Dysbindin-1 regulates mitochondrial fission and gamma oscillations.

Mitochondria are cellular ATP generators. They are dynamic structures undergoing fission and fusion. While much is known about the mitochondrial fission machinery, the mechanism of initiating fission and the significance of fission to neurophysiology are largely unclear. Gamma oscillations are synchronized neural activities that impose a great energy challenge to synapses. The cellular mechanism of fueling gamma oscillations has yet to be defined. Here, we show that dysbindin-1, a protein decreased in the brain of individuals with schizophrenia, is required for neural activity-induced fission by promoting Drp1 oligomerization. This process is engaged by gamma-frequency activities and in turn, supports gamma oscillations. Gamma oscillations and novel object recognition are impaired in dysbindin-1 null mice. These defects can be ameliorated by increasing mitochondrial fission. These findings identify a molecular mechanism for activity-induced mitochondrial fission, a role of mitochondrial fission in gamma oscillations, and mitochondrial fission as a potential target for improving cognitive functions.

Widespread promoter methylation of synaptic plasticity genes in long-term potentiation in the adult brain in vivo.

BACKGROUND: DNA methylation is a key modulator of gene expression in mammalian development and cellular differentiation, including neurons. To date, the role of DNA modifications in long-term potentiation (LTP) has not been explored. RESULTS: To investigate the occurrence of DNA methylation changes in LTP, we undertook the first detailed study to describe the methylation status of all known LTP-associated genes during LTP induction in the dentate gyrus of live rats. Using a methylated DNA immunoprecipitation (MeDIP)-array, together with previously published matched RNA-seq and public histone modification data, we discover widespread changes in methylation status of LTP-genes. We further show that the expression of many LTP-genes is correlated with their methylation status. We show that these correlated genes are enriched for RNA-processing, active histone marks, and specific transcription factors. These data reveal that the synaptic activity-evoked methylation changes correlates with pre-existing activation of the chromatin landscape. Finally, we show that methylation of Brain-derived neurotrophic factor (Bdnf) CpG-islands correlates with isoform switching from transcripts containing exon IV to exon I. CONCLUSIONS: Together, these data provide the first evidence of widespread regulation of methylation status in LTP-associated genes.

Paraneoplastic CDR2 and CDR2L antibodies affect Purkinje cell calcium homeostasis.

Paraneoplastic cerebellar degeneration (PCD) is characterized by loss of Purkinje cells (PCs) associated with progressive pancerebellar dysfunction in the presence of onconeural Yo antibodies. These antibodies recognize the cerebellar degeneration-related antigens CDR2 and CDR2L. Response to PCD therapy is disappointing due to limited understanding of the neuropathological mechanisms. Here, we report the pathological role of CDR antibodies on the calcium homeostasis in PCs. We developed an antibody-mediated PCD model based on co-incubation of cerebellar organotypic slice culture with human patient serum or rabbit CDR2 and CDR2L antibodies. The CDR antibody-induced pathology was investigated by high-resolution multiphoton imaging and biochemical analysis. Both human and rabbit CDR antibodies were rapidly internalized by PCs and led to reduced immunoreactivity of calbindin D28K (CB) and L7/Pcp-2 as well as reduced dendritic arborizations in the remaining PCs. Washout of the CDR antibodies partially recovered CB immunoreactivity, suggesting a transient structural change in CB calcium-binding site. We discovered that CDR2 and CB co-immunoprecipitate. Furthermore, the expression levels of voltage-gated calcium channel Cav2.1, protein kinase C gamma and calcium-dependent protease, calpain-2, were increased after CDR antibody internalization. Inhibition of these signaling pathways prevented or attenuated CDR antibody-induced CB and L7/Pcp-2 immunoreactivity loss, morphological changes and increased protein expression. These results signify that CDR antibody internalization causes dysregulation of cell calcium homeostasis. Hence, drugs that modulate these events may represent novel neuroprotective therapies that limit the damaging effects of CDR antibodies and prevent PC neurodegeneration.

Enhanced cognitive function and antidepressant-like effects after krill oil supplementation in rats.

BACKGROUND: The purpose of the study was to evaluate the effects of krill oil (KO) on cognition and depression-like behaviour in rats. METHODS: Cognition was assessed using the Aversive Light Stimulus Avoidance Test (ALSAT). The Unavoidable Aversive Light Stimulus (UALST) and the Forced Swimming Test (FST) were used to evaluate the antidepressant-like effects of KO. Imipramine (IMIP) was used as the antidepressant reference substance. RESULTS: After 7 weeks of KO intake, both males and females treated with KO were significantly better in discriminating between the active and the inactive levers in the ALSAT from day 1 of training (p<0.01). Both KO and IMIP prevented resignation/depression on the third day in the UALST. Similarly, a shorter immobility time was observed for the KO and IMIP groups compared to the control in the FST (p<0.001). These data support a robust antidepressant-like potential and beneficial cognitive effect of KO. Changes in expression of synaptic plasticity-related genes in the prefrontal cortex and hippocampus were also investigated. mRNA for brain-derived neurotrophic factor (Bdnf) was specifically upregulated in the hippocampus of female rats receiving 7 weeks of KO supplementation (p=0.04) and a similar trend was observed in males (p=0.08). Males also exhibited an increase in prefrontal cortex expression of Arc mRNA, a key protein in long-term synaptic plasticity (p=0.05). IMIP induced clear effects on several plasticity related genes including Bdnf and Arc. CONCLUSIONS: These results indicate that active components (eicosapentaenoic acid, docosahexaenoic acid and astaxanthin) in KO facilitate learning processes and provide antidepressant-like effects. Our findings also suggest that KO might work through different physiological mechanisms than IMIP.

Consolidation and translation regulation.

mRNA translation, or protein synthesis, is a major component of the transformation of the genetic code into any cellular activity. This complicated, multistep process is divided into three phases: initiation, elongation, and termination. Initiation is the step at which the ribosome is recruited to the mRNA, and is regarded as the major rate-limiting step in translation, while elongation consists of the elongation of the polypeptide chain; both steps are frequent targets for regulation, which is defined as a change in the rate of translation of an mRNA per unit time. In the normal brain, control of translation is a key mechanism for regulation of memory and synaptic plasticity consolidation, i.e., the off-line processing of acquired information. These regulation processes may differ between different brain structures or neuronal populations. Moreover, dysregulation of translation leads to pathological brain function such as memory impairment. Both normal and abnormal function of the translation machinery is believed to lead to translational up-regulation or down-regulation of a subset of mRNAs. However, the identification of these newly synthesized proteins and determination of the rates of protein synthesis or degradation taking place in different neuronal types and compartments at different time points in the brain demand new proteomic methods and system biology approaches. Here, we discuss in detail the relationship between translation regulation and memory or synaptic plasticity consolidation while focusing on a model of cortical-dependent taste learning task and hippocampal-dependent plasticity. In addition, we describe a novel systems biology perspective to better describe consolidation.

Temporal origin of nestedness in interaction networks.

Nestedness is a common property of communication, finance, trade, and ecological networks. In networks with high levels of nestedness, the link positions of low-degree nodes (those with few links) form nested subsets of the link positions of high-degree nodes (those with many links), leading to matrix representations with characteristic upper triangular or staircase patterns. Recent theoretical work has connected nestedness to the functionality of complex systems and has suggested that it is a structural by-product of the skewed degree distributions often seen in empirical data. However, mechanisms for generating nestedness remain poorly understood, limiting the connections that can be made between system processes and observed network structures. Here, we show that a simple probabilistic model based on phenology-the timing of copresences among interaction partners-can produce nested structures and correctly predict around two-thirds of interactions in two fish market networks and around one-third of interactions in 22 plant-pollinator networks. Notably, the links most readily explained by frequent actor copresences appear to form a backbone of nested interactions, with the remaining interactions attributable to opportunistic interactions or preferences for particular interaction partners that are not routinely available.

Domain Growth in Polycrystalline Graphene.

Graphene is a two-dimensional carbon allotrope which exhibits exceptional properties, making it highly suitable for a wide range of applications. Practical graphene fabrication often yields a polycrystalline structure with many inherent defects, which significantly influence its performance. In this study, we utilize a Monte Carlo approach based on the optimized Wooten, Winer and Weaire (WWW) algorithm to simulate the crystalline domain coarsening process of polycrystalline graphene. Our sample configurations show excellent agreement with experimental data. We conduct statistical analyses of the bond and angle distribution, temporal evolution of the defect distribution, and spatial correlation of the lattice orientation that follows a stretched exponential distribution. Furthermore, we thoroughly investigate the diffusion behavior of defects and find that the changes in domain size follow a power-law distribution. We briefly discuss the possible connections of these results to (and differences from) domain growth processes in other statistical models, such as the Ising dynamics. We also examine the impact of buckling of polycrystalline graphene on the crystallization rate under substrate effects. Our findings may offer valuable guidance and insights for both theoretical investigations and experimental advancements.

Reducing societal impacts of SARS-CoV-2 interventions through subnational implementation.

To curb the initial spread of SARS-CoV-2, many countries relied on nation-wide implementation of non-pharmaceutical intervention measures, resulting in substantial socio-economic impacts. Potentially, subnational implementations might have had less of a societal impact, but comparable epidemiological impact. Here, using the first COVID-19 wave in the Netherlands as a case in point, we address this issue by developing a high-resolution analysis framework that uses a demographically stratified population and a spatially explicit, dynamic, individual contact-pattern based epidemiology, calibrated to hospital admissions data and mobility trends extracted from mobile phone signals and Google. We demonstrate how a subnational approach could achieve similar level of epidemiological control in terms of hospital admissions, while some parts of the country could stay open for a longer period. Our framework is exportable to other countries and settings, and may be used to develop policies on subnational approach as a better strategic choice for controlling future epidemics.

Structural dynamics of polycrystalline graphene.

The exceptional properties of the two-dimensional material graphene make it attractive for multiple functional applications, whose large-area samples are typically polycrystalline. Here, we study the mechanical properties of graphene in computer simulations and connect these to the experimentally relevant mechanical properties. In particular, we study the fluctuations in the lateral dimensions of the periodic simulation cell. We show that over short timescales, both the area A and the aspect ratio B of the rectangular periodic box show diffusive behavior under zero external field during dynamical evolution, with diffusion coefficients D_{A} and D_{B} that are related to each other. At longer times, fluctuations in A are bounded, while those in B are not. This makes the direct determination of D_{B} much more accurate, from which D_{A} can then be derived indirectly. We then show that the dynamic behavior of polycrystalline graphene under external forces can also be derived from D_{A} and D_{B} via the Nernst-Einstein relation. Additionally, we study how the diffusion coefficients depend on structural properties of the polycrystalline graphene, in particular, the density of defects.

Hidden dependence of spreading vulnerability on topological complexity.

Many dynamical phenomena in complex systems concern spreading that plays out on top of networks with changing architecture over time-commonly known as temporal networks. A complex system's proneness to facilitate spreading phenomena, which we abbreviate as its "spreading vulnerability," is often surmised to be related to the topology of the temporal network featured by the system. Yet, cleanly extracting spreading vulnerability of a complex system directly from the topological information of the temporal network remains a challenge. Here, using data from a diverse set of real-world complex systems, we develop the "entropy of temporal entanglement" as a quantity to measure topological complexities of temporal networks. We show that this parameter-free quantity naturally allows for topological comparisons across vastly different complex systems. Importantly, by simulating three different types of stochastic dynamical processes playing out on top of temporal networks, we demonstrate that the entropy of temporal entanglement serves as a quantitative embodiment of the systems' spreading vulnerability, irrespective of the details of the processes. In being able to do so, i.e., in being able to quantitatively extract a complex system's proneness to facilitate spreading phenomena from topology, this entropic measure opens itself for applications in a wide variety of natural, social, biological, and engineered systems.

Quantifying agent impacts on contact sequences in social interactions.

Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population. Social interactions determine the contact network among individuals, while spreading, requiring individual-to-individual transmission, takes place on top of the network. Studying the topological aspects of a contact network, therefore, not only has the potential of leading to valuable insights into how the behavior of individuals impacts spreading phenomena, but it may also open up possibilities for devising effective behavioral interventions. Because of the temporal nature of interactions-since the topology of the network, containing who is in contact with whom, when, for how long, and in which precise sequence, varies (rapidly) in time-analyzing them requires developing network methods and metrics that respect temporal variability, in contrast to those developed for static (i.e., time-invariant) networks. Here, by means of event mapping, we propose a method to quantify how quickly agents mingle by transforming temporal network data of agent contacts. We define a novel measure called contact sequence centrality, which quantifies the impact of an individual on the contact sequences, reflecting the individual's behavioral potential for spreading. Comparing contact sequence centrality across agents allows for ranking the impact of agents and identifying potential 'behavioral super-spreaders'. The method is applied to social interaction data collected at an art fair in Amsterdam. We relate the measure to the existing network metrics, both temporal and static, and find that (mostly at longer time scales) traditional metrics lose their resemblance to contact sequence centrality. Our work highlights the importance of accounting for the sequential nature of contacts when analyzing social interactions.

Translocation of DNA molecules through nanopores with salt gradients: the role of osmotic flow.

Recent experiments of translocation of double-stranded DNA through nanopores [M. Wanunu et al., Nature Nanotech. 5, 160 (2009)] reveal that the DNA capture rate can be significantly influenced by a salt gradient across the pore. We show that osmotic flow combined with electrophoretic effects can quantitatively explain the experimental data on the salt-gradient dependence of the capture rate.

Structural modes of a polymer in the repton model.

Using extensive computer simulations, the behavior of the structural modes-more precisely, the eigenmodes of a phantom Rouse polymer-are characterized for a polymer in the three-dimensional repton model and are used to study the polymer dynamics at time scales well before the tube renewal. Although these modes are not the eigenmodes for a polymer in the repton model, we show that numerically the modes maintain a high degree of statistical independence. The correlations in the mode amplitudes decay exponentially with (p∕N)(2)A(t), in which p is the mode number, N is the polymer length, and A(t) is a single function shared by all modes. In time, the quantity A(t) causes an exponential decay for the mode amplitude correlation functions for times <1; a stretched exponential with an exponent 1∕2 between times 1 and τ(R) ∼ N(2), the time-scale for diffusion of tagged reptons along the contour of the polymer; and again an exponential decay for times t > τ(R). Having assumed statistical independence and the validity of a single function A(t) for all modes, we compute the temporal behavior of three structural quantities: the vectorial distance between the positions of the middle monomer and the center-of-mass, the end-to-end vector, and the vector connecting two nearby reptons around the middle of the polymer. Furthermore, we study the mean-squared displacement of the center-of-mass and the middle repton, and their relation with the temporal behavior of the modes.

Cascading dominates large-scale disruptions in transport over complex networks.

The core functionality of many socio-technical systems, such as supply chains, (inter)national trade and human mobility, concern transport over large geographically-spread complex networks. The dynamical intertwining of many heterogeneous operational elements, agents and locations are oft-cited generic factors to make these systems prone to large-scale disruptions: initially localised perturbations amplify and spread over the network, leading to a complete standstill of transport. Our level of understanding of such phenomena, let alone the ability to anticipate or predict their evolution in time, remains rudimentary. We approach the problem with a prime example: railways. Analysing spreading of train delays on the network by building a physical model, supported by data, reveals that the emergence of large-scale disruptions rests on the dynamic interdependencies among multiple 'layers' of operational elements (resources and services). The interdependencies provide pathways for the so-called delay cascading mechanism, which gets activated when, constrained by local unavailability of on-time resources, already-delayed ones are used to operate new services. Cascading locally amplifies delays, which in turn get transported over the network to give rise to new constraints elsewhere. This mechanism is a rich addition to some well-understood ones in, e.g., epidemiological spreading, or the spreading of rumours and opinions over (contact) networks, and stimulates rethinking spreading dynamics on complex networks. Having these concepts built into the model provides it with the ability to predict the evolution of large-scale disruptions in the railways up to 30-60 minutes up front. For transport systems, our work suggests that possible alleviation of constraints as well as a modular operational approach would arrest cascading, and therefore be effective measures against large-scale disruptions.

miR-936 is Increased in Schizophrenia and Inhibits Neural Development and AMPA Receptor-Mediated Synaptic Transmission.

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression and play important roles in the development and function of synapses. miR-936 is a primate-specific miRNA increased in the dorsolateral prefrontal cortex (DLPFC) of individuals with schizophrenia. The significance of miR-936 increase to schizophrenia is unknown. Here, we show that miR-936 in the human DLPFC is enriched in cortical layer 2/3 and expressed in glutamatergic and GABAergic neurons. miR-936 is increased from layers 2 to 6 of the DLPFC in schizophrenia samples. In neurons derived from human induced pluripotent stem cells (iNs), miR-936 reduces the number of excitatory synapses, inhibits AMPA receptor-mediated synaptic transmission, and increases intrinsic excitability. These effects are mediated by its target gene TMOD2. These results indicate that miR-936 restricts the number of synapses and the strength of glutamatergic synaptic transmission by inhibiting TMOD2 expression. miR-936 upregulation in the DLPFC, therefore, can reduce glutamatergic synapses and weaken excitatory synaptic transmission, which underlie the synaptic pathology and hypofrontality in schizophrenia.

Characterizing neural phase-space trajectories via Principal Louvain Clustering.

BACKGROUND: With the growing size and richness of neuroscience datasets in terms of dimension, volume, and resolution, identifying spatiotemporal patterns in those datasets is increasingly important. Multivariate dimension-reduction methods are particularly adept at addressing these challenges. NEW METHOD: In this paper, we propose a novel method, which we refer to as Principal Louvain Clustering (PLC), to identify clusters in a low-dimensional data subspace, based on time-varying trajectories of spectral dynamics across multisite local field potential (LFP) recordings in awake behaving mice. Data were recorded from prefrontal cortex, hippocampus, and parietal cortex in eleven mice while they explored novel and familiar environments. RESULTS: PLC-identified subspaces and clusters showed high consistency across animals, and were modulated by the animals' ongoing behavior. CONCLUSIONS: PLC adds to an important growing literature on methods for characterizing dynamics in high-dimensional datasets, using a smaller number of parameters. The method is also applicable to other kinds of datasets, such as EEG or MEG.

Mitophagy in the basolateral amygdala mediates increased anxiety induced by aversive social experience.

Psychosocial stress is a common risk factor for anxiety disorders. The cellular mechanism for the anxiogenic effect of psychosocial stress is largely unclear. Here, we show that chronic social defeat (CSD) stress in mice causes mitochondrial impairment, which triggers the PINK1-Parkin mitophagy pathway selectively in the amygdala. This mitophagy elevation causes excessive mitochondrial elimination and consequent mitochondrial deficiency. Mitochondrial deficiency in the basolateral amygdalae (BLA) causes weakening of synaptic transmission in the BLA-BNST (bed nucleus of the stria terminalis) anxiolytic pathway and increased anxiety. The CSD-induced increase in anxiety-like behaviors is abolished in Pink1-/- and Park2-/- mice and alleviated by optogenetic activation of the BLA-BNST synapse. This study identifies an unsuspected role of mitophagy in psychogenetic-stress-induced anxiety elevation and reveals that mitochondrial deficiency is sufficient to increase anxiety and underlies the psychosocial-stress-induced anxiety increase. Mitochondria and mitophagy, therefore, can be potentially targeted to ameliorate anxiety.

Novel translational control in Arc-dependent long term potentiation consolidation in vivo.

Regulation of translation factor activity plays a major role in protein synthesis-dependent forms of synaptic plasticity. We examined translational control across the critical period of Arc synthesis underlying consolidation of long term potentiation (LTP) in the dentate gyrus of intact, anesthetized rats. LTP induction by high frequency stimulation (HFS) evoked phosphorylation of the cap-binding protein eukaryotic initiation factor 4E (eIF4E) and dephosphorylation of eIF2alpha on a protracted time course matching the time-window of Arc translation. Local infusion of the ERK inhibitor U0126 inhibited LTP maintenance and Arc protein expression, blocked changes in eIF4E and eIF2alpha phosphorylation state, and prevented initiation complex (eIF4F) formation. Surprisingly, inhibition of the mTOR protein complex 1 (mTORC1) with rapamycin did not impair LTP maintenance or Arc synthesis nor did it inhibit eIF4F formation or phosphorylation of eIF4E. Rapamycin nonetheless blocked mTOR signaling to p70 S6 kinase and ribosomal protein S6 and inhibited synthesis of components of the translational machinery. Using immunohistochemistry and in situ hybridization, we show that Arc protein expression depends on dual, ERK-dependent transcription and translation. Arc translation is selectively blocked by pharmacological inhibition of mitogen-activated protein kinase-interacting kinase (MNK), the kinase coupling ERK to eIF4E phosphorylation. Furthermore, MNK signaling was required for eIF4F formation. These results support a dominant role for ERK-MNK signaling in control of translational initiation and Arc synthesis during LTP consolidation in the dentate gyrus. In contrast, mTORC1 signaling is activated but nonessential for Arc synthesis and LTP. The work, thus, identifies translational control mechanisms uniquely tuned to Arc-dependent LTP consolidation in live rats.

Differential regulation of mature and precursor microRNA expression by NMDA and metabotropic glutamate receptor activation during LTP in the adult dentate gyrus in vivo.

Regulation of microRNA (miRNA) expression and function in the context of activity-dependent synaptic plasticity in the adult brain is little understood. Here, we examined miRNA expression during long-term potentiation (LTP) in the dentate gyrus of adult anesthetized rats. Microarray expression profiling identified a subpopulation of regulated mature miRNAs 2 h after the induction of LTP by high-frequency stimulation (HFS) of the medial perforant pathway. Real-time polymerase chain reaction analysis confirmed modest upregulation of miR-132 and miR-212, and downregulation of miR-219, while no changes occurred at 10 min post-HFS. Surprisingly, pharmacological blockade of N-methyl-d-aspartate receptor (NMDAR)-dependent LTP enhanced expression of these mature miRNAs. This HFS-evoked expression was abolished by local infusion of the group 1 metabotropic glutamate receptor (mGluR) antagonist, (RS)-1-aminoindan-1,5-dicarboxylic acid (AIDA). AIDA had no effect on LTP induction or maintenance, but blocked activity-dependent depotentiation of LTP. Turning to the analysis of miRNA precursors, we show that HFS elicits 50-fold elevations of primary (pri) and precursor (pre) miR-132/212 that is transcription dependent and mGluR dependent, but insensitive to NMDAR blockade. Primary miR-219 expression was unchanged during LTP. In situ hybridization showed upregulation of the pri-miR-132/212 cluster restricted to dentate granule cell somata. Thus, HFS induces transcription miR-132/212 that is mGluR dependent and functionally correlated with depotentiation rather than LTP. In contrast, NMDAR activation selectively downregulates mature miR-132, -212 and -219 levels, indicating accelerated decay of these mature miRNAs. This study demonstrates differential regulation of primary and mature miRNA expression by mGluR and NMDAR signaling following LTP induction, the function of which remains to be defined.

Dynamics of bacteriophage genome ejection in vitro and in vivo.

Bacteriophages, phages for short, are viruses of bacteria. The majority of phages contain a double-stranded DNA genome packaged in a capsid at a density of ∼500 mg ml(-1). This high density requires substantial compression of the normal B-form helix, leading to the conjecture that DNA in mature phage virions is under significant pressure, and that pressure is used to eject the DNA during infection. A large number of theoretical, computer simulation and in vitro experimental studies surrounding this conjecture have revealed many--though often isolated and/or contradictory--aspects of packaged DNA. This prompts us to present a unified view of the statistical physics and thermodynamics of DNA packaged in phage capsids. We argue that the DNA in a mature phage is in a (meta)stable state, wherein electrostatic self-repulsion is balanced by curvature stress due to confinement in the capsid. We show that in addition to the osmotic pressure associated with the packaged DNA and its counterions, there are four different pressures within the capsid: pressure on the DNA, hydrostatic pressure, the pressure experienced by the capsid and the pressure associated with the chemical potential of DNA ejection. Significantly, we analyze the mechanism of force transmission in the packaged DNA and demonstrate that the pressure on DNA is not important for ejection. We derive equations showing a strong hydrostatic pressure difference across the capsid shell. We propose that when a phage is triggered to eject by interaction with its receptor in vitro, the (thermodynamic) incentive of water molecules to enter the phage capsid flushes the DNA out of the capsid. In vivo, the difference between the osmotic pressures in the bacterial cell cytoplasm and the culture medium similarly results in a water flow that drags the DNA out of the capsid and into the bacterial cell.