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Nern A, Lösche F, Takemura SY, Burnett LE, Dreher M, Gruntman E, Hoeller J, Huang GB, Januszewski M, Klapoetke NC, Koskela S, Longden KD, Lu Z, Preibisch S, Qiu W, Rogers EM, Seenivasan P, Zhao A, Bogovic J, Canino BS, Clements J, Cook M, Finley-May S, Flynn MA, Hameed I, Hayworth KJ, Hopkins GP, Hubbard PM, Katz WT, Kovalyak J, Lauchie SA, Leonard M, Lohff A, Maldonado CA, Mooney C, Okeoma N, Olbris DJ, Ordish C, Paterson T, Phillips EM, Pietzsch T, Salinas JR, Rivlin PK, Scott AL, Scuderi LA, Takemura S, Talebi I, Thomson A, Trautman ET, Umayam L, Walsh C, Walsh JJ, Shan Xu C, Yakal EA, Yang T, Zhao T, Funke J, George R, Hess HF, Jefferis GSXE, Knecht C, Korff W, Plaza SM, Romani S, Saalfeld S, Scheffer LK, Berg S, Rubin GM, Reiser MB. Connectome-driven neural inventory of a complete visual system. bioRxiv 2024:2024.04.16.589741. [PMID: 38659887 PMCID: PMC11042306 DOI: 10.1101/2024.04.16.589741] [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] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain's volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly's visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the ~53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Gregory SXE Jefferis
- MRC Laboratory of Molecular Biology, Cambridge, UK and Department of Zoology, University of Cambridge, UK
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2
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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. Author Correction: Architecture and dynamics of a desmosome-endoplasmic reticulum complex. Nat Cell Biol 2024; 26:660. [PMID: 38347183 DOI: 10.1038/s41556-024-01376-0] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2024]
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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Moore J, Basurto-Lozada D, Besson S, Bogovic J, Bragantini J, Brown EM, Burel JM, Casas Moreno X, de Medeiros G, Diel EE, Gault D, Ghosh SS, Gold I, Halchenko YO, Hartley M, Horsfall D, Keller MS, Kittisopikul M, Kovacs G, Küpcü Yoldaş A, Kyoda K, le Tournoulx de la Villegeorges A, Li T, Liberali P, Lindner D, Linkert M, Lüthi J, Maitin-Shepard J, Manz T, Marconato L, McCormick M, Lange M, Mohamed K, Moore W, Norlin N, Ouyang W, Özdemir B, Palla G, Pape C, Pelkmans L, Pietzsch T, Preibisch S, Prete M, Rzepka N, Samee S, Schaub N, Sidky H, Solak AC, Stirling DR, Striebel J, Tischer C, Toloudis D, Virshup I, Walczysko P, Watson AM, Weisbart E, Wong F, Yamauchi KA, Bayraktar O, Cimini BA, Gehlenborg N, Haniffa M, Hotaling N, Onami S, Royer LA, Saalfeld S, Stegle O, Theis FJ, Swedlow JR. OME-Zarr: a cloud-optimized bioimaging file format with international community support. Histochem Cell Biol 2023; 160:223-251. [PMID: 37428210 PMCID: PMC10492740 DOI: 10.1007/s00418-023-02209-1] [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] [Accepted: 05/16/2023] [Indexed: 07/11/2023]
Abstract
A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.
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Affiliation(s)
- Josh Moore
- German BioImaging-Gesellschaft für Mikroskopie und Bildanalyse e.V., Constance, Germany.
| | | | - Sébastien Besson
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - John Bogovic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Eva M Brown
- Allen Institute for Cell Science, Seattle, WA, USA
| | - Jean-Marie Burel
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Xavier Casas Moreno
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | | | - David Gault
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | | | - Ilan Gold
- Harvard Medical School, Boston, MA, USA
| | | | - Matthew Hartley
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Cambridge, UK
| | - Dave Horsfall
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Mark Kittisopikul
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Gabor Kovacs
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Aybüke Küpcü Yoldaş
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Cambridge, UK
| | - Koji Kyoda
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | | | - Tong Li
- Wellcome Sanger Institute, Hinxton, UK
| | - Prisca Liberali
- Friedrich Miescher Institute for Biomedical Imaging, Basel, Switzerland
| | - Dominik Lindner
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | | | - Joel Lüthi
- Friedrich Miescher Institute for Biomedical Imaging, Basel, Switzerland
| | | | | | - Luca Marconato
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | | | | | - Khaled Mohamed
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - William Moore
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Nils Norlin
- Department of Experimental Medical Science & Lund Bioimaging Centre, Lund University, Lund, Sweden
| | - Wei Ouyang
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - Giovanni Palla
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | | | | | - Tobias Pietzsch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | | | | | - Nicholas Schaub
- Information Technology Branch, National Center for Advancing Translational Science, National Institutes of Health, Bethesda, USA
| | | | | | | | | | | | | | - Isaac Virshup
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Petr Walczysko
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | | | - Erin Weisbart
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Frances Wong
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Kevin A Yamauchi
- Department of Biosystems Science and Engineering, ETH Zürich, Zürich, Switzerland
| | | | - Beth A Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Nathan Hotaling
- Information Technology Branch, National Center for Advancing Translational Science, National Institutes of Health, Bethesda, USA
| | - Shuichi Onami
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | | | - Stephan Saalfeld
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Oliver Stegle
- Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jason R Swedlow
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
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Arthur BJ, Kim CM, Chen S, Preibisch S, Darshan R. A scalable implementation of the recursive least-squares algorithm for training spiking neural networks. Front Neuroinform 2023; 17:1099510. [PMID: 37441157 PMCID: PMC10333503 DOI: 10.3389/fninf.2023.1099510] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 06/05/2023] [Indexed: 07/15/2023] Open
Abstract
Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short period of time using minimal resources. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation can train networks of one million neurons, with 100 million plastic synapses and a billion static synapses, about 1,000 times faster than an unoptimized reference CPU implementation. We demonstrate the code's utility by training a network, in less than an hour, to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables a more interactive in-silico study of the dynamics and connectivity underlying multi-area computations. It also admits the possibility to train models as in-vivo experiments are being conducted, thus closing the loop between modeling and experiments.
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Affiliation(s)
- Benjamin J. Arthur
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Christopher M. Kim
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
- Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Ran Darshan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
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5
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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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6
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Moore J, Basurto-Lozada D, Besson S, Bogovic J, Bragantini J, Brown EM, Burel JM, Moreno XC, de Medeiros G, Diel EE, Gault D, Ghosh SS, Gold I, Halchenko YO, Hartley M, Horsfall D, Keller MS, Kittisopikul M, Kovacs G, Yoldaş AK, Kyoda K, de la Villegeorges ALT, Li T, Liberali P, Lindner D, Linkert M, Lüthi J, Maitin-Shepard J, Manz T, Marconato L, McCormick M, Lange M, Mohamed K, Moore W, Norlin N, Ouyang W, Özdemir B, Palla G, Pape C, Pelkmans L, Pietzsch T, Preibisch S, Prete M, Rzepka N, Samee S, Schaub N, Sidky H, Solak AC, Stirling DR, Striebel J, Tischer C, Toloudis D, Virshup I, Walczysko P, Watson AM, Weisbart E, Wong F, Yamauchi KA, Bayraktar O, Cimini BA, Gehlenborg N, Haniffa M, Hotaling N, Onami S, Royer LA, Saalfeld S, Stegle O, Theis FJ, Swedlow JR. OME-Zarr: a cloud-optimized bioimaging file format with international community support. bioRxiv 2023:2023.02.17.528834. [PMID: 36865282 PMCID: PMC9980008 DOI: 10.1101/2023.02.17.528834] [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: 02/23/2023]
Abstract
A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.
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Affiliation(s)
- Josh Moore
- German BioImaging – Gesellschaft für Mikroskopie und Bildanalyse e.V., Konstanz, Germany
| | | | - Sébastien Besson
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - John Bogovic
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Eva M. Brown
- Allen Institute for Cell Science, Seattle, WA, USA
| | - Jean-Marie Burel
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Xavier Casas Moreno
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | | | - David Gault
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | | | - Ilan Gold
- Harvard Medical School, Boston, MA, USA
| | | | - Matthew Hartley
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Cambridge, UK
| | - Dave Horsfall
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Mark Kittisopikul
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Gabor Kovacs
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Aybüke Küpcü Yoldaş
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Cambridge, UK
| | - Koji Kyoda
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | | | - Tong Li
- Wellcome Sanger Institute, Hinxton, UK
| | - Prisca Liberali
- Friedrich Miescher Institute for Biomedical Imaging, Basel, Switzerland
| | - Dominik Lindner
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | | | - Joel Lüthi
- Friedrich Miescher Institute for Biomedical Imaging, Basel, Switzerland
| | | | | | - Luca Marconato
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | | | - Merlin Lange
- Chan Zuckerberg Biohub, San Francisco, CA, United States
| | - Khaled Mohamed
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - William Moore
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Nils Norlin
- Department of Experimental Medical Science & Lund Bioimaging Centre, Lund University, Lund, Sweden
| | - Wei Ouyang
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - Giovanni Palla
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | | | | | - Tobias Pietzsch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | | | | | - Nicholas Schaub
- Information Technology Branch, National Center for Advancing Translational Science, National Institutes of Health
| | | | | | | | | | | | | | - Isaac Virshup
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Petr Walczysko
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | | | - Erin Weisbart
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Frances Wong
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
| | - Kevin A. Yamauchi
- Department of Biosystems Science and Engineering, ETH Zürich, Switzerland
| | | | - Beth A. Cimini
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | | | - Nathan Hotaling
- Information Technology Branch, National Center for Advancing Translational Science, National Institutes of Health
| | - Shuichi Onami
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Loic A. Royer
- Chan Zuckerberg Biohub, San Francisco, CA, United States
| | - Stephan Saalfeld
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Oliver Stegle
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Fabian J. Theis
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jason R. Swedlow
- Divisions of Molecular Cell and Developmental Biology, and Computational Biology, University of Dundee, Dundee, Scotland, UK
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7
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Malin-Mayor C, Hirsch P, Guignard L, McDole K, Wan Y, Lemon WC, Kainmueller D, Keller PJ, Preibisch S, Funke J. Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations. Nat Biotechnol 2023; 41:44-49. [PMID: 36065022 PMCID: PMC7614077 DOI: 10.1038/s41587-022-01427-7] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 07/12/2022] [Indexed: 01/19/2023]
Abstract
We present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8% of cell lineages spanning 1 h, as compared to 31.8% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.
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Affiliation(s)
| | - Peter Hirsch
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Faculty of Mathematics and Natural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Leo Guignard
- HHMI Janelia, Ashburn, VA, USA
- CNRS, UTLN, LIS 7020, Turing Centre for Living Systems, Aix Marseille University, Marseille, France
| | - Katie McDole
- HHMI Janelia, Ashburn, VA, USA
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Yinan Wan
- HHMI Janelia, Ashburn, VA, USA
- Biozentrum, University of Basel, Basel, Switzerland
| | | | - Dagmar Kainmueller
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Faculty of Mathematics and Natural Sciences, Humboldt-Universität zu Berlin, Berlin, Germany
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8
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Preusser F, Neuschulz A, Junker JP, Rajewsky N, Preibisch S. Long-term imaging reveals behavioral plasticity during C. elegans dauer exit. BMC Biol 2022; 20:277. [PMID: 36514066 DOI: 10.1186/s12915-022-01471-4] [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: 06/16/2022] [Accepted: 11/18/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND During their lifetime, animals must adapt their behavior to survive in changing environments. This ability requires the nervous system to undergo adjustments at distinct temporal scales, from short-term dynamic changes in expression of neurotransmitters and receptors to longer-term growth, spatial and connectivity reorganization, while integrating external stimuli. The nematode Caenorhabditis elegans provides a model of nervous system plasticity, in particular its dauer exit decision. Under unfavorable conditions, larvae will enter the non-feeding and non-reproductive stress-resistant dauer stage and adapt their behavior to cope with the harsh new environment, with active reversal under improved conditions leading to resumption of reproductive development. However, how different environmental stimuli regulate the exit decision mechanism and thereby drive the larva's behavioral change is unknown. To fill this gap and provide insights on behavioral changes over extended periods of time, we developed a new open hardware method for long-term imaging (12h) of C. elegans larvae. RESULTS Our WormObserver platform comprises open hardware and software components for video acquisition, automated processing of large image data (> 80k images/experiment) and data analysis. We identified dauer-specific behavioral motifs and characterized the behavioral trajectory of dauer exit in different environments and genetic backgrounds to identify key decision points and stimuli promoting dauer exit. Combining long-term behavioral imaging with transcriptomics data, we find that bacterial ingestion triggers a change in neuropeptide gene expression to establish post-dauer behavior. CONCLUSIONS Taken together, we show how a developing nervous system can robustly integrate environmental changes activate a developmental switch and adapt the organism's behavior to a new environment. WormObserver is generally applicable to other research questions within and beyond the C. elegans field, having a modular and customizable character and allowing assessment of behavioral plasticity over longer periods.
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Affiliation(s)
- Friedrich Preusser
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany. .,Institute for Biology, Humboldt University of Berlin, 10099, Berlin, Germany.
| | - Anika Neuschulz
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany.,Institute for Biology, Humboldt University of Berlin, 10099, Berlin, Germany
| | - Jan Philipp Junker
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany
| | - Nikolaus Rajewsky
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20147, USA.
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9
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Bahry E, Breimann L, Zouinkhi M, Epstein L, Kolyvanov K, Mamrak N, King B, Long X, Harrington KIS, Lionnet T, Preibisch S. RS-FISH: precise, interactive, fast, and scalable FISH spot detection. Nat Methods 2022; 19:1563-1567. [PMID: 36396787 PMCID: PMC9718671 DOI: 10.1038/s41592-022-01669-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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 09/28/2022] [Indexed: 11/18/2022]
Abstract
Fluorescent in-situ hybridization (FISH)-based methods extract spatially resolved genetic and epigenetic information from biological samples by detecting fluorescent spots in microscopy images, an often challenging task. We present Radial Symmetry-FISH (RS-FISH), an accurate, fast, and user-friendly software for spot detection in two- and three-dimensional images. RS-FISH offers interactive parameter tuning and readily scales to large datasets and image volumes of cleared or expanded samples using distributed processing on workstations, clusters, or the cloud. RS-FISH maintains high detection accuracy and low localization error across a wide range of signal-to-noise ratios, a key feature for single-molecule FISH, spatial transcriptomics, or spatial genomics applications.
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Affiliation(s)
- Ella Bahry
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
| | - Laura Breimann
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Marwan Zouinkhi
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Leo Epstein
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Helmholtz Imaging Platform, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Klim Kolyvanov
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
| | - Nicholas Mamrak
- Institute for Systems Genetics and Department of Cell Biology, NYU School of Medicine, New York, NY, USA
| | - Benjamin King
- Institute for Systems Genetics and Department of Cell Biology, NYU School of Medicine, New York, NY, USA
| | - Xi Long
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kyle I S Harrington
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
- Helmholtz Imaging Platform, Max Delbrück Center for Molecular Medicine, Berlin, Germany.
| | - Timothée Lionnet
- Institute for Systems Genetics and Department of Cell Biology, NYU School of Medicine, New York, NY, USA.
- Department of Bioengineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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10
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Gandin V, English BP, Freeman M, Leroux LP, Preibisch S, Walpita D, Jaramillo M, Singer RH. Cap-dependent translation initiation monitored in living cells. Nat Commun 2022; 13:6558. [PMID: 36323665 PMCID: PMC9630388 DOI: 10.1038/s41467-022-34052-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 10/06/2022] [Indexed: 11/19/2022] Open
Abstract
mRNA translation is tightly regulated to preserve cellular homeostasis. Despite extensive biochemical, genetic, and structural studies, a detailed understanding of mRNA translation regulation is lacking. Imaging methodologies able to resolve the binding dynamics of translation factors at single-cell and single-mRNA resolution were necessary to fully elucidate regulation of this paramount process. Here live-cell spectroscopy and single-particle tracking were combined to interrogate the binding dynamics of endogenous initiation factors to the 5'cap. The diffusion of initiation factors (IFs) changed markedly upon their association with mRNA. Quantifying their diffusion characteristics revealed the sequence of IFs assembly and disassembly in cell lines and the clustering of translation in neurons. This approach revealed translation regulation at high spatial and temporal resolution that can be applied to the formation of any endogenous complex that results in a measurable shift in diffusion.
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Affiliation(s)
- Valentina Gandin
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Brian P. English
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Melanie Freeman
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Louis-Philippe Leroux
- grid.418084.10000 0000 9582 2314Institut National de la Recherche Scientifique (INRS)-Centre Armand-Frappier Santé Biotechnologie (CAFSB), Laval, QC Canada
| | - Stephan Preibisch
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Deepika Walpita
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
| | - Maritza Jaramillo
- grid.418084.10000 0000 9582 2314Institut National de la Recherche Scientifique (INRS)-Centre Armand-Frappier Santé Biotechnologie (CAFSB), Laval, QC Canada
| | - Robert H. Singer
- grid.443970.dJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA USA
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11
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Nielsen AF, Bindereif A, Bozzoni I, Hanan M, Hansen TB, Irimia M, Kadener S, Kristensen LS, Legnini I, Morlando M, Jarlstad Olesen MT, Pasterkamp RJ, Preibisch S, Rajewsky N, Suenkel C, Kjems J. Best practice standards for circular RNA research. Nat Methods 2022; 19:1208-1220. [PMID: 35618955 PMCID: PMC9759028 DOI: 10.1038/s41592-022-01487-2] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [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: 07/07/2021] [Accepted: 03/16/2022] [Indexed: 12/26/2022]
Abstract
Circular RNAs (circRNAs) are formed in all domains of life and via different mechanisms. There has been an explosion in the number of circRNA papers in recent years; however, as a relatively young field, circRNA biology has an urgent need for common experimental standards for isolating, analyzing, expressing and depleting circRNAs. Here we propose a set of guidelines for circRNA studies based on the authors' experience. This Perspective will specifically address the major class of circRNAs in Eukarya that are generated by a spliceosome-catalyzed back-splicing event. We hope that the implementation of best practice principles for circRNA research will help move the field forward and allow a better functional understanding of this fascinating group of RNAs.
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Affiliation(s)
- Anne F Nielsen
- Interdisciplinary Nanoscience Center, Aarhus University, Aarhus, Denmark
- Center for Cellular Signal Patterns (CellPAT), Aarhus University, Aarhus, Denmark
| | - Albrecht Bindereif
- Department of Biology and Chemistry, Institute of Biochemistry, Justus Liebig University of Giessen, Giessen, Germany
| | - Irene Bozzoni
- Department of Biology and Biotechnology, Charles Darwin, and Center for Life Nano- & Neuro-Science, Fondazione Istituto Italiano di Tecnologia (IIT), Sapienza University of Rome, Rome, Italy
| | - Mor Hanan
- Department of Biological Chemistry, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Thomas B Hansen
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- TargoVax - Clinical Science, Oslo, Norway
| | - Manuel Irimia
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- ICREA, Barcelona, Spain
| | | | | | - Ivano Legnini
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Mariangela Morlando
- Department of Pharmaceutical Sciences, 'Department of Excellence 2018-2022', University of Perugia, Perugia, Italy
| | | | - R Jeroen Pasterkamp
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- HHMI Janelia Research campus, Ashburn, VA, USA
| | - Nikolaus Rajewsky
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Christin Suenkel
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Lonza - Drug Product Services, Basel, Switzerland
| | - Jørgen Kjems
- Interdisciplinary Nanoscience Center, Aarhus University, Aarhus, Denmark.
- Center for Cellular Signal Patterns (CellPAT), Aarhus University, Aarhus, Denmark.
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark.
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12
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Breimann L, Morao AK, Kim J, Jimenez DS, Maryn N, Bikkasani K, Carrozza MJ, Albritton SE, Kramer M, Street LA, Cerimi K, Schumann VF, Bahry E, Preibisch S, Woehler A, Ercan S. The H4K20 demethylase DPY-21 regulates the dynamics of condensin DC binding. J Cell Sci 2021; 135:273768. [PMID: 34918745 PMCID: PMC8917352 DOI: 10.1242/jcs.258818] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 11/29/2021] [Indexed: 11/26/2022] Open
Abstract
Condensin is a multi-subunit structural maintenance of chromosomes (SMC) complex that binds to and compacts chromosomes. Here, we addressed the regulation of condensin binding dynamics using Caenorhabditis elegans condensin DC, which represses X chromosomes in hermaphrodites for dosage compensation. We established fluorescence recovery after photobleaching (FRAP) using the SMC4 homolog DPY-27 and showed that a well-characterized ATPase mutation abolishes DPY-27 binding to X chromosomes. Next, we performed FRAP in the background of several chromatin modifier mutants that cause varying degrees of X chromosome derepression. The greatest effect was in a null mutant of the H4K20me2 demethylase DPY-21, where the mobile fraction of condensin DC reduced from ∼30% to 10%. In contrast, a catalytic mutant of dpy-21 did not regulate condensin DC mobility. Hi-C sequencing data from the dpy-21 null mutant showed little change compared to wild-type data, uncoupling Hi-C-measured long-range DNA contacts from transcriptional repression of the X chromosomes. Taken together, our results indicate that DPY-21 has a non-catalytic role in regulating the dynamics of condensin DC binding, which is important for transcription repression. Summary: The histone demethylase DPY-21 has catalytic and non-catalytic roles in condensin DC-mediated X chromosome repression. The non-catalytic activity regulates dynamics of condensin DC binding to X chromosomes.
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Affiliation(s)
- Laura Breimann
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA.,Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany.,Institute for Biology, Humboldt University of Berlin, Berlin, Germany
| | - Ana Karina Morao
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Jun Kim
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - David Sebastian Jimenez
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Nina Maryn
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Krishna Bikkasani
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Michael J Carrozza
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Sarah E Albritton
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Maxwell Kramer
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Lena Annika Street
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - Kustrim Cerimi
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Vic-Fabienne Schumann
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Ella Bahry
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany.,Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Andrew Woehler
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Sevinç Ercan
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, USA
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13
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Vladimirov N, Preusser F, Wisniewski J, Yaniv Z, Desai RA, Woehler A, Preibisch S. Dual-view light-sheet imaging through a tilted glass interface using a deformable mirror. Biomed Opt Express 2021; 12:2186-2203. [PMID: 33996223 PMCID: PMC8086485 DOI: 10.1364/boe.416737] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 02/12/2021] [Accepted: 02/16/2021] [Indexed: 05/02/2023]
Abstract
Light-sheet microscopy has become indispensable for imaging developing organisms, and imaging from multiple directions (views) is essential to improve its spatial resolution. We combine multi-view light-sheet microscopy with microfluidics using adaptive optics (deformable mirror) which corrects aberrations introduced by the 45o-tilted glass coverslip. The optimal shape of the deformable mirror is computed by an iterative algorithm that optimizes the point-spread function in two orthogonal views. Simultaneous correction in two optical arms is achieved via a knife-edge mirror that splits the excitation path and combines the detection paths. Our design allows multi-view light-sheet microscopy with microfluidic devices for precisely controlled experiments and high-content screening.
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Affiliation(s)
- Nikita Vladimirov
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
| | - Friedrich Preusser
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
| | - Jan Wisniewski
- Confocal Microscopy and Digital Imaging Facility, Experimental Immunology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Ziv Yaniv
- Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - Ravi Anand Desai
- Francis Crick Institute, Making Science and Technology Platform, London NW1 1AT, UK
| | - Andrew Woehler
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
- HHMI Janelia Research Campus, Ashburn, Virginia 20147, USA
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14
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Preusser F, dos Santos N, Contzen J, Stachelscheid H, Costa ÉT, Mergenthaler P, Preibisch S. FRC-QE: a robust and comparable 3D microscopy image quality metric for cleared organoids. Bioinformatics 2021; 37:3088-3090. [PMID: 33693580 PMCID: PMC8479654 DOI: 10.1093/bioinformatics/btab160] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 02/04/2021] [Accepted: 03/04/2021] [Indexed: 02/02/2023] Open
Abstract
SUMMARY Here, we propose Fourier ring correlation-based quality estimation (FRC-QE) as a new metric for automated image quality estimation in 3D fluorescence microscopy acquisitions of cleared organoids that yields comparable measurements across experimental replicates, clearing protocols and works for different microscopy modalities. AVAILABILITY AND IMPLEMENTATION FRC-QE is written in ImgLib2/Java and provided as an easy-to-use and macro-scriptable plugin for Fiji. Code, documentation, sample images and further information can be found under https://github.com/PreibischLab/FRC-QE. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Friedrich Preusser
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin 10115, Germany
| | - Natália dos Santos
- Molecular Oncology Center, Hospital Sirio-Libanese, São Paulo, SP 01308-050, Brazil
| | - Jörg Contzen
- Department of Experimental Neurology, Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Harald Stachelscheid
- Stem Cell Core Facility, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin 13353, Germany
| | - Érico Tosoni Costa
- Molecular Oncology Center, Hospital Sirio-Libanese, São Paulo, SP 01308-050, Brazil
| | - Philipp Mergenthaler
- Department of Experimental Neurology, Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin 10117, Germany,Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin 10117, Germany,BIH Academy, Berlin Institute of Health at Charité –Universitätsmedizin Berlin, Berlin 10117, Germany,To whom correspondence should be addressed. or
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin 10115, Germany,Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA,To whom correspondence should be addressed. or
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15
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Le Poul Y, Xin Y, Ling L, Mühling B, Jaenichen R, Hörl D, Bunk D, Harz H, Leonhardt H, Wang Y, Osipova E, Museridze M, Dharmadhikari D, Murphy E, Rohs R, Preibisch S, Prud'homme B, Gompel N. Regulatory encoding of quantitative variation in spatial activity of a Drosophila enhancer. Sci Adv 2020; 6:6/49/eabe2955. [PMID: 33268361 PMCID: PMC7821883 DOI: 10.1126/sciadv.abe2955] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 10/20/2020] [Indexed: 06/12/2023]
Abstract
Developmental enhancers control the expression of genes prefiguring morphological patterns. The activity of an enhancer varies among cells of a tissue, but collectively, expression levels in individual cells constitute a spatial pattern of gene expression. How the spatial and quantitative regulatory information is encoded in an enhancer sequence is elusive. To link spatial pattern and activity levels of an enhancer, we used systematic mutations of the yellow spot enhancer, active in developing Drosophila wings, and tested their effect in a reporter assay. Moreover, we developed an analytic framework based on the comprehensive quantification of spatial reporter activity. We show that the quantitative enhancer activity results from densely packed regulatory information along the sequence, and that a complex interplay between activators and multiple tiers of repressors carves the spatial pattern. Our results shed light on how an enhancer reads and integrates trans-regulatory landscape information to encode a spatial quantitative pattern.
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Affiliation(s)
- Yann Le Poul
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Yaqun Xin
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Liucong Ling
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Bettina Mühling
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Rita Jaenichen
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - David Hörl
- Human Biology and Bioimaging, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - David Bunk
- Human Biology and Bioimaging, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Hartmann Harz
- Human Biology and Bioimaging, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Heinrich Leonhardt
- Human Biology and Bioimaging, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Yingfei Wang
- Quantitative and Computational Biology, Departments of Biological Sciences, Chemistry, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089, USA
| | - Elena Osipova
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Mariam Museridze
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Deepak Dharmadhikari
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Eamonn Murphy
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany
| | - Remo Rohs
- Quantitative and Computational Biology, Departments of Biological Sciences, Chemistry, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089, USA
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Str. 10, 13092 Berlin, Germany
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Benjamin Prud'homme
- Aix-Marseille Université, CNRS, IBDM, Institut de Biologie du Développement de Marseille, Campus de Luminy Case 907, 13288 Marseille Cedex 9, France.
| | - Nicolas Gompel
- Evolutionary Ecology, Ludwig-Maximilians Universität München, Fakultät für Biologie, Biozentrum, Grosshaderner Strasse 2, 82152 Planegg-Martinsried, Germany.
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16
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Friedrich D, Friedel L, Finzel A, Herrmann A, Preibisch S, Loewer A. Stochastic transcription in the p53-mediated response to DNA damage is modulated by burst frequency. Mol Syst Biol 2019; 15:e9068. [PMID: 31885199 PMCID: PMC6886302 DOI: 10.15252/msb.20199068] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 11/04/2019] [Accepted: 11/07/2019] [Indexed: 12/15/2022] Open
Abstract
Discontinuous transcription has been described for different mammalian cell lines and numerous promoters. However, our knowledge of how the activity of individual promoters is adjusted by dynamic signaling inputs from transcription factors is limited. To address this question, we characterized the activity of selected target genes that are regulated by pulsatile accumulation of the tumor suppressor p53 in response to ionizing radiation. We performed time-resolved measurements of gene expression at the single-cell level by smFISH and used the resulting data to inform a mathematical model of promoter activity. We found that p53 target promoters are regulated by frequency modulation of stochastic bursting and can be grouped along three archetypes of gene expression. The occurrence of these archetypes cannot solely be explained by nuclear p53 abundance or promoter binding of total p53. Instead, we provide evidence that the time-varying acetylation state of p53's C-terminal lysine residues is critical for gene-specific regulation of stochastic bursting.
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Affiliation(s)
- Dhana Friedrich
- Department for BiologyTechnische Universität DarmstadtDarmstadtGermany
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
- Department for BiologyHumboldt Universität zu BerlinBerlinGermany
| | - Laura Friedel
- Department for BiologyTechnische Universität DarmstadtDarmstadtGermany
| | - Ana Finzel
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
| | - Andreas Herrmann
- Department for BiologyHumboldt Universität zu BerlinBerlinGermany
| | - Stephan Preibisch
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
- Janelia Research CampusHoward Hughes Medical InstituteVAAshburnUSA
| | - Alexander Loewer
- Department for BiologyTechnische Universität DarmstadtDarmstadtGermany
- Berlin Institute for Medical Systems BiologyMax Delbrück Center in the Helmholtz AssociationBerlinGermany
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17
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Lahmann I, Bröhl D, Zyrianova T, Isomura A, Czajkowski MT, Kapoor V, Griger J, Ruffault PL, Mademtzoglou D, Zammit PS, Wunderlich T, Spuler S, Kühn R, Preibisch S, Wolf J, Kageyama R, Birchmeier C. Oscillations of MyoD and Hes1 proteins regulate the maintenance of activated muscle stem cells. Genes Dev 2019; 33:524-535. [PMID: 30862660 PMCID: PMC6499323 DOI: 10.1101/gad.322818.118] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 02/19/2019] [Indexed: 11/25/2022]
Abstract
Lahmann et al. show that Hes1 controls the balance between proliferation and differentiation of activated muscle stem cells in both developing and regenerating muscle. Hes1 is expressed in an oscillatory manner in activated stem cells, where it drives the oscillatory expression of MyoD. The balance between proliferation and differentiation of muscle stem cells is tightly controlled, ensuring the maintenance of a cellular pool needed for muscle growth and repair. We demonstrate here that the transcriptional regulator Hes1 controls the balance between proliferation and differentiation of activated muscle stem cells in both developing and regenerating muscle. We observed that Hes1 is expressed in an oscillatory manner in activated stem cells where it drives the oscillatory expression of MyoD. MyoD expression oscillates in activated muscle stem cells from postnatal and adult muscle under various conditions: when the stem cells are dispersed in culture, when they remain associated with single muscle fibers, or when they reside in muscle biopsies. Unstable MyoD oscillations and long periods of sustained MyoD expression are observed in differentiating cells. Ablation of the Hes1 oscillator in stem cells interfered with stable MyoD oscillations and led to prolonged periods of sustained MyoD expression, resulting in increased differentiation propensity. This interfered with the maintenance of activated muscle stem cells, and impaired muscle growth and repair. We conclude that oscillatory MyoD expression allows the cells to remain in an undifferentiated and proliferative state and is required for amplification of the activated stem cell pool.
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Affiliation(s)
- Ines Lahmann
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Dominique Bröhl
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Tatiana Zyrianova
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Akihiro Isomura
- Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto 606-8507, Japan
| | - Maciej T Czajkowski
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Varun Kapoor
- Microscopy/Image Analysis, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Joscha Griger
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Pierre-Louis Ruffault
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Despoina Mademtzoglou
- IMRB U955-E10, Institut National de la Santé et de la Recherche Médicale (INSERM), Faculté de Medicine, Université Paris Est, 94000 Creteil, France
| | - Peter S Zammit
- Randall Centre for Cell and Molecular Biophysics, King's College London, London SE1 1UL, United Kingdom
| | - Thomas Wunderlich
- Max Planck Institute for Metabolism Research, 50931 Cologne, Germany
| | - Simone Spuler
- Muscle Research Unit, Experimental and Clinical Research Center, Max-Delbrück-Center, Charité Medical Faculty, 13125 Berlin, Germany
| | - Ralf Kühn
- Transgenic Core Facility, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany.,Berlin Institute of Health, 10178 Berlin, Germany
| | - Stephan Preibisch
- Microscopy/Image Analysis, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Jana Wolf
- Mathematical Modelling, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
| | - Ryoichiro Kageyama
- Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto 606-8507, Japan
| | - Carmen Birchmeier
- Developmental Biology/Signal Transduction, Max-Delbrück-Center for Molecular Medicine, 13125 Berlin, Germany
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18
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19
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Wolff C, Tinevez JY, Pietzsch T, Stamataki E, Harich B, Guignard L, Preibisch S, Shorte S, Keller PJ, Tomancak P, Pavlopoulos A. Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb. eLife 2018; 7:34410. [PMID: 29595475 PMCID: PMC5929908 DOI: 10.7554/elife.34410] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 03/26/2018] [Indexed: 12/11/2022] Open
Abstract
During development, coordinated cell behaviors orchestrate tissue and organ morphogenesis. Detailed descriptions of cell lineages and behaviors provide a powerful framework to elucidate the mechanisms of morphogenesis. To study the cellular basis of limb development, we imaged transgenic fluorescently-labeled embryos from the crustacean Parhyale hawaiensis with multi-view light-sheet microscopy at high spatiotemporal resolution over several days of embryogenesis. The cell lineage of outgrowing thoracic limbs was reconstructed at single-cell resolution with new software called Massive Multi-view Tracker (MaMuT). In silico clonal analyses suggested that the early limb primordium becomes subdivided into anterior-posterior and dorsal-ventral compartments whose boundaries intersect at the distal tip of the growing limb. Limb-bud formation is associated with spatial modulation of cell proliferation, while limb elongation is also driven by preferential orientation of cell divisions along the proximal-distal growth axis. Cellular reconstructions were predictive of the expression patterns of limb development genes including the BMP morphogen Decapentaplegic. During early life, animals develop from a single fertilized egg cell to hundreds, millions or even trillions of cells. These cells specialize to do different tasks; forming different tissues and organs like muscle, skin, lungs and liver. For more than a century, scientists have strived to understand the details of how animal cells become different and specialize, and have created many new techniques and technologies to help them achieve this goal. Limbs – such as arms, legs and wings – form from small lumps of cells called limb buds. Scientists use the shrimp-like crustacean, Parhyale hawaiensis, to study development, including limb growth. This species is useful because it is easy to grow, manipulate and observe its developing young in the laboratory. Understanding how its limbs develop offers important new insights into how limbs develop in other animals too. Wolff, Tinevez, Pietzsch et al. have now combined advanced microscopy with custom computer software, called Massive Multi-view Tracker (MaMuT) to investigate this. As limbs develop in Parhyale, the MaMuT software tracks how cells behave, and how they are organized. This analysis revealed that for cells to produce a limb bud, they need to split at an early stage into separate groups. These groups are organized along two body axes, one that goes from head to tail, and one that runs from back to belly. The limb grows perpendicular to these main body axes, along a new ‘proximal-distal’ axis that goes from nearest to furthest from the body. Wolff et al. found that the cells that contribute to the extremities of the limb divide faster than the ones that stay closer to the body. Finally, the results show that when cells in a limb divide, they mostly divide along the proximal-distal axis, producing one cell that is further from the body than the other. These cell activities may help limbs to get longer as they grow. Notably, the groups of cells seen by Wolff et al. were expressing genes that had previously been identified in developing limbs. This helps to validate the new results and to identify which active genes control the behaviors of the analyzed cells. These findings reveal new ways to study animal development. This approach could have many research uses and may help to link the mechanisms of cell biology to their effects. It could also contribute to new understanding of developmental and genetic conditions that affect human health.
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Affiliation(s)
- Carsten Wolff
- Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | - Tobias Pietzsch
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Evangelia Stamataki
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Benjamin Harich
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Léo Guignard
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Stephan Preibisch
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | | | - Philipp J Keller
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Pavel Tomancak
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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20
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Abstract
Light sheet fluorescence microscopy (LSFM) is gaining more and more popularity as a method to image embryonic development. The main advantages of LSFM compared to confocal systems are its low phototoxicity, gentle mounting strategies, fast acquisition with high signal to noise ratio and the possibility of imaging samples from various angles (views) for long periods of time. Imaging from multiple views unleashes the full potential of LSFM, but at the same time it can create terabyte-sized datasets. Processing such datasets is the biggest challenge of using LSFM. In this protocol we outline some solutions to this problem. Until recently, LSFM was mostly performed in laboratories that had the expertise to build and operate their own light sheet microscopes. However, in the last three years several commercial implementations of LSFM became available, which are multipurpose and easy to use for any developmental biologist. This article is primarily directed to those researchers, who are not LSFM technology developers, but want to employ LSFM as a tool to answer specific developmental biology questions. Here, we use imaging of zebrafish eye development as an example to introduce the reader to LSFM technology and we demonstrate applications of LSFM across multiple spatial and temporal scales. This article describes a complete experimental protocol starting with the mounting of zebrafish embryos for LSFM. We then outline the options for imaging using the commercially available light sheet microscope. Importantly, we also explain a pipeline for subsequent registration and fusion of multiview datasets using an open source solution implemented as a Fiji plugin. While this protocol focuses on imaging the developing zebrafish eye and processing data from a particular imaging setup, most of the insights and troubleshooting suggestions presented here are of general use and the protocol can be adapted to a variety of light sheet microscopy experiments.
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Affiliation(s)
- Jaroslav Icha
- Max Planck Institute of Molecular Cell Biology and Genetics;
| | | | | | - Pavel Tomancak
- Max Planck Institute of Molecular Cell Biology and Genetics
| | - Stephan Preibisch
- Max Planck Institute of Molecular Cell Biology and Genetics; HHMI Janelia Research Campus; Berlin Institute of Medical Systems Biology of the Max Delbrück Center
| | - Caren Norden
- Max Planck Institute of Molecular Cell Biology and Genetics;
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21
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Schmied C, Steinbach P, Pietzsch T, Preibisch S, Tomancak P. An automated workflow for parallel processing of large multiview SPIM recordings. Bioinformatics 2015; 32:1112-4. [PMID: 26628585 PMCID: PMC4896369 DOI: 10.1093/bioinformatics/btv706] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Accepted: 11/25/2015] [Indexed: 11/18/2022] Open
Abstract
Summary: Selective Plane Illumination Microscopy (SPIM) allows to image developing organisms in 3D at unprecedented temporal resolution over long periods of time. The resulting massive amounts of raw image data requires extensive processing interactively via dedicated graphical user interface (GUI) applications. The consecutive processing steps can be easily automated and the individual time points can be processed independently, which lends itself to trivial parallelization on a high performance computing (HPC) cluster. Here, we introduce an automated workflow for processing large multiview, multichannel, multiillumination time-lapse SPIM data on a single workstation or in parallel on a HPC cluster. The pipeline relies on snakemake to resolve dependencies among consecutive processing steps and can be easily adapted to any cluster environment for processing SPIM data in a fraction of the time required to collect it. Availability and implementation: The code is distributed free and open source under the MIT license http://opensource.org/licenses/MIT. The source code can be downloaded from github: https://github.com/mpicbg-scicomp/snakemake-workflows. Documentation can be found here: http://fiji.sc/Automated_workflow_for_parallel_Multiview_Reconstruction. Contact: schmied@mpi-cbg.de Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Christopher Schmied
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Peter Steinbach
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Tobias Pietzsch
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Stephan Preibisch
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany, HHMI Janelia Research Campus, Ashburn, VA, USA and Max Delbrück Center for Molecular Medicine, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Pavel Tomancak
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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22
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Smith CS, Preibisch S, Joseph A, Abrahamsson S, Rieger B, Myers E, Singer RH, Grunwald D. Nuclear accessibility of β-actin mRNA is measured by 3D single-molecule real-time tracking. ACTA ACUST UNITED AC 2015; 209:609-19. [PMID: 26008747 PMCID: PMC4442804 DOI: 10.1083/jcb.201411032] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Imaging single proteins or RNAs allows direct visualization of the inner workings of the cell. Typically, three-dimensional (3D) images are acquired by sequentially capturing a series of 2D sections. The time required to step through the sample often impedes imaging of large numbers of rapidly moving molecules. Here we applied multifocus microscopy (MFM) to instantaneously capture 3D single-molecule real-time images in live cells, visualizing cell nuclei at 10 volumes per second. We developed image analysis techniques to analyze messenger RNA (mRNA) diffusion in the entire volume of the nucleus. Combining MFM with precise registration between fluorescently labeled mRNA, nuclear pore complexes, and chromatin, we obtained globally optimal image alignment within 80-nm precision using transformation models. We show that β-actin mRNAs freely access the entire nucleus and fewer than 60% of mRNAs are more than 0.5 µm away from a nuclear pore, and we do so for the first time accounting for spatial inhomogeneity of nuclear organization.
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Affiliation(s)
- Carlas S Smith
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
| | - Stephan Preibisch
- Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY 10461 Howard Hughes Medical Institute Janelia Farm, Ashburn, VA 20147 Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany
| | - Aviva Joseph
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
| | - Sara Abrahamsson
- Howard Hughes Medical Institute Janelia Farm, Ashburn, VA 20147 The Rockefeller University, New York, NY 10065
| | - Bernd Rieger
- Department of Imaging Sciences, Technical University Delft, Delft 2628CJ, Netherlands
| | - Eugene Myers
- Howard Hughes Medical Institute Janelia Farm, Ashburn, VA 20147 Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany
| | - Robert H Singer
- Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, NY 10461 Howard Hughes Medical Institute Janelia Farm, Ashburn, VA 20147
| | - David Grunwald
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605
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23
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Preibisch S, Amat F, Stamataki E, Sarov M, Singer RH, Myers E, Tomancak P. Efficient Bayesian-based multiview deconvolution. Nat Methods 2014; 11:645-8. [PMID: 24747812 DOI: 10.1038/nmeth.2929] [Citation(s) in RCA: 188] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2013] [Accepted: 03/06/2014] [Indexed: 12/20/2022]
Abstract
Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware.
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Affiliation(s)
- Stephan Preibisch
- 1] Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. [2] Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. [3] Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York, USA. [4] Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Fernando Amat
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Evangelia Stamataki
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Mihail Sarov
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Robert H Singer
- 1] Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. [2] Department of Anatomy and Structural Biology, Albert Einstein College of Medicine, Bronx, New York, USA. [3] Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Eugene Myers
- 1] Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. [2] Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Pavel Tomancak
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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24
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Jug F, Pietzsch T, Preibisch S, Tomancak P. Bioimage Informatics in the context of Drosophila research. Methods 2014; 68:60-73. [PMID: 24732429 DOI: 10.1016/j.ymeth.2014.04.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [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: 02/25/2014] [Revised: 04/02/2014] [Accepted: 04/04/2014] [Indexed: 01/05/2023] Open
Abstract
Modern biological research relies heavily on microscopic imaging. The advanced genetic toolkit of Drosophila makes it possible to label molecular and cellular components with unprecedented level of specificity necessitating the application of the most sophisticated imaging technologies. Imaging in Drosophila spans all scales from single molecules to the entire populations of adult organisms, from electron microscopy to live imaging of developmental processes. As the imaging approaches become more complex and ambitious, there is an increasing need for quantitative, computer-mediated image processing and analysis to make sense of the imagery. Bioimage Informatics is an emerging research field that covers all aspects of biological image analysis from data handling, through processing, to quantitative measurements, analysis and data presentation. Some of the most advanced, large scale projects, combining cutting edge imaging with complex bioimage informatics pipelines, are realized in the Drosophila research community. In this review, we discuss the current research in biological image analysis specifically relevant to the type of systems level image datasets that are uniquely available for the Drosophila model system. We focus on how state-of-the-art computer vision algorithms are impacting the ability of Drosophila researchers to analyze biological systems in space and time. We pay particular attention to how these algorithmic advances from computer science are made usable to practicing biologists through open source platforms and how biologists can themselves participate in their further development.
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Affiliation(s)
- Florian Jug
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
| | - Tobias Pietzsch
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
| | - Stephan Preibisch
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Department of Anatomy and Structural Biology, Gruss Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Pavel Tomancak
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
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25
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Pitrone PG, Schindelin J, Stuyvenberg L, Preibisch S, Weber M, Eliceiri KW, Huisken J, Tomancak P. OpenSPIM: an open-access light-sheet microscopy platform. Nat Methods 2013; 10:598-9. [PMID: 23749304 DOI: 10.1038/nmeth.2507] [Citation(s) in RCA: 253] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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26
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Pietzsch T, Preibisch S, Tomancak P, Saalfeld S. ImgLib2--generic image processing in Java. Bioinformatics 2013. [DOI: 10.1093/bioinformatics/bts685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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27
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Abstract
Summary: ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins. Availability: ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib. Supplementary Information:Supplementary data are available at Bioinformatics Online. Contact: saalfeld@mpi-cbg.de
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Affiliation(s)
- Tobias Pietzsch
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
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28
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Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012. [PMID: 22743772 DOI: 10.1038/nmeth.2019.fiji] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2023]
Abstract
Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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Affiliation(s)
- Johannes Schindelin
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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29
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Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012. [PMID: 22743772 DOI: 10.1038/nmeth.2019.pmid:22743772;pmcid:pmc3855844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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Affiliation(s)
- Johannes Schindelin
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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30
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Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A. Fiji: an open-source platform for biological-image analysis. Nat Methods 2012; 9:676-82. [PMID: 22743772 DOI: 10.1038/nmeth.2019] [Citation(s) in RCA: 33678] [Impact Index Per Article: 2806.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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Affiliation(s)
- Johannes Schindelin
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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31
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Cardona A, Saalfeld S, Schindelin J, Arganda-Carreras I, Preibisch S, Longair M, Tomancak P, Hartenstein V, Douglas RJ. TrakEM2 software for neural circuit reconstruction. PLoS One 2012; 7:e38011. [PMID: 22723842 PMCID: PMC3378562 DOI: 10.1371/journal.pone.0038011] [Citation(s) in RCA: 586] [Impact Index Per Article: 48.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2012] [Accepted: 04/28/2012] [Indexed: 11/24/2022] Open
Abstract
A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.
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Affiliation(s)
- Albert Cardona
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
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32
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Abstract
Light microscopy images suffer from poor contrast due to light absorption and scattering by the media. The resulting decay in contrast varies exponentially across the image along the incident light path. Classical space invariant deconvolution approaches, while very effective in deblurring, are not designed for the restoration of uneven illumination in microscopy images. In this article, we present a modified radiative transfer theory approach to solve the contrast degradation problem of light sheet microscopy (LSM) images. We confirmed the effectiveness of our approach through simulation as well as real LSM images.
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Affiliation(s)
- Mohammad Shorif Uddin
- Imaging Informatics Division, Bioinformatics Institute, 30 Biopolis Street, Singapore 13867, Singapore
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Carrillo Oesterreich F, Preibisch S, Neugebauer KM. Global analysis of nascent RNA reveals transcriptional pausing in terminal exons. Mol Cell 2010; 40:571-81. [PMID: 21095587 DOI: 10.1016/j.molcel.2010.11.004] [Citation(s) in RCA: 203] [Impact Index Per Article: 14.5] [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: 04/22/2010] [Revised: 07/07/2010] [Accepted: 09/22/2010] [Indexed: 11/17/2022]
Abstract
Pre-mRNA splicing is catalyzed by the spliceosome, which can assemble on pre-mRNA cotranscriptionally. However, whether splicing generally occurs during transcription has not been addressed. Indeed, splicing catalysis is expected to occur posttranscriptionally in yeast, where the shortness of terminal exons should leave insufficient time for splicing. Here, we isolate endogenous S. cerevisiae nascent RNA and determine gene-specific splicing efficiencies and transcription profiles, using high-density tiling microarrays. Surprisingly, we find that splicing occurs cotranscriptionally for the majority of intron-containing genes. Analysis of transcription profiles reveals Pol II pausing within the terminal exons of these genes. Intronless and inefficiently spliced genes lack this pause. In silico simulations of transcription and splicing kinetics confirm that this pausing event provides sufficient time for splicing before termination. The discovery of terminal exon pausing demonstrates functional coupling of transcription and splicing near gene ends.
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Cardona A, Saalfeld S, Preibisch S, Schmid B, Cheng A, Pulokas J, Tomancak P, Hartenstein V. An integrated micro- and macroarchitectural analysis of the Drosophila brain by computer-assisted serial section electron microscopy. PLoS Biol 2010; 8:e1000502. [PMID: 20957184 PMCID: PMC2950124 DOI: 10.1371/journal.pbio.1000502] [Citation(s) in RCA: 200] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2010] [Accepted: 08/19/2010] [Indexed: 11/18/2022] Open
Abstract
The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile.
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Affiliation(s)
- Albert Cardona
- Institute of Neuroinformatics, ETH/University of Zürich, Zürich, Switzerland
| | - Stephan Saalfeld
- Max Plank Institute for Molecular Cell Biology and Genetics, Dresden, Germany
| | - Stephan Preibisch
- Max Plank Institute for Molecular Cell Biology and Genetics, Dresden, Germany
| | - Benjamin Schmid
- Lehrstuhl für Genetik und Neurobiologie, University of Würzburg, Würzburg, Germany
| | - Anchi Cheng
- Automated Molecular Imaging Group, The Scripps Research Institute (TSRI), San Diego, California, United States of America
| | - Jim Pulokas
- Automated Molecular Imaging Group, The Scripps Research Institute (TSRI), San Diego, California, United States of America
| | - Pavel Tomancak
- Max Plank Institute for Molecular Cell Biology and Genetics, Dresden, Germany
| | - Volker Hartenstein
- Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
- Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
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Oteiza P, Köppen M, Krieg M, Pulgar E, Farias C, Melo C, Preibisch S, Müller D, Tada M, Hartel S, Heisenberg CP, Concha ML. Planar cell polarity signalling regulates cell adhesion properties in progenitors of the zebrafish laterality organ. Development 2010; 137:3459-68. [PMID: 20843857 DOI: 10.1242/dev.049981] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Organ formation requires the precise assembly of progenitor cells into a functional multicellular structure. Mechanical forces probably participate in this process but how they influence organ morphogenesis is still unclear. Here, we show that Wnt11- and Prickle1a-mediated planar cell polarity (PCP) signalling coordinates the formation of the zebrafish ciliated laterality organ (Kupffer's vesicle) by regulating adhesion properties between organ progenitor cells (the dorsal forerunner cells, DFCs). Combined inhibition of Wnt11 and Prickle1a reduces DFC cell-cell adhesion and impairs their compaction and arrangement during vesicle lumen formation. This leads to the formation of a mis-shapen vesicle with small fragmented lumina and shortened cilia, resulting in severely impaired organ function and, as a consequence, randomised laterality of both molecular and visceral asymmetries. Our results reveal a novel role for PCP-dependent cell adhesion in coordinating the supracellular organisation of progenitor cells during vertebrate laterality organ formation.
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Affiliation(s)
- Pablo Oteiza
- Anatomy and Developmental Biology Program, Institute of Biomedical Sciences, University of Chile, Santiago, Chile
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Oteiza P, Koeppen M, Krieg M, Preibisch S, Haertel S, Mueller D, Heisenberg CP, Concha M. 03-P045 Wnt11/Pk1a-mediated planar cell polarity signalling orchestrates epithelial organ morphogenesis by regulating N-cadherin dependent cell adhesion forces. Mech Dev 2009. [DOI: 10.1016/j.mod.2009.06.098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Abstract
Motivation: Modern anatomical and developmental studies often require high-resolution imaging of large specimens in three dimensions (3D). Confocal microscopy produces high-resolution 3D images, but is limited by a relatively small field of view compared with the size of large biological specimens. Therefore, motorized stages that move the sample are used to create a tiled scan of the whole specimen. The physical coordinates provided by the microscope stage are not precise enough to allow direct reconstruction (Stitching) of the whole image from individual image stacks. Results: To optimally stitch a large collection of 3D confocal images, we developed a method that, based on the Fourier Shift Theorem, computes all possible translations between pairs of 3D images, yielding the best overlap in terms of the cross-correlation measure and subsequently finds the globally optimal configuration of the whole group of 3D images. This method avoids the propagation of errors by consecutive registration steps. Additionally, to compensate the brightness differences between tiles, we apply a smooth, non-linear intensity transition between the overlapping images. Our stitching approach is fast, works on 2D and 3D images, and for small image sets does not require prior knowledge about the tile configuration. Availability: The implementation of this method is available as an ImageJ plugin distributed as a part of the Fiji project (FijiisjustImageJ: http://pacific.mpi-cbg.de/). Contact:tomancak@mpi-cbg.de
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Affiliation(s)
- Stephan Preibisch
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
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Binder H, Krohn K, Preibisch S. "Hook"-calibration of GeneChip-microarrays: chip characteristics and expression measures. Algorithms Mol Biol 2008; 3:11. [PMID: 18759984 PMCID: PMC2543012 DOI: 10.1186/1748-7188-3-11] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2008] [Accepted: 08/29/2008] [Indexed: 11/10/2022] Open
Abstract
Background Microarray experiments rely on several critical steps that may introduce biases and uncertainty in downstream analyses. These steps include mRNA sample extraction, amplification and labelling, hybridization, and scanning causing chip-specific systematic variations on the raw intensity level. Also the chosen array-type and the up-to-dateness of the genomic information probed on the chip affect the quality of the expression measures. In the accompanying publication we presented theory and algorithm of the so-called hook method which aims at correcting expression data for systematic biases using a series of new chip characteristics. Results In this publication we summarize the essential chip characteristics provided by this method, analyze special benchmark experiments to estimate transcript related expression measures and illustrate the potency of the method to detect and to quantify the quality of a particular hybridization. It is shown that our single-chip approach provides expression measures responding linearly on changes of the transcript concentration over three orders of magnitude. In addition, the method calculates a detection call judging the relation between the signal and the detection limit of the particular measurement. The performance of the method in the context of different chip generations and probe set assignments is illustrated. The hook method characterizes the RNA-quality in terms of the 3'/5'-amplification bias and the sample-specific calling rate. We show that the proper judgement of these effects requires the disentanglement of non-specific and specific hybridization which, otherwise, can lead to misinterpretations of expression changes. The consequences of modifying probe/target interactions by either changing the labelling protocol or by substituting RNA by DNA targets are demonstrated. Conclusion The single-chip based hook-method provides accurate expression estimates and chip-summary characteristics using the natural metrics given by the hybridization reaction with the potency to develop new standards for microarray quality control and calibration.
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Binder H, Preibisch S. "Hook"-calibration of GeneChip-microarrays: theory and algorithm. Algorithms Mol Biol 2008; 3:12. [PMID: 18759985 PMCID: PMC2546411 DOI: 10.1186/1748-7188-3-12] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2008] [Accepted: 08/29/2008] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND : The improvement of microarray calibration methods is an essential prerequisite for quantitative expression analysis. This issue requires the formulation of an appropriate model describing the basic relationship between the probe intensity and the specific transcript concentration in a complex environment of competing interactions, the estimation of the magnitude these effects and their correction using the intensity information of a given chip and, finally the development of practicable algorithms which judge the quality of a particular hybridization and estimate the expression degree from the intensity values. RESULTS : We present the so-called hook-calibration method which co-processes the log-difference (delta) and -sum (sigma) of the perfect match (PM) and mismatch (MM) probe-intensities. The MM probes are utilized as an internal reference which is subjected to the same hybridization law as the PM, however with modified characteristics. After sequence-specific affinity correction the method fits the Langmuir-adsorption model to the smoothed delta-versus-sigma plot. The geometrical dimensions of this so-called hook-curve characterize the particular hybridization in terms of simple geometric parameters which provide information about the mean non-specific background intensity, the saturation value, the mean PM/MM-sensitivity gain and the fraction of absent probes. This graphical summary spans a metrics system for expression estimates in natural units such as the mean binding constants and the occupancy of the probe spots. The method is single-chip based, i.e. it separately uses the intensities for each selected chip. CONCLUSION : The hook-method corrects the raw intensities for the non-specific background hybridization in a sequence-specific manner, for the potential saturation of the probe-spots with bound transcripts and for the sequence-specific binding of specific transcripts. The obtained chip characteristics in combination with the sensitivity corrected probe-intensity values provide expression estimates scaled in natural units which are given by the binding constants of the particular hybridization.
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Binder H, Preibisch S, Kirsten T. Base pair interactions and hybridization isotherms of matched and mismatched oligonucleotide probes on microarrays. Langmuir 2005; 21:9287-302. [PMID: 16171364 DOI: 10.1021/la051231s] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The microarray technology enables the expression degree of thousands of genes to be estimated at once by the measurement of the abundance of the respective messenger RNA. This method is based on the sequence specific binding of RNA to DNA probes and its detection using fluorescent labels. The raw intensity data are affected by the sequence-specific affinity of probe and RNA for duplex formation, by the background intensity due to nonspecific hybridization at small transcript concentrations and by the saturation of the probes at high transcript concentration owing to surface adsorption. We address these issues using a binding model which describes specific and nonspecific hybridization in terms of a competitive two-species Langmuir isotherm and DNA/RNA duplex formation in terms of sequence-specific, single-base related interactions. The GeneChip microarrays technology uses pairs of so-called perfect match (PM) and mismatch (MM) oligonucleotide probes to estimate the amount of nonspecific hybridization. The mean affinity of the probes decrease according to PM(specific) > MM(specific) >> PM(nonspecific) approximately MM(nonspecific). The stability of specific and nonspecific DNA/RNA duplexes is mainly determined by Watson Crick (WC) pairings. Mismatched self-complementary pairings in the middle of the MM sequence only weakly contribute to the duplex stability. The asymmetry of base pair interaction in the DNA/RNA hybrid duplexes gives rise to a duplet-like symmetry of the PM - MM intensity difference at dominating nonspecific hybridization and a triplet-like symmetry at specific hybridization. The signal intensities of the PM and MM probes and their difference are assessed in terms of sensitivity and specificity. The presented results imply the refinement of existing algorithms of probe level analysis to correct microarray data for nonspecific background intensities and saturation on the basis of the probe sequence.
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Affiliation(s)
- Hans Binder
- Interdisciplinary Centre for Bioinformatics, University of Leipzig, Haertelstrasse 16-18, D-04107 Leipzig, Germany.
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Abstract
Gene expression analysis by means of microarrays is based on the sequence-specific binding of RNA to DNA oligonucleotide probes and its measurement using fluorescent labels. The binding of RNA fragments involving sequences other than the intended target is problematic because it adds a chemical background to the signal, which is not related to the expression degree of the target gene. The article presents a molecular signature of specific and nonspecific hybridization with potential consequences for gene expression analysis. We analyzed the signal intensities of perfect match (PM) and mismatch (MM) probes of GeneChip microarrays to specify the effect of specific and nonspecific hybridization. We found that these events give rise to different relations between the PM and MM intensities as function of the middle base of the PM, namely a triplet-like (C > G approximately T > A > 0) and a duplet-like (C approximately T > 0 > G approximately A) pattern of the PM-MM log-intensity difference upon binding of specific and nonspecific RNA fragments, respectively. The systematic behavior of the intensity difference can be rationalized on the level of basepairings of DNA/RNA oligonucleotide duplexes in the middle of the probe sequence. Nonspecific binding is characterized by the reversal of the central Watson-Crick (WC) pairing for each PM/MM probe pair, whereas specific binding refers to the combination of a WC and a self-complementary (SC) pairing in PM and MM probes, respectively. The Gibbs free energy contribution of WC pairs to duplex stability is asymmetric for purines and pyrimidines of the PM and decreases according to C > G approximately T > A. SC pairings on the average only weakly contribute to duplex stability. The intensity of complementary MM introduces a systematic source of variation which decreases the precision of expression measures based on the MM intensities.
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Affiliation(s)
- Hans Binder
- Interdisciplinary Centre for Bioinformatics, University of Leipzig, Leipzig, Germany.
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