1
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Morris GP, Foster CG, Sutherland BA, Grubb S. Microglia contact cerebral vasculature through gaps between astrocyte endfeet. J Cereb Blood Flow Metab 2024:271678X241280775. [PMID: 39253821 DOI: 10.1177/0271678x241280775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
The close spatial relationship between microglia and cerebral blood vessels implicates microglia in vascular development, homeostasis and disease. In this study we used the publicly available Cortical MM^3 electron microscopy dataset to systematically investigate microglial interactions with the vasculature. Our analysis revealed that approximately 20% of microglia formed direct contacts with blood vessels through gaps between adjacent astrocyte endfeet. We termed these contact points "plugs". Plug-forming microglia exhibited closer proximity to blood vessels than non-plug forming microglia and formed multiple plugs, predominantly near the soma, ranging in surface area from ∼0.01 μm2 to ∼15 μm2. Plugs were enriched at the venule end of the vascular tree and displayed a preference for contacting endothelial cells over pericytes at a ratio of 3:1. In summary, we provide novel insights into the ultrastructural relationship between microglia and the vasculature, laying a foundation for understanding how these contacts contribute to the functional cross-talk between microglia and cells of the vasculature in health and disease.
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Affiliation(s)
- Gary P Morris
- Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Catherine G Foster
- Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia
- Center for Developmental Biology and Regenerative Medicine, Seattle Children's Research Institute, Seattle, WA, USA
| | - Brad A Sutherland
- Tasmanian School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Søren Grubb
- Center for Translational Neuromedicine, Faculty of Health Sciences, University of Copenhagen, Copenhagen N, Denmark
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2
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Bame X, Hill RA. Mitochondrial network reorganization and transient expansion during oligodendrocyte generation. Nat Commun 2024; 15:6979. [PMID: 39143079 PMCID: PMC11324877 DOI: 10.1038/s41467-024-51016-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 07/24/2024] [Indexed: 08/16/2024] Open
Abstract
Oligodendrocyte precursor cells (OPCs) give rise to myelinating oligodendrocytes of the brain. This process persists throughout life and is essential for recovery from neurodegeneration. To better understand the cellular checkpoints that occur during oligodendrogenesis, we determined the mitochondrial distribution and morphometrics across the oligodendrocyte lineage in mouse and human cerebral cortex. During oligodendrocyte generation, mitochondrial content expands concurrently with a change in subcellular partitioning towards the distal processes. These changes are followed by an abrupt loss of mitochondria in the oligodendrocyte processes and myelin, coinciding with sheath compaction. This reorganization and extensive expansion and depletion take 3 days. Oligodendrocyte mitochondria are stationary over days while OPC mitochondrial motility is modulated by animal arousal state within minutes. Aged OPCs also display decreased mitochondrial size, volume fraction, and motility. Thus, mitochondrial dynamics are linked to oligodendrocyte generation, dynamically modified by their local microenvironment, and altered in the aging brain.
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Affiliation(s)
- Xhoela Bame
- Department of Biological Sciences, Dartmouth College, Hanover, NH, USA
| | - Robert A Hill
- Department of Biological Sciences, Dartmouth College, Hanover, NH, USA.
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3
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Zheng Z, Own CS, Wanner AA, Koene RA, Hammerschmith EW, Silversmith WM, Kemnitz N, Lu R, Tank DW, Seung HS. Fast imaging of millimeter-scale areas with beam deflection transmission electron microscopy. Nat Commun 2024; 15:6860. [PMID: 39127683 PMCID: PMC11316758 DOI: 10.1038/s41467-024-50846-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 07/23/2024] [Indexed: 08/12/2024] Open
Abstract
Serial section transmission electron microscopy (TEM) has proven to be one of the leading methods for millimeter-scale 3D imaging of brain tissues at nanoscale resolution. It is important to further improve imaging efficiency to acquire larger and more brain volumes. We report here a threefold increase in the speed of TEM by using a beam deflecting mechanism to enable highly efficient acquisition of multiple image tiles (nine) for each motion of the mechanical stage. For millimeter-scale areas, the duty cycle of imaging doubles to more than 30%, yielding a net average imaging rate of 0.3 gigapixels per second. If fully utilized, an array of four beam deflection TEMs should be capable of imaging a dataset of cubic millimeter scale in five weeks.
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Affiliation(s)
- Zhihao Zheng
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Adrian A Wanner
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Paul Scherrer Institute, Villigen, Switzerland
| | | | | | | | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Ran Lu
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - David W Tank
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - H Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
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4
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Han X, Lu X, Li PH, Wang S, Schalek R, Meirovitch Y, Lin Z, Adhinarta J, Murray KD, MacNiven LM, Berger DR, Wu Y, Fang T, Meral ES, Asraf S, Ploegh H, Pfister H, Wei D, Jain V, Trimmer JS, Lichtman JW. Multiplexed volumetric CLEM enabled by scFvs provides insights into the cytology of cerebellar cortex. Nat Commun 2024; 15:6648. [PMID: 39103318 DOI: 10.1038/s41467-024-50411-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 07/01/2024] [Indexed: 08/07/2024] Open
Abstract
Mapping neuronal networks is a central focus in neuroscience. While volume electron microscopy (vEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide molecular information to identify cell types or functions. We developed an approach that uses fluorescent single-chain variable fragments (scFvs) to perform multiplexed detergent-free immunolabeling and volumetric-correlated-light-and-electron-microscopy on the same sample. We generated eight fluorescent scFvs targeting brain markers. Six fluorescent probes were imaged in the cerebellum of a female mouse, using confocal microscopy with spectral unmixing, followed by vEM of the same sample. The results provide excellent ultrastructure superimposed with multiple fluorescence channels. Using this approach, we documented a poorly described cell type, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.
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Affiliation(s)
- Xiaomeng Han
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
| | - Xiaotang Lu
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
| | | | - Shuohong Wang
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Richard Schalek
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Yaron Meirovitch
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Zudi Lin
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Jason Adhinarta
- Computer Science Department, Boston College, Chestnut Hill, MA, USA
| | - Karl D Murray
- Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Davis, CA, USA
| | - Leah M MacNiven
- Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Davis, CA, USA
| | - Daniel R Berger
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Yuelong Wu
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Tao Fang
- Program of Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
| | | | - Shadnan Asraf
- School of Public Health, University of Massachusetts Amherst, Amherst, MA, USA
| | - Hidde Ploegh
- Program of Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Hanspeter Pfister
- Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Davis, CA, USA
| | - Donglai Wei
- Computer Science Department, Boston College, Chestnut Hill, MA, USA
| | | | - James S Trimmer
- Department of Physiology and Membrane Biology, University of California Davis School of Medicine, Davis, CA, USA
| | - Jeff W Lichtman
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
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5
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Affiliation(s)
| | - Viren Jain
- Google Research, Mountain View, CA, USA.
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6
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Cano-Astorga N, Plaza-Alonso S, DeFelipe J, Alonso-Nanclares L. Volume electron microscopy analysis of synapses in primary regions of the human cerebral cortex. Cereb Cortex 2024; 34:bhae312. [PMID: 39106175 DOI: 10.1093/cercor/bhae312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/03/2024] [Accepted: 07/12/2024] [Indexed: 08/09/2024] Open
Abstract
Functional and structural studies investigating macroscopic connectivity in the human cerebral cortex suggest that high-order associative regions exhibit greater connectivity compared to primary ones. However, the synaptic organization of these brain regions remains unexplored. In the present work, we conducted volume electron microscopy to investigate the synaptic organization of the human brain obtained at autopsy. Specifically, we examined layer III of Brodmann areas 17, 3b, and 4, as representative areas of primary visual, somatosensorial, and motor cortex. Additionally, we conducted comparative analyses with our previous datasets of layer III from temporopolar and anterior cingulate associative cortical regions (Brodmann areas 24, 38, and 21). 9,690 synaptic junctions were 3D reconstructed, showing that certain synaptic characteristics are specific to particular regions. The number of synapses per volume, the proportion of the postsynaptic targets, and the synaptic size may distinguish one region from another, regardless of whether they are associative or primary cortex. By contrast, other synaptic characteristics were common to all analyzed regions, such as the proportion of excitatory and inhibitory synapses, their shapes, their spatial distribution, and a higher proportion of synapses located on dendritic spines. The present results provide further insights into the synaptic organization of the human cerebral cortex.
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Affiliation(s)
- Nicolás Cano-Astorga
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- PhD Program in Neuroscience, Autonoma de Madrid University-Cajal Institute, Arzobispo Morcillo 4, Madrid 28029, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Sergio Plaza-Alonso
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
| | - Lidia Alonso-Nanclares
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid 28223, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce 37, Madrid 28002, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Valderrebollo 5, Madrid 28031, Spain
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7
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Nassan M. Proposal for a Mechanistic Disease Conceptualization in Clinical Neurosciences: The Neural Network Components (NNC) Model. Harv Rev Psychiatry 2024; 32:150-159. [PMID: 38990903 DOI: 10.1097/hrp.0000000000000399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
ABSTRACT Clinical neurosciences, and psychiatry specifically, have been challenged by the lack of a comprehensive and practical framework that explains the core mechanistic processes of variable psychiatric presentations. Current conceptualization and classification of psychiatric presentations are primarily centered on a non-biologically based clinical descriptive approach. Despite various attempts, advances in neuroscience research have not led to an improved conceptualization or mechanistic classification of psychiatric disorders. This perspective article proposes a new-work-in-progress-framework for conceptualizing psychiatric presentations based on neural network components (NNC). This framework could guide the development of mechanistic disease classification, improve understanding of underpinning pathology, and provide specific intervention targets. This model also has the potential to dissolve artificial barriers between the fields of psychiatry and neurology.
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Affiliation(s)
- Malik Nassan
- From Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University, Chicago, IL; Department of Neurology and Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine (Dr. Nassan)
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8
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Turegano-Lopez M, de Las Pozas F, Santuy A, Rodriguez JR, DeFelipe J, Merchan-Perez A. Tracing nerve fibers with volume electron microscopy to quantitatively analyze brain connectivity. Commun Biol 2024; 7:796. [PMID: 38951162 PMCID: PMC11217374 DOI: 10.1038/s42003-024-06491-0] [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: 12/18/2023] [Accepted: 06/21/2024] [Indexed: 07/03/2024] Open
Abstract
The highly complex structure of the brain requires an approach that can unravel its connectivity. Using volume electron microscopy and a dedicated software we can trace and measure all nerve fibers present within different samples of brain tissue. With this software tool, individual dendrites and axons are traced, obtaining a simplified "skeleton" of each fiber, which is linked to its corresponding synaptic contacts. The result is an intricate meshwork of axons and dendrites interconnected by a cloud of synaptic junctions. To test this methodology, we apply it to the stratum radiatum of the hippocampus and layers 1 and 3 of the somatosensory cortex of the mouse. We find that nerve fibers are densely packed in the neuropil, reaching up to 9 kilometers per cubic mm. We obtain the number of synapses, the number and lengths of dendrites and axons, the linear densities of synapses established by dendrites and axons, and their location on dendritic spines and shafts. The quantitative data obtained through this method enable us to identify subtle traits and differences in the synaptic organization of the samples, which might have been overlooked in a qualitative analysis.
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Affiliation(s)
- Marta Turegano-Lopez
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031, Madrid, Spain
| | - Felix de Las Pozas
- Visualization & Graphics Lab (VG-Lab), Universidad Rey Juan Carlos, C/Tulipán S/N, Móstoles, 28933, Madrid, Spain
| | - Andrea Santuy
- Department of Basic Sciences, Universitat Internacional de Catalunya (UIC), San Cugat del Vallès, 08195, Barcelona, Spain
| | - Jose-Rodrigo Rodriguez
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031, Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce, 37, 28002, Madrid, Spain
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031, Madrid, Spain
- Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Avda. Doctor Arce, 37, 28002, Madrid, Spain
| | - Angel Merchan-Perez
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223, Madrid, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031, Madrid, Spain.
- Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223, Madrid, Spain.
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9
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Leiwe MN, Fujimoto S, Baba T, Moriyasu D, Saha B, Sakaguchi R, Inagaki S, Imai T. Automated neuronal reconstruction with super-multicolour Tetbow labelling and threshold-based clustering of colour hues. Nat Commun 2024; 15:5279. [PMID: 38918382 PMCID: PMC11199630 DOI: 10.1038/s41467-024-49455-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 06/06/2024] [Indexed: 06/27/2024] Open
Abstract
Fluorescence imaging is widely used for the mesoscopic mapping of neuronal connectivity. However, neurite reconstruction is challenging, especially when neurons are densely labelled. Here, we report a strategy for the fully automated reconstruction of densely labelled neuronal circuits. Firstly, we establish stochastic super-multicolour labelling with up to seven different fluorescent proteins using the Tetbow method. With this method, each neuron is labelled with a unique combination of fluorescent proteins, which are then imaged and separated by linear unmixing. We also establish an automated neurite reconstruction pipeline based on the quantitative analysis of multiple dyes (QDyeFinder), which identifies neurite fragments with similar colour combinations. To classify colour combinations, we develop unsupervised clustering algorithm, dCrawler, in which data points in multi-dimensional space are clustered based on a given threshold distance. Our strategy allows the reconstruction of neurites for up to hundreds of neurons at the millimetre scale without using their physical continuity.
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Affiliation(s)
- Marcus N Leiwe
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- MetaCell LCC, LTD, Cambridge, MA, USA
| | - Satoshi Fujimoto
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshikazu Baba
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Daichi Moriyasu
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Biswanath Saha
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Richi Sakaguchi
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shigenori Inagaki
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takeshi Imai
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
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10
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Bourdillon P, Ren L, Halgren M, Paulk AC, Salami P, Ulbert I, Fabó D, King JR, Sjoberg KM, Eskandar EN, Madsen JR, Halgren E, Cash SS. Differential cortical layer engagement during seizure initiation and spread in humans. Nat Commun 2024; 15:5153. [PMID: 38886376 PMCID: PMC11183216 DOI: 10.1038/s41467-024-48746-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 05/10/2024] [Indexed: 06/20/2024] Open
Abstract
Despite decades of research, we still do not understand how spontaneous human seizures start and spread - especially at the level of neuronal microcircuits. In this study, we used laminar arrays of micro-electrodes to simultaneously record the local field potentials and multi-unit neural activities across the six layers of the neocortex during focal seizures in humans. We found that, within the ictal onset zone, the discharges generated during a seizure consisted of current sinks and sources only within the infra-granular and granular layers. Outside of the seizure onset zone, ictal discharges reflected current flow in the supra-granular layers. Interestingly, these patterns of current flow evolved during the course of the seizure - especially outside the seizure onset zone where superficial sinks and sources extended into the deeper layers. Based on these observations, a framework describing cortical-cortical dynamics of seizures is proposed with implications for seizure localization, surgical targeting, and neuromodulation techniques to block the generation and propagation of seizures.
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Affiliation(s)
- Pierre Bourdillon
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Neurosurgery, Hospital Foundation Adolphe de Rothschild, Paris, France.
- Integrative Neuroscience and Cognition Center, Paris Cité University, Paris, France.
| | - Liankun Ren
- Department of Neurology, Xuanwu Hospital, National Center for Neurological Disorders, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Mila Halgren
- Brain and Cognitive Sciences Department and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Pariya Salami
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - István Ulbert
- HUN-REN, Research Center for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Budapest, Hungary
- Faculty of Information Technology and Bionics, Péter Pázmány Catholic University, Budapest, Hungary
- Department of Neurosurgery and Neurointervention, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Dániel Fabó
- Department of Neurosurgery and Neurointervention, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Jean-Rémi King
- Laboratoire des Systèmes Perceptifs, Département d'études cognitives, École normale supérieure, PSL University, CNRS, Paris, France
| | - Kane M Sjoberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Harvard College, Cambridge, MA, 02138, USA
| | - Emad N Eskandar
- Department of Neurological Surgery, Albert Einstein College of Medicine - Montefiore Medical Center, Bronx, NY, USA
| | - Joseph R Madsen
- Department of Neurosurgery, Boston Children Hospital, Harvard Medical School, Boston, MA, USA
| | - Eric Halgren
- Departments of Radiology and, Neurosciences, University of California, San Diego, San Diego, CA, USA
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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11
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Meirovitch Y, Park CF, Mi L, Potocek P, Sawmya S, Li Y, Chandok IS, Athey TL, Karlupia N, Wu Y, Berger DR, Schalek R, Pfister H, Schoenmakers R, Peemen M, Lichtman JW, Samuel ADT, Shavit N. SmartEM: machine-learning guided electron microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.05.561103. [PMID: 38915594 PMCID: PMC11195061 DOI: 10.1101/2023.10.05.561103] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Connectomics provides essential nanometer-resolution, synapse-level maps of neural circuits to understand brain activity and behavior. However, few researchers have access to the high-throughput electron microscopes necessary to generate enough data for whole circuit or brain reconstruction. To date, machine-learning methods have been used after the collection of images by electron microscopy (EM) to accelerate and improve neuronal segmentation, synapse reconstruction and other data analysis. With the computational improvements in processing EM images, acquiring EM images has now become the rate-limiting step. Here, in order to speed up EM imaging, we integrate machine-learning into real-time image acquisition in a singlebeam scanning electron microscope. This SmartEM approach allows an electron microscope to perform intelligent, data-aware imaging of specimens. SmartEM allocates the proper imaging time for each region of interest - scanning all pixels equally rapidly, then re-scanning small subareas more slowly where a higher quality signal is required to achieve accurate segmentability, in significantly less time. We demonstrate that this pipeline achieves a 7-fold acceleration of image acquisition time for connectomics using a commercial single-beam SEM. We apply SmartEM to reconstruct a portion of mouse cortex with the same accuracy as traditional microscopy but in less time.
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Affiliation(s)
- Yaron Meirovitch
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Core Francisco Park
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Lu Mi
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Pavel Potocek
- Thermo Fisher Scientific, Eindhoven, the Netherlands
- Saarland University, 66123, Saarbrücken, Germany
| | - Shashata Sawmya
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yicong Li
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Ishaan Singh Chandok
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Thomas L Athey
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Neha Karlupia
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Yuelong Wu
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Daniel R Berger
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Richard Schalek
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Hanspeter Pfister
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | | | | | - Jeff W Lichtman
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Aravinthan D T Samuel
- Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Nir Shavit
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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12
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Torres R, Takasaki K, Gliko O, Laughland C, Yu WQ, Turschak E, Hellevik A, Balaram P, Perlman E, Sümbül U, Reid RC. A scalable and modular computational pipeline for axonal connectomics: automated tracing and assembly of axons across serial sections. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598365. [PMID: 38915568 PMCID: PMC11195148 DOI: 10.1101/2024.06.11.598365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Progress in histological methods and in microscope technology has enabled dense staining and imaging of axons over large brain volumes, but tracing axons over such volumes requires new computational tools for 3D reconstruction of data acquired from serial sections. We have developed a computational pipeline for automated tracing and volume assembly of densely stained axons imaged over serial sections, which leverages machine learning-based segmentation to enable stitching and alignment with the axon traces themselves. We validated this segmentation-driven approach to volume assembly and alignment of individual axons over centimeter-scale serial sections and show the application of the output traces for analysis of local orientation and for proofreading over aligned volumes. The pipeline is scalable, and combined with recent advances in experimental approaches, should enable new studies of mesoscale connectivity and function over the whole human brain.
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Czeisler MÉ, Shan Y, Schalek R, Berger DR, Suissa-Peleg A, Takahashi JS, Lichtman JW. Extensive soma-soma plate-like contact sites (ephapses) connect suprachiasmatic nucleus neurons. J Comp Neurol 2024; 532:e25624. [PMID: 38896499 DOI: 10.1002/cne.25624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 03/30/2024] [Accepted: 04/29/2024] [Indexed: 06/21/2024]
Abstract
The hypothalamic suprachiasmatic nucleus (SCN) is the central pacemaker for mammalian circadian rhythms. As such, this ensemble of cell-autonomous neuronal oscillators with divergent periods must maintain coordinated oscillations. To investigate ultrastructural features enabling such synchronization, 805 coronal ultrathin sections of mouse SCN tissue were imaged with electron microscopy and aligned into a volumetric stack, from which selected neurons within the SCN core were reconstructed in silico. We found that clustered SCN core neurons were physically connected to each other via multiple large soma-to-soma plate-like contacts. In some cases, a sliver of a glial process was interleaved. These contacts were large, covering on average ∼21% of apposing neuronal somata. It is possible that contacts may be the electrophysiological substrate for synchronization between SCN neurons. Such plate-like contacts may explain why the synchronization of SCN neurons is maintained even when chemical synaptic transmission or electrical synaptic transmission via gap junctions is blocked. Such ephaptic contact-mediated synchronization among nearby neurons may therefore contribute to the wave-like oscillations of circadian core clock genes and calcium signals observed in the SCN.
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Affiliation(s)
- Mark É Czeisler
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Yongli Shan
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Richard Schalek
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Daniel R Berger
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Adi Suissa-Peleg
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Joseph S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jeff W Lichtman
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
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Lu C, Chen K, Qiu H, Chen X, Chen G, Qi X, Jiang H. Diffusion-based deep learning method for augmenting ultrastructural imaging and volume electron microscopy. Nat Commun 2024; 15:4677. [PMID: 38824146 PMCID: PMC11144272 DOI: 10.1038/s41467-024-49125-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 05/20/2024] [Indexed: 06/03/2024] Open
Abstract
Electron microscopy (EM) revolutionized the way to visualize cellular ultrastructure. Volume EM (vEM) has further broadened its three-dimensional nanoscale imaging capacity. However, intrinsic trade-offs between imaging speed and quality of EM restrict the attainable imaging area and volume. Isotropic imaging with vEM for large biological volumes remains unachievable. Here, we developed EMDiffuse, a suite of algorithms designed to enhance EM and vEM capabilities, leveraging the cutting-edge image generation diffusion model. EMDiffuse generates realistic predictions with high resolution ultrastructural details and exhibits robust transferability by taking only one pair of images of 3 megapixels to fine-tune in denoising and super-resolution tasks. EMDiffuse also demonstrated proficiency in the isotropic vEM reconstruction task, generating isotropic volume even in the absence of isotropic training data. We demonstrated the robustness of EMDiffuse by generating isotropic volumes from seven public datasets obtained from different vEM techniques and instruments. The generated isotropic volume enables accurate three-dimensional nanoscale ultrastructure analysis. EMDiffuse also features self-assessment functionalities on predictions' reliability. We envision EMDiffuse to pave the way for investigations of the intricate subcellular nanoscale ultrastructure within large volumes of biological systems.
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Affiliation(s)
- Chixiang Lu
- Department of Chemistry, The University of Hong Kong, Hong Kong, China
| | - Kai Chen
- Department of Chemistry, The University of Hong Kong, Hong Kong, China
- School of Molecular Sciences, The University of Western Australia, Perth, WA, Australia
| | - Heng Qiu
- Department of Chemistry, The University of Hong Kong, Hong Kong, China
| | - Xiaojun Chen
- School of Molecular Sciences, The University of Western Australia, Perth, WA, Australia
| | - Gu Chen
- Department of Chemistry, The University of Hong Kong, Hong Kong, China
| | - Xiaojuan Qi
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.
| | - Haibo Jiang
- Department of Chemistry, The University of Hong Kong, Hong Kong, China.
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Wong C. Cubic millimetre of brain mapped in spectacular detail. Nature 2024; 629:739-740. [PMID: 38724661 DOI: 10.1038/d41586-024-01387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
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16
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Kievits AJ, Duinkerken BHP, Lane R, de Heus C, van Beijeren Bergen en Henegouwen D, Höppener T, Wolters AHG, Liv N, Giepmans BNG, Hoogenboom JP. FAST-EM array tomography: a workflow for multibeam volume electron microscopy. METHODS IN MICROSCOPY 2024; 1:49-64. [PMID: 39119255 PMCID: PMC11308914 DOI: 10.1515/mim-2024-0005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 06/17/2024] [Indexed: 08/10/2024]
Abstract
Elucidating the 3D nanoscale structure of tissues and cells is essential for understanding the complexity of biological processes. Electron microscopy (EM) offers the resolution needed for reliable interpretation, but the limited throughput of electron microscopes has hindered its ability to effectively image large volumes. We report a workflow for volume EM with FAST-EM, a novel multibeam scanning transmission electron microscope that speeds up acquisition by scanning the sample in parallel with 64 electron beams. FAST-EM makes use of optical detection to separate the signals of the individual beams. The acquisition and 3D reconstruction of ultrastructural data from multiple biological samples is demonstrated. The results show that the workflow is capable of producing large reconstructed volumes with high resolution and contrast to address biological research questions within feasible acquisition time frames.
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Affiliation(s)
- Arent J. Kievits
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - B. H. Peter Duinkerken
- Department of Biomedical Sciences, University Medical Center Groningen, Groningen, The Netherlands
| | - Ryan Lane
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Cecilia de Heus
- Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Tibbe Höppener
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Anouk H. G. Wolters
- Department of Biomedical Sciences, University Medical Center Groningen, Groningen, The Netherlands
| | - Nalan Liv
- Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ben N. G. Giepmans
- Department of Biomedical Sciences, University Medical Center Groningen, Groningen, The Netherlands
| | - Jacob P. Hoogenboom
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
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