201
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Bo T, Li J, Hu G, Zhang G, Wang W, Lv Q, Zhao S, Ma J, Qin M, Yao X, Wang M, Wang GZ, Wang Z. Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys. Nat Commun 2023; 14:1499. [PMID: 36932104 PMCID: PMC10023667 DOI: 10.1038/s41467-023-37246-w] [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: 08/08/2022] [Accepted: 03/06/2023] [Indexed: 03/19/2023] Open
Abstract
Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.
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Affiliation(s)
- Tingting Bo
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Ganlu Hu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Ge Zhang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China
| | - Wei Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qian Lv
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Shaoling Zhao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Meng Qin
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Xiaohui Yao
- Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao, Shandong, China
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China.
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Zheng Wang
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
- School of Biomedical Engineering, Hainan University, Haikou, Hainan, China.
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202
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Luria V, Ma S, Shibata M, Pattabiraman K, Sestan N. Molecular and cellular mechanisms of human cortical connectivity. Curr Opin Neurobiol 2023; 80:102699. [PMID: 36921362 DOI: 10.1016/j.conb.2023.102699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 02/05/2023] [Indexed: 03/18/2023]
Abstract
Comparative studies of the cerebral cortex have identified various human and primate-specific changes in both local and long-range connectivity, which are thought to underlie our advanced cognitive capabilities. These changes are likely mediated by the divergence of spatiotemporal regulation of gene expression, which is particularly prominent in the prenatal and early postnatal human and non-human primate cerebral cortex. In this review, we describe recent advances in characterizing human and primate genetic and cellular innovations including identification of novel species-specific, especially human-specific, genes, gene expression patterns, and cell types. Finally, we highlight three recent studies linking these molecular changes to reorganization of cortical connectivity.
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Affiliation(s)
- Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Mikihito Shibata
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Kartik Pattabiraman
- Yale Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA.
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA; Yale Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA; Departments of Psychiatry, Genetics and Comparative Medicine, Program in Cellular Neuroscience, Neurodegeneration and Repair, and Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA.
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203
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Praschberger R, Kuenen S, Schoovaerts N, Kaempf N, Singh J, Janssens J, Swerts J, Nachman E, Calatayud C, Aerts S, Poovathingal S, Verstreken P. Neuronal identity defines α-synuclein and tau toxicity. Neuron 2023; 111:1577-1590.e11. [PMID: 36948206 DOI: 10.1016/j.neuron.2023.02.033] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/22/2022] [Accepted: 02/23/2023] [Indexed: 03/24/2023]
Abstract
Pathogenic α-synuclein and tau are critical drivers of neurodegeneration, and their mutations cause neuronal loss in patients. Whether the underlying preferential neuronal vulnerability is a cell-type-intrinsic property or a consequence of increased expression levels remains elusive. Here, we explore cell-type-specific α-synuclein and tau expression in human brain datasets and use deep phenotyping as well as brain-wide single-cell RNA sequencing of >200 live neuron types in fruit flies to determine which cellular environments react most to α-synuclein or tau toxicity. We detect phenotypic and transcriptomic evidence of differential neuronal vulnerability independent of α-synuclein or tau expression levels. Comparing vulnerable with resilient neurons in Drosophila enabled us to predict numerous human neuron subtypes with increased intrinsic susceptibility to pathogenic α-synuclein or tau. By uncovering synapse- and Ca2+ homeostasis-related genes as tau toxicity modifiers, our work paves the way to leverage neuronal identity to uncover modifiers of neurodegeneration-associated toxic proteins.
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Affiliation(s)
- Roman Praschberger
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium.
| | - Sabine Kuenen
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Nils Schoovaerts
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Natalie Kaempf
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Jeevanjot Singh
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Jasper Janssens
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Human Genetics, 3000 Leuven, Belgium
| | - Jef Swerts
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Eliana Nachman
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Carles Calatayud
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Stein Aerts
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Human Genetics, 3000 Leuven, Belgium
| | | | - Patrik Verstreken
- VIB-KU Leuven Center for Brain & Disease Research, 3000 Leuven, Belgium; KU Leuven, Department of Neurosciences, Leuven Brain Institute, 3000 Leuven, Belgium.
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204
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Hunt S, Leibner Y, Mertens EJ, Barros-Zulaica N, Kanari L, Heistek TS, Karnani MM, Aardse R, Wilbers R, Heyer DB, Goriounova NA, Verhoog MB, Testa-Silva G, Obermayer J, Versluis T, Benavides-Piccione R, de Witt-Hamer P, Idema S, Noske DP, Baayen JC, Lein ES, DeFelipe J, Markram H, Mansvelder HD, Schürmann F, Segev I, de Kock CPJ. Strong and reliable synaptic communication between pyramidal neurons in adult human cerebral cortex. Cereb Cortex 2023; 33:2857-2878. [PMID: 35802476 PMCID: PMC10016070 DOI: 10.1093/cercor/bhac246] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 12/25/2022] Open
Abstract
Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3-4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.
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Affiliation(s)
| | | | - Eline J Mertens
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Natalí Barros-Zulaica
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Lida Kanari
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Tim S Heistek
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Mahesh M Karnani
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Romy Aardse
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | | | | | - Joshua Obermayer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Tamara Versluis
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Ruth Benavides-Piccione
- Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, Madrid 28223, Spain
| | - Philip de Witt-Hamer
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Sander Idema
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - David P Noske
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Johannes C Baayen
- Neurosurgery Department, Amsterdam Universitair Medische Centra, location VUmc, 1081 HV Amsterdam, the Netherlands
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Universidad Politécnica de Madrid and Instituto Cajal (CSIC), Pozuelo de Alarcón, Madrid 28223, Spain
| | - Henry Markram
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
| | - Felix Schürmann
- Blue Brain Project, Ecole polytechnique fédérale de Lausanne, Campus Biotech, Geneva 1202, Switzerland
| | - Idan Segev
- Department of Neurobiology and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, 9190501 Jerusalem, Israel
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205
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Anderson AG, Rogers BB, Loupe JM, Rodriguez-Nunez I, Roberts SC, White LM, Brazell JN, Bunney WE, Bunney BG, Watson SJ, Cochran JN, Myers RM, Rizzardi LF. Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements. CELL GENOMICS 2023; 3:100263. [PMID: 36950385 PMCID: PMC10025452 DOI: 10.1016/j.xgen.2023.100263] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 12/06/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023]
Abstract
Cell type-specific transcriptional differences between brain tissues from donors with Alzheimer's disease (AD) and unaffected controls have been well documented, but few studies have rigorously interrogated the regulatory mechanisms responsible for these alterations. We performed single nucleus multiomics (snRNA-seq plus snATAC-seq) on 105,332 nuclei isolated from cortical tissues from 7 AD and 8 unaffected donors to identify candidate cis-regulatory elements (CREs) involved in AD-associated transcriptional changes. We detected 319,861 significant correlations, or links, between gene expression and cell type-specific transposase accessible regions enriched for active CREs. Among these, 40,831 were unique to AD tissues. Validation experiments confirmed the activity of many regions, including several candidate regulators of APP expression. We identified ZEB1 and MAFB as candidate transcription factors playing important roles in AD-specific gene regulation in neurons and microglia, respectively. Microglia links were globally enriched for heritability of AD risk and previously identified active regulatory regions.
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Affiliation(s)
| | - Brianne B. Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jacob M. Loupe
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | | | - Lauren M. White
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - William E. Bunney
- Department of Psychiatry and Human Behavior, College of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Blynn G. Bunney
- Department of Psychiatry and Human Behavior, College of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Stanley J. Watson
- Mental Health Research Institute, University of Michigan, Ann Arbor, MI, USA
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206
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Zhang M, Pan X, Jung W, Halpern A, Eichhorn SW, Lei Z, Cohen L, Smith KA, Tasic B, Yao Z, Zeng H, Zhuang X. A molecularly defined and spatially resolved cell atlas of the whole mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.06.531348. [PMID: 36945367 PMCID: PMC10028822 DOI: 10.1101/2023.03.06.531348] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in ~8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to ~300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.
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Affiliation(s)
- Meng Zhang
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
- These authors contributed equally
| | - Xingjie Pan
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
- These authors contributed equally
| | - Won Jung
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
- These authors contributed equally
| | - Aaron Halpern
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Stephen W. Eichhorn
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Zhiyun Lei
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Limor Cohen
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | | | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
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207
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Yao Z, van Velthoven CTJ, Kunst M, Zhang M, McMillen D, Lee C, Jung W, Goldy J, Abdelhak A, Baker P, Barkan E, Bertagnolli D, Campos J, Carey D, Casper T, Chakka AB, Chakrabarty R, Chavan S, Chen M, Clark M, Close J, Crichton K, Daniel S, Dolbeare T, Ellingwood L, Gee J, Glandon A, Gloe J, Gould J, Gray J, Guilford N, Guzman J, Hirschstein D, Ho W, Jin K, Kroll M, Lathia K, Leon A, Long B, Maltzer Z, Martin N, McCue R, Meyerdierks E, Nguyen TN, Pham T, Rimorin C, Ruiz A, Shapovalova N, Slaughterbeck C, Sulc J, Tieu M, Torkelson A, Tung H, Cuevas NV, Wadhwani K, Ward K, Levi B, Farrell C, Thompson CL, Mufti S, Pagan CM, Kruse L, Dee N, Sunkin SM, Esposito L, Hawrylycz MJ, Waters J, Ng L, Smith KA, Tasic B, Zhuang X, Zeng H. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.06.531121. [PMID: 37034735 PMCID: PMC10081189 DOI: 10.1101/2023.03.06.531121] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.
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Affiliation(s)
- Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Meng Zhang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | | | - Changkyu Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Won Jung
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Pamela Baker
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Eliza Barkan
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Daniel Carey
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Min Chen
- University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jennie Close
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Scott Daniel
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tim Dolbeare
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - James Gee
- University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jessica Gloe
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - James Gray
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Windy Ho
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Kelly Jin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Kanan Lathia
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Arielle Leon
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Brian Long
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Zoe Maltzer
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Naomi Martin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Rachel McCue
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | | | - Josef Sulc
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Herman Tung
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Katelyn Ward
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Boaz Levi
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Shoaib Mufti
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Lauren Kruse
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Jack Waters
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
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208
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Astrocyte heterogeneity and interactions with local neural circuits. Essays Biochem 2023; 67:93-106. [PMID: 36748397 PMCID: PMC10011406 DOI: 10.1042/ebc20220136] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/09/2023] [Accepted: 01/09/2023] [Indexed: 02/08/2023]
Abstract
Astrocytes are ubiquitous within the central nervous system (CNS). These cells possess many individual processes which extend out into the neuropil, where they interact with a variety of other cell types, including neurons at synapses. Astrocytes are now known to be active players in all aspects of the synaptic life cycle, including synapse formation and elimination, synapse maturation, maintenance of synaptic homeostasis and modulation of synaptic transmission. Traditionally, astrocytes have been studied as a homogeneous group of cells. However, recent studies have uncovered a surprising degree of heterogeneity in their development and function, suggesting that astrocytes may be matched to neurons to support local circuits. Hence, a better understanding of astrocyte heterogeneity and its implications are needed to understand brain function.
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209
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Bingham CS, Petersen MV, Parent M, McIntyre CC. Evolving characterization of the human hyperdirect pathway. Brain Struct Funct 2023; 228:353-365. [PMID: 36708394 PMCID: PMC10716731 DOI: 10.1007/s00429-023-02610-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 01/11/2023] [Indexed: 01/29/2023]
Abstract
The hyperdirect pathway (HDP) represents the main glutamatergic input to the subthalamic nucleus (STN), through which the motor and prefrontal cerebral cortex can modulate basal ganglia activity. Further, direct activation of the motor HDP is thought to be an important component of therapeutic deep brain stimulation (DBS), mediating the disruption of pathological oscillations. Alternatively, unintended recruitment of the prefrontal HDP may partly explain some cognitive side effects of DBS therapy. Previous work describing the HDP has focused on non-human primate (NHP) histological pathway tracings, diffusion-weighted MRI analysis of human white matter, and electrophysiology studies involving paired cortical recordings with DBS. However, none of these approaches alone yields a complete understanding of the complexities of the HDP. As such, we propose that generative modeling methods hold promise to bridge anatomy and physiology results, from both NHPs and humans, into a more detailed representation of the human HDP. Nonetheless, numerous features of the HDP remain to be experimentally described before model-based methods can simulate corticosubthalamic activity with a high degree of scientific detail. Therefore, the goals of this review are to examine the experimental evidence for HDP projections from across the primate neocortex and discuss new data which are required to improve the utility of anatomical and biophysical models of the human corticosubthalamic system.
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Affiliation(s)
- Clayton S Bingham
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Martin Parent
- Department of Psychiatry and Neuroscience, Laval University, Quebec, Canada
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurosurgery, Duke University, Durham, NC, USA.
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210
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Fu Z, Sajad A, Errington SP, Schall JD, Rutishauser U. Neurophysiological mechanisms of error monitoring in human and non-human primates. Nat Rev Neurosci 2023; 24:153-172. [PMID: 36707544 PMCID: PMC10231843 DOI: 10.1038/s41583-022-00670-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/16/2022] [Indexed: 01/29/2023]
Abstract
Performance monitoring is an important executive function that allows us to gain insight into our own behaviour. This remarkable ability relies on the frontal cortex, and its impairment is an aspect of many psychiatric diseases. In recent years, recordings from the macaque and human medial frontal cortex have offered a detailed understanding of the neurophysiological substrate that underlies performance monitoring. Here we review the discovery of single-neuron correlates of error monitoring, a key aspect of performance monitoring, in both species. These neurons are the generators of the error-related negativity, which is a non-invasive biomarker that indexes error detection. We evaluate a set of tasks that allows the synergistic elucidation of the mechanisms of cognitive control across the two species, consider differences in brain anatomy and testing conditions across species, and describe the clinical relevance of these findings for understanding psychopathology. Last, we integrate the body of experimental facts into a theoretical framework that offers a new perspective on how error signals are computed in both species and makes novel, testable predictions.
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Affiliation(s)
- Zhongzheng Fu
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.
| | - Amirsaman Sajad
- Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Steven P Errington
- Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Jeffrey D Schall
- Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN, USA.
- Department of Psychology, Vanderbilt University, Nashville, TN, USA.
- Centre for Vision Research, York University, Toronto, Ontario, Canada.
- Vision: Science to Applications (VISTA), York University, Toronto, Ontario, Canada.
- Department of Biology, Faculty of Science, York University, Toronto, Ontario, Canada.
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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211
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Lukacs IP, Francavilla R, Field M, Hunter E, Howarth M, Horie S, Plaha P, Stacey R, Livermore L, Ansorge O, Tamas G, Somogyi P. Differential effects of group III metabotropic glutamate receptors on spontaneous inhibitory synaptic currents in spine-innervating double bouquet and parvalbumin-expressing dendrite-targeting GABAergic interneurons in human neocortex. Cereb Cortex 2023; 33:2101-2142. [PMID: 35667019 PMCID: PMC9977385 DOI: 10.1093/cercor/bhac195] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/12/2022] Open
Abstract
Diverse neocortical GABAergic neurons specialize in synaptic targeting and their effects are modulated by presynaptic metabotropic glutamate receptors (mGluRs) suppressing neurotransmitter release in rodents, but their effects in human neocortex are unknown. We tested whether activation of group III mGluRs by L-AP4 changes GABAA receptor-mediated spontaneous inhibitory postsynaptic currents (sIPSCs) in 2 distinct dendritic spine-innervating GABAergic interneurons recorded in vitro in human neocortex. Calbindin-positive double bouquet cells (DBCs) had columnar "horsetail" axons descending through layers II-V innervating dendritic spines (48%) and shafts, but not somata of pyramidal and nonpyramidal neurons. Parvalbumin-expressing dendrite-targeting cell (PV-DTC) axons extended in all directions innervating dendritic spines (22%), shafts (65%), and somata (13%). As measured, 20% of GABAergic neuropil synapses innervate spines, hence DBCs, but not PV-DTCs, preferentially select spine targets. Group III mGluR activation paradoxically increased the frequency of sIPSCs in DBCs (to median 137% of baseline) but suppressed it in PV-DTCs (median 92%), leaving the amplitude unchanged. The facilitation of sIPSCs in DBCs may result from their unique GABAergic input being disinhibited via network effect. We conclude that dendritic spines receive specialized, diverse GABAergic inputs, and group III mGluRs differentially regulate GABAergic synaptic transmission to distinct GABAergic cell types in human cortex.
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Affiliation(s)
- Istvan P Lukacs
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | | | - Martin Field
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Emily Hunter
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Michael Howarth
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Sawa Horie
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Puneet Plaha
- Department of Neurosurgery, John Radcliffe Hospital, OUH NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Richard Stacey
- Department of Neurosurgery, John Radcliffe Hospital, OUH NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Laurent Livermore
- Department of Neurosurgery, John Radcliffe Hospital, OUH NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Gabor Tamas
- Department of Physiology, Anatomy and Neuroscience, University of Szeged, 6726 Szeged, Hungary
| | - Peter Somogyi
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
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212
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Huuki-Myers L, Spangler A, Eagles N, Montgomery KD, Kwon SH, Guo B, Grant-Peters M, Divecha HR, Tippani M, Sriworarat C, Nguyen AB, Ravichandran P, Tran MN, Seyedian A, Hyde TM, Kleinman JE, Battle A, Page SC, Ryten M, Hicks SC, Martinowich K, Collado-Torres L, Maynard KR. Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528722. [PMID: 36824961 PMCID: PMC9949126 DOI: 10.1101/2023.02.15.528722] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.
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Affiliation(s)
- Louise Huuki-Myers
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Abby Spangler
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Nick Eagles
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Kelsey D Montgomery
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Boyi Guo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Melissa Grant-Peters
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Heena R Divecha
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Madhavi Tippani
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Chaichontat Sriworarat
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Annie B Nguyen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | | | - Matthew N Tran
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Arta Seyedian
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie C Page
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Mina Ryten
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
| | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | | | - Kristen R Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
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213
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Vanderhaeghen P, Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat Rev Neurosci 2023; 24:213-232. [PMID: 36792753 PMCID: PMC10064077 DOI: 10.1038/s41583-023-00675-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 02/17/2023]
Abstract
The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.
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Affiliation(s)
- Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium.
- Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Franck Polleux
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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214
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Wildenberg G, Li H, Kasthuri N. The Development of Synapses in Mouse and Macaque Primary Sensory Cortices. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528564. [PMID: 36824798 PMCID: PMC9949058 DOI: 10.1101/2023.02.15.528564] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
We report that the rate of synapse development in primary sensory cortices of mice and macaques is unrelated to lifespan, as was previously thought. We analyzed 28,084 synapses over multiple developmental time points in both species and find, instead, that net excitatory synapse development of mouse and macaque neurons primarily increased at similar rates in the first few postnatal months, and then decreased over a span of 1-1.5 years of age. The development of inhibitory synapses differed qualitatively across species. In macaques, net inhibitory synapses first increase and then decrease on excitatory soma at similar ages as excitatory synapses. In mice, however, such synapses are added throughout life. These findings contradict the long-held belief that the cycle of synapse formation and pruning occurs earlier in shorter-lived animals. Instead, our results suggest more nuanced rules, with the development of different types of synapses following different timing rules or different trajectories across species.
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Affiliation(s)
- Gregg Wildenberg
- Department of Neurobiology, The University of Chicago
- Argonne National Laboratory, Biosciences Division
| | - Hanyu Li
- Department of Neurobiology, The University of Chicago
- Argonne National Laboratory, Biosciences Division
| | - Narayanan Kasthuri
- Department of Neurobiology, The University of Chicago
- Argonne National Laboratory, Biosciences Division
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215
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Molecular and cellular evolution of the amygdala across species analyzed by single-nucleus transcriptome profiling. Cell Discov 2023; 9:19. [PMID: 36788214 PMCID: PMC9929086 DOI: 10.1038/s41421-022-00506-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 11/24/2022] [Indexed: 02/16/2023] Open
Abstract
The amygdala, or an amygdala-like structure, is found in the brains of all vertebrates and plays a critical role in survival and reproduction. However, the cellular architecture of the amygdala and how it has evolved remain elusive. Here, we generated single-nucleus RNA-sequencing data for more than 200,000 cells in the amygdala of humans, macaques, mice, and chickens. Abundant neuronal cell types from different amygdala subnuclei were identified in all datasets. Cross-species analysis revealed that inhibitory neurons and inhibitory neuron-enriched subnuclei of the amygdala were well-conserved in cellular composition and marker gene expression, whereas excitatory neuron-enriched subnuclei were relatively divergent. Furthermore, LAMP5+ interneurons were much more abundant in primates, while DRD2+ inhibitory neurons and LAMP5+SATB2+ excitatory neurons were dominant in the human central amygdalar nucleus (CEA) and basolateral amygdalar complex (BLA), respectively. We also identified CEA-like neurons and their species-specific distribution patterns in chickens. This study highlights the extreme cell-type diversity in the amygdala and reveals the conservation and divergence of cell types and gene expression patterns across species that may contribute to species-specific adaptations.
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216
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Szegedi V, Bakos E, Furdan S, Kovács BH, Varga D, Erdélyi M, Barzó P, Szücs A, Tamás G, Lamsa K. HCN channels at the cell soma ensure the rapid electrical reactivity of fast-spiking interneurons in human neocortex. PLoS Biol 2023; 21:e3002001. [PMID: 36745683 PMCID: PMC9934405 DOI: 10.1371/journal.pbio.3002001] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 02/16/2023] [Accepted: 01/17/2023] [Indexed: 02/07/2023] Open
Abstract
Accumulating evidence indicates that there are substantial species differences in the properties of mammalian neurons, yet theories on circuit activity and information processing in the human brain are based heavily on results obtained from rodents and other experimental animals. This knowledge gap may be particularly important for understanding the neocortex, the brain area responsible for the most complex neuronal operations and showing the greatest evolutionary divergence. Here, we examined differences in the electrophysiological properties of human and mouse fast-spiking GABAergic basket cells, among the most abundant inhibitory interneurons in cortex. Analyses of membrane potential responses to current input, pharmacologically isolated somatic leak currents, isolated soma outside-out patch recordings, and immunohistochemical staining revealed that human neocortical basket cells abundantly express hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channel isoforms HCN1 and HCN2 at the cell soma membrane, whereas these channels are sparse at the rodent basket cell soma membrane. Antagonist experiments showed that HCN channels in human neurons contribute to the resting membrane potential and cell excitability at the cell soma, accelerate somatic membrane potential kinetics, and shorten the lag between excitatory postsynaptic potentials and action potential generation. These effects are important because the soma of human fast-spiking neurons without HCN channels exhibit low persistent ion leak and slow membrane potential kinetics, compared with mouse fast-spiking neurons. HCN channels speed up human cell membrane potential kinetics and help attain an input-output rate close to that of rodent cells. Computational modeling demonstrated that HCN channel activity at the human fast-spiking cell soma membrane is sufficient to accelerate the input-output function as observed in cell recordings. Thus, human and mouse fast-spiking neurons exhibit functionally significant differences in ion channel composition at the cell soma membrane to set the speed and fidelity of their input-output function. These HCN channels ensure fast electrical reactivity of fast-spiking cells in human neocortex.
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Affiliation(s)
- Viktor Szegedi
- Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
- Hungarian Centre of Excellence for Molecular Medicine Research Group for Human neuron physiology and therapy, Szeged, Hungary
| | - Emőke Bakos
- Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
- Hungarian Centre of Excellence for Molecular Medicine Research Group for Human neuron physiology and therapy, Szeged, Hungary
| | - Szabina Furdan
- Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
- Hungarian Centre of Excellence for Molecular Medicine Research Group for Human neuron physiology and therapy, Szeged, Hungary
| | - Bálint H. Kovács
- Department of Optics and Quantum Electronics, University of Szeged, Szeged, Hungary
| | - Dániel Varga
- Department of Optics and Quantum Electronics, University of Szeged, Szeged, Hungary
| | - Miklós Erdélyi
- Department of Optics and Quantum Electronics, University of Szeged, Szeged, Hungary
| | - Pál Barzó
- Department of Neurosurgery, University of Szeged, Szeged, Hungary
| | - Attila Szücs
- Hungarian Centre of Excellence for Molecular Medicine Research Group for Human neuron physiology and therapy, Szeged, Hungary
- Neuronal Cell Biology Research Group, Eötvös Loránd University, Budapest, Budapest, Hungary
| | - Gábor Tamás
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Karri Lamsa
- Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
- Hungarian Centre of Excellence for Molecular Medicine Research Group for Human neuron physiology and therapy, Szeged, Hungary
- * E-mail: ,
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217
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Yadav A, Matson KJE, Li L, Hua I, Petrescu J, Kang K, Alkaslasi MR, Lee DI, Hasan S, Galuta A, Dedek A, Ameri S, Parnell J, Alshardan MM, Qumqumji FA, Alhamad SM, Wang AP, Poulen G, Lonjon N, Vachiery-Lahaye F, Gaur P, Nalls MA, Qi YA, Maric D, Ward ME, Hildebrand ME, Mery PF, Bourinet E, Bauchet L, Tsai EC, Phatnani H, Le Pichon CE, Menon V, Levine AJ. A cellular taxonomy of the adult human spinal cord. Neuron 2023; 111:328-344.e7. [PMID: 36731429 PMCID: PMC10044516 DOI: 10.1016/j.neuron.2023.01.007] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 11/30/2022] [Accepted: 01/11/2023] [Indexed: 02/04/2023]
Abstract
The mammalian spinal cord functions as a community of cell types for sensory processing, autonomic control, and movement. While animal models have advanced our understanding of spinal cellular diversity, characterizing human biology directly is important to uncover specialized features of basic function and human pathology. Here, we present a cellular taxonomy of the adult human spinal cord using single-nucleus RNA sequencing with spatial transcriptomics and antibody validation. We identified 29 glial clusters and 35 neuronal clusters, organized principally by anatomical location. To demonstrate the relevance of this resource to human disease, we analyzed spinal motoneurons, which degenerate in amyotrophic lateral sclerosis (ALS) and other diseases. We found that compared with other spinal neurons, human motoneurons are defined by genes related to cell size, cytoskeletal structure, and ALS, suggesting a specialized molecular repertoire underlying their selective vulnerability. We include a web resource to facilitate further investigations into human spinal cord biology.
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Affiliation(s)
- Archana Yadav
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA
| | - Kaya J E Matson
- Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Johns Hopkins University Department of Biology, Baltimore, MD 21218, USA
| | - Li Li
- Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Isabelle Hua
- Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Joana Petrescu
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA; Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
| | - Kristy Kang
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA; Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
| | - Mor R Alkaslasi
- Unit on the Development of Neurodegeneration, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA; Department of Neuroscience, Brown University, Providence, RI, USA
| | - Dylan I Lee
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA
| | - Saadia Hasan
- Inherited Neurodegenerative Diseases Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Ahmad Galuta
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Annemarie Dedek
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada; Department of Neuroscience, Carleton University, Ottawa, ON, Canada
| | - Sara Ameri
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Jessica Parnell
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada; Department of Neuroscience, Carleton University, Ottawa, ON, Canada
| | | | | | - Saud M Alhamad
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Alick Pingbei Wang
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Gaetan Poulen
- Department of Neurosurgery, Gui de Chauliac Hospital, and Donation and Transplantation Coordination Unit, Montpellier University Medical Center, Montpellier, France
| | - Nicolas Lonjon
- Department of Neurosurgery, Gui de Chauliac Hospital, and Donation and Transplantation Coordination Unit, Montpellier University Medical Center, Montpellier, France
| | - Florence Vachiery-Lahaye
- Department of Neurosurgery, Gui de Chauliac Hospital, and Donation and Transplantation Coordination Unit, Montpellier University Medical Center, Montpellier, France
| | - Pallavi Gaur
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International LLC, Glen Echo, MD, USA
| | - Yue A Qi
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Dragan Maric
- Flow and Imaging Cytometry Core Facility, National Institute of Neurological Disorders and Stroke; Bethesda, MD, USA
| | - Michael E Ward
- Inherited Neurodegenerative Diseases Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Michael E Hildebrand
- Inherited Neurodegenerative Diseases Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Pierre-Francois Mery
- Institute of Functional Genomics, Montpellier University, CNRS, INSERM, Montpellier, France
| | - Emmanuel Bourinet
- Institute of Functional Genomics, Montpellier University, CNRS, INSERM, Montpellier, France
| | - Luc Bauchet
- Department of Neurosurgery, Gui de Chauliac Hospital, and Donation and Transplantation Coordination Unit, Montpellier University Medical Center, Montpellier, France; Institute of Functional Genomics, Montpellier University, CNRS, INSERM, Montpellier, France
| | - Eve C Tsai
- Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Hemali Phatnani
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA; Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
| | - Claire E Le Pichon
- Unit on the Development of Neurodegeneration, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - Vilas Menon
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY, USA.
| | - Ariel J Levine
- Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
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218
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Ding L, Shi H, Qian C, Burdyshaw C, Veloso JP, Khatamian A, Pan Q, Dhungana Y, Xie Z, Risch I, Yang X, Huang X, Yan L, Rusch M, Brewer M, Yan KK, Chi H, Yu J. scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.26.523391. [PMID: 36747870 PMCID: PMC9901187 DOI: 10.1101/2023.01.26.523391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.
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Affiliation(s)
- Liang Ding
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- These authors contributed equally
| | - Hao Shi
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- These authors contributed equally
| | - Chenxi Qian
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Chad Burdyshaw
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Joao Pedro Veloso
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Alireza Khatamian
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Qingfei Pan
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Yogesh Dhungana
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Zhen Xie
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Physiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Isabel Risch
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Xu Yang
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Xin Huang
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Lei Yan
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Michael Rusch
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Michael Brewer
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Koon-Kiu Yan
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Hongbo Chi
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Jiyang Yu
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
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219
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Ding L, Shi H, Qian C, Burdyshaw C, Veloso JP, Khatamian A, Pan Q, Dhungana Y, Xie Z, Risch I, Yang X, Huang X, Yan L, Rusch M, Brewer M, Yan KK, Chi H, Yu J. scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data. RESEARCH SQUARE 2023:rs.3.rs-2476875. [PMID: 36747874 PMCID: PMC9901036 DOI: 10.21203/rs.3.rs-2476875/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.
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Affiliation(s)
- Liang Ding
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Hao Shi
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Chenxi Qian
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Chad Burdyshaw
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Joao Pedro Veloso
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Alireza Khatamian
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Qingfei Pan
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Yogesh Dhungana
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Zhen Xie
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Physiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Isabel Risch
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Xu Yang
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Xin Huang
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Lei Yan
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Michael Rusch
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Michael Brewer
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Koon-Kiu Yan
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Hongbo Chi
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Jiyang Yu
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
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220
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Garnier Artiñano T, Andalibi V, Atula I, Maestri M, Vanni S. Biophysical parameters control signal transfer in spiking network. Front Comput Neurosci 2023; 17:1011814. [PMID: 36761840 PMCID: PMC9905747 DOI: 10.3389/fncom.2023.1011814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 01/09/2023] [Indexed: 01/26/2023] Open
Abstract
Introduction Information transmission and representation in both natural and artificial networks is dependent on connectivity between units. Biological neurons, in addition, modulate synaptic dynamics and post-synaptic membrane properties, but how these relate to information transmission in a population of neurons is still poorly understood. A recent study investigated local learning rules and showed how a spiking neural network can learn to represent continuous signals. Our study builds on their model to explore how basic membrane properties and synaptic delays affect information transfer. Methods The system consisted of three input and output units and a hidden layer of 300 excitatory and 75 inhibitory leaky integrate-and-fire (LIF) or adaptive integrate-and-fire (AdEx) units. After optimizing the connectivity to accurately replicate the input patterns in the output units, we transformed the model to more biologically accurate units and included synaptic delay and concurrent action potential generation in distinct neurons. We examined three different parameter regimes which comprised either identical physiological values for both excitatory and inhibitory units (Comrade), more biologically accurate values (Bacon), or the Comrade regime whose output units were optimized for low reconstruction error (HiFi). We evaluated information transmission and classification accuracy of the network with four distinct metrics: coherence, Granger causality, transfer entropy, and reconstruction error. Results Biophysical parameters showed a major impact on information transfer metrics. The classification was surprisingly robust, surviving very low firing and information rates, whereas information transmission overall and particularly low reconstruction error were more dependent on higher firing rates in LIF units. In AdEx units, the firing rates were lower and less information was transferred, but interestingly the highest information transmission rates were no longer overlapping with the highest firing rates. Discussion Our findings can be reflected on the predictive coding theory of the cerebral cortex and may suggest information transfer qualities as a phenomenological quality of biological cells.
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Affiliation(s)
- Tomás Garnier Artiñano
- Helsinki University Hospital (HUS) Neurocenter, Neurology, Helsinki University Hospital, Helsinki, Finland,Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland
| | - Vafa Andalibi
- Department of Computer Science, Indiana University Bloomington, Bloomington, IN, United States
| | - Iiris Atula
- Helsinki University Hospital (HUS) Neurocenter, Neurology, Helsinki University Hospital, Helsinki, Finland,Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland
| | - Matteo Maestri
- Helsinki University Hospital (HUS) Neurocenter, Neurology, Helsinki University Hospital, Helsinki, Finland,Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland,Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Simo Vanni
- Helsinki University Hospital (HUS) Neurocenter, Neurology, Helsinki University Hospital, Helsinki, Finland,Department of Neurosciences, Clinicum, University of Helsinki, Helsinki, Finland,Department of Physiology, Medicum, University of Helsinki, Helsinki, Finland,*Correspondence: Simo Vanni,
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221
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Brain Data Standards - A method for building data-driven cell-type ontologies. Sci Data 2023; 10:50. [PMID: 36693887 PMCID: PMC9873614 DOI: 10.1038/s41597-022-01886-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 12/06/2022] [Indexed: 01/25/2023] Open
Abstract
Large-scale single-cell 'omics profiling is being used to define a complete catalogue of brain cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem: How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a partial solution to these problems, but no existing ontology schemas support the definition of cell types by direct reference to supporting data, classification of cell types using classifications derived directly from data, or links from cell types to marker sets along with confidence scores. Here we describe a generally applicable schema that solves these problems and its application in a semi-automated pipeline to build a data-linked extension to the Cell Ontology representing cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole-brain atlases currently in preparation.
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222
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Jung M, Dourado M, Maksymetz J, Jacobson A, Laufer BI, Baca M, Foreman O, Hackos DH, Riol-Blanco L, Kaminker JS. Cross-species transcriptomic atlas of dorsal root ganglia reveals species-specific programs for sensory function. Nat Commun 2023; 14:366. [PMID: 36690629 PMCID: PMC9870891 DOI: 10.1038/s41467-023-36014-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 01/12/2023] [Indexed: 01/24/2023] Open
Abstract
Sensory neurons of the dorsal root ganglion (DRG) are critical for maintaining tissue homeostasis by sensing and initiating responses to stimuli. While most preclinical studies of DRGs are conducted in rodents, much less is known about the mechanisms of sensory perception in primates. We generated a transcriptome atlas of mouse, guinea pig, cynomolgus monkey, and human DRGs by implementing a common laboratory workflow and multiple data-integration approaches to generate high-resolution cross-species mappings of sensory neuron subtypes. Using our atlas, we identified conserved core modules highlighting subtype-specific biological processes related to inflammatory response. We also identified divergent expression of key genes involved in DRG function, suggesting species-specific adaptations specifically in nociceptors that likely point to divergent function of nociceptors. Among these, we validated that TAFA4, a member of the druggable genome, was expressed in distinct populations of DRG neurons across species, highlighting species-specific programs that are critical for therapeutic development.
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Affiliation(s)
- Min Jung
- Department of OMNI Bioinformatics, Genentech, Inc., South San Francisco, CA, USA
| | - Michelle Dourado
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA, USA
| | - James Maksymetz
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA, USA
| | - Amanda Jacobson
- Department of Immunology Discovery, Genentech, Inc., South San Francisco, CA, USA
| | - Benjamin I Laufer
- Department of OMNI Bioinformatics, Genentech, Inc., South San Francisco, CA, USA
| | - Miriam Baca
- Department of Pathology, Genentech, Inc., South San Francisco, CA, USA
| | - Oded Foreman
- Department of Pathology, Genentech, Inc., South San Francisco, CA, USA
| | - David H Hackos
- Department of Neuroscience, Genentech, Inc., South San Francisco, CA, USA.
| | - Lorena Riol-Blanco
- Department of Immunology Discovery, Genentech, Inc., South San Francisco, CA, USA.
| | - Joshua S Kaminker
- Department of OMNI Bioinformatics, Genentech, Inc., South San Francisco, CA, USA.
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223
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Yang Y, Booker SA, Clegg JM, Quintana-Urzainqui I, Sumera A, Kozic Z, Dando O, Martin Lorenzo S, Herault Y, Kind PC, Price DJ, Pratt T. Identifying foetal forebrain interneurons as a target for monogenic autism risk factors and the polygenic 16p11.2 microdeletion. BMC Neurosci 2023; 24:5. [PMID: 36658491 PMCID: PMC9850541 DOI: 10.1186/s12868-022-00771-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/21/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Autism spectrum condition or 'autism' is associated with numerous genetic risk factors including the polygenic 16p11.2 microdeletion. The balance between excitatory and inhibitory neurons in the cerebral cortex is hypothesised to be critical for the aetiology of autism making improved understanding of how risk factors impact on the development of these cells an important area of research. In the current study we aim to combine bioinformatics analysis of human foetal cerebral cortex gene expression data with anatomical and electrophysiological analysis of a 16p11.2+/- rat model to investigate how genetic risk factors impact on inhibitory neuron development. METHODS We performed bioinformatics analysis of single cell transcriptomes from gestational week (GW) 8-26 human foetal prefrontal cortex and anatomical and electrophysiological analysis of 16p11.2+/- rat cerebral cortex and hippocampus at post-natal day (P) 21. RESULTS We identified a subset of human interneurons (INs) first appearing at GW23 with enriched expression of a large fraction of risk factor transcripts including those expressed from the 16p11.2 locus. This suggests the hypothesis that these foetal INs are vulnerable to mutations causing autism. We investigated this in a rat model of the 16p11.2 microdeletion. We found no change in the numbers or position of either excitatory or inhibitory neurons in the somatosensory cortex or CA1 of 16p11.2+/- rats but found that CA1 Sst INs were hyperexcitable with an enlarged axon initial segment, which was not the case for CA1 pyramidal cells. LIMITATIONS The human foetal gene expression data was acquired from cerebral cortex between gestational week (GW) 8 to 26. We cannot draw inferences about potential vulnerabilities to genetic autism risk factors for cells not present in the developing cerebral cortex at these stages. The analysis 16p11.2+/- rat phenotypes reported in the current study was restricted to 3-week old (P21) animals around the time of weaning and to a single interneuron cell-type while in human 16p11.2 microdeletion carriers symptoms likely involve multiple cell types and manifest in the first few years of life and on into adulthood. CONCLUSIONS We have identified developing interneurons in human foetal cerebral cortex as potentially vulnerable to monogenic autism risk factors and the 16p11.2 microdeletion and report interneuron phenotypes in post-natal 16p11.2+/- rats.
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Affiliation(s)
- Yifei Yang
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Department of Brain Sciences, Imperial College London, London, W12 0NN, United Kingdom
| | - Sam A Booker
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - James M Clegg
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - Idoia Quintana-Urzainqui
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Developmental Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69012, Heidelberg, Germany
| | - Anna Sumera
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - Zrinko Kozic
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - Owen Dando
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - Sandra Martin Lorenzo
- CNRS, Université de Strasbourg, INSERM, Institut de Génétique et de Biologie Moléculaire et Cellulaire, IGBMC, 1 rue Laurent Fries, 67404, Illkirch, France
| | - Yann Herault
- CNRS, Université de Strasbourg, INSERM, Institut de Génétique et de Biologie Moléculaire et Cellulaire, IGBMC, 1 rue Laurent Fries, 67404, Illkirch, France
| | - Peter C Kind
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - David J Price
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom
| | - Thomas Pratt
- Simons Initiative for the Developing Brain, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom. .,Centre for Discovery Brain Sciences, The University of Edinburgh, 15 George Square, Edinburgh, EH8 9XD, United Kingdom.
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224
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Ament SA, Adkins RS, Carter R, Chrysostomou E, Colantuoni C, Crabtree J, Creasy HH, Degatano K, Felix V, Gandt P, Garden G, Giglio M, Herb BR, Khajouei F, Kiernan E, McCracken C, McDaniel K, Nadendla S, Nickel L, Olley D, Orvis J, Receveur J, Schor M, Sonthalia S, Tickle T, Way J, Hertzano R, Mahurkar A, White O. The Neuroscience Multi-Omic Archive: a BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain. Nucleic Acids Res 2023; 51:D1075-D1085. [PMID: 36318260 PMCID: PMC9825473 DOI: 10.1093/nar/gkac962] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/30/2022] [Accepted: 10/27/2022] [Indexed: 11/06/2022] Open
Abstract
Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org).
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Affiliation(s)
- Seth A Ament
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ricky S Adkins
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Robert Carter
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Elena Chrysostomou
- Department of Otorhinolaryngology Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Carlo Colantuoni
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Departments of Neurology and Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jonathan Crabtree
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Heather H Creasy
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kylee Degatano
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Victor Felix
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Peter Gandt
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Gwenn A Garden
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michelle Giglio
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Brian R Herb
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Farzaneh Khajouei
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elizabeth Kiernan
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Carrie McCracken
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kennedy McDaniel
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Suvarna Nadendla
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lance Nickel
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dustin Olley
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Orvis
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joseph P Receveur
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mike Schor
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shreyash Sonthalia
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Timothy L Tickle
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jessica Way
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ronna Hertzano
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Otorhinolaryngology Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Anup A Mahurkar
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Owen R White
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
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225
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Mobility Coupled with Motivation Promotes Survival: The Evolution of Cognition as an Adaptive Strategy. BIOLOGY 2023; 12:biology12010080. [PMID: 36671772 PMCID: PMC9855669 DOI: 10.3390/biology12010080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 12/28/2022] [Accepted: 12/30/2022] [Indexed: 01/06/2023]
Abstract
Morphine plays a critical regulatory role in both simple and complex plant species. Dopamine is a critical chemical intermediate in the morphine biosynthetic pathway and may have served as a primordial agonist in developing catecholamine signaling pathways. While dopamine remains the preeminent catecholamine in invertebrate neural systems, epinephrine is the major product of catecholamine synthetic pathways in vertebrate species. Given that the enzymatic steps leading to the generation of morphine are similar to those constraining the evolutionary adaptation of the biosynthesis of catecholamines, we hypothesize that the emergence of these more advanced signaling pathways was based on conservation and selective "retrofitting" of pre-existing enzyme activities. This is consistent with observations that support the recruitment of enzymatically synthesized tetrahydrobiopterin (BH4), which is a cofactor for tyrosine hydroxylase, the enzyme responsible for dopamine production. BH4 is also an electron donor involved in the production of nitric oxide (NO). The links that coordinate BH4-mediated NO and catecholaminergic-mediated processes provide these systems with the capacity to regulate numerous downstream signaling pathways. We hypothesize that the evolution of catecholamine signaling pathways in animal species depends on the acquisition of a mobile lifestyle and motivationally driven feeding, sexual, and self-protective responses.
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226
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Neurodevelopmental disorders-high-resolution rethinking of disease modeling. Mol Psychiatry 2023; 28:34-43. [PMID: 36434058 PMCID: PMC9812768 DOI: 10.1038/s41380-022-01876-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/06/2022] [Accepted: 11/07/2022] [Indexed: 11/27/2022]
Abstract
Neurodevelopmental disorders arise due to various risk factors that can perturb different stages of brain development, and a combinatorial impact of these risk factors programs the phenotype in adulthood. While modeling the complete phenotype of a neurodevelopmental disorder is challenging, individual developmental perturbations can be successfully modeled in vivo in animals and in vitro in human cellular models. Nevertheless, our limited knowledge of human brain development restricts modeling strategies and has raised questions of how well a model corresponds to human in vivo brain development. Recent progress in high-resolution analysis of human tissue with single-cell and spatial omics techniques has enhanced our understanding of the complex events that govern the development of the human brain in health and disease. This new knowledge can be utilized to improve modeling of neurodevelopmental disorders and pave the way to more accurately portraying the relevant developmental perturbations in disease models.
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227
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Palmer CR, Chun J. Extraction and Purification of Single Nuclei from Frozen Human Brain Tissue. Methods Mol Biol 2023; 2561:31-42. [PMID: 36399263 DOI: 10.1007/978-1-0716-2655-9_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] [Indexed: 06/16/2023]
Abstract
Resolving the complexity of the human brain at the level of single cells is essential to gaining an understanding of the immense diversity of cell types and functional states in both healthy and diseased brains. To exploit fully the technologies available for such studies, one must extract and isolate pure nuclei from unfixed postmortem tissue while preserving the molecules to be interrogated. Currently, nuclei are necessary substitutes for individual brain cells, since myriad cell types/sub-types constituting the human brain are embedded within the neuropil-a complex milieu of interconnected cells, processes, and synapses-which precludes intact and selective isolation of single brain cells. Here, we describe a protocol for the extraction and purification of intact single nuclei from frozen human brain tissue along with modifications to accommodate numerous downstream analyses, particularly for transcriptomic applications.
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Affiliation(s)
- Carter R Palmer
- Translational Neuroscience Initiative, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA
- Biomedical Sciences Program, School of Medicine, La Jolla, CA, USA
| | - Jerold Chun
- Translational Neuroscience Initiative, Neuroscience Drug Discovery, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
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228
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Xing Y, Zan C, Liu L. Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing. Front Neural Circuits 2023; 17:1007755. [PMID: 37063385 PMCID: PMC10097998 DOI: 10.3389/fncir.2023.1007755] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 02/16/2023] [Indexed: 04/18/2023] Open
Abstract
Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.
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Affiliation(s)
- Yu Xing
- Department of Neurology, Beidahuang Industry Group General Hospital, Harbin, China
| | - Chunfang Zan
- Institute for Stroke and Dementia Research (ISD), LMU Klinikum, Ludwig-Maximilian-University (LMU), Munich, Germany
| | - Lu Liu
- Munich Medical Research School (MMRS), LMU Klinikum, Ludwig-Maximilian-University (LMU), Munich, Germany
- *Correspondence: Lu Liu, ,
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229
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Murat F, Mbengue N, Winge SB, Trefzer T, Leushkin E, Sepp M, Cardoso-Moreira M, Schmidt J, Schneider C, Mößinger K, Brüning T, Lamanna F, Belles MR, Conrad C, Kondova I, Bontrop R, Behr R, Khaitovich P, Pääbo S, Marques-Bonet T, Grützner F, Almstrup K, Schierup MH, Kaessmann H. The molecular evolution of spermatogenesis across mammals. Nature 2023; 613:308-316. [PMID: 36544022 PMCID: PMC9834047 DOI: 10.1038/s41586-022-05547-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 11/09/2022] [Indexed: 12/24/2022]
Abstract
The testis produces gametes through spermatogenesis and evolves rapidly at both the morphological and molecular level in mammals1-6, probably owing to the evolutionary pressure on males to be reproductively successful7. However, the molecular evolution of individual spermatogenic cell types across mammals remains largely uncharacterized. Here we report evolutionary analyses of single-nucleus transcriptome data for testes from 11 species that cover the three main mammalian lineages (eutherians, marsupials and monotremes) and birds (the evolutionary outgroup), and include seven primates. We find that the rapid evolution of the testis was driven by accelerated fixation rates of gene expression changes, amino acid substitutions and new genes in late spermatogenic stages, probably facilitated by reduced pleiotropic constraints, haploid selection and transcriptionally permissive chromatin. We identify temporal expression changes of individual genes across species and conserved expression programs controlling ancestral spermatogenic processes. Genes predominantly expressed in spermatogonia (germ cells fuelling spermatogenesis) and Sertoli (somatic support) cells accumulated on X chromosomes during evolution, presumably owing to male-beneficial selective forces. Further work identified transcriptomal differences between X- and Y-bearing spermatids and uncovered that meiotic sex-chromosome inactivation (MSCI) also occurs in monotremes and hence is common to mammalian sex-chromosome systems. Thus, the mechanism of meiotic silencing of unsynapsed chromatin, which underlies MSCI, is an ancestral mammalian feature. Our study illuminates the molecular evolution of spermatogenesis and associated selective forces, and provides a resource for investigating the biology of the testis across mammals.
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Affiliation(s)
- Florent Murat
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany. .,INRAE, LPGP, Rennes, France.
| | - Noe Mbengue
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany.
| | - Sofia Boeg Winge
- Department of Growth and Reproduction, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Timo Trefzer
- Berlin Institute of Health at Charité, University of Medicine Berlin, Corporate Member of the Free University of Berlin, Humboldt-University of Berlin, Berlin, Germany
| | - Evgeny Leushkin
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | - Mari Sepp
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | | | - Julia Schmidt
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | - Celine Schneider
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | - Katharina Mößinger
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | - Thoomke Brüning
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | - Francesco Lamanna
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany
| | | | - Christian Conrad
- Berlin Institute of Health at Charité, University of Medicine Berlin, Corporate Member of the Free University of Berlin, Humboldt-University of Berlin, Berlin, Germany
| | - Ivanela Kondova
- Biomedical Primate Research Center (BPRC), Rijswijk, the Netherlands
| | - Ronald Bontrop
- Biomedical Primate Research Center (BPRC), Rijswijk, the Netherlands
| | - Rüdiger Behr
- German Primate Center (DPZ), Platform Degenerative Diseases, Göttingen, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Göttingen, Göttingen, Germany
| | - Philipp Khaitovich
- Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Svante Pääbo
- Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), Barcelona, Spain.,Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain.,CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Miquel Crusafont Catalan Institute of Paleontology, Autonomous University of Barcelona, Barcelona, Spain
| | - Frank Grützner
- The Robinson Research Institute, School of Biological Science, University of Adelaide, Adelaide, South Australia, Australia
| | - Kristian Almstrup
- Department of Growth and Reproduction, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,International Center for Research and Research Training in Endocrine Disruption of Male Reproduction and Child Health, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Henrik Kaessmann
- Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Heidelberg, Germany.
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230
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Preissl S, Gaulton KJ, Ren B. Characterizing cis-regulatory elements using single-cell epigenomics. Nat Rev Genet 2023; 24:21-43. [PMID: 35840754 PMCID: PMC9771884 DOI: 10.1038/s41576-022-00509-1] [Citation(s) in RCA: 65] [Impact Index Per Article: 65.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2022] [Indexed: 12/24/2022]
Abstract
Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.
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Affiliation(s)
- 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.
| | - Kyle J Gaulton
- Department of Paediatrics, Paediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
| | - Bing Ren
- 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.
- Ludwig Institute for Cancer Research, La Jolla, CA, USA.
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231
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Caglayan E, Liu Y, Konopka G. Neuronal ambient RNA contamination causes misinterpreted and masked cell types in brain single-nuclei datasets. Neuron 2022; 110:4043-4056.e5. [PMID: 36240767 PMCID: PMC9789184 DOI: 10.1016/j.neuron.2022.09.010] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/20/2022] [Accepted: 09/08/2022] [Indexed: 12/31/2022]
Abstract
Ambient RNA contamination in single-cell and single-nuclei RNA sequencing (snRNA-seq) is a significant problem, but its consequences are poorly understood. Here, we show that ambient RNAs in brain snRNA-seq datasets have a nuclear or non-nuclear origin with distinct gene set signatures. Both ambient RNA signatures are predominantly neuronal, and we find that some previously annotated neuronal cell types are distinguished by ambient RNA contamination. We detect pervasive neuronal ambient RNA contamination in all glial cell types unless glia and neurons are physically separated prior to sequencing. We demonstrate that this contamination can be removed in silico and show that previous single-nuclei RNA-seq-based annotations of immature oligodendrocytes are glial nuclei contaminated with ambient RNAs. After ambient RNA removal, we detect rare, committed oligodendrocyte progenitor cells not annotated in most previous adult human brain datasets. Together, these results provide an in-depth analysis of ambient RNA contamination in brain single-nuclei datasets.
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Affiliation(s)
- Emre Caglayan
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX 75390, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.
| | - Yuxiang Liu
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX 75390, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX 75390, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX 75390, USA.
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232
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Fischer S, Gillis J. Defining the extent of gene function using ROC curvature. Bioinformatics 2022; 38:5390-5397. [PMID: 36271855 PMCID: PMC9750128 DOI: 10.1093/bioinformatics/btac692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 09/19/2022] [Accepted: 10/20/2022] [Indexed: 12/25/2022] Open
Abstract
MOTIVATION Interactions between proteins help us understand how genes are functionally related and how they contribute to phenotypes. Experiments provide imperfect 'ground truth' information about a small subset of potential interactions in a specific biological context, which can then be extended to the whole genome across different contexts, such as conditions, tissues or species, through machine learning methods. However, evaluating the performance of these methods remains a critical challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves. RESULTS We identify Functional Equivalence Classes (FECs), subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves built from gene-centric prediction tasks, such as function or interaction predictions. FECs are widespread across data types and methods, they can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10-50 genes), and tissue-specific secondary markers (100-500 genes). In addition, FECs suggest the existence of functional modules that span a wide range of the genome, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in the definition of functional gene sets. AVAILABILITY AND IMPLEMENTATION Code for analyses and figures is available at https://github.com/yexilein/pyroc. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Stephan Fischer
- Cold Spring Harbor Laboratory, Stanley Institute for Cognitive Genomics, Cold Spring Harbor, NY 11724, USA
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris F-75015, France
| | - Jesse Gillis
- Cold Spring Harbor Laboratory, Stanley Institute for Cognitive Genomics, Cold Spring Harbor, NY 11724, USA
- Department of Physiology, University of Toronto, Toronto, ON, Canada
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233
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Chiou KL, DeCasien AR, Rees KP, Testard C, Spurrell CH, Gogate AA, Pliner HA, Tremblay S, Mercer A, Whalen CJ, Negrón-Del Valle JE, Janiak MC, Bauman Surratt SE, González O, Compo NR, Stock MK, Ruiz-Lambides AV, Martínez MI, Wilson MA, Melin AD, Antón SC, Walker CS, Sallet J, Newbern JM, Starita LM, Shendure J, Higham JP, Brent LJN, Montague MJ, Platt ML, Snyder-Mackler N. Multiregion transcriptomic profiling of the primate brain reveals signatures of aging and the social environment. Nat Neurosci 2022; 25:1714-1723. [PMID: 36424430 PMCID: PMC10055353 DOI: 10.1038/s41593-022-01197-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 10/05/2022] [Indexed: 11/26/2022]
Abstract
Aging is accompanied by a host of social and biological changes that correlate with behavior, cognitive health and susceptibility to neurodegenerative disease. To understand trajectories of brain aging in a primate, we generated a multiregion bulk (N = 527 samples) and single-nucleus (N = 24 samples) brain transcriptional dataset encompassing 15 brain regions and both sexes in a unique population of free-ranging, behaviorally phenotyped rhesus macaques. We demonstrate that age-related changes in the level and variance of gene expression occur in genes associated with neural functions and neurological diseases, including Alzheimer's disease. Further, we show that higher social status in females is associated with younger relative transcriptional ages, providing a link between the social environment and aging in the brain. Our findings lend insight into biological mechanisms underlying brain aging in a nonhuman primate model of human behavior, cognition and health.
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Affiliation(s)
- Kenneth L Chiou
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.
- School of Life Sciences, Arizona State University, Tempe, AZ, USA.
- Department of Psychology, University of Washington, Seattle, WA, USA.
- Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA, USA.
| | - Alex R DeCasien
- Department of Anthropology, New York University, New York, NY, USA.
- New York Consortium in Evolutionary Primatology, New York, NY, USA.
| | - Katherina P Rees
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Camille Testard
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Aishwarya A Gogate
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
| | - Hannah A Pliner
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Sébastien Tremblay
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Arianne Mercer
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Connor J Whalen
- Department of Anthropology, New York University, New York, NY, USA
| | | | - Mareike C Janiak
- School of Science, Engineering, & Environment, University of Salford, Salford, UK
| | | | - Olga González
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Nicole R Compo
- Caribbean Primate Research Center, University of Puerto Rico, San Juan, PR, USA
| | - Michala K Stock
- Department of Sociology and Anthropology, Metropolitan State University of Denver, Denver, CO, USA
| | | | - Melween I Martínez
- Caribbean Primate Research Center, University of Puerto Rico, San Juan, PR, USA
| | - Melissa A Wilson
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Amanda D Melin
- Department of Anthropology and Archaeology, University of Calgary, Calgary, Alberta, Canada
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Susan C Antón
- Department of Anthropology, New York University, New York, NY, USA
- New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - Christopher S Walker
- Department of Molecular Biomedical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, USA
| | - Jérôme Sallet
- Stem Cell and Brain Research Institute, Université Lyon, Lyon, France
| | - Jason M Newbern
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
| | - James P Higham
- Department of Anthropology, New York University, New York, NY, USA
- New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - Lauren J N Brent
- Centre for Research in Animal Behaviour, University of Exeter, Exeter, UK
| | - Michael J Montague
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael L Platt
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
- Marketing Department, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Noah Snyder-Mackler
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.
- School of Life Sciences, Arizona State University, Tempe, AZ, USA.
- Department of Psychology, University of Washington, Seattle, WA, USA.
- Nathan Shock Center of Excellence in the Basic Biology of Aging, University of Washington, Seattle, WA, USA.
- Center for Studies in Demography & Ecology, University of Washington, Seattle, WA, USA.
- ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ, USA.
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA.
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234
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Molecular and spatial heterogeneity of microglia in Rasmussen encephalitis. Acta Neuropathol Commun 2022; 10:168. [PMID: 36411471 PMCID: PMC9677917 DOI: 10.1186/s40478-022-01472-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/02/2022] [Indexed: 11/22/2022] Open
Abstract
Rasmussen encephalitis (RE) is a rare childhood neurological disease characterized by progressive unilateral loss of function, hemispheric atrophy and drug-resistant epilepsy. Affected brain tissue shows signs of infiltrating cytotoxic T-cells, microglial activation, and neuronal death, implicating an inflammatory disease process. Recent studies have identified molecular correlates of inflammation in RE, but cell-type-specific mechanisms remain unclear. We used single-nucleus RNA-sequencing (snRNA-seq) to assess gene expression across multiple cell types in brain tissue resected from two children with RE. We found transcriptionally distinct microglial populations enriched in RE compared to two age-matched individuals with unaffected brain tissue and two individuals with Type I focal cortical dysplasia (FCD). Specifically, microglia in RE tissues demonstrated increased expression of genes associated with cytokine signaling, interferon-mediated pathways, and T-cell activation. We extended these findings using spatial proteomic analysis of tissue from four surgical resections to examine expression profiles of microglia within their pathological context. Microglia that were spatially aggregated into nodules had increased expression of dynamic immune regulatory markers (PD-L1, CD14, CD11c), T-cell activation markers (CD40, CD80) and were physically located near distinct CD4+ and CD8+ lymphocyte populations. These findings help elucidate the complex immune microenvironment of RE.
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235
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Um S, Zhang B, Wattal S, Yoo Y. Software Components and Product Variety in a Platform Ecosystem: A Dynamic Network Analysis of WordPress. INFORMATION SYSTEMS RESEARCH 2022. [DOI: 10.1287/isre.2022.1172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Software components such as application programming interfaces (APIs) provided by external developers are vital to online digital platforms. Although APIs generally increase the variety of products according to anecdote, the precise relationship between the categories of APIs and product variety is not yet known. We find that APIs, regarding their use frequency, are categorized into three groups. The core is a group of frequently used APIs, whereas the periphery is a group of sparsely used APIs. In a large and mature platform ecosystem, an additional group of APIs, the regular core, mainly provided by third-party developers, emerges. APIs in the regular core are the main driver of product variety. However, we also find that the strength of this effect diminishes in a newly created product category when most of the new products are built by duplicating the usage of APIs from other products. A platform owner can stimulate developers’ creativity by acting as a bridge between digital product providers and third-party developers. It can collect functional needs from third-party developers and then share them with product providers. Therefore, the latter can build APIs that developers need.
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Affiliation(s)
- Sungyong Um
- Department of Information Systems and Analytics, School of Computing, National University of Singapore, Singapore 119391, Singapore
| | - Bin Zhang
- Department of Information and Operations Management, Mays Business School, Texas A&M University, College Station, Texas 77843
| | - Sunil Wattal
- Department of Management Information Systems, Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122
| | - Youngjin Yoo
- Department of Design and Innovation, Weatherhead School of Management, Case Western Reserve University, Cleveland, Ohio 44106
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236
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Tissue dissociation for single-cell and single-nuclei RNA sequencing for low amounts of input material. Front Zool 2022; 19:27. [DOI: 10.1186/s12983-022-00472-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 10/27/2022] [Indexed: 11/15/2022] Open
Abstract
Abstract
Background
Recent technological advances opened the opportunity to simultaneously study gene expression for thousands of individual cells on a genome-wide scale. The experimental accessibility of such single-cell RNA sequencing (scRNAseq) approaches allowed gaining insights into the cell type composition of heterogeneous tissue samples of animal model systems and emerging models alike. A major prerequisite for a successful application of the method is the dissociation of complex tissues into individual cells, which often requires large amounts of input material and harsh mechanical, chemical and temperature conditions. However, the availability of tissue material may be limited for small animals, specific organs, certain developmental stages or if samples need to be acquired from collected specimens. Therefore, we evaluated different dissociation protocols to obtain single cells from small tissue samples of Drosophila melanogaster eye-antennal imaginal discs.
Results
We show that a combination of mechanical and chemical dissociation resulted in sufficient high-quality cells. As an alternative, we tested protocols for the isolation of single nuclei, which turned out to be highly efficient for fresh and frozen tissue samples. Eventually, we performed scRNAseq and single-nuclei RNA sequencing (snRNAseq) to show that the best protocols for both methods successfully identified relevant cell types. At the same time, snRNAseq resulted in less artificial gene expression that is caused by rather harsh dissociation conditions needed to obtain single cells for scRNAseq. A direct comparison of scRNAseq and snRNAseq data revealed that both datasets share biologically relevant genes among the most variable genes, and we showed differences in the relative contribution of the two approaches to identified cell types.
Conclusion
We present two dissociation protocols that allow isolating single cells and single nuclei, respectively, from low input material. Both protocols resulted in extraction of high-quality RNA for subsequent scRNAseq or snRNAseq applications. If tissue availability is limited, we recommend the snRNAseq procedure of fresh or frozen tissue samples as it is perfectly suited to obtain thorough insights into cellular diversity of complex tissue.
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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: 11] [Impact Index Per Article: 5.5] [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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238
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Wang S, Ding P, Yuan J, Wang H, Zhang X, Chen D, Ma D, Zhang X, Wang F. Integrative cross-species analysis of GABAergic neuron cell types and their functions in Alzheimer's disease. Sci Rep 2022; 12:19358. [PMID: 36369318 PMCID: PMC9652313 DOI: 10.1038/s41598-022-21496-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 09/28/2022] [Indexed: 11/13/2022] Open
Abstract
Understanding the phenotypic and functional diversity of cerebral cortical GABAergic neurons requires a comprehensive analysis of key transcriptional signatures and neuronal subtype identity. However, the diversity and conservation of GABAergic neurons across multiple mammals remain unclear. Here, we collected the single-nucleus RNA sequencing (snRNA-seq) datasets of cerebral cortex from human, macaque, mouse, and pig to identify the conserved neuronal cell types across species. After systematic analysis of the heterogeneity of GABAergic neurons, we defined four major conserved GABAergic neuron subclasses (Inc SST, Inc LAMP5, Inc PVALB, and Inc VIP) across species. We characterized the species-enriched subclasses of GABAergic neurons from four mammals, such as Inc Meis2 in mouse. Then, we depicted the genetic regulatory network (GRNs) of GABAergic neuron subclasses, which showed the conserved and species-specific GRNs for GABAergic neuron cell types. Finally, we investigated the GABAergic neuron subclass-specific expression modules of Alzheimer's disease (AD)-related genes in GABAergic neuron cell types. Overall, our study reveals the conserved and divergent GABAergic neuron subclasses and GRNs across multiple species and unravels the gene expression modules of AD-risk genes in GABAergic neuron subclasses, facilitating the GABAergic neurons research and clinical treatment.
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Affiliation(s)
- Shiyou Wang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Peiwen Ding
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Jingnan Yuan
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Haoyu Wang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Xiuqing Zhang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Dongli Ma
- Department of Respiratory Diseases, Institute of Pediatrics, Shenzhen Children's Hospital, Shenzhen, 518038, China
| | - Xingliang Zhang
- Department of Respiratory Diseases, Institute of Pediatrics, Shenzhen Children's Hospital, Shenzhen, 518038, China.
- Department of Pediatrics, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524001, China.
| | - Fei Wang
- BGI-Shenzhen, Shenzhen, 518083, China.
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
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239
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Wallace MN, Zobay O, Hardman E, Thompson Z, Dobbs P, Chakrabarti L, Palmer AR. The large numbers of minicolumns in the primary visual cortex of humans, chimpanzees and gorillas are related to high visual acuity. Front Neuroanat 2022; 16:1034264. [PMID: 36439196 PMCID: PMC9681811 DOI: 10.3389/fnana.2022.1034264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/21/2022] [Indexed: 11/10/2022] Open
Abstract
Minicolumns are thought to be a fundamental neural unit in the neocortex and their replication may have formed the basis of the rapid cortical expansion that occurred during primate evolution. We sought evidence of minicolumns in the primary visual cortex (V-1) of three great apes, three rodents and representatives from three other mammalian orders: Eulipotyphla (European hedgehog), Artiodactyla (domestic pig) and Carnivora (ferret). Minicolumns, identified by the presence of a long bundle of radial, myelinated fibers stretching from layer III to the white matter of silver-stained sections, were found in the human, chimpanzee, gorilla and guinea pig V-1. Shorter bundles confined to one or two layers were found in the other species but represent modules rather than minicolumns. The inter-bundle distance, and hence density of minicolumns, varied systematically both within a local area that might represent a hypercolumn but also across the whole visual field. The distance between all bundles had a similar range for human, chimpanzee, gorilla, ferret and guinea pig: most bundles were 20-45 μm apart. By contrast, the space between bundles was greater for the hedgehog and pig (20-140 μm). The mean density of minicolumns was greater in tangential sections of the gorilla and chimpanzee (1,243-1,287 bundles/mm2) than in human (314-422 bundles/mm2) or guinea pig (643 bundles/mm2). The minicolumnar bundles did not form a hexagonal lattice but were arranged in thin curving and branched bands separated by thicker bands of neuropil/somata. Estimates of the total number of modules/minicolumns within V-1 were strongly correlated with visual acuity.
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Affiliation(s)
- Mark N. Wallace
- Medical Research Council (MRC) Institute of Hearing Research, University Park, Nottingham, United Kingdom
- Hearing Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Oliver Zobay
- Medical Research Council (MRC) Institute of Hearing Research, University Park, Nottingham, United Kingdom
- School of Medicine, University of Nottingham, Hearing Sciences—Scottish Section, Glasgow Royal Infirmary, Glasgow, United Kingdom
| | - Eden Hardman
- Medical Research Council (MRC) Institute of Hearing Research, University Park, Nottingham, United Kingdom
| | - Zoe Thompson
- Medical Research Council (MRC) Institute of Hearing Research, University Park, Nottingham, United Kingdom
| | - Phillipa Dobbs
- Veterinary Department, Twycross Zoo, East Midland Zoological Society, Atherstone, United Kingdom
| | - Lisa Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Nottingham, United Kingdom
| | - Alan R. Palmer
- Medical Research Council (MRC) Institute of Hearing Research, University Park, Nottingham, United Kingdom
- Hearing Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
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240
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Hogeveen J, Medalla M, Ainsworth M, Galeazzi JM, Hanlon CA, Mansouri FA, Costa VD. What Does the Frontopolar Cortex Contribute to Goal-Directed Cognition and Action? J Neurosci 2022; 42:8508-8513. [PMID: 36351824 PMCID: PMC9665930 DOI: 10.1523/jneurosci.1143-22.2022] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/30/2022] [Accepted: 08/31/2022] [Indexed: 11/17/2022] Open
Abstract
Understanding the unique functions of different subregions of primate prefrontal cortex has been a longstanding goal in cognitive neuroscience. Yet, the anatomy and function of one of its largest subregions (the frontopolar cortex) remain enigmatic and underspecified. Our Society for Neuroscience minisymposium Primate Frontopolar Cortex: From Circuits to Complex Behaviors will comprise a range of new anatomic and functional approaches that have helped to clarify the basic circuit anatomy of the frontal pole, its functional involvement during performance of cognitively demanding behavioral paradigms in monkeys and humans, and its clinical potential as a target for noninvasive brain stimulation in patients with brain disorders. This review consolidates knowledge about the anatomy and connectivity of frontopolar cortex and provides an integrative summary of its function in primates. We aim to answer the question: what, if anything, does frontopolar cortex contribute to goal-directed cognition and action?
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Affiliation(s)
- Jeremy Hogeveen
- Department of Psychology & Psychology Clinical Neuroscience Center, University of New Mexico, Albuquerque, NM 87131
| | - Maria Medalla
- Department of Anatomy & Neurobiology, Boston University, Boston, MA 02118
| | - Matthew Ainsworth
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
| | - Juan M Galeazzi
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
| | - Colleen A Hanlon
- Department of Cancer Biology
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC 27101
| | - Farshad Alizadeh Mansouri
- Department of Physiology, Monash Biomedicine Discovery Institute, Clayton Victoria, 3800, Australia
- ARC Centre for Integrative Brain Function, Monash University, Clayton Victoria, 3800, Australia
| | - Vincent D Costa
- Division of Neuroscience, Oregon National Primate Research Center, Beaverton, OR 97006
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241
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Spatially resolved gene regulatory and disease-related vulnerability map of the adult Macaque cortex. Nat Commun 2022; 13:6747. [PMID: 36347848 PMCID: PMC9643508 DOI: 10.1038/s41467-022-34413-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 10/24/2022] [Indexed: 11/09/2022] Open
Abstract
Single cell approaches have increased our knowledge about the cell type composition of the non-human primate (NHP), but a detailed characterization of area-specific regulatory features remains outstanding. We generated single-cell transcriptomic and chromatin accessibility (single-cell ATAC) data of 358,237 cells from prefrontal cortex (PFC), primary motor cortex (M1) and primary visual cortex (V1) of adult female cynomolgus monkey brain, and integrated this dataset with Stereo-seq (spatial enhanced resolution omics-sequencing) of the corresponding cortical areas to assign topographic information to molecular states. We identified area-specific chromatin accessible sites and their targeted genes, including the cell type-specific transcriptional regulatory network associated with excitatory neurons heterogeneity. We reveal calcium ion transport and axon guidance genes related to specialized functions of PFC and M1, identified the similarities and differences between adult macaque and human oligodendrocyte trajectories, and mapped the genetic variants and gene perturbations of human diseases to NHP cortical cells. This resource establishes a transcriptomic and chromatin accessibility combinatory regulatory landscape at a single-cell and spatially resolved resolution in NHP cortex.
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242
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Galakhova AA, Hunt S, Wilbers R, Heyer DB, de Kock CPJ, Mansvelder HD, Goriounova NA. Evolution of cortical neurons supporting human cognition. Trends Cogn Sci 2022; 26:909-922. [PMID: 36117080 PMCID: PMC9561064 DOI: 10.1016/j.tics.2022.08.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 08/18/2022] [Accepted: 08/24/2022] [Indexed: 01/12/2023]
Abstract
Human cognitive abilities are generally thought to arise from cortical expansion over the course of human brain evolution. In addition to increased neuron numbers, this cortical expansion might be driven by adaptations in the properties of single neurons and their local circuits. We review recent findings on the distinct structural, functional, and transcriptomic features of human cortical neurons and their organization in cortical microstructure. We focus on the supragranular cortical layers, which showed the most prominent expansion during human brain evolution, and the properties of their principal cells: pyramidal neurons. We argue that the evolutionary adaptations in neuronal features that accompany the expansion of the human cortex partially underlie interindividual variability in human cognitive abilities.
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Affiliation(s)
- A A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - S Hunt
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - R Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - D B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - C P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - H D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - N A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands.
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243
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Roberts RJV, Pop S, Prieto-Godino LL. Evolution of central neural circuits: state of the art and perspectives. Nat Rev Neurosci 2022; 23:725-743. [DOI: 10.1038/s41583-022-00644-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/22/2022] [Indexed: 11/09/2022]
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244
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Verkest C, Salinas M, Diochot S, Deval E, Lingueglia E, Baron A. Mechanisms of Action of the Peptide Toxins Targeting Human and Rodent Acid-Sensing Ion Channels and Relevance to Their In Vivo Analgesic Effects. Toxins (Basel) 2022; 14:toxins14100709. [PMID: 36287977 PMCID: PMC9612379 DOI: 10.3390/toxins14100709] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/30/2022] [Accepted: 10/02/2022] [Indexed: 11/16/2022] Open
Abstract
Acid-sensing ion channels (ASICs) are voltage-independent H+-gated cation channels largely expressed in the nervous system of rodents and humans. At least six isoforms (ASIC1a, 1b, 2a, 2b, 3 and 4) associate into homotrimers or heterotrimers to form functional channels with highly pH-dependent gating properties. This review provides an update on the pharmacological profiles of animal peptide toxins targeting ASICs, including PcTx1 from tarantula and related spider toxins, APETx2 and APETx-like peptides from sea anemone, and mambalgin from snake, as well as the dimeric protein snake toxin MitTx that have all been instrumental to understanding the structure and the pH-dependent gating of rodent and human cloned ASICs and to study the physiological and pathological roles of native ASICs in vitro and in vivo. ASICs are expressed all along the pain pathways and the pharmacological data clearly support a role for these channels in pain. ASIC-targeting peptide toxins interfere with ASIC gating by complex and pH-dependent mechanisms sometimes leading to opposite effects. However, these dual pH-dependent effects of ASIC-inhibiting toxins (PcTx1, mambalgin and APETx2) are fully compatible with, and even support, their analgesic effects in vivo, both in the central and the peripheral nervous system, as well as potential effects in humans.
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Affiliation(s)
- Clément Verkest
- CNRS (Centre National de la Recherche Scientifique), IPMC (Institut de Pharmacologie Moléculaire et Cellulaire), LabEx ICST (Laboratory of Excellence in Ion Channel Science and Therapeutics), FHU InovPain (Fédération Hospitalo-Universitaire “Innovative Solutions in Refractory Chronic Pain”), Université Côte d’Azur, 660 Route des Lucioles, Sophia-Antipolis, 06560 Nice, France
- Department of Anesthesiology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Miguel Salinas
- CNRS (Centre National de la Recherche Scientifique), IPMC (Institut de Pharmacologie Moléculaire et Cellulaire), LabEx ICST (Laboratory of Excellence in Ion Channel Science and Therapeutics), FHU InovPain (Fédération Hospitalo-Universitaire “Innovative Solutions in Refractory Chronic Pain”), Université Côte d’Azur, 660 Route des Lucioles, Sophia-Antipolis, 06560 Nice, France
| | - Sylvie Diochot
- CNRS (Centre National de la Recherche Scientifique), IPMC (Institut de Pharmacologie Moléculaire et Cellulaire), LabEx ICST (Laboratory of Excellence in Ion Channel Science and Therapeutics), FHU InovPain (Fédération Hospitalo-Universitaire “Innovative Solutions in Refractory Chronic Pain”), Université Côte d’Azur, 660 Route des Lucioles, Sophia-Antipolis, 06560 Nice, France
| | - Emmanuel Deval
- CNRS (Centre National de la Recherche Scientifique), IPMC (Institut de Pharmacologie Moléculaire et Cellulaire), LabEx ICST (Laboratory of Excellence in Ion Channel Science and Therapeutics), FHU InovPain (Fédération Hospitalo-Universitaire “Innovative Solutions in Refractory Chronic Pain”), Université Côte d’Azur, 660 Route des Lucioles, Sophia-Antipolis, 06560 Nice, France
| | - Eric Lingueglia
- CNRS (Centre National de la Recherche Scientifique), IPMC (Institut de Pharmacologie Moléculaire et Cellulaire), LabEx ICST (Laboratory of Excellence in Ion Channel Science and Therapeutics), FHU InovPain (Fédération Hospitalo-Universitaire “Innovative Solutions in Refractory Chronic Pain”), Université Côte d’Azur, 660 Route des Lucioles, Sophia-Antipolis, 06560 Nice, France
| | - Anne Baron
- CNRS (Centre National de la Recherche Scientifique), IPMC (Institut de Pharmacologie Moléculaire et Cellulaire), LabEx ICST (Laboratory of Excellence in Ion Channel Science and Therapeutics), FHU InovPain (Fédération Hospitalo-Universitaire “Innovative Solutions in Refractory Chronic Pain”), Université Côte d’Azur, 660 Route des Lucioles, Sophia-Antipolis, 06560 Nice, France
- Correspondence:
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245
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Zheng Y, Shen S, Keleş S. Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D. Genome Biol 2022; 23:222. [PMID: 36253828 PMCID: PMC9575231 DOI: 10.1186/s13059-022-02774-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 09/19/2022] [Indexed: 11/10/2022] Open
Abstract
Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.
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Affiliation(s)
- Ye Zheng
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA
| | - Siqi Shen
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, USA
| | - Sündüz Keleş
- Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Madison, USA
- Department of Statistics, University of Wisconsin - Madison, Madison, USA
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246
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Batiuk MY, Tyler T, Dragicevic K, Mei S, Rydbirk R, Petukhov V, Deviatiiarov R, Sedmak D, Frank E, Feher V, Habek N, Hu Q, Igolkina A, Roszik L, Pfisterer U, Garcia-Gonzalez D, Petanjek Z, Adorjan I, Kharchenko PV, Khodosevich K. Upper cortical layer-driven network impairment in schizophrenia. SCIENCE ADVANCES 2022; 8:eabn8367. [PMID: 36223459 PMCID: PMC9555788 DOI: 10.1126/sciadv.abn8367] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 08/24/2022] [Indexed: 05/31/2023]
Abstract
Schizophrenia is one of the most widespread and complex mental disorders. To characterize the impact of schizophrenia, we performed single-nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. In addition, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most marked in upper-layer GABAergic neurons, including down-regulation in energy metabolism and up-regulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Last, Visium spatial transcriptomics further corroborated upper-layer neuron vulnerability in schizophrenia. Overall, our results point toward general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology.
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Affiliation(s)
- Mykhailo Y. Batiuk
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Teadora Tyler
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest H-1085, Hungary
| | - Katarina Dragicevic
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Shenglin Mei
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Rasmus Rydbirk
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Viktor Petukhov
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Ruslan Deviatiiarov
- The National Center for Personalized Medicine of Endocrine Diseases, Moscow 115478, Russia
- Kazan Federal University, Kazan 420043, Russia
| | - Dora Sedmak
- Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb 10000, Croatia
| | - Erzsebet Frank
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest H-1085, Hungary
| | - Virginia Feher
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest H-1085, Hungary
| | - Nikola Habek
- Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb 10000, Croatia
| | - Qiwen Hu
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Anna Igolkina
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
- St. Petersburg Polytechnical University, St. Petersburg 195251, Russia
| | - Lilla Roszik
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest H-1085, Hungary
| | - Ulrich Pfisterer
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Diego Garcia-Gonzalez
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Zdravko Petanjek
- Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb 10000, Croatia
| | - Istvan Adorjan
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest H-1085, Hungary
| | - Peter V. Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
| | - Konstantin Khodosevich
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
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247
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Valihrach L, Matusova Z, Zucha D, Klassen R, Benesova S, Abaffy P, Kubista M, Anderova M. Recent advances in deciphering oligodendrocyte heterogeneity with single-cell transcriptomics. Front Cell Neurosci 2022; 16:1025012. [PMID: 36313617 PMCID: PMC9606807 DOI: 10.3389/fncel.2022.1025012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 09/22/2022] [Indexed: 11/18/2022] Open
Abstract
Oligodendrocytes (OL) have been for decades considered a passive, homogenous population of cells that provide support to neurons, and show a limited response to pathological stimuli. This view has been dramatically changed by the introduction of powerful transcriptomic methods that have uncovered a broad spectrum of OL populations that co-exist within the healthy central nervous system (CNS) and also across a variety of diseases. Specifically, single-cell and single-nucleus RNA-sequencing (scRNA-seq, snRNA-seq) have been used to reveal OL variations in maturation, myelination and immune status. The newly discovered immunomodulatory role suggests that OL may serve as targets for future therapies. In this review, we summarize the current understanding of OL heterogeneity in mammalian CNS as revealed by scRNA-seq and snRNA-seq. We provide a list of key studies that identify consensus marker genes defining the currently known OL populations. This resource can be used to standardize analysis of OL related datasets and improve their interpretation, ultimately leading to a better understanding of OL functions in health and disease.
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Affiliation(s)
- Lukas Valihrach
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
- Department of Cellular Neurophysiology, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
- *Correspondence: Lukas Valihrach,
| | - Zuzana Matusova
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
- Faculty of Science, Charles University, Prague, Czechia
| | - Daniel Zucha
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
- Department of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology, Prague, Czechia
| | - Ruslan Klassen
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
- Department of Biochemistry and Microbiology, Faculty of Food and Biochemical Technology, University of Chemistry and Technology, Prague, Czechia
| | - Sarka Benesova
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
- Department of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology, Prague, Czechia
| | - Pavel Abaffy
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
| | - Mikael Kubista
- Laboratory of Gene Expression, Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czechia
- TATAA Biocenter AB, Gothenburg, Sweden
| | - Miroslava Anderova
- Department of Cellular Neurophysiology, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czechia
- Miroslava Anderova,
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248
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Moore H, Lega BC, Konopka G. Riding brain "waves" to identify human memory genes. Curr Opin Cell Biol 2022; 78:102118. [PMID: 35947942 DOI: 10.1016/j.ceb.2022.102118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 06/24/2022] [Accepted: 06/28/2022] [Indexed: 01/31/2023]
Abstract
While there is extensive research on memory-related oscillations and brain gene expression, the relationship between oscillations and gene expression has rarely been studied. Recently, progress has been made to identify specific genes associated with oscillations that are correlated with episodic memory. Neocortical regions, in particular the temporal pole, have been examined in this line of research due to their accessibility during neurosurgical procedures. By harnessing this accessibility, a unique and powerful study design has allowed gene expression and intracranial oscillatory data to be sourced from the same human patients. These studies have identified a plethora of understudied gene targets that should be further characterized with respect to human brain function. Future work should extend to other brain regions to increase our understanding of the genetic signatures of oscillations and, ultimately, human cognition.
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Affiliation(s)
- Haley Moore
- Department of Neuroscience, UT Southwestern Medical Center, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, USA; Department of Neurosurgery, UT Southwestern Medical Center, USA
| | - Bradley C Lega
- Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, USA; Department of Neurosurgery, UT Southwestern Medical Center, USA.
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, USA; Peter O'Donnell Jr. Brain Institute, UT Southwestern Medical Center, USA.
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249
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Revah O, Gore F, Kelley KW, Andersen J, Sakai N, Chen X, Li MY, Birey F, Yang X, Saw NL, Baker SW, Amin ND, Kulkarni S, Mudipalli R, Cui B, Nishino S, Grant GA, Knowles JK, Shamloo M, Huguenard JR, Deisseroth K, Pașca SP. Maturation and circuit integration of transplanted human cortical organoids. Nature 2022; 610:319-326. [PMID: 36224417 PMCID: PMC9556304 DOI: 10.1038/s41586-022-05277-w] [Citation(s) in RCA: 122] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 08/25/2022] [Indexed: 01/26/2023]
Abstract
Self-organizing neural organoids represent a promising in vitro platform with which to model human development and disease1-5. However, organoids lack the connectivity that exists in vivo, which limits maturation and makes integration with other circuits that control behaviour impossible. Here we show that human stem cell-derived cortical organoids transplanted into the somatosensory cortex of newborn athymic rats develop mature cell types that integrate into sensory and motivation-related circuits. MRI reveals post-transplantation organoid growth across multiple stem cell lines and animals, whereas single-nucleus profiling shows progression of corticogenesis and the emergence of activity-dependent transcriptional programs. Indeed, transplanted cortical neurons display more complex morphological, synaptic and intrinsic membrane properties than their in vitro counterparts, which enables the discovery of defects in neurons derived from individuals with Timothy syndrome. Anatomical and functional tracings show that transplanted organoids receive thalamocortical and corticocortical inputs, and in vivo recordings of neural activity demonstrate that these inputs can produce sensory responses in human cells. Finally, cortical organoids extend axons throughout the rat brain and their optogenetic activation can drive reward-seeking behaviour. Thus, transplanted human cortical neurons mature and engage host circuits that control behaviour. We anticipate that this approach will be useful for detecting circuit-level phenotypes in patient-derived cells that cannot otherwise be uncovered.
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Affiliation(s)
- Omer Revah
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Felicity Gore
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Kevin W Kelley
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Jimena Andersen
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Noriaki Sakai
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Xiaoyu Chen
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Min-Yin Li
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Fikri Birey
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Xiao Yang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
- Department of Chemistry, Stanford University, Stanford, CA, USA
| | - Nay L Saw
- Stanford Behavioral and Functional Neuroscience Laboratory, Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Samuel W Baker
- Department of Comparative Medicine, Stanford University, Stanford, CA, USA
| | - Neal D Amin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Shravanti Kulkarni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA
| | - Rachana Mudipalli
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Bianxiao Cui
- Department of Chemistry, Stanford University, Stanford, CA, USA
| | - Seiji Nishino
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Gerald A Grant
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Juliet K Knowles
- Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Mehrdad Shamloo
- Stanford Behavioral and Functional Neuroscience Laboratory, Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - John R Huguenard
- Department of Neurology and Neurological Sciences, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Sergiu P Pașca
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
- Stanford Brain Organogenesis, Wu Tsai Neurosciences Institute and Bio-X, Stanford University, Stanford, CA, USA.
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250
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Ma S, Skarica M, Li Q, Xu C, Risgaard RD, Tebbenkamp AT, Mato-Blanco X, Kovner R, Krsnik Ž, de Martin X, Luria V, Martí-Pérez X, Liang D, Karger A, Schmidt DK, Gomez-Sanchez Z, Qi C, Gobeske KT, Pochareddy S, Debnath A, Hottman CJ, Spurrier J, Teo L, Boghdadi AG, Homman-Ludiye J, Ely JJ, Daadi EW, Mi D, Daadi M, Marín O, Hof PR, Rasin MR, Bourne J, Sherwood CC, Santpere G, Girgenti MJ, Strittmatter SM, Sousa AM, Sestan N. Molecular and cellular evolution of the primate dorsolateral prefrontal cortex. Science 2022; 377:eabo7257. [PMID: 36007006 PMCID: PMC9614553 DOI: 10.1126/science.abo7257] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The granular dorsolateral prefrontal cortex (dlPFC) is an evolutionary specialization of primates that is centrally involved in cognition. We assessed more than 600,000 single-nucleus transcriptomes from adult human, chimpanzee, macaque, and marmoset dlPFC. Although most cell subtypes defined transcriptomically are conserved, we detected several that exist only in a subset of species as well as substantial species-specific molecular differences across homologous neuronal, glial, and non-neural subtypes. The latter are exemplified by human-specific switching between expression of the neuropeptide somatostatin and tyrosine hydroxylase, the rate-limiting enzyme in dopamine production in certain interneurons. The above molecular differences are also illustrated by expression of the neuropsychiatric risk gene FOXP2, which is human-specific in microglia and primate-specific in layer 4 granular neurons. We generated a comprehensive survey of the dlPFC cellular repertoire and its shared and divergent features in anthropoid primates.
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Affiliation(s)
- Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Mario Skarica
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Qian Li
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Chuan Xu
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ryan D. Risgaard
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Xoel Mato-Blanco
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Rothem Kovner
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Željka Krsnik
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Xabier de Martin
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Xavier Martí-Pérez
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Dan Liang
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Amir Karger
- IT-Research Computing, Harvard Medical School, Boston, MA, USA
| | - Danielle K. Schmidt
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Zachary Gomez-Sanchez
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Cai Qi
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Kevin T. Gobeske
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Sirisha Pochareddy
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ashwin Debnath
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Cade J. Hottman
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Joshua Spurrier
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neurology, Yale School of Medicine, New Haven, CT 06536, USA
| | - Leon Teo
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Anthony G. Boghdadi
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Jihane Homman-Ludiye
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - John J. Ely
- MAEBIOS, Alamogordo, NM 88310, USA
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Etienne W. Daadi
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Da Mi
- Tsinghua-Peking Center for Life Sciences, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Marcel Daadi
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
- Department of Cell Systems & Anatomy, Radiology, Long School of Medicine, UT Health San Antonio
- NeoNeuron LLC, Palo Alto, CA 94306, USA
| | - Oscar Marín
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mladen-Roko Rasin
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - James Bourne
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Gabriel Santpere
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Matthew J. Girgenti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
- National Center for PTSD, US Department of Veterans Affairs, White River Junction, VT, USA
| | - Stephen M. Strittmatter
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neurology, Yale School of Medicine, New Haven, CT 06536, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - André M.M. Sousa
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Departments of Genetics and Comparative Medicine, Program in Cellular Neuroscience, Neurodegeneration and Repair, and Yale Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
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