Ultrafast glutamate sensors resolve high-frequency release at Schaffer collateral synapses

Glutamatergic synapses display a rich repertoire of plasticity mechanisms on many different time scales, involving dynamic changes in the efficacy of transmitter release as well as changes in the number and function of postsynaptic glutamate receptors. The genetically encoded glutamate sensor iGluSnFR enables visualization of glutamate release from presynaptic terminals at frequencies up to ∼10 Hz. However, to resolve glutamate dynamics during high-frequency bursts, faster indicators are required. Here, we report the development of fast (iGluf) and ultrafast (iGluu) variants with comparable brightness but increased Kd for glutamate (137 μM and 600 μM, respectively). Compared with iGluSnFR, iGluu has a sixfold faster dissociation rate in vitro and fivefold faster kinetics in synapses. Fitting a three-state model to kinetic data, we identify the large conformational change after glutamate binding as the rate-limiting step. In rat hippocampal slice culture stimulated at 100 Hz, we find that iGluu is sufficiently fast to resolve individual glutamate release events, revealing that glutamate is rapidly cleared from the synaptic cleft. Depression of iGluu responses during 100-Hz trains correlates with depression of postsynaptic EPSPs, indicating that depression during high-frequency stimulation is purely presynaptic in origin. At individual boutons, the recovery from depression could be predicted from the amount of glutamate released on the second pulse (paired pulse facilitation/depression), demonstrating differential frequency-dependent filtering of spike trains at Schaffer collateral boutons

Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy

Modelling Vesicular Release at Hippocampal Synapses

We study local calcium dynamics leading to a vesicle fusion in a stochastic, and spatially explicit, biophysical model of the CA3-CA1 presynaptic bouton. The kinetic model for vesicle release has two calcium sensors, a sensor for fast synchronous release that lasts a few tens of milliseconds and a separate sensor for slow asynchronous release that lasts a few hundred milliseconds. A wide range of data can be accounted for consistently only when a refractory period lasting a few milliseconds between releases is included. The inclusion of a second sensor for asynchronous release with a slow unbinding site, and thereby a long memory, affects short-term plasticity by facilitating release. Our simulations also reveal a third time scale of vesicle release that is correlated with the stimulus and is distinct from the fast and the slow releases. In these detailed Monte Carlo simulations all three time scales of vesicle release are insensitive to the spatial details of the synaptic ultrastructure. Furthermore, our simulations allow us to identify features of synaptic transmission that are universal and those that are modulated by structure

The Effects of NR2 Subunit-Dependent NMDA Receptor Kinetics on Synaptic Transmission and CaMKII Activation

N-Methyl-d-aspartic acid (NMDA) receptors are widely expressed in the brain and are critical for many forms of synaptic plasticity. Subtypes of the NMDA receptor NR2 subunit are differentially expressed during development; in the forebrain, the NR2B receptor is dominant early in development, and later both NR2A and NR2B are expressed. In heterologous expression systems, NR2A-containing receptors open more reliably and show much faster opening and closing kinetics than do NR2B-containing receptors. However, conflicting data, showing similar open probabilities, exist for receptors expressed in neurons. Similarly, studies of synaptic plasticity have produced divergent results, with some showing that only NR2A-containing receptors can drive long-term potentiation and others showing that either subtype is capable of driving potentiation. In order to address these conflicting results as well as open questions about the number and location of functional receptors in the synapse, we constructed a Monte Carlo model of glutamate release, diffusion, and binding to NMDA receptors and of receptor opening and closing as well as a model of the activation of calcium-calmodulin kinase II, an enzyme critical for induction of synaptic plasticity, by NMDA receptor-mediated calcium influx. Our results suggest that the conflicting data concerning receptor open probabilities can be resolved, with NR2A- and NR2B-containing receptors having very different opening probabilities. They also support the conclusion that receptors containing either subtype can drive long-term potentiation. We also are able to estimate the number of functional receptors at a synapse from experimental data. Finally, in our models, the opening of NR2B-containing receptors is highly dependent on the location of the receptor relative to the site of glutamate release whereas the opening of NR2A-containing receptors is not. These results help to clarify the previous findings and suggest future experiments to address open questions concerning NMDA receptor function

Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications

This work was supported by a restricted research grant of Bayer AG

Automated analysis of spine dynamics on live CA1 pyramidal cells

Dendritic spines may be tiny in volume, but are of major importance for neuroscience. They are the main receivers for excitatory synaptic connections, and their constant changes in number and in shape reflect the dynamic connectivity of the brain. Two-photon microscopy allows following the fate of individual spines in brain slice preparations and in live animals. The diffraction-limited and non-isotropic resolution of this technique, however, makes detection of such tiny structures rather challenging, especially along the optical axis (z-direction). Here we present a novel spine detection algorithm based on a statistical dendrite intensity model and a corresponding spine probability model. To quantify the fidelity of spine detection, we generated correlative datasets: Following two-photon imaging of live pyramidal cell dendrites, we used Serial Block-Face Scanning Electron Microscopy (SBEM) to reconstruct dendritic ultrastructure in 3D. Statistical models were trained on synthetic fluorescence images generated from SBEM datasets via Point Spread Function (PSF) convolution. After the training period, we tested automatic spine detection on real two-photon datasets and compared the result to ground truth (correlative SBEM data). The performance of our algorithm allowed tracking changes in spine volume automatically over several hours. Using a second fluorescent protein targeted to the endoplasmic reticulum, we could analyze the motion of this organelle inside individual spines. Furthermore, we show that it is possible to distinguish activated spines from non-stimulated neighbors by detection of fluorescently labeled presynaptic vesicle clusters. These examples illustrate how automatic segmentation in 5D (x, y, z, t, λ) allows us to investigate brain dynamics at the level of individual synaptic connections

Subliminal messages in hippocampal pyramidal cells

Synaptic activity regulates gene transcription in neurons. The coupling between synaptic transmission and transcription is accomplished by the second messenger calcium, which enters the cell through synaptic receptors and voltage-gated calcium channels and binds enzymes that activate transcription factors. In schematic diagrams showing these calcium-activated pathways, synaptic calcium influx happens conveniently close to the nucleus (West et al. 2001). In reality, however, synapses are distributed over an extensive dendritic tree. How then is information about synaptic activity passed on to the nucleus, which can be hundreds of micrometres from activated synapses? Passive diffusion is too slow for a long-range signalling system, especially given the high buffer capacity of the dendritic cytoplasm for calcium and the slow diffusion of these buffers (Helmchen et al. 1996). The report of Nakamura et al. (2002) in this issue of The Journal of Physiology takes a closer look at the properties of regenerative calcium waves in the apical dendrite of CA1 pyramidal cells (see also: Kapur et al. 2001; Nakamura et al. 1999, 2000). These waves, which depend upon activation of inositol 1,4,5-trisphosphate (IP3) receptors, are a prime candidate for a signalling system that locally integrates synaptic activity in the dendrite and sends a binary signal to the nucleus (Berridge, 1998)