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Prochukhan N, Rafferty A, Canavan M, Daly D, Selkirk A, Rameshkumar S, Morris MA. Development and application of a 3D image analysis strategy for focused ion beam - Scanning electron microscopy tomography of porous soft materials. Microsc Res Tech 2024; 87:1335-1347. [PMID: 38362795 DOI: 10.1002/jemt.24514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/20/2024] [Accepted: 01/31/2024] [Indexed: 02/17/2024]
Abstract
In recent years, the potential of porous soft materials in various device technologies has increased in importance due to applications in fields, such as wearable electronics, medicine, and transient devices. However, understanding the 3-dimensional architecture of porous soft materials at the microscale remains a challenge. Herein, we present a method to structurally analyze soft materials using Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) tomography. Two materials, polymethyl methacrylate (PMMA) membrane and pine wood veneer were chosen as test-cases. FIB-SEM was successfully used to reconstruct the true topography of these materials in 3D. Structural and physical properties were subsequently deduced from the rendered 3D models. The methodology used segmentation, coupled with optimized thresholding, image processing, and reconstruction protocols. The 3D models generated pore size distribution, pore inter-connectivity, tortuosity, thickness, and curvature data. It was shown that FIB-SEM tomography provides both an informative and visual depiction of structure. To evaluate and validate the FIB-SEM reconstructions, porous properties were generated from the physical property analysis techniques, gas adsorption analysis using Brunauer-Emmett-Teller (BET) surface area analysis and mercury intrusion porosimetry (MIP) analysis. In general, the data obtained from the FIB-SEM reconstructions was well-matched with the physical data. RESEARCH HIGHLIGHTS: Porous specimens of both synthetic and biological nature, a poly(methyl methacrylate) membrane and a pine veneer respectively, are reconstructed via FIB-SEM tomography without resin-embedding. Different thresholding and reconstruction methods are explored whereby shadowing artifacts are present with the aid of free open-source software. Reconstruction data is compared to physical data: MIP, gas adsorption isotherms which are analyzed via BET and Barrett-Joyner-Halenda (BJH) analysis to yield a full picture of the materials.
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Affiliation(s)
- Nadezda Prochukhan
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
- BiOrbic, Bioeconomy SFI Research Centre, University College Dublin, Dublin, Ireland
| | - Aran Rafferty
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
| | - Megan Canavan
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
| | - Dermot Daly
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
| | - Andrew Selkirk
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
| | - Saranya Rameshkumar
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
- BiOrbic, Bioeconomy SFI Research Centre, University College Dublin, Dublin, Ireland
| | - Michael A Morris
- School of Chemistry, Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) and Advanced Materials and Bioengineering Research (AMBER) Research Centres, Trinity College, Dublin, Ireland
- BiOrbic, Bioeconomy SFI Research Centre, University College Dublin, Dublin, Ireland
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Parlakgül G, Pang S, Artico LL, Min N, Cagampan E, Villa R, Goncalves RLS, Lee GY, Xu CS, Hotamışlıgil GS, Arruda AP. Spatial mapping of hepatic ER and mitochondria architecture reveals zonated remodeling in fasting and obesity. Nat Commun 2024; 15:3982. [PMID: 38729945 PMCID: PMC11087507 DOI: 10.1038/s41467-024-48272-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 04/26/2024] [Indexed: 05/12/2024] Open
Abstract
The hepatocytes within the liver present an immense capacity to adapt to changes in nutrient availability. Here, by using high resolution volume electron microscopy, we map how hepatic subcellular spatial organization is regulated during nutritional fluctuations and as a function of liver zonation. We identify that fasting leads to remodeling of endoplasmic reticulum (ER) architecture in hepatocytes, characterized by the induction of single rough ER sheet around the mitochondria, which becomes larger and flatter. These alterations are enriched in periportal and mid-lobular hepatocytes but not in pericentral hepatocytes. Gain- and loss-of-function in vivo models demonstrate that the Ribosome receptor binding protein1 (RRBP1) is required to enable fasting-induced ER sheet-mitochondria interactions and to regulate hepatic fatty acid oxidation. Endogenous RRBP1 is enriched around periportal and mid-lobular regions of the liver. In obesity, ER-mitochondria interactions are distinct and fasting fails to induce rough ER sheet-mitochondrion interactions. These findings illustrate the importance of a regulated molecular architecture for hepatocyte metabolic flexibility.
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Affiliation(s)
- Güneş Parlakgül
- Department of Molecular Metabolism and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA, USA
| | - Song Pang
- HHMI Janelia Research Campus, Ashburn, VA, USA
- Yale School of Medicine, New Haven, CT, USA
| | - Leonardo L Artico
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA, USA
| | - Nina Min
- Department of Molecular Metabolism and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Erika Cagampan
- Department of Molecular Metabolism and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Reyna Villa
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA, USA
| | - Renata L S Goncalves
- Department of Molecular Metabolism and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Grace Yankun Lee
- Department of Molecular Metabolism and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - C Shan Xu
- HHMI Janelia Research Campus, Ashburn, VA, USA
- Department of Cellular & Molecular Physiology, Yale School of Medicine, New Haven, CT, USA
| | - Gökhan S Hotamışlıgil
- Department of Molecular Metabolism and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Ana Paula Arruda
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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Müller A, Schmidt D, Albrecht JP, Rieckert L, Otto M, Galicia Garcia LE, Fabig G, Solimena M, Weigert M. Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets. Nat Protoc 2024; 19:1436-1466. [PMID: 38424188 DOI: 10.1038/s41596-024-00957-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 11/24/2023] [Indexed: 03/02/2024]
Abstract
Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and spatial analysis is necessary. Here we describe a practical and annotation-efficient pipeline for organelle-specific segmentation, spatial analysis and visualization of large volume electron microscopy datasets using freely available, user-friendly software tools that can be run on a single standard workstation. The procedures are aimed at researchers in the life sciences with modest computational expertise, who use volume electron microscopy and need to generate three-dimensional (3D) segmentation labels for different types of cell organelles while minimizing manual annotation efforts, to analyze the spatial interactions between organelle instances and to visualize the 3D segmentation results. We provide detailed guidelines for choosing well-suited segmentation tools for specific cell organelles, and to bridge compatibility issues between freely available open-source tools, we distribute the critical steps as easily installable Album solutions for deep learning segmentation, spatial analysis and 3D rendering. Our detailed description can serve as a reference for similar projects requiring particular strategies for single- or multiple-organelle analysis, which can be achieved with computational resources commonly available to single-user setups.
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Affiliation(s)
- Andreas Müller
- Molecular Diabetology, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany.
- Paul Langerhans Institute Dresden (PLID) of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus and Faculty of Medicine of the TU Dresden, Dresden, Germany.
- German Center for Diabetes Research, Neuherberg, Germany.
| | - Deborah Schmidt
- HELMHOLTZ IMAGING, Max Delbrück Center for Molecular Medicine (MDC) in the Helmholtz Association, Berlin, Germany.
| | - Jan Philipp Albrecht
- HELMHOLTZ IMAGING, Max Delbrück Center for Molecular Medicine (MDC) in the Helmholtz Association, Berlin, Germany
- Humboldt-Universität zu Berlin, Faculty of Mathematics and Natural Sciences, Berlin, Germany
| | - Lucas Rieckert
- HELMHOLTZ IMAGING, Max Delbrück Center for Molecular Medicine (MDC) in the Helmholtz Association, Berlin, Germany
| | - Maximilian Otto
- HELMHOLTZ IMAGING, Max Delbrück Center for Molecular Medicine (MDC) in the Helmholtz Association, Berlin, Germany
| | - Leticia Elizabeth Galicia Garcia
- Molecular Diabetology, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden (PLID) of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus and Faculty of Medicine of the TU Dresden, Dresden, Germany
- German Center for Diabetes Research, Neuherberg, Germany
- DFG Cluster of Excellence 'Physics of Life', TU Dresden, Dresden, Germany
| | - Gunar Fabig
- Experimental Center, Faculty of Medicine Carl Gustav Carus, Dresden, Dresden, Germany
| | - Michele Solimena
- Molecular Diabetology, University Hospital and Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany
- Paul Langerhans Institute Dresden (PLID) of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus and Faculty of Medicine of the TU Dresden, Dresden, Germany
- German Center for Diabetes Research, Neuherberg, Germany
- DFG Cluster of Excellence 'Physics of Life', TU Dresden, Dresden, Germany
| | - Martin Weigert
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
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Sarkar M, Adams F, Dar SA, Penn J, Ji Y, Gundimeda A, Zhu T, Liu C, Hirshy H, Massabuau FCP, O'Hanlon T, Kappers MJ, Ghosh S, Kusch G, Oliver RA. Sub-surface Imaging of Porous GaN Distributed Bragg Reflectors via Backscattered Electrons. Microsc Microanal 2024; 30:208-225. [PMID: 38578956 DOI: 10.1093/mam/ozae028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/09/2024] [Accepted: 03/04/2024] [Indexed: 04/07/2024]
Abstract
In this article, porous GaN distributed Bragg reflectors (DBRs) were fabricated by epitaxy of undoped/doped multilayers followed by electrochemical etching. We present backscattered electron scanning electron microscopy (BSE-SEM) for sub-surface plan-view imaging, enabling efficient, non-destructive pore morphology characterization. In mesoporous GaN DBRs, BSE-SEM images the same branching pores and Voronoi-like domains as scanning transmission electron microscopy. In microporous GaN DBRs, micrographs were dominated by first porous layer features (45 nm to 108 nm sub-surface) with diffuse second layer (153 nm to 216 nm sub-surface) contributions. The optimum primary electron landing energy (LE) for image contrast and spatial resolution in a Zeiss GeminiSEM 300 was approximately 20 keV. BSE-SEM detects porosity ca. 295 nm sub-surface in an overgrown porous GaN DBR, yielding low contrast that is still first porous layer dominated. Imaging through a ca. 190 nm GaN cap improves contrast. We derived image contrast, spatial resolution, and information depth expectations from semi-empirical expressions. These theoretical studies echo our experiments as image contrast and spatial resolution can improve with higher LE, plateauing towards 30 keV. BSE-SEM is predicted to be dominated by the uppermost porous layer's uppermost region, congruent with experimental analysis. Most pertinently, information depth increases with LE, as observed.
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Affiliation(s)
- Maruf Sarkar
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Francesca Adams
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Sidra A Dar
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Jordan Penn
- Department of Physics, University of Oxford, Oxford OX1 3PJ, UK
| | - Yihong Ji
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Abhiram Gundimeda
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | | | | | | | | | - Thomas O'Hanlon
- Plymouth Electron Microscopy Center, University of Plymouth, Plymouth PL4 8AA, UK
| | - Menno J Kappers
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Saptarsi Ghosh
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Gunnar Kusch
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
| | - Rachel A Oliver
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, UK
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Liao YC, Pang S, Li WP, Shtengel G, Choi H, Schaefer K, Xu CS, Lippincott-Schwartz J. COPII with ALG2 and ESCRTs control lysosome-dependent microautophagy of ER exit sites. Dev Cell 2024:S1534-5807(24)00195-3. [PMID: 38593803 DOI: 10.1016/j.devcel.2024.03.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 09/23/2023] [Accepted: 03/12/2024] [Indexed: 04/11/2024]
Abstract
Endoplasmic reticulum exit sites (ERESs) are tubular outgrowths of endoplasmic reticulum that serve as the earliest station for protein sorting and export into the secretory pathway. How these structures respond to different cellular conditions remains unclear. Here, we report that ERESs undergo lysosome-dependent microautophagy when Ca2+ is released by lysosomes in response to nutrient stressors such as mTOR inhibition or amino acid starvation in mammalian cells. Targeting and uptake of ERESs into lysosomes were observed by super-resolution live-cell imaging and focus ion beam scanning electron microscopy (FIB-SEM). The mechanism was ESCRT dependent and required ubiquitinated SEC31, ALG2, and ALIX, with a knockout of ALG2 or function-blocking mutations of ALIX preventing engulfment of ERESs by lysosomes. In vitro, reconstitution of the pathway was possible using lysosomal lipid-mimicking giant unilamellar vesicles and purified recombinant components. Together, these findings demonstrate a pathway of lysosome-dependent ERES microautophagy mediated by COPII, ALG2, and ESCRTS induced by nutrient stress.
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Affiliation(s)
| | - Song Pang
- HHMI Janelia Research Campus, Ashburn, VA, USA; Yale School of Medicine, New Haven, CT, USA
| | - Wei-Ping Li
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | | | - Heejun Choi
- HHMI Janelia Research Campus, Ashburn, VA, USA
| | | | - C Shan Xu
- HHMI Janelia Research Campus, Ashburn, VA, USA; Yale School of Medicine, New Haven, CT, USA
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Zhang Y, Gu S, Du J, Huang G, Shi J, Lu X, Wang J, Yang W, Guo X, Zhao C. Plant microphenotype: from innovative imaging to computational analysis. Plant Biotechnol J 2024; 22:802-818. [PMID: 38217351 PMCID: PMC10955502 DOI: 10.1111/pbi.14244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 11/09/2023] [Accepted: 11/11/2023] [Indexed: 01/15/2024]
Abstract
The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications of microphenotyping in plant science over the past two decades. We then point out several challenges in this field and suggest that cross-scale image acquisition strategies, powerful artificial intelligence algorithms, advanced genetic analysis, and computational phenotyping need to be established and performed to better understand interactions among genotype, environment, and management. Microphenotyping has entered the era of Microphenotyping 3.0 and will largely advance functional genomics and plant science.
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Affiliation(s)
- Ying Zhang
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Shenghao Gu
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jianjun Du
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Guanmin Huang
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jiawei Shi
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xianju Lu
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jinglu Wang
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Wanneng Yang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xinyu Guo
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Chunjiang Zhao
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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Zhao J, Yu X, Shentu X, Li D. The application and development of electron microscopy for three-dimensional reconstruction in life science: a review. Cell Tissue Res 2024; 396:1-18. [PMID: 38416172 DOI: 10.1007/s00441-024-03878-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 02/13/2024] [Indexed: 02/29/2024]
Abstract
Imaging technologies have played a pivotal role in advancing biological research by enabling visualization of biological structures and processes. While traditional electron microscopy (EM) produces two-dimensional images, emerging techniques now allow high-resolution three-dimensional (3D) characterization of specimens in situ, meeting growing needs in molecular and cellular biology. Combining transmission electron microscopy (TEM) with serial sectioning inaugurated 3D imaging, attracting biologists seeking to explore cell ultrastructure and driving advancement of 3D EM reconstruction. By comprehensively and precisely rendering internal structure and distribution, 3D TEM reconstruction provides unparalleled ultrastructural insights into cells and molecules, holding tremendous value for elucidating structure-function relationships and broadly propelling structural biology. Here, we first introduce the principle of 3D reconstruction of cells and tissues by classical approaches in TEM and then discuss modern technologies utilizing TEM and on new SEM-based as well as cryo-electron microscope (cryo-EM) techniques. 3D reconstruction techniques from serial sections, electron tomography (ET), and the recent single-particle analysis (SPA) are examined; the focused ion beam scanning electron microscopy (FIB-SEM), the serial block-face scanning electron microscopy (SBF-SEM), and automatic tape-collecting lathe ultramicrotome (ATUM-SEM) for 3D reconstruction of large volumes are discussed. Finally, we review the challenges and development prospects of these technologies in life science. It aims to provide an informative reference for biological researchers.
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Affiliation(s)
- Jingjing Zhao
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Science, China , Jiliang University, Hangzhou, 310018, China
| | - Xiaoping Yu
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Science, China , Jiliang University, Hangzhou, 310018, China
| | - Xuping Shentu
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Science, China , Jiliang University, Hangzhou, 310018, China
| | - Danting Li
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection and Quarantine, College of Life Science, China , Jiliang University, Hangzhou, 310018, China.
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Fahy K, Kapishnikov S, Donnellan M, McEnroe T, O'Reilly F, Fyans W, Sheridan P. Laboratory based correlative cryo-soft X-ray tomography and cryo-fluorescence microscopy. Methods Cell Biol 2024; 187:293-320. [PMID: 38705628 DOI: 10.1016/bs.mcb.2024.02.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
Cryo-soft X-ray tomography is the unique technology that can image whole intact cells in 3D under normal and pathological conditions without labelling or fixation, at high throughput and spatial resolution. The sample preparation is relatively straightforward; requiring just fast freezing of the specimen before transfer to the microscope for imaging. It is also possible to image chemically fixed samples where necessary. The technique can be correlated with cryo fluorescence microscopy to localize fluorescent proteins to organelles within the whole cell volume. Cryo-correlated light and soft X-ray tomography is particularly useful for the study of gross morphological changes brought about by disease or drugs. For example, viral fluorescent tags can be co-localized to sites of viral replication in the soft X-ray volume. In general this approach is extremely useful in the study of complex 3D organelle structure, nanoparticle uptake or in the detection of rare events in the context of whole cell structure. The main challenge of soft X-ray tomography is that the soft X-ray illumination required for imaging has heretofore only been available at a small number of synchrotron labs worldwide. Recently, a compact device with a footprint small enough to fit in a standard laboratory setting has been deployed ("the SXT-100") and is routinely imaging cryo prepared samples addressing a variety of disease and drug research applications. The SXT-100 facilitates greater access to this powerful technique and greatly increases the scope and throughput of potential research projects. Furthermore, the availability of cryo-soft X-ray tomography in the laboratory will accelerate the development of novel correlative and multimodal workflows by integration with light and electron microscope based approaches. It also allows for co-location of this powerful imaging modality at BSL3 labs or other facilities where safety or intellectual property considerations are paramount. Here we describe the compact SXT-100 microscope along with its novel integrated cryo-fluorescence imaging capability.
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Affiliation(s)
- Kenneth Fahy
- SiriusXT Ltd., Stillorgan Industrial Park, Dublin, Ireland.
| | | | | | - Tony McEnroe
- SiriusXT Ltd., Stillorgan Industrial Park, Dublin, Ireland
| | - Fergal O'Reilly
- SiriusXT Ltd., Stillorgan Industrial Park, Dublin, Ireland; University College Dublin, School of Physics, Dublin, Ireland; University College Dublin, School of Biology and Environmental Sciences, Dublin, Ireland
| | - William Fyans
- SiriusXT Ltd., Stillorgan Industrial Park, Dublin, Ireland
| | - Paul Sheridan
- SiriusXT Ltd., Stillorgan Industrial Park, Dublin, Ireland
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Phan J, Sarmad M, Ruspini L, Kiss G, Lindseth F. Generating 3D images of material microstructures from a single 2D image: a denoising diffusion approach. Sci Rep 2024; 14:6498. [PMID: 38499588 PMCID: PMC10948834 DOI: 10.1038/s41598-024-56910-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 03/12/2024] [Indexed: 03/20/2024] Open
Abstract
Three-dimensional (3D) images provide a comprehensive view of material microstructures, enabling numerical simulations unachievable with two-dimensional (2D) imaging alone. However, obtaining these 3D images can be costly and constrained by resolution limitations. We introduce a novel method capable of generating large-scale 3D images of material microstructures, such as metal or rock, from a single 2D image. Our approach circumvents the need for 3D image data while offering a cost-effective, high-resolution alternative to existing imaging techniques. Our method combines a denoising diffusion probabilistic model with a generative adversarial network framework. To compensate for the lack of 3D training data, we implement chain sampling, a technique that utilizes the 3D intermediate outputs obtained by reversing the diffusion process. During the training phase, these intermediate outputs are guided by a 2D discriminator. This technique facilitates our method's ability to gradually generate 3D images that accurately capture the geometric properties and statistical characteristics of the original 2D input. This study features a comparative analysis of the 3D images generated by our method, SliceGAN (the current state-of-the-art method), and actual 3D micro-CT images, spanning a diverse set of rock and metal types. The results shown an improvement of up to three times in the Frechet inception distance score, a typical metric for evaluating the performance of image generative models, and enhanced accuracy in derived properties compared to SliceGAN. The potential of our method to produce high-resolution and statistically representative 3D images paves the way for new applications in material characterization and analysis domains.
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Affiliation(s)
- Johan Phan
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway.
- Petricore Norway, Trondheim, Norway.
| | - Muhammad Sarmad
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Gabriel Kiss
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Lindseth
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
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10
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Clements J, Goina C, Hubbard PM, Kawase T, Olbris DJ, Otsuna H, Svirskas R, Rokicki K. NeuronBridge: an intuitive web application for neuronal morphology search across large data sets. BMC Bioinformatics 2024; 25:114. [PMID: 38491365 PMCID: PMC10943809 DOI: 10.1186/s12859-024-05732-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/06/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Neuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome's structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities. RESULTS Here, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine. CONCLUSIONS NeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org .
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Affiliation(s)
- Jody Clements
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Cristian Goina
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Philip M Hubbard
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Takashi Kawase
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Donald J Olbris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Hideo Otsuna
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Robert Svirskas
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Konrad Rokicki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA.
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11
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Kuan AT, Bondanelli G, Driscoll LN, Han J, Kim M, Hildebrand DGC, Graham BJ, Wilson DE, Thomas LA, Panzeri S, Harvey CD, Lee WCA. Synaptic wiring motifs in posterior parietal cortex support decision-making. Nature 2024; 627:367-373. [PMID: 38383788 DOI: 10.1038/s41586-024-07088-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 01/17/2024] [Indexed: 02/23/2024]
Abstract
The posterior parietal cortex exhibits choice-selective activity during perceptual decision-making tasks1-10. However, it is not known how this selective activity arises from the underlying synaptic connectivity. Here we combined virtual-reality behaviour, two-photon calcium imaging, high-throughput electron microscopy and circuit modelling to analyse how synaptic connectivity between neurons in the posterior parietal cortex relates to their selective activity. We found that excitatory pyramidal neurons preferentially target inhibitory interneurons with the same selectivity. In turn, inhibitory interneurons preferentially target pyramidal neurons with opposite selectivity, forming an opponent inhibition motif. This motif was present even between neurons with activity peaks in different task epochs. We developed neural-circuit models of the computations performed by these motifs, and found that opponent inhibition between neural populations with opposite selectivity amplifies selective inputs, thereby improving the encoding of trial-type information. The models also predict that opponent inhibition between neurons with activity peaks in different task epochs contributes to creating choice-specific sequential activity. These results provide evidence for how synaptic connectivity in cortical circuits supports a learned decision-making task.
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Affiliation(s)
- Aaron T Kuan
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Giulio Bondanelli
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genoa, Italy
- Department of Excellence for Neural Information Processing, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Laura N Driscoll
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Allen Institute for Neural Dynamics, Allen Institute, Seattle, WA, USA
| | - Julie Han
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Khoury College of Computer Sciences, Northeastern University, Seattle, WA, USA
| | - Minsu Kim
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - David G C Hildebrand
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Laboratory of Neural Systems, The Rockefeller University, New York, NY, USA
| | - Brett J Graham
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Space Telescope Science Institute, Baltimore, MD, USA
| | - Daniel E Wilson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Logan A Thomas
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Biophysics Graduate Group, University of California Berkeley, Berkeley, CA, USA
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genoa, Italy.
- Department of Excellence for Neural Information Processing, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
| | | | - Wei-Chung Allen Lee
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
- FM Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA.
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12
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Lillvis JL, Wang K, Shiozaki HM, Xu M, Stern DL, Dickson BJ. Nested neural circuits generate distinct acoustic signals during Drosophila courtship. Curr Biol 2024; 34:808-824.e6. [PMID: 38295797 DOI: 10.1016/j.cub.2024.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 01/02/2024] [Accepted: 01/08/2024] [Indexed: 02/29/2024]
Abstract
Many motor control systems generate multiple movements using a common set of muscles. How are premotor circuits able to flexibly generate diverse movement patterns? Here, we characterize the neuronal circuits that drive the distinct courtship songs of Drosophila melanogaster. Male flies vibrate their wings toward females to produce two different song modes-pulse and sine song-which signal species identity and male quality. Using cell-type-specific genetic reagents and the connectome, we provide a cellular and synaptic map of the circuits in the male ventral nerve cord that generate these songs and examine how activating or inhibiting each cell type within these circuits affects the song. Our data reveal that the song circuit is organized into two nested feedforward pathways with extensive reciprocal and feedback connections. The larger network produces pulse song, the more complex and ancestral song form. A subset of this network produces sine song, the simpler and more recent form. Such nested organization may be a common feature of motor control circuits in which evolution has layered increasing flexibility onto a basic movement pattern.
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Affiliation(s)
- Joshua L Lillvis
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr., Ashburn, VA 20147, USA.
| | - Kaiyu Wang
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr., Ashburn, VA 20147, USA; Lingang Laboratory, Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201602, China
| | - Hiroshi M Shiozaki
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr., Ashburn, VA 20147, USA
| | - Min Xu
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr., Ashburn, VA 20147, USA
| | - David L Stern
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr., Ashburn, VA 20147, USA
| | - Barry J Dickson
- Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Dr., Ashburn, VA 20147, USA; Queensland Brain Institute, University of Queensland, St. Lucia, QLD 4067, Australia.
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13
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Zelinger E, Brumfeld V, Rechav K, Waiger D, Kossovsky T, Heifetz Y. Three-dimensional correlative microscopy of the Drosophila female reproductive tract reveals modes of communication in seminal receptacle sperm storage. Commun Biol 2024; 7:155. [PMID: 38321098 PMCID: PMC10847118 DOI: 10.1038/s42003-024-05829-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/17/2024] [Indexed: 02/08/2024] Open
Abstract
In many taxa, females store sperm in specialized storage organs. Most insect sperm storage organs have a tubular structure, typically consisting of a central lumen surrounded by epithelial cells. These specialized tubules perform the essential tasks of transporting sperm through the female reproductive tract and supporting long-term sperm survival and function. Little is known about the way in which female sperm storage organs provide an environment conducive to sperm survival. We address this using a combined light microscopy, micro computed tomography (microCT), and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) approach for high-resolution correlative three-dimensional imaging to advance our understanding of sperm-female interactions in Drosophila melanogaster. Using this multimodal approach, we were able to scan the lower female reproductive tract and distal portion of the seminal receptacle at low magnification, and to subsequently zoom in for further analysis on an ultrastructural level. Our findings highlight aspects of the way in which the seminal receptacle keeps sperm viable in the lumen, and set the stage for further studies. The methods developed are suitable not only for Drosophila but also for other organisms with soft, delicate tissues.
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Affiliation(s)
- Einat Zelinger
- Department of Entomology, The Hebrew University, Rehovot, Israel
- Center for Scientific Imaging, The Hebrew University, Rehovot, Israel
| | - Vlad Brumfeld
- Chemical Research Support Department, Weizmann Institute, Rehovot, Israel
| | - Katya Rechav
- Chemical Research Support Department, Weizmann Institute, Rehovot, Israel
| | - Daniel Waiger
- Center for Scientific Imaging, The Hebrew University, Rehovot, Israel
| | - Tally Kossovsky
- Center for Scientific Imaging, The Hebrew University, Rehovot, Israel
| | - Yael Heifetz
- Department of Entomology, The Hebrew University, Rehovot, Israel.
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14
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McCafferty CL, Klumpe S, Amaro RE, Kukulski W, Collinson L, Engel BD. Integrating cellular electron microscopy with multimodal data to explore biology across space and time. Cell 2024; 187:563-584. [PMID: 38306982 DOI: 10.1016/j.cell.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/03/2024] [Accepted: 01/03/2024] [Indexed: 02/04/2024]
Abstract
Biology spans a continuum of length and time scales. Individual experimental methods only glimpse discrete pieces of this spectrum but can be combined to construct a more holistic view. In this Review, we detail the latest advancements in volume electron microscopy (vEM) and cryo-electron tomography (cryo-ET), which together can visualize biological complexity across scales from the organization of cells in large tissues to the molecular details inside native cellular environments. In addition, we discuss emerging methodologies for integrating three-dimensional electron microscopy (3DEM) imaging with multimodal data, including fluorescence microscopy, mass spectrometry, single-particle analysis, and AI-based structure prediction. This multifaceted approach fills gaps in the biological continuum, providing functional context, spatial organization, molecular identity, and native interactions. We conclude with a perspective on incorporating diverse data into computational simulations that further bridge and extend length scales while integrating the dimension of time.
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Affiliation(s)
| | - Sven Klumpe
- Research Group CryoEM Technology, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.
| | - Rommie E Amaro
- Department of Molecular Biology, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Wanda Kukulski
- Institute of Biochemistry and Molecular Medicine, University of Bern, Bühlstrasse 28, 3012 Bern, Switzerland.
| | - Lucy Collinson
- Electron Microscopy Science Technology Platform, Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
| | - Benjamin D Engel
- Biozentrum, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland.
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15
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Obara CJ, Nixon-Abell J, Moore AS, Riccio F, Hoffman DP, Shtengel G, Xu CS, Schaefer K, Pasolli HA, Masson JB, Hess HF, Calderon CP, Blackstone C, Lippincott-Schwartz J. Motion of VAPB molecules reveals ER-mitochondria contact site subdomains. Nature 2024; 626:169-176. [PMID: 38267577 PMCID: PMC10830423 DOI: 10.1038/s41586-023-06956-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 12/08/2023] [Indexed: 01/26/2024]
Abstract
To coordinate cellular physiology, eukaryotic cells rely on the rapid exchange of molecules at specialized organelle-organelle contact sites1,2. Endoplasmic reticulum-mitochondrial contact sites (ERMCSs) are particularly vital communication hubs, playing key roles in the exchange of signalling molecules, lipids and metabolites3,4. ERMCSs are maintained by interactions between complementary tethering molecules on the surface of each organelle5,6. However, due to the extreme sensitivity of these membrane interfaces to experimental perturbation7,8, a clear understanding of their nanoscale organization and regulation is still lacking. Here we combine three-dimensional electron microscopy with high-speed molecular tracking of a model organelle tether, Vesicle-associated membrane protein (VAMP)-associated protein B (VAPB), to map the structure and diffusion landscape of ERMCSs. We uncovered dynamic subdomains within VAPB contact sites that correlate with ER membrane curvature and undergo rapid remodelling. We show that VAPB molecules enter and leave ERMCSs within seconds, despite the contact site itself remaining stable over much longer time scales. This metastability allows ERMCSs to remodel with changes in the physiological environment to accommodate metabolic needs of the cell. An amyotrophic lateral sclerosis-associated mutation in VAPB perturbs these subdomains, likely impairing their remodelling capacity and resulting in impaired interorganelle communication. These results establish high-speed single-molecule imaging as a new tool for mapping the structure of contact site interfaces and reveal that the diffusion landscape of VAPB at contact sites is a crucial component of ERMCS homeostasis.
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Affiliation(s)
| | - Jonathon Nixon-Abell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
- Cambridge Institute for Medical Research (CIMR), Cambridge, UK
| | - Andrew S Moore
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Federica Riccio
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
- Centre for Gene Therapy & Regenerative Medicine, King's College London, London, UK
| | - David P Hoffman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- 10x Genomics, Pleasanton, CA, USA
| | - Gleb Shtengel
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - C Shan Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT, USA
| | - Kathy Schaefer
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - H Amalia Pasolli
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jean-Baptiste Masson
- Decision and Bayesian Computation, Neuroscience, & Computational Biology Departments, CNRS UMR 3751, Institut Pasteur, Université de Paris, Paris, France
| | - Harald F Hess
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Christopher P Calderon
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
- Ursa Analytics, Inc., Denver, CO, USA
| | - Craig Blackstone
- Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD, USA
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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16
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Schubert PJ, Saxena R, Kornfeld J. DeepFocus: fast focus and astigmatism correction for electron microscopy. Nat Commun 2024; 15:948. [PMID: 38296974 PMCID: PMC10830472 DOI: 10.1038/s41467-024-45042-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 01/10/2024] [Indexed: 02/02/2024] Open
Abstract
High-throughput 2D and 3D scanning electron microscopy, which relies on automation and dependable control algorithms, requires high image quality with minimal human intervention. Classical focus and astigmatism correction algorithms attempt to explicitly model image formation and subsequently aberration correction. Such models often require parameter adjustments by experts when deployed to new microscopes, challenging samples, or imaging conditions to prevent unstable convergence, making them hard to use in practice or unreliable. Here, we introduce DeepFocus, a purely data-driven method for aberration correction in scanning electron microscopy. DeepFocus works under very low signal-to-noise ratio conditions, reduces processing times by more than an order of magnitude compared to the state-of-the-art method, rapidly converges within a large aberration range, and is easily recalibrated to different microscopes or challenging samples.
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Affiliation(s)
- P J Schubert
- Max Planck Institute for Biological Intelligence, Martinsried, 82152, Germany
| | - R Saxena
- Max Planck Institute for Biological Intelligence, Martinsried, 82152, Germany
| | - J Kornfeld
- Max Planck Institute for Biological Intelligence, Martinsried, 82152, Germany.
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17
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Maeshima K, Iida S, Shimazoe MA, Tamura S, Ide S. Is euchromatin really open in the cell? Trends Cell Biol 2024; 34:7-17. [PMID: 37385880 DOI: 10.1016/j.tcb.2023.05.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 05/16/2023] [Accepted: 05/19/2023] [Indexed: 07/01/2023]
Abstract
Genomic DNA is wrapped around a core histone octamer and forms a nucleosome. In higher eukaryotic cells, strings of nucleosomes are irregularly folded as chromatin domains that act as functional genome units. According to a typical textbook model, chromatin can be categorized into two types, euchromatin and heterochromatin, based on its degree of compaction. Euchromatin is open, while heterochromatin is closed and condensed. However, is euchromatin really open in the cell? New evidence from genomics and advanced imaging studies has revealed that euchromatin consists of condensed liquid-like domains. Condensed chromatin seems to be the default chromatin state in higher eukaryotic cells. We discuss this novel view of euchromatin in the cell and how the revealed organization is relevant to genome functions.
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Affiliation(s)
- Kazuhiro Maeshima
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan; Graduate Institute for Advanced Studies, SOKENDAI, Mishima, Shizuoka 411-8540, Japan.
| | - Shiori Iida
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan; Graduate Institute for Advanced Studies, SOKENDAI, Mishima, Shizuoka 411-8540, Japan
| | - Masa A Shimazoe
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan; Graduate Institute for Advanced Studies, SOKENDAI, Mishima, Shizuoka 411-8540, Japan
| | - Sachiko Tamura
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Satoru Ide
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan; Graduate Institute for Advanced Studies, SOKENDAI, Mishima, Shizuoka 411-8540, Japan
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18
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McLaughlin MR, Weaver SA, Syed F, Evans-Molina C. Advanced Imaging Techniques for the Characterization of Subcellular Organelle Structure in Pancreatic Islet β Cells. Compr Physiol 2023; 14:5243-5267. [PMID: 38158370 DOI: 10.1002/cphy.c230002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Type 2 diabetes (T2D) affects more than 32.3 million individuals in the United States, creating an economic burden of nearly $966 billion in 2021. T2D results from a combination of insulin resistance and inadequate insulin secretion from the pancreatic β cell. However, genetic and physiologic data indicate that defects in β cell function are the chief determinant of whether an individual with insulin resistance will progress to a diagnosis of T2D. The subcellular organelles of the insulin secretory pathway, including the endoplasmic reticulum, Golgi apparatus, and secretory granules, play a critical role in maintaining the heavy biosynthetic burden of insulin production, processing, and secretion. In addition, the mitochondria enable the process of insulin release by integrating the metabolism of nutrients into energy output. Advanced imaging techniques are needed to determine how changes in the structure and composition of these organelles contribute to the loss of insulin secretory capacity in the β cell during T2D. Several microscopy techniques, including electron microscopy, fluorescence microscopy, and soft X-ray tomography, have been utilized to investigate the structure-function relationship within the β cell. In this overview article, we will detail the methodology, strengths, and weaknesses of each approach. © 2024 American Physiological Society. Compr Physiol 14:5243-5267, 2024.
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Affiliation(s)
- Madeline R McLaughlin
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Staci A Weaver
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- The Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Farooq Syed
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- The Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Carmella Evans-Molina
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- The Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Herman B Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Anatomy, Cell Biology, and Physiology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Roudebush VA Medical Center, Indianapolis, Indiana, USA
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19
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Chen X, Godel B, Verrall M. Comparison of Laboratory Diffraction Contrast Tomography and Electron Backscatter Diffraction Results: Application to Naturally Occurring Chromites. Microsc Microanal 2023; 29:1901-1920. [PMID: 38064652 DOI: 10.1093/micmic/ozad130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 10/09/2023] [Accepted: 11/02/2023] [Indexed: 12/23/2023]
Abstract
Understanding how minerals are spatially distributed within natural materials and their textures is indispensable to understanding the fundamental processes of how these materials form and how they will behave from a mining engineering perspective. In the past few years, laboratory diffraction contrast tomography (LabDCT) has emerged as a nondestructive technique for 3D mapping of crystallographic orientations in polycrystalline samples. In this study, we demonstrate the application of LabDCT on both chromite sand and a complex chromitite sample from the Merensky Reef (Bushveld Complex, South Africa). Both samples were scanned using LabDCT and Electron Backscatter Diffraction (EBSD), and the obtained results were rigorously evaluated using a comprehensive set of qualitative and quantitative characterization techniques. The quality of LabDCT results was accessed by using the "completeness" value, while the inaccuracies were thoroughly discussed, along with proposed potential solutions. The results indicate that the grain orientations obtained from LabDCT are comparable to that of 2D EBSD but have the advantage of collecting true 3D size, shape, and textural information. This study highlights the significant contribution of LabDCT in the understanding of complex rock materials from an earth science perspective, particularly in characterizing mineral texture and crystallography in 3D.
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Affiliation(s)
- Xiao Chen
- CSIRO Mineral Resources, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, WA 6151, Australia
| | - Belinda Godel
- CSIRO Mineral Resources, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, WA 6151, Australia
| | - Michael Verrall
- CSIRO Mineral Resources, Australian Resources Research Centre, 26 Dick Perry Avenue, Kensington, WA 6151, Australia
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20
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Weisbord I, Segal-Peretz T. Revealing the 3D Structure of Block Copolymers with Electron Microscopy: Current Status and Future Directions. ACS Appl Mater Interfaces 2023; 15:58003-58022. [PMID: 37338172 DOI: 10.1021/acsami.3c02956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2023]
Abstract
Block copolymers (BCPs) are considered model systems for understanding and utilizing self-assembly in soft matter. Their tunable nanometric structure and composition enable comprehensive studies of self-assembly processes as well as make them relevant materials in diverse applications. A key step in developing and controlling BCP nanostructures is a full understanding of their three-dimensional (3D) structure and how this structure is affected by the BCP chemistry, confinement, boundary conditions, and the self-assembly evolution and dynamics. Electron microscopy (EM) is a leading method in BCP 3D characterization owing to its high resolution in imaging nanosized structures. Here we discuss the two main 3D EM methods: namely, transmission EM tomography and slice and view scanning EM tomography. We present each method's principles, examine their strengths and weaknesses, and discuss ways researchers have devised to overcome some of the challenges in BCP 3D characterization with EM- from specimen preparation to imaging radiation-sensitive materials. Importantly, we review current and new cutting-edge EM methods such as direct electron detectors, energy dispersive X-ray spectroscopy of soft matter, high temporal rate imaging, and single-particle analysis that have great potential for expanding the BCP understanding through EM in the future.
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Affiliation(s)
- Inbal Weisbord
- Chemical Engineering Department, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - Tamar Segal-Peretz
- Chemical Engineering Department, Technion-Israel Institute of Technology, Haifa 3200003, Israel
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21
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Ezzedine JA, Uwizeye C, Si Larbi G, Villain G, Louwagie M, Schilling M, Hagenmuller P, Gallet B, Stewart A, Petroutsos D, Devime F, Salze P, Liger L, Jouhet J, Dumont M, Ravanel S, Amato A, Valay JG, Jouneau PH, Falconet D, Maréchal E. Adaptive traits of cysts of the snow alga Sanguina nivaloides unveiled by 3D subcellular imaging. Nat Commun 2023; 14:7500. [PMID: 37980360 PMCID: PMC10657455 DOI: 10.1038/s41467-023-43030-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 10/26/2023] [Indexed: 11/20/2023] Open
Abstract
Sanguina nivaloides is the main alga forming red snowfields in high mountains and Polar Regions. It is non-cultivable. Analysis of environmental samples by X-ray tomography, focused-ion-beam scanning-electron-microscopy, physicochemical and physiological characterization reveal adaptive traits accounting for algal capacity to reside in snow. Cysts populate liquid water at the periphery of ice, are photosynthetically active, can survive for months, and are sensitive to freezing. They harbor a wrinkled plasma membrane expanding the interface with environment. Ionomic analysis supports a cell efflux of K+, and assimilation of phosphorus. Glycerolipidomic analysis confirms a phosphate limitation. The chloroplast contains thylakoids oriented in all directions, fixes carbon in a central pyrenoid and produces starch in peripheral protuberances. Analysis of cells kept in the dark shows that starch is a short-term carbon storage. The biogenesis of cytosolic droplets shows that they are loaded with triacylglycerol and carotenoids for long-term carbon storage and protection against oxidative stress.
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Affiliation(s)
- Jade A Ezzedine
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Clarisse Uwizeye
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Grégory Si Larbi
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Gaelle Villain
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Mathilde Louwagie
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Marion Schilling
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Pascal Hagenmuller
- Centre d'Etudes de la Neige, Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, 38000, Grenoble, France
| | - Benoît Gallet
- Institut de Biologie Structurale, Centre National de la Recherche Scientifique, Université Grenoble Alpes, Commissariat à l'Energie Atomique et aux Energies Alternatives; IRIG, 71 avenue des Martyrs, 38000, Grenoble, France
| | - Adeline Stewart
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Dimitris Petroutsos
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Fabienne Devime
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Pascal Salze
- Jardin du Lautaret, Université Grenoble-Alpes, Centre National de la Recherche Scientifique; 2233 rue de la piscine, Domaine Universitaire, 38610, Gières, France
| | - Lucie Liger
- Jardin du Lautaret, Université Grenoble-Alpes, Centre National de la Recherche Scientifique; 2233 rue de la piscine, Domaine Universitaire, 38610, Gières, France
| | - Juliette Jouhet
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Marie Dumont
- Centre d'Etudes de la Neige, Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, 38000, Grenoble, France
| | - Stéphane Ravanel
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Alberto Amato
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Jean-Gabriel Valay
- Jardin du Lautaret, Université Grenoble-Alpes, Centre National de la Recherche Scientifique; 2233 rue de la piscine, Domaine Universitaire, 38610, Gières, France
| | - Pierre-Henri Jouneau
- Laboratoire Modélisation et Exploration des Matériaux, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Denis Falconet
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France
| | - Eric Maréchal
- Laboratoire de Physiologie Cellulaire et Végétale, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Commissariat à l'Energie Atomique et aux Energies Alternatives, Université Grenoble Alpes; IRIG, CEA-Grenoble, 17 avenue des Martyrs, 38000, Grenoble, France.
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22
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Chua NJ, Makarova AA, Gunn P, Villani S, Cohen B, Thasin M, Wu J, Shefter D, Pang S, Xu CS, Hess HF, Polilov AA, Chklovskii DB. A complete reconstruction of the early visual system of an adult insect. Curr Biol 2023; 33:4611-4623.e4. [PMID: 37774707 DOI: 10.1016/j.cub.2023.09.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 10/01/2023]
Abstract
For most model organisms in neuroscience, research into visual processing in the brain is difficult because of a lack of high-resolution maps that capture complex neuronal circuitry. The microinsect Megaphragma viggianii, because of its small size and non-trivial behavior, provides a unique opportunity for tractable whole-organism connectomics. We image its whole head using serial electron microscopy. We reconstruct its compound eye and analyze the optical properties of the ommatidia as well as the connectome of the first visual neuropil-the lamina. Compared with the fruit fly and the honeybee, Megaphragma visual system is highly simplified: it has 29 ommatidia per eye and 6 lamina neuron types. We report features that are both stereotypical among most ommatidia and specialized to some. By identifying the "barebones" circuits critical for flying insects, our results will facilitate constructing computational models of visual processing in insects.
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Affiliation(s)
- Nicholas J Chua
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA; Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | | | - Pat Gunn
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Sonia Villani
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Ben Cohen
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Myisha Thasin
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Jingpeng Wu
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Deena Shefter
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA
| | - Song Pang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - C Shan Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Harald F Hess
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Alexey A Polilov
- Faculty of Biology, Lomonosov Moscow State University, Moscow 119991, Russia
| | - Dmitri B Chklovskii
- Center for Computational Neuroscience, Flatiron Institute, New York, NY 10010, USA; Neuroscience Institute, New York University Langone Medical Center, New York, NY 10016, USA.
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23
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Wang X, Huang R, Wang Y, Zhou W, Hu Y, Yao Y, Cheng K, Li X, Xu B, Zhang J, Xu Y, Zeng F, Zhu Y, Chen XW. Manganese regulation of COPII condensation controls circulating lipid homeostasis. Nat Cell Biol 2023; 25:1650-1663. [PMID: 37884645 DOI: 10.1038/s41556-023-01260-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 09/18/2023] [Indexed: 10/28/2023]
Abstract
Precise control of circulating lipids is instrumental in health and disease. Bulk lipids, carried by specialized lipoproteins, are secreted into the circulation, initially via the coat protein complex II (COPII). How the universal COPII machinery accommodates the abundant yet unconventional lipoproteins remains unclear, let alone its therapeutic translation. Here we report that COPII uses manganese-tuning, self-constrained condensation to selectively drive lipoprotein delivery and set lipid homeostasis in vivo. Serendipitously, adenovirus hijacks the condensation-based transport mechanism, thus enabling the identification of cytosolic manganese as an unexpected control signal. Manganese directly binds the inner COPII coat and enhances its condensation, thereby shifting the assembly-versus-dynamics balance of the transport machinery. Manganese can be mobilized from mitochondria stores to signal COPII, and selectively controls lipoprotein secretion with a distinctive, bell-shaped function. Consequently, dietary titration of manganese enables tailored lipid management that counters pathological dyslipidaemia and atherosclerosis, implicating a condensation-targeting strategy with broad therapeutic potential for cardio-metabolic health.
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Affiliation(s)
- Xiao Wang
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China.
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China.
- PKU-THU Joint Center for Life Sciences, Peking University, Beijing, China.
| | - Runze Huang
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Yawei Wang
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- PKU-THU Joint Center for Life Sciences, Peking University, Beijing, China
| | - Wenjing Zhou
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Yating Hu
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Yuanhang Yao
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Kunlun Cheng
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xin Li
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Bolin Xu
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jie Zhang
- Department of Clinical Research Center, Dazhou Hospital, Dazhou, Sichuan, China
| | - Yaowen Xu
- Department of Clinical Research Center, Dazhou Hospital, Dazhou, Sichuan, China
| | - Fanxin Zeng
- Department of Clinical Research Center, Dazhou Hospital, Dazhou, Sichuan, China
| | - Yuangang Zhu
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xiao-Wei Chen
- State Key Laboratory of Membrane Biology, Peking University, Beijing, China.
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China.
- PKU-THU Joint Center for Life Sciences, Peking University, Beijing, China.
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24
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Kievits AJ, Duinkerken BHP, Fermie J, Lane R, Giepmans BNG, Hoogenboom JP. Optical STEM detection for scanning electron microscopy. Ultramicroscopy 2023; 256:113877. [PMID: 37931528 DOI: 10.1016/j.ultramic.2023.113877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/13/2023] [Accepted: 10/21/2023] [Indexed: 11/08/2023]
Abstract
Recent advances in electron microscopy techniques have led to a significant scale up in volumetric imaging of biological tissue. The throughput of electron microscopes, however, remains a limiting factor for the volume that can be imaged in high resolution within reasonable time. Faster detection methods will improve throughput. Here, we have characterized and benchmarked a novel detection technique for scanning electron microscopy: optical scanning transmission electron microscopy (OSTEM). A qualitative and quantitative comparison was performed between OSTEM, secondary and backscattered electron detection and annular dark field detection in scanning transmission electron microscopy. Our analysis shows that OSTEM produces images similar to backscattered electron detection in terms of contrast, resolution and signal-to-noise ratio. OSTEM can complement large scale imaging with (scanning) transmission electron microscopy and has the potential to speed up imaging in single-beam scanning electron microscope.
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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 of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | | | - Ryan Lane
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Ben N G Giepmans
- Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Jacob P Hoogenboom
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
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25
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Baldwin KT, Murai KK, Khakh BS. Astrocyte morphology. Trends Cell Biol 2023:S0962-8924(23)00204-0. [PMID: 38180380 DOI: 10.1016/j.tcb.2023.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 09/18/2023] [Accepted: 09/29/2023] [Indexed: 01/06/2024]
Abstract
Astrocytes are predominant glial cells that tile the central nervous system (CNS). A cardinal feature of astrocytes is their complex and visually enchanting morphology, referred to as bushy, spongy, and star-like. A central precept of this review is that such complex morphological shapes evolved to allow astrocytes to contact and signal with diverse cells at a range of distances in order to sample, regulate, and contribute to the extracellular milieu, and thus participate widely in cell-cell signaling during physiology and disease. The recent use of improved imaging methods and cell-specific molecular evaluations has revealed new information on the structural organization and molecular underpinnings of astrocyte morphology, the mechanisms of astrocyte morphogenesis, and the contributions to disease states of reduced morphology. These insights have reignited interest in astrocyte morphological complexity as a cornerstone of fundamental glial biology and as a critical substrate for multicellular spatial and physiological interactions in the CNS.
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Affiliation(s)
- Katherine T Baldwin
- Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Keith K Murai
- Centre for Research in Neuroscience, Department of Neurology and Neurosurgery, Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montreal General Hospital, 1650 Cedar Avenue, Montreal, QC H3G 1A4, Canada.
| | - Baljit S Khakh
- Department of Physiology, David Geffen School of Medicine, University of California Los Angeles, 10833 Le Conte Avenue, Los Angeles, CA 90034, USA; Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, 10833 Le Conte Avenue, Los Angeles, CA 90034, USA.
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26
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Handler A, Zhang Q, Pang S, Nguyen TM, Iskols M, Nolan-Tamariz M, Cattel S, Plumb R, Sanchez B, Ashjian K, Shotland A, Brown B, Kabeer M, Turecek J, DeLisle MM, Rankin G, Xiang W, Pavarino EC, Africawala N, Santiago C, Lee WCA, Xu CS, Ginty DD. Three-dimensional reconstructions of mechanosensory end organs suggest a unifying mechanism underlying dynamic, light touch. Neuron 2023; 111:3211-3229.e9. [PMID: 37725982 PMCID: PMC10773061 DOI: 10.1016/j.neuron.2023.08.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/31/2023] [Accepted: 08/22/2023] [Indexed: 09/21/2023]
Abstract
Across mammalian skin, structurally complex and diverse mechanosensory end organs respond to mechanical stimuli and enable our perception of dynamic, light touch. How forces act on morphologically dissimilar mechanosensory end organs of the skin to gate the requisite mechanotransduction channel Piezo2 and excite mechanosensory neurons is not understood. Here, we report high-resolution reconstructions of the hair follicle lanceolate complex, Meissner corpuscle, and Pacinian corpuscle and the subcellular distribution of Piezo2 within them. Across all three end organs, Piezo2 is restricted to the sensory axon membrane, including axon protrusions that extend from the axon body. These protrusions, which are numerous and elaborate extensively within the end organs, tether the axon to resident non-neuronal cells via adherens junctions. These findings support a unified model for dynamic touch in which mechanical stimuli stretch hundreds to thousands of axon protrusions across an end organ, opening proximal, axonal Piezo2 channels and exciting the neuron.
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Affiliation(s)
- Annie Handler
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Qiyu Zhang
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Song Pang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Tri M Nguyen
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Michael Iskols
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Michael Nolan-Tamariz
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Stuart Cattel
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rebecca Plumb
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Brianna Sanchez
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Karyl Ashjian
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Aria Shotland
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Bartianna Brown
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Madiha Kabeer
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Josef Turecek
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Michelle M DeLisle
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Genelle Rankin
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Wangchu Xiang
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Elisa C Pavarino
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Nusrat Africawala
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Celine Santiago
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Wei-Chung Allen Lee
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
| | - C Shan Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - David D Ginty
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA; Howard Hughes Medical Institute, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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27
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Zeng Y, Liang Z, Liu Z, Li B, Cui Y, Gao C, Shen J, Wang X, Zhao Q, Zhuang X, Erdmann PS, Wong KB, Jiang L. Recent advances in plant endomembrane research and new microscopical techniques. New Phytol 2023; 240:41-60. [PMID: 37507353 DOI: 10.1111/nph.19134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/19/2023] [Indexed: 07/30/2023]
Abstract
The endomembrane system consists of various membrane-bound organelles including the endoplasmic reticulum (ER), Golgi apparatus, trans-Golgi network (TGN), endosomes, and the lysosome/vacuole. Membrane trafficking between distinct compartments is mainly achieved by vesicular transport. As the endomembrane compartments and the machineries regulating the membrane trafficking are largely conserved across all eukaryotes, our current knowledge on organelle biogenesis and endomembrane trafficking in plants has mainly been shaped by corresponding studies in mammals and yeast. However, unique perspectives have emerged from plant cell biology research through the characterization of plant-specific regulators as well as the development and application of the state-of-the-art microscopical techniques. In this review, we summarize our current knowledge on the plant endomembrane system, with a focus on several distinct pathways: ER-to-Golgi transport, protein sorting at the TGN, endosomal sorting on multivesicular bodies, vacuolar trafficking/vacuole biogenesis, and the autophagy pathway. We also give an update on advanced imaging techniques for the plant cell biology research.
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Affiliation(s)
- Yonglun Zeng
- School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Zizhen Liang
- School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Zhiqi Liu
- School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Baiying Li
- School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Yong Cui
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Caiji Gao
- Guangdong Provincial Key Laboratory of Biotechnology for Plant Development, School of Life Sciences, South China Normal University, Guangzhou, 510631, China
| | - Jinbo Shen
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, 311300, China
| | - Xiangfeng Wang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Qiong Zhao
- School of Life Sciences, East China Normal University, Shanghai, 200062, China
| | - Xiaohong Zhuang
- School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Philipp S Erdmann
- Human Technopole, Viale Rita Levi-Montalcini, 1, Milan, I-20157, Italy
| | - Kam-Bo Wong
- Centre for Protein Science and Crystallography, School of Life Sciences, The Chinese University of Hong Kong (CUHK), Shatin, Hong Kong, China
| | - Liwen Jiang
- School of Life Sciences, Centre for Cell & Developmental Biology and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- The CUHK Shenzhen Research Institute, Shenzhen, 518057, China
- Institute of Plant Molecular Biology and Agricultural Biotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, China
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28
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Chang S, Li L, Hong B, Liu J, Xu Y, Pang K, Zhang L, Han H, Chen X. An intelligent workflow for sub-nanoscale 3D reconstruction of intact synapses from serial section electron tomography. BMC Biol 2023; 21:198. [PMID: 37743470 PMCID: PMC10519085 DOI: 10.1186/s12915-023-01696-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 09/06/2023] [Indexed: 09/26/2023] Open
Abstract
BACKGROUND As an extension of electron tomography (ET), serial section electron tomography (serial section ET) aims to align the tomographic images of multiple thick tissue sections together, to break through the volume limitation of the single section and preserve the sub-nanoscale voxel size. It could be applied to reconstruct the intact synapse, which expands about one micrometer and contains nanoscale vesicles. However, there are several drawbacks of the existing serial section ET methods. First, locating and imaging regions of interest (ROIs) in serial sections during the shooting process is time-consuming. Second, the alignment of ET volumes is difficult due to the missing information caused by section cutting and imaging. Here we report a workflow to simplify the acquisition of ROIs in serial sections, automatically align the volume of serial section ET, and semi-automatically reconstruct the target synaptic structure. RESULTS We propose an intelligent workflow to reconstruct the intact synapse with sub-nanometer voxel size. Our workflow includes rapid localization of ROIs in serial sections, automatic alignment, restoration, assembly of serial ET volumes, and semi-automatic target structure segmentation. For the localization and acquisition of ROIs in serial sections, we use affine transformations to calculate their approximate position based on their relative location in orderly placed sections. For the alignment of consecutive ET volumes with significantly distinct appearances, we use multi-scale image feature matching and the elastic with belief propagation (BP-Elastic) algorithm to align them from coarse to fine. For the restoration of the missing information in ET, we first estimate the number of lost images based on the pixel changes of adjacent volumes after alignment. Then, we present a missing information generation network that is appropriate for small-sample of ET volume using pre-training interpolation network and distillation learning. And we use it to generate the missing information to achieve the whole volume reconstruction. For the reconstruction of synaptic ultrastructures, we use a 3D neural network to obtain them quickly. In summary, our workflow can quickly locate and acquire ROIs in serial sections, automatically align, restore, assemble serial sections, and obtain the complete segmentation result of the target structure with minimal manual manipulation. Multiple intact synapses in wild-type rat were reconstructed at a voxel size of 0.664 nm/voxel to demonstrate the effectiveness of our workflow. CONCLUSIONS Our workflow contributes to obtaining intact synaptic structures at the sub-nanometer scale through serial section ET, which contains rapid ROI locating, automatic alignment, volume reconstruction, and semi-automatic synapse reconstruction. We have open-sourced the relevant code in our workflow, so it is easy to apply it to other labs and obtain complete 3D ultrastructures which size is similar to intact synapses with sub-nanometer voxel size.
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Affiliation(s)
- Sheng Chang
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, 100190, Beijing, China
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Linlin Li
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Bei Hong
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, 100190, Beijing, China
| | - Jing Liu
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Yuxuan Xu
- School of Software and Microelectronics, Peking University, 100871, Beijing, China
| | - Keliang Pang
- School of Pharmaceutical Sciences, Tsinghua University, 100084, Beijing, China
| | - Lina Zhang
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Hua Han
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, 101408, China.
| | - Xi Chen
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China.
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29
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Nikolaev YA, Ziolkowski LH, Pang S, Li WP, Feketa VV, Xu CS, Gracheva EO, Bagriantsev SN. 3D architecture and a bicellular mechanism of touch detection in mechanosensory corpuscle. Sci Adv 2023; 9:eadi4147. [PMID: 37703368 PMCID: PMC10499330 DOI: 10.1126/sciadv.adi4147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 08/09/2023] [Indexed: 09/15/2023]
Abstract
Mechanosensory corpuscles detect transient touch and vibration in the skin of vertebrates, enabling precise sensation of the physical environment. The corpuscle contains a mechanoreceptor afferent surrounded by lamellar cells (LCs), but corpuscular ultrastructure and the role of LCs in touch detection are unknown. We report the three-dimensional architecture of the avian Meissner (Grandry) corpuscle acquired using enhanced focused ion beam scanning electron microscopy and machine learning-based segmentation. The corpuscle comprises a stack of LCs interdigitated with terminal endings from two afferents. Simultaneous electrophysiological recordings from both cell types revealed that mechanosensitive LCs use calcium influx to trigger action potentials in the afferent and thus serve as physiological touch sensors in the skin. The elaborate architecture and bicellular sensory mechanism in the corpuscles, which comprises the afferents and LCs, create the capacity for nuanced encoding of the submodalities of touch.
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Affiliation(s)
- Yury A. Nikolaev
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Luke H. Ziolkowski
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Song Pang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Wei-Ping Li
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Viktor V. Feketa
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA
| | - C. Shan Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Elena O. Gracheva
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale University School of Medicine, New Haven, CT 06510, USA
- Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Sviatoslav N. Bagriantsev
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
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30
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Desyatirkina IA, Makarova AA, Pang S, Xu CS, Hess H, Polilov AA. Multiscale head anatomy of Megaphragma (Hymenoptera: Trichogrammatidae). Arthropod Struct Dev 2023; 76:101299. [PMID: 37666087 DOI: 10.1016/j.asd.2023.101299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/10/2023] [Accepted: 08/15/2023] [Indexed: 09/06/2023]
Abstract
Methods of three-dimensional electron microscopy have been actively developed recently and open up great opportunities for morphological work. This approach is especially useful for studying microinsects, since it is possible to obtain complete series of high-resolution sections of a whole insect. Studies on the genus Megaphragma are especially important, since the unique phenomenon of lysis of most of the neuron nuclei was discovered in species of this genus. In this study we reveal the anatomical structure of the head of Megaphragma viggianii at all levels from organs to subcellular structures. Despite the miniature size of the body, most of the organ systems of M. viggianii retain the structural plan and complexity of organization at all levels. The set of muscles and the well-developed stomatogastric nervous system of this species correspond to those of larger insects, and there is also a well-developed tracheal system in the head of this species. Reconstructions of the head of M. viggianii at the cellular and subcellular levels were obtained, and of volumetric data were analyzed. A total of 689 nucleated cells of the head were reconstructed. The ultrastructure of M. viggianii is surprisingly complex, and the evolutionary benefits of such complexity are probably among the factors limiting the further miniaturization of parasitoid wasps.
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Affiliation(s)
- Inna A Desyatirkina
- Department of Entomology, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia.
| | - Anastasia A Makarova
- Department of Entomology, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Song Pang
- Janelia Research Campus of the Howard Hughes Medical Institute, Ashburn, USA; Yale School of Medicine, New Haven, CT, USA
| | - C Shan Xu
- Janelia Research Campus of the Howard Hughes Medical Institute, Ashburn, USA; Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT, USA
| | - Harald Hess
- Janelia Research Campus of the Howard Hughes Medical Institute, Ashburn, USA
| | - Alexey A Polilov
- Department of Entomology, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
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31
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Kolotuev I. Work smart, not hard: How array tomography can help increase the ultrastructure data output. J Microsc 2023. [PMID: 37626455 DOI: 10.1111/jmi.13217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 08/16/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023]
Abstract
Transmission electron microscopy has been essential for understanding cell biology for over six decades. Volume electron microscopy tools, such as serial block face and focused ion beam scanning electron microscopy acquisition, brought a new era to ultrastructure analysis. 'Array Tomography' (AT) refers to sequential image acquisition of resin-embedded sample sections on a large support (coverslip, glass slide, silicon wafers) for immunolabelling with multiple fluorescent labels, occasionally combined with ultrastructure observation. Subsequently, the term was applied to generating and imaging a series of sections to acquire a 3D representation of a structure using scanning electron microscopy (SEM). Although this is a valuable application, the potential of AT is to facilitate many tasks that are difficult or even impossible to obtain by Transmission Electron Microscopy (TEM). Due to the straightforward nature and versatility of AT sample preparation and image acquisition, the technique can be applied practically to any biological sample for selected sections or volume electron microscopy analysis. Furthermore, in addition to the benefits described here, AT is compatible with morphological analysis, multiplex immunolabelling, immune-gold labelling, and correlative light and electron microscopy workflow applicable for single cells, tissue and small organisms. This versatility makes AT attractive not only for basic research but as a diagnostic tool with a simplified routine.
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Affiliation(s)
- Irina Kolotuev
- Electron Microscopy Facility, University of Lausanne, Lausanne, Switzerland
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32
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Low SWY, Lim RR, Grant DG, Patterson S, Chaurasia SS. New Insights into RPE-Photoreceptor Complex Ultrastructure using Focused Ion Beam-Scanning Election Microscopy (FIB-SEM). Res Sq 2023:rs.3.rs-3200741. [PMID: 37609321 PMCID: PMC10441459 DOI: 10.21203/rs.3.rs-3200741/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Photoreceptors in the retina are specialized neuronal cells that perceive light and play a central role in the visual system. Damage to photoreceptors is a clinical feature often associated with various retinal degenerative disorders. The photoreceptor bed comprises a unique extracellular matrix (ECM) scaffold often described as the interphotoreceptor matrix (IPM) in the subretinal space, vital during retinal development and homeostasis. In this study, we used focused ion beam scanning electron microscopy (FIB-SEM) and transmission electron microscopy (TEM) to analyze the ultrastructural architecture of the retinal pigmented epithelium (RPE)-photoreceptor complex in mice. Additionally, we describe methods for retinal preparation in EM imaging. TEM images display ultrastructural retina layers, including Bruch's membrane and the interdigitation zone (IZ). The 3-dimensional reconstruction of the outer retina revealed individual photoreceptors, the connection between their inner and outer segment via the photoreceptor cilia, and photoreceptor interaction with the RPE ciliary processes. Our findings highlight the importance of FIB-SEM in deciphering the ultrastructural details of RPE-photoreceptor interactions in the IPM complex which are essential for the maintenance of retinal architecture.
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33
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Marshall AG, Neikirk K, Stephens DC, Vang L, Vue Z, Beasley HK, Crabtree A, Scudese E, Lopez EG, Shao B, Krystofiak E, Rutledge S, Davis J, Murray SA, Damo SM, Katti P, Hinton A. Serial Block Face-Scanning Electron Microscopy as a Burgeoning Technology. Adv Biol (Weinh) 2023; 7:e2300139. [PMID: 37246236 PMCID: PMC10950369 DOI: 10.1002/adbi.202300139] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 05/09/2023] [Indexed: 05/30/2023]
Abstract
Serial block face scanning electron microscopy (SBF-SEM), also referred to as serial block-face electron microscopy, is an advanced ultrastructural imaging technique that enables three-dimensional visualization that provides largerx- and y-axis ranges than other volumetric EM techniques. While SEM is first introduced in the 1930s, SBF-SEM is developed as a novel method to resolve the 3D architecture of neuronal networks across large volumes with nanometer resolution by Denk and Horstmann in 2004. Here, the authors provide an accessible overview of the advantages and challenges associated with SBF-SEM. Beyond this, the applications of SBF-SEM in biochemical domains as well as potential future clinical applications are briefly reviewed. Finally, the alternative forms of artificial intelligence-based segmentation which may contribute to devising a feasible workflow involving SBF-SEM, are also considered.
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Affiliation(s)
- Andrea G Marshall
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Kit Neikirk
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Dominique C Stephens
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Larry Vang
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Zer Vue
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Heather K Beasley
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Amber Crabtree
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Estevão Scudese
- Laboratory of Biosciences of Human Motricity (LABIMH) of the Federal University of State of Rio de Janeiro (UNIRIO), Rio de Janeiro, Brazil
- Sport Sciences and Exercise Laboratory (LaCEE), Catholic University of Petrópolis (UCP), Catholic, 25685-100, Brazil
| | - Edgar Garza Lopez
- Department of Internal Medicine, University of Iowa, Iowa City, IA, 52242, USA
| | - Bryanna Shao
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Evan Krystofiak
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, 37232, USA
| | - Sharifa Rutledge
- Department of Chemistry, University of Alabama in Huntsville, Huntsville, AL, 35899, USA
| | - Jaimaine Davis
- Department of Biochemistry, Cancer Biology, Neuroscience, Pharmacology, Meharry Medical College, Nashville, TN, 37232, USA
| | - Sandra A Murray
- Department of Cell Biology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Steven M Damo
- Department of Life and Physical Sciences, Fisk University, Nashville, TN, 37208, USA
- Center for Structural Biology, Vanderbilt University, Nashville, TN, 37232, USA
| | - Prasanna Katti
- National Heart, Lung and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD, 20892, USA
| | - Antentor Hinton
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
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34
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Cooper C, Thompson RCA, Clode PL. Investigating parasites in three dimensions: trends in volume microscopy. Trends Parasitol 2023; 39:668-681. [PMID: 37302958 DOI: 10.1016/j.pt.2023.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/17/2023] [Accepted: 05/17/2023] [Indexed: 06/13/2023]
Abstract
To best understand parasite, host, and vector morphologies, host-parasite interactions, and to develop new drug and vaccine targets, structural data should, ideally, be obtained and visualised in three dimensions (3D). Recently, there has been a significant uptake of available 3D volume microscopy techniques that allow collection of data across centimetre (cm) to Angstrom (Å) scales by utilising light, X-ray, electron, and ion sources. Here, we present and discuss microscopy tools available for the collection of 3D structural data, focussing on electron microscopy-based techniques. We highlight their strengths and limitations, such that parasitologists can identify techniques best suited to answer their research questions. Additionally, we review the importance of volume microscopy to the advancement of the field of parasitology.
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Affiliation(s)
- Crystal Cooper
- Centre for Microscopy, Characterisation, and Analysis, University of Western Australia, Stirling Hwy, Crawley, WA 6009, Australia.
| | - R C Andrew Thompson
- School of Veterinary and Life Sciences, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia
| | - Peta L Clode
- Centre for Microscopy, Characterisation, and Analysis, University of Western Australia, Stirling Hwy, Crawley, WA 6009, Australia; School of Biological Sciences, University of Western Australia, Stirling Hwy, Crawley, WA 6009, Australia
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35
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Pang S. Enhanced FIB-SEM Sample Preparation Methods and Pipeline for Comparative Biology. Microsc Microanal 2023; 29:1187. [PMID: 37613191 DOI: 10.1093/micmic/ozad067.611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Song Pang
- Yale School of Medicine, New Haven, CT, USA
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36
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Allen FI. FIB Milling with Alternative Beams for Microscopy and Microanalysis. Microsc Microanal 2023; 29:501-502. [PMID: 37613023 DOI: 10.1093/micmic/ozad067.238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Frances I Allen
- Department of Materials Science and Engineering, University of California, Berkeley, CA, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA, USA
- National Center for Electron Microscopy, Molecular Foundry, Lawrence Berkeley National Laboratory, CA, USA
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37
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Dorkenwald S, Matsliah A, Sterling AR, Schlegel P, Yu SC, McKellar CE, Lin A, Costa M, Eichler K, Yin Y, Silversmith W, Schneider-Mizell C, Jordan CS, Brittain D, Halageri A, Kuehner K, Ogedengbe O, Morey R, Gager J, Kruk K, Perlman E, Yang R, Deutsch D, Bland D, Sorek M, Lu R, Macrina T, Lee K, Bae JA, Mu S, Nehoran B, Mitchell E, Popovych S, Wu J, Jia Z, Castro M, Kemnitz N, Ih D, Bates AS, Eckstein N, Funke J, Collman F, Bock DD, Jefferis GS, Seung HS, Murthy M. Neuronal wiring diagram of an adult brain. bioRxiv 2023:2023.06.27.546656. [PMID: 37425937 PMCID: PMC10327113 DOI: 10.1101/2023.06.27.546656] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×107 chemical synapses between ~130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.
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Affiliation(s)
- Sven Dorkenwald
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Arie Matsliah
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Amy R Sterling
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Eyewire, Boston, USA
| | - Philipp Schlegel
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Szi-chieh Yu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Albert Lin
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Center for the Physics of Biological Function, Princeton University, Princeton, USA
| | - Marta Costa
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Katharina Eichler
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Yijie Yin
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Will Silversmith
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Chris S. Jordan
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Akhilesh Halageri
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Kai Kuehner
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | - Ryan Morey
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Jay Gager
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | | | | | - Runzhe Yang
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - David Deutsch
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Department of Neurobiology, University of Haifa, Haifa, Israel
| | - Doug Bland
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Marissa Sorek
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Eyewire, Boston, USA
| | - Ran Lu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Thomas Macrina
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Kisuk Lee
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Brain & Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, USA
| | - J. Alexander Bae
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Electrical and Computer Engineering Department, Princeton University, Princeton, USA
| | - Shang Mu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Barak Nehoran
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Eric Mitchell
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Sergiy Popovych
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Jingpeng Wu
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Zhen Jia
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Manuel Castro
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Nico Kemnitz
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Dodam Ih
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Alexander Shakeel Bates
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- Harvard Medical School, Boston, USA
- Centre for Neural Circuits and Behaviour, The University of Oxford, Oxford, UK
| | - Nils Eckstein
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | - Jan Funke
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, USA
| | | | - Davi D. Bock
- Department of Neurological Sciences, Larner College of Medicine, University of Vermont, Burlington, USA
| | - Gregory S.X.E Jefferis
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
- Drosophila Connectomics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - H. Sebastian Seung
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
- Computer Science Department, Princeton University, Princeton, USA
| | - Mala Murthy
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
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38
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Ali MK, Javaid S, Afzal H, Zafar I, Fayyaz K, Ain Q, Rather MA, Hossain MJ, Rashid S, Khan KA, Sharma R. Exploring the multifunctional roles of quantum dots for unlocking the future of biology and medicine. Environ Res 2023; 232:116290. [PMID: 37295589 DOI: 10.1016/j.envres.2023.116290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/28/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023]
Abstract
With recent advancements in nanomedicines and their associated research with biological fields, their translation into clinically-applicable products is still below promises. Quantum dots (QDs) have received immense research attention and investment in the four decades since their discovery. We explored the extensive biomedical applications of QDs, viz. Bio-imaging, drug research, drug delivery, immune assays, biosensors, gene therapy, diagnostics, their toxic effects, and bio-compatibility. We unravelled the possibility of using emerging data-driven methodologies (bigdata, artificial intelligence, machine learning, high-throughput experimentation, computational automation) as excellent sources for time, space, and complexity optimization. We also discussed ongoing clinical trials, related challenges, and the technical aspects that should be considered to improve the clinical fate of QDs and promising future research directions.
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Affiliation(s)
- Muhammad Kashif Ali
- Deparment of Physiology, Rashid Latif Medical College, Lahore, Punjab, 54700, Pakistan.
| | - Saher Javaid
- KAM School of Life Sciences, Forman Christian College (a Chartered University) Lahore, Punjab, Pakistan.
| | - Haseeb Afzal
- Department of ENT, Ameer Ud Din Medical College, Lahore, Punjab, 54700, Pakistan.
| | - Imran Zafar
- Department of Bioinformatics and Computational Biology, Virtual University, Punjab, 54700, Pakistan.
| | - Kompal Fayyaz
- Department of National Centre for Bioinformatics, Quaid-I-Azam University, Islamabad, 45320, Pakistan.
| | - Quratul Ain
- Department of Chemistry, Government College Women University Faisalabad (GCWUF), Punjab, 54700, Pakistan.
| | - Mohd Ashraf Rather
- Division of Fish Genetics and Biotechnology, Faculty of Fisheries, Rangil- Gandarbal (SKAUST-K), India.
| | - Md Jamal Hossain
- Department of Pharmacy, State University of Bangladesh, 77 Satmasjid Road, Dhanmondi, Dhaka, 1205, Bangladesh.
| | - Summya Rashid
- Department of Pharmacology & Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj, 11942, Saudi Arabia.
| | - Khalid Ali Khan
- Unit of Bee Research and Honey Production, Research Center for Advanced Materials Science (RCAMS), King Khalid University, P.O. Box 9004, Abha, 61413, Saudi Arabia; Applied College, King Khalid University, P. O. Box 9004, Abha, 61413, Saudi Arabia.
| | - Rohit Sharma
- Department of Rasa Shastra and Bhaishajya Kalpana, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, 221005, Uttar Pradesh, India.
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Marshall AG, Damo SM, Hinton A. Revisiting focused ion beam scanning electron microscopy. Trends Biochem Sci 2023; 48:585-586. [PMID: 36990957 DOI: 10.1016/j.tibs.2023.02.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/27/2023] [Accepted: 02/23/2023] [Indexed: 03/29/2023]
Affiliation(s)
- Andrea G Marshall
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA
| | - Steven M Damo
- Department of Life and Physical Sciences, Fisk University, Nashville, TN, 37232, USA; Center for Structural Biology, Vanderbilt University, Nashville, TN, 37232, USA
| | - Antentor Hinton
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, 37232, USA.
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40
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Collinson LM, Bosch C, Bullen A, Burden JJ, Carzaniga R, Cheng C, Darrow MC, Fletcher G, Johnson E, Narayan K, Peddie CJ, Winn M, Wood C, Patwardhan A, Kleywegt GJ, Verkade P. Volume EM: a quiet revolution takes shape. Nat Methods 2023; 20:777-782. [PMID: 37076630 PMCID: PMC7614633 DOI: 10.1038/s41592-023-01861-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
Volume Electron Microscopy is a group of techniques that reveal the 3D ultrastructure of cells and tissues through volumes greater than 1 cubic micron. A burgeoning grass roots community effort is fast building the profile, and revealing the impact, of vEM technology in the life sciences and clinical research.
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Affiliation(s)
- Lucy M Collinson
- Electron Microscopy Science Technology Platform, Francis Crick Institute, London, UK.
| | - Carles Bosch
- Sensory Circuits and Neurotechnology Laboratory, Francis Crick Institute, London, UK
| | - Anwen Bullen
- UCL Ear Institute, University College London, London, UK
| | - Jemima J Burden
- Laboratory for Molecular Cell Biology, University College London, London, UK
| | - Raffaella Carzaniga
- Zeiss Research Microscopy Solutions, Carl Zeiss Ltd, Zeiss Group, Cambourne, UK
| | | | - Michele C Darrow
- Artificial Intelligence & Informatics, The Rosalind Franklin Institute, Didcot, UK
- SPT Labtech Ltd., Melbourn, UK
| | | | - Errin Johnson
- Dunn School Bioimaging Facility, Sir William Dunn School of Pathology, Oxford University, Oxford, UK
| | - Kedar Narayan
- Center for Molecular Microscopy, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Christopher J Peddie
- Electron Microscopy Science Technology Platform, Francis Crick Institute, London, UK
| | - Martyn Winn
- UKRI-STFC, Rutherford Appleton Laboratory, Didcot, UK
| | - Charles Wood
- Future Technology Centre, School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth, UK
| | - Ardan Patwardhan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Gerard J Kleywegt
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Paul Verkade
- School of Biochemistry, University of Bristol, Bristol, UK.
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Bharathan NK, Giang W, Hoffman CL, Aaron JS, Khuon S, Chew TL, Preibisch S, Trautman ET, Heinrich L, Bogovic J, Bennett D, Ackerman D, Park W, Petruncio A, Weigel AV, Saalfeld S, Wayne Vogl A, Stahley SN, Kowalczyk AP. Architecture and dynamics of a desmosome-endoplasmic reticulum complex. Nat Cell Biol 2023; 25:823-835. [PMID: 37291267 PMCID: PMC10960982 DOI: 10.1038/s41556-023-01154-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 04/24/2023] [Indexed: 06/10/2023]
Abstract
The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signalling and lipid transfer. Here, using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometre proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization, mobility and expression of ER stress transcripts. These findings indicate that desmosomes and the keratin cytoskeleton regulate the distribution, function and dynamics of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction.
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Affiliation(s)
- Navaneetha Krishnan Bharathan
- Departments of Dermatology and Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - William Giang
- Departments of Dermatology and Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Coryn L Hoffman
- Departments of Dermatology and Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jesse S Aaron
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Satya Khuon
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Teng-Leong Chew
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Stephan Preibisch
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Eric T Trautman
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Larissa Heinrich
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - John Bogovic
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Davis Bennett
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - David Ackerman
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Woohyun Park
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Alyson Petruncio
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Aubrey V Weigel
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Stephan Saalfeld
- Advanced Imaging Center, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - A Wayne Vogl
- Life Sciences Institute and the Department of Cellular and Physiological Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sara N Stahley
- Departments of Dermatology and Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Andrew P Kowalczyk
- Departments of Dermatology and Cellular and Molecular Physiology, Pennsylvania State University College of Medicine, Hershey, PA, USA.
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Zhu J, Boivin JC, Pang S, Xu CS, Lu Z, Saalfeld S, Hess HF, Ohyama T. Comparative connectomics and escape behavior in larvae of closely related Drosophila species. Curr Biol 2023:S0960-9822(23)00675-9. [PMID: 37285846 DOI: 10.1016/j.cub.2023.05.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 05/02/2023] [Accepted: 05/17/2023] [Indexed: 06/09/2023]
Abstract
Evolution has generated an enormous variety of morphological, physiological, and behavioral traits in animals. How do behaviors evolve in different directions in species equipped with similar neurons and molecular components? Here we adopted a comparative approach to investigate the similarities and differences of escape behaviors in response to noxious stimuli and their underlying neural circuits between closely related drosophilid species. Drosophilids show a wide range of escape behaviors in response to noxious cues, including escape crawling, stopping, head casting, and rolling. Here we find that D. santomea, compared with its close relative D. melanogaster, shows a higher probability of rolling in response to noxious stimulation. To assess whether this behavioral difference could be attributed to differences in neural circuitry, we generated focused ion beam-scanning electron microscope volumes of the ventral nerve cord of D. santomea to reconstruct the downstream partners of mdIV, a nociceptive sensory neuron in D. melanogaster. Along with partner interneurons of mdVI (including Basin-2, a multisensory integration neuron necessary for rolling) previously identified in D. melanogaster, we identified two additional partners of mdVI in D. santomea. Finally, we showed that joint activation of one of the partners (Basin-1) and a common partner (Basin-2) in D. melanogaster increased rolling probability, suggesting that the high rolling probability in D. santomea is mediated by the additional activation of Basin-1 by mdIV. These results provide a plausible mechanistic explanation for how closely related species exhibit quantitative differences in the likelihood of expressing the same behavior.
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Affiliation(s)
- Jiayi Zhu
- Department of Biology, McGill University, Docteur Penfield, Montreal, QC H3A 1B1, Canada; Integrated Program of Neuroscience, McGill University, Pine Avenue W., Montreal, QC H3A 1A1, Canada
| | - Jean-Christophe Boivin
- Department of Biology, McGill University, Docteur Penfield, Montreal, QC H3A 1B1, Canada; Integrated Program of Neuroscience, McGill University, Pine Avenue W., Montreal, QC H3A 1A1, Canada
| | - Song Pang
- Janelia Research Campus, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, USA
| | - C Shan Xu
- Janelia Research Campus, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, USA
| | - Zhiyuan Lu
- Janelia Research Campus, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, USA
| | - Stephan Saalfeld
- Janelia Research Campus, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, USA
| | - Harald F Hess
- Janelia Research Campus, Howard Hughes Medical Institute, Helix Drive, Ashburn, VA 20147, USA
| | - Tomoko Ohyama
- Department of Biology, McGill University, Docteur Penfield, Montreal, QC H3A 1B1, Canada; Alan Edwards Center for Research on Pain, McGill University, University Street, Montreal, QC H3A 2B4, Canada.
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43
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Wen C, Matsumoto M, Sawada M, Sawamoto K, Kimura KD. Seg2Link: an efficient and versatile solution for semi-automatic cell segmentation in 3D image stacks. Sci Rep 2023; 13:7109. [PMID: 37217545 DOI: 10.1038/s41598-023-34232-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 04/26/2023] [Indexed: 05/24/2023] Open
Abstract
Recent advances in microscopy techniques, especially in electron microscopy, are transforming biomedical studies by acquiring large quantities of high-precision 3D cell image stacks. To examine cell morphology and connectivity in organs such as the brain, scientists need to conduct cell segmentation, which extracts individual cell regions of different shapes and sizes from a 3D image. This is challenging due to the indistinct images often encountered in real biomedical research: in many cases, automatic segmentation methods inevitably contain numerous mistakes in the segmentation results, even when using advanced deep learning methods. To analyze 3D cell images effectively, a semi-automated software solution is needed that combines powerful deep learning techniques with the ability to perform post-processing, generate accurate segmentations, and incorporate manual corrections. To address this gap, we developed Seg2Link, which takes deep learning predictions as inputs and use watershed 2D + cross-slice linking to generate more accurate automatic segmentations than previous methods. Additionally, it provides various manual correction tools essential for correcting mistakes in 3D segmentation results. Moreover, our software has been optimized for efficiently processing large 3D images in diverse organisms. Thus, Seg2Link offers an practical solution for scientists to study cell morphology and connectivity in 3D image stacks.
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Affiliation(s)
- Chentao Wen
- Graduate School of Science, Nagoya City University, Nagoya, Japan.
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Mami Matsumoto
- Department of Developmental and Regenerative Neurobiology, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Division of Neural Development and Regeneration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Masato Sawada
- Department of Developmental and Regenerative Neurobiology, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Division of Neural Development and Regeneration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Kazunobu Sawamoto
- Department of Developmental and Regenerative Neurobiology, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Division of Neural Development and Regeneration, National Institute for Physiological Sciences, Okazaki, Japan
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44
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de Beer M, Daviran D, Roverts R, Rutten L, Macías-Sánchez E, Metz JR, Sommerdijk N, Akiva A. Precise targeting for 3D cryo-correlative light and electron microscopy volume imaging of tissues using a FinderTOP. Commun Biol 2023; 6:510. [PMID: 37169904 PMCID: PMC10175257 DOI: 10.1038/s42003-023-04887-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 04/28/2023] [Indexed: 05/13/2023] Open
Abstract
Cryo-correlative light and electron microscopy (cryoCLEM) is a powerful strategy to high resolution imaging in the unperturbed hydrated state. In this approach fluorescence microscopy aids localizing the area of interest, and cryogenic focused ion beam/scanning electron microscopy (cryoFIB/SEM) allows preparation of thin cryo-lamellae for cryoET. However, the current method cannot be accurately applied on bulky (3D) samples such as tissues and organoids. 3D cryo-correlative imaging of large volumes is needed to close the resolution gap between cryo-light microscopy and cryoET, placing sub-nanometer observations in a larger biological context. Currently technological hurdles render 3D cryoCLEM an unexplored approach. Here we demonstrate a cryoCLEM workflow for tissues, correlating cryo-Airyscan confocal microscopy with 3D cryoFIB/SEM volume imaging. Accurate correlation is achieved by imprinting a FinderTOP pattern in the sample surface during high pressure freezing, and allows precise targeting for cryoFIB/SEM volume imaging.
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Affiliation(s)
- Marit de Beer
- Electron Microscopy Center, Radboud Technology Center Microscopy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Deniz Daviran
- Electron Microscopy Center, Radboud Technology Center Microscopy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Rona Roverts
- Electron Microscopy Center, Radboud Technology Center Microscopy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Luco Rutten
- Electron Microscopy Center, Radboud Technology Center Microscopy, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Elena Macías-Sánchez
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Stratigraphy and Paleontology, University of Granada, Granada, Spain
| | - Juriaan R Metz
- Department of Animal Ecology and Physiology, Radboud Institute for Biological and Environmental Sciences, Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - Nico Sommerdijk
- Electron Microscopy Center, Radboud Technology Center Microscopy, Radboud University Medical Center, Nijmegen, The Netherlands.
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Anat Akiva
- Electron Microscopy Center, Radboud Technology Center Microscopy, Radboud University Medical Center, Nijmegen, The Netherlands.
- Department of Medical Biosciences, Radboud University Medical Center, Nijmegen, The Netherlands.
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45
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Wang T, Shi P, Luo D, Guo J, Liu H, Yuan J, Jin H, Wu X, Zhang Y, Xiong Z, Zhu J, Zhou R, Zhang R. A Convenient All-Cell Optical Imaging Method Compatible with Serial SEM for Brain Mapping. Brain Sci 2023; 13:brainsci13050711. [PMID: 37239183 DOI: 10.3390/brainsci13050711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/04/2023] [Accepted: 04/12/2023] [Indexed: 05/28/2023] Open
Abstract
The mammalian brain, with its complexity and intricacy, poses significant challenges for researchers aiming to understand its inner workings. Optical multilayer interference tomography (OMLIT) is a novel, promising imaging technique that enables the mapping and reconstruction of mesoscale all-cell brain atlases and is seamlessly compatible with tape-based serial scanning electron microscopy (SEM) for microscale mapping in the same tissue. However, currently, OMLIT suffers from imperfect coatings, leading to background noise and image contamination. In this study, we introduced a new imaging configuration using carbon spraying to eliminate the tape-coating step, resulting in reduced noise and enhanced imaging quality. We demonstrated the improved imaging quality and validated its applicability through a correlative light-electron imaging workflow. Our method successfully reconstructed all cells and vasculature within a large OMLIT dataset, enabling basic morphological classification and analysis. We also show that this approach can perform effectively on thicker sections, extending its applicability to sub-micron scale slices, saving sample preparation and imaging time, and increasing imaging throughput. Consequently, this method emerges as a promising candidate for high-speed, high-throughput brain tissue reconstruction and analysis. Our findings open new avenues for exploring the structure and function of the brain using OMLIT images.
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Affiliation(s)
- Tianyi Wang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China
- Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Peiyao Shi
- Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Dingsan Luo
- Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Jun Guo
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Hui Liu
- Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Jinyun Yuan
- Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Haiqun Jin
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Xiaolong Wu
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Yueyi Zhang
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Zhiwei Xiong
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
| | - Jinlong Zhu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Renjie Zhou
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Ruobing Zhang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China
- Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China
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D'Imprima E, Garcia Montero M, Gawrzak S, Ronchi P, Zagoriy I, Schwab Y, Jechlinger M, Mahamid J. Light and electron microscopy continuum-resolution imaging of 3D cell cultures. Dev Cell 2023; 58:616-632.e6. [PMID: 36990090 PMCID: PMC10114294 DOI: 10.1016/j.devcel.2023.03.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 12/14/2022] [Accepted: 03/02/2023] [Indexed: 03/30/2023]
Abstract
3D cell cultures, in particular organoids, are emerging models in the investigation of healthy or diseased tissues. Understanding the complex cellular sociology in organoids requires integration of imaging modalities across spatial and temporal scales. We present a multi-scale imaging approach that traverses millimeter-scale live-cell light microscopy to nanometer-scale volume electron microscopy by performing 3D cell cultures in a single carrier that is amenable to all imaging steps. This allows for following organoids' growth, probing their morphology with fluorescent markers, identifying areas of interest, and analyzing their 3D ultrastructure. We demonstrate this workflow on mouse and human 3D cultures and use automated image segmentation to annotate and quantitatively analyze subcellular structures in patient-derived colorectal cancer organoids. Our analyses identify local organization of diffraction-limited cell junctions in compact and polarized epithelia. The continuum-resolution imaging pipeline is thus suited to fostering basic and translational organoid research by simultaneously exploiting the advantages of light and electron microscopy.
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Affiliation(s)
- Edoardo D'Imprima
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Marta Garcia Montero
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Sylwia Gawrzak
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Paolo Ronchi
- Electron Microscopy Core Facility, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Ievgeniia Zagoriy
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Yannick Schwab
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany; Electron Microscopy Core Facility, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany
| | - Martin Jechlinger
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
| | - Julia Mahamid
- Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany; Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
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47
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Nikolaev YA, Ziolkowski LH, Pang S, Li WP, Feketa VV, Xu CS, Gracheva EO, Bagriantsev SN. 3D architecture and a bi-cellular mechanism of touch detection in mechanosensory corpuscle. bioRxiv 2023:2023.04.05.535701. [PMID: 37066170 PMCID: PMC10104047 DOI: 10.1101/2023.04.05.535701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Mechanosensory corpuscles detect transient touch and vibratory signals in the skin of vertebrates, enabling navigation, foraging, and precise manipulation of objects 1 . The corpuscle core comprises a terminal neurite of a mechanoreceptor afferent, the only known touch-sensing element within corpuscles, surrounded by terminal Schwann cells called lamellar cells (LCs) 2â€"4 . However, the precise corpuscular ultrastructure, and the role of LCs in touch detection are unknown. Here we used enhanced focused ion beam scanning electron microscopy and electron tomography to reveal the three-dimensional architecture of avian Meissner (Grandry) corpuscle 5 . We show that corpuscles contain a stack of LCs innervated by two afferents, which form large-area contacts with LCs. LCs form tether-like connections with the afferent membrane and contain dense core vesicles which release their content onto the afferent. Furthermore, by performing simultaneous electrophysiological recordings from both cell types, we show that mechanosensitive LCs use calcium influx to trigger action potential firing in the afferent and thus serve as physiological touch sensors in the skin. Our findings suggest a bi-cellular mechanism of touch detection, which comprises the afferent and LCs, likely enables corpuscles to encode the nuances of tactile stimuli.
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Pang S, Xu CS. Methods of enhanced FIB-SEM sample preparation and image acquisition. Methods Cell Biol 2023; 177:269-300. [PMID: 37451770 DOI: 10.1016/bs.mcb.2023.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
The ability to view biomolecules in cells and measure changes in their structure, quantity, distribution, and interaction is fundamental to understanding biology. By coupling nano -scale resolution with meso and even macro scale volumes, the enhanced focused ion beam-scanning electron microscopy (FIB-SEM) pipeline has enabled numerous transformational discoveries in life science, many of which were major new landmarks in their fields. This pipeline consists of EM sample preparation, FIB-SEM sample preparation, FIB-SEM imaging, data alignment, and image analysis. While the EM sample preparation, data alignment, and image analysis are consistent with those from other volume Electron Microscopy (vEM) approaches, the enhanced FIB-SEM sample preparation and imaging are unique to the rest of comparable methods. We here illustrate the detailed methods of enhanced FIB-SEM sample preparation and image acquisition that have not been previously described. These methods can also be applied to the conventional FIB-SEM platforms for improved image acquisition quality and pipeline throughput.
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Affiliation(s)
- Song Pang
- Yale School of Medicine, New Haven, CT, United States.
| | - C Shan Xu
- Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT, United States
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Handler A, Zhang Q, Pang S, Nguyen TM, Iskols M, Nolan-Tamariz M, Cattel S, Plumb R, Sanchez B, Ashjian K, Shotland A, Brown B, Kabeer M, Turecek J, Rankin G, Xiang W, Pavarino EC, Africawala N, Santiago C, Lee WCA, Shan Xu C, Ginty DD. Three-dimensional reconstructions of mechanosensory end organs suggest a unifying mechanism underlying dynamic, light touch. bioRxiv 2023:2023.03.17.533188. [PMID: 36993253 PMCID: PMC10055218 DOI: 10.1101/2023.03.17.533188] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Specialized mechanosensory end organs within mammalian skin-hair follicle-associated lanceolate complexes, Meissner corpuscles, and Pacinian corpuscles-enable our perception of light, dynamic touch 1 . In each of these end organs, fast-conducting mechanically sensitive neurons, called Aβ low-threshold mechanoreceptors (Aβ LTMRs), associate with resident glial cells, known as terminal Schwann cells (TSCs) or lamellar cells, to form complex axon ending structures. Lanceolate-forming and corpuscle-innervating Aβ LTMRs share a low threshold for mechanical activation, a rapidly adapting (RA) response to force indentation, and high sensitivity to dynamic stimuli 1-6 . How mechanical stimuli lead to activation of the requisite mechanotransduction channel Piezo2 7-15 and Aβ RA-LTMR excitation across the morphologically dissimilar mechanosensory end organ structures is not understood. Here, we report the precise subcellular distribution of Piezo2 and high-resolution, isotropic 3D reconstructions of all three end organs formed by Aβ RA-LTMRs determined by large volume enhanced Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) imaging. We found that within each end organ, Piezo2 is enriched along the sensory axon membrane and is minimally or not expressed in TSCs and lamellar cells. We also observed a large number of small cytoplasmic protrusions enriched along the Aβ RA-LTMR axon terminals associated with hair follicles, Meissner corpuscles, and Pacinian corpuscles. These axon protrusions reside within close proximity to axonal Piezo2, occasionally contain the channel, and often form adherens junctions with nearby non-neuronal cells. Our findings support a unified model for Aβ RA-LTMR activation in which axon protrusions anchor Aβ RA-LTMR axon terminals to specialized end organ cells, enabling mechanical stimuli to stretch the axon in hundreds to thousands of sites across an individual end organ and leading to activation of proximal Piezo2 channels and excitation of the neuron.
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Maheshwari R, Rahman MM, Drey S, Onyundo M, Fabig G, Martinez MAQ, Matus DQ, Müller-Reichert T, Cohen-Fix O. A membrane reticulum, the centriculum, affects centrosome size and function in Caenorhabditis elegans. Curr Biol 2023; 33:791-806.e7. [PMID: 36693370 PMCID: PMC10023444 DOI: 10.1016/j.cub.2022.12.059] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 11/21/2022] [Accepted: 12/21/2022] [Indexed: 01/24/2023]
Abstract
Centrosomes are cellular structures that nucleate microtubules. At their core is a pair of centrioles that recruit pericentriolar material (PCM). Although centrosomes are considered membraneless organelles, in many cell types, including human cells, centrosomes are surrounded by endoplasmic reticulum (ER)-derived membranes of unknown structure and function. Using volume electron microscopy (vEM), we show that centrosomes in the Caenorhabditis elegans (C. elegans) early embryo are surrounded by a three-dimensional (3D), ER-derived membrane reticulum that we call the centriculum, for centrosome-associated membrane reticulum. The centriculum is adjacent to the nuclear envelope in interphase and early mitosis and fuses with the fenestrated nuclear membrane at metaphase. Centriculum formation is dependent on the presence of an underlying centrosome and on microtubules. Conversely, increasing centriculum size by genetic means led to the expansion of the PCM, increased microtubule nucleation capacity, and altered spindle width. The effect of the centriculum on centrosome function suggests that in the C. elegans early embryo, the centrosome is not membraneless. Rather, it is encased in a membrane meshwork that affects its properties. We provide evidence that the centriculum serves as a microtubule "filter," preventing the elongation of a subset of microtubules past the centriculum. Finally, we propose that the fusion between the centriculum and the nuclear membrane contributes to nuclear envelope breakdown by coupling spindle elongation to nuclear membrane fenestration.
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Affiliation(s)
- Richa Maheshwari
- The Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mohammad M Rahman
- The Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD 20892, USA
| | - Seth Drey
- The Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD 20892, USA
| | - Megan Onyundo
- The Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD 20892, USA
| | - Gunar Fabig
- Experimental Center, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307 Dresden, Germany
| | - Michael A Q Martinez
- Department of Biochemistry and Cell Biology, Stony Brook University, 450 Life Sciences Building, Stony Brook, NY 11794, USA
| | - David Q Matus
- Department of Biochemistry and Cell Biology, Stony Brook University, 450 Life Sciences Building, Stony Brook, NY 11794, USA
| | - Thomas Müller-Reichert
- Experimental Center, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307 Dresden, Germany
| | - Orna Cohen-Fix
- The Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Bethesda, MD 20892, USA.
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