Relationship between monomer packing and receptor binding domain pocket status in the spike trimer of SARS-CoV-2 variants

Existence of a SARS-CoV-2 spike protein trimer form with closer packing between monomers when receptor binding domains (RBDs) are all down, locked as opposed to closed, has been associated with linoleic acid (LA) binding at neutral pH, or can occur at acidic pH in the absence of LA binding. The relationship between degree of closure of the LA binding pocket of the RBD, and monomer burial in the trimer, is examined for a range of spike protein structures, including those with D614G mutation, and that of the Delta variant (which also carries D614G). Some spike protein structures with this aspartic acid mutation show monomer packing approaching that of the locked form (at neutral pH, without LA binding) for two segments, a third (around the RBD) remains less closely packed. Analysis of other coronavirus RBD structures suggests that mutation of the RBD in spike protein of the Omicron variant could lead to LA binding pocket changes. It is proposed that these changes could lead to one of two consequences for the Omicron variant spike protein (which also has the D614G mutation), at neutral pH and without LA binding, either easier access to a locked form throughout that leads to cooperative transitions between all RBD down and all RBD up, or maintenance of a spike trimer with locked characteristics C-terminal to the RBD at the same time as the RBD is free to transit between down and up states. The situation may also be impacted by spike protein charge mutations in the Omicron lineage that alter pH-dependence around the RBD, in a similar way to the changes induced elsewhere by D614G.

Emergence and fragmentation of the alpha-band driven by neuronal network dynamics

Rhythmic neuronal network activity underlies brain oscillations. To investigate how connected neuronal networks contribute to the emergence of the α-band and to the regulation of Up and Down states, we study a model based on synaptic short-term depression-facilitation with afterhyperpolarization (AHP). We found that the α-band is generated by the network behavior near the attractor of the Up-state. Coupling inhibitory and excitatory networks by reciprocal connections leads to the emergence of a stable α-band during the Up states, as reflected in the spectrogram. To better characterize the emergence and stability of thalamocortical oscillations containing α and δ rhythms during anesthesia, we model the interaction of two excitatory networks with one inhibitory network, showing that this minimal topology underlies the generation of a persistent α-band in the neuronal voltage characterized by dominant Up over Down states. Finally, we show that the emergence of the α-band appears when external inputs are suppressed, while fragmentation occurs at small synaptic noise or with increasing inhibitory inputs. To conclude, α-oscillations could result from the synaptic dynamics of interacting excitatory neuronal networks with and without AHP, a principle that could apply to other rhythms.

The Flow of Axonal Information Among Hippocampal Subregions: 1. Feed-Forward and Feedback Network Spatial Dynamics Underpinning Emergent Information Processing

The tri-synaptic pathway in the mammalian hippocampus enables cognitive learning and memory. Despite decades of reports on anatomy and physiology, the functional architecture of the hippocampal network remains poorly understood in terms of the dynamics of axonal information transfer between subregions. Information inputs largely flow from the entorhinal cortex (EC) to the dentate gyrus (DG), and then are processed further in the CA3 and CA1 before returning to the EC. Here, we reconstructed elements of the rat hippocampus in a novel device over an electrode array that allowed for monitoring the directionality of individual axons between the subregions. The direction of spike propagation was determined by the transmission delay of the axons recorded between two electrodes in microfluidic tunnels. The majority of axons from the EC to the DG operated in the feed-forward direction, with other regions developing unexpectedly large proportions of feedback axons to balance excitation. Spike timing in axons between each region followed single exponential log-log distributions over two orders of magnitude from 0.01 to 1 s, indicating that conventional descriptors of mean firing rates are misleading assumptions. Most of the spiking occurred in bursts that required two exponentials to fit the distribution of inter-burst intervals. This suggested the presence of up-states and down-states in every region, with the least up-states in the DG to CA3 feed-forward axons and the CA3 subregion. The peaks of the log-normal distributions of intra-burst spike rates were similar in axons between regions with modes around 95 Hz distributed over an order of magnitude. Burst durations were also log-normally distributed around a peak of 88 ms over two orders of magnitude. Despite the diversity of these spike distributions, spike rates from individual axons were often linearly correlated to subregions. These linear relationships enabled the generation of structural connectivity graphs, not possible previously without the directional flow of axonal information. The rich axonal spike dynamics between subregions of the hippocampus reveal both constraints and broad emergent dynamics of hippocampal architecture. Knowledge of this network architecture may enable more efficient computational artificial intelligence (AI) networks, neuromorphic hardware, and stimulation and decoding from cognitive implants.

SARS-CoV-2 spike opening dynamics and energetics reveal the individual roles of glycans and their collective impact

The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, is responsible for binding to human ACE2 receptors. The binding process is initiated when the receptor binding domain (RBD) of at least one protomer switches from a "down" (closed) to an "up" (open) state. Here, we used molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations to investigate the transition between the two S-protein conformations with and without glycosylation. We show that the glycosylated spike has a higher barrier to opening than the non-glycosylated one with comparable populations of the down and up states. In contrast, we observed that the up conformation is favored without glycans. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state. We also identify roles for glycans at N165 and N343 in stabilizing the down and up states. Finally we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the epitope of the BD-368-2 antibody remains exposed irrespective of the S-protein conformation, explaining the high efficacy of this antibody.

Magnetic single atom catalyst in C2N to induce adsorption selectivity toward oxidizing gases

Density functional theory (DFT) method is used to study the effect of single-atom catalyst (SAC) of Mn embedded in C2N nanoribbon (C2N-NR) on the adsorption properties as an attempt to achieve selectivity. Many gases (e.g., CO, CO2, H2, H2O, H2S, N2 and O2) of interest to energy and environmental applications were tested. The results show that SAC-Mn alters chemisorption processes with all gas molecules except N2. Clear adsorption selectivity is obtained towards oxidizing CO, CO2 and O2 molecules as evidenced by the enhancements in binding energy and charge transfer and the reduction in magnetization. While the SAC-Mn contributes predominantly to Fermi-energy region with spin-down states, the strong binding to oxidizing molecules introduces there more spin-up states to compromise and reduce the magnetization. Hence, C2N-NR:Mn is proposed to be used as platform for gas sensor (if combined with magnetic sensor) to yield high selectivity toward these latter gases.

Synthetic Experiences for Accelerating DQN Performance in Discrete Non-Deterministic Environments

State-of-the-art Deep Reinforcement Learning Algorithms such as DQN and DDPG use the concept of a replay buffer called Experience Replay. The default usage contains only the experiences that have been gathered over the runtime. We propose a method called Interpolated Experience Replay that uses stored (real) transitions to create synthetic ones to assist the learner. In this first approach to this field, we limit ourselves to discrete and non-deterministic environments and use a simple equally weighted average of the reward in combination with observed follow-up states. We could demonstrate a significantly improved overall mean average in comparison to a DQN network with vanilla Experience Replay on the discrete and non-deterministic FrozenLake8x8-v0 environment.

Self-Organized Criticality in the Brain

Self-organized criticality (SOC) refers to the ability of complex systems to evolve toward a second-order phase transition at which interactions between system components lead to scale-invariant events that are beneficial for system performance. For the last two decades, considerable experimental evidence has accumulated that the mammalian cortex with its diversity in cell types, interconnectivity, and plasticity might exhibit SOC. Here, we review the experimental findings of isolated, layered cortex preparations to self-organize toward four dynamical motifs presently identified in the intact cortex in vivo: up-states, oscillations, neuronal avalanches, and coherence potentials. During up-states, the synchronization observed for nested theta/gamma oscillations embeds scale-invariant neuronal avalanches, which can be identified by robust power law scaling in avalanche sizes with a slope of −3/2 and a critical branching parameter of 1. This precise dynamical coordination, tracked in the negative transients of the local field potential (nLFP) and spiking activity of pyramidal neurons using two-photon imaging, emerges autonomously in superficial layers of organotypic cortex cultures and acute cortex slices, is homeostatically regulated, exhibits separation of time scales, and reveals unique size vs. quiet time dependencies. A subclass of avalanches, the coherence potentials, exhibits precise maintenance of the time course in propagated local synchrony. Avalanches emerge in superficial layers of the cortex under conditions of strong external drive. The balance of excitation and inhibition (E/I), as well as neuromodulators such as dopamine, establishes powerful control parameters for avalanche dynamics. This rich dynamical repertoire is not observed in dissociated cortex cultures, which lack the differentiation into cortical layers and exhibit a dynamical phenotype expected for a first-order phase transition. The precise interactions between up-states, nested oscillations, and avalanches in superficial layers of the cortex provide compelling evidence for SOC in the brain.

Effect of natural mutations of SARS-CoV-2 on spike structure, conformation, and antigenicity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with multiple spike mutations enable increased transmission and antibody resistance. We combined cryo–electron microscopy (cryo-EM), binding, and computational analyses to study variant spikes, including one that was involved in transmission between minks and humans, and others that originated and spread in human populations. All variants showed increased angiotensin-converting enzyme 2 (ACE2) receptor binding and increased propensity for receptor binding domain (RBD)–up states. While adaptation to mink resulted in spike destabilization, the B.1.1.7 (UK) spike balanced stabilizing and destabilizing mutations. A local destabilizing effect of the RBD E484K mutation was implicated in resistance of the B.1.1.28/P.1 (Brazil) and B.1.351 (South Africa) variants to neutralizing antibodies. Our studies revealed allosteric effects of mutations and mechanistic differences that drive either interspecies transmission or escape from antibody neutralization.

Multiscale dynamics underlying neocortical slow oscillations

Slow oscillations in the sleeping and anesthetized brain invariantly emerge as an alternation between Up (high firing) and Down (almost quiescent) states. In cortex, they occur simultaneously in cell assemblies in different layers and propagate as traveling waves, a concerted activity at multiple scales whose interplay and role is still under debate. Slow oscillations have been reported to start in deep layers, more specifically in layer 5. Here, we studied the laminar organization of slow oscillations in the anesthetized rat cortex and we found that the activity leading to Up states actually initiates in layer 6, then spreads towards upper layers. Layer 5 cell assemblies have a threshold-like activation that can persist after layer 6 inactivation, giving rise to hysteresis loops like in "flip-flop" computational units. We found that such hysteresis is finely tuned by the columnar circuitry depending on the recent history of the local ongoing activity. Furthermore, thalamic inactivation reduced infragranular excitability without affecting the columnar activation pattern. We propose a role for layer 6 acting as a hub unraveling a hierarchy of cortical loops.