synapses in acute hippocampal slices, before and after the induction of LTP. We attempted to trace release events at multiple synapses simultaneously, by using two-photon excitation imaging in fast frame-scanning mode. We thus detected a significant increase in the average iGluSnFR signal during potentiation, which lasted for up to 90 min. This increase may reflect an increased amount of released glutamate or, alternatively, reduced glutamate binding to high-affinity glutamate transporters that compete with iGluSnFR

Exploring Nanoscale Organisation of Synapses with Super-Resolution Microscopy

The rapid advance of super-resolution microscopy and its experimental applications has provided neuroscientists with a pass to the nanoscopic world of synaptic machinery. Here we will briefly overview and discuss current progress in our understanding of the three-dimensional synaptic architecture and molecular organisation as gleaned from the imaging methods that go beyond the diffraction limit of conventional light microscopy. We will argue that such methods are to take our knowledge of synapses to a qualitatively new level, providing the neuroscience research community with novel organising principles and concepts pertinent to the workings of the brain

Noisy Synaptic Conductance: Bug or a Feature?

More often than not, action potentials fail to trigger neurotransmitter release. And even when neurotransmitter is released, the resulting change in synaptic conductance is highly variable. Given the energetic cost of generating and propagating action potentials, and the importance of information transmission across synapses, this seems both wasteful and inefficient. However, synaptic noise arising from variable transmission can improve, in certain restricted conditions, information transmission. Under broader conditions, it can improve information transmission per release, a quantity that is relevant given the energetic constraints on computing in the brain. Here we discuss the role, both positive and negative, synaptic noise plays in information transmission and computation in the brain

Conductance of porous media depends on external electric fields

In obstacle-filled media, such as extracellular or intracellular lumen of brain tissue, effective ion diffusion permeability is a key determinant of electrogenic reactions. Although this diffusion permeability is thought to depend entirely on structural features of the medium, such as porosity and tortuosity, brain tissue shows prominent non-ohmic properties, the origins of which remain poorly understood. Here, we explore Monte Carlo simulations of ion diffusion in a space filled with overlapping spheres, to predict that diffusion permeability of such media decreases with stronger external electric fields. This dependence increases with lower medium porosity while decreasing with radial (2D or 3D) compared to homogenous (1D) fields. We test our predictions empirically in an electrolyte chamber filled with microscopic glass spheres and find good correspondence with our predictions. A theoretical insight relates this phenomenon to a disproportionately increased dwell time of diffusing ions at potential barriers (or traps) representing geometric obstacles, when the field strength increases. The dependence of medium ion-diffusion permeability on electric field could be important for understanding conductivity properties of porous materials, in particular for the accurate interpretation of electric activity recordings in brain tissue

Buffering by Transporters Can Spare Geometric Hindrance in Controlling Glutamate Escape

The surface of astrocyte processes that often surround excitatory synapses is packed with high-affinity glutamate transporters, largely preventing extrasynaptic glutamate escape. The shape and prevalence of perisynaptic astroglia vary among brain regions, in some cases providing a complete isolation of synaptic connections from the surrounding tissue. The perception has been that the geometry of perisynaptic environment is therefore essential to preventing extrasynaptic glutamate escape. To understand to what degree this notion holds, we modelled brain neuropil as a space filled with a scatter of randomly sized, overlapping spheres representing randomly shaped cellular elements and intercellular lumen. Simulating release and diffusion of glutamate molecules inside the interstitial gaps in this medium showed that high-affinity transporters would efficiently constrain extrasynaptic spread of glutamate even when diffusion passages are relatively open. We thus estimate that, in the hippocampal or cerebellar neuropil, the bulk of glutamate released by a synaptic vesicle is rapidly bound by transporters (or high-affinity target receptors) mainly in close proximity of the synaptic cleft, whether or not certain physiological or pathological events change local tissue geometry

ARACHNE: A neural-neuroglial network builder with remotely controlled parallel computing

Creating and running realistic models of neural networks has hitherto been a task for computing professionals rather than experimental neuroscientists. This is mainly because such networks usually engage substantial computational resources, the handling of which requires specific programing skills. Here we put forward a newly developed simulation environment ARACHNE: it enables an investigator to build and explore cellular networks of arbitrary biophysical and architectural complexity using the logic of NEURON and a simple interface on a local computer or a mobile device. The interface can control, through the internet, an optimized computational kernel installed on a remote computer cluster. ARACHNE can combine neuronal (wired) and astroglial (extracellular volume-transmission driven) network types and adopt realistic cell models from the NEURON library. The program and documentation (current version) are available at GitHub repository https://github.com/LeonidSavtchenko/Arachne under the MIT License (MIT)