Regional Diversity in the Postsynaptic Proteome of the Mouse Brain

Src dependency of the regulation of LTP by alternative splicing of GRIN1 exon 5

Alternative splicing of Grin1 exon 5 regulates induction of long-term potentiation (LTP) at Schaffer collateral-CA1 synapses: LTP in mice lacking the GluN1 exon 5-encoded N1 cassette (GluN1a mice) is significantly increased compared with that in mice compulsorily expressing this exon (GluN1b mice). The mechanism underlying this difference is unknown. Here, we report that blocking the non-receptor tyrosine kinase Src prevents induction of LTP in GluN1a mice but not in GluN1b. We find that activating Src enhances pharmacologically isolated synaptic N-methyl-d-aspartate receptor (NMDAR) currents in GluN1a mice but not in GluN1b. Moreover, we observe that Src activation increases the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor component of Schaffer collateral-evoked excitatory post-synaptic potentials in GluN1a mice, but this increase is prevented by blocking NMDARs. We conclude that at these synapses, NMDARs in GluN1a mice are subject to upregulation by Src that mediates induction of LTP, whereas NMDARs in GluN1b mice are not regulated by Src, leading to Src-resistance of LTP. Thus, we have uncovered that a key regulatory mechanism for synaptic potentiation is gated by differential splicing of exon 5 of Grin1. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Remodeling of the postsynaptic proteome in male mice and marmosets during synapse development

Postsynaptic proteins play crucial roles in synaptic function and plasticity. During brain development, alterations in synaptic number, shape, and stability occur, known as synapse maturation. However, the postsynaptic protein composition changes during development are not fully understood. Here, we show the trajectory of the postsynaptic proteome in developing male mice and common marmosets. Proteomic analysis of mice at 2, 3, 6, and 12 weeks of age shows that proteins involved in synaptogenesis are differentially expressed during this period. Analysis of published transcriptome datasets shows that the changes in postsynaptic protein composition in the mouse brain after 2 weeks of age correlate with gene expression changes. Proteomic analysis of marmosets at 0, 2, 3, 6, and 24 months of age show that the changes in the marmoset brain can be categorized into two parts: the first 2 months and after that. The changes observed in the first 2 months are similar to those in the mouse brain between 2 and 12 weeks of age. The changes observed in marmoset after 2 months old include differential expression of synaptogenesis-related molecules, which hardly overlap with that in mice. Our results provide a comprehensive proteomic resource that underlies developmental synapse maturation in rodents and primates.

Protein 4.1N Plays a Cell Type-Specific Role in Hippocampal Glutamatergic Synapse Regulation

Many glutamatergic synapse proteins contain a 4.1N protein binding domain. However, a role for 4.1N in the regulation of glutamatergic neurotransmission has been controversial. Here, we observe significantly higher expression of protein 4.1N in granule neurons of the dentate gyrus (DG granule neurons) compared with other hippocampal regions. We discover that reducing 4.1N expression in rat DG granule neurons of either sex results in a significant reduction in glutamatergic synapse function that is caused by a decrease in the number of glutamatergic synapses. By contrast, we find reduction of 4.1N expression in hippocampal CA1 pyramidal neurons has no impact on basal glutamatergic neurotransmission. We also find 4.1N's C-terminal domain (CTD) to be nonessential to its role in the regulation of glutamatergic synapses of DG granule neurons. Instead, we show that 4.1N's four-point-one, ezrin, radixin, and moesin (FERM) domain is essential for supporting synaptic AMPA receptor (AMPAR) function in these neurons. Altogether, this work demonstrates a novel, cell type-specific role for protein 4.1N in governing glutamatergic synapse function.SIGNIFICANCE STATEMENT Glutamatergic synapses exhibit immense molecular diversity. In comparison to heavily studied Schaffer collateral, CA1 glutamatergic synapses, significantly less is known about perforant path-dentate gyrus (DG) synapses. Our data demonstrate that compromising 4.1N function in CA1 pyramidal neurons produces no alteration in basal glutamatergic synaptic transmission. However, in DG granule neurons, compromising 4.1N function leads to a significant decrease in the strength of glutamatergic neurotransmission at perforant pathway synapses. Together, our data identifies 4.1N as a cell type-specific regulator of synaptic transmission within the hippocampus and reveals a unique molecular program that governs perforant pathway synapse function.

Synapse-specific diversity of distinct postsynaptic GluN2 subtypes defines transmission strength in spinal lamina I

The unitary postsynaptic response to presynaptic quantal glutamate release is the fundamental basis of excitatory information transfer between neurons. The view, however, of individual glutamatergic synaptic connections in a population as homogenous, fixed-strength units of neural communication is becoming increasingly scrutinized. Here, we used minimal stimulation of individual glutamatergic afferent axons to evoke single synapse resolution postsynaptic responses from central sensory lamina I neurons in an ex vivo adult rat spinal slice preparation. We detected unitary events exhibiting a NMDA receptor component with distinct kinetic properties across synapses conferred by specific GluN2 subunit composition, indicative of GluN2 subtype-based postsynaptic heterogeneity. GluN2A, 2A and 2B, or 2B and 2D synaptic predominance functioned on distinct lamina I neuron types to narrowly, intermediately, or widely tune, respectively, the duration of evoked unitary depolarization events from resting membrane potential, which enabled individual synapses to grade differentially depolarizing steps during temporally patterned afferent input. Our results lead to a model wherein a core locus of proteomic complexity prevails at this central glutamatergic sensory synapse that involves distinct GluN2 subtype configurations. These findings have major implications for subthreshold integrative capacity and transmission strength in spinal lamina I and other CNS regions.

Altered striatal actin dynamics drives behavioral inflexibility in a mouse model of fragile X syndrome

The proteome of glutamatergic synapses is diverse across the mammalian brain and involved in neurodevelopmental disorders (NDDs). Among those is fragile X syndrome (FXS), an NDD caused by the absence of the functional RNA-binding protein FMRP. Here, we demonstrate how the brain region-specific composition of postsynaptic density (PSD) contributes to FXS. In the striatum, the FXS mouse model shows an altered association of the PSD with the actin cytoskeleton, reflecting immature dendritic spine morphology and reduced synaptic actin dynamics. Enhancing actin turnover with constitutively active RAC1 ameliorates these deficits. At the behavioral level, the FXS model displays striatal-driven inflexibility, a typical feature of FXS individuals, which is rescued by exogenous RAC1. Striatal ablation of Fmr1 is sufficient to recapitulate behavioral impairments observed in the FXS model. These results indicate that dysregulation of synaptic actin dynamics in the striatum, a region largely unexplored in FXS, contributes to the manifestation of FXS behavioral phenotypes.

Alterations in the Proteome of Developing Neocortical Synaptosomes in the Absence of MET Signaling Revealed by Comparative Proteomics

Alterations in the expression of genes encoding proteins involved in synapse formation, maturation, and function are a hallmark of many neurodevelopmental and psychiatric disorders. For example, there is reduced neocortical expression of the MET receptor tyrosine kinase (MET) transcript and protein in Autism Spectrum Disorder (ASD) and Rett syndrome. Preclinical in vivo and in vitro models manipulating MET signaling reveal that the receptor modulates excitatory synapse development and maturation in select forebrain circuits. The molecular adaptations underlying the altered synaptic development remain unknown. We performed a comparative mass spectrometry analysis of synaptosomes generated from the neocortex of wild type and Met null mice during the peak of synaptogenesis (postnatal day 14; data are available from ProteomeXchange with identifier PXD033204). The analyses revealed broad disruption of the developing synaptic proteome in the absence of MET, consistent with the localization of MET protein in pre- and postsynaptic compartments, including proteins associated with the neocortical synaptic MET interactome and those encoded by syndromic and ASD risk genes. In addition to an overrepresentation of altered proteins associated with the SNARE complex, multiple proteins in the ubiquitin-proteasome system and associated with the synaptic vesicle, as well as proteins that regulate actin filament organization and synaptic vesicle exocytosis/endocytosis, were disrupted. Taken together, the proteomic changes are consistent with structural and functional changes observed following alterations in MET signaling. We hypothesize that the molecular adaptations following Met deletion may reflect a general mechanism that produces circuit-specific molecular changes due to loss or reduction of synaptic signaling proteins.

An Optimized Comparative Proteomic Approach as a Tool in Neurodegenerative Disease Research

Recent advances in proteomic technologies now allow unparalleled assessment of the molecular composition of a wide range of sample types. However, the application of such technologies and techniques should not be undertaken lightly. Here, we describe why the design of a proteomics experiment itself is only the first step in yielding high-quality, translatable results. Indeed, the effectiveness and/or impact of the majority of contemporary proteomics screens are hindered not by commonly considered technical limitations such as low proteome coverage but rather by insufficient analyses. Proteomic experimentation requires a careful methodological selection to account for variables from sample collection, through to database searches for peptide identification to standardised post-mass spectrometry options directed analysis workflow, which should be adjusted for each study, from determining when and how to filter proteomic data to choosing holistic versus trend-wise analyses for biologically relevant patterns. Finally, we highlight and discuss the difficulties inherent in the modelling and study of the majority of progressive neurodegenerative conditions. We provide evidence (in the context of neurodegenerative research) for the benefit of undertaking a comparative approach through the application of the above considerations in the alignment of publicly available pre-existing data sets to identify potential novel regulators of neuronal stability.

Cell type-specific biotin labeling in vivo resolves regional neuronal and astrocyte proteomic differences in mouse brain

Proteomic profiling of brain cell types using isolation-based strategies pose limitations in resolving cellular phenotypes representative of their native state. We describe a mouse line for cell type-specific expression of biotin ligase TurboID, for in vivo biotinylation of proteins. Using adenoviral and transgenic approaches to label neurons, we show robust protein biotinylation in neuronal soma and axons throughout the brain, allowing quantitation of over 2000 neuron-derived proteins spanning synaptic proteins, transporters, ion channels and disease-relevant druggable targets. Next, we contrast Camk2a-neuron and Aldh1l1-astrocyte proteomes and identify brain region-specific proteomic differences within both cell types, some of which might potentially underlie the selective vulnerability to neurological diseases. Leveraging the cellular specificity of proteomic labeling, we apply an antibody-based approach to uncover differences in neuron and astrocyte-derived signaling phospho-proteins and cytokines. This approach will facilitate the characterization of cell-type specific proteomes in a diverse number of tissues under both physiological and pathological states.

Synaptic protein interaction networks encode experience by assuming stimulus-specific and brain-region-specific states

A core network of widely expressed proteins within the glutamatergic post-synapse mediates activity-dependent synaptic plasticity throughout the brain, but the specific proteomic composition of synapses differs between brain regions. Here, we address the question, how does proteomic composition affect activity-dependent protein-protein interaction networks (PINs) downstream of synaptic activity? Using quantitative multiplex co-immunoprecipitation, we compare the PIN response of in vivo or ex vivo neurons derived from different brain regions to activation by different agonists or different forms of eyeblink conditioning. We report that PINs discriminate between incoming stimuli using differential kinetics of overlapping and non-overlapping PIN parameters. Further, these "molecular logic rules" differ by brain region. We conclude that although the PIN of the glutamatergic post-synapse is expressed widely throughout the brain, its activity-dependent dynamics show remarkable stimulus-specific and brain-region-specific diversity. This diversity may help explain the challenges in developing molecule-specific drug therapies for neurological disorders.

A single-synapse resolution survey of PSD95-positive synapses in twenty human brain regions

Mapping the molecular composition of individual excitatory synapses across the mouse brain reveals high synapse diversity with each brain region showing a distinct composition of synapse types. As a first step towards systematic mapping of synapse diversity across the human brain, we have labelled and imaged synapses expressing the excitatory synapse protein PSD95 in twenty human brain regions, including 13 neocortical, two subcortical, one hippocampal, one cerebellar and three brainstem regions, in four phenotypically normal individuals. We quantified the number, size and intensity of individual synaptic puncta and compared their regional distributions. We found that each region showed a distinct signature of synaptic puncta parameters. Comparison of brain regions showed that cortical and hippocampal structures are similar, and distinct from those of cerebellum and brainstem. Comparison of synapse parameters from human and mouse brain revealed conservation of parameters, hierarchical organization of brain regions and network architecture. This work illustrates the feasibility of generating a systematic single-synapse resolution atlas of the human brain, a potentially significant resource in studies of brain health and disease.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

Neuroproteomics of the Synapse: Subcellular Quantification of Protein Networks and Signaling Dynamics

One of the most fascinating features of the brain is its ability to adapt to its surroundings. Synaptic plasticity, the dynamic mechanism of functional and structural alterations in synaptic strength, is essential for brain functioning and underlies a variety of processes such as learning and memory. Although the molecular mechanisms underlying such rapid plasticity are not fully understood, a consensus exists on the important role of proteins. The study of these neuronal proteins using neuroproteomics has increased rapidly in the last decades, and advancements in MS-based proteomics have broadened our understanding of neuroplasticity exponentially. In this review, we discuss the trends in MS-based neuroproteomics for the study of synaptic protein-protein interactions and protein signaling dynamics, with a focus on sample types, different labeling and enrichment approaches, and data analysis and interpretation. We highlight studies from the last 5 years, with a focus on synapse structure, composition, functioning, or signaling and finally discuss some recent developments that could further advance the field of neuroproteomics.

Uncovering Statistical Links Between Gene Expression and Structural Connectivity Patterns in the Mouse Brain

Finding links between genes and structural connectivity is of the utmost importance for unravelling the underlying mechanism of the brain connectome. In this study we identify links between the gene expression and the axonal projection density in the mouse brain, by applying a modified version of the Linked ICA method to volumetric data from the Allen Institute for Brain Science for identifying independent sources of information that link both modalities at the voxel level. We performed separate analyses on sets of projections from the visual cortex, the caudoputamen and the midbrain reticular nucleus, and we determined those brain areas, injections and genes that were most involved in independent components that link both gene expression and projection density data, while we validated their biological context through enrichment analysis. We identified representative and literature-validated cortico-midbrain and cortico-striatal projections, whose gene subsets were enriched with annotations for neuronal and synaptic function and related developmental and metabolic processes. The results were highly reproducible when including all available projections, as well as consistent with factorisations obtained using the Dictionary Learning and Sparse Coding technique. Hence, Linked ICA yielded reproducible independent components that were preserved under increasing data variance. Taken together, we have developed and validated a novel paradigm for linking gene expression and structural projection patterns in the mouse mesoconnectome, which can power future studies aiming to relate genes to brain function.

Proteomic insights into synaptic signaling in the brain: the past, present and future

Chemical synapses in the brain connect neurons to form neural circuits, providing the structural and functional bases for neural communication. Disrupted synaptic signaling is closely related to a variety of neurological and psychiatric disorders. In the past two decades, proteomics has blossomed as a versatile tool in biological and biomedical research, rendering a wealth of information toward decoding the molecular machinery of life. There is enormous interest in employing proteomic approaches for the study of synapses, and substantial progress has been made. Here, we review the findings of proteomic studies of chemical synapses in the brain, with special attention paid to the key players in synaptic signaling, i.e., the synaptic protein complexes and their post-translational modifications. Looking toward the future, we discuss the technological advances in proteomics such as data-independent acquisition mass spectrometry (DIA-MS), cross-linking in combination with mass spectrometry (CXMS), and proximity proteomics, along with their potential to untangle the mystery of how the brain functions at the molecular level. Last but not least, we introduce the newly developed synaptomic methods. These methods and their successful applications marked the beginnings of the synaptomics era.

The synapse in traumatic brain injury

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide and is a risk factor for dementia later in life. Research into the pathophysiology of TBI has focused on the impact of injury on the neuron. However, recent advances have shown that TBI has a major impact on synapse structure and function through a combination of the immediate mechanical insult and the ensuing secondary injury processes, leading to synapse loss. In this review, we highlight the role of the synapse in TBI pathophysiology with a focus on the confluence of multiple secondary injury processes including excitotoxicity, inflammation and oxidative stress. The primary insult triggers a cascade of events in each of these secondary processes and we discuss the complex interplay that occurs at the synapse. We also examine how the synapse is impacted by traumatic axonal injury and the role it may play in the spread of tau after TBI. We propose that astrocytes play a crucial role by mediating both synapse loss and recovery. Finally, we highlight recent developments in the field including synapse molecular imaging, fluid biomarkers and therapeutics. In particular, we discuss advances in our understanding of synapse diversity and suggest that the new technology of synaptome mapping may prove useful in identifying synapses that are vulnerable or resistant to TBI.

Molecular Diversity of Glutamatergic and GABAergic Synapses from Multiplexed Fluorescence Imaging

Neuronal synapses contain hundreds of different protein species important for regulating signal transmission. Characterizing differential expression profiles of proteins within synapses in distinct regions of the brain has revealed a high degree of synaptic diversity defined by unique molecular organization. Multiplexed imaging of in vitro rat primary hippocampal culture models at single synapse resolution offers new opportunities for exploring synaptic reorganization in response to chemical and genetic perturbations. Here, we combine 12-color multiplexed fluorescence imaging with quantitative image analysis and machine learning to identify novel synaptic subtypes within excitatory and inhibitory synapses based on the expression profiles of major synaptic components. We characterize differences in the correlated expression of proteins within these subtypes and we examine how the distribution of these synapses is modified following induction of synaptic plasticity. Under chronic suppression of neuronal activity, phenotypic characterization revealed coordinated increases in both excitatory and inhibitory protein levels without changes in the distribution of synaptic subtypes, suggesting concerted events targeting glutamatergic and GABAergic synapses. Our results offer molecular insight into the mechanisms of synaptic plasticity.

The aging mouse brain: cognition, connectivity and calcium

Aging is a complex process that differentially impacts multiple cognitive, sensory, neuronal and molecular processes. Technological innovations now allow for parallel investigation of neuronal circuit function, structure and molecular composition in the brain of awake behaving adult mice. Thus, mice have become a critical tool to better understand how aging impacts the brain. However, a more granular systems-based approach, which considers the impact of age on key features relating to neural processing, is required. Here, we review evidence probing the impact of age on the mouse brain. We focus on a range of processes relating to neuronal function, including cognitive abilities, sensory systems, synaptic plasticity and calcium regulation. Across many systems, we find evidence for prominent age-related dysregulation even before 12 months of age, suggesting that emerging age-related alterations can manifest by late adulthood. However, we also find reports suggesting that some processes are remarkably resilient to aging. The evidence suggests that aging does not drive a parallel, linear dysregulation of all systems, but instead impacts some processes earlier, and more severely, than others. We propose that capturing the more fine-scale emerging features of age-related vulnerability and resilience may provide better opportunities for the rejuvenation of the aged brain.

Prediction of a Cell-Class-Specific Mouse Mesoconnectome Using Gene Expression Data

Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-class specificity would be a major step forward. We analyzed the ability of gene expression patterns to predict cell-class and layer-specific projection patterns and assessed the functional annotations of the most predictive groups of genes. To achieve our goal we used publicly available volumetric gene expression and connectivity data and we trained computational models to learn and predict cell-class and layer-specific axonal projections using gene expression data. Predictions were done in two ways, namely predicting projection strengths using the expression of individual genes and using the co-expression of genes organized in spatial modules, as well as predicting binary forms of projection. For predicting the strength of projections, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r² score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using a dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r² score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function. Taken together, we have demonstrated a prediction workflow that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.

The Synapse Diversity Dilemma: Molecular Heterogeneity Confounds Studies of Synapse Function

Recent studies have shown an unexpectedly high degree of synapse diversity arising from molecular and morphological differences among individual synapses. Diverse synapse types are spatially distributed within individual dendrites, between different neurons, and across and between brain regions, producing the synaptome architecture of the brain. The spatial organization of synapse heterogeneity is important because the physiological activation of heterogeneous excitatory synapses produces a non-uniform spatial output of synaptic potentials, which confounds the interpretation of measurements obtained from population-averaging electrodes, optrodes and biochemical methods that lack single-synapse resolution. Population-averaging measurements cannot distinguish between changes in the composition of populations of synapses and changing synaptic physiology. Here we consider the implications of synapse diversity and its organization into synaptome architecture for studies of synapse physiology, plasticity, development and behavior, and for the interpretation of phenotypes arising from pharmacological and genetic perturbations. We conclude that prevailing models based on population-averaging measurements need reconsideration and that single-synapse resolution physiological recording methods are required to confirm or refute the major synaptic models of behavior.

Estimation of the number of synapses in the hippocampus and brain-wide by volume electron microscopy and genetic labeling

Determining the number of synapses that are present in different brain regions is crucial to understand brain connectivity as a whole. Membrane-associated guanylate kinases (MAGUKs) are a family of scaffolding proteins that are expressed in excitatory glutamatergic synapses. We used genetic labeling of two of these proteins (PSD95 and SAP102), and Spinning Disc confocal Microscopy (SDM), to estimate the number of fluorescent puncta in the CA1 area of the hippocampus. We also used FIB-SEM, a three-dimensional electron microscopy technique, to calculate the actual numbers of synapses in the same area. We then estimated the ratio between the three-dimensional densities obtained with FIB-SEM (synapses/µm³) and the bi-dimensional densities obtained with SDM (puncta/100 µm²). Given that it is impractical to use FIB-SEM brain-wide, we used previously available SDM data from other brain regions and we applied this ratio as a conversion factor to estimate the minimum density of synapses in those regions. We found the highest densities of synapses in the isocortex, olfactory areas, hippocampal formation and cortical subplate. Low densities were found in the pallidum, hypothalamus, brainstem and cerebellum. Finally, the striatum and thalamus showed a wide range of synapse densities.

Proteomic Analysis of Brain Region and Sex-Specific Synaptic Protein Expression in the Adult Mouse Brain

Genetic disruption of synaptic proteins results in a whole variety of human neuropsychiatric disorders including intellectual disability, schizophrenia or autism spectrum disorder (ASD). In a wide range of these so-called synaptopathies a sex bias in prevalence and clinical course has been reported. Using an unbiased proteomic approach, we analyzed the proteome at the interaction site of the pre- and postsynaptic compartment, in the prefrontal cortex, hippocampus, striatum and cerebellum of male and female adult C57BL/6J mice. We were able to reveal a specific repertoire of synaptic proteins in different brain areas as it has been implied before. Additionally, we found a region-specific set of novel synaptic proteins differentially expressed between male and female individuals including the strong ASD candidates DDX3X, KMT2C, MYH10 and SET. Being the first comprehensive analysis of brain region-specific synaptic proteomes from male and female mice, our study provides crucial information on sex-specific differences in the molecular anatomy of the synapse. Our efforts should serve as a neurobiological framework to better understand the influence of sex on synapse biology in both health and disease.

Cellular Mechanisms Contributing to the Functional Heterogeneity of GABAergic Synapses

GABAergic inhibitory neurotransmission contributes to diverse aspects of brain development and adult plasticity, including the expression of complex cognitive processes. This is afforded for in part by the dynamic adaptations occurring at inhibitory synapses, which show great heterogeneity both in terms of upstream signaling and downstream effector mechanisms. Single-particle tracking and live imaging have revealed that complex receptor-scaffold interactions critically determine adaptations at GABAergic synapses. Super-resolution imaging studies have shown that protein interactions at synaptic sites contribute to nano-scale scaffold re-arrangements through post-translational modifications (PTMs), facilitating receptor and scaffold recruitment to synaptic sites. Additionally, plasticity mechanisms may be affected by the protein composition at individual synapses and the type of pre-synaptic input. This mini-review article examines recent discoveries of plasticity mechanisms that are operational within GABAergic synapses and discusses their contribution towards functional heterogeneity in inhibitory neurotransmission.

Editorial for Special Issue: Neuroproteomics

Recent advances in mass spectrometry (MS) instrumentation [...].

Exploiting Gene Expression Profiles for the Automated Prediction of Connectivity between Brain Regions

The brain comprises a complex system of neurons interconnected by an intricate network of anatomical links. While recent studies demonstrated the correlation between anatomical connectivity patterns and gene expression of neurons, using transcriptomic information to automatically predict such patterns is still an open challenge. In this work, we present a completely data-driven approach relying on machine learning (i.e., neural networks) to learn the anatomical connection directly from a training set of gene expression data. To do so, we combined gene expression and connectivity data from the Allen Mouse Brain Atlas to generate thousands of gene expression profile pairs from different brain regions. To each pair, we assigned a label describing the physical connection between the corresponding brain regions. Then, we exploited these data to train neural networks, designed to predict brain area connectivity. We assessed our solution on two prediction problems (with three and two connectivity class categories) involving cortical and cerebellum regions. As demonstrated by our results, we distinguish between connected and unconnected regions with 85% prediction accuracy and good balance of precision and recall. In our future work we may extend the analysis to more complex brain structures and consider RNA-Seq data as additional input to our model.

The Synaptomic Theory of Behavior and Brain Disease

The purpose of this article is to outline a new molecular and synaptic theory of behavior called the "synaptomic theory," named because it is centered on the synaptome-the complement of synapses in the brain. Synaptomic theory posits that synapses are structures of high molecular complexity and vast diversity that are observable in maps of the brain and that these synaptome maps are fundamental to behavior. Synaptome maps are a means of writing or storing information that can be retrieved by the patterns of activity that stimulate synapses. Synaptome maps have the capacity to store large amounts of information, including multiple representations within the same map. The dynamic properties of synapses allow synaptome maps to store dynamic sequences of representations that could serve to program behavioral sequences. Synaptome maps are genetically programmed and experience-dependent, thereby storing innate and learned behaviors, respectively. Although learning occurs by modification of the synapse proteome, it does not require long-term potentiation (LTP) of synaptic weight or growth of new synapses, and the theory predicts that LTP modulates information recall. The spatial architecture of synaptome maps arise from an underlying molecular hierarchy linking the genome to the supramolecular assembly of proteins into complexes and supercomplexes. This molecular hierarchy can explain how genome evolution results in the behavioral repertoire of the organism. Mutations disrupting this molecular hierarchy change the architecture of synaptome maps, potentially accounting for the behavioral phenotypes associated with neurological and psychiatric disorders.

Regulatory mechanisms in postsynaptic phosphorylation networks

The modulation of the postsynaptic signaling machinery by protein phosphorylation has attracted much interest since it is key for the understanding of the regulation of a variety of synaptic functions. While advances in mass spectrometry have allowed us to begin performing large-scale analysis of protein phosphorylation in components of the PSD, the systematic collection of datasets and their functional significance within the context of regulatory signaling networks is in its infancy. Here, we will focus on the composition of the PSD phosphoproteome describing kinase, phosphatase, and protein domain modules involved in the regulation of phosphorylation signaling. We will discuss the impact of synaptic plasticity mechanisms such as long-term potentiation (LTP) in mammalian kinomes and describe the general rules of signaling organization in the PSD phosphoproteome.

Mapping the Proteome of the Synaptic Cleft through Proximity Labeling Reveals New Cleft Proteins

Synapses are specialized neuronal cell-cell contacts that underlie network communication in the mammalian brain. Across neuronal populations and circuits, a diverse set of synapses is utilized, and they differ in their molecular composition to enable heterogenous connectivity patterns and functions. In addition to pre- and post-synaptic specializations, the synaptic cleft is now understood to be an integral compartment of synapses that contributes to their structural and functional organization. Aiming to map the cleft proteome, this study applied a peroxidase-mediated proximity labeling approach and used the excitatory synaptic cell adhesion protein SynCAM 1 fused to horseradish peroxidase (HRP) as a reporter in cultured cortical neurons. This reporter marked excitatory synapses as measured by confocal microcopy and was targeted to the edge zone of the synaptic cleft as determined using 3D dSTORM super-resolution imaging. Proximity labeling with a membrane-impermeant biotin-phenol compound restricted labeling to the cell surface, and Label-Free Quantitation (LFQ) mass spectrometry combined with ratiometric HRP tagging of membrane vs. synaptic surface proteins was used to identify the proteomic content of excitatory clefts. Novel cleft candidates were identified, and Receptor-type tyrosine-protein phosphatase zeta was selected and successfully validated. This study supports the robust applicability of peroxidase-mediated proximity labeling for synaptic cleft proteomics and its potential for understanding synapse heterogeneity in health and changes in diseases such as psychiatric disorders and addiction.