Neuronal Cell Types Research Articles

High activity and high functional connectivity are mutually exclusive in resting state zebrafish and human brains

BackgroundThe structural connectivity of neurons in the brain allows active neurons to impact the physiology of target neuron types with which they are functionally connected. While the structural connectome is at the basis of functional connectome, it is the functional connectivity measured through correlations between time series of individual neurophysiological events that underlies behavioral and mental states. However, in light of the diverse neuronal cell types populating the brain and their unique connectivity properties, both neuronal activity and functional connectivity are heterogeneous across the brain, and the nature of their relationship is not clear. Here, we employ brain-wide calcium imaging at cellular resolution in larval zebrafish to understand the principles of resting state functional connectivity.ResultsWe recorded the spontaneous activity of >12,000 neurons in the awake resting state forebrain. By classifying their activity (i.e., variances of ΔF/F across time) and functional connectivity into three levels (high, medium, low), we find that highly active neurons have low functional connections and highly connected neurons are of low activity. This finding holds true when neuronal activity and functional connectivity data are classified into five instead of three levels, and in whole brain spontaneous activity datasets. Moreover, such activity-connectivity relationship is not observed in randomly shuffled, noise-added, or simulated datasets, suggesting that it reflects an intrinsic brain network property. Intriguingly, deploying the same analytical tools on functional magnetic resonance imaging (fMRI) data from the resting state human brain, we uncover a similar relationship between activity (signal variance over time) and functional connectivity, that is, regions of high activity are non-overlapping with those of high connectivity.ConclusionsWe found a mutually exclusive relationship between high activity (signal variance over time) and high functional connectivity of neurons in zebrafish and human brains. These findings reveal a previously unknown and evolutionarily conserved brain organizational principle, which has implications for understanding disease states and designing artificial neuronal networks.

Editorial

Editorial

Investigation of Spatial Interaction Between Astrocytes and Neurons in Cleared Brains.

Combining viral vector transduction and tissue clearing using the CLARITY method makes it possible to simultaneously investigate several types of brain cells and their interactions. Viral vector transduction enables the marking of diverse cell types in different fluorescence colors within the same tissue. Cells can be identified genetically by activity or projection. Using a modified CLARITY protocol, the potential sample size of astrocytes and neurons has grown by 2-3 orders of magnitude. The use of CLARITY allows the imaging of complete astrocytes, which are too large to fit in their entirety in slices, and the examination of the somata with all their processes. In addition, it provides the opportunity to investigate the spatial interaction between astrocytes and different neuronal cell types, namely, the number of pyramidal neurons in each astrocytic domain or the proximity between astrocytes and specific inhibitory neuron populations. This paper describes, in detail, how these methods are to be applied.

Adult enteric Dclk1-positive glial and neuronal cells reveal distinct responses to acute intestinal injury.

Intestinal ganglionic cells in the adult enteric nervous system (ENS) are continually exposed to stimuli from the surrounding microenvironment and need at times to respond to disturbed homeostasis following acute intestinal injury. The kinase DCLK1 and intestinal Dclk1-positive cells have been reported to contribute to intestinal regeneration. Although Dclk1-positive cells are present in adult enteric ganglia, their cellular identity and response to acute injury have not been investigated in detail. Here, we reveal the presence of distinct Dclk1-tdTom+/CD49b+ glial-like and Dclk1-tdTom+/CD49b- neuronal cell types in adult myenteric ganglia. These ganglionic cells demonstrate distinct patterns of tracing over time yet show a similar expansion in response to elevated serotonergic signaling. Interestingly, Dclk1-tdTom+ glial-like and neuronal cell types appear resistant to acute irradiation injury-mediated cell death. Moreover, Dclk1-tdTom+/CD49b+ glial-like cells show prominent changes in gene expression profiles induced by injury, in contrast to Dclk1-tdTom+/CD49b- neuronal cell types. Finally, subsets of Dclk1-tdTom+/CD49b+ glial-like cells demonstrate prominent overlap with Nestin and p75NTR and strong responses to elevated serotonergic signaling or acute injury. These findings, together with their role in early development and their neural crest-like gene expression signature, suggest the presence of reserve progenitor cells in the adult Dclk1 glial cell lineage.NEW & NOTEWORTHY The kinase DCLK1 identifies glial-like and neuronal cell types in adult murine enteric ganglia, which resist acute injury-mediated cell death yet differ in their cellular response to injury. Interestingly, Dclk1-labeled glial-like cells show prominent transcriptional changes in response to injury and harbor features reminiscent of previously described enteric neural precursor cells. Our data thus add to recently emerging evidence of reserve cellular plasticity in the adult enteric nervous system.

Omega-3/Omega-6 Long-Chain Fatty Acid Imbalance in Phase I Retinopathy of Prematurity.

There is a gap in understanding the effect of the essential ω-3 and ω-6 long-chain polyunsaturated fatty acids (LCPUFA) on Phase I retinopathy of prematurity (ROP), which precipitates proliferative ROP. Postnatal hyperglycemia contributes to Phase I ROP by delaying retinal vascularization. In mouse neonates with hyperglycemia-associated Phase I retinopathy, dietary ω-3 (vs. ω-6 LCPUFA) supplementation promoted retinal vessel development. However, ω-6 (vs. ω-3 LCPUFA) was also developmentally essential, promoting neuronal growth and metabolism as suggested by a strong metabolic shift in almost all types of retinal neuronal and glial cells identified with single-cell transcriptomics. Loss of adiponectin (APN) in mice (mimicking the low APN levels in Phase I ROP) decreased LCPUFA levels (including ω-3 and ω-6) in retinas under normoglycemic and hyperglycemic conditions. ω-3 (vs. ω-6) LCPUFA activated the APN pathway by increasing the circulating APN levels and inducing expression of the retinal APN receptor. Our findings suggested that both ω-3 and ω-6 LCPUFA are crucial in protecting against retinal neurovascular dysfunction in a Phase I ROP model; adequate ω-6 LCPUFA levels must be maintained in addition to ω-3 supplementation to prevent retinopathy. Activation of the APN pathway may further enhance the ω-3 and ω-6 LCPUFA’s protection against ROP.

Integration of Spatial and Temporal Patterning in the Invertebrate and Vertebrate Nervous System.

The nervous system is one of the most sophisticated animal tissues, consisting of thousands of interconnected cell types. How the nervous system develops its diversity from a few neural stem cells remains a challenging question. Spatial and temporal patterning mechanisms provide an efficient model through which diversity can be generated. The molecular mechanism of spatiotemporal patterning has been studied extensively in Drosophila melanogaster, where distinct sets of transcription factors define the spatial domains and temporal windows that give rise to different cell types. Similarly, in vertebrates, spatial domains defined by transcription factors produce different types of neurons in the brain and neural tube. At the same time, different cortical neuronal types are generated within the same cell lineage with a specific birth order. However, we still do not understand how the orthogonal information of spatial and temporal patterning is integrated into the progenitor and post-mitotic cells to combinatorially give rise to different neurons. In this review, after introducing spatial and temporal patterning in Drosophila and mice, we discuss possible mechanisms that neural progenitors may use to integrate spatial and temporal information. We finally review the functional implications of spatial and temporal patterning and conclude envisaging how small alterations of these mechanisms can lead to the evolution of new neuronal cell types.

Thomas Michael Jessell. 2 August 1951—28 April 2019

Tom Jessell was a British neuroscientist who made pioneering discoveries in developmental neurobiology. Beginning with a neuropharmacology training in London and Cambridge, Tom moved to Harvard and finally Columbia University. There, Tom embraced the dramatic late twentieth-century developments in molecular biology to unravel the genetic basis of spinal cord neuronal diversity and developmental mechanisms of circuit formation. Combining encyclopaedic knowledge of the classical neurobiology literature with virtuoso molecular genetic, anatomical and electrophysiological techniques, exploited by his team of gifted students, post-docs and collaborators, Tom made seminal contributions to broad areas of neuroscience. Notable contributions included the discovery of extracellular factors that induce distinct neuronal cell types and guide their connectivity, as well as the identification of the transcriptional repertoires that led to neuronal complexity in the developing spinal cord. Important insights into circuitry and behaviour followed these defining studies. At the same time, Tom was heavily involved in neuroscience education and the development of new neuroscience research institutes. For all his Herculean energy for research, he still found great pleasure in fine art, cricket and jazz, and his life was greatly enriched by his partner Jane Dodd, also a Cambridge-trained neuroscientist, and their three daughters. Tom's wit, energy and incisive intelligence will be sorely missed. His legacy is not only a paradigm-shifting body of papers, but also his educational and institutional achievements and the remarkable group of scientists, once his trainees, who, in their turn, continue to advance neuroscience research around the world.

Absence of Connexin 43 Results in Smaller Retinas and Arrested, Depolarized Retinal Progenitor Cells in Human Retinal Organoids.

The development of the vertebrate retina relies on complex regulatory mechanisms to achieve its characteristic layered morphology containing multiple neuronal cell types. While connexin 43 (CX43) is not expressed by mature retinal neurons, mutations in its gene GJA1 are associated with microphthalmia and low vision in patients. To delineate how lack of CX43 affects retinal development, GJA1 was disrupted in human induced pluripotent stem cells (hiPSCs) (GJA1-/-) using CRISPR/Cas9 editing, and these were subsequently differentiated into retinal organoids. GJA1-/- hiPSCs do not display defects in self-renewal and pluripotency, but the resulting organoids are smaller with a thinner neural retina and decreased abundance of many retinal cell types. CX43-deficient organoids express lower levels of the neural marker PAX6 and the retinal progenitor cell (RPC) markers PAX6, SIX3, and SIX6. Conversely, expression of the early neuroectoderm markers SOX1 and SOX2 remains high in GJA1-/- organoids throughout their development. The lack of CX43 results in an increased population of CHX10-positive RPCs that are smaller, disorganized, do not become polarized, and possess a limited ability to commit to retinal fate specification. Our data indicate that lack of CX43 causes a developmental arrest in RPCs that subsequently leads to pan-retinal defects and stunted ocular growth.

Robust regulatory architecture of pan-neuronal gene expression

Pan-neuronally expressed genes, such as genes involved in the synaptic vesicle cycle or in neuropeptide maturation, are critical for proper function of all neurons, but the transcriptional control mechanisms that direct such genes to all neurons of a nervous system remain poorly understood. We show here that six members of the CUT family of homeobox genes control pan-neuronal identity specification in Caenorhabditis elegans. Single CUT mutants show barely any effects on pan-neuronal gene expression or global nervous system function, but such effects become apparent and progressively worsen upon removal of additional CUT family members, indicating a critical role of gene dosage. Overexpression of each individual CUT gene rescued the phenotype of compound mutants, corroborating that gene dosage, rather than the activity of specific members of the gene family, is critical for CUT gene family function. Genome-wide binding profiles, as well as mutation of CUT homeodomain binding sites by CRISPR/Cas9 genome engineering show that CUT genes directly control the expression of pan-neuronal features. Moreover, CUT genes act in conjunction with neuron-type-specific transcription factors to control pan-neuronal gene expression. Our study, therefore, provides a previously missing key insight into how neuronal gene expression programs are specified and reveals a highly buffered and robust mechanism that controls the most critical functional features of all neuronal cell types.

Kinase activity profiling identifies putative downstream targets of cGMP/PKG signaling in inherited retinal neurodegeneration

Inherited retinal diseases (IRDs) are a group of neurodegenerative disorders that lead to photoreceptor cell death and eventually blindness. IRDs are characterised by a high genetic heterogeneity, making it imperative to design mutation-independent therapies. Mutations in a number of IRD disease genes have been associated with a rise of cyclic 3’,5’-guanosine monophosphate (cGMP) levels in photoreceptors. Accordingly, the cGMP-dependent protein kinase (PKG) has emerged as a new potential target for the mutation-independent treatment of IRDs. However, the substrates of PKG and the downstream degenerative pathways triggered by its activity have yet to be determined. Here, we performed kinome activity profiling of different murine organotypic retinal explant cultures (diseased rd1 and wild-type controls) using multiplex peptide microarrays to identify proteins whose phosphorylation was significantly altered by PKG activity. In addition, we tested the downstream effect of a known PKG inhibitor CN03 in these organotypic retina cultures. Among the PKG substrates were potassium channels belonging to the Kv1 family (KCNA3, KCNA6), cyclic AMP-responsive element-binding protein 1 (CREB1), DNA topoisomerase 2-α (TOP2A), 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (F263), and the glutamate ionotropic receptor kainate 2 (GRIK2). The retinal expression of these PKG targets was further confirmed by immunofluorescence and could be assigned to various neuronal cell types, including photoreceptors, horizontal cells, and ganglion cells. Taken together, this study confirmed the key role of PKG in photoreceptor cell death and identified new downstream targets of cGMP/PKG signalling that will improve the understanding of the degenerative mechanisms underlying IRDs.

Insights into Human-Induced Pluripotent Stem Cell-Derived Astrocytes in Neurodegenerative Disorders.

Most neurodegenerative disorders have complex and still unresolved pathology characterized by progressive neuronal damage and death. Astrocytes, the most-abundant non-neuronal cell population in the central nervous system, play a vital role in these processes. They are involved in various functions in the brain, such as the regulation of synapse formation, neuroinflammation, and lactate and glutamate levels. The development of human-induced pluripotent stem cells (iPSCs) reformed the research in neurodegenerative disorders allowing for the generation of disease-relevant neuronal and non-neuronal cell types that can help in disease modeling, drug screening, and, possibly, cell transplantation strategies. In the last 14 years, the differentiation of human iPSCs into astrocytes allowed for the opportunity to explore the contribution of astrocytes to neurodegenerative diseases. This review discusses the development protocols and applications of human iPSC-derived astrocytes in the most common neurodegenerative conditions.

High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0.

MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type-specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.Availability and implementationThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/).Supplementary information Supplementary data are available at Bioinformatics online.

Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition.

It is generally appreciated that storing memories of specific events in the mammalian brain, and associating features of the environment with behavioral outcomes requires fine-tuning of the strengths of connections between neurons through synaptic plasticity. It is less understood whether the organization of neuronal circuits comprised of multiple distinct neuronal cell types provides an architectural prior that facilitates learning and memory by generating unique patterns of neuronal activity in response to different stimuli in the environment, even before plasticity and learning occur. Here we simulated a neuronal network responding to sensory stimuli, and systematically determined the effects of specific neuronal cell types and connections on three key metrics of neuronal sensory representations: sparsity, selectivity, and discriminability. We found that when the total amount of input varied considerably across stimuli, standard feedforward and feedback inhibitory circuit motifs failed to discriminate all stimuli without sacrificing sparsity or selectivity. Interestingly, networks that included dedicated excitatory feedback interneurons based on the mossy cells of the hippocampal dentate gyrus exhibited improved pattern separation, a result that depended on the indirect recruitment of feedback inhibition. These results elucidate the roles of cellular diversity and neural circuit architecture on generating neuronal representations with properties advantageous for memory storage and recall.

Cell-type-specific responses to associative learning in the primary motor cortex.

The primary motor cortex (M1) is known to be a critical site for movement initiation and motor learning. Surprisingly, it has also been shown to possess reward-related activity, presumably to facilitate reward-based learning of new movements. However, whether reward-related signals are represented among different cell types in M1, and whether their response properties change after cue-reward conditioning remains unclear. Here, we performed longitudinal in vivo two-photon Ca2+ imaging to monitor the activity of different neuronal cell types in M1 while mice engaged in a classical conditioning task. Our results demonstrate that most of the major neuronal cell types in M1 showed robust but differential responses to both the conditioned cue stimulus (CS) and reward, and their response properties undergo cell-type-specific modifications after associative learning. PV-INs' responses became more reliable to the CS, while VIP-INs' responses became more reliable to reward. Pyramidal neurons only showed robust responses to novel reward, and they habituated to it after associative learning. Lastly, SOM-INs' responses emerged and became more reliable to both the CS and reward after conditioning. These observations suggest that cue- and reward-related signals are preferentially represented among different neuronal cell types in M1, and the distinct modifications they undergo during associative learning could be essential in triggering different aspects of local circuit reorganization in M1 during reward-based motor skill learning.

Human iPSC-Derived Neural Models for Studying Alzheimer\u2019s Disease: from Neural Stem Cells to Cerebral Organoids

During the past two decades, induced pluripotent stem cells (iPSCs) have been widely used to study mechanisms of human neural development, disease modeling, and drug discovery in vitro. Especially in the field of Alzheimer’s disease (AD), where this treatment is lacking, tremendous effort has been put into the investigation of molecular mechanisms behind this disease using induced pluripotent stem cell-based models. Numerous of these studies have found either novel regulatory mechanisms that could be exploited to develop relevant drugs for AD treatment or have already tested small molecules on in vitro cultures, directly demonstrating their effect on amelioration of AD-associated pathology. This review thus summarizes currently used differentiation strategies of induced pluripotent stem cells towards neuronal and glial cell types and cerebral organoids and their utilization in modeling AD and potential drug discovery.Graphical abstract

Parallel evolution of a splicing program controlling neuronal excitability in flies and mammals.

Alternative splicing increases neuronal transcriptomic complexity throughout animal phylogeny. To delve into the mechanisms controlling the assembly and evolution of this regulatory layer, we characterized the neuronal microexon program in Drosophila and compared it with that of mammals. In nonvertebrate bilaterians, this splicing program is restricted to neurons by the posttranscriptional processing of the enhancer of microexons (eMIC) domain in Srrm234. In Drosophila, this processing is dependent on regulation by Elav/Fne. eMIC deficiency or misexpression leads to widespread neurological alterations largely emerging from impaired neuronal activity, as revealed by a combination of neuronal imaging experiments and cell type–specific rescues. These defects are associated with the genome-wide skipping of short neural exons, which are strongly enriched in ion channels. We found no overlap of eMIC-regulated exons between flies and mice, illustrating how ancient posttranscriptional programs can evolve independently in different phyla to affect distinct cellular modules while maintaining cell-type specificity.

Single Cell Transcriptomic and Chromatin Profiles Suggest Layer Vb Is the Only Layer With Shared Excitatory Cell Types in the Medial and Lateral Entorhinal Cortex.

All brain functionality arises from the activity in neural circuits in different anatomical regions. These regions contain different circuits comprising unique cell types. An integral part to understanding neural circuits is a full census of the constituent parts, i.e., the neural cell types. This census can be based on different characteristics. Previously combinations of morphology and physiology, gene expression, and chromatin accessibility have been used in various cortical and subcortical regions. This has given an extensive yet incomplete overview of neural cell types. However, these techniques have not been applied to all brain regions. Here we apply single cell analysis of accessible chromatin on two similar but different cortical regions, the medial and the lateral entorhinal cortices. Even though these two regions are anatomically similar, their intrinsic and extrinsic connectivity are different. In 4,136 cells we identify 20 different clusters representing different cell types. As expected, excitatory cells show regionally specific clusters, whereas inhibitory neurons are shared between regions. We find that several deep layer excitatory neuronal cell types as defined by chromatin profile are also shared between the two different regions. Integration with a larger scRNA-seq dataset maintains this shared characteristic for cells in Layer Vb. Interestingly, this layer contains three clusters, two specific to either subregion and one shared between the two. These clusters can be putatively associated with particular functional and anatomical cell types found in this layer. This information is a step forwards into elucidating the cell types within the entorhinal circuit and by extension its functional underpinnings.

Juxtacellular opto-tagging of hippocampal CA1 neurons in freely moving mice.

Neural circuits are made of a vast diversity of neuronal cell types. While immense progress has been made in classifying neurons based on morphological, molecular, and functional properties, understanding how this heterogeneity contributes to brain function during natural behavior has remained largely unresolved. In the present study, we combined the juxtacellular recording and labeling technique with optogenetics in freely moving mice. This allowed us to selectively target molecularly defined cell classes for in vivo single-cell recordings and morphological analysis. We validated this strategy in the CA1 region of the mouse hippocampus by restricting Channelrhodopsin expression to Calbindin-positive neurons. Directly versus indirectly light-activated neurons could be readily distinguished based on the latencies of light-evoked spikes, with juxtacellular labeling and post hoc histological analysis providing 'ground-truth' validation. Using these opto-juxtacellular procedures in freely moving mice, we found that Calbindin-positive CA1 pyramidal cells were weakly spatially modulated and conveyed less spatial information than Calbindin-negative neurons - pointing to pyramidal cell identity as a key determinant for neuronal recruitment into the hippocampal spatial map. Thus, our method complements current in vivo techniques by enabling optogenetic-assisted structure-function analysis of single neurons recorded during natural, unrestrained behavior.

Intrinsic mechanisms in the gating of resurgent Na+ currents.

The resurgent component of the voltage-gated sodium current (INaR) is a depolarizing conductance, revealed on membrane hyperpolarizations following brief depolarizing voltage steps, which has been shown to contribute to regulating the firing properties of numerous neuronal cell types throughout the central and peripheral nervous systems. Although mediated by the same voltage-gated sodium (Nav) channels that underlie the transient and persistent Nav current components, the gating mechanisms that contribute to the generation of INaR remain unclear. Here, we characterized Nav currents in mouse cerebellar Purkinje neurons, and used tailored voltage-clamp protocols to define how the voltage and the duration of the initial membrane depolarization affect the amplitudes and kinetics of INaR. Using the acquired voltage-clamp data, we developed a novel Markov kinetic state model with parallel (fast and slow) inactivation pathways and, we show that this model reproduces the properties of the resurgent, as well as the transient and persistent, Nav currents recorded in (mouse) cerebellar Purkinje neurons. Based on the acquired experimental data and the simulations, we propose that resurgent Na+ influx occurs as a result of fast inactivating Nav channels transitioning into an open/conducting state on membrane hyperpolarization, and that the decay of INaR reflects the slow accumulation of recovered/opened Nav channels into a second, alternative and more slowly populated, inactivated state. Additional simulations reveal that extrinsic factors that affect the kinetics of fast or slow Nav channel inactivation and/or impact the relative distribution of Nav channels in the fast- and slow-inactivated states, such as the accessory Navβ4 channel subunit, can modulate the amplitude of INaR.

Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain.

The brain is composed of diverse neuronal and non-neuronal cell types with complex regional connectivity patterns that create the anatomical infrastructure underlying cognition. Remarkable advances in neuroscience techniques enable labeling and imaging of these individual cell types and their interactions throughout intact mammalian brains at a cellular resolution allowing neuroscientists to examine microscopic details in macroscopic brain circuits. Nevertheless, implementing these tools is fraught with many technical and analytical challenges with a need for high-level data analysis. Here we review key technical considerations for implementing a brain mapping pipeline using the mouse brain as a primary model system. Specifically, we provide practical details for choosing methods including cell type specific labeling, sample preparation (e.g., tissue clearing), microscopy modalities, image processing, and data analysis (e.g., image registration to standard atlases). We also highlight the need to develop better 3D atlases with standardized anatomical labels and nomenclature across species and developmental time points to extend the mapping to other species including humans and to facilitate data sharing, confederation, and integrative analysis. In summary, this review provides key elements and currently available resources to consider while developing and implementing high-resolution mapping methods.