1
|
Wang M, Zhang L, Novak SW, Yu J, Gallina IS, Xu LL, Lim CK, Fernandes S, Shokhirev MN, Williams AE, Saxena MD, Coorapati S, Parylak SL, Quintero C, Molina E, Andrade LR, Manor U, Gage FH. Morphological diversification and functional maturation of human astrocytes in glia-enriched cortical organoid transplanted in mouse brain. Nat Biotechnol 2024:10.1038/s41587-024-02157-8. [PMID: 38418648 DOI: 10.1038/s41587-024-02157-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 01/30/2024] [Indexed: 03/02/2024]
Abstract
Astrocytes, the most abundant glial cell type in the brain, are underrepresented in traditional cortical organoid models due to the delayed onset of cortical gliogenesis. Here we introduce a new glia-enriched cortical organoid model that exhibits accelerated astrogliogenesis. We demonstrated that induction of a gliogenic switch in a subset of progenitors enabled the rapid derivation of astroglial cells, which account for 25-31% of the cell population within 8-10 weeks of differentiation. Intracerebral transplantation of these organoids reliably generated a diverse repertoire of cortical neurons and anatomical subclasses of human astrocytes. Spatial transcriptome profiling identified layer-specific expression patterns among distinct subclasses of astrocytes within organoid transplants. Using an in vivo acute neuroinflammation model, we identified a subpopulation of astrocytes that rapidly activates pro-inflammatory pathways upon cytokine stimulation. Additionally, we demonstrated that CD38 signaling has a crucial role in mediating metabolic and mitochondrial stress in reactive astrocytes. This model provides a robust platform for investigating human astrocyte function.
Collapse
Affiliation(s)
- Meiyan Wang
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lei Zhang
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Sammy Weiser Novak
- Waitt Advanced Biophotonics Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jingting Yu
- Integrative Genomics and Bioinformatics Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Iryna S Gallina
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lynne L Xu
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Christina K Lim
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Sarah Fernandes
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Maxim N Shokhirev
- Integrative Genomics and Bioinformatics Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - April E Williams
- Integrative Genomics and Bioinformatics Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Monisha D Saxena
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Shashank Coorapati
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Sarah L Parylak
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cristian Quintero
- Next Generation Sequencing Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Elsa Molina
- Next Generation Sequencing Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Leonardo R Andrade
- Waitt Advanced Biophotonics Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Uri Manor
- Waitt Advanced Biophotonics Core, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Fred H Gage
- Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, USA.
| |
Collapse
|
2
|
Samavat M, Bartol TM, Bromer C, Hubbard DD, Hanka DC, Kuwajima M, Mendenhall JM, Parker PH, Bowden JB, Abraham WC, Sejnowski TJ, Harris KM. Long-Term Potentiation Produces a Sustained Expansion of Synaptic Information Storage Capacity in Adult Rat Hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.12.574766. [PMID: 38260636 PMCID: PMC10802612 DOI: 10.1101/2024.01.12.574766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Long-term potentiation (LTP) has become a standard model for investigating synaptic mechanisms of learning and memory. Increasingly, it is of interest to understand how LTP affects the synaptic information storage capacity of the targeted population of synapses. Here, structural synaptic plasticity during LTP was explored using three-dimensional reconstruction from serial section electron microscopy. Storage capacity was assessed by applying a new analytical approach, Shannon information theory, to delineate the number of functionally distinguishable synaptic strengths. LTP was induced by delta-burst stimulation of perforant pathway inputs to the middle molecular layer of hippocampal dentate granule cells in adult rats. Spine head volumes were measured as predictors of synaptic strength and compared between LTP and control hemispheres at 30 min and 2 hr after the induction of LTP. Synapses from the same axon onto the same dendrite were used to determine the precision of synaptic plasticity based on the similarity of their physical dimensions. Shannon entropy was measured by exploiting the frequency of spine heads in functionally distinguishable sizes to assess the degree to which LTP altered the number of bits of information storage. Outcomes from these analyses reveal that LTP expanded storage capacity; the distribution of spine head volumes was increased from 2 bits in controls to 3 bits at 30 min and 2.7 bits at 2 hr after the induction of LTP. Furthermore, the distribution of spine head volumes was more uniform across the increased number of functionally distinguishable sizes following LTP, thus achieving more efficient use of coding space across the population of synapses.
Collapse
Affiliation(s)
- Mohammad Samavat
- Department of Electrical and Computer Engineering, Jacobs School of Engineering, UC San Diego
- Computational Neurobiology Laboratory, The Salk Institute for Biological Sciences, La Jolla, CA 92037
| | - Thomas M Bartol
- Computational Neurobiology Laboratory, The Salk Institute for Biological Sciences, La Jolla, CA 92037
| | - Cailey Bromer
- Computational Neurobiology Laboratory, The Salk Institute for Biological Sciences, La Jolla, CA 92037
| | - Dusten D Hubbard
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
| | - Dakota C Hanka
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
| | - Masaaki Kuwajima
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
| | - John M Mendenhall
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
| | - Patrick H Parker
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
| | - Jared B Bowden
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
- Department of Neuroscience, The University of Texas at Austin, Austin, TX 78712
| | - Wickliffe C Abraham
- Department of Psychology and Brain Health Research Centre, University of Otago, Dunedin, 9016, New Zealand
| | - Terrence J Sejnowski
- Computational Neurobiology Laboratory, The Salk Institute for Biological Sciences, La Jolla, CA 92037
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093
| | - Kristen M Harris
- Center for Learning and Memory, The University of Texas at Austin, Austin, TX 78712
- Department of Neuroscience, The University of Texas at Austin, Austin, TX 78712
| |
Collapse
|
3
|
Alice Liang FX. Optimal Diverse Biological Sample Preparation Methods for 2D and 3D Electron Microscopy Imaging. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2023; 29:92. [PMID: 37613164 DOI: 10.1093/micmic/ozad067.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Feng-Xia Alice Liang
- The Microscopy Core Laboratory, Division of Advanced Research Technologies, New York University Grossman School of Medicine, New York, USA
| |
Collapse
|
4
|
Lewczuk B, Szyryńska N. Field-Emission Scanning Electron Microscope as a Tool for Large-Area and Large-Volume Ultrastructural Studies. Animals (Basel) 2021; 11:ani11123390. [PMID: 34944167 PMCID: PMC8698110 DOI: 10.3390/ani11123390] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 11/24/2021] [Accepted: 11/25/2021] [Indexed: 11/29/2022] Open
Abstract
Simple Summary Ultrastructural studies of cells and tissues are usually performed using transmission electron microscopy (TEM), which enables imaging at the highest possible resolution. The weak point of TEM is the limited ability to analyze the ultrastructure of large areas and volumes of biological samples. This limitation can be overcome by using modern field-emission scanning electron microscopy (FE-SEM) with high-sensitivity detection, which enables the creation of TEM-like images from the flat surfaces of resin-embedded biological specimens. Several FE-SEM-based techniques for two- and three-dimensional ultrastructural studies of cells, tissues, organs, and organisms have been developed in the 21st century. These techniques have created a new era in structural biology and have changed the role of the scanning electron microscope (SEM) in biological and medical laboratories. Since the premiere of the first commercially available SEM in 1965, these instruments were used almost exclusively to obtain topographical information over a large range of magnifications. Currently, FE-SEM offers many attractive possibilities in the studies of cell and tissue ultrastructure, and they are presented in this review. Abstract The development of field-emission scanning electron microscopes for high-resolution imaging at very low acceleration voltages and equipped with highly sensitive detectors of backscattered electrons (BSE) has enabled transmission electron microscopy (TEM)-like imaging of the cut surfaces of tissue blocks, which are impermeable to the electron beam, or tissue sections mounted on the solid substrates. This has resulted in the development of methods that simplify and accelerate ultrastructural studies of large areas and volumes of biological samples. This article provides an overview of these methods, including their advantages and disadvantages. The imaging of large sample areas can be performed using two methods based on the detection of transmitted electrons or BSE. Effective imaging using BSE requires special fixation and en bloc contrasting of samples. BSE imaging has resulted in the development of volume imaging techniques, including array tomography (AT) and serial block-face imaging (SBF-SEM). In AT, serial ultrathin sections are collected manually on a solid substrate such as a glass and silicon wafer or automatically on a tape using a special ultramicrotome. The imaging of serial sections is used to obtain three-dimensional (3D) information. SBF-SEM is based on removing the top layer of a resin-embedded sample using an ultramicrotome inside the SEM specimen chamber and then imaging the exposed surface with a BSE detector. The steps of cutting and imaging the resin block are repeated hundreds or thousands of times to obtain a z-stack for 3D analyses.
Collapse
|
5
|
Fang L, Monroe F, Novak SW, Kirk L, Schiavon CR, Yu SB, Zhang T, Wu M, Kastner K, Latif AA, Lin Z, Shaw A, Kubota Y, Mendenhall J, Zhang Z, Pekkurnaz G, Harris K, Howard J, Manor U. Deep learning-based point-scanning super-resolution imaging. Nat Methods 2021; 18:406-416. [PMID: 33686300 PMCID: PMC8035334 DOI: 10.1038/s41592-021-01080-z] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 01/28/2021] [Indexed: 01/28/2023]
Abstract
Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-scanning systems are difficult to optimize simultaneously. We show these limitations can be mitigated via the use of deep learning-based supersampling of undersampled images acquired on a point-scanning system, which we term point-scanning super-resolution (PSSR) imaging. We designed a 'crappifier' that computationally degrades high SNR, high-pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. For high spatiotemporal resolution fluorescence time-lapse data, we developed a 'multi-frame' PSSR approach that uses information in adjacent frames to improve model predictions. PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed and sensitivity. All the training data, models and code for PSSR are publicly available at 3DEM.org.
Collapse
Affiliation(s)
- Linjing Fang
- Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Fred Monroe
- Wicklow AI Medical Research Initiative, San Francisco, CA, USA
| | - Sammy Weiser Novak
- Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lyndsey Kirk
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA
| | - Cara R Schiavon
- Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Seungyoon B Yu
- Neurobiology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Tong Zhang
- Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Melissa Wu
- Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Kyle Kastner
- Montreal Institute for Learning Algorithms, Université de Montréal, Montréal, Canada
| | - Alaa Abdel Latif
- Fast.AI, University of San Francisco Data Institute, San Francisco, CA, USA
| | - Zijun Lin
- Fast.AI, University of San Francisco Data Institute, San Francisco, CA, USA
| | - Andrew Shaw
- Fast.AI, University of San Francisco Data Institute, San Francisco, CA, USA
| | - Yoshiyuki Kubota
- Division of Cerebral Circuitry, National Institute for Physiological Sciences, Okazaki, Japan
| | - John Mendenhall
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA
| | - Zhao Zhang
- Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, USA
| | - Gulcin Pekkurnaz
- Neurobiology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Kristen Harris
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA
| | - Jeremy Howard
- Fast.AI, University of San Francisco Data Institute, San Francisco, CA, USA
| | - Uri Manor
- Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA.
| |
Collapse
|
6
|
Nahirney PC, Tremblay ME. Brain Ultrastructure: Putting the Pieces Together. Front Cell Dev Biol 2021; 9:629503. [PMID: 33681208 PMCID: PMC7930431 DOI: 10.3389/fcell.2021.629503] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Accepted: 01/20/2021] [Indexed: 12/11/2022] Open
Abstract
Unraveling the fine structure of the brain is important to provide a better understanding of its normal and abnormal functioning. Application of high-resolution electron microscopic techniques gives us an unprecedented opportunity to discern details of the brain parenchyma at nanoscale resolution, although identifying different cell types and their unique features in two-dimensional, or three-dimensional images, remains a challenge even to experts in the field. This article provides insights into how to identify the different cell types in the central nervous system, based on nuclear and cytoplasmic features, amongst other unique characteristics. From the basic distinction between neurons and their supporting cells, the glia, to differences in their subcellular compartments, organelles and their interactions, ultrastructural analyses can provide unique insights into the changes in brain function during aging and disease conditions, such as stroke, neurodegeneration, infection and trauma. Brain parenchyma is composed of a dense mixture of neuronal and glial cell bodies, together with their intertwined processes. Intracellular components that vary between cells, and can become altered with aging or disease, relate to the cytoplasmic and nucleoplasmic density, nuclear heterochromatin pattern, mitochondria, endoplasmic reticulum and Golgi complex, lysosomes, neurosecretory vesicles, and cytoskeletal elements (actin, intermediate filaments, and microtubules). Applying immunolabeling techniques to visualize membrane-bound or intracellular proteins in neurons and glial cells gives an even better appreciation of the subtle differences unique to these cells across contexts of health and disease. Together, our observations reveal how simple ultrastructural features can be used to identify specific changes in cell types, their health status, and functional relationships in the brain.
Collapse
|
7
|
Abstract
Unraveling the fine structure of the brain is important to provide a better understanding of its normal and abnormal functioning. Application of high-resolution electron microscopic techniques gives us an unprecedented opportunity to discern details of the brain parenchyma at nanoscale resolution, although identifying different cell types and their unique features in two-dimensional, or three-dimensional images, remains a challenge even to experts in the field. This article provides insights into how to identify the different cell types in the central nervous system, based on nuclear and cytoplasmic features, amongst other unique characteristics. From the basic distinction between neurons and their supporting cells, the glia, to differences in their subcellular compartments, organelles and their interactions, ultrastructural analyses can provide unique insights into the changes in brain function during aging and disease conditions, such as stroke, neurodegeneration, infection and trauma. Brain parenchyma is composed of a dense mixture of neuronal and glial cell bodies, together with their intertwined processes. Intracellular components that vary between cells, and can become altered with aging or disease, relate to the cytoplasmic and nucleoplasmic density, nuclear heterochromatin pattern, mitochondria, endoplasmic reticulum and Golgi complex, lysosomes, neurosecretory vesicles, and cytoskeletal elements (actin, intermediate filaments, and microtubules). Applying immunolabeling techniques to visualize membrane-bound or intracellular proteins in neurons and glial cells gives an even better appreciation of the subtle differences unique to these cells across contexts of health and disease. Together, our observations reveal how simple ultrastructural features can be used to identify specific changes in cell types, their health status, and functional relationships in the brain.
Collapse
Affiliation(s)
- Patrick C Nahirney
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Marie-Eve Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| |
Collapse
|
8
|
Ultrastructure of light-activated axons following optogenetic stimulation to produce late-phase long-term potentiation. PLoS One 2020; 15:e0226797. [PMID: 31940316 PMCID: PMC6961864 DOI: 10.1371/journal.pone.0226797] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 12/04/2019] [Indexed: 12/03/2022] Open
Abstract
Analysis of neuronal compartments has revealed many state-dependent changes in geometry but establishing synapse-specific mechanisms at the nanoscale has proven elusive. We co-expressed channelrhodopsin2-GFP and mAPEX2 in a subset of hippocampal CA3 neurons and used trains of light to induce late-phase long-term potentiation (L-LTP) in area CA1. L-LTP was shown to be specific to the labeled axons by severing CA3 inputs, which prevented back-propagating recruitment of unlabeled axons. Membrane-associated mAPEX2 tolerated microwave-enhanced chemical fixation and drove tyramide signal amplification to deposit Alexa Fluor dyes in the light-activated axons. Subsequent post-embedding immunogold labeling resulted in outstanding ultrastructure and clear distinctions between labeled (activated), and unlabeled axons without obscuring subcellular organelles. The gold-labeled axons in potentiated slices were reconstructed through serial section electron microscopy; presynaptic vesicles and other constituents could be quantified unambiguously. The genetic specification, reliable physiology, and compatibility with established methods for ultrastructural preservation make this an ideal approach to link synapse ultrastructure and function in intact circuits.
Collapse
|
9
|
Affiliation(s)
- Kristen M Harris
- Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, Texas 78712
| |
Collapse
|
10
|
Long-term potentiation expands information content of hippocampal dentate gyrus synapses. Proc Natl Acad Sci U S A 2018; 115:E2410-E2418. [PMID: 29463730 DOI: 10.1073/pnas.1716189115] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
An approach combining signal detection theory and precise 3D reconstructions from serial section electron microscopy (3DEM) was used to investigate synaptic plasticity and information storage capacity at medial perforant path synapses in adult hippocampal dentate gyrus in vivo. Induction of long-term potentiation (LTP) markedly increased the frequencies of both small and large spines measured 30 minutes later. This bidirectional expansion resulted in heterosynaptic counterbalancing of total synaptic area per unit length of granule cell dendrite. Control hemispheres exhibited 6.5 distinct spine sizes for 2.7 bits of storage capacity while LTP resulted in 12.9 distinct spine sizes (3.7 bits). In contrast, control hippocampal CA1 synapses exhibited 4.7 bits with much greater synaptic precision than either control or potentiated dentate gyrus synapses. Thus, synaptic plasticity altered total capacity, yet hippocampal subregions differed dramatically in their synaptic information storage capacity, reflecting their diverse functions and activation histories.
Collapse
|
11
|
Smith HL, Bourne JN, Cao G, Chirillo MA, Ostroff LE, Watson DJ, Harris KM. Mitochondrial support of persistent presynaptic vesicle mobilization with age-dependent synaptic growth after LTP. eLife 2016; 5. [PMID: 27991850 PMCID: PMC5235352 DOI: 10.7554/elife.15275] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 12/16/2016] [Indexed: 12/22/2022] Open
Abstract
Mitochondria support synaptic transmission through production of ATP, sequestration of calcium, synthesis of glutamate, and other vital functions. Surprisingly, less than 50% of hippocampal CA1 presynaptic boutons contain mitochondria, raising the question of whether synapses without mitochondria can sustain changes in efficacy. To address this question, we analyzed synapses from postnatal day 15 (P15) and adult rat hippocampus that had undergone theta-burst stimulation to produce long-term potentiation (TBS-LTP) and compared them to control or no stimulation. At 30 and 120 min after TBS-LTP, vesicles were decreased only in presynaptic boutons that contained mitochondria at P15, and vesicle decrement was greatest in adult boutons containing mitochondria. Presynaptic mitochondrial cristae were widened, suggesting a sustained energy demand. Thus, mitochondrial proximity reflected enhanced vesicle mobilization well after potentiation reached asymptote, in parallel with the apparently silent addition of new dendritic spines at P15 or the silent enlargement of synapses in adults. DOI:http://dx.doi.org/10.7554/eLife.15275.001
Collapse
Affiliation(s)
- Heather L Smith
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, United States
| | - Jennifer N Bourne
- Department of Cell and Developmental Biology, University of Colorado Denver - Anschutz Medical Campus, Aurora, United States
| | - Guan Cao
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, United States
| | - Michael A Chirillo
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, United States
| | - Linnaea E Ostroff
- Center for Neural Science, New York University, Washington, New York
| | - Deborah J Watson
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, United States
| | - Kristen M Harris
- Department of Neuroscience, Center for Learning and Memory, Institute for Neuroscience, University of Texas at Austin, Austin, United States
| |
Collapse
|
12
|
Kuipers J, Kalicharan RD, Wolters AHG, van Ham TJ, Giepmans BNG. Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain. J Vis Exp 2016. [PMID: 27285162 PMCID: PMC4927742 DOI: 10.3791/53635] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae1-7. Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically ~ 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture1-5. Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)8 on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner.
Collapse
|
13
|
Watson DJ, Ostroff L, Cao G, Parker PH, Smith H, Harris KM. LTP enhances synaptogenesis in the developing hippocampus. Hippocampus 2016; 26:560-76. [PMID: 26418237 PMCID: PMC4811749 DOI: 10.1002/hipo.22536] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/20/2015] [Indexed: 12/27/2022]
Abstract
In adult hippocampus, long-term potentiation (LTP) produces synapse enlargement while preventing the formation of new small dendritic spines. Here, we tested how LTP affects structural synaptic plasticity in hippocampal area CA1 of Long-Evans rats at postnatal day 15 (P15). P15 is an age of robust synaptogenesis when less than 35% of dendritic spines have formed. We hypothesized that LTP might therefore have a different effect on synapse structure than in adults. Theta-burst stimulation (TBS) was used to induce LTP at one site and control stimulation was delivered at an independent site, both within s. radiatum of the same hippocampal slice. Slices were rapidly fixed at 5, 30, and 120 min after TBS, and processed for analysis by three-dimensional reconstruction from serial section electron microscopy (3DEM). All findings were compared to hippocampus that was perfusion-fixed (PF) in vivo at P15. Excitatory and inhibitory synapses on dendritic spines and shafts were distinguished from synaptic precursors, including filopodia and surface specializations. The potentiated response plateaued between 5 and 30 min and remained potentiated prior to fixation. TBS resulted in more small spines relative to PF by 30 min. This TBS-related spine increase lasted 120 min, hence, there were substantially more small spines with LTP than in the control or PF conditions. In contrast, control test pulses resulted in spine loss relative to PF by 120 min, but not earlier. The findings provide accurate new measurements of spine and synapse densities and sizes. The added or lost spines had small synapses, took time to form or disappear, and did not result in elevated potentiation or depression at 120 min. Thus, at P15 the spines formed following TBS, or lost with control stimulation, appear to be functionally silent. With TBS, existing synapses were awakened and then new spines formed as potential substrates for subsequent plasticity.
Collapse
Affiliation(s)
- Deborah J. Watson
- Department of Neuroscience, Center for Learning and MemoryInstitute for Neuroscience, University of Texas at AustinAustinTexas78731
| | | | - Guan Cao
- Department of Neuroscience, Center for Learning and MemoryInstitute for Neuroscience, University of Texas at AustinAustinTexas78731
| | - Patrick H. Parker
- Department of Neuroscience, Center for Learning and MemoryInstitute for Neuroscience, University of Texas at AustinAustinTexas78731
| | - Heather Smith
- Department of Neuroscience, Center for Learning and MemoryInstitute for Neuroscience, University of Texas at AustinAustinTexas78731
| | - Kristen M. Harris
- Department of Neuroscience, Center for Learning and MemoryInstitute for Neuroscience, University of Texas at AustinAustinTexas78731
| |
Collapse
|
14
|
Naugle MM, Lozano SA, Guarraci FA, Lindsey LF, Kim JE, Morrison JH, Janssen WG, Yin W, Gore AC. Age and Long-Term Hormone Treatment Effects on the Ultrastructural Morphology of the Median Eminence of Female Rhesus Macaques. Neuroendocrinology 2016; 103:650-64. [PMID: 26536204 PMCID: PMC4860175 DOI: 10.1159/000442015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2015] [Accepted: 10/29/2015] [Indexed: 12/26/2022]
Abstract
The median eminence (ME) of the hypothalamus comprises the hypothalamic nerve terminals, glia (especially tanycytes) and the portal capillary vasculature that transports hypothalamic neurohormones to the anterior pituitary gland. The ultrastructure of the ME is dynamically regulated by hormones and undergoes organizational changes during development and reproductive cycles in adult females, but relatively little is known about the ME during aging, especially in nonhuman primates. Therefore, we used a novel transmission scanning electron microscopy technique to examine the cytoarchitecture of the ME of young and aged female rhesus macaques in a preclinical monkey model of menopausal hormone treatments. Rhesus macaques were ovariectomized and treated for 2 years with vehicle, estradiol (E2), or estradiol + progesterone (E2 + P4). While the overall cytoarchitecture of the ME underwent relatively few changes with age and hormones, changes to some features of neural and glial components near the portal capillaries were observed. Specifically, large neuroterminal size was greater in aged compared to young adult animals, an effect that was mitigated or reversed by E2 alone but not by E2 + P4 treatment. Overall glial size and the density and tissue fraction of the largest subset of glia were greater in aged monkeys, and in some cases reversed by E2 treatment. Mitochondrial size was decreased by E2, but not E2 + P4, only in aged macaques. These results contrast substantially with work in rodents, suggesting that the ME of aging macaques is less vulnerable to age-related disorganization, and that the effects of E2 on monkeys' ME are age specific.
Collapse
Affiliation(s)
| | - Sateria A. Lozano
- Division of Pharmacology & Toxicology, University of Texas at Austin, Austin, TX
| | - Fay A. Guarraci
- Department of Psychology, Southwestern University, Georgetown, TX
| | - Larry F. Lindsey
- Center for Learning and Memory, University of Texas at Austin, Austin, TX
| | - Ji E. Kim
- Division of Pharmacology & Toxicology, University of Texas at Austin, Austin, TX
| | - John H. Morrison
- Fishberg Department of Neuroscience and the Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - William G.M. Janssen
- Fishberg Department of Neuroscience and the Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Weiling Yin
- Division of Pharmacology & Toxicology, University of Texas at Austin, Austin, TX
| | - Andrea C. Gore
- Institute for Neuroscience, University of Texas at Austin, Austin, TX
- Division of Pharmacology & Toxicology, University of Texas at Austin, Austin, TX
- Institute for Cellular & Molecular Biology, University of Texas at Austin, Austin, TX
- Correspondence: Andrea C Gore, PhD, The University of Texas at Austin, 107 West Dean Keeton, C0875, Austin, TX, 78712, USA, ; Tel: +1-512-471-3669; Fax: +1-512-471-5002
| |
Collapse
|
15
|
Treweek JB, Chan KY, Flytzanis NC, Yang B, Deverman BE, Greenbaum A, Lignell A, Xiao C, Cai L, Ladinsky MS, Bjorkman PJ, Fowlkes CC, Gradinaru V. Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping. Nat Protoc 2015; 10:1860-1896. [PMID: 26492141 PMCID: PMC4917295 DOI: 10.1038/nprot.2015.122] [Citation(s) in RCA: 189] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1-2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks.
Collapse
Affiliation(s)
- Jennifer B Treweek
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Ken Y Chan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Nicholas C Flytzanis
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Bin Yang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Benjamin E Deverman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Alon Greenbaum
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Antti Lignell
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Cheng Xiao
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Long Cai
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Mark S Ladinsky
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Pamela J Bjorkman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Charless C Fowlkes
- Department of Computer Science, University of California, Irvine, California, USA
| | - Viviana Gradinaru
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| |
Collapse
|
16
|
DeFelipe J. The anatomical problem posed by brain complexity and size: a potential solution. Front Neuroanat 2015; 9:104. [PMID: 26347617 PMCID: PMC4542575 DOI: 10.3389/fnana.2015.00104] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Accepted: 07/21/2015] [Indexed: 01/08/2023] Open
Abstract
Over the years the field of neuroanatomy has evolved considerably but unraveling the extraordinary structural and functional complexity of the brain seems to be an unattainable goal, partly due to the fact that it is only possible to obtain an imprecise connection matrix of the brain. The reasons why reaching such a goal appears almost impossible to date is discussed here, together with suggestions of how we could overcome this anatomical problem by establishing new methodologies to study the brain and by promoting interdisciplinary collaboration. Generating a realistic computational model seems to be the solution rather than attempting to fully reconstruct the whole brain or a particular brain region.
Collapse
Affiliation(s)
- Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales (Centro de Tecnología Biomédica: UPM), Instituto Cajal (CSIC) and CIBERNED Madrid, Spain
| |
Collapse
|
17
|
Kuwajima M, Spacek J, Harris KM. Beyond counts and shapes: studying pathology of dendritic spines in the context of the surrounding neuropil through serial section electron microscopy. Neuroscience 2013; 251:75-89. [PMID: 22561733 PMCID: PMC3535574 DOI: 10.1016/j.neuroscience.2012.04.061] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2012] [Revised: 04/16/2012] [Accepted: 04/20/2012] [Indexed: 02/06/2023]
Abstract
Because dendritic spines are the sites of excitatory synapses, pathological changes in spine morphology should be considered as part of pathological changes in neuronal circuitry in the forms of synaptic connections and connectivity strength. In the past, spine pathology has usually been measured by changes in their number or shape. A more complete understanding of spine pathology requires visualization at the nanometer level to analyze how the changes in number and size affect their presynaptic partners and associated astrocytic processes, as well as organelles and other intracellular structures. Currently, serial section electron microscopy (ssEM) offers the best approach to address this issue because of its ability to image the volume of brain tissue at the nanometer resolution. Renewed interest in ssEM has led to recent technological advances in imaging techniques and improvements in computational tools indispensable for three-dimensional analyses of brain tissue volumes. Here we consider the small but growing literature that has used ssEM analysis to unravel ultrastructural changes in neuropil including dendritic spines. These findings have implications in altered synaptic connectivity and cell biological processes involved in neuropathology, and serve as anatomical substrates for understanding changes in network activity that may underlie clinical symptoms.
Collapse
Affiliation(s)
- Masaaki Kuwajima
- Center for Learning and Memory, The University of Texas at Austin
| | - Josef Spacek
- Charles University Prague, Faculty of Medicine in Hradec Kralove, Czech Republic
| | - Kristen M. Harris
- Center for Learning and Memory, The University of Texas at Austin
- Section of Neurobiology, The University of Texas at Austin
| |
Collapse
|
18
|
Kuwajima M, Mendenhall JM, Lindsey LF, Harris KM. Automated transmission-mode scanning electron microscopy (tSEM) for large volume analysis at nanoscale resolution. PLoS One 2013; 8:e59573. [PMID: 23555711 PMCID: PMC3608656 DOI: 10.1371/journal.pone.0059573] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Accepted: 02/15/2013] [Indexed: 11/19/2022] Open
Abstract
Transmission-mode scanning electron microscopy (tSEM) on a field emission SEM platform was developed for efficient and cost-effective imaging of circuit-scale volumes from brain at nanoscale resolution. Image area was maximized while optimizing the resolution and dynamic range necessary for discriminating key subcellular structures, such as small axonal, dendritic and glial processes, synapses, smooth endoplasmic reticulum, vesicles, microtubules, polyribosomes, and endosomes which are critical for neuronal function. Individual image fields from the tSEM system were up to 4,295 µm2 (65.54 µm per side) at 2 nm pixel size, contrasting with image fields from a modern transmission electron microscope (TEM) system, which were only 66.59 µm2 (8.160 µm per side) at the same pixel size. The tSEM produced outstanding images and had reduced distortion and drift relative to TEM. Automated stage and scan control in tSEM easily provided unattended serial section imaging and montaging. Lens and scan properties on both TEM and SEM platforms revealed no significant nonlinear distortions within a central field of ∼100 µm2 and produced near-perfect image registration across serial sections using the computational elastic alignment tool in Fiji/TrakEM2 software, and reliable geometric measurements from RECONSTRUCT™ or Fiji/TrakEM2 software. Axial resolution limits the analysis of small structures contained within a section (∼45 nm). Since this new tSEM is non-destructive, objects within a section can be explored at finer axial resolution in TEM tomography with current methods. Future development of tSEM tomography promises thinner axial resolution producing nearly isotropic voxels and should provide within-section analyses of structures without changing platforms. Brain was the test system given our interest in synaptic connectivity and plasticity; however, the new tSEM system is readily applicable to other biological systems.
Collapse
Affiliation(s)
- Masaaki Kuwajima
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States of America
| | - John M. Mendenhall
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States of America
| | - Laurence F. Lindsey
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States of America
| | - Kristen M. Harris
- Center for Learning and Memory, The University of Texas at Austin, Austin, Texas, United States of America
- Section of Neurobiology, The University of Texas at Austin, Austin, Texas, United States of America
- * E-mail:
| |
Collapse
|