Do Place Cells Dream of Deceptive Moves in a Signaling Game?

We consider the possibility of applying game theory to analysis and modeling of neurobiological systems. Specifically, the basic properties and features of information asymmetric signaling games are considered and discussed as having potential to explain diverse neurobiological phenomena; we focus on neuronal action potential discharge that can represent cognitive variables in memory and purposeful behavior. We begin by arguing that there is a pressing need for conceptual frameworks that can permit analysis and integration of information and explanations across many scales of biological function including gene regulation, molecular and biochemical signaling, cellular and metabolic function, neuronal population, and systems level organization to generate plausible hypotheses across these scales. Developing such integrative frameworks is crucial if we are to understand cognitive functions like learning, memory, and perception. The present work focuses on systems neuroscience organized around the connected brain regions of the entorhinal cortex and hippocampus. These areas are intensely studied in rodent subjects as model neuronal systems that undergo activity-dependent synaptic plasticity to form neuronal circuits and represent memories and spatial knowledge used for purposeful navigation. Examples of cognition-related spatial information in the observed neuronal discharge of hippocampal place cell populations and medial entorhinal head-direction cell populations are used to illustrate possible challenges to information maximization concepts. It may be natural to explain these observations using the ideas and features of information asymmetric signaling games.

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing.

The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.

Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers.

A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n = 26) and recent-onset schizophrenia patients (n = 36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F = 10.75, P = 0.002, Q = 0.024 and F = 21.58, P = 2.8 × 10-5, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10-5, Q = 0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66-0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n = 34) from healthy controls (n = 39) with an AUC of 0.75 (95% CI: 0.64-0.86), and also differentiated schizophrenia patients (n = 22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n = 68), with an AUC of 0.83 (95% CI: 0.75-0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.

Rapid Identification of Druggable Targets and the Power of the PHENotype SIMulator for Effective Drug Repurposing in COVID-19.

The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with very few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which - by leveraging available transcriptomic and proteomic databases - allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both > 96%) the viral effects on cellular host-immune response, resulting in a specific cellular SARS-CoV-2 signature and ii) utilize this specific signature to narrow down promising repurposable therapeutic strategies. Powered by this tool, coupled with domain expertise, we have identified several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential new druggable targets in COVID-19 pathogenesis.

Exploring cellular markers of metabolic syndrome in peripheral blood mononuclear cells across the neuropsychiatric spectrum.

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy.

ANERGY TO SYNERGY-THE ENERGY FUELING THE RXCOVEA FRAMEWORK.

We write to introduce our novel group formed to confront some of the issues raised by the COVID-19 pandemic. Information about the group, which we named "cure COVid for Ever and for All" (RxCOVEA), its dynamic membership (changing regularly), and some of its activities-described in more technical detail for expert perusal and commentary-are available upon request.

Exploring the neuropsychiatric spectrum using high-content functional analysis of single-cell signaling networks.

Neuropsychiatric disorders overlap in symptoms and share genetic risk factors, challenging their current classification into distinct diagnostic categories. Novel cross-disorder approaches are needed to improve our understanding of the heterogeneous nature of neuropsychiatric diseases and overcome existing bottlenecks in their diagnosis and treatment. Here we employ high-content multi-parameter phospho-specific flow cytometry, fluorescent cell barcoding and automated sample preparation to characterize ex vivo signaling network responses (n = 1764) measured at the single-cell level in B and T lymphocytes across patients diagnosed with four major neuropsychiatric disorders: autism spectrum condition (ASC), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ; n = 25 each), alongside matched healthy controls (n = 100). We identified 25 nodes (individual cell subtype-epitope-ligand combinations) significantly altered relative to the control group, with variable overlap between different neuropsychiatric diseases and heterogeneously expressed at the level of each individual patient. Reconstruction of the diagnostic categories from the altered nodes revealed an overlapping neuropsychiatric spectrum extending from MDD on one end, through BD and SCZ, to ASC on the other end. Network analysis showed that although the pathway structure of the epitopes was broadly preserved across the clinical groups, there were multiple discrete alterations in network connectivity, such as disconnections within the antigen/integrin receptor pathway and increased negative regulation within the Akt1 pathway in CD4+ T cells from ASC and SCZ patients, in addition to increased correlation of Stat1 (pY701) and Stat5 (pY694) responses in B cells from BD and MDD patients. Our results support the "dimensional" approach to neuropsychiatric disease classification and suggest potential novel drug targets along the neuropsychiatric spectrum.

Alteration of Neuronal Excitability and Short-Term Synaptic Plasticity in the Prefrontal Cortex of a Mouse Model of Mental Illness.

Using a genetic mouse model that faithfully recapitulates a DISC1 genetic alteration strongly associated with schizophrenia and other psychiatric disorders, we examined the impact of this mutation within the prefrontal cortex. Although cortical layering, cytoarchitecture, and proteome were found to be largely unaffected, electrophysiological examination of the mPFC revealed both neuronal hyperexcitability and alterations in short-term synaptic plasticity consistent with enhanced neurotransmitter release. Increased excitability of layer II/III pyramidal neurons was accompanied by consistent reductions in voltage-activated potassium currents near the action potential threshold as well as by enhanced recruitment of inputs arising from superficial layers to layer V. We further observed reductions in both the paired-pulse ratios and the enhanced short-term depression of layer V synapses arising from superficial layers consistent with enhanced neurotransmitter release at these synapses. Recordings from layer II/III pyramidal neurons revealed action potential widening that could account for enhanced neurotransmitter release. Significantly, we found that reduced functional expression of the voltage-dependent potassium channel subunit Kv1.1 substantially contributes to both the excitability and short-term plasticity alterations that we observed. The underlying dysregulation of Kv1.1 expression was attributable to cAMP elevations in the PFC secondary to reduced phosphodiesterase 4 activity present in Disc1 deficiency and was rescued by pharmacological blockade of adenylate cyclase. Our results demonstrate a potentially devastating impact of Disc1 deficiency on neural circuit function, partly due to Kv1.1 dysregulation that leads to a dual dysfunction consisting of enhanced neuronal excitability and altered short-term synaptic plasticity.SIGNIFICANCE STATEMENT Schizophrenia is a profoundly disabling psychiatric illness with a devastating impact not only upon the afflicted but also upon their families and the broader society. Although the underlying causes of schizophrenia remain poorly understood, a growing body of studies has identified and strongly implicated various specific risk genes in schizophrenia pathogenesis. Here, using a genetic mouse model, we explored the impact of one of the most highly penetrant schizophrenia risk genes, DISC1, upon the medial prefrontal cortex, the region believed to be most prominently dysfunctional in schizophrenia. We found substantial derangements in both neuronal excitability and short-term synaptic plasticity-parameters that critically govern neural circuit information processing-suggesting that similar changes may critically, and more broadly, underlie the neural computational dysfunction prototypical of schizophrenia.

Cell Type-Specific Effects of Mutant DISC1: A Proteomics Study.

Despite the recent progress in psychiatric genetics, very few studies have focused on genetic risk factors in glial cells that, compared to neurons, can manifest different molecular pathologies underlying psychiatric disorders. In order to address this issue, we studied the effects of mutant disrupted in schizophrenia 1 (DISC1), a genetic risk factor for schizophrenia, in cultured primary neurons and astrocytes using an unbiased mass spectrometry-based proteomic approach. We found that selective expression of mutant DISC1 in neurons affects a wide variety of proteins predominantly involved in neuronal development (e.g., SOX1) and vesicular transport (Rab proteins), whereas selective expression of mutant DISC1 in astrocytes produces changes in the levels of mitochondrial (GDPM), nuclear (TMM43) and cell adhesion (ECM2) proteins. The present study demonstrates that DISC1 variants can perturb distinct molecular pathways in a cell type-specific fashion to contribute to psychiatric disorders through heterogenic effects in diverse brain cells.

Synaptic vesicle dynamic changes in a model of fragile X.

BACKGROUND: Fragile X syndrome (FXS) is a single-gene disorder that is the most common heritable cause of intellectual disability and the most frequent monogenic cause of autism spectrum disorders (ASD). FXS is caused by an expansion of trinucleotide repeats in the promoter region of the fragile X mental retardation gene (Fmr1). This leads to a lack of fragile X mental retardation protein (FMRP), which regulates translation of a wide range of messenger RNAs (mRNAs). The extent of expression level alterations of synaptic proteins affected by FMRP loss and their consequences on synaptic dynamics in FXS has not been fully investigated. METHODS: Here, we used an Fmr1 knockout (KO) mouse model to investigate the molecular mechanisms underlying FXS by monitoring protein expression changes using shotgun label-free liquid-chromatography mass spectrometry (LC-MS(E)) in brain tissue and synaptosome fractions. FXS-associated candidate proteins were validated using selected reaction monitoring (SRM) in synaptosome fractions for targeted protein quantification. Furthermore, functional alterations in synaptic release and dynamics were evaluated using live-cell imaging, and interpretation of synaptic dynamics differences was investigated using electron microscopy. RESULTS: Key findings relate to altered levels of proteins involved in GABA-signalling, especially in the cerebellum. Further exploration using microscopy studies found reduced synaptic vesicle unloading of hippocampal neurons and increased vesicle unloading in cerebellar neurons, which suggests a general decrease of synaptic transmission. CONCLUSIONS: Our findings suggest that FMRP is a regulator of synaptic vesicle dynamics, which supports the role of FMRP in presynaptic functions. Taken together, these studies provide novel insights into the molecular changes associated with FXS.

Munc18-1 redistributes in nerve terminals in an activity- and PKC-dependent manner.

Munc18-1 is a soluble protein essential for synaptic transmission. To investigate the dynamics of endogenous Munc18-1 in neurons, we created a mouse model expressing fluorescently tagged Munc18-1 from the endogenous munc18-1 locus. We show using fluorescence recovery after photobleaching in hippocampal neurons that the majority of Munc18-1 trafficked through axons and targeted to synapses via lateral diffusion together with syntaxin-1. Munc18-1 was strongly expressed at presynaptic terminals, with individual synapses showing a large variation in expression. Axon-synapse exchange rates of Munc18-1 were high: during stimulation, Munc18-1 rapidly dispersed from synapses and reclustered within minutes. Munc18-1 reclustering was independent of syntaxin-1, but required calcium influx and protein kinase C (PKC) activity. Importantly, a PKC-insensitive Munc18-1 mutant did not recluster. We show that synaptic Munc18-1 levels correlate with synaptic strength, and that synapses that recruit more Munc18-1 after stimulation have a larger releasable vesicle pool. Hence, PKC-dependent dynamic control of Munc18-1 levels enables individual synapses to tune their output during periods of activity.

The need for a comprehensive molecular characterization of autism spectrum disorders.

Autism spectrum disorders (ASD) are a heterogeneous group of disorders which have complex behavioural phenotypes. Although ASD is a highly heritable neuropsychiatric disorder, genetic research alone has not provided a profound understanding of the underlying causes. Recent developments using biochemical tools such as transcriptomics, proteomics and cellular models, will pave the way to gain new insights into the underlying pathological pathways. This review addresses the state-of-the-art in the search for molecular biomarkers for ASD. In particular, the most important findings in the biochemical field are highlighted and the need for establishing streamlined interaction between behavioural studies, genetics and proteomics is stressed. Eventually, these approaches will lead to suitable translational ASD models and, therefore, a better disease understanding which may facilitate novel drug discovery efforts in this challenging field.