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468 results for “Spikes”
Data from: Testing Darwin’s hypothesis about the wonderful Venus flytrap: marginal spikes form a ‘horrid prison’ for moderate-sized insect prey
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Cleavage of SARS-CoV-2 spike protein mutants
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Source data for: Presynaptic NMDARs cooperate with local spikes toward GABA release from the reciprocal olfactory bulb granule cell spine
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Plasmodium infection is associated with cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein
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Figure 4 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 4 Docking energies and interface score charts. A shows the Rosetta Dock results, binding energies from PDBEPISA server in B shows good results for ΔG. Developability of this antibody shows all green flags in C.
Figure 3 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 3 Docking interface between the modified 80R antibody and the RBD of the SARS-CoV-2 spike protein. The model shows the structural interface with the 80R antibody above and the RBD below. The seven substitutions in 80R are shown in magenta and RBD residues are shown in cyan. Notice how the substitutions in 80R allow new aromatic-aromatic interactions that improve binding to the RBD and are not present in wild type 80R. E484 is shown pointing towards the beta strand of 80R and a glycine substitution was therefore introduced to avoid clashes.
Figure 6 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 6 m396 mutations docking results. A shows Rosetta Dock funnels for the original partners SARS-CoV and m396, SARS-CoV-2 and m396 and the SARS-CoV-2 and mutated m396. Notice how the binding is improved to the level of the original partners. B shows the ΔG energies again notice the improvement of binding when the mutations are introduced. Finally, C shows the developability flags with only one warning that is not that far from green flag.
Figure 5 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 5 Docking interface between the modified m396 antibody and SARS-CoV-2 spike protein RBD. In magenta is m396 mutant and in cyan SARS-CoV-2 RBD. These five mutations introduce many electrostatic interactions between the partners therefore stabilizing very much the binding.
Figure 2 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 2 Structural analysis of SARS-CoV spike glycoprotein. In A the SARS-CoV spike protein (PDB ID: 6ACG) is shown bound to ACE2 (brown) and 80R antibody (cyan), superimposed on the same binding site. In B the spike protein is shown bound only to the 80R antibody (PDB ID: 2GHW), with the structural model of the RBD of the SARS-CoV-2 spike protein (magenta) containing the missing loops. This homology model served as the basis for the docking experiments. In C it is shown a spike colored by subunit and showing the glycans. There are only two possible glycans in RBD region at 331 and 343 and neither of these sites affect the 80R binding.
Figure 1 from: Padilla-Sanchez V (2020) In silico analysis of SARS-CoV-2 spike glycoprotein and insights into antibody binding. Research Ideas and Outcomes 6: e55281. https://doi.org/10.3897/rio.6.e55281
Figure 1 Structural model of SARS-CoV-2 infection. This structural model was built with UCSF Chimera using high-performance computers (Bridges Large and Frontera). The model shows 16 viruses, with the spike proteins shown in green (PDB ID: 6VSB) and an actual lipid bilayer membrane, with ACE2 dimers shown in magenta. All these structures are at atomic resolution. The length of the membrane is approximately 1 micrometer.
Supplementary Structural Models (SARS-CoV-2 Spike-RBD:ACE2 complex and TMPRSS2) - SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals
<p>Structural Models (PDB) of SARS-CoV-2 Spike RBD bound to ACE2 receptors of 215 animals.</p> <p>Structural model of Human TMPRSS2.</p> <p>Modelled using the FunMod pipeline and referenced in the preprint</p> <p><a href="https://www.biorxiv.org/content/10.1101/2020.05.01.072371v5">SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals</a></p> <p> </p>
Dendritic integration in olfactory bulb granule cells upon simultaneous multi-spine activation: Low thresholds for non-local spiking activity
<p class="CxSpFirst">The inhibitory axonless olfactory bulb granule cells form reciprocal dendrodendritic synapses with mitral and tufted cells via large spines, mediating recurrent and lateral inhibition. As a case in point for dendritic transmitter release, rat granule cell dendrites are highly excitable, featuring local Na<sup>+</sup> spine spikes and global Ca<sup>2+</sup>- and Na<sup>+</sup>-spikes. To investigate the transition from local to global signaling we performed holographic, simultaneous two-photon uncaging of glutamate at up to twelve granule cell spines, along with whole-cell recording and dendritic two-photon Ca<sup>2+</sup> imaging in acute juvenile rat brain slices. Coactivation of less than ten reciprocal spines was sufficient to generate diverse regenerative signals that included regional dendritic Ca<sup>2+</sup>-spikes and dendritic Na<sup>+</sup>-spikes (D-spikes). Global Na<sup>+</sup>-spikes could be triggered in one third of granule cells. Individual spines and dendritic segments sensed the respective signal transitions as increments in Ca<sup>2+</sup> entry. Dendritic integration as monitored by the somatic membrane potential was mostly linear until a threshold number of spines was activated, where often D-spikes along with supralinear summation set in. As to the mechanisms supporting active integration, NMDA receptors strongly contributed to all aspects of supralinearity, followed by dendritic voltage-gated Na<sup>+</sup>- and Ca<sup>2+</sup>-channels, whereas local Na<sup>+</sup> spine spikes as well as morphological parameters barely mattered.</p> <p>Because of the low numbers of coactive spines required to trigger dendritic Ca<sup>2+</sup> signals and thus possibly lateral release of GABA onto mitral and tufted cells, we predict that thresholds for granule cell-mediated bulbar lateral inhibition are low. Moreover, D-spikes could provide a plausible substrate for granule cell-mediated gamma oscillations.</p>
SARS-CoV-2 spike binding to ACE2-B0AT1 complex
<p>Cryo-EM maps and models of SARS-CoV-2 spike (EMD:21457) and ACE2-B0AT1 (EMD:30039) are illustrated. Membranes are shown around the B0AT1 and approximated around the spike, which is lacking the trans-membrane domain. The binding of the spike to the ACE2 receptor is shown based on the model RBD built into the ACE2-B0AT1 map. The appears to attain a sharp angle wrt. the membrane surface to allow this binding.</p>
Supervised molecular dynamics for exploring the druggability of the SARS-CoV-2 spike protein (Topology and .xtc files)
<p>ABSTRACT. The recent outbreak of the respiratory syndrome-related coronavirus (SARS-CoV-2) is stimulating an unprecedented scientific campaign to alleviate the burden of the coronavirus disease (COVID-19). One line of research has focused on targeting SARS-CoV-2 proteins fundamental for its replication by repurposing drugs approved for other diseases. The first interaction between the virus and the host cell is mediated by the spike protein on the virus surface and the human angiotensin-converting enzyme (ACE2). Small molecules able to bind the receptor-binding domain (RBD) of the spike protein and disrupt the binding to ACE2 would offer an important tool for slowing, or even preventing, the infection. Here, we screened 2421 approved small molecules<em> in </em>silico and validated the docking outcomes through extensive molecular dynamics simulations. Out of six drugs characterized as putative RBD binders, the cephalosporin antibiotic cefsulodin was further assessed for its effect on the binding between the RBD and ACE2, suggesting the importance of considering the dynamic formation of the heterodimer when judging any potential candidate.</p>
3D model of the human ACE2 receptor bound to the SARS-CoV-2 Spike RBD
<p>3D structure model of the receptor-binding domain of SARS-CoV-2 (top) bound to the human ACE2 receptor (bottom). The two highlighted aminoacids - ACE2 D30 (red) and RBD K417 (blue) - are part of a set of interactions that is conserved in animal species susceptible to infection by the virus but are absent from immune species.</p>
Data from: Complex spike synchrony dependent modulation of rat deep cerebellar nuclear activity
The rules determining cerebellar output are not fully understood, but must involve Purkinje cell activity (PCs), as PCs are the major input to deep cerebellar nuclear (DCN) cells (which form the majority of cerebellar output). Here, the influence of PC complex spikes (CSs) was investigated by simultaneously recording DCN activity with CSs from PC arrays in anesthetized rats. Crosscorrelograms were used to identify PCs that were presynaptic to recorded DCN cells (presynaptic PCs). Such PCs were located within rostrocaudal cortical strips and displayed synchronous CS activity. CS-associated modulation of DCN activity included a short-latency post-CS inhibition and long-latency excitations before and after the CS. The amplitudes of the post-CS responses correlated with the level of synchronization among presynaptic PCs. A temporal precision of {less than or equal to} 10 ms was generally required for CSs to be maximally effective. The results suggest that CS synchrony is a key control parameter of cerebellar output.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
Data from: Spike-triggered covariance analysis reveals phenomenological diversity of contrast adaptation in the retina
When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.
Data from: ASSET: analysis of sequences of synchronous events in massively parallel spike trains
With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity.
Inference of nonlinear receptive field subunits with spike-triggered clustering
<p>Responses of sensory neurons are often modeled using a weighted combination of rectified linear subunits. Since these subunits often cannot be measured directly, a flexible method is needed to infer their properties from the responses of downstream neurons. We present a method for maximum likelihood estimation of subunits by soft-clustering spike-triggered stimuli, and demonstrate its effectiveness in visual neurons. Subunits estimated from parasol retinal ganglion cells (RGCs) in macaque retina partitioned the receptive field into compact regions, likely representing aggregated bipolar cell inputs. Joint clustering revealed shared subunits in neighboring RGCs, producing a parsimonious population model. Closed-loop validation, using stimuli lying in the null space of the linear receptive field, revealed stronger nonlinearities in OFF cells than ON cells. Responses to natural images, jittered to emulate fixational eye movements, were accurately predicted by the subunit model. Finally, the generality of the approach was demonstrated in macaque V1 neurons.</p>
Data from: Discrepancies in the spiking threshold and frequency sensitivity in nocturnal moths explainable by biases in the 3222 auditory stimulation method45
The auditory stimulation method used in experiments on moth A cell(s) is generally believed to be adequate to characterize the encoding of bat echolocation signals. The stimulation method hosts, though, several biases. Their compounded effects can explain a range of discrepancies between the reported electrophysiological recordings and significantly alter the current interpretation. To test the hypothesis that the bias may significantly alter our current understanding of the moth's auditory transducer characteristics, papers using the same auditory stimulation method and reporting on either spiking threshold or spiking activity of the moth's A cells were analysed. The consistency of the reported data was assessed. A range of corrections issued from best practices and theoretical background were applied to the data in an attempt to re-interpret the data. We found that it is not possible to apply a posteriori corrections to all data and bias. However the corrected data indicates that the A cell's spiking may be (i) independent of the repetition rate, (ii) maximum when detecting long and low intensity pulses, and (iii) steadily reduce as the bat closes on the moth. These observations raise the possibility that a fixed action pattern drives the moths' erratic evasive manoeuvres until the final moment. In depth investigation of the potential bias also suggest that the auditory transducer's response may be constant for a larger frequency range than thought so far, and provide clues to explain the negative taxis in response to the searching bats' calls detection.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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