1
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Naffaa MM. Neurogenesis dynamics in the olfactory bulb: deciphering circuitry organization, function, and adaptive plasticity. Neural Regen Res 2025; 20:1565-1581. [PMID: 38934393 PMCID: PMC11688548 DOI: 10.4103/nrr.nrr-d-24-00312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/20/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024] Open
Abstract
Adult neurogenesis persists after birth in the subventricular zone, with new neurons migrating to the granule cell layer and glomerular layers of the olfactory bulb, where they integrate into existing circuitry as inhibitory interneurons. The generation of these new neurons in the olfactory bulb supports both structural and functional plasticity, aiding in circuit remodeling triggered by memory and learning processes. However, the presence of these neurons, coupled with the cellular diversity within the olfactory bulb, presents an ongoing challenge in understanding its network organization and function. Moreover, the continuous integration of new neurons in the olfactory bulb plays a pivotal role in regulating olfactory information processing. This adaptive process responds to changes in epithelial composition and contributes to the formation of olfactory memories by modulating cellular connectivity within the olfactory bulb and interacting intricately with higher-order brain regions. The role of adult neurogenesis in olfactory bulb functions remains a topic of debate. Nevertheless, the functionality of the olfactory bulb is intricately linked to the organization of granule cells around mitral and tufted cells. This organizational pattern significantly impacts output, network behavior, and synaptic plasticity, which are crucial for olfactory perception and memory. Additionally, this organization is further shaped by axon terminals originating from cortical and subcortical regions. Despite the crucial role of olfactory bulb in brain functions and behaviors related to olfaction, these complex and highly interconnected processes have not been comprehensively studied as a whole. Therefore, this manuscript aims to discuss our current understanding and explore how neural plasticity and olfactory neurogenesis contribute to enhancing the adaptability of the olfactory system. These mechanisms are thought to support olfactory learning and memory, potentially through increased complexity and restructuring of neural network structures, as well as the addition of new granule granule cells that aid in olfactory adaptation. Additionally, the manuscript underscores the importance of employing precise methodologies to elucidate the specific roles of adult neurogenesis amidst conflicting data and varying experimental paradigms. Understanding these processes is essential for gaining insights into the complexities of olfactory function and behavior.
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Affiliation(s)
- Moawiah M. Naffaa
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Department of Cell Biology, Duke University School of Medicine, Durham, NC, USA
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2
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Moore JR, Nemera MT, D'Souza RD, Hamagami N, Clemens AW, Beard DC, Urman A, Razia Y, Rodriguez Mendoza V, Law TE, Edwards JR, Gabel HW. MeCP2 and non-CG DNA methylation stabilize the expression of long genes that distinguish closely related neuron types. Nat Neurosci 2025:10.1038/s41593-025-01947-w. [PMID: 40355611 DOI: 10.1038/s41593-025-01947-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/14/2025] [Indexed: 05/14/2025]
Abstract
The diversity of mammalian neurons is delineated by subtle gene expression differences that may require specialized mechanisms to be maintained. Neurons uniquely express the longest genes in the genome and use non-CG DNA methylation (mCA), together with the Rett syndrome protein methyl-CpG-binding protein 2 (MeCP2), to control gene expression. However, whether these distinctive gene structures and molecular machinery regulate neuronal diversity remains unexplored. Here, we use genomic and spatial transcriptomic analyses to show that MeCP2 maintains transcriptomic diversity across closely related neuron types. We uncover differential susceptibility of neuronal populations to MeCP2 loss according to global mCA levels and dissect methylation patterns driving shared and distinct MeCP2 gene regulation. We show that MeCP2 regulates long, mCA-enriched, 'repeatedly tuned' genes, that is, genes differentially expressed between many closely related neuron types, including across spatially distinct, vision-dependent gene programs in the visual cortex. Thus, MeCP2 maintains neuron type-specific gene programs to facilitate cellular diversity in the brain.
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Affiliation(s)
- J Russell Moore
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Mati T Nemera
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Rinaldo D D'Souza
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicole Hamagami
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Adam W Clemens
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Diana C Beard
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Alaina Urman
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Medicine, Division of Oncology, Washington University, St. Louis, MO, USA
| | - Yasmin Razia
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Victoria Rodriguez Mendoza
- Opportunities in Genomic Research Program, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Travis E Law
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Medicine, Division of Oncology, Washington University, St. Louis, MO, USA
| | - John R Edwards
- Department of Medicine, Division of Oncology, Washington University, St. Louis, MO, USA
| | - Harrison W Gabel
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA.
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3
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Schneider-Mizell CM, Bodor AL, Brittain D, Buchanan J, Bumbarger DJ, Elabbady L, Gamlin C, Kapner D, Kinn S, Mahalingam G, Seshamani S, Suckow S, Takeno M, Torres R, Yin W, Dorkenwald S, Bae JA, Castro MA, Halageri A, Jia Z, Jordan C, Kemnitz N, Lee K, Li K, Lu R, Macrina T, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Silversmith W, Turner NL, Wong W, Wu J, Reimer J, Tolias AS, Seung HS, Reid RC, Collman F, da Costa NM. Inhibitory specificity from a connectomic census of mouse visual cortex. Nature 2025; 640:448-458. [PMID: 40205209 PMCID: PMC11981935 DOI: 10.1038/s41586-024-07780-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 07/03/2024] [Indexed: 04/11/2025]
Abstract
Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties1. Synaptic connectivity shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here we used millimetre-scale volumetric electron microscopy2 to investigate the connectivity of all inhibitory neurons across a densely segmented neuronal population of 1,352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibition with more than 70,000 synapses. Inspired by classical neuroanatomy, we classified inhibitory neurons based on targeting of dendritic compartments and developed an excitatory neuron classification based on dendritic reconstructions with whole-cell maps of synaptic input. Single-cell connectivity showed a class of disinhibitory specialist that targets basket cells. Analysis of inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of spatially intermingled subpopulations. Inhibitory targeting was organized into 'motif groups', diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking contemporary multimodal neuronal atlases with the cortical wiring diagram.
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Affiliation(s)
| | | | | | | | | | | | - Clare Gamlin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Sam Kinn
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Marc Takeno
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Wenjing Yin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - J Alexander Bae
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Electrical and Computer Engineering Department, Princeton University, Princeton, NJ, USA
| | - Manuel A Castro
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Akhilesh Halageri
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Zhen Jia
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - Chris Jordan
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Kisuk Lee
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Kai Li
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - Ran Lu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Thomas Macrina
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - Eric Mitchell
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Shanka Subhra Mondal
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Electrical and Computer Engineering Department, Princeton University, Princeton, NJ, USA
| | - Shang Mu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Barak Nehoran
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - Sergiy Popovych
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | | | - Nicholas L Turner
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - William Wong
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Jingpeng Wu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Jacob Reimer
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, USA
- Brain & Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - H Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Computer Science Department, Princeton University, Princeton, NJ, USA
| | - R Clay Reid
- Allen Institute for Brain Science, Seattle, WA, USA
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4
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Xie F, Jain S, Xu R, Butrus S, Tan Z, Xu X, Shekhar K, Zipursky SL. Spatial profiling of the interplay between cell type- and vision-dependent transcriptomic programs in the visual cortex. Proc Natl Acad Sci U S A 2025; 122:e2421022122. [PMID: 39946537 PMCID: PMC11848306 DOI: 10.1073/pnas.2421022122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Accepted: 01/07/2025] [Indexed: 02/19/2025] Open
Abstract
How early sensory experience during "critical periods" of postnatal life affects the organization of the mammalian neocortex at the resolution of neuronal cell types is poorly understood. We previously reported that the functional and molecular profiles of layer 2/3 (L2/3) cell types in the primary visual cortex (V1) are vision-dependent [S. Cheng et al., Cell 185, 311-327.e24 (2022)]. Here, we characterize the spatial organization of L2/3 cell types with and without visual experience. Spatial transcriptomic profiling based on 500 genes recapitulates the zonation of L2/3 cell types along the pial-ventricular axis in V1. By applying multitasking theory, we suggest that the spatial zonation of L2/3 cell types is linked to the continuous nature of their gene expression profiles, which can be represented as a 2D manifold bounded by three archetypal cell types. By comparing normally reared and dark reared L2/3 cells, we show that visual deprivation-induced transcriptomic changes comprise two independent gene programs. The first, induced specifically in the visual cortex, includes immediate-early genes and genes associated with metabolic processes. It manifests as a change in cell state that is orthogonal to cell-type-specific gene expression programs. By contrast, the second program impacts L2/3 cell-type identity, regulating a subset of cell-type-specific genes and shifting the distribution of cells within the L2/3 cell-type manifold. Through an integrated analysis of spatial transcriptomics with single-nucleus RNA-seq data, we describe how vision patterns cortical L2/3 cell types during the critical period.
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Affiliation(s)
- Fangming Xie
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, CA90095
| | - Saumya Jain
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, CA90095
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA30332
| | - Runzhe Xu
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, CA90095
| | - Salwan Butrus
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA94720
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA94720
| | - Zhiqun Tan
- Department of Anatomy and Neurobiology, Center for Neural Circuit Mapping, Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA92697
| | - Xiangmin Xu
- Department of Anatomy and Neurobiology, Center for Neural Circuit Mapping, Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA92697
| | - Karthik Shekhar
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA94720
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA94720
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA94720
| | - S. Lawrence Zipursky
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, CA90095
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5
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Cassidy RM, Macias AV, Lagos WN, Ugorji C, Callaway EM. Complementary Organization of Mouse Driver and Modulator Cortico-thalamo-cortical Circuits. J Neurosci 2025; 45:e1167242024. [PMID: 39824633 PMCID: PMC11780356 DOI: 10.1523/jneurosci.1167-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 10/30/2024] [Accepted: 11/11/2024] [Indexed: 01/20/2025] Open
Abstract
Corticocortical (CC) projections in the visual system facilitate hierarchical processing of sensory information. In addition to direct CC connections, indirect cortico-thalamo-cortical (CTC) pathways through the pulvinar nucleus of the thalamus can relay sensory signals and mediate cortical interactions according to behavioral demands. While the pulvinar connects extensively to the entire visual cortex, it is unknown whether transthalamic pathways link all cortical areas or whether they follow systematic organizational rules. Because mouse pulvinar neurons projecting to different areas are spatially intermingled, their input/output relationships have been difficult to characterize using traditional anatomical methods. To determine the organization of CTC circuits, we mapped the higher visual areas (HVAs) of male and female mice with intrinsic signal imaging and targeted five pulvinar→HVA pathways for projection-specific rabies tracing. We aligned postmortem cortical tissue to in vivo maps for precise quantification of the areas and cell types projecting to each pulvinar→HVA population. Layer 5 corticothalamic (L5CT) "driver" inputs to the pulvinar originate predominantly from primary visual cortex (V1), consistent with the CC hierarchy. L5CT inputs from lateral HVAs specifically avoid driving reciprocal connections, consistent with the "no-strong-loops" hypothesis. Conversely, layer 6 corticothalamic (L6CT) "modulator" inputs are distributed across areas and are biased toward reciprocal connections. Unlike previous studies in primates, we find that every HVA receives disynaptic input from the superior colliculus. CTC circuits in the pulvinar thus depend on both target HVA and input cell type, such that driving and modulating higher-order pathways follow complementary connection rules similar to those governing first-order CT circuits.
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Affiliation(s)
- Rachel M Cassidy
- The Salk Institute for Biological Studies, La Jolla, California 92037
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California 92037
| | - Angel V Macias
- The Salk Institute for Biological Studies, La Jolla, California 92037
| | - Willian N Lagos
- The Salk Institute for Biological Studies, La Jolla, California 92037
| | - Chiamaka Ugorji
- The Salk Institute for Biological Studies, La Jolla, California 92037
| | - Edward M Callaway
- The Salk Institute for Biological Studies, La Jolla, California 92037
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California 92037
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6
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Han X, Bonin V. Higher-order cortical and thalamic pathways shape visual processing streams in the mouse cortex. Curr Biol 2024; 34:5671-5684.e6. [PMID: 39566501 DOI: 10.1016/j.cub.2024.10.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 07/21/2024] [Accepted: 10/17/2024] [Indexed: 11/22/2024]
Abstract
Mammalian visual functions rely on distributed processing across interconnected cortical and subcortical regions. In higher-order visual areas (HVAs), visual features are processed in specialized streams that integrate feedforward and higher-order inputs from intracortical and thalamocortical pathways. However, the precise circuit organization responsible for HVA specialization remains unclear. We investigated the cellular architecture of primary visual cortex (V1) and higher-order visual pathways in the mouse, focusing on their roles in shaping visual representations. Using in vivo functional imaging and neural circuit tracing, we found that HVAs preferentially receive inputs from both V1 and higher-order pathways tuned to similar spatiotemporal properties, with the strongest selectivity seen in layer 2/3 neurons. These neurons exhibit target-specific tuning and sublaminar specificity in their projections, reflecting cell-type-specific visual information flow. In contrast, HVA layer 5 pathways nonspecifically broadcast visual signals across cortical areas, suggesting a role in distributing HVA outputs. Additionally, thalamocortical pathways from the lateral posterior thalamic nucleus (LP) provide highly specific, nearly non-overlapping visual inputs to HVAs, complementing intracortical inputs and contributing to input functional diversity. Our findings suggest that the convergence of laminar and cell-type-specific pathways V1 and higher-order intracortical and thalamocortical pathways plays a key role in shaping the functional specialization and diversity of HVAs.
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Affiliation(s)
- Xu Han
- Neuro-Electronics Research Flanders, 3000 Leuven, Belgium; KU Leuven, Department of Biology & Leuven Brain Institute, 3000 Leuven, Belgium; VIB, 3000 Leuven, Belgium.
| | - Vincent Bonin
- Neuro-Electronics Research Flanders, 3000 Leuven, Belgium; KU Leuven, Department of Biology & Leuven Brain Institute, 3000 Leuven, Belgium; VIB, 3000 Leuven, Belgium.
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7
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Patiño M, Rossa MA, Lagos WN, Patne NS, Callaway EM. Transcriptomic cell-type specificity of local cortical circuits. Neuron 2024; 112:3851-3866.e4. [PMID: 39353431 PMCID: PMC11624072 DOI: 10.1016/j.neuron.2024.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 07/02/2024] [Accepted: 09/04/2024] [Indexed: 10/04/2024]
Abstract
Complex neocortical functions rely on networks of diverse excitatory and inhibitory neurons. While local connectivity rules between major neuronal subclasses have been established, the specificity of connections at the level of transcriptomic subtypes remains unclear. We introduce single transcriptome assisted rabies tracing (START), a method combining monosynaptic rabies tracing and single-nuclei RNA sequencing to identify transcriptomic cell types, providing inputs to defined neuron populations. We employ START to transcriptomically characterize inhibitory neurons providing monosynaptic input to 5 different layer-specific excitatory cortical neuron populations in mouse primary visual cortex (V1). At the subclass level, we observe results consistent with findings from prior studies that resolve neuronal subclasses using antibody staining, transgenic mouse lines, and morphological reconstruction. With improved neuronal subtype granularity achieved with START, we demonstrate transcriptomic subtype specificity of inhibitory inputs to various excitatory neuron subclasses. These results establish local connectivity rules at the resolution of transcriptomic inhibitory cell types.
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Affiliation(s)
- Maribel Patiño
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA; Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
| | - Marley A Rossa
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA; Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Willian Nuñez Lagos
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Neelakshi S Patne
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA; Neuroscience Graduate Program, Boston University, Boston, MA, USA
| | - Edward M Callaway
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
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8
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Chen X. Reimagining Cortical Connectivity by Deconstructing Its Molecular Logic into Building Blocks. Cold Spring Harb Perspect Biol 2024; 16:a041509. [PMID: 38621822 PMCID: PMC11529856 DOI: 10.1101/cshperspect.a041509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
Comprehensive maps of neuronal connectivity provide a foundation for understanding the structure of neural circuits. In a circuit, neurons are diverse in morphology, electrophysiology, gene expression, activity, and other neuronal properties. Thus, constructing a comprehensive connectivity map requires associating various properties of neurons, including their connectivity, at cellular resolution. A commonly used approach is to use the gene expression profiles as an anchor to which all other neuronal properties are associated. Recent advances in genomics and anatomical techniques dramatically improved the ability to determine and associate the long-range projections of neurons with their gene expression profiles. These studies revealed unprecedented details of the gene-projection relationship, but also highlighted conceptual challenges in understanding this relationship. In this article, I delve into the findings and the challenges revealed by recent studies using state-of-the-art neuroanatomical and transcriptomic techniques. Building upon these insights, I propose an approach that focuses on understanding the gene-projection relationship through basic features in gene expression profiles and projections, respectively, that associate with underlying cellular processes. I then discuss how the developmental trajectories of projections and gene expression profiles create additional challenges and necessitate interrogating the gene-projection relationship across time. Finally, I explore complementary strategies that, together, can provide a comprehensive view of the gene-projection relationship.
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Affiliation(s)
- Xiaoyin Chen
- Allen Institute for Brain Science, Seattle, Washington 98109, USA
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9
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McCollum M, Manning A, Bender PTR, Mendelson BZ, Anderson CT. Cell-type-specific enhancement of deviance detection by synaptic zinc in the mouse auditory cortex. Proc Natl Acad Sci U S A 2024; 121:e2405615121. [PMID: 39312661 PMCID: PMC11459170 DOI: 10.1073/pnas.2405615121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 08/15/2024] [Indexed: 09/25/2024] Open
Abstract
Stimulus-specific adaptation is a hallmark of sensory processing in which a repeated stimulus results in diminished successive neuronal responses, but a deviant stimulus will still elicit robust responses from the same neurons. Recent work has established that synaptically released zinc is an endogenous mechanism that shapes neuronal responses to sounds in the auditory cortex. Here, to understand the contributions of synaptic zinc to deviance detection of specific neurons, we performed wide-field and 2-photon calcium imaging of multiple classes of cortical neurons. We find that intratelencephalic (IT) neurons in both layers 2/3 and 5 as well as corticocollicular neurons in layer 5 all demonstrate deviance detection; however, we find a specific enhancement of deviance detection in corticocollicular neurons that arises from ZnT3-dependent synaptic zinc in layer 2/3 IT neurons. Genetic deletion of ZnT3 from layer 2/3 IT neurons removes the enhancing effects of synaptic zinc on corticocollicular neuron deviance detection and results in poorer acuity of detecting deviant sounds by behaving mice.
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Affiliation(s)
- Mason McCollum
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV26505
| | - Abbey Manning
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV26505
| | - Philip T. R. Bender
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV26505
| | - Benjamin Z. Mendelson
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV26505
| | - Charles T. Anderson
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV26505
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10
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Dembrow NC, Sawchuk S, Dalley R, Opitz-Araya X, Hudson M, Radaelli C, Alfiler L, Walling-Bell S, Bertagnolli D, Goldy J, Johansen N, Miller JA, Nasirova K, Owen SF, Parga-Becerra A, Taskin N, Tieu M, Vumbaco D, Weed N, Wilson J, Lee BR, Smith KA, Sorensen SA, Spain WJ, Lein ES, Perlmutter SI, Ting JT, Kalmbach BE. Areal specializations in the morpho-electric and transcriptomic properties of primate layer 5 extratelencephalic projection neurons. Cell Rep 2024; 43:114718. [PMID: 39277859 PMCID: PMC11488157 DOI: 10.1016/j.celrep.2024.114718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 07/22/2024] [Accepted: 08/20/2024] [Indexed: 09/17/2024] Open
Abstract
Large-scale analysis of single-cell gene expression has revealed transcriptomically defined cell subclasses present throughout the primate neocortex with gene expression profiles that differ depending upon neocortical region. Here, we test whether the interareal differences in gene expression translate to regional specializations in the physiology and morphology of infragranular glutamatergic neurons by performing Patch-seq experiments in brain slices from the temporal cortex (TCx) and motor cortex (MCx) of the macaque. We confirm that transcriptomically defined extratelencephalically projecting neurons of layer 5 (L5 ET neurons) include retrogradely labeled corticospinal neurons in the MCx and find multiple physiological properties and ion channel genes that distinguish L5 ET from non-ET neurons in both areas. Additionally, while infragranular ET and non-ET neurons retain distinct neuronal properties across multiple regions, there are regional morpho-electric and gene expression specializations in the L5 ET subclass, providing mechanistic insights into the specialized functional architecture of the primate neocortex.
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Affiliation(s)
- Nikolai C Dembrow
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Epilepsy Center of Excellence, Department of Veterans Affairs Medical Center, Seattle, WA 98108, USA.
| | - Scott Sawchuk
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Rachel Dalley
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Mark Hudson
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA
| | | | - Lauren Alfiler
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | | | - Scott F Owen
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Alejandro Parga-Becerra
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Naz Taskin
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - David Vumbaco
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Natalie Weed
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Julia Wilson
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Brian R Lee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | | | - William J Spain
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Epilepsy Center of Excellence, Department of Veterans Affairs Medical Center, Seattle, WA 98108, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Steve I Perlmutter
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Washington National Primate Research Center, Seattle, WA 98195, USA
| | - Jonathan T Ting
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Allen Institute for Brain Science, Seattle, WA 98109, USA; Washington National Primate Research Center, Seattle, WA 98195, USA
| | - Brian E Kalmbach
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Allen Institute for Brain Science, Seattle, WA 98109, USA.
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11
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Mao X, Staiger JF. Multimodal cortical neuronal cell type classification. Pflugers Arch 2024; 476:721-733. [PMID: 38376567 PMCID: PMC11033238 DOI: 10.1007/s00424-024-02923-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 02/01/2024] [Accepted: 02/07/2024] [Indexed: 02/21/2024]
Abstract
Since more than a century, neuroscientists have distinguished excitatory (glutamatergic) neurons with long-distance projections from inhibitory (GABAergic) neurons with local projections and established layer-dependent schemes for the ~ 80% excitatory (principal) cells as well as the ~ 20% inhibitory neurons. Whereas, in the early days, mainly morphological criteria were used to define cell types, later supplemented by electrophysiological and neurochemical properties, nowadays. single-cell transcriptomics is the method of choice for cell type classification. Bringing recent insight together, we conclude that despite all established layer- and area-dependent differences, there is a set of reliably identifiable cortical cell types that were named (among others) intratelencephalic (IT), extratelencephalic (ET), and corticothalamic (CT) for the excitatory cells, which altogether comprise ~ 56 transcriptomic cell types (t-types). By the same means, inhibitory neurons were subdivided into parvalbumin (PV), somatostatin (SST), vasoactive intestinal polypeptide (VIP), and "other (i.e. Lamp5/Sncg)" subpopulations, which altogether comprise ~ 60 t-types. The coming years will show which t-types actually translate into "real" cell types that show a common set of multimodal features, including not only transcriptome but also physiology and morphology as well as connectivity and ultimately function. Only with the better knowledge of clear-cut cell types and experimental access to them, we will be able to reveal their specific functions, a task which turned out to be difficult in a part of the brain being so much specialized for cognition as the cerebral cortex.
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Affiliation(s)
- Xiaoyi Mao
- Institute for Neuroanatomy, University Medical Center Göttingen, Georg-August-University, Kreuzbergring 36, 37075, Göttingen, Germany
| | - Jochen F Staiger
- Institute for Neuroanatomy, University Medical Center Göttingen, Georg-August-University, Kreuzbergring 36, 37075, Göttingen, Germany.
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12
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Yang L, Liu F, Hahm H, Okuda T, Li X, Zhang Y, Kalyanaraman V, Heitmeier MR, Samineni VK. Projection-TAGs enable multiplex projection tracing and multi-modal profiling of projection neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.590975. [PMID: 38712231 PMCID: PMC11071495 DOI: 10.1101/2024.04.24.590975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Single-cell multiomic techniques have sparked immense interest in developing a comprehensive multi-modal map of diverse neuronal cell types and their brain wide projections. However, investigating the spatial organization, transcriptional and epigenetic landscapes of brain wide projection neurons is hampered by the lack of efficient and easily adoptable tools. Here we introduce Projection-TAGs, a retrograde AAV platform that allows multiplex tagging of projection neurons using RNA barcodes. By using Projection-TAGs, we performed multiplex projection tracing of the mouse cortex and high-throughput single-cell profiling of the transcriptional and epigenetic landscapes of the cortical projection neurons. Projection-TAGs can be leveraged to obtain a snapshot of activity-dependent recruitment of distinct projection neurons and their molecular features in the context of a specific stimulus. Given its flexibility, usability, and compatibility, we envision that Projection-TAGs can be readily applied to build a comprehensive multi-modal map of brain neuronal cell types and their projections.
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Affiliation(s)
- Lite Yang
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
- Neuroscience Graduate Program, Division of Biology & Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, United States
| | - Fang Liu
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Hannah Hahm
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Takao Okuda
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Xiaoyue Li
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Yufen Zhang
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Vani Kalyanaraman
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Monique R. Heitmeier
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Vijay K. Samineni
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
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13
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Mazo C, Baeta M, Petreanu L. Auditory cortex conveys non-topographic sound localization signals to visual cortex. Nat Commun 2024; 15:3116. [PMID: 38600132 PMCID: PMC11006897 DOI: 10.1038/s41467-024-47546-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 04/02/2024] [Indexed: 04/12/2024] Open
Abstract
Spatiotemporally congruent sensory stimuli are fused into a unified percept. The auditory cortex (AC) sends projections to the primary visual cortex (V1), which could provide signals for binding spatially corresponding audio-visual stimuli. However, whether AC inputs in V1 encode sound location remains unknown. Using two-photon axonal calcium imaging and a speaker array, we measured the auditory spatial information transmitted from AC to layer 1 of V1. AC conveys information about the location of ipsilateral and contralateral sound sources to V1. Sound location could be accurately decoded by sampling AC axons in V1, providing a substrate for making location-specific audiovisual associations. However, AC inputs were not retinotopically arranged in V1, and audio-visual modulations of V1 neurons did not depend on the spatial congruency of the sound and light stimuli. The non-topographic sound localization signals provided by AC might allow the association of specific audiovisual spatial patterns in V1 neurons.
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Affiliation(s)
- Camille Mazo
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
| | - Margarida Baeta
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Leopoldo Petreanu
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
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14
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Shen Y, Shao M, Hao ZZ, Huang M, Xu N, Liu S. Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity. Neurosci Bull 2024; 40:517-532. [PMID: 38194157 PMCID: PMC11003949 DOI: 10.1007/s12264-023-01160-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 09/23/2023] [Indexed: 01/10/2024] Open
Abstract
Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.
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Affiliation(s)
- Yuhui Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mingting Shao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Mengyao Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Nana Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, 510060, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, 510080, China.
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15
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Tereshenko V, Dotzauer DC, Schmoll M, Harnoncourt L, Carrero Rojas G, Gfrerer L, Eberlin KR, Austen WG, Blumer R, Farina D, Aszmann OC. Peripheral neural interfaces: Skeletal muscles are hyper-reinnervated according to the axonal capacity of the surgically rewired nerves. SCIENCE ADVANCES 2024; 10:eadj3872. [PMID: 38416828 PMCID: PMC10901366 DOI: 10.1126/sciadv.adj3872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 01/23/2024] [Indexed: 03/01/2024]
Abstract
Advances in robotics have outpaced the capabilities of man-machine interfaces to decipher and transfer neural information to and from prosthetic devices. We emulated clinical scenarios where high- (facial) or low-neural capacity (ulnar) donor nerves were surgically rewired to the sternomastoid muscle, which is controlled by a very small number of motor axons. Using retrograde tracing and electrophysiological assessments, we observed a nearly 15-fold functional hyper-reinnervation of the muscle after high-capacity nerve transfer, demonstrating its capability of generating a multifold of neuromuscular junctions. Moreover, the surgically redirected axons influenced the muscle's physiological characteristics, by altering the expression of myosin heavy-chain types in alignment with the donor nerve. These findings highlight the remarkable capacity of skeletal muscles to act as biological amplifiers of neural information from the spinal cord for governing bionic prostheses, with the potential of expressing high-dimensional neural function for high-information transfer interfaces.
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Affiliation(s)
- Vlad Tereshenko
- Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna, Vienna, Austria
| | - Dominik C Dotzauer
- Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna, Vienna, Austria
| | - Martin Schmoll
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Leopold Harnoncourt
- Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna, Vienna, Austria
| | - Genova Carrero Rojas
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Lisa Gfrerer
- Division of Plastic and Reconstructive Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Kyle R Eberlin
- Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - William G Austen
- Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roland Blumer
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Dario Farina
- Department of Bioengineering, Imperial College London, South Kensington Campus London, SW7 2AZ London, UK
| | - Oskar C Aszmann
- Clinical Laboratory for Bionic Extremity Reconstruction, Medical University of Vienna, Vienna, Austria
- Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
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16
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Moore JR, Nemera MT, D’Souza RD, Hamagami N, Clemens AW, Beard DC, Urman A, Mendoza VR, Gabel HW. Non-CG DNA methylation and MeCP2 stabilize repeated tuning of long genes that distinguish closely related neuron types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.30.577861. [PMID: 38352532 PMCID: PMC10862856 DOI: 10.1101/2024.01.30.577861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
The extraordinary diversity of neuron types in the mammalian brain is delineated at the highest resolution by subtle gene expression differences that may require specialized molecular mechanisms to be maintained. Neurons uniquely express the longest genes in the genome and utilize neuron-enriched non-CG DNA methylation (mCA) together with the Rett syndrome protein, MeCP2, to control gene expression, but the function of these unique gene structures and machinery in regulating finely resolved neuron type-specific gene programs has not been explored. Here, we employ epigenomic and spatial transcriptomic analyses to discover a major role for mCA and MeCP2 in maintaining neuron type-specific gene programs at the finest scale of cellular resolution. We uncover differential susceptibility to MeCP2 loss in neuronal populations depending on global mCA levels and dissect methylation patterns and intragenic enhancer repression that drive overlapping and distinct gene regulation between neuron types. Strikingly, we show that mCA and MeCP2 regulate genes that are repeatedly tuned to differentiate neuron types at the highest cellular resolution, including spatially resolved, vision-dependent gene programs in the visual cortex. These repeatedly tuned genes display genomic characteristics, including long length, numerous intragenic enhancers, and enrichment for mCA, that predispose them to regulation by MeCP2. Thus, long gene regulation by the MeCP2 pathway maintains differential gene expression between closely-related neurons to facilitate the exceptional cellular diversity in the complex mammalian brain.
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Affiliation(s)
- J. Russell Moore
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Mati T. Nemera
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Rinaldo D. D’Souza
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Nicole Hamagami
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Adam W. Clemens
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Diana C. Beard
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Alaina Urman
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Victoria Rodriguez Mendoza
- Opportunities in Genomic Research Program, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Harrison W. Gabel
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
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17
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Schneider-Mizell CM, Bodor AL, Brittain D, Buchanan J, Bumbarger DJ, Elabbady L, Gamlin C, Kapner D, Kinn S, Mahalingam G, Seshamani S, Suckow S, Takeno M, Torres R, Yin W, Dorkenwald S, Bae JA, Castro MA, Halageri A, Jia Z, Jordan C, Kemnitz N, Lee K, Li K, Lu R, Macrina T, Mitchell E, Mondal SS, Mu S, Nehoran B, Popovych S, Silversmith W, Turner NL, Wong W, Wu J, Reimer J, Tolias AS, Seung HS, Reid RC, Collman F, Maçarico da Costa N. Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.23.525290. [PMID: 36747710 PMCID: PMC9900837 DOI: 10.1101/2023.01.23.525290] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into "motif groups," diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Sam Kinn
- Allen Institute for Brain Science, Seattle, WA
| | | | | | | | - Marc Takeno
- Allen Institute for Brain Science, Seattle, WA
| | | | - Wenjing Yin
- Allen Institute for Brain Science, Seattle, WA
| | - Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - J Alexander Bae
- Princeton Neuroscience Institute, Princeton University, NJ
- Electrical and Computer Engineering Department, Princeton University
| | | | | | - Zhen Jia
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - Chris Jordan
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Kisuk Lee
- Brain & Cognitive Sciences Department, Massachusetts Institute of Technology
| | - Kai Li
- Computer Science Department, Princeton University
| | - Ran Lu
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Thomas Macrina
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - Eric Mitchell
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Shanka Subhra Mondal
- Princeton Neuroscience Institute, Princeton University, NJ
- Electrical and Computer Engineering Department, Princeton University
| | - Shang Mu
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Barak Nehoran
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - Sergiy Popovych
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | | | - Nicholas L Turner
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - William Wong
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Jingpeng Wu
- Princeton Neuroscience Institute, Princeton University, NJ
| | - Jacob Reimer
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, TX
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine
- Department of Electrical and Computer Engineering, Rice University
| | - H Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, NJ
- Computer Science Department, Princeton University
| | - R Clay Reid
- Allen Institute for Brain Science, Seattle, WA
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18
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Rader Groves AM, Gallimore CG, Hamm JP. Modern Methods for Unraveling Cell- and Circuit-Level Mechanisms of Neurophysiological Biomarkers in Psychiatry. ADVANCES IN NEUROBIOLOGY 2024; 40:157-188. [PMID: 39562445 DOI: 10.1007/978-3-031-69491-2_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2024]
Abstract
Methods for studying the mammalian brain in vivo have advanced dramatically in the past two decades. State-of-the-art optical and electrophysiological techniques allow direct recordings of the functional dynamics of thousands of neurons across distributed brain circuits with single-cell resolution. With transgenic tools, specific neuron types, pathways, and/or neurotransmitters can be targeted in user-determined brain areas for precise measurement and manipulation. In this chapter, we catalog these advancements. We emphasize that the impact of this methodological revolution on neuropsychiatry remains uncertain. This stems from the fact that these tools remain mostly limited to research in mice. And while translational paradigms are needed, recapitulations of human psychiatric disease states (e.g., schizophrenia) in animal models are inherently challenging to validate and may have limited utility in heterogeneous disease populations. Here we focus on an alternative strategy aimed at the study of neurophysiological biomarkers-the subject of this volume-translated to animal models, where precision neuroscience tools can be applied to provide molecular, cellular, and circuit-level insights and novel therapeutic targets. We summarize several examples of this approach throughout the chapter and emphasize the importance of careful experimental design and choice of dependent measures.
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Affiliation(s)
- A M Rader Groves
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA, USA
| | - C G Gallimore
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA, USA
| | - J P Hamm
- Neuroscience Institute, Georgia State University, Petit Science Center, Atlanta, GA, USA.
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19
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Malaguti M, Lebek T, Blin G, Lowell S. Enabling neighbour labelling: using synthetic biology to explore how cells influence their neighbours. Development 2024; 151:dev201955. [PMID: 38165174 PMCID: PMC10820747 DOI: 10.1242/dev.201955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 11/28/2023] [Indexed: 01/03/2024]
Abstract
Cell-cell interactions are central to development, but exploring how a change in any given cell relates to changes in the neighbour of that cell can be technically challenging. Here, we review recent developments in synthetic biology and image analysis that are helping overcome this problem. We highlight the opportunities presented by these advances and discuss opportunities and limitations in applying them to developmental model systems.
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Affiliation(s)
- Mattias Malaguti
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Tamina Lebek
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Guillaume Blin
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
| | - Sally Lowell
- Centre for Regenerative Medicine, Institute for Stem Cell Research, School of Biological Sciences, University of Edinburgh, 5 Little France Drive, Edinburgh EH16 4UU, UK
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20
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Zhou J, Zhang Z, Wu M, Liu H, Pang Y, Bartlett A, Peng Z, Ding W, Rivkin A, Lagos WN, Williams E, Lee CT, Miyazaki PA, Aldridge A, Zeng Q, Salinda JLA, Claffey N, Liem M, Fitzpatrick C, Boggeman L, Yao Z, Smith KA, Tasic B, Altshul J, Kenworthy MA, Valadon C, Nery JR, Castanon RG, Patne NS, Vu M, Rashid M, Jacobs M, Ito T, Osteen J, Emerson N, Lee J, Cho S, Rink J, Huang HH, Pinto-Duartec A, Dominguez B, Smith JB, O'Connor C, Zeng H, Chen S, Lee KF, Mukamel EA, Jin X, Margarita Behrens M, Ecker JR, Callaway EM. Brain-wide correspondence of neuronal epigenomics and distant projections. Nature 2023; 624:355-365. [PMID: 38092919 PMCID: PMC10719087 DOI: 10.1038/s41586-023-06823-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023]
Abstract
Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.
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Affiliation(s)
- Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Zhuzhu Zhang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | - May Wu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Yan Pang
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Zihao Peng
- School of Mathematics and Computer Science, Nanchang University, Nanchang, China
- Henan Engineering Research Center of Intelligent Technology and Application, Henan University, Kaifeng, China
| | - Wubin Ding
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Angeline Rivkin
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Will N Lagos
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Elora Williams
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cheng-Ta Lee
- Peptide Biology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Paula Assakura Miyazaki
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Andrew Aldridge
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Qiurui Zeng
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - J L Angelo Salinda
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Michelle Liem
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Conor Fitzpatrick
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lara Boggeman
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Jordan Altshul
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Mia A Kenworthy
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rosa G Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Neelakshi S Patne
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Minh Vu
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Mohammad Rashid
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Matthew Jacobs
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Tony Ito
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Julia Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Nora Emerson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jasper Lee
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Silvia Cho
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jon Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Hsiang-Hsuan Huang
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - António Pinto-Duartec
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bertha Dominguez
- Peptide Biology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jared B Smith
- Molecular Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Carolyn O'Connor
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Shengbo Chen
- Henan Engineering Research Center of Intelligent Technology and Application, Henan University, Kaifeng, China
- School of Computer and Information Engineering, Henan University, Kaifeng, China
| | - Kuo-Fen Lee
- Peptide Biology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Eran A Mukamel
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
| | - Xin Jin
- Center for Motor Control and Disease, Key Laboratory of Brain Functional Genomics, East China Normal University, Shanghai, China
- NYU-ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai, China
| | - M Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Edward M Callaway
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA.
- Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA, USA.
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21
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Sorensen SA, Gouwens NW, Wang Y, Mallory M, Budzillo A, Dalley R, Lee B, Gliko O, Kuo HC, Kuang X, Mann R, Ahmadinia L, Alfiler L, Baftizadeh F, Baker K, Bannick S, Bertagnolli D, Bickley K, Bohn P, Brown D, Bomben J, Brouner K, Chen C, Chen K, Chvilicek M, Collman F, Daigle T, Dawes T, de Frates R, Dee N, DePartee M, Egdorf T, El-Hifnawi L, Enstrom R, Esposito L, Farrell C, Gala R, Glomb A, Gamlin C, Gary A, Goldy J, Gu H, Hadley K, Hawrylycz M, Henry A, Hill D, Hirokawa KE, Huang Z, Johnson K, Juneau Z, Kebede S, Kim L, Lee C, Lesnar P, Li A, Glomb A, Li Y, Liang E, Link K, Maxwell M, McGraw M, McMillen DA, Mukora A, Ng L, Ochoa T, Oldre A, Park D, Pom CA, Popovich Z, Potekhina L, Rajanbabu R, Ransford S, Reding M, Ruiz A, Sandman D, Siverts L, Smith KA, Stoecklin M, Sulc J, Tieu M, Ting J, Trinh J, Vargas S, Vumbaco D, Walker M, Wang M, Wanner A, Waters J, Williams G, Wilson J, Xiong W, Lein E, Berg J, Kalmbach B, Yao S, Gong H, Luo Q, Ng L, Sümbül U, Jarsky T, et alSorensen SA, Gouwens NW, Wang Y, Mallory M, Budzillo A, Dalley R, Lee B, Gliko O, Kuo HC, Kuang X, Mann R, Ahmadinia L, Alfiler L, Baftizadeh F, Baker K, Bannick S, Bertagnolli D, Bickley K, Bohn P, Brown D, Bomben J, Brouner K, Chen C, Chen K, Chvilicek M, Collman F, Daigle T, Dawes T, de Frates R, Dee N, DePartee M, Egdorf T, El-Hifnawi L, Enstrom R, Esposito L, Farrell C, Gala R, Glomb A, Gamlin C, Gary A, Goldy J, Gu H, Hadley K, Hawrylycz M, Henry A, Hill D, Hirokawa KE, Huang Z, Johnson K, Juneau Z, Kebede S, Kim L, Lee C, Lesnar P, Li A, Glomb A, Li Y, Liang E, Link K, Maxwell M, McGraw M, McMillen DA, Mukora A, Ng L, Ochoa T, Oldre A, Park D, Pom CA, Popovich Z, Potekhina L, Rajanbabu R, Ransford S, Reding M, Ruiz A, Sandman D, Siverts L, Smith KA, Stoecklin M, Sulc J, Tieu M, Ting J, Trinh J, Vargas S, Vumbaco D, Walker M, Wang M, Wanner A, Waters J, Williams G, Wilson J, Xiong W, Lein E, Berg J, Kalmbach B, Yao S, Gong H, Luo Q, Ng L, Sümbül U, Jarsky T, Yao Z, Tasic B, Zeng H. Connecting single-cell transcriptomes to projectomes in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.25.568393. [PMID: 38168270 PMCID: PMC10760188 DOI: 10.1101/2023.11.25.568393] [Show More Authors] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.
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Affiliation(s)
| | | | - Yun Wang
- Allen Institute for Brain Science
| | | | | | | | | | | | | | - Xiuli Kuang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | | | - Chao Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Kai Chen
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | - Nick Dee
- Allen Institute for Brain Science
| | | | | | | | | | | | | | | | | | | | | | | | - Hong Gu
- Allen Institute for Brain Science
| | | | | | | | | | | | - Zili Huang
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | - Lisa Kim
- Allen Institute for Brain Science
| | | | | | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | | | - Yaoyao Li
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | | | | | | | | | | | | | | | | | | | | | | | - Zoran Popovich
- University of Washington, Dept. of Computer Science and Engineering
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Wei Xiong
- School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
| | - Ed Lein
- Allen Institute for Brain Science
| | - Jim Berg
- Allen Institute for Brain Science
| | | | | | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
| | - Qingming Luo
- State Key Laboratory of Digital Medical Engineering, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Lydia Ng
- Allen Institute for Brain Science
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22
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Golan N, Ehrlich D, Bonanno J, O'Brien RF, Murillo M, Kauer SD, Ravindra N, Van Dijk D, Cafferty WB. Anatomical Diversity of the Adult Corticospinal Tract Revealed by Single-Cell Transcriptional Profiling. J Neurosci 2023; 43:7929-7945. [PMID: 37748862 PMCID: PMC10669816 DOI: 10.1523/jneurosci.0811-22.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/28/2023] [Accepted: 08/01/2023] [Indexed: 09/27/2023] Open
Abstract
The corticospinal tract (CST) forms a central part of the voluntary motor apparatus in all mammals. Thus, injury, disease, and subsequent degeneration within this pathway result in chronic irreversible functional deficits. Current strategies to repair the damaged CST are suboptimal in part because of underexplored molecular heterogeneity within the adult tract. Here, we combine spinal retrograde CST tracing with single-cell RNA sequencing (scRNAseq) in adult male and female mice to index corticospinal neuron (CSN) subtypes that differentially innervate the forelimb and hindlimb. We exploit publicly available datasets to confer anatomic specialization among CSNs and show that CSNs segregate not only along the forelimb and hindlimb axis but also by supraspinal axon collateralization. These anatomically defined transcriptional data allow us to use machine learning tools to build classifiers that discriminate between CSNs and cortical layer 2/3 and nonspinally terminating layer 5 neurons in M1 and separately identify limb-specific CSNs. Using these tools, CSN subtypes can be differentially identified to study postnatal patterning of the CST in vivo, leveraged to screen for novel limb-specific axon growth survival and growth activators in vitro, and ultimately exploited to repair the damaged CST after injury and disease.SIGNIFICANCE STATEMENT Therapeutic interventions designed to repair the damaged CST after spinal cord injury have remained functionally suboptimal in part because of an incomplete understanding of the molecular heterogeneity among subclasses of CSNs. Here, we combine spinal retrograde labeling with scRNAseq and annotate a CSN index by the termination pattern of their primary axon in the cervical or lumbar spinal cord and supraspinal collateral terminal fields. Using machine learning we have confirmed the veracity of our CSN gene lists to train classifiers to identify CSNs among all classes of neurons in primary motor cortex to study the development, patterning, homeostasis, and response to injury and disease, and ultimately target streamlined repair strategies to this critical motor pathway.
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Affiliation(s)
- Noa Golan
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Daniel Ehrlich
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Psychiatry, Yale University School, New Haven, Connecticut 06511
| | - James Bonanno
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Rory F O'Brien
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Matias Murillo
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Sierra D Kauer
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Neal Ravindra
- Department of Internal Medicine, Yale University School, New Haven, Connecticut 06511
- Department of Computer Science, Yale University School, New Haven, Connecticut 06511
| | - David Van Dijk
- Department of Internal Medicine, Yale University School, New Haven, Connecticut 06511
- Department of Computer Science, Yale University School, New Haven, Connecticut 06511
| | - William B Cafferty
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
- Department of Neuroscience, Yale University School, New Haven, Connecticut 06511
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23
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Wu SJ, Sevier E, Dwivedi D, Saldi GA, Hairston A, Yu S, Abbott L, Choi DH, Sherer M, Qiu Y, Shinde A, Lenahan M, Rizzo D, Xu Q, Barrera I, Kumar V, Marrero G, Prönneke A, Huang S, Kullander K, Stafford DA, Macosko E, Chen F, Rudy B, Fishell G. Cortical somatostatin interneuron subtypes form cell-type-specific circuits. Neuron 2023; 111:2675-2692.e9. [PMID: 37390821 PMCID: PMC11645782 DOI: 10.1016/j.neuron.2023.05.032] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 03/16/2023] [Accepted: 05/31/2023] [Indexed: 07/02/2023]
Abstract
The cardinal classes are a useful simplification of cortical interneuron diversity, but such broad subgroupings gloss over the molecular, morphological, and circuit specificity of interneuron subtypes, most notably among the somatostatin interneuron class. Although there is evidence that this diversity is functionally relevant, the circuit implications of this diversity are unknown. To address this knowledge gap, we designed a series of genetic strategies to target the breadth of somatostatin interneuron subtypes and found that each subtype possesses a unique laminar organization and stereotyped axonal projection pattern. Using these strategies, we examined the afferent and efferent connectivity of three subtypes (two Martinotti and one non-Martinotti) and demonstrated that they possess selective connectivity with intratelecephalic or pyramidal tract neurons. Even when two subtypes targeted the same pyramidal cell type, their synaptic targeting proved selective for particular dendritic compartments. We thus provide evidence that subtypes of somatostatin interneurons form cell-type-specific cortical circuits.
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Affiliation(s)
- Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Elaine Sevier
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Deepanjali Dwivedi
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giuseppe-Antonio Saldi
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ariel Hairston
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sabrina Yu
- Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Lydia Abbott
- Department of Biology, College of Science, Northeastern University, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Da Hae Choi
- Department of Behavioral Neuroscience, College of Science, Northeastern University, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mia Sherer
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yanjie Qiu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ashwini Shinde
- Department of Behavioral Neuroscience, College of Science, Northeastern University, Boston, MA 02115, USA; Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA
| | - Mackenzie Lenahan
- Department of Biology, College of Science, Northeastern University, Boston, MA, USA; Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA
| | - Daniella Rizzo
- Department of Biology, Brandeis University, Waltham, MA, USA; Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA
| | - Qing Xu
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Irving Barrera
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vipin Kumar
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giovanni Marrero
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alvar Prönneke
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
| | - Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Klas Kullander
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - David A Stafford
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Evan Macosko
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Fei Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Bernardo Rudy
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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24
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Bender PTR, McCollum M, Boyd-Pratt H, Mendelson BZ, Anderson CT. Synaptic zinc potentiates AMPA receptor function in mouse auditory cortex. Cell Rep 2023; 42:112932. [PMID: 37585291 PMCID: PMC10514716 DOI: 10.1016/j.celrep.2023.112932] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/23/2023] [Accepted: 07/18/2023] [Indexed: 08/18/2023] Open
Abstract
Synaptic zinc signaling modulates synaptic activity and is present in specific populations of cortical neurons, suggesting that synaptic zinc contributes to the diversity of intracortical synaptic microcircuits and their functional specificity. To understand the role of zinc signaling in the cortex, we performed whole-cell patch-clamp recordings from intratelencephalic (IT)-type neurons and pyramidal tract (PT)-type neurons in layer 5 of the mouse auditory cortex during optogenetic stimulation of specific classes of presynaptic neurons. Our results show that synaptic zinc potentiates AMPA receptor (AMPAR) function in a synapse-specific manner. We performed in vivo 2-photon calcium imaging of the same classes of neurons in awake mice and found that changes in synaptic zinc can widen or sharpen the sound-frequency tuning bandwidth of IT-type neurons but only widen the tuning bandwidth of PT-type neurons. These results provide evidence for synapse- and cell-type-specific actions of synaptic zinc in the cortex.
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Affiliation(s)
- Philip T R Bender
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV 26506, USA
| | - Mason McCollum
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV 26506, USA
| | - Helen Boyd-Pratt
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV 26506, USA
| | - Benjamin Z Mendelson
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV 26506, USA
| | - Charles T Anderson
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University School of Medicine, Morgantown, WV 26506, USA.
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25
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Chen BN, Humenick A, Yew WP, Peterson RA, Wiklendt L, Dinning PG, Spencer NJ, Wattchow DA, Costa M, Brookes SJH. Types of Neurons in the Human Colonic Myenteric Plexus Identified by Multilayer Immunohistochemical Coding. Cell Mol Gastroenterol Hepatol 2023; 16:573-605. [PMID: 37355216 PMCID: PMC10469081 DOI: 10.1016/j.jcmgh.2023.06.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 06/14/2023] [Accepted: 06/15/2023] [Indexed: 06/26/2023]
Abstract
BACKGROUND AND AIMS Gut functions including motility, secretion, and blood flow are largely controlled by the enteric nervous system. Characterizing the different classes of enteric neurons in the human gut is an important step to understand how its circuitry is organized and how it is affected by disease. METHODS Using multiplexed immunohistochemistry, 12 discriminating antisera were applied to distinguish different classes of myenteric neurons in the human colon (2596 neurons, 12 patients) according to their chemical coding. All antisera were applied to every neuron, in multiple layers, separated by elutions. RESULTS A total of 164 combinations of immunohistochemical markers were present among the 2596 neurons, which could be divided into 20 classes, with statistical validation. Putative functions were ascribed for 4 classes of putative excitatory motor neurons (EMN1-4), 4 inhibitory motor neurons (IMN1-4), 3 ascending interneurons (AIN1-3), 6 descending interneurons (DIN1-6), 2 classes of multiaxonal sensory neurons (SN1-2), and a small, miscellaneous group (1.8% of total). Soma-dendritic morphology was analyzed, revealing 5 common shapes distributed differentially between the 20 classes. Distinctive baskets of axonal varicosities surrounded 45% of myenteric nerve cell bodies and were associated with close appositions, suggesting possible connectivity. Baskets of cholinergic terminals and several other types of baskets selectively targeted ascending interneurons and excitatory motor neurons but were significantly sparser around inhibitory motor neurons. CONCLUSIONS Using a simple immunohistochemical method, human myenteric neurons were shown to comprise multiple classes based on chemical coding and morphology and dense clusters of axonal varicosities were selectively associated with some classes.
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Affiliation(s)
- Bao Nan Chen
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Adam Humenick
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Wai Ping Yew
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Rochelle A Peterson
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Lukasz Wiklendt
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Phil G Dinning
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia; Colorectal Surgical Unit, Division of Surgery, Flinders Medical Centre, Bedford Park, South Australia, Australia
| | - Nick J Spencer
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - David A Wattchow
- Colorectal Surgical Unit, Division of Surgery, Flinders Medical Centre, Bedford Park, South Australia, Australia
| | - Marcello Costa
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Simon J H Brookes
- Human Physiology, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.
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26
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Hostetler RE, Hu H, Agmon A. Genetically Defined Subtypes of Somatostatin-Containing Cortical Interneurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526850. [PMID: 36778499 PMCID: PMC9915678 DOI: 10.1101/2023.02.02.526850] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Inhibitory interneurons play a crucial role in proper development and function of the mammalian cerebral cortex. Of the different inhibitory subclasses, dendritic-targeting, somatostatin-containing (SOM) interneurons may be the most diverse. Earlier studies used transgenic mouse lines to identify and characterize subtypes of SOM interneurons by morphological, electrophysiological and neurochemical properties. More recently, large-scale studies classified SOM interneurons into 13 morpho-electro-transcriptomic (MET) types. It remains unclear, however, how these various classification schemes relate to each other, and experimental access to MET types has been limited by the scarcity of type-specific mouse driver lines. To begin to address these issues we crossed Flp and Cre driver mouse lines and a dual-color combinatorial reporter, allowing experimental access to genetically defined SOM subsets. Brains from adult mice of both sexes were retrogradely dye-labeled from the pial surface to identify layer 1-projecting neurons, and immunostained against several marker proteins, allowing correlation of genetic label, axonal target and marker protein expression in the same neurons. Using whole-cell recordings ex-vivo, we compared electrophysiological properties between intersectional and transgenic SOM subsets. We identified two layer 1-targeting intersectional subsets with non-overlapping marker protein expression and electrophysiological properties which, together with a previously characterized layer 4-targeting subtype, account for about half of all layer 5 SOM cells and >40% of all SOM cells, and appear to map onto 5 of the 13 MET types. Genetic access to these subtypes will allow researchers to determine their synaptic inputs and outputs and uncover their roles in cortical computations and animal behavior. SIGNIFICANCE STATEMENT Inhibitory neurons are critically important for proper development and function of the cerebral cortex. Although a minority population, they are highly diverse, which poses a major challenge to investigating their contributions to cortical computations and animal and human behavior. As a step towards understanding this diversity we crossed genetically modified mouse lines to allow detailed examination of genetically-defined groups of the most diverse inhibitory subtype, somatostatin-containing interneurons. We identified and characterized three somatostatin subtypes in the deep cortical layers with distinct combinations of anatomical, neurochemical and electrophysiological properties. Future studies could now use these genetic tools to examine how these different subtypes are integrated into the cortical circuit and what roles they play during sensory, cognitive or motor behavior.
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Affiliation(s)
- Rachel E Hostetler
- Dept. of Neuroscience, West Virginia University School of Medicine, WV Rockefeller Neuroscience Institute, Morgantown, WV 26506, USA
| | - Hang Hu
- Dept. of Neuroscience, West Virginia University School of Medicine, WV Rockefeller Neuroscience Institute, Morgantown, WV 26506, USA
| | - Ariel Agmon
- Dept. of Neuroscience, West Virginia University School of Medicine, WV Rockefeller Neuroscience Institute, Morgantown, WV 26506, USA
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Lee H, Ciabatti E, González-Rueda A, Williams E, Nugent F, Mookerjee S, Morgese F, Tripodi M. Combining long-term circuit mapping and network transcriptomics with SiR-N2c. Nat Methods 2023; 20:580-589. [PMID: 36864202 PMCID: PMC7614628 DOI: 10.1038/s41592-023-01787-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 01/23/2023] [Indexed: 03/04/2023]
Abstract
An exciting frontier in circuit neuroscience lies at the intersection between neural network mapping and single-cell genomics. Monosynaptic rabies viruses provide a promising platform for the merger of circuit mapping methods with -omics approaches. However, three key limitations have hindered the extraction of physiologically meaningful gene expression profiles from rabies-mapped circuits: inherent viral cytotoxicity, high viral immunogenicity and virus-induced alteration of cellular transcriptional regulation. These factors alter the transcriptional and translational profiles of infected neurons and their neighboring cells. To overcome these limitations we applied a self-inactivating genomic modification to the less immunogenic rabies strain, CVS-N2c, to generate a self-inactivating CVS-N2c rabies virus (SiR-N2c). SiR-N2c not only eliminates undesired cytotoxic effects but also substantially reduces gene expression alterations in infected neurons and dampens the recruitment of innate and acquired immune responses, thus enabling open-ended interventions on neural networks and their genetic characterization using single-cell genomic approaches.
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Affiliation(s)
- Hassal Lee
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Ernesto Ciabatti
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
| | | | - Elena Williams
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Fiona Nugent
- IMAXT Laboratory, Cancer Research UK Cambridge Institute, Cambridge, UK
| | | | - Fabio Morgese
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK
| | - Marco Tripodi
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
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28
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Yao S, Wang Q, Hirokawa KE, Ouellette B, Ahmed R, Bomben J, Brouner K, Casal L, Caldejon S, Cho A, Dotson NI, Daigle TL, Egdorf T, Enstrom R, Gary A, Gelfand E, Gorham M, Griffin F, Gu H, Hancock N, Howard R, Kuan L, Lambert S, Lee EK, Luviano J, Mace K, Maxwell M, Mortrud MT, Naeemi M, Nayan C, Ngo NK, Nguyen T, North K, Ransford S, Ruiz A, Seid S, Swapp J, Taormina MJ, Wakeman W, Zhou T, Nicovich PR, Williford A, Potekhina L, McGraw M, Ng L, Groblewski PA, Tasic B, Mihalas S, Harris JA, Cetin A, Zeng H. A whole-brain monosynaptic input connectome to neuron classes in mouse visual cortex. Nat Neurosci 2023; 26:350-364. [PMID: 36550293 PMCID: PMC10039800 DOI: 10.1038/s41593-022-01219-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 10/27/2022] [Indexed: 12/24/2022]
Abstract
Identification of structural connections between neurons is a prerequisite to understanding brain function. Here we developed a pipeline to systematically map brain-wide monosynaptic input connections to genetically defined neuronal populations using an optimized rabies tracing system. We used mouse visual cortex as the exemplar system and revealed quantitative target-specific, layer-specific and cell-class-specific differences in its presynaptic connectomes. The retrograde connectivity indicates the presence of ventral and dorsal visual streams and further reveals topographically organized and continuously varying subnetworks mediated by different higher visual areas. The visual cortex hierarchy can be derived from intracortical feedforward and feedback pathways mediated by upper-layer and lower-layer input neurons. We also identify a new role for layer 6 neurons in mediating reciprocal interhemispheric connections. This study expands our knowledge of the visual system connectomes and demonstrates that the pipeline can be scaled up to dissect connectivity of different cell populations across the mouse brain.
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Affiliation(s)
- Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA, USA.
| | - Quanxin Wang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Karla E Hirokawa
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | | | | | | | | | - Linzy Casal
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Andy Cho
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Tom Egdorf
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Amanda Gary
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Hong Gu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Leonard Kuan
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Kyla Mace
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | - Kat North
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | | | | | - Sam Seid
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jackie Swapp
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Thomas Zhou
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Philip R Nicovich
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | | | | | - Medea McGraw
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Ali Cetin
- Allen Institute for Brain Science, Seattle, WA, USA
- CNC Program, Stanford University, Palo Alto, CA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA.
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29
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Grieco SF, Holmes TC, Xu X. Meeting report for the 2022 UC Irvine Center for neural circuit mapping conference: linking brain function to cell types and circuits. Mol Psychiatry 2023; 28:2-3. [PMID: 36198768 DOI: 10.1038/s41380-022-01810-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Steven F Grieco
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, USA
| | - Todd C Holmes
- Department of Physiology and Biophysics, School of Medicine, University of California, Irvine, CA, USA
- Center for Neural Circuit Mapping (CNCM), University of California, Irvine, CA, 92697, USA
| | - Xiangmin Xu
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, USA.
- Center for Neural Circuit Mapping (CNCM), University of California, Irvine, CA, 92697, USA.
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30
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Lanjewar AL, Jagetia S, Khan ZM, Eagleson KL, Levitt P. Subclass-specific expression patterns of MET receptor tyrosine kinase during development in medial prefrontal and visual cortices. J Comp Neurol 2023; 531:132-148. [PMID: 36201439 PMCID: PMC9691614 DOI: 10.1002/cne.25418] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/17/2022] [Accepted: 09/05/2022] [Indexed: 01/12/2023]
Abstract
Met encodes a receptor tyrosine kinase (MET) that is expressed during development and regulates cortical synapse maturation. Conditional deletion of Met in the nervous system during embryonic development leads to deficits in adult contextual fear learning, a medial prefrontal cortex (mPFC)-dependent cognitive task. MET also regulates the timing of critical period plasticity for ocular dominance in primary visual cortex (V1). However, the underlying circuitry responsible remains unknown. Therefore, this study determines the broad expression patterns of MET throughout postnatal development in mPFC and V1 projection neurons (PNs), providing insight into similarities and differences in the neuronal subtypes and temporal patterns of MET expression between cortical areas. Using a transgenic mouse line that expresses green fluorescent protein (GFP) in Met+ neurons, immunofluorescence and confocal microscopy were performed to visualize MET-GFP+ cell bodies and PN subclass-specific protein markers. Analyses reveal that the MET expression is highly enriched in infragranular layers of mPFC, but in supragranular layers of V1. Interestingly, temporal regulation of the percentage of MET+ neurons across development not only differs between cortical regions but also is distinct between lamina within a cortical region. Further, MET is expressed predominantly in the subcerebral PN subclass in mPFC, but the intratelencephalic PN subclass in V1. The data suggest that MET signaling influences the development of distinct circuits in mPFC and V1 that underlie subcerebral and intracortical functional deficits following Met deletion, respectively.
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Affiliation(s)
- Alexandra L. Lanjewar
- Program in Developmental Neuroscience and Neurogenetics, Children's Hospital Los AngelesThe Saban Research InstituteLos AngelesCaliforniaUSA,Department of PediatricsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA,Neuroscience Graduate ProgramUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sonum Jagetia
- Program in Developmental Neuroscience and Neurogenetics, Children's Hospital Los AngelesThe Saban Research InstituteLos AngelesCaliforniaUSA,Department of PediatricsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Zuhayr M. Khan
- Program in Developmental Neuroscience and Neurogenetics, Children's Hospital Los AngelesThe Saban Research InstituteLos AngelesCaliforniaUSA,Department of PediatricsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Kathie L. Eagleson
- Program in Developmental Neuroscience and Neurogenetics, Children's Hospital Los AngelesThe Saban Research InstituteLos AngelesCaliforniaUSA,Department of PediatricsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Pat Levitt
- Program in Developmental Neuroscience and Neurogenetics, Children's Hospital Los AngelesThe Saban Research InstituteLos AngelesCaliforniaUSA,Department of PediatricsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
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31
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Wang H, Dey O, Lagos WN, Callaway EM. Diversity in spatial frequency, temporal frequency, and speed tuning across mouse visual cortical areas and layers. J Comp Neurol 2022; 530:3226-3247. [PMID: 36070574 PMCID: PMC9588602 DOI: 10.1002/cne.25404] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 08/15/2022] [Accepted: 08/18/2022] [Indexed: 11/06/2022]
Abstract
The mouse visual system consists of several visual cortical areas thought to be specialized for different visual features and/or tasks. Previous studies have revealed differences between primary visual cortex (V1) and other higher visual areas, namely, anterolateral (AL) and posteromedial (PM), and their tuning preferences for spatial and temporal frequency. However, these differences have primarily been characterized using methods that are biased toward superficial layers of cortex, such as two-photon calcium imaging. Fewer studies have investigated cell types in deeper layers of these areas and their tuning preferences. Because superficial versus deep-layer neurons and different types of deep-layer neurons are known to have different feedforward and feedback inputs and outputs, comparing the tuning preferences of these groups is important for understanding cortical visual information processing. In this study, we used extracellular electrophysiology and two-photon calcium imaging targeted toward two different layer 5 cell classes to characterize their tuning properties in V1, AL, and PM. We find that deep-layer neurons, similar to superficial layer neurons, are also specialized for different spatial and temporal frequencies, with the strongest differences between AL and V1, and AL and PM, but not V1 and PM. However, we note that the deep-layer neuron populations preferred a larger range of SFs and TFs compared to previous studies. We also find that extratelencephalically projecting layer 5 neurons are more direction selective than intratelencephalically projecting layer 5 neurons.
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Affiliation(s)
- Helen Wang
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Oyshi Dey
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Willian N. Lagos
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Edward M. Callaway
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
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32
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Vasile F, Petreanu L. The perfect timing for multimodal integration is not the same in all L5 neurons. Neuron 2022; 110:3648-3650. [PMID: 36395750 DOI: 10.1016/j.neuron.2022.09.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this issue of Neuron, Rindner et al. (2022) demonstrate that subclasses of layer 5 pyramidal neurons in the parietal cortex integrate inputs from frontal and sensory areas supralinearly and with distinct temporal dynamics.
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Affiliation(s)
- Flora Vasile
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Leopoldo Petreanu
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
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33
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Wei JR, Hao ZZ, Xu C, Huang M, Tang L, Xu N, Liu R, Shen Y, Teichmann SA, Miao Z, Liu S. Identification of visual cortex cell types and species differences using single-cell RNA sequencing. Nat Commun 2022; 13:6902. [PMID: 36371428 PMCID: PMC9653448 DOI: 10.1038/s41467-022-34590-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 10/31/2022] [Indexed: 11/13/2022] Open
Abstract
The primate neocortex exerts high cognitive ability and strong information processing capacity. Here, we establish a single-cell RNA sequencing dataset of 133,454 macaque visual cortical cells. It covers major cortical cell classes including 25 excitatory neuron types, 37 inhibitory neuron types and all glial cell types. We identified layer-specific markers including HPCAL1 and NXPH4, and also identified two cell types, an NPY-expressing excitatory neuron type that expresses the dopamine receptor D3 gene; and a primate specific activity-dependent OSTN + sensory neuron type. Comparisons of our dataset with humans and mice show that the gene expression profiles differ between species in relation to genes that are implicated in the synaptic plasticity and neuromodulation of excitatory neurons. The comparisons also revealed that glutamatergic neurons may be more diverse across species than GABAergic neurons and non-neuronal cells. These findings pave the way for understanding how the primary cortex fulfills the high-cognitive functions.
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Affiliation(s)
- Jia-Ru Wei
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Chuan Xu
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Mengyao Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Lei Tang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Nana Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Ruifeng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Yuhui Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Sarah A Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK.
- Department of Physics, Cavendish Laboratory, University of Cambridge, Cambridge, UK.
| | - Zhichao Miao
- GMU-GIBH Joint School of Life Sciences, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou, China.
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, UK.
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, China.
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34
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Zhang Y, Amaral ML, Zhu C, Grieco SF, Hou X, Lin L, Buchanan J, Tong L, Preissl S, Xu X, Ren B. Single-cell epigenome analysis reveals age-associated decay of heterochromatin domains in excitatory neurons in the mouse brain. Cell Res 2022; 32:1008-1021. [PMID: 36207411 PMCID: PMC9652396 DOI: 10.1038/s41422-022-00719-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/21/2022] [Indexed: 01/31/2023] Open
Abstract
Loss of heterochromatin has been implicated as a cause of pre-mature aging and age-associated decline in organ functions in mammals; however, the specific cell types and gene loci affected by this type of epigenetic change have remained unclear. To address this knowledge gap, we probed chromatin accessibility at single-cell resolution in the brains, hearts, skeletal muscles, and bone marrows from young, middle-aged, and old mice, and assessed age-associated changes at 353,126 candidate cis-regulatory elements (cCREs) across 32 major cell types. Unexpectedly, we detected increased chromatin accessibility within specific heterochromatin domains in old mouse excitatory neurons. The gain of chromatin accessibility at these genomic loci was accompanied by the cell-type-specific loss of heterochromatin and activation of LINE1 elements. Immunostaining further confirmed the loss of the heterochromatin mark H3K9me3 in the excitatory neurons but not in inhibitory neurons or glial cells. Our results reveal the cell-type-specific changes in chromatin landscapes in old mice and shed light on the scope of heterochromatin loss in mammalian aging.
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Affiliation(s)
- Yanxiao Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
- School of Life Sciences, Westlake University, Hangzhou, China.
| | - Maria Luisa Amaral
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Chenxu Zhu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Steven Francis Grieco
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, USA
| | - Xiaomeng Hou
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Lin Lin
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Justin Buchanan
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Liqi Tong
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Xiangmin Xu
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, USA.
- The Center for Neural Circuit Mapping, University of California, Irvine, CA, USA.
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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35
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Hanson MA, Wester JC. Advances in approaches to study cell-type specific cortical circuits throughout development. Front Cell Neurosci 2022; 16:1031389. [PMID: 36324861 PMCID: PMC9618604 DOI: 10.3389/fncel.2022.1031389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 09/29/2022] [Indexed: 11/17/2022] Open
Abstract
Neurons in the neocortex and hippocampus are diverse and form synaptic connections that depend on their type. Recent work has improved our understanding of neuronal cell-types and how to target them for experiments. This is crucial for investigating cortical circuit architecture, as the current catalog of established cell-type specific circuit motifs is small relative to the diversity of neuronal subtypes. Some of these motifs are found throughout the cortex, suggesting they are canonical circuits necessary for basic computations. However, the extent to which circuit organization is stereotyped across the brain or varies by cortical region remains unclear. Cortical circuits are also plastic, and their organization evolves throughout each developmental stage. Thus, experimental access to neuronal subtypes with temporal control is essential for studying cortical structure and function. In this mini review, we highlight several recent advances to target specific neuronal subtypes and study their synaptic connectivity and physiology throughout development. We emphasize approaches that combine multiple techniques, provide examples of successful applications, and describe potential future applications of novel tools.
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Affiliation(s)
- Meretta A. Hanson
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, OH, United States
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36
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Globig AM, Mayer LS, Heeg M, Andrieux G, Ku M, Otto-Mora P, Hipp AV, Zoldan K, Pattekar A, Rana N, Schell C, Boerries M, Hofmann M, Neumann-Haefelin C, Kuellmer A, Schmidt A, Boettler T, Tomov V, Thimme R, Hasselblatt P, Bengsch B. Exhaustion of CD39-Expressing CD8 + T Cells in Crohn's Disease Is Linked to Clinical Outcome. Gastroenterology 2022; 163:965-981.e31. [PMID: 35738329 DOI: 10.1053/j.gastro.2022.06.045] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 06/07/2022] [Accepted: 06/14/2022] [Indexed: 12/02/2022]
Abstract
BACKGROUND & AIMS Exhaustion of CD8 T cells has been suggested to inform different clinical outcomes in Crohn's disease, but detailed analyses are lacking. This study aimed to identify the role of exhaustion on a single-cell level and identify relevant CD8 T cell populations in Crohn's disease. METHODS Blood and intestinal tissue from 58 patients with Crohn's disease (active disease or remission) were assessed for CD8 T cell expression of exhaustion markers and their cytokine profile by highly multiplexed flow and mass cytometry. Key disease-associated subsets were sorted and analyzed by RNA sequencing. CD39 inhibition assays were performed in vitro. RESULTS Activated CD39+ and CD39+PD-1+ CD8 T cell subsets expressing multiple exhaustion markers were enriched at low frequency in active Crohn's disease. Their cytokine production capacity was inversely linked to the Harvey-Bradshaw Index. Subset-level protein and transcriptome profiling revealed co-existence of effector and exhaustion programs in CD39+ and CD39+ PD-1+CD8 T cells, with CD39+ cells likely originating from the intestine. CD39 enzymatic activity controlled T cell cytokine production. Importantly, transcriptional exhaustion signatures were enriched in remission in CD39-expressing subsets with up-regulation of TOX. Subset-level transcriptomics revealed a CD39-related gene module that is associated with the clinical course. CONCLUSIONS These data showed a role for the exhaustion of peripheral CD39-expressing CD8 T cell subsets in Crohn's disease. Their low frequency illustrated the utility of single-cell cytometry methods for identification of relevant immune populations. Importantly, the link of their exhaustion status to the clinical activity and their specific gene signatures have implications for exhaustion-based personalized medicine approaches.
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Affiliation(s)
- Anna-Maria Globig
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Lena Sophie Mayer
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Maximilian Heeg
- Institute for Immunodeficiency, Center for Chronic Immunodeficiency, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Geoffroy Andrieux
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium Partner Site Freiburg, German Cancer Research Center, Heidelberg, Germany
| | - Manching Ku
- Department of Pediatrics and Adolescent Medicine, Division of Pediatric Hematology and Oncology, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Patricia Otto-Mora
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Anna Veronika Hipp
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Katharina Zoldan
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Ajinkya Pattekar
- Department of Medicine, Division of Gastroenterology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Nisha Rana
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Christoph Schell
- Institute for Surgical Pathology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Melanie Boerries
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium Partner Site Freiburg, German Cancer Research Center, Heidelberg, Germany
| | - Maike Hofmann
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Christoph Neumann-Haefelin
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Armin Kuellmer
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Arthur Schmidt
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Tobias Boettler
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Vesselin Tomov
- Department of Medicine, Division of Gastroenterology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Robert Thimme
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Peter Hasselblatt
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Bertram Bengsch
- Clinic for Internal Medicine II, Gastroenterology, Hepatology, Endocrinology, and Infectious Diseases, University Medical Center Freiburg, Faculty of Medicine, Freiburg, Germany; German Cancer Consortium Partner Site Freiburg, German Cancer Research Center, Heidelberg, Germany; Centre for Biological Signalling Studies (BIOSS) and Centre for Integrative Biological Signalling Studies (CIBSS), University of Freiburg, Freiburg, Germany.
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37
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Huang W, Xu Q, Su J, Tang L, Hao ZZ, Xu C, Liu R, Shen Y, Sang X, Xu N, Tie X, Miao Z, Liu X, Xu Y, Liu F, Liu Y, Liu S. Linking transcriptomes with morphological and functional phenotypes in mammalian retinal ganglion cells. Cell Rep 2022; 40:111322. [PMID: 36103830 DOI: 10.1016/j.celrep.2022.111322] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/19/2022] [Accepted: 08/17/2022] [Indexed: 11/03/2022] Open
Abstract
Retinal ganglion cells (RGCs) are the brain's gateway to the visual world. They can be classified into different types on the basis of their electrophysiological, transcriptomic, or morphological characteristics. Here, we characterize the transcriptomic, morphological, and functional features of 472 high-quality RGCs using Patch sequencing (Patch-seq), providing functional and morphological annotation of many transcriptomic-defined cell types of a previously established RGC atlas. We show a convergence of different modalities in defining the RGC identity and reveal the degree of correspondence for well-characterized cell types across multimodal data. Moreover, we complement some RGC types with detailed morphological and functional properties. We also identify differentially expressed genes among ON, OFF, and ON-OFF RGCs such as Vat1l, Slitrk6, and Lmo7, providing candidate marker genes for functional studies. Our research suggests that the molecularly distinct clusters may also differ in their roles of encoding visual information.
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Affiliation(s)
- Wanjing Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Qiang Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Jing Su
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Lei Tang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Chuan Xu
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Ruifeng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Yuhui Shen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Xuan Sang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Nana Xu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Xiaoxiu Tie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Zhichao Miao
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge CB10 1SD, UK
| | - Xialin Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China
| | - Ying Xu
- Guangdong-Hongkong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou, 510632, China; Key Laboratory of CNS Regeneration (Jinan University), Ministry of Education, Guangzhou, 510632, China
| | - Feng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China.
| | - Yizhi Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China; Research Unit of Ocular Development and Regeneration, Chinese Academy of Medical Sciences, Beijing 100085, China.
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou 510060, China; Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou 510080, China.
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38
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Weiler S, Guggiana Nilo D, Bonhoeffer T, Hübener M, Rose T, Scheuss V. Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex. Cereb Cortex 2022; 33:3715-3733. [PMID: 36017976 PMCID: PMC10068292 DOI: 10.1093/cercor/bhac303] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 07/12/2022] [Accepted: 07/12/2022] [Indexed: 11/13/2022] Open
Abstract
Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. These PyrCs show pial depth-dependent functional and structural specializations, indicating participation in different functional microcircuits. However, whether these depth-dependent differences result from separable PyrC subtypes or whether their features display a continuum correlated with pial depth is unknown. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory connectivity across the depth of L2/3 in the binocular visual cortex of mice. We find that the apical, but not the basal dendritic tree structure, varies with pial depth, which is accompanied by variation in subthreshold electrophysiological properties. Lower L2/3 PyrCs receive increased input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. In vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper PyrCs are more driven by contralateral than ipsilateral eye stimulation. Importantly, the property value transitions are gradual, and L2/3 PyrCs do not display discrete subtypes based on these parameters. Therefore, L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth, forming a continuum rather than discrete subtypes.
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Affiliation(s)
- Simon Weiler
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Großhaderner Str. 2, Planegg 82152, Germany.,Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, 25 Howland Street, London W1T 4JG, United Kingdom
| | - Drago Guggiana Nilo
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Max Planck Institute for Biological Intelligence, in foundation, Martinsried, Germany
| | - Tobias Bonhoeffer
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Max Planck Institute for Biological Intelligence, in foundation, Martinsried, Germany
| | - Mark Hübener
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Max Planck Institute for Biological Intelligence, in foundation, Martinsried, Germany
| | - Tobias Rose
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Institute for Experimental Epileptology and Cognition Research, University of Bonn, Venusberg-Campus 1, Bonn 53127, Germany
| | - Volker Scheuss
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Department of Psychiatry, Ludwig-Maximilians-Universität München, Nussbaumstr. 7, München 80336, Germany
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39
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Zeng H. What is a cell type and how to define it? Cell 2022; 185:2739-2755. [PMID: 35868277 DOI: 10.1016/j.cell.2022.06.031] [Citation(s) in RCA: 202] [Impact Index Per Article: 67.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 06/14/2022] [Accepted: 06/14/2022] [Indexed: 12/20/2022]
Abstract
Cell types are the basic functional units of an organism. Cell types exhibit diverse phenotypic properties at multiple levels, making them challenging to define, categorize, and understand. This review provides an overview of the basic principles of cell types rooted in evolution and development and discusses approaches to characterize and classify cell types and investigate how they contribute to the organism's function, using the mammalian brain as a primary example. I propose a roadmap toward a conceptual framework and knowledge base of cell types that will enable a deeper understanding of the dynamic changes of cellular function under healthy and diseased conditions.
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Affiliation(s)
- Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA.
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40
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Xu J, Jo A, DeVries RP, Deniz S, Cherian S, Sunmola I, Song X, Marshall JJ, Gruner KA, Daigle TL, Contractor A, Lerner TN, Zeng H, Zhu Y. Intersectional mapping of multi-transmitter neurons and other cell types in the brain. Cell Rep 2022; 40:111036. [PMID: 35793636 PMCID: PMC9290751 DOI: 10.1016/j.celrep.2022.111036] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 04/04/2022] [Accepted: 06/13/2022] [Indexed: 01/04/2023] Open
Abstract
Recent developments in intersectional strategies have greatly advanced our ability to precisely target brain cell types based on unique co-expression patterns. To accelerate the application of intersectional genetics, we perform a brain-wide characterization of 13 Flp and tTA mouse driver lines and selected seven for further analysis based on expression of vesicular neurotransmitter transporters. Using selective Cre driver lines, we created more than 10 Cre/tTA combinational lines for cell type targeting and circuit analysis. We then used VGLUT-Cre/VGAT-Flp combinational lines to identify and map 30 brain regions containing neurons that co-express vesicular glutamate and gamma-aminobutyric acid (GABA) transporters, followed by tracing their projections with intersectional viral vectors. Focusing on the lateral habenula (LHb) as a target, we identified glutamatergic, GABAergic, or co-glutamatergic/GABAergic innervations from ∼40 brain regions. These data provide an important resource for the future application of intersectional strategies and expand our understanding of the neuronal subtypes in the brain.
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Affiliation(s)
- Jian Xu
- Departments of Ophthalmology and Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Andrew Jo
- Departments of Ophthalmology and Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Raina P DeVries
- Department of Organismal Biology and Anatomy, The University of Chicago, Chicago, IL 60637, USA
| | - Sercan Deniz
- Departments of Ophthalmology and Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Suraj Cherian
- Departments of Ophthalmology and Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Idris Sunmola
- Departments of Ophthalmology and Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Xingqi Song
- School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - John J Marshall
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Katherine A Gruner
- Mouse Histology and Phenotyping Laboratory, Northwestern University, Chicago, IL 60611, USA
| | - Tanya L Daigle
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Anis Contractor
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Talia N Lerner
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Yongling Zhu
- Departments of Ophthalmology and Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
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41
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Nano PR, Bhaduri A. Evaluation of advances in cortical development using model systems. Dev Neurobiol 2022; 82:408-427. [PMID: 35644985 PMCID: PMC10924780 DOI: 10.1002/dneu.22879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 04/26/2022] [Accepted: 04/30/2022] [Indexed: 11/11/2022]
Abstract
Compared with that of even the closest primates, the human cortex displays a high degree of specialization and expansion that largely emerges developmentally. Although decades of research in the mouse and other model systems has revealed core tenets of cortical development that are well preserved across mammalian species, small deviations in transcription factor expression, novel cell types in primates and/or humans, and unique cortical architecture distinguish the human cortex. Importantly, many of the genes and signaling pathways thought to drive human-specific cortical expansion also leave the brain vulnerable to disease, as the misregulation of these factors is highly correlated with neurodevelopmental and neuropsychiatric disorders. However, creating a comprehensive understanding of human-specific cognition and disease remains challenging. Here, we review key stages of cortical development and highlight known or possible differences between model systems and the developing human brain. By identifying the developmental trajectories that may facilitate uniquely human traits, we highlight open questions in need of approaches to examine these processes in a human context and reveal translatable insights into human developmental disorders.
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Affiliation(s)
- Patricia R Nano
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Aparna Bhaduri
- Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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42
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Kim HB, Lu Y, Oh SC, Morris J, Miyashiro K, Kim J, Eberwine J, Sul JY. Astrocyte ethanol exposure reveals persistent and defined calcium response subtypes and associated gene signatures. J Biol Chem 2022; 298:102147. [PMID: 35716779 PMCID: PMC9293641 DOI: 10.1016/j.jbc.2022.102147] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 06/10/2022] [Accepted: 06/12/2022] [Indexed: 11/26/2022] Open
Abstract
Astrocytes play a critical role in brain function, but their contribution during ethanol (EtOH) consumption remains largely understudied. In light of recent findings on the heterogeneity of astrocyte physiology and gene expression, an approach with the ability to identify subtypes and capture this heterogeneity is necessary. Here, we combined measurements of calcium signaling and gene expression to define EtOH-induced astrocyte subtypes. In the absence of a demonstrated EtOH receptor, EtOH is believed to have effects on the function of many receptors and downstream biological cascades that underlie calcium responsiveness. This mechanism of EtOH-induced calcium signaling is unknown and this study provides the first step in understanding the characteristics of cells displaying these observed responses. To characterize underlying astrocyte subtypes, we assessed the correlation between calcium signaling and astrocyte gene expression signature in response to EtOH. We found that various EtOH doses increased intracellular calcium levels in a subset of astrocytes, distinguishing three cellular response types and one nonresponsive subtype as categorized by response waveform properties. Furthermore, single-cell RNA-seq analysis of astrocytes from the different response types identified type-enriched discriminatory gene expression signatures. Combining single-cell calcium responses and gene expression analysis identified specific astrocyte subgroups among astrocyte populations defined by their response to EtOH. This result provides a basis for identifying the relationship between astrocyte susceptibility to EtOH and corresponding measurable markers of calcium signaling and gene expression, which will be useful to investigate potential subgroup-specific influences of astrocytes on the physiology and pathology of EtOH exposure in the brain.
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Affiliation(s)
- Hyun-Bum Kim
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Youtao Lu
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Seonkyung C Oh
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jacqueline Morris
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kevin Miyashiro
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Junhyong Kim
- Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA; PENN Program in Single Cell Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - James Eberwine
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; PENN Program in Single Cell Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jai-Yoon Sul
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; PENN Program in Single Cell Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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43
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Morphological pseudotime ordering and fate mapping reveal diversification of cerebellar inhibitory interneurons. Nat Commun 2022; 13:3433. [PMID: 35701402 PMCID: PMC9197879 DOI: 10.1038/s41467-022-30977-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 05/20/2022] [Indexed: 12/15/2022] Open
Abstract
Understanding how diverse neurons are assembled into circuits requires a framework for describing cell types and their developmental trajectories. Here we combine genetic fate-mapping, pseudotemporal profiling of morphogenesis, and dual morphology and RNA labeling to resolve the diversification of mouse cerebellar inhibitory interneurons. Molecular layer interneurons (MLIs) derive from a common progenitor population but comprise diverse dendritic-, somatic-, and axon initial segment-targeting interneurons. Using quantitative morphology from 79 mature MLIs, we identify two discrete morphological types and presence of extensive within-class heterogeneity. Pseudotime trajectory inference using 732 developmental morphologies indicate the emergence of distinct MLI types during migration, before reaching their final positions. By comparing MLI identities from morphological and transcriptomic signatures, we demonstrate the dissociation between these modalities and that subtype divergence can be resolved from axonal morphogenesis prior to marker gene expression. Our study illustrates the utility of applying single-cell methods to quantify morphology for defining neuronal diversification.
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44
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Tukker JJ, Beed P, Brecht M, Kempter R, Moser EI, Schmitz D. Microcircuits for spatial coding in the medial entorhinal cortex. Physiol Rev 2022; 102:653-688. [PMID: 34254836 PMCID: PMC8759973 DOI: 10.1152/physrev.00042.2020] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The hippocampal formation is critically involved in learning and memory and contains a large proportion of neurons encoding aspects of the organism's spatial surroundings. In the medial entorhinal cortex (MEC), this includes grid cells with their distinctive hexagonal firing fields as well as a host of other functionally defined cell types including head direction cells, speed cells, border cells, and object-vector cells. Such spatial coding emerges from the processing of external inputs by local microcircuits. However, it remains unclear exactly how local microcircuits and their dynamics within the MEC contribute to spatial discharge patterns. In this review we focus on recent investigations of intrinsic MEC connectivity, which have started to describe and quantify both excitatory and inhibitory wiring in the superficial layers of the MEC. Although the picture is far from complete, it appears that these layers contain robust recurrent connectivity that could sustain the attractor dynamics posited to underlie grid pattern formation. These findings pave the way to a deeper understanding of the mechanisms underlying spatial navigation and memory.
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Affiliation(s)
- John J Tukker
- German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany
| | - Prateep Beed
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humbold-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Michael Brecht
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
- Neurocure Cluster of Excellence, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Richard Kempter
- Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Edvard I Moser
- Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, Trondheim, Norway
| | - Dietmar Schmitz
- German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany
- Neuroscience Research Center, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humbold-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Neurocure Cluster of Excellence, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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45
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Brain-wide projection reconstruction of single functionally defined neurons. Nat Commun 2022; 13:1531. [PMID: 35318336 PMCID: PMC8940919 DOI: 10.1038/s41467-022-29229-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 03/04/2022] [Indexed: 12/23/2022] Open
Abstract
Reconstructing axonal projections of single neurons at the whole-brain level is currently a converging goal of the neuroscience community that is fundamental for understanding the logic of information flow in the brain. Thousands of single neurons from different brain regions have recently been morphologically reconstructed, but the corresponding physiological functional features of these reconstructed neurons are unclear. By combining two-photon Ca2+ imaging with targeted single-cell plasmid electroporation, we reconstruct the brain-wide morphologies of single neurons that are defined by a sound-evoked response map in the auditory cortices (AUDs) of awake mice. Long-range interhemispheric projections can be reliably labelled via co-injection with an adeno-associated virus, which enables enhanced expression of indicator protein in the targeted neurons. Here we show that this method avoids the randomness and ambiguity of conventional methods of neuronal morphological reconstruction, offering an avenue for developing a precise one-to-one map of neuronal projection patterns and physiological functional features. Brain-wide axonal projections of single neurons have been extensively reconstructed without any functional characterization. The authors present a method that allows for developing a precise one-to-one map of both projection patterns and functional features of single neurons in mice.
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46
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Cheng S, Butrus S, Tan L, Xu R, Sagireddy S, Trachtenberg JT, Shekhar K, Zipursky SL. Vision-dependent specification of cell types and function in the developing cortex. Cell 2022; 185:311-327.e24. [PMID: 35063073 PMCID: PMC8813006 DOI: 10.1016/j.cell.2021.12.022] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 11/22/2021] [Accepted: 12/15/2021] [Indexed: 01/22/2023]
Abstract
The role of postnatal experience in sculpting cortical circuitry, while long appreciated, is poorly understood at the level of cell types. We explore this in the mouse primary visual cortex (V1) using single-nucleus RNA sequencing, visual deprivation, genetics, and functional imaging. We find that vision selectively drives the specification of glutamatergic cell types in upper layers (L) (L2/3/4), while deeper-layer glutamatergic, GABAergic, and non-neuronal cell types are established prior to eye opening. L2/3 cell types form an experience-dependent spatial continuum defined by the graded expression of ∼200 genes, including regulators of cell adhesion and synapse formation. One of these genes, Igsf9b, a vision-dependent gene encoding an inhibitory synaptic cell adhesion molecule, is required for the normal development of binocular responses in L2/3. In summary, vision preferentially regulates the development of upper-layer glutamatergic cell types through the regulation of cell-type-specific gene expression programs.
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Affiliation(s)
- Sarah Cheng
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Salwan Butrus
- Department of Chemical and Biomolecular Engineering, Helen Wills Neuroscience Institute, California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA 94720, USA
| | - Liming Tan
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Runzhe Xu
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Srikant Sagireddy
- Department of Chemical and Biomolecular Engineering, Helen Wills Neuroscience Institute, California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA 94720, USA
| | - Joshua T Trachtenberg
- Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Karthik Shekhar
- Department of Chemical and Biomolecular Engineering, Helen Wills Neuroscience Institute, California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA 94720, USA; Faculty Scientist, Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
| | - S Lawrence Zipursky
- Department of Biological Chemistry, Howard Hughes Medical Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Identifying Types of Neurons in the Human Colonic Enteric Nervous System. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1383:243-249. [PMID: 36587163 DOI: 10.1007/978-3-031-05843-1_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Distinguishing and characterising the different classes of neurons that make up a neural circuit has been a long-term goal for many neuroscientists. The enteric nervous system is a large but moderately simple part of the nervous system. Enteric neurons in laboratory animals have been extensively characterised morphologically, electrophysiologically, by projections and immunohistochemically. However, studies of human enteric nervous system are less advanced despite the potential availability of tissue from elective surgery (with appropriate ethics permits). Recent studies using single cell sequencing have confirmed and extended the classification of enteric neurons in mice and human, but it is not clear whether an encompassing classification has been achieved. We present preliminary data on a means to distinguish classes of myenteric neurons in specimens of human colon combining immunohistochemical, morphological, projection and size data on single cells. A method to apply multiple layers of antisera to specimens was developed, allowing up to 12 markers to be characterised in individual neurons. Applied to multi-axonal Dogiel type II neurons, this approach demonstrated that they constitute fewer than 5% of myenteric neurons, are nearly all immunoreactive for choline acetyltransferase and tachykinins. Many express the calcium-binding proteins calbindin and calretinin and they are larger than average myenteric cells. This methodology provides a complementary approach to single-cell mRNA profiling to provide a comprehensive account of the types of myenteric neurons in the human colon.
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Emerging strategies for the genetic dissection of gene functions, cell types, and neural circuits in the mammalian brain. Mol Psychiatry 2022; 27:422-435. [PMID: 34561609 DOI: 10.1038/s41380-021-01292-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 08/17/2021] [Accepted: 09/08/2021] [Indexed: 02/08/2023]
Abstract
The mammalian brain is composed of a large number of highly diverse cell types with different molecular, anatomical, and functional features. Distinct cellular identities are generated during development under the regulation of intricate genetic programs and manifested through unique combinations of gene expression. Recent advancements in our understanding of the molecular and cellular mechanisms underlying the assembly, function, and pathology of the brain circuitry depend on the invention and application of genetic strategies that engage intrinsic gene regulatory mechanisms. Here we review the strategies for gene regulation on DNA, RNA, and protein levels and their applications in cell type targeting and neural circuit dissection. We highlight newly emerged strategies and emphasize the importance of combinatorial approaches. We also discuss the potential caveats and pitfalls in current methods and suggest future prospects to improve their comprehensiveness and versatility.
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Masaki Y, Yamaguchi M, Takeuchi RF, Osakada F. Monosynaptic rabies virus tracing from projection-targeted single neurons. Neurosci Res 2022; 178:20-32. [DOI: 10.1016/j.neures.2022.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/16/2022] [Accepted: 01/25/2022] [Indexed: 10/19/2022]
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Moussa AJ, Wester JC. Cell-type specific transcriptomic signatures of neocortical circuit organization and their relevance to autism. Front Neural Circuits 2022; 16:982721. [PMID: 36213201 PMCID: PMC9545608 DOI: 10.3389/fncir.2022.982721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 08/29/2022] [Indexed: 11/17/2022] Open
Abstract
A prevailing challenge in neuroscience is understanding how diverse neuronal cell types select their synaptic partners to form circuits. In the neocortex, major classes of excitatory projection neurons and inhibitory interneurons are conserved across functionally distinct regions. There is evidence these classes form canonical circuit motifs that depend primarily on their identity; however, regional cues likely also influence their choice of synaptic partners. We mined the Allen Institute's single-cell RNA-sequencing database of mouse cortical neurons to study the expression of genes necessary for synaptic connectivity and physiology in two regions: the anterior lateral motor cortex (ALM) and the primary visual cortex (VISp). We used the Allen's metadata to parse cells by clusters representing major excitatory and inhibitory classes that are common to both ALM and VISp. We then performed two types of pairwise differential gene expression analysis: (1) between different neuronal classes within the same brain region (ALM or VISp), and (2) between the same neuronal class in ALM and VISp. We filtered our results for differentially expressed genes related to circuit connectivity and developed a novel bioinformatic approach to determine the sets uniquely enriched in each neuronal class in ALM, VISp, or both. This analysis provides an organized set of genes that may regulate synaptic connectivity and physiology in a cell-type-specific manner. Furthermore, it identifies candidate mechanisms for circuit organization that are conserved across functionally distinct cortical regions or that are region dependent. Finally, we used the SFARI Human Gene Module to identify genes from this analysis that are related to risk for autism spectrum disorder (ASD). Our analysis provides clear molecular targets for future studies to understand neocortical circuit organization and abnormalities that underlie autistic phenotypes.
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Affiliation(s)
- Anthony J Moussa
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, OH, United States
| | - Jason C Wester
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, OH, United States
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