Conserved cell types with divergent features in human versus mouse cortex

Establishment of human cerebral organoid systems to model early neural development and assess the central neurotoxicity of environmental toxins

JOURNAL/nrgr/04.03/01300535-202501000-00032/figure1/v/2024-05-14T021156Z/r/image-tiff Human brain development is a complex process, and animal models often have significant limitations. To address this, researchers have developed pluripotent stem cell-derived three-dimensional structures, known as brain-like organoids, to more accurately model early human brain development and disease. To enable more consistent and intuitive reproduction of early brain development, in this study, we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid culture. This involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation, resulting in a new type of human brain organoid system. This cerebral organoid system replicated the temporospatial characteristics of early human brain development, including neuroepithelium derivation, neural progenitor cell production and maintenance, neuron differentiation and migration, and cortical layer patterning and formation, providing more consistent and reproducible organoids for developmental modeling and toxicology testing. As a proof of concept, we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental toxins. Brain organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns, including bursts of cortical cell death and premature differentiation. Cadmium exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity, accompanied by compensatory cell proliferation at ectopic locations. The convenience, flexibility, and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental, neurological, and neurotoxicological studies.

Evolutionary neurogenomics at single-cell resolution

The human brain is composed of increasingly recognized heterogeneous cell types. Applying single-cell genomics to brain tissue can elucidate relative cell type proportions as well as differential gene expression and regulation among humans and other species. Here, we review recent studies that utilized high-throughput genomics approaches to compare brains among species at single-cell resolution. These studies identified genomic elements that are similar among species as well as evolutionary novelties on the human lineage. We focus on those human-relevant innovations and discuss the biological implications of these modifications. Finally, we discuss areas of comparative single-cell genomics that remain unexplored either due to needed technological advances or due to biological availability at the brain region or species level.

Persistent sodium currents in neurons: potential mechanisms and pharmacological blockers

Persistent sodium current (INaP) is an important activity-dependent regulator of neuronal excitability. It is involved in a variety of physiological and pathological processes, including pacemaking, prolongation of sensory potentials, neuronal injury, chronic pain and diseases such as epilepsy and amyotrophic lateral sclerosis. Despite its importance, neither the molecular basis nor the regulation of INaP are sufficiently understood. Of particular significance is a solid knowledge and widely accepted consensus about pharmacological tools for analysing the function of INaP and for developing new therapeutic strategies. However, the literature on INaP is heterogeneous, with varying definitions and methodologies used across studies. To address these issues, we provide a systematic review of the current state of knowledge on INaP, with focus on mechanisms and effects of this current in the central nervous system. We provide an overview of the specificity and efficacy of the most widely used INaP blockers: amiodarone, cannabidiol, carbamazepine, cenobamate, eslicarbazepine, ethosuximide, gabapentin, GS967, lacosamide, lamotrigine, lidocaine, NBI-921352, oxcarbazepine, phenytoine, PRAX-562, propofol, ranolazine, riluzole, rufinamide, topiramate, valproaic acid and zonisamide. We conclude that there is strong variance in the pharmacological effects of these drugs, and in the available information. At present, GS967 and riluzole can be regarded bona fide INaP blockers, while phenytoin and lacosamide are blockers that only act on the slowly inactivating component of sodium currents.

Ultrasound pulse repetition frequency preferentially activates different neuron populations independent of cell type

Objective. Transcranial ultrasound (US) stimulation serves as an external input to a neuron, and thus the evoked response relies on neurons' intrinsic properties. Neural activity is limited to a couple hundred hertz and often exhibits preference to input frequencies. Accordingly, US pulsed at specific physiologic pulse repetition frequencies (PRFs) may selectively engage neurons with the corresponding input frequency preference. However, most US parametric studies examine the effects of supraphysiologic PRFs. It remains unclear whether pulsing US at different physiologic PRFs could activate distinct neurons in the awake mammalian brain.Approach. We recorded cellular calcium responses of individual motor cortex neurons to US pulsed at PRFs of 10, 40, and 140 Hz in awake mice. We compared the evoked responses across these PRFs in the same neurons. To further understand the cell-type dependent effects, we categorized the recorded neurons as parvalbumin positive fast spiking interneurons or putative excitatory neurons and analyzed single-cell mechanosensitive channel expression in mice and humans using the Allen Brain Institute's RNA-sequencing databases.Main results. We discovered that many neurons were preferentially activated by only one PRF and different PRFs selectively engaged distinct neuronal populations. US-evoked cellular calcium responses exhibited the same characteristics as those naturally occurring during spiking, suggesting that US increases intrinsic neuronal activity. Furthermore, evoked responses were similar between fast-spiking inhibitory neurons and putative excitatory neurons. Thus, variation in individual neuron's cellular properties dominates US-evoked response heterogeneity, consistent with our observed cell-type independent expression patterns of mechanosensitive channels across individual neurons in mice and humans. Finally, US transiently increased network synchrony without producing prolonged over-synchronization that could be detrimental to neural circuit functions.Significance. These results highlight the feasibility of activating distinct neuronal subgroups by varying PRF and the potential to improve neuromodulation effects by combining physiologic PRFs.

Transcriptomic pathology of neocortical microcircuit cell types across psychiatric disorders

Psychiatric disorders such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are characterized by altered cognition and mood, brain functions that depend on information processing by cortical microcircuits. We hypothesized that psychiatric disorders would display cell type-specific transcriptional alterations in neuronal subpopulations that make up cortical microcircuits: excitatory pyramidal (PYR) neurons and vasoactive intestinal peptide- (VIP), somatostatin- (SST), and parvalbumin- (PVALB) expressing inhibitory interneurons. Using laser capture microdissection followed by RNA sequencing (LCM-seq), we performed cell type-specific molecular profiling of subgenual anterior cingulate cortex, a region implicated in mood and cognitive control. We sequenced libraries from 130 whole cells pooled per neuronal subtype (VIP, SST, PVALB, superficial and deep PYR) in 76 subjects from the University of Pittsburgh Brain Tissue Donation Program, evenly split between MDD, BD and SCZ subjects and healthy controls (totaling 380 bulk transcriptomes from ~50,000 neurons). We identified hundreds of differentially expressed (DE) genes and biological pathways across disorders and neuronal subtypes, with the vast majority in interneurons, particularly PVALB. While DE genes were unique to each cell type, there was a partial overlap across disorders for genes involved in the formation and maintenance of neuronal circuits. We observed coordinated alterations in biological pathways between select pairs of microcircuit cell types, also partially shared across disorders. Finally, DE genes coincided with known risk variants from psychiatric genome-wide association studies, suggesting cell type-specific convergence between genetic and transcriptomic risk for psychiatric disorders. Our study suggests transdiagnostic cortical microcircuit pathology in SCZ, BD, and MDD and sets the stage for larger-scale studies investigating how cell circuit-based changes contribute to shared psychiatric risk.

Human-derived monoclonal autoantibodies as interrogators of cellular proteotypes in the brain

A major aim of neuroscience is to identify and model the functional properties of neural cells whose dysfunction underlie neuropsychiatric illness. In this article, we propose that human-derived monoclonal autoantibodies (HD-mAbs) are well positioned to selectively target and manipulate neural subpopulations as defined by their protein expression; that is, cellular proteotypes. Recent technical advances allow for efficient cloning of autoantibodies from neuropsychiatric patients. These HD-mAbs can be introduced into animal models to gain biological and pathobiological insights about neural proteotypes of interest. Protein engineering can be used to modify, enhance, silence, or confer new functional properties to native HD-mAbs, thereby enhancing their versatility. Finally, we discuss the challenges and limitations confronting HD-mAbs as experimental research tools for neuroscience.

Single-cell RNA sequencing illuminates the ontogeny, conservation and diversification of cartilaginous and bony fish lymphocytes

Elucidating cellular architecture and cell-type evolution across species is central to understanding immune system function and susceptibility to disease. Adaptive immunity is a shared trait of the common ancestor of cartilaginous and bony fishes. However, evolutionary features of lymphocytes in these two jawed vertebrates remain unclear. Here, we present a single-cell RNA sequencing atlas of immune cells from cartilaginous (white-spotted bamboo shark) and bony (zebrafish and Chinese tongue sole) fishes. Cross-species comparisons show that the same cell types across different species exhibit similar transcriptional profiles. In the bamboo shark, we identify a phagocytic B cell population expressing several pattern recognition receptors, as well as a T cell sub-cluster co-expressing both T and B cell markers. In contrast to a division by function in the bony fishes, we show close linkage and poor functional specialization among lymphocytes in the cartilaginous fish. Our cross-species single-cell comparison presents a resource for uncovering the origin and evolution of the gnathostome immune system.

Human-unique brain cell clusters are associated with learning disorders and human episodic memory activity

The advanced evolution of the human cerebral cortex forms the basis for our high-level cognitive functions. Through a comparative analysis of single-nucleus transcriptome data from the human neocortex and that of chimpanzees, macaques, and marmosets, we discovered 20 subgroups of cell types unique to the human brain, which include 11 types of excitatory neurons. Many of these human-unique cell clusters exhibit significant overexpression of genes regulated by human-specific enhancers. Notably, these specific cell clusters also express genes associated with disease risk, particularly those related to brain dysfunctions like learning disorders. Furthermore, genes linked to cortical thickness and human episodic memory encoding activities show heightened expression within these cell subgroups. These findings underscore the critical role of human brain-unique cell clusters in the evolution of human brain functions.

Single-cell DNA methylation analysis tool Amethyst reveals distinct noncanonical methylation patterns in human glial cells

Single-cell sequencing technologies have revolutionized biomedical research by enabling deconvolution of cell type-specific properties in highly heterogeneous tissue. While robust tools have been developed to handle bioinformatic challenges posed by single-cell RNA and ATAC data, options for emergent modalities such as methylation are much more limited, impeding the utility of results. Here we present Amethyst, a comprehensive R package for atlas-scale single-cell methylation sequencing data analysis. Amethyst begins with base-level methylation calls and expedites batch integration, doublet detection, dimensionality reduction, clustering, cell type annotation, differentially methylated region calling, and interpretation of results, facilitating rapid data interaction in a local environment. We introduce the workflow using published single-cell methylation human peripheral blood mononuclear cell (PBMC) and human cortex data. We further leverage Amethyst on an atlas-scale brain dataset to describe a noncanonical methylation pattern in human astrocytes and oligodendrocytes, challenging the notion that this form of methylation is principally relevant to neurons in the brain. Tools such as Amethyst will increase accessibility to single-cell methylation data analysis, catalyzing research progress across diverse contexts.

ADAR3 modulates neuronal differentiation and regulates mRNA stability and translation

ADAR3 is a catalytically inactive member of the family of adenosine deaminases acting on RNA (ADARs). Here we have investigated its function in the context of the developing mouse brain. The expression of ADAR3 gradually increases throughout embryogenesis and drops after birth. Using primary cortical neurons, we show that ADAR3 is only expressed in a subpopulation of in vitro differentiated neurons, which suggests specific functions rather than being a general regulator of ADAR editing in the brain. The analysis of the ADAR3 interactome suggested a role in mRNA stability and translation, and we show that expression of ADAR3 in a neuronal cell line that is otherwise ADAR3-negative changes the expression and stability of a large number of mRNAs. Notably, we show that ADAR3 associates with polysomes and inhibits translation. We propose that ADAR3 binds to target mRNAs and stabilizes them in non-productive polysome complexes. Interestingly, the expression of ADAR3 downregulates genes related to neuronal differentiation and inhibits neurofilament outgrowth in vitro. In summary, we propose that ADAR3 negatively regulates neuronal differentiation, and that it does so by regulating mRNA stability and translation in an editing-independent manner.

Expression of activity-regulated transcripts in pyramidal neurons across the cortical visuospatial working memory network in unaffected comparison individuals and individuals with schizophrenia

Visuospatial working memory (vsWM), which is impaired in schizophrenia (SZ), is mediated by multiple cortical regions including the primary (V1) and association (V2) visual, posterior parietal (PPC) and dorsolateral prefrontal (DLPFC) cortices. In these regions, parvalbumin (PV) or somatostatin (SST) GABA neurons are altered in SZ as reflected in lower levels of activity-regulated transcripts. As PV and SST neurons receive excitatory inputs from neighboring pyramidal neurons, we hypothesized that levels of activity-regulated transcripts are also lower in pyramidal neurons in these regions. Thus, we quantified levels of four activity-regulated, pyramidal neuron-selective transcripts, namely adenylate cyclase-activating polypeptide-1 (ADCYAP1), brain-derived neurotrophic factor (BDNF), neuronal pentraxin-2 (NPTX2) and neuritin-1 (NRN1) mRNAs, in V1, V2, PPC and DLPFC from unaffected comparison and SZ individuals. In SZ, BDNF and NPTX2 mRNA levels were lower across all four regions, whereas ADCYAP1 and NRN1 mRNA levels were lower in V1 and V2. The regional pattern of deficits in BDNF and NPTX2 mRNAs was similar to that in transcripts in PV and SST neurons in SZ. These findings suggest that lower activity of pyramidal neurons expressing BDNF and/or NPTX2 mRNAs might contribute to alterations in PV and SST neurons across the vsWM network in SZ.

Characterization of reduced astrocyte creatine kinase levels in Alzheimer's disease

The creatine-phosphocreatine cycle serves as a crucial temporary energy buffering system in the brain, regulated by brain creatine kinase (CKB), in maintaining Adenosine triphosphate (ATP) levels. Alzheimer's disease (AD) has been linked to increased CKB oxidation and loss of its regulatory function, although specific pathological processes and affected cell types remain unclear. In our study, cerebral cortex samples from individuals with AD, dementia with Lewy bodies (DLB), and age-matched controls were analyzed using antibody-based methods to quantify CKB levels and assess alterations associated with disease processes. Two independently validated antibodies exclusively labeled astrocytes in the human cerebral cortex. Combining immunofluorescence (IF) and mass spectrometry (MS), we explored CKB availability in AD and DLB cases. IF and Western blot analysis demonstrated a loss of CKB immunoreactivity correlated with increased plaque load, severity of tau pathology, and Lewy body pathology. However, transcriptomics data and targeted MS demonstrated unaltered total CKB levels, suggesting posttranslational modifications (PTMs) affecting antibody binding. This aligns with altered efficiency at proteolytic cleavage sites indicated in the targeted MS experiment. These findings highlight that the proper function of astrocytes, understudied in the brain compared with neurons, is highly affected by PTMs. Reduction in ATP levels within astrocytes can disrupt ATP-dependent processes, such as the glutamate-glutamine cycle. As CKB and the creatine-phosphocreatine cycle are important in securing constant ATP availability, PTMs in CKB, and astrocyte dysfunction may disturb homeostasis, driving excitotoxicity in the AD brain. CKB and its activity could be promising biomarkers for monitoring early-stage energy deficits in AD.

Graph Fourier transform for spatial omics representation and analyses of complex organs

Spatial omics technologies decipher functional components of complex organs at cellular and subcellular resolutions. We introduce Spatial Graph Fourier Transform (SpaGFT) and apply graph signal processing to a wide range of spatial omics profiling platforms to generate their interpretable representations. This representation supports spatially variable gene identification and improves gene expression imputation, outperforming existing tools in analyzing human and mouse spatial transcriptomics data. SpaGFT can identify immunological regions for B cell maturation in human lymph nodes Visium data and characterize variations in secondary follicles using in-house human tonsil CODEX data. Furthermore, it can be integrated seamlessly into other machine learning frameworks, enhancing accuracy in spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%. Notably, SpaGFT detects rare subcellular organelles, such as Cajal bodies and Set1/COMPASS complexes, in high-resolution spatial proteomics data. This approach provides an explainable graph representation method for exploring tissue biology and function.

Single-nucleus RNA-sequencing of orbitofrontal cortex in rat model of methamphetamine-induced sensitization

The behavioral sensitization, characterized by escalated behavioral responses triggered by recurrent exposure to psychostimulants, involves neurobiological mechanisms that are brain-region and cell-type specific. Enduring neuroadaptive changes have been observed in response to methamphetamine (METH) within the orbitofrontal cortex (OFC), the cell-type specific transcriptional alterations in response to METH sensitization remain understudied. In this study, we utilized Single-nucleus RNA-sequencing (snRNA-seq) to profile the gene expression changes in the OFC of a rat METH sensitization model. The analyses of differentially expressed genes (DEGs) unveiled cell-type specific transcriptional reactions associated with METH sensitization, with the most significant alterations documented in microglial cells. Bioinformatic investigations revealed that distinct functional and signaling pathways enriched in microglia-specific DEGs majorly involved in macroautophagy processes and the activation of N-methyl-D-aspartate ionotropic glutamate receptors (NMDAR). To validate the translational relevance of our findings, we analyzed our snRNA-seq data in conjunction with a transcriptomic study of individuals with opioid use disorder (OUD) and a large-scale Genome-Wide Association Studies (GWAS) from multiple externalizing phenotypes related to drug addiction. The validation analysis confirmed the consistent expression changes of key microglial DEGs in human METH addiction. Moreover, the integration with GWAS data revealed associations between addiction risk genes and the DEGs observed in specific cell types, particularly microglia and excitatory neurons. Our study highlights the importance of cell-type specific transcriptional alterations in the OFC in the context of METH sensitization and their potential translational relevance to human drug addiction.

Organotypic culture of post-mortem adult human brain explants exhibits synaptic plasticity

BACKGROUND

Synaptic plasticity is an essential process encoding fine-tuned brain functions, but models to study this process in adult human systems are lacking.

OBJECTIVE

We aim to test whether ex vivo organotypic culture of post-mortem adult brain explants (OPABs) retain synaptic plasticity.

METHODS

OPABs were seeded on 3D microelectrode arrays to measure local field potential (LFP). Paired stimulation of distant electrodes was performed over three days to investigate our capacity to modulate specific neuronal connections.

RESULTS

Long-term potentiation (LTP) or depression (LTD) did not occur within a single day. In contrast, after two and three days of training, OPABs showed a significant modulation of the paired electrodes' response compared to the non-paired electrodes from the same array. This response was alleviated upon treatment with dopamine.

CONCLUSION

Our work highlights that adult human brain explants retain synaptic plasticity, offering novel approaches to neural circuitry in animal-free models.

Pathophysiological mechanisms underlying the development of focal cortical dysplasia and their association with epilepsy: Experimental models as a research approach

Focal cortical dysplasia (FCD) is a structural lesion that is the most common anatomical lesion identified in children, and the second most common in adults with drug-resistant focal-onset epilepsy. These lesions vary in size, location, and histopathological manifestations. FCDs are classified into three subtypes associated with loss-of-function mutations in PI3K/AKT, TSC1/TSC2, RHEB, and DEPDC/NPRL2/NPRL3. During the decades of research into FCD, experimental models have played an irreplaceable role in the research design of studies investigating disease pathogenesis, pathophysiology, and treatment. Further, the establishment of FCD experimental models has moved the field forward by (1) revealing the cellular processes and signaling pathways underlying FCD pathogenesis and (2) varying the methods and materials to study the function of FCD proteins. Currently, FCD experimental models are predominantly murine, with each model providing unique insights into FCD lesions. This review briefly summarizes the pathology and molecular functions of FCD, further comparing the available modeling methods and indexes, as well as the utilization of models, followed by an analysis of the similarities, advantages, and disadvantages between these models and human FCD.

A gene regulatory network-aware graph learning method for cell identity annotation in single-cell RNA-seq data

Cell identity annotation for single-cell transcriptome data is a crucial process for constructing cell atlases, unraveling pathogenesis, and inspiring therapeutic approaches. Currently, the efficacy of existing methodologies is contingent upon specific data sets. Nevertheless, such data are often sourced from various batches, sequencing technologies, tissues, and even species. Notably, the gene regulatory relationship remains unaffected by the aforementioned factors, highlighting the extensive gene interactions within organisms. Therefore, we propose scHGR, an automated annotation tool designed to leverage gene regulatory relationships in constructing gene-mediated cell communication graphs for single-cell transcriptome data. This strategy helps reduce noise from diverse data sources while establishing distant cellular connections, yielding valuable biological insights. Experiments involving 22 scenarios demonstrate that scHGR precisely and consistently annotates cell identities, benchmarked against state-of-the-art methods. Crucially, scHGR uncovers novel subtypes within peripheral blood mononuclear cells, specifically from CD4+ T cells and cytotoxic T cells. Furthermore, by characterizing a cell atlas comprising 56 cell types for COVID-19 patients, scHGR identifies vital factors like IL1 and calcium ions, offering insights for targeted therapeutic interventions.

Efficient fabrication of 3D bioprinted functional sensory neurons using an inducible Neurogenin-2 human pluripotent stem cell line

Three-dimensional (3D) tissue models have gained recognition for their improved ability to mimic the native cell microenvironment compared to traditional two-dimensional models. This progress has been driven by advances in tissue-engineering technologies such as 3D bioprinting, a promising method for fabricating biomimetic living tissues. While bioprinting has succeeded in generating various tissues to date, creating neural tissue models remains challenging. In this context, we present an accelerated approach to fabricate 3D sensory neuron (SN) structures using a transgenic human pluripotent stem cell (hPSC)-line that contains an inducible Neurogenin-2 (NGN2) expression cassette. The NGN2 hPSC line was first differentiated to neural crest cell (NCC) progenitors, then incorporated into a cytocompatible gelatin methacryloyl-based bioink for 3D bioprinting. Upregulated NGN2 expression in the bioprinted NCCs resulted in induced SN (iSN) populations that exhibited specific cell markers, with 3D analysis revealing widespread neurite outgrowth through the scaffold volume. Calcium imaging demonstrated functional activity of iSNs, including membrane excitability properties and voltage-gated sodium channel (NaV) activity. This efficient approach to generate 3D bioprinted iSN structures streamlines the development of neural tissue models, useful for the study of neurodevelopment and disease states and offering translational potential.

Induction of astrocyte reactivity promotes neurodegeneration in human pluripotent stem cell models

Reactive astrocytes are known to exert detrimental effects upon neurons in several neurodegenerative diseases, yet our understanding of how astrocytes promote neurotoxicity remains incomplete, especially in human systems. In this study, we leveraged human pluripotent stem cell (hPSC) models to examine how reactivity alters astrocyte function and mediates neurodegeneration. hPSC-derived astrocytes were induced to a reactive phenotype, at which point they exhibited a hypertrophic profile and increased complement C3 expression. Functionally, reactive astrocytes displayed decreased intracellular calcium, elevated phagocytic capacity, and decreased contribution to the blood-brain barrier. Subsequently, co-culture of reactive astrocytes with a variety of neuronal cell types promoted morphological and functional alterations. Furthermore, when reactivity was induced in astrocytes from patient-specific hPSCs (glaucoma, Alzheimer's disease, and amyotrophic lateral sclerosis), the reactive state exacerbated astrocytic disease-associated phenotypes. These results demonstrate how reactive astrocytes modulate neurodegeneration, significantly contributing to our understanding of a role for reactive astrocytes in neurodegenerative diseases.

Generation of hiPSC-derived brain microvascular endothelial cells using a combination of directed differentiation and transcriptional reprogramming strategies

The blood-brain barrier (BBB), formed by specialized brain microvascular endothelial cells (BMECs), regulates brain function in health and disease. In vitro modeling of the human BBB is limited by the lack of robust hiPSC protocols to generate BMECs. Here, we report generation, transcriptomic and functional characterization of reprogrammed BMECs (rBMECs) by combining hiPSC differentiation into BBB-primed endothelial cells and reprogramming with two BBB transcription factors FOXF2 and ZIC3. rBMECs express a subset of the BBB gene repertoire including tight junctions and transporters, exhibit stronger paracellular barrier properties, lower caveolar-mediated transcytosis, and similar p-Glycoprotein activity compared to primary HBMECs. They can acquire an inflammatory phenotype when treated with oligomeric Aβ42. rBMECs integrate with hiPSC-derived pericytes and astrocytes to form a 3D neurovascular system using the MIMETAS microfluidics platform. This novel 3D system resembles the in vivo BBB at structural and functional levels to enable investigation of pathogenic mechanisms of neurological diseases.

Cell-type-specific effects of age and sex on human cortical neurons

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

BLEND: Probabilistic Cellular Deconvolution with Automated Reference Selection

Cellular deconvolution aims to estimate cell type fractions from bulk transcriptomic and other omics data. Most existing deconvolution methods fail to account for the heterogeneity in cell type-specific (CTS) expression across bulk samples, ignore discrepancies between CTS expression in bulk and cell type reference data, and provide no guidance on cell type reference selection or integration. To address these issues, we introduce BLEND, a hierarchical Bayesian method that leverages multiple reference datasets. BLEND learns the most suitable references for each bulk sample by exploring the convex hulls of references and employs a "bag-of-words" representation for bulk count data for deconvolution. To speed up the computation, we provide an efficient EM algorithm for parameter estimation. Notably, BLEND requires no data transformation, normalization, cell type marker gene selection, or reference quality evaluation. Benchmarking studies on both simulated and real human brain data highlight BLEND's superior performance in various scenarios. The analysis of Alzheimer's disease data illustrates BLEND's application in real data and reference resource integration.

scPriorGraph: constructing biosemantic cell-cell graphs with prior gene set selection for cell type identification from scRNA-seq data

Cell type identification is an indispensable analytical step in single-cell data analyses. To address the high noise stemming from gene expression data, existing computational methods often overlook the biologically meaningful relationships between genes, opting to reduce all genes to a unified data space. We assume that such relationships can aid in characterizing cell type features and improving cell type recognition accuracy. To this end, we introduce scPriorGraph, a dual-channel graph neural network that integrates multi-level gene biosemantics. Experimental results demonstrate that scPriorGraph effectively aggregates feature values of similar cells using high-quality graphs, achieving state-of-the-art performance in cell type identification.

A general principle governing neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans

The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons-layer 2/3 intratelencephalic excitatory neurons-has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.

Early nuclear phenotypes and reactive transformation in human iPSC-derived astrocytes from ALS patients with SOD1 mutations

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the progressive death of motor neurons (MNs). Glial cells play roles in MN degeneration in ALS. More specifically, astrocytes with mutations in the ALS-associated gene Cu/Zn superoxide dismutase 1 (SOD1) promote MN death. The mechanisms by which SOD1-mutated astrocytes reduce MN survival are incompletely understood. To characterize the impact of SOD1 mutations on astrocyte physiology, we generated astrocytes from human induced pluripotent stem cell (iPSC) derived from ALS patients carrying SOD1 mutations, together with control isogenic iPSCs. We report that astrocytes harboring SOD1(A4V) and SOD1(D90A) mutations exhibit molecular and morphological changes indicative of reactive astrogliosis when compared to isogenic astrocytes. We show further that a number of nuclear phenotypes precede, or coincide with, reactive transformation. These include increased nuclear oxidative stress and DNA damage, and accumulation of the SOD1 protein in the nucleus. These findings reveal early cell-autonomous phenotypes in SOD1-mutated astrocytes that may contribute to the acquisition of a reactive phenotype involved in alterations of astrocyte-MN communication in ALS.

Single-cell multiregion dissection of Alzheimer's disease

Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1-3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer's disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer's disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer's disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer's disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer's disease pathology.

Single-cell atlas of the human brain vasculature across development, adulthood and disease

A broad range of brain pathologies critically relies on the vasculature, and cerebrovascular disease is a leading cause of death worldwide. However, the cellular and molecular architecture of the human brain vasculature remains incompletely understood1. Here we performed single-cell RNA sequencing analysis of 606,380 freshly isolated endothelial cells, perivascular cells and other tissue-derived cells from 117 samples, from 68 human fetuses and adult patients to construct a molecular atlas of the developing fetal, adult control and diseased human brain vasculature. We identify extensive molecular heterogeneity of the vasculature of healthy fetal and adult human brains and across five vascular-dependent central nervous system (CNS) pathologies, including brain tumours and brain vascular malformations. We identify alteration of arteriovenous differentiation and reactivated fetal as well as conserved dysregulated genes and pathways in the diseased vasculature. Pathological endothelial cells display a loss of CNS-specific properties and reveal an upregulation of MHC class II molecules, indicating atypical features of CNS endothelial cells. Cell-cell interaction analyses predict substantial endothelial-to-perivascular cell ligand-receptor cross-talk, including immune-related and angiogenic pathways, thereby revealing a central role for the endothelium within brain neurovascular unit signalling networks. Our single-cell brain atlas provides insights into the molecular architecture and heterogeneity of the developing, adult/control and diseased human brain vasculature and serves as a powerful reference for future studies.

Whole brain alignment of spatial transcriptomics between humans and mice with BrainAlign

The increasing utilization of mouse models in human neuroscience research places higher demands on computational methods to translate findings from the mouse brain to the human one. In this study, we develop BrainAlign, a self-supervised learning approach, for the whole brain alignment of spatial transcriptomics (ST) between humans and mice. BrainAlign encodes spots and genes simultaneously in two separated shared embedding spaces by a heterogeneous graph neural network. We demonstrate that BrainAlign could integrate cross-species spots into the embedding space and reveal the conserved brain regions supported by ST information, which facilitates the detection of homologous regions between humans and mice. Genomic analysis further presents gene expression connections between humans and mice and reveals similar expression patterns for marker genes. Moreover, BrainAlign can accurately map spatially similar homologous regions or clusters onto a unified spatial structural domain while preserving their relative positions.

The Genetic Architecture of the Human Corpus Callosum and its Subregions

The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.

Genetic approaches to elucidating cortical and hippocampal GABAergic interneuron diversity

GABAergic interneurons (INs) in the mammalian forebrain represent a diverse population of cells that provide specialized forms of local inhibition to regulate neural circuit activity. Over the last few decades, the development of a palette of genetic tools along with the generation of single-cell transcriptomic data has begun to reveal the molecular basis of IN diversity, thereby providing deep insights into how different IN subtypes function in the forebrain. In this review, we outline the emerging picture of cortical and hippocampal IN speciation as defined by transcriptomics and developmental origin and summarize the genetic strategies that have been utilized to target specific IN subtypes, along with the technical considerations inherent to each approach. Collectively, these methods have greatly facilitated our understanding of how IN subtypes regulate forebrain circuitry via cell type and compartment-specific inhibition and thus have illuminated a path toward potential therapeutic interventions for a variety of neurocognitive disorders.

Expansion-assisted selective plane illumination microscopy for nanoscale imaging of centimeter-scale tissues

Recent advances in tissue processing, labeling, and fluorescence microscopy are providing unprecedented views of the structure of cells and tissues at sub-diffraction resolutions and near single molecule sensitivity, driving discoveries in diverse fields of biology, including neuroscience. Biological tissue is organized over scales of nanometers to centimeters. Harnessing molecular imaging across intact, three-dimensional samples on this scale requires new types of microscopes with larger fields of view and working distance, as well as higher throughput. We present a new expansion-assisted selective plane illumination microscope (ExA-SPIM) with aberration-free 1×1×3 μm optical resolution over a large field of view (10.6×8.0 mm 2 ) and working distance (35 mm) at speeds up to 946 megavoxels/sec. Combined with new tissue clearing and expansion methods, the microscope allows imaging centimeter-scale samples with 250×250×750 nm optical resolution (4× expansion), including entire mouse brains, with high contrast and without sectioning. We illustrate ExA-SPIM by reconstructing individual neurons across the mouse brain, imaging cortico-spinal neurons in the macaque motor cortex, and visualizing axons in human white matter.

Neural effects of dopaminergic compounds revealed by multi-site electrophysiology and interpretable machine-learning

Background

Neuropsychopharmacological compounds may exert complex brain-wide effects due to an anatomically and genetically broad expression of their molecular targets and indirect effects via interconnected brain circuits. Electrophysiological measurements in multiple brain regions using electroencephalography (EEG) or local field potential (LFP) depth-electrodes may record fingerprints of such pharmacologically-induced changes in local activity and interregional connectivity (pEEG/pLFP). However, in order to reveal such patterns comprehensively and potentially derive mechanisms of therapeutic pharmacological effects, both activity and connectivity have to be estimated for many brain regions. This entails the problem that hundreds of electrophysiological parameters are derived from a typically small number of subjects, making frequentist statistics ill-suited for their analysis.

Methods

We here present an optimized interpretable machine-learning (ML) approach which relies on predictive power in individual recording sequences to extract and quantify the robustness of compound-induced neural changes from multi-site recordings using Shapley additive explanations (SHAP) values. To evaluate this approach, we recorded LFPs in mediodorsal thalamus (MD), prefrontal cortex (PFC), dorsal hippocampus (CA1 and CA3), and ventral hippocampus (vHC) of mice after application of amphetamine or of the dopaminergic antagonists clozapine, raclopride, or SCH23390, for which effects on directed neural communication between those brain structures were so far unknown.

Results

Our approach identified complex patterns of neurophysiological changes induced by each of these compounds, which were reproducible across time intervals, doses (where tested), and ML algorithms. We found, for example, that the action of clozapine in the analysed cortico-thalamo-hippocampal network entails a larger share of D1-as opposed to D2-receptor induced effects, and that the D2-antagonist raclopride reconfigures connectivity in the delta-frequency band. Furthermore, the effects of amphetamine and clozapine were surprisingly similar in terms of decreasing thalamic input to PFC and vHC, and vHC activity, whereas an increase of dorsal-hippocampal communication and of thalamic activity distinguished amphetamine from all tested anti-dopaminergic drugs.

Conclusion

Our study suggests that communication from the dorsal hippocampus scales proportionally with dopamine receptor activation and demonstrates, more generally, the high complexity of neuropharmacological effects on the circuit level. We envision that the presented approach can aid in the standardization and improved data extraction in pEEG/pLFP-studies.

Single-nucleus multi-omics of Parkinson's disease reveals a glutamatergic neuronal subtype susceptible to gene dysregulation via alteration of transcriptional networks

The genetic architecture of Parkinson's disease (PD) is complex and multiple brain cell subtypes are involved in the neuropathological progression of the disease. Here we aimed to advance our understanding of PD genetic complexity at a cell subtype precision level. Using parallel single-nucleus (sn)RNA-seq and snATAC-seq analyses we simultaneously profiled the transcriptomic and chromatin accessibility landscapes in temporal cortex tissues from 12 PD compared to 12 control subjects at a granular single cell resolution. An integrative bioinformatic pipeline was developed and applied for the analyses of these snMulti-omics datasets. The results identified a subpopulation of cortical glutamatergic excitatory neurons with remarkably altered gene expression in PD, including differentially-expressed genes within PD risk loci identified in genome-wide association studies (GWAS). This was the only neuronal subtype showing significant and robust overexpression of SNCA. Further characterization of this neuronal-subpopulation showed upregulation of specific pathways related to axon guidance, neurite outgrowth and post-synaptic structure, and downregulated pathways involved in presynaptic organization and calcium response. Additionally, we characterized the roles of three molecular mechanisms in governing PD-associated cell subtype-specific dysregulation of gene expression: (1) changes in cis-regulatory element accessibility to transcriptional machinery; (2) changes in the abundance of master transcriptional regulators, including YY1, SP3, and KLF16; (3) candidate regulatory variants in high linkage disequilibrium with PD-GWAS genomic variants impacting transcription factor binding affinities. To our knowledge, this study is the first and the most comprehensive interrogation of the multi-omics landscape of PD at a cell-subtype resolution. Our findings provide new insights into a precise glutamatergic neuronal cell subtype, causal genes, and non-coding regulatory variants underlying the neuropathological progression of PD, paving the way for the development of cell- and gene-targeted therapeutics to halt disease progression as well as genetic biomarkers for early preclinical diagnosis.

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their 'volume transmission' output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.

Obesity and the cerebral cortex: Underlying neurobiology in mice and humans

Obesity is a major modifiable risk factor for Alzheimer's disease (AD), characterized by progressive atrophy of the cerebral cortex. The neurobiology of obesity contributions to AD is poorly understood. Here we show with in vivo MRI that diet-induced obesity decreases cortical volume in mice, and that higher body adiposity associates with lower cortical volume in humans. Single-nuclei transcriptomics of the mouse cortex reveals that dietary obesity promotes an array of neuron-adverse transcriptional dysregulations, which are mediated by an interplay of excitatory neurons and glial cells, and which involve microglial activation and lowered neuronal capacity for neuritogenesis and maintenance of membrane potential. The transcriptional dysregulations of microglia, more than of other cell types, are like those in AD, as assessed with single-nuclei cortical transcriptomics in a mouse model of AD and two sets of human donors with the disease. Serial two-photon tomography of microglia demonstrates microgliosis throughout the mouse cortex. The spatial pattern of adiposity-cortical volume associations in human cohorts interrogated together with in silico bulk and single-nucleus transcriptomic data from the human cortex implicated microglia (along with other glial cells and subtypes of excitatory neurons), and it correlated positively with the spatial profile of cortical atrophy in patients with mild cognitive impairment and AD. Thus, multi-cell neuron-adverse dysregulations likely contribute to the loss of cortical tissue in obesity. The dysregulations of microglia may be pivotal to the obesity-related risk of AD.

Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images

Microscopy-based spatially resolved omic methods are transforming the life sciences. However, these methods rely on high numerical aperture objectives and cannot resolve crowded molecular targets, limiting the amount of extractable biological information. To overcome these limitations, here we develop Deconwolf, an open-source, user-friendly software for high-performance deconvolution of widefield fluorescence microscopy images, which efficiently runs on laptop computers. Deconwolf enables accurate quantification of crowded diffraction limited fluorescence dots in DNA and RNA fluorescence in situ hybridization images and allows robust detection of individual transcripts in tissue sections imaged with ×20 air objectives. Deconvolution of in situ spatial transcriptomics images with Deconwolf increased the number of transcripts identified more than threefold, while the application of Deconwolf to images obtained by fluorescence in situ sequencing of barcoded Oligopaint probes drastically improved chromosome tracing. Deconwolf greatly facilitates the use of deconvolution in many bioimaging applications.

Repetitive Transcranial Magnetic Stimulation Reversing Abnormal Brain Function in Mood Disorders with Early Life Stress: from preclinical models to clinical applications

BACKGROUND

Early life stress (ELS) significantly increases the risk of mood disorders and affects the neurodevelopment of the primary cortex.

HYPOTHESIS

Modulating the primary cortex through neural intervention can ameliorate the impact of ELS on brain development and consequently alleviate its effects on mood disorders.

METHOD

We induced the chronic unpredictable mild stress (CUMS) model in adolescent rats, followed by applying repetitive transcranial magnetic stimulation (rTMS) to their primary cortex in early adulthood. To assess the applicability of primary cortex rTMS in humans, we recruited individuals aged 17-25 with mood disorders who had experienced ELS and performed primary cortex rTMS on them. Functional magnetic resonance imaging (fMRI) and depression-related behavioral and clinical symptoms were conducted in both rats and human subjects before and after the rTMS.

RESULTS

In animals, fMRI analysis revealed increased activation in the primary cortex of CUMS rats and decrease subcortical activation. Following the intervention of primary cortex rTMS, the abnormal functional activity was reversed. Similarly, in mood disorders patients with ELS, increased activation in the primary cortex and decreased activation in the frontal cortex were observed. During rTMS intervention, similar neuroimaging improvements were noted, particularly decreased activation in the primary cortex. This suggests that targeted rTMS in the primary cortex can reverse the abnormal neuroimaging.

CONCLUSION

This cross-species translational study has identified the primary cortex as a key region in mood disorders patients with ELS. Targeting the primary cortex with rTMS can correct abnormal functional activity while improving symptoms. Our study provides translational evidence for therapeutics targeting the ELS factor of mood disorders patients.

SPRITE: improving spatial gene expression imputation with gene and cell networks

MOTIVATION

Spatially resolved single-cell transcriptomics have provided unprecedented insights into gene expression in situ, particularly in the context of cell interactions or organization of tissues. However, current technologies for profiling spatial gene expression at single-cell resolution are generally limited to the measurement of a small number of genes. To address this limitation, several algorithms have been developed to impute or predict the expression of additional genes that were not present in the measured gene panel. Current algorithms do not leverage the rich spatial and gene relational information in spatial transcriptomics. To improve spatial gene expression predictions, we introduce Spatial Propagation and Reinforcement of Imputed Transcript Expression (SPRITE) as a meta-algorithm that processes predictions obtained from existing methods by propagating information across gene correlation networks and spatial neighborhood graphs.

RESULTS

SPRITE improves spatial gene expression predictions across multiple spatial transcriptomics datasets. Furthermore, SPRITE predicted spatial gene expression leads to improved clustering, visualization, and classification of cells. SPRITE can be used in spatial transcriptomics data analysis to improve inferences based on predicted gene expression.

AVAILABILITY AND IMPLEMENTATION

The SPRITE software package is available at https://github.com/sunericd/SPRITE. Code for generating experiments and analyses in the manuscript is available at https://github.com/sunericd/sprite-figures-and-analyses.

Discovery of optimal cell type classification marker genes from single cell RNA sequencing data

The use of single cell/nucleus RNA sequencing (scRNA-seq) technologies that quantitively describe cell transcriptional phenotypes is revolutionizing our understanding of cell biology, leading to new insights in cell type identification, disease mechanisms, and drug development. The tremendous growth in scRNA-seq data has posed new challenges in efficiently characterizing data-driven cell types and identifying quantifiable marker genes for cell type classification. The use of machine learning and explainable artificial intelligence has emerged as an effective approach to study large-scale scRNA-seq data. NS-Forest is a random forest machine learning-based algorithm that aims to provide a scalable data-driven solution to identify minimum combinations of necessary and sufficient marker genes that capture cell type identity with maximum classification accuracy. Here, we describe the latest version, NS-Forest version 4.0 and its companion Python package (https://github.com/JCVenterInstitute/NSForest), with several enhancements to select marker gene combinations that exhibit highly selective expression patterns among closely related cell types and more efficiently perform marker gene selection for large-scale scRNA-seq data atlases with millions of cells. By modularizing the final decision tree step, NS-Forest v4.0 can be used to compare the performance of user-defined marker genes with the NS-Forest computationally-derived marker genes based on the decision tree classifiers. To quantify how well the identified markers exhibit the desired pattern of being exclusively expressed at high levels within their target cell types, we introduce the On-Target Fraction metric that ranges from 0 to 1, with a metric of 1 assigned to markers that are only expressed within their target cell types and not in cells of any other cell types. NS-Forest v4.0 outperforms previous versions on its ability to identify markers with higher On-Target Fraction values for closely related cell types and outperforms other marker gene selection approaches at classification with significantly higher F-beta scores when applied to datasets from three human organs - brain, kidney, and lung.

Midline Assembloids Reveal Regulators of Human Axon Guidance

Organizers are specialized cell populations that orchestrate cell patterning and axon guidance in the developing nervous system. Although non-human models have led to fundamental discoveries about the organization of the nervous system midline by the floor plate, an experimental model of human floor plate would enable broader insights into regulation of human neurodevelopment and midline connectivity. Here, we have developed stem cell-derived organoids resembling human floor plate (hFpO) and assembled them with spinal cord organoids (hSpO) to generate midline assembloids (hMA). We demonstrate that hFpO promote Sonic hedgehog-dependent ventral patterning of human spinal progenitors and Netrin-dependent guidance of human commissural axons, paralleling non-human models. To investigate evolutionary-divergent midline regulators, we profiled the hFpO secretome and identified 27 evolutionarily divergent genes between human and mouse. Utilizing the hMA platform, we targeted these candidates in an arrayed CRISPR knockout screen and reveal that GALNT2 , a gene involved in O-linked glycosylation, impairs floor plate-mediated guidance of commissural axons in humans. This novel platform extends prior axon guidance discoveries into human-specific neurobiology with implications for mechanisms of nervous system evolution and neurodevelopmental disorders.

The Brain-Heart Network of Syncope

Observed and recorded in various forms since ancient times, 'syncope' is often popularly called 'fainting', such that the two terms are used synonymously. Syncope/fainting can be caused by a variety of conditions, including but not limited to head injuries, vertigo, and oxygen deficiency. Here, we draw on a large body of literature on syncope, including the role of a recently discovered set of specialized mammalian neurons. Although the etiology of syncope still remains a mystery, we have attempted to provide a comprehensive account of what is known and what still needs to be performed. Much of our understanding of syncope is owing to studies in the laboratory mouse, whereas evidence from human patients remains scarce. Interestingly, the cardioinhibitory Bezold-Jarisch reflex, recognized in the early 1900s, has an intriguing similarity to-and forms the basis of-syncope. In this review, we have integrated this minimal model into the modern view of the brain-neuron-heart signaling loop of syncope, to which several signaling events contribute. Molecular signaling is our major focus here, presented in terms of a normal heart, and thus, syncope due to abnormal or weak heart activity is not discussed in detail. In addition, we have offered possible directions for clinical intervention based on this model. Overall, this article is expected to generate interest in chronic vertigo and syncope/fainting, an enigmatic condition that affects most humans at some point in life; it is also hoped that this may lead to a mechanism-based clinical intervention in the future.

Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome

Chromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke's area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.

Neocortical long-range inhibition promotes cortical synchrony and sleep

Behavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, the in vivo circuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.

Variation and convergence in the morpho-functional properties of the mammalian neocortex

Man's natural inclination to classify and hierarchize the living world has prompted neurophysiologists to explore possible differences in brain organisation between mammals, with the aim of understanding the diversity of their behavioural repertoires. But what really distinguishes the human brain from that of a platypus, an opossum or a rodent? In this review, we compare the structural and electrical properties of neocortical neurons in the main mammalian radiations and examine their impact on the functioning of the networks they form. We discuss variations in overall brain size, number of neurons, length of their dendritic trees and density of spines, acknowledging their increase in humans as in most large-brained species. Our comparative analysis also highlights a remarkable consistency, particularly pronounced in marsupial and placental mammals, in the cell typology, intrinsic and synaptic electrical properties of pyramidal neuron subtypes, and in their organisation into functional circuits. These shared cellular and network characteristics contribute to the emergence of strikingly similar large-scale physiological and pathological brain dynamics across a wide range of species. These findings support the existence of a core set of neural principles and processes conserved throughout mammalian evolution, from which a number of species-specific adaptations appear, likely allowing distinct functional needs to be met in a variety of environmental contexts.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Kynurenic acid inflammatory signaling expands in primates and impairs prefrontal cortical cognition

Cognitive deficits from dorsolateral prefrontal cortex (dlPFC) dysfunction are common in neuroinflammatory disorders, including long-COVID, schizophrenia and Alzheimer's disease, and have been correlated with kynurenine inflammatory signaling. Kynurenine is further metabolized to kynurenic acid (KYNA) in brain, where it blocks NMDA and α7-nicotinic receptors (nic-α7Rs). These receptors are essential for neurotransmission in dlPFC, suggesting that KYNA may cause higher cognitive deficits in these disorders. The current study found that KYNA and its synthetic enzyme, KAT II, have greatly expanded expression in primate dlPFC in both glia and neurons. Local application of KYNA onto dlPFC neurons markedly reduced the delay-related firing needed for working memory via actions at NMDA and nic-α7Rs, while inhibition of KAT II enhanced neuronal firing in aged macaques. Systemic administration of agents that reduce KYNA production similarly improved cognitive performance in aged monkeys, suggesting a therapeutic avenue for the treatment of cognitive deficits in neuroinflammatory disorders.

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Human iPSC-Derived Neurons with Reliable Synapses and Large Presynaptic Action Potentials

Understanding the function of the human brain requires determining basic properties of synaptic transmission in human neurons. One of the most fundamental parameters controlling neurotransmitter release is the presynaptic action potential, but its amplitude and duration remain controversial. Presynaptic action potentials have so far been measured with high temporal resolution only in a limited number of vertebrate but not in human neurons. To uncover properties of human presynaptic action potentials, we exploited recently developed tools to generate human glutamatergic neurons by transient expression of Neurogenin 2 (Ngn2) in pluripotent stem cells. During maturation for 3 to 9 weeks of culturing in different established media, the proportion of cells with multiple axon initial segments decreased, while the amount of axonal tau protein and neuronal excitability increased. Super-resolution microscopy revealed the alignment of the pre- and postsynaptic proteins, Bassoon and Homer. Synaptic transmission was surprisingly reliable at frequencies of 20, 50, and 100 Hz. The synchronicity of synaptic transmission during high-frequency transmission increased during 9 weeks of neuronal maturation. To analyze the mechanisms of synchronous high-frequency glutamate release, we developed direct presynaptic patch-clamp recordings from human neurons. The presynaptic action potentials had large overshoots to ∼25 mV and short durations of ∼0.5 ms. Our findings show that Ngn2-induced neurons represent an elegant model system allowing for functional, structural, and molecular analyses of glutamatergic synaptic transmission with high spatiotemporal resolution in human neurons. Furthermore, our data predict that glutamatergic transmission is mediated by large and rapid presynaptic action potentials in the human brain.

Neurogliaform Cells Exhibit Laminar-specific Responses in the Visual Cortex and Modulate Behavioral State-dependent Cortical Activity

Neurogliaform cells are a distinct type of GABAergic cortical interneurons known for their "volume transmission" output property. However, their activity and function within cortical circuits remain unclear. Here, we developed two genetic tools to target these neurons and examine their function in the primary visual cortex. We found that the spontaneous activity of neurogliaform cells positively correlated with locomotion. Silencing these neurons increased spontaneous activity during locomotion and impaired visual responses in L2/3 pyramidal neurons. Furthermore, the contrast-dependent visual response of neurogliaform cells varies with their laminar location and is constrained by their morphology and input connectivity. These findings demonstrate the importance of neurogliaform cells in regulating cortical behavioral state-dependent spontaneous activity and indicate that their functional engagement during visual stimuli is influenced by their laminar positioning and connectivity.