A Proteome-Wide Effect of PHF8 Knockdown on Cortical Neurons Shows Downregulation of Parkinson's Disease-Associated Protein Alpha-Synuclein and Its Interactors.

Synaptic dysfunction may underlie the pathophysiology of Parkinson's disease (PD), a presently incurable condition characterized by motor and cognitive symptoms. Here, we used quantitative proteomics to study the role of PHD Finger Protein 8 (PHF8), a histone demethylating enzyme found to be mutated in X-linked intellectual disability and identified as a genetic marker of PD, in regulating the expression of PD-related synaptic plasticity proteins. Amongst the list of proteins found to be affected by PHF8 knockdown were Parkinson's-disease-associated SNCA (alpha synuclein) and PD-linked genes DNAJC6 (auxilin), SYNJ1 (synaptojanin 1), and the PD risk gene SH3GL2 (endophilin A1). Findings in this study show that depletion of PHF8 in cortical neurons affects the activity-induced expression of proteins involved in synaptic plasticity, synaptic structure, vesicular release and membrane trafficking, spanning the spectrum of pre-synaptic and post-synaptic transmission. Given that the depletion of even a single chromatin-modifying enzyme can affect synaptic protein expression in such a concerted manner, more in-depth studies will be needed to show whether such a mechanism can be exploited as a potential disease-modifying therapeutic drug target in PD.

Selective increase of correlated activity in Arc-positive neurons after chemically induced long-term potentiation in cultured hippocampal neurons.

The activity-dependent expression of immediate-early genes (IEGs) has been utilised to label memory traces. However, their roles in engram specification are incompletely understood. Outstanding questions remain as to whether expression of IEGs can interplay with network properties such as functional connectivity and also if neurons expressing different IEGs are functionally distinct. In order to connect IEG expression at the cellular level with changes in functional-connectivity, we investigated the expression of 2 IEGs, Arc and c-Fos, in cultured hippocampal neurons. Primary neuronal cultures were treated with a chemical cocktail (4-aminopyridine, bicuculline, and forskolin) to increase neuronal activity, IEG expression, and induce chemical long-term potentiation. Neuronal firing is assayed by intracellular calcium imaging using GCaMP6m and expression of IEGs is assessed by immunofluorescence staining. We noted an emergent network property of refinement in network activity, characterized by a global downregulation of correlated activity, together with an increase in correlated activity between subsets of specific neurons. Subsequently, we show that Arc expression correlates with the effects of refinement, as the increase in correlated activity occurs specifically between Arc-positive neurons. The expression patterns of the IEGs c-Fos and Arc strongly overlap, but Arc was more selectively expressed than c-Fos. A subpopulation of neurons positive for both Arc and c-Fos shows increased correlated activity, while correlated firing between Arc+/cFos- neurons is reduced. Our results relate neuronal activity-dependent expression of the IEGs Arc and c-Fos on the individual cellular level to changes in correlated activity of the neuronal network.SIGNIFICANCEEstablishing a stable long-lasting memory requires neuronal network-level changes in connection strengths in a subset of neurons, which together constitute a memory trace or engram. Two genes, c-Fos and Arc, have been implicated to play critical roles in the formation of the engram. They have been studied extensively at the cellular/molecular level, and have been used as markers of memory traces in mice. We have correlated Arc and c-Fos cellular expression with refinement of correlated neuronal activity following pharmacological activation of networks formed by cultured hippocampal neurons. Whereas there is a global loss of correlated activity, Arc-positive neurons show selectively increased correlated activity. Arc is more selectively expressed than c-Fos, but the two genes act together in encoding information about changes in correlated firing.

Familiarity Detection and Memory Consolidation in Cortical Assemblies.

Humans have a large capacity of recognition memory (Dudai, 1997), a fundamental property of higher-order brain functions such as abstraction and generalization (Vogt and Magnussen, 2007). Familiarity is the first step towards recognition memory. We have previously demonstrated using unsupervised neural network simulations that familiarity detection of complex patterns emerges in generic cortical microcircuits with bidirectional synaptic plasticity. It is therefore meaningful to conduct similar experiments on biological neuronal networks to validate these results. Studies of learning and memory in dissociated rodent neuronal cultures remain inconclusive to date. Synchronized network bursts (SNBs) that occur spontaneously and periodically have been speculated to be an intervening factor. By optogenetically stimulating cultured cortical networks with random dot movies (RDMs), we were able to reduce the occurrence of SNBs, after which an ability for familiarity detection emerged: previously seen patterns elicited higher firing rates than novel ones. Differences in firing rate were distributed over the entire network, suggesting that familiarity detection is a system level property. We also studied the change in SNB patterns following familiarity encoding. Support vector machine (SVM) classification results indicate that SNBs may be facilitating memory consolidation of the learned pattern. In addition, using a novel network connectivity probing method, we were able to trace the change in synaptic efficacy induced by familiarity encoding, providing insights on the long-term impact of having SNBs in the cultures.

The effect of Bacopa monnieri on gene expression levels in SH-SY5Y human neuroblastoma cells.

Bacopa monnieri is a plant used as a nootropic in Ayurveda, a 5000-year-old system of traditional Indian medicine. Although both animal and clinical studies supported its role as a memory enhancer, the molecular and cellular mechanism underlying Bacopa's nootropic action are not understood. In this study, we used deep sequencing (RNA-Seq) to identify the transcriptome changes upon Bacopa treatment on SH-SY5Y human neuroblastoma cells. We identified several genes whose expression levels were regulated by Bacopa. Biostatistical analysis of the RNA-Seq data identified biological pathways and molecular functions that were regulated by Bacopa, including regulation of mRNA translation and transmembrane transport, responses to oxidative stress and protein misfolding. Pathway analysis using the Ingenuity platform suggested that Bacopa may protect against brain damage and improve brain development. These newly identified molecular and cellular determinants may contribute to the nootropic action of Bacopa and open up a new direction of investigation into its mechanism of action.

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher's discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits.

Genetic Correction of SOD1 Mutant iPSCs Reveals ERK and JNK Activated AP1 as a Driver of Neurodegeneration in Amyotrophic Lateral Sclerosis.

Although mutations in several genes with diverse functions have been known to cause amyotrophic lateral sclerosis (ALS), it is unknown to what extent causal mutations impinge on common pathways that drive motor neuron (MN)-specific neurodegeneration. In this study, we combined induced pluripotent stem cells-based disease modeling with genome engineering and deep RNA sequencing to identify pathways dysregulated by mutant SOD1 in human MNs. Gene expression profiling and pathway analysis followed by pharmacological screening identified activated ERK and JNK signaling as key drivers of neurodegeneration in mutant SOD1 MNs. The AP1 complex member JUN, an ERK/JNK downstream target, was observed to be highly expressed in MNs compared with non-MNs, providing a mechanistic insight into the specific degeneration of MNs. Importantly, investigations of mutant FUS MNs identified activated p38 and ERK, indicating that network perturbations induced by ALS-causing mutations converge partly on a few specific pathways that are drug responsive and provide immense therapeutic potential.

Molecular Features Underlying Neurodegeneration Identified through In Vitro Modeling of Genetically Diverse Parkinson's Disease Patients.

The fact that Parkinson's disease (PD) can arise from numerous genetic mutations suggests a unifying molecular pathology underlying the various genetic backgrounds. To address this hypothesis, we took an integrated approach utilizing in vitro disease modeling and comprehensive transcriptome profiling to advance our understanding of PD progression and the concordant downstream signaling pathways across divergent genetic predispositions. To model PD in vitro, we generated neurons harboring disease-causing mutations from patient-specific, induced pluripotent stem cells (iPSCs). We observed signs of degeneration in midbrain dopaminergic neurons, reflecting the cardinal feature of PD. Gene expression signatures of PD neurons provided molecular insights into disease phenotypes observed in vitro, including oxidative stress vulnerability and altered neuronal activity. Notably, PD neurons show that elevated RBFOX1, a gene previously linked to neurodevelopmental diseases, underlies a pattern of alternative RNA-processing associated with PD-specific phenotypes.

A novel imaging method for quantitative Golgi localization reveals differential intra-Golgi trafficking of secretory cargoes.

Cellular functions of the Golgi are determined by the unique distribution of its resident proteins. Currently, electron microscopy is required for the localization of a Golgi protein at the sub-Golgi level. We developed a quantitative sub-Golgi localization method based on centers of fluorescence masses of nocodazole-induced Golgi ministacks under conventional optical microscopy. Our method is rapid, convenient, and quantitative, and it yields a practical localization resolution of ∼ 30 nm. The method was validated by the previous electron microscopy data. We quantitatively studied the intra-Golgi trafficking of synchronized secretory membrane cargoes and directly demonstrated the cisternal progression of cargoes from the cis- to the trans-Golgi. Our data suggest that the constitutive efflux of secretory cargoes could be restricted at the Golgi stack, and the entry of the trans-Golgi network in secretory pathway could be signal dependent.

A Neuronal Activity-Dependent Dual Function Chromatin-Modifying Complex Regulates Arc Expression

Chromatin modification is an important epigenetic mechanism underlying neuroplasticity. Histone methylation and acetylation have both been shown to modulate gene expression, but the machinery responsible for mediating these changes in neurons has remained elusive. Here we identify a chromatin-modifying complex containing the histone demethylase PHF8 and the acetyltransferase TIP60 as a key regulator of the activity-induced expression of Arc, an important mediator of synaptic plasticity. Clinically, mutations in PHF8 cause X-linked mental retardation while TIP60 has been implicated in the pathogenesis of Alzheimer's disease. Within minutes of increased synaptic activity, this dual function complex is rapidly recruited to the Arc promoter, where it specifically counteracts the transcriptionally repressive histone mark H3K9me2 to facilitate the formation of the transcriptionally permissive H3K9acS10P, thereby favoring transcriptional activation. Consequently, gain-of-function of the PHF8-TIP60 complex in primary rat hippocampal neurons has a positive effect on early activity-induced Arc gene expression, whereas interfering with the function of this complex abrogates it. A global proteomics screen revealed that the majority of common interactors of PHF8 and TIP60 were involved in mRNA processing, including PSF, an important molecule involved in neuronal gene regulation. Finally, we proceeded to show, using super-resolution microscopy, that PHF8 and TIP60 interact at the single molecule level with PSF, thereby situating this chromatin modifying complex at the crossroads of transcriptional activation. These findings point toward a mechanism by which an epigenetic pathway can regulate neuronal activity-dependent gene transcription, which has implications in the development of novel therapeutics for disorders of learning and memory.

Spatiotemporal memory is an intrinsic property of networks of dissociated cortical neurons.

The ability to process complex spatiotemporal information is a fundamental process underlying the behavior of all higher organisms. However, how the brain processes information in the temporal domain remains incompletely understood. We have explored the spatiotemporal information-processing capability of networks formed from dissociated rat E18 cortical neurons growing in culture. By combining optogenetics with microelectrode array recording, we show that these randomly organized cortical microcircuits are able to process complex spatiotemporal information, allowing the identification of a large number of temporal sequences and classification of musical styles. These experiments uncovered spatiotemporal memory processes lasting several seconds. Neural network simulations indicated that both short-term synaptic plasticity and recurrent connections are required for the emergence of this capability. Interestingly, NMDA receptor function is not a requisite for these short-term spatiotemporal memory processes. Indeed, blocking the NMDA receptor with the antagonist APV significantly improved the temporal processing ability of the networks, by reducing spontaneously occurring network bursts. These highly synchronized events have disastrous effects on spatiotemporal information processing, by transiently erasing short-term memory. These results show that the ability to process and integrate complex spatiotemporal information is an intrinsic property of generic cortical networks that does not require specifically designed circuits.

Stimulus information stored in lasting active and hidden network states is destroyed by network bursts.

In both humans and animals brief synchronizing bursts of epileptiform activity known as interictal epileptiform discharges (IEDs) can, even in the absence of overt seizures, cause transient cognitive impairments (TCI) that include problems with perception or short-term memory. While no evidence from single units is available, it has been assumed that IEDs destroy information represented in neuronal networks. Cultured neuronal networks are a model for generic cortical microcircuits, and their spontaneous activity is characterized by the presence of synchronized network bursts (SNBs), which share a number of properties with IEDs, including the high degree of synchronization and their spontaneous occurrence in the absence of an external stimulus. As a model approach to understanding the processes underlying IEDs, optogenetic stimulation and multielectrode array (MEA) recordings of cultured neuronal networks were used to study whether stimulus information represented in these networks survives SNBs. When such networks are optically stimulated they encode and maintain stimulus information for as long as one second. Experiments involved recording the network response to a single stimulus and trials where two different stimuli were presented sequentially, akin to a paired pulse trial. We broke the sequential stimulus trials into encoding, delay and readout phases and found that regardless of which phase the SNB occurs, stimulus-specific information was impaired. SNBs were observed to increase the mean network firing rate, but this did not translate monotonically into increases in network entropy. It was found that the more excitable a network, the more stereotyped its response was during a network burst. These measurements speak to whether SNBs are capable of transmitting information in addition to blocking it. These results are consistent with previous reports and provide baseline predictions concerning the neural mechanisms by which IEDs might cause TCI.

Nuclear Arc Interacts with the Histone Acetyltransferase Tip60 to Modify H4K12 Acetylation(1,2,3).

Arc is an immediate-early gene whose genetic ablation selectively abrogates long-term memory, indicating a critical role in memory consolidation. Although Arc protein is found at synapses, it also localizes to the neuronal nucleus, where its function is less understood. Nuclear Arc forms a complex with the ß-spectrin isoform ßSpIVΣ5 and associates with PML bodies, sites of epigenetic regulation of gene expression. We report here a novel interaction between Arc and Tip60, a histone-acetyltransferase and subunit of a chromatin-remodelling complex, using biochemistry and super-resolution microscopy in primary rat hippocampal neurons. Arc and ßSpIVΣ5 are recruited to nuclear Tip60 speckles, and the three proteins form a tight complex that localizes to nuclear perichromatin regions, sites of transcriptional activity. Neuronal activity-induced expression of Arc (1) increases endogenous nuclear Tip60 puncta, (2) recruits Tip60 to PML bodies, and (3) increases histone acetylation of Tip60 substrate H4K12, a learning-induced chromatin modification. These mechanisms point to an epigenetic role for Arc in regulating memory consolidation.

Short-term memory in networks of dissociated cortical neurons.

Short-term memory refers to the ability to store small amounts of stimulus-specific information for a short period of time. It is supported by both fading and hidden memory processes. Fading memory relies on recurrent activity patterns in a neuronal network, whereas hidden memory is encoded using synaptic mechanisms, such as facilitation, which persist even when neurons fall silent. We have used a novel computational and optogenetic approach to investigate whether these same memory processes hypothesized to support pattern recognition and short-term memory in vivo, exist in vitro. Electrophysiological activity was recorded from primary cultures of dissociated rat cortical neurons plated on multielectrode arrays. Cultures were transfected with ChannelRhodopsin-2 and optically stimulated using random dot stimuli. The pattern of neuronal activity resulting from this stimulation was analyzed using classification algorithms that enabled the identification of stimulus-specific memories. Fading memories for different stimuli, encoded in ongoing neural activity, persisted and could be distinguished from each other for as long as 1 s after stimulation was terminated. Hidden memories were detected by altered responses of neurons to additional stimulation, and this effect persisted longer than 1 s. Interestingly, network bursts seem to eliminate hidden memories. These results are similar to those that have been reported from similar experiments in vivo and demonstrate that mechanisms of information processing and short-term memory can be studied using cultured neuronal networks, thereby setting the stage for therapeutic applications using this platform.

Effects of synaptic connectivity on liquid state machine performance.

The Liquid State Machine (LSM) is a biologically plausible computational neural network model for real-time computing on time-varying inputs, whose structure and function were inspired by the properties of neocortical columns in the central nervous system of mammals. The LSM uses spiking neurons connected by dynamic synapses to project inputs into a high dimensional feature space, allowing classification of inputs by linear separation, similar to the approach used in support vector machines (SVMs). The performance of a LSM neural network model on pattern recognition tasks mainly depends on its parameter settings. Two parameters are of particular interest: the distribution of synaptic strengths and synaptic connectivity. To design an efficient liquid filter that performs desired kernel functions, these parameters need to be optimized. We have studied performance as a function of these parameters for several models of synaptic connectivity. The results show that in order to achieve good performance, large synaptic weights are required to compensate for a small number of synapses in the liquid filter, and vice versa. In addition, a larger variance of the synaptic weights results in better performance for LSM benchmark problems. We also propose a genetic algorithm-based approach to evolve the liquid filter from a minimum structure with no connections, to an optimized kernel with a minimal number of synapses and high classification accuracy. This approach facilitates the design of an optimal LSM with reduced computational complexity. Results obtained using this genetic programming approach show that the synaptic weight distribution after evolution is similar in shape to that found in cortical circuitry.

Nuclear deformation during breast cancer cell transmigration.

Metastasis is the main cause of cancer mortality. During this process, cancer cells dislodge from a primary tumor, enter the circulation and form secondary tumors in distal organs. It is poorly understood how these cells manage to cross the tight syncytium of endothelial cells that lines the capillaries. Such capillary transmigration would require a drastic change in cell shape. We have therefore developed a microfluidic platform to study the transmigration of cancer cells. The device consists of an array of microchannels mimicking the confined spaces encountered. A thin glass coverslip bottom allows high resolution imaging of cell dynamics. We show that nuclear deformation is a critical and rate-limiting step for transmigration of highly metastatic human breast cancer cells. Transmigration was significantly reduced following the treatment with a protein methyltransferase inhibitor, suggesting that chromatin condensation might play an important role. Since transmigration is critical for cancer metastasis, this new platform may be useful for developing improved cancer therapies.

Emergent bursting and synchrony in computer simulations of neuronal cultures.

Experimental studies of neuronal cultures have revealed a wide variety of spiking network activity ranging from sparse, asynchronous firing to distinct, network-wide synchronous bursting. However, the functional mechanisms driving these observed firing patterns are not well understood. In this work, we develop an in silico network of cortical neurons based on known features of similar in vitro networks. The activity from these simulations is found to closely mimic experimental data. Furthermore, the strength or degree of network bursting is found to depend on a few parameters: the density of the culture, the type of synaptic connections, and the ratio of excitatory to inhibitory connections. Network bursting gradually becomes more prominent as either the density, the fraction of long range connections, or the fraction of excitatory neurons is increased. Interestingly, biologically prevalent values of parameters result in networks that are at the transition between strong bursting and sparse firing. Using principal components analysis, we show that a large fraction of the variance in firing rates is captured by the first component for bursting networks. These results have implications for understanding how information is encoded at the population level as well as for why certain network parameters are ubiquitous in cortical tissue.

The NR1 M3 domain mediates allosteric coupling in the N-methyl-D-aspartate receptor.

N-Methyl-D-aspartate (NMDA) receptors play a critical role in both development of the central nervous system and adult neuroplasticity. However, although the NMDA receptor presents a valuable therapeutic target, the relationship between its structure and functional properties has yet to be fully elucidated. To further explore the mechanism of receptor activation, we characterized two gain-of-function mutations within the NR1 M3 segment, a transmembrane domain proposed to couple ligand binding and channel opening. Both mutants (A7Q and A7Y) displayed significant glycine-independent currents, indicating that their M3 domains may preferentially adopt a more activated conformation. Substituted cysteine modification experiments revealed that the glycine binding clefts of both A7Q and A7Y are inaccessible to modifying reagents and resistant to competitive antagonism. These data suggest that perturbation of M3 can stabilize the ligand binding domain in a closed cleft conformation, even in the absence of agonist. Both mutants also displayed significant glutamate-independent current and insensitivity to glutamate-site antagonism, indicating partial activation by either glycine or glutamate alone. Furthermore, A7Q and A7Y increased accessibility of the NR2 M3 domain, providing evidence for intersubunit coupling at the transmembrane level and suggesting that these NR1 mutations dominate the properties of the intact heteromeric receptor. The equivalent mutations in NR2 did not exhibit comparable phenotypes, indicating that the NR1 and NR2 M3 domains may play different functional roles. In summary, our data demonstrate that the NR1 M3 segment is functionally coupled to key structural domains in both the NR1 and NR2 subunits.

Constitutive activation of the N-methyl-D-aspartate receptor via cleft-spanning disulfide bonds.

Although the N-methyl-D-aspartate (NMDA) receptor plays a critical role in the central nervous system, many questions remain regarding the relationship between its structure and functional properties. In particular, the involvement of ligand-binding domain closure in determining agonist efficacy, which has been reported in other glutamate receptor subtypes, remains unresolved. To address this question, we designed dual cysteine point mutations spanning the NR1 and NR2 ligand-binding clefts, aiming to stabilize these domains in closed cleft conformations. Two mutants, E522C/I691C in NR1 (EI) and K487C/N687C in NR2 (KN) were found to exhibit significant glycine- and glutamate-independent activation, respectively, and co-expression of the two subunits produced a constitutively active channel. However, both individual mutants could be activated above constitutive levels in a concentration-dependent manner, indicating that cleft closure does not completely prevent agonist association. Interestingly, whereas the NR2 KN disulfide was found to potentiate channel gating and M3 accessibility, NR1 EI exhibited the opposite phenotype, suggesting that the EI disulfide may trap the NR1 ligand-binding domain in a lower efficacy conformation. Furthermore, both mutants affected agonist sensitivity at the opposing subunit, suggesting that closed cleft stabilization may contribute to coupling between the subunits. These results support a correlation between cleft stability and receptor activation, providing compelling evidence for the Venus flytrap mechanism of glutamate receptor domain closure.

Arc/Arg3.1 translation is controlled by convergent N-methyl-D-aspartate and Gs-coupled receptor signaling pathways.

Arc/Arg3.1 is an immediate early gene whose expression is necessary for the late-phase of long-term potentiation (LTP) and memory consolidation. Whereas pathways regulating Arc transcription have been extensively investigated, less is known about the role of post-transcriptional mechanisms in Arc expression. Fluorescence microscopy experiments in cultured hippocampal neurons revealed that Arc protein level was dramatically increased by activation of the cAMP-dependent protein kinase (PKA) pathway, which is implicated in long-term memory. A PKA-dependent increase in Arc protein level was observed after pharmacological or synaptic activation of N-methyl-D-aspartate (NMDA) receptors, which play a critical role in both LTP induction and learning. Arc protein was also up-regulated by activation of PKA through G(s)-coupled dopamine and beta-adrenergic receptors, which regulate the late-phase of LTP and memory. When agonists for the NMDA and G(s)-coupled receptors were co-applied, they had an additive effect on Arc protein expression. Interestingly, G(s)-coupled receptor stimulation was ineffective in the presence of an NMDA receptor antagonist, suggesting calcium influx through the NMDA receptor plays a gating role in this pathway. Stimulation of the cAMP/PKA pathway did not affect Arc mRNA level or protein stability, identifying translational efficacy as the main determinant of Arc protein expression level. It is concluded that efficient Arc translation requires NMDA receptor activity, whereas a further enhancement can be achieved with activation of G(s)-coupled receptors. These experiments have, therefore, revealed remarkable similarities in the signaling pathways that control Arc expression and those that regulate LTP, learning, and memory.

Activity-regulated cytoskeleton-associated protein Arc/Arg3.1 binds to spectrin and associates with nuclear promyelocytic leukemia (PML) bodies.

Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) is an immediate early gene, whose expression in the central nervous system is induced by specific patterns of synaptic activity. Arc is required for the late-phase of long-term potentiation (LTP) and memory consolidation, and has been implicated in AMPA receptor trafficking. Since Arc's molecular function remains incompletely understood, we have determined its subcellular localization in cultured hippocampal neurons and HEK 293T cells. Fluorescence microscopy experiments revealed that both endogenous and exogenous Arc protein was primarily found in the nucleus, where it concentrated in puncta associated with promyelocytic leukemia (PML) bodies, proposed sites of transcriptional regulation. Arc co-localized and interacted with the betaIV spectrin splice variant betaSpIVSigma5, a nuclear spectrin isoform associated with PML bodies and the nuclear matrix. A small region of Arc containing the coiled-coil domain is also restricted to beta-spectrin-positive puncta, while the isolated spectrin homology domain is diffusely localized. Finally, Arc and betaSpIVSigma5 synergistically increased the number of PML bodies. These results suggest that Arc functions as a spectrin-binding protein, forming a complex that may provide a role at sites of transcriptional regulation within the nucleus.