SynGAP isoforms exert opposing effects on synaptic strength

Peer reviewedPublisher PD

The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour

Neuronal synapses play fundamental roles in information processing, behaviour and disease. Neurotransmitter receptor complexes, such as the mammalian N-methyl-D-aspartate receptor complex (NRC/MASC) comprising 186 proteins, are major components of the synapse proteome. Here we investigate the organisation and function of NRC/MASC using a systems biology approach. Systematic annotation showed that the complex contained proteins implicated in a wide range of cognitive processes, synaptic plasticity and psychiatric diseases. Protein domains were evolutionarily conserved from yeast, but enriched with signalling domains associated with the emergence of multicellularity. Mapping of protein–protein interactions to create a network representation of the complex revealed that simple principles underlie the functional organisation of both proteins and their clusters, with modularity reflecting functional specialisation. The known functional roles of NRC/MASC proteins suggest the complex co-ordinates signalling to diverse effector pathways underlying neuronal plasticity. Importantly, using quantitative data from synaptic plasticity experiments, our model correctly predicts robustness to mutations and drug interference. These studies of synapse proteome organisation suggest that molecular networks with simple design principles underpin synaptic signalling properties with important roles in physiology, behaviour and disease

Signal Propagation in Feedforward Neuronal Networks with Unreliable Synapses

In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.Comment: 33pages, 16 figures; Journal of Computational Neuroscience (published

An enhanced CRISPR repressor for targeted mammalian gene regulation.

The RNA-guided endonuclease Cas9 can be converted into a programmable transcriptional repressor, but inefficiencies in target-gene silencing have limited its utility. Here we describe an improved Cas9 repressor based on the C-terminal fusion of a rationally designed bipartite repressor domain, KRAB-MeCP2, to nuclease-dead Cas9. We demonstrate the system's superiority in silencing coding and noncoding genes, simultaneously repressing a series of target genes, improving the results of single and dual guide RNA library screens, and enabling new architectures of synthetic genetic circuits

Correlation function of quasars in real and redshift space from the Sloan Digital Sky Survey Data Release 7

We analyze the quasar two-point correlation function (2pCF) within the redshift interval $0.8<z<2.2$ using a sample of 52303 quasars selected from the recent 7th Data Release of the Sloan Digital Sky Survey. Our approach to 2pCF uses a concept of locally Lorentz (Fermi) frame for determination of the distance between objects and permutation method of the random catalogue generation. Assuming the spatially flat cosmological model with given $\Omega_{\Lambda}=0.726$, we found that the real-space 2pCF is fitted well with the power-low model within the distance range $1<\sigma<35$ $h^{-1}$ Mpc with the correlation length $r_{0}=5.85\pm0.33$ $h^{-1}$ Mpc and the slope $\gamma=1.87\pm0.07$. The redshift-space 2pCF is approximated with $s_{0}=6.43\pm0.63$ $h^{-1}$ Mpc and $\gamma=1.21\pm0.24$ for $1<s<10$ $h^{-1}$ Mpc, and $s_{0}=7.37\pm0.81$ $h^{-1}$ Mpc and $\gamma=1.90\pm0.24$ for $1010\,h^{-1}$ Mpc the parameter describing the large-scale infall to density inhomogeneities is $\beta=0.63\pm0.10$ with the linear bias $b=1.44\pm0.22$ that marginally (within 2$\sigma$) agrees with the linear theory of cosmological perturbations. We discuss possibilities to obtain a statistical estimate of the random component of quasars velocities (different from the large-scale infall). We note rather slight dependence of quasars velocity dispersion upon the 2pCF parameters in the region $r<2$ Mpc.Comment: 15 pages, 17 figures, online published in MNRAS; final version to match the published versio

Associations between stratospheric variability and tropospheric blocking

There is widely believed to be a link between stratospheric flow variability and stationary, persistent “blocking” weather systems, but the precise nature of this link has proved elusive. Using data from the ERA-40 Reanalysis and an atmospheric general circulation model (GCM) with a well-resolved stratosphere (HadGAM), it is shown that there are in fact several different highly significant associations, with blocking in different regions being related to different patterns of stratospheric variability. This is true in both hemispheres and in both data sets. The associations in HadGAM are shown to be very similar to those in ERA-40, although the model has a tendency to underestimate both European blocking and the wave number 2 stratospheric variability to which this is related. Although the focus is on stratospheric variability in general, several of the blocking links are seen to occur in association with the major stratospheric sudden warmings. In general, the direction of influence appears to be upward, as blocking anomalies are shown to modify the planetary stationary waves, leading to an upward propagation of wave activity into the stratosphere. However, significant correlations are also apparent with the zonal mean flow in the stratosphere leading the occurrence of blocking at high latitudes. Finally, the underestimation of blocking is an enduring problem in GCMs, and an example has recently been given in which improving the resolution of the stratosphere improved the representation of blocking. Here, however, another example is given, in which increasing the stratospheric resolution unfortunately does not lead to an improvement in blocking

Extended T2-IVIM model for correction of TE dependence of pseudo-diffusion volume fraction in clinical diffusion-weighted magnetic resonance imaging.

The bi-exponential intravoxel-incoherent-motion (IVIM) model for diffusion-weighted MRI (DWI) fails to account for differential T 2 s in the model compartments, resulting in overestimation of pseudodiffusion fraction f. An extended model, T2-IVIM, allows removal of the confounding echo-time (TE) dependence of f, and provides direct compartment T 2 estimates. Two consented healthy volunteer cohorts (n  =  5, 6) underwent DWI comprising multiple TE/b-value combinations (Protocol 1: TE  =  62-102 ms, b  =  0-250 mm-2s, 30 combinations. Protocol 2: 8 b-values 0-800 mm-2s at TE  =  62 ms, with 3 additional b-values 0-50 mm-2s at TE  =  80, 100 ms; scanned twice). Data from liver ROIs were fitted with IVIM at individual TEs, and with the T2-IVIM model using all data. Repeat-measures coefficients of variation were assessed for Protocol 2. Conventional IVIM modelling at individual TEs (Protocol 1) demonstrated apparent f increasing with longer TE: 22.4  ±  7% (TE  =  62 ms) to 30.7  ±  11% (TE  =  102 ms); T2-IVIM model fitting accounted for all data variation. Fitting of Protocol 2 data using T2-IVIM yielded reduced f estimates (IVIM: 27.9  ±  6%, T2-IVIM: 18.3  ±  7%), as well as T 2  =  42.1  ±  7 ms, 77.6  ±  30 ms for true and pseudodiffusion compartments, respectively. A reduced Protocol 2 dataset yielded comparable results in a clinical time frame (11 min). The confounding dependence of IVIM f on TE can be accounted for using additional b/TE images and the extended T2-IVIM model