1
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Le DJ, Hafner A, Gaddam S, Wang KC, Boettiger AN. Super-enhancer interactomes from single cells link clustering and transcription. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.08.593251. [PMID: 38766104 PMCID: PMC11100725 DOI: 10.1101/2024.05.08.593251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Regulation of gene expression hinges on the interplay between enhancers and promoters, traditionally explored through pairwise analyses. Recent advancements in mapping genome folding, like GAM, SPRITE, and multi-contact Hi-C, have uncovered multi-way interactions among super-enhancers (SEs), spanning megabases, yet have not measured their frequency in single cells or the relationship between clustering and transcription. To close this gap, here we used multiplexed imaging to map the 3D positions of 376 SEs across thousands of mammalian nuclei. Notably, our single-cell images reveal that while SE-SE contacts are rare, SEs often form looser associations we termed "communities". These communities, averaging 4-5 SEs, assemble cooperatively under the combined effects of genomic tethers, Pol2 clustering, and nuclear compartmentalization. Larger communities are associated with more frequent and larger transcriptional bursts. Our work provides insights about the SE interactome in single cells that challenge existing hypotheses on SE clustering in the context of transcriptional regulation.
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Affiliation(s)
- Derek J. Le
- Department of Developmental Biology, Stanford University, Stanford, CA, United States
- Cancer Biology Program, Stanford University, Stanford, CA, United States
- Department of Dermatology, Stanford University, Stanford, CA, United States
- These authors contributed equally
| | - Antonina Hafner
- Department of Developmental Biology, Stanford University, Stanford, CA, United States
- These authors contributed equally
| | - Sadhana Gaddam
- Department of Dermatology, Stanford University, Stanford, CA, United States
| | - Kevin C. Wang
- Department of Dermatology, Stanford University, Stanford, CA, United States
| | - Alistair N. Boettiger
- Department of Developmental Biology, Stanford University, Stanford, CA, United States
- Lead contact
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2
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Murphy SE, Boettiger AN. Polycomb repression of Hox genes involves spatial feedback but not domain compaction or phase transition. Nat Genet 2024; 56:493-504. [PMID: 38361032 DOI: 10.1038/s41588-024-01661-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 01/10/2024] [Indexed: 02/17/2024]
Abstract
Polycomb group proteins have a critical role in silencing transcription during development. It is commonly proposed that Polycomb-dependent changes in genome folding, which compact chromatin, contribute directly to repression by blocking the binding of activating complexes. Recently, it has also been argued that liquid-liquid demixing of Polycomb proteins facilitates this compaction and repression by phase-separating target genes into a membraneless compartment. To test these models, we used Optical Reconstruction of Chromatin Architecture to trace the Hoxa gene cluster, a canonical Polycomb target, in thousands of single cells. Across multiple cell types, we find that Polycomb-bound chromatin frequently explores decompact states and partial mixing with neighboring chromatin, while remaining uniformly repressed, challenging the repression-by-compaction or phase-separation models. Using polymer simulations, we show that these observed flexible ensembles can be explained by 'spatial feedback'-transient contacts that contribute to the propagation of the epigenetic state (epigenetic memory), without inducing a globular organization.
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Affiliation(s)
- Sedona Eve Murphy
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Developmental Biology, Stanford University, Stanford, CA, USA
- Department of Cell Biology, Yale University, New Haven, CT, USA
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3
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Bialy N, Alber F, Andrews B, Angelo M, Beliveau B, Bintu L, Boettiger A, Boehm U, Brown CM, Maina MB, Chambers JJ, Cimini BA, Eliceiri K, Errington R, Faklaris O, Gaudreault N, Germain RN, Goscinski W, Grunwald D, Halter M, Hanein D, Hickey JW, Lacoste J, Laude A, Lundberg E, Ma J, Malacrida L, Moore J, Nelson G, Neumann EK, Nitschke R, Onami S, Pimentel JA, Plant AL, Radtke AJ, Sabata B, Schapiro D, Schöneberg J, Spraggins JM, Sudar D, Adrien Maria Vierdag WM, Volkmann N, Wählby C, Wang SS, Yaniv Z, Strambio-De-Castillia C. Harmonizing the Generation and Pre-publication Stewardship of FAIR Image data. ARXIV 2024:arXiv:2401.13022v4. [PMID: 38351940 PMCID: PMC10862930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured image data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable image data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled "Enabling Global Image Data Sharing in the Life Sciences," which is published in parallel and addresses the need to build the cyberinfrastructure for sharing the digital array data (arXiv:2401.13023 [q-bio.OT], https://doi.org/10.48550/arXiv.2401.13023). In this White Paper, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse image data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges, and democratize access to common practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.
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Affiliation(s)
- Nikki Bialy
- Morgridge Institute for Research, Madison, USA
| | | | | | | | | | | | | | | | | | | | | | - Beth A Cimini
- Broad Institute of MIT and Harvard, Imaging Platform, Cambridge, USA
| | - Kevin Eliceiri
- Morgridge Institute for Research, Madison, USA
- University of Wisconsin-Madison, Madison, USA
| | | | | | | | - Ronald N Germain
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA
| | | | | | - Michael Halter
- National Institute of Standards and Technology, Gaithersburg, USA
| | | | | | | | - Alex Laude
- Newcastle University, Newcastle upon Tyne, UK
| | - Emma Lundberg
- Stanford University, Palo Alto, USA
- SciLifeLab, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Jian Ma
- Carnegie Mellon University, Pittsburgh, USA
| | - Leonel Malacrida
- Institut Pasteur de Montevideo, & Universidad de la República, Montevideo, Uruguay
| | - Josh Moore
- German BioImaging-Gesellschaft für Mikroskopie und Bildanalyse e.V., Constance, Germany
| | - Glyn Nelson
- Newcastle University, Newcastle upon Tyne, UK
| | | | | | - Shuichi Onami
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | | | - Anne L Plant
- National Institute of Standards and Technology, Gaithersburg, USA
| | - Andrea J Radtke
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA
| | | | | | | | | | - Damir Sudar
- Quantitative Imaging Systems LLC, Portland, USA
| | | | | | | | | | - Ziv Yaniv
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, USA
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4
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Schmied C, Nelson MS, Avilov S, Bakker GJ, Bertocchi C, Bischof J, Boehm U, Brocher J, Carvalho MT, Chiritescu C, Christopher J, Cimini BA, Conde-Sousa E, Ebner M, Ecker R, Eliceiri K, Fernandez-Rodriguez J, Gaudreault N, Gelman L, Grunwald D, Gu T, Halidi N, Hammer M, Hartley M, Held M, Jug F, Kapoor V, Koksoy AA, Lacoste J, Le Dévédec S, Le Guyader S, Liu P, Martins GG, Mathur A, Miura K, Montero Llopis P, Nitschke R, North A, Parslow AC, Payne-Dwyer A, Plantard L, Ali R, Schroth-Diez B, Schütz L, Scott RT, Seitz A, Selchow O, Sharma VP, Spitaler M, Srinivasan S, Strambio-De-Castillia C, Taatjes D, Tischer C, Jambor HK. Community-developed checklists for publishing images and image analyses. Nat Methods 2024; 21:170-181. [PMID: 37710020 PMCID: PMC10922596 DOI: 10.1038/s41592-023-01987-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 07/26/2023] [Indexed: 09/16/2023]
Abstract
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.
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Affiliation(s)
- Christopher Schmied
- Fondazione Human Technopole, Milano, Italy.
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany.
| | - Michael S Nelson
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Sergiy Avilov
- Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany
| | - Gert-Jan Bakker
- Medical BioSciences Department, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Cristina Bertocchi
- Laboratory for Molecular Mechanics of Cell Adhesions, Pontificia Universidad Católica de Chile Santiago, Santiago de Chile, Chile
- Graduate School of Engineering Science, Osaka University, Osaka, Japan
| | | | | | - Jan Brocher
- Scientific Image Processing and Analysis, BioVoxxel, Ludwigshafen, Germany
| | - Mariana T Carvalho
- Nanophotonics and BioImaging Facility at INL, International Iberian Nanotechnology Laboratory, Braga, Portugal
| | | | - Jana Christopher
- Biochemistry Center Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Beth A Cimini
- Imaging Platform, Broad Institute, Cambridge, MA, USA
| | - Eduardo Conde-Sousa
- i3S, Instituto de Investigação e Inovação Em Saúde and INEB, Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
| | - Michael Ebner
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Berlin, Germany
| | - Rupert Ecker
- Translational Research Institute, Queensland University of Technology, Woolloongabba, Queensland, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia
- TissueGnostics GmbH, Vienna, Austria
| | - Kevin Eliceiri
- Department of Medical Physics and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Julia Fernandez-Rodriguez
- Centre for Cellular Imaging Core Facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Laurent Gelman
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - David Grunwald
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | | | - Nadia Halidi
- Advanced Light Microscopy Unit, Centre for Genomic Regulation, Barcelona, Spain
| | - Mathias Hammer
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Matthew Hartley
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Hinxton, UK
| | - Marie Held
- Centre for Cell Imaging, the University of Liverpool, Liverpool, UK
| | | | - Varun Kapoor
- Department of AI Research, Kapoor Labs, Paris, France
| | | | | | - Sylvia Le Dévédec
- Division of Drug Discovery and Safety, Cell Observatory, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | | | - Penghuan Liu
- Key Laboratory for Modern Measurement Technology and Instruments of Zhejiang Province, College of Optical and Electronic Technology, China Jiliang University, Hangzhou, China
| | - Gabriel G Martins
- Advanced Imaging Facility, Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | | | - Kota Miura
- Bioimage Analysis and Research, Heidelberg, Germany
| | | | - Roland Nitschke
- Life Imaging Center, Signalling Research Centres CIBSS and BIOSS, University of Freiburg, Freiburg, Germany
| | - Alison North
- Bio-Imaging Resource Center, the Rockefeller University, New York, NY, USA
| | - Adam C Parslow
- Baker Institute Microscopy Platform, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Alex Payne-Dwyer
- School of Physics, Engineering and Technology, University of York, Heslington, UK
| | - Laure Plantard
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Rizwan Ali
- King Abdullah International Medical Research Center (KAIMRC), Medical Research Core Facility and Platforms (MRCFP), King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Britta Schroth-Diez
- Light Microscopy Facility, Max Planck Institute of Molecular Cell Biology and Genetics Dresden, Dresden, Germany
| | | | - Ryan T Scott
- Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA
| | - Arne Seitz
- BioImaging and Optics Platform, Faculty of Life Sciences (SV), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Olaf Selchow
- Microscopy and BioImaging Consulting, Image Processing and Large Data Handling, Gera, Germany
| | - Ved P Sharma
- Bio-Imaging Resource Center, the Rockefeller University, New York, NY, USA
| | | | - Sathya Srinivasan
- Imaging and Morphology Support Core, Oregon National Primate Research Center, OHSU West Campus, Beaverton, OR, USA
| | | | - Douglas Taatjes
- Department of Pathology and Laboratory Medicine, Microscopy Imaging Center, Center for Biomedical Shared Resources, University of Vermont, Burlington, VT, USA
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5
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Schmied C, Nelson MS, Avilov S, Bakker GJ, Bertocchi C, Bischof J, Boehm U, Brocher J, Carvalho M, Chiritescu C, Christopher J, Cimini BA, Conde-Sousa E, Ebner M, Ecker R, Eliceiri K, Fernandez-Rodriguez J, Gaudreault N, Gelman L, Grunwald D, Gu T, Halidi N, Hammer M, Hartley M, Held M, Jug F, Kapoor V, Koksoy AA, Lacoste J, Dévédec SL, Guyader SL, Liu P, Martins GG, Mathur A, Miura K, Montero Llopis P, Nitschke R, North A, Parslow AC, Payne-Dwyer A, Plantard L, Ali R, Schroth-Diez B, Schütz L, Scott RT, Seitz A, Selchow O, Sharma VP, Spitaler M, Srinivasan S, Strambio-De-Castillia C, Taatjes D, Tischer C, Jambor HK. Community-developed checklists for publishing images and image analyses. ARXIV 2023:arXiv:2302.07005v2. [PMID: 36824427 PMCID: PMC9949169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality and explanatory power of microscopy data is in publications.
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Affiliation(s)
- Christopher Schmied
- Fondazione Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milano, Italy
- Present address: Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Str. 10, 13125 Berlin, Germany
| | - Michael S Nelson
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Sergiy Avilov
- Max Planck Institute of Immunobiology and Epigenetics, 79108 Freiburg, Germany
| | - Gert-Jan Bakker
- Medical BioSciences department, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Cristina Bertocchi
- Laboratory for Molecular mechanics of cell adhesions, Pontificia Universidad Católica de Chile Santiago
- Osaka University, Graduate School of Engineering Science, Japan
| | - Johanna Bischof
- Euro-BioImaging ERIC, Bio-Hub, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Ulrike Boehm
- Carl Zeiss AG, Carl-Zeiss-Straße 22, 73447 Oberkochen, Germany
| | - Jan Brocher
- BioVoxxel, Scientific Image Processing and Analysis, Eugen-Roth-Strasse 8, 67071 Ludwigshafen, Germany
| | - Mariana Carvalho
- Nanophotonics and BioImaging Facility at INL, International Iberian Nanotechnology Laboratory, 4715-330, Portugal
| | | | | | - Beth A Cimini
- Imaging Platform, Broad Institute, Cambridge, MA 02142
| | - Eduardo Conde-Sousa
- i3S, Instituto de Investigação e Inovação Em Saúde and INEB, Instituto de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
| | - Michael Ebner
- Fondazione Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milano, Italy
| | - Rupert Ecker
- Translational Research Institute, Queensland University of Technology, 37 Kent Street, Woolloongabba, QLD 4102, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD 4059, Australia
- TissueGnostics GmbH, 1020 Vienna, Austria
| | - Kevin Eliceiri
- Department of Medical Physics and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | | | | | - Laurent Gelman
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - David Grunwald
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | | | - Nadia Halidi
- Advanced Light Microscopy Unit, Centre for Genomic Regulation, Barcelona, Spain
| | - Mathias Hammer
- RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Matthew Hartley
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Marie Held
- Centre for Cell Imaging, The University of Liverpool, UK
| | - Florian Jug
- Fondazione Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milano, Italy
| | - Varun Kapoor
- Department of AI research, Kapoor Labs, Paris, 75005, France
| | | | | | - Sylvia Le Dévédec
- Division of Drug Discovery and Safety, Cell Observatory, Leiden Academic Centre for Drug Research, Leiden University, 2333 CC Leiden, The Netherlands
| | | | - Penghuan Liu
- Key Laboratory for Modern Measurement Technology and Instruments of Zhejiang Province, College of Optical and Electronic Technology, China Jiliang University, Hangzhou, China
| | - Gabriel G Martins
- Advanced Imaging Facility, Instituto Gulbenkian de Ciência, Oeiras 2780-156 - Portugal
| | - Aastha Mathur
- Euro-BioImaging ERIC, Bio-Hub, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Kota Miura
- Bioimage Analysis & Research, 69127 Heidelberg/Germany
| | | | - Roland Nitschke
- Life Imaging Center, Signalling Research Centres CIBSS and BIOSS, University of Freiburg, Germany
| | - Alison North
- Bio-Imaging Resource Center, The Rockefeller University, New York, NY USA
| | - Adam C Parslow
- Baker Institute Microscopy Platform, Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia
| | - Alex Payne-Dwyer
- School of Physics, Engineering and Technology, University of York, Heslington, YO10 5DD, UK
| | - Laure Plantard
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Rizwan Ali
- King Abdullah International Medical Research Center (KAIMRC), Medical Research Core Facility and Platforms (MRCFP), King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Ministry of National Guard Health Affairs (MNGHA), Riyadh 11481, Saudi Arabia
| | - Britta Schroth-Diez
- Light Microscopy Facility, Max Planck Institute of Molecular Cell Biology and Genetics Dresden, Pfotenhauerstrasse 108, 01307 Dresden, Germany
| | - Lucas Schütz
- ariadne.ai (Germany) GmbH, 69115 Heidelberg, Germany
| | - Ryan T Scott
- Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA
| | - Arne Seitz
- BioImaging & Optics Platform (BIOP), Ecole Polytechnique Fédérale de Lausanne (EPFL), Faculty of Life sciences (SV), CH-1015 Lausanne
| | - Olaf Selchow
- Microscopy & BioImaging Consulting, Image Processing & Large Data Handling, Tobias-Hoppe-Strassse 3, 07548 Gera, Germany
| | - Ved P Sharma
- Bio-Imaging Resource Center, The Rockefeller University, New York, NY USA
| | - Martin Spitaler
- Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany
| | - Sathya Srinivasan
- Imaging and Morphology Support Core, Oregon National Primate Research Center - (ONPRC - OHSU West Campus), Beaverton, Oregon 97006, USA
| | | | - Douglas Taatjes
- Department of Pathology and Laboratory Medicine, Microscopy Imaging Center (RRID# SCR_018821), Center for Biomedical Shared Resources, University of Vermont, Burlington, VT 05405 USA
| | - Christian Tischer
- Centre for Bioimage Analysis, EMBL Heidelberg, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Helena Klara Jambor
- NCT-UCC, Medizinische Fakultät TU Dresden, Fetscherstrasse 105, 01307 Dresden/Germany
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6
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Kemmer I, Keppler A, Serrano-Solano B, Rybina A, Özdemir B, Bischof J, El Ghadraoui A, Eriksson JE, Mathur A. Building a FAIR image data ecosystem for microscopy communities. Histochem Cell Biol 2023; 160:199-209. [PMID: 37341795 PMCID: PMC10492678 DOI: 10.1007/s00418-023-02203-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/27/2023] [Indexed: 06/22/2023]
Abstract
Bioimaging has now entered the era of big data with faster-than-ever development of complex microscopy technologies leading to increasingly complex datasets. This enormous increase in data size and informational complexity within those datasets has brought with it several difficulties in terms of common and harmonized data handling, analysis, and management practices, which are currently hampering the full potential of image data being realized. Here, we outline a wide range of efforts and solutions currently being developed by the microscopy community to address these challenges on the path towards FAIR bioimaging data. We also highlight how different actors in the microscopy ecosystem are working together, creating synergies that develop new approaches, and how research infrastructures, such as Euro-BioImaging, are fostering these interactions to shape the field.
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Affiliation(s)
- Isabel Kemmer
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Antje Keppler
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Beatriz Serrano-Solano
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Arina Rybina
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Buğra Özdemir
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Johanna Bischof
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - Ayoub El Ghadraoui
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany
| | - John E Eriksson
- Euro-BioImaging ERIC Statutory Seat, Tykistökatu 6, P.O. Box 123, 20521, Turku, Finland
| | - Aastha Mathur
- Euro-BioImaging ERIC Bio-Hub, European Molecular Biology Laboratory (EMBL) Heidelberg, Meyerhofstraße 1, 69117, Heidelberg, Germany.
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7
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Poger D, Yen L, Braet F. Big data in contemporary electron microscopy: challenges and opportunities in data transfer, compute and management. Histochem Cell Biol 2023; 160:169-192. [PMID: 37052655 PMCID: PMC10492738 DOI: 10.1007/s00418-023-02191-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/21/2023] [Indexed: 04/14/2023]
Abstract
The second decade of the twenty-first century witnessed a new challenge in the handling of microscopy data. Big data, data deluge, large data, data compliance, data analytics, data integrity, data interoperability, data retention and data lifecycle are terms that have introduced themselves to the electron microscopy sciences. This is largely attributed to the booming development of new microscopy hardware tools. As a result, large digital image files with an average size of one terabyte within one single acquisition session is not uncommon nowadays, especially in the field of cryogenic electron microscopy. This brings along numerous challenges in data transfer, compute and management. In this review, we will discuss in detail the current state of international knowledge on big data in contemporary electron microscopy and how big data can be transferred, computed and managed efficiently and sustainably. Workflows, solutions, approaches and suggestions will be provided, with the example of the latest experiences in Australia. Finally, important principles such as data integrity, data lifetime and the FAIR and CARE principles will be considered.
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Affiliation(s)
- David Poger
- Microscopy Australia, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Lisa Yen
- Microscopy Australia, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Filip Braet
- Australian Centre for Microscopy and Microanalysis, The University of Sydney, Sydney, NSW, 2006, Australia
- School of Medical Sciences (Molecular and Cellular Biomedicine), The University of Sydney, Sydney, NSW, 2006, Australia
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8
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Dekker J, Alber F, Aufmkolk S, Beliveau BJ, Bruneau BG, Belmont AS, Bintu L, Boettiger A, Calandrelli R, Disteche CM, Gilbert DM, Gregor T, Hansen AS, Huang B, Huangfu D, Kalhor R, Leslie CS, Li W, Li Y, Ma J, Noble WS, Park PJ, Phillips-Cremins JE, Pollard KS, Rafelski SM, Ren B, Ruan Y, Shav-Tal Y, Shen Y, Shendure J, Shu X, Strambio-De-Castillia C, Vertii A, Zhang H, Zhong S. Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project. Mol Cell 2023; 83:2624-2640. [PMID: 37419111 PMCID: PMC10528254 DOI: 10.1016/j.molcel.2023.06.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/10/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.
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Affiliation(s)
- Job Dekker
- University of Massachusetts Chan Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | - Frank Alber
- University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | - Benoit G Bruneau
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | - Bo Huang
- University of California, San Francisco, San Francisco, CA, USA
| | - Danwei Huangfu
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Reza Kalhor
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Wenbo Li
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yun Li
- University of North Carolina, Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Jian Ma
- Carnegie Mellon University, Pittsburgh, PA, USA
| | | | | | | | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA, USA; University of California, San Francisco, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA
| | | | - Bing Ren
- University of California, San Diego, La Jolla, CA, USA
| | - Yijun Ruan
- Zhejiang University, Hangzhou, Zhejiang, China
| | | | - Yin Shen
- University of California, San Francisco, San Francisco, CA, USA
| | | | - Xiaokun Shu
- University of California, San Francisco, San Francisco, CA, USA
| | | | | | | | - Sheng Zhong
- University of California, San Diego, La Jolla, CA, USA.
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9
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Helmbrecht H, Lin TJ, Janakiraman S, Decker K, Nance E. Prevalence and practices of immunofluorescent cell image processing: a systematic review. Front Cell Neurosci 2023; 17:1188858. [PMID: 37545881 PMCID: PMC10400723 DOI: 10.3389/fncel.2023.1188858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 07/06/2023] [Indexed: 08/08/2023] Open
Abstract
Background We performed a systematic review that identified at least 9,000 scientific papers on PubMed that include immunofluorescent images of cells from the central nervous system (CNS). These CNS papers contain tens of thousands of immunofluorescent neural images supporting the findings of over 50,000 associated researchers. While many existing reviews discuss different aspects of immunofluorescent microscopy, such as image acquisition and staining protocols, few papers discuss immunofluorescent imaging from an image-processing perspective. We analyzed the literature to determine the image processing methods that were commonly published alongside the associated CNS cell, microscopy technique, and animal model, and highlight gaps in image processing documentation and reporting in the CNS research field. Methods We completed a comprehensive search of PubMed publications using Medical Subject Headings (MeSH) terms and other general search terms for CNS cells and common fluorescent microscopy techniques. Publications were found on PubMed using a combination of column description terms and row description terms. We manually tagged the comma-separated values file (CSV) metadata of each publication with the following categories: animal or cell model, quantified features, threshold techniques, segmentation techniques, and image processing software. Results Of the almost 9,000 immunofluorescent imaging papers identified in our search, only 856 explicitly include image processing information. Moreover, hundreds of the 856 papers are missing thresholding, segmentation, and morphological feature details necessary for explainable, unbiased, and reproducible results. In our assessment of the literature, we visualized current image processing practices, compiled the image processing options from the top twelve software programs, and designed a road map to enhance image processing. We determined that thresholding and segmentation methods were often left out of publications and underreported or underutilized for quantifying CNS cell research. Discussion Less than 10% of papers with immunofluorescent images include image processing in their methods. A few authors are implementing advanced methods in image analysis to quantify over 40 different CNS cell features, which can provide quantitative insights in CNS cell features that will advance CNS research. However, our review puts forward that image analysis methods will remain limited in rigor and reproducibility without more rigorous and detailed reporting of image processing methods. Conclusion Image processing is a critical part of CNS research that must be improved to increase scientific insight, explainability, reproducibility, and rigor.
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Affiliation(s)
- Hawley Helmbrecht
- Department of Chemical Engineering, University of Washington, Seattle, WA, United States
| | - Teng-Jui Lin
- Department of Chemical Engineering, University of Washington, Seattle, WA, United States
| | - Sanjana Janakiraman
- Paul G. Allen School of Computer Science & Engineering, Seattle, WA, United States
| | - Kaleb Decker
- Department of Chemical Engineering, University of Washington, Seattle, WA, United States
| | - Elizabeth Nance
- Department of Chemical Engineering, University of Washington, Seattle, WA, United States
- Department of Bioengineering, University of Washington, Seattle, WA, United States
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10
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Hafner A, Park M, Berger SE, Murphy SE, Nora EP, Boettiger AN. Loop stacking organizes genome folding from TADs to chromosomes. Mol Cell 2023; 83:1377-1392.e6. [PMID: 37146570 PMCID: PMC10167645 DOI: 10.1016/j.molcel.2023.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 02/17/2023] [Accepted: 04/06/2023] [Indexed: 05/07/2023]
Abstract
Although population-level analyses revealed significant roles for CTCF and cohesin in mammalian genome organization, their contributions at the single-cell level remain incompletely understood. Here, we used a super-resolution microscopy approach to measure the effects of removal of CTCF or cohesin in mouse embryonic stem cells. Single-chromosome traces revealed cohesin-dependent loops, frequently stacked at their loop anchors forming multi-way contacts (hubs), bridging across TAD boundaries. Despite these bridging interactions, chromatin in intervening TADs was not intermixed, remaining separated in distinct loops around the hub. At the multi-TAD scale, steric effects from loop stacking insulated local chromatin from ultra-long range (>4 Mb) contacts. Upon cohesin removal, the chromosomes were more disordered and increased cell-cell variability in gene expression. Our data revise the TAD-centric understanding of CTCF and cohesin and provide a multi-scale, structural picture of how they organize the genome on the single-cell level through distinct contributions to loop stacking.
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Affiliation(s)
- Antonina Hafner
- Department of Developmental Biology, Stanford University, Stanford, CA, USA
| | - Minhee Park
- Department of Developmental Biology, Stanford University, Stanford, CA, USA
| | - Scott E Berger
- Biophysics Program, Stanford University, Stanford, CA, USA
| | - Sedona E Murphy
- Department of Developmental Biology, Stanford University, Stanford, CA, USA; Department of Genetics, Stanford University, Stanford, CA, USA
| | - Elphège P Nora
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA; Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
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11
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Kunis S, Bernhardt K, Hensel M. Setting up a data management infrastructure for bioimaging. Biol Chem 2023; 404:433-439. [PMID: 36853922 DOI: 10.1515/hsz-2022-0304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 01/27/2023] [Indexed: 03/01/2023]
Abstract
While the FAIR (Findable, Accessible, Interoperable, and Re-usable) principles are well accepted in the scientific community, there are still many challenges in implementing them in the day-to-day scientific process. Data management of microscopy images poses special challenges due to the volume, variety, and many proprietary formats. In particular, appropriate metadata collection, a basic requirement for FAIR data, is a real challenge for scientists due to the technical and content-related aspects. Researchers benefit here from interdisciplinary research network with centralized data management. The typically multimodal structure requires generalized data management and the corresponding acquisition of metadata. Here we report on the establishment of an appropriate infrastructure for the research network by a Core Facility and the development and integration of a software tool MDEmic that allows easy and convenient processing of metadata of microscopy images while providing high flexibility in terms of customization of metadata sets. Since it is also in the interest of the core facility to apply standards regarding the scope and serialization formats to realize successful and sustainable data management for bioimaging, we report on our efforts within the community to define standards in metadata, interfaces, and to reduce the barriers of daily data management.
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Affiliation(s)
- Susanne Kunis
- Department of Biology/Chemistry, Center of Cellular Nanoanalytics, Integrated Bioimaging Facility iBiOs, Osnabrück University, Babarastrasse 11, D-49076 Osnabrück, Germany
| | - Karen Bernhardt
- Department of Biology/Chemistry, IT, Osnabrück University, D-49076 Osnabrück, Germany
| | - Michael Hensel
- Department of Biology/Chemistry, Center of Cellular Nanoanalytics and Microbiology Division, Osnabrück University, D-49076 Osnabrück, Germany
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12
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Roy AL, Conroy RS, Taylor VG, Mietz J, Fingerman IM, Pazin MJ, Smith P, Hutter CM, Singer DS, Wilder EL. Elucidating the structure and function of the nucleus-The NIH Common Fund 4D Nucleome program. Mol Cell 2023; 83:335-342. [PMID: 36640770 PMCID: PMC9898192 DOI: 10.1016/j.molcel.2022.12.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/19/2022] [Accepted: 12/20/2022] [Indexed: 01/15/2023]
Abstract
Genomic architecture appears to play crucial roles in health and a variety of diseases. How nuclear structures reorganize over different timescales is elusive, partly because the tools needed to probe and perturb them are not as advanced as needed by the field. To fill this gap, the National Institutes of Health Common Fund started a program in 2015, called the 4D Nucleome (4DN), with the goal of developing and ultimately applying technologies to interrogate the structure and function of nuclear organization in space and time.
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Affiliation(s)
- Ananda L Roy
- Office of Strategic Coordination, National Institutes of Health, Bethesda, MD 20892, USA; Division of Program Coordination, Planning, and Strategic Initiative, National Institutes of Health, Bethesda, MD 20892, USA; Office of the National Institutes of Health Director, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Richard S Conroy
- Office of Strategic Coordination, National Institutes of Health, Bethesda, MD 20892, USA; Division of Program Coordination, Planning, and Strategic Initiative, National Institutes of Health, Bethesda, MD 20892, USA; Office of the National Institutes of Health Director, National Institutes of Health, Bethesda, MD 20892, USA
| | - Veronica G Taylor
- Office of Strategic Coordination, National Institutes of Health, Bethesda, MD 20892, USA; Division of Program Coordination, Planning, and Strategic Initiative, National Institutes of Health, Bethesda, MD 20892, USA; Office of the National Institutes of Health Director, National Institutes of Health, Bethesda, MD 20892, USA
| | - Judy Mietz
- National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Ian M Fingerman
- National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael J Pazin
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Phillip Smith
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD 20892, USA
| | - Carolyn M Hutter
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Dinah S Singer
- National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Elizabeth L Wilder
- Office of Strategic Coordination, National Institutes of Health, Bethesda, MD 20892, USA; Division of Program Coordination, Planning, and Strategic Initiative, National Institutes of Health, Bethesda, MD 20892, USA; Office of the National Institutes of Health Director, National Institutes of Health, Bethesda, MD 20892, USA
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13
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Faklaris O, Bancel-Vallée L, Dauphin A, Monterroso B, Frère P, Geny D, Manoliu T, de Rossi S, Cordelières FP, Schapman D, Nitschke R, Cau J, Guilbert T. Quality assessment in light microscopy for routine use through simple tools and robust metrics. J Biophys Biochem Cytol 2022; 221:213512. [PMID: 36173380 PMCID: PMC9526251 DOI: 10.1083/jcb.202107093] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 04/04/2022] [Accepted: 08/31/2022] [Indexed: 11/22/2022] Open
Abstract
Although there is a need to demonstrate reproducibility in light microscopy acquisitions, the lack of standardized guidelines monitoring microscope health status over time has so far impaired the widespread use of quality control (QC) measurements. As scientists from 10 imaging core facilities who encounter various types of projects, we provide affordable hardware and open source software tools, rigorous protocols, and define reference values to assess QC metrics for the most common fluorescence light microscopy modalities. Seven protocols specify metrics on the microscope resolution, field illumination flatness, chromatic aberrations, illumination power stability, stage drift, positioning repeatability, and spatial-temporal noise of camera sensors. We designed the MetroloJ_QC ImageJ/Fiji Java plugin to incorporate the metrics and automate analysis. Measurements allow us to propose an extensive characterization of the QC procedures that can be used by any seasoned microscope user, from research biologists with a specialized interest in fluorescence light microscopy through to core facility staff, to ensure reproducible and quantifiable microscopy results.
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Affiliation(s)
- Orestis Faklaris
- Montpellier Ressources Imagerie, Biocampus, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Leslie Bancel-Vallée
- Montpellier Ressources Imagerie, Biocampus, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Aurélien Dauphin
- Unite Genetique et Biologie du Développement U934, PICT-IBiSA, Institut Curie, INSERM, CNRS, PSL Research University, Paris, France
| | - Baptiste Monterroso
- Prism, Institut de Biologie Valrose, CNRS UMR 7277, INSERM 1091, University of Nice Sophia Antipolis - Parc Valrose, Nice, France
| | - Perrine Frère
- Plate-forme d'Imagerie de Tenon, UMR_S 1155, Hôpital Tenon, Paris, France
| | - David Geny
- Institut de Psychiatrie Et Neurosciences de Paris, INSERM U1266, Paris, France
| | - Tudor Manoliu
- Gustave Roussy, Université Paris-Saclay, Plate-forme Imagerie et Cytométrie, UMS AMMICa. Villejuif, France
| | - Sylvain de Rossi
- Montpellier Ressources Imagerie, Biocampus, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Fabrice P Cordelières
- University of Bordeaux, CNRS, INSERM, Bordeaux Imaging Center, UMS 3420, US 4, Bordeaux, France
| | - Damien Schapman
- Université of Rouen Normandie, INSERM, Plate-Forme de Recherche en Imagerie Cellulaire de Normandie, Rouen, France
| | - Roland Nitschke
- Life Imaging Center and Signalling Research Centres CIBSS and BIOSS, University Freiburg, Freiburg, Germany
| | - Julien Cau
- Montpellier Ressources Imagerie, Biocampus, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Thomas Guilbert
- Institut Cochin, INSERM (U1016), CNRS (UMR 8104), Universite de Paris (UMR-S1016), Paris, France
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14
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Schmidt C, Hanne J, Moore J, Meesters C, Ferrando-May E, Weidtkamp-Peters S. Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey. F1000Res 2022; 11:638. [PMID: 36405555 PMCID: PMC9641114 DOI: 10.12688/f1000research.121714.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/16/2022] [Indexed: 01/13/2023] Open
Abstract
Background: Knowing the needs of the bioimaging community with respect to research data management (RDM) is essential for identifying measures that enable adoption of the FAIR (findable, accessible, interoperable, reusable) principles for microscopy and bioimage analysis data across disciplines. As an initiative within Germany's National Research Data Infrastructure, we conducted this community survey in summer 2021 to assess the state of the art of bioimaging RDM and the community needs. Methods: An online survey was conducted with a mixed question-type design. We created a questionnaire tailored to relevant topics of the bioimaging community, including specific questions on bioimaging methods and bioimage analysis, as well as more general questions on RDM principles and tools. 203 survey entries were included in the analysis covering the perspectives from various life and biomedical science disciplines and from participants at different career levels. Results: The results highlight the importance and value of bioimaging RDM and data sharing. However, the practical implementation of FAIR practices is impeded by technical hurdles, lack of knowledge, and insecurity about the legal aspects of data sharing. The survey participants request metadata guidelines and annotation tools and endorse the usage of image data management platforms. At present, OMERO (Open Microscopy Environment Remote Objects) is the best known and most widely used platform. Most respondents rely on image processing and analysis, which they regard as the most time-consuming step of the bioimage data workflow. While knowledge about and implementation of electronic lab notebooks and data management plans is limited, respondents acknowledge their potential value for data handling and publication. Conclusion: The bioimaging community acknowledges and endorses the value of RDM and data sharing. Still, there is a need for information, guidance, and standardization to foster the adoption of FAIR data handling. This survey may help inspiring targeted measures to close this gap.
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Affiliation(s)
- Christian Schmidt
- Enabling Technology, German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany,Bioimaging Center, University of Konstanz, Konstanz, Germany,
| | - Janina Hanne
- German BioImaging - Society for Microscopy and Image Analysis e.V., Konstanz, Germany,
| | - Josh Moore
- German BioImaging - Society for Microscopy and Image Analysis e.V., Konstanz, Germany,Open Microscopy Environment Consortium, University of Dundee, Dundee, UK
| | - Christian Meesters
- High Performance Computing, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Elisa Ferrando-May
- Enabling Technology, German Cancer Research Center, Heidelberg, Baden-Württemberg, Germany,Bioimaging Center, University of Konstanz, Konstanz, Germany,German BioImaging - Society for Microscopy and Image Analysis e.V., Konstanz, Germany
| | - Stefanie Weidtkamp-Peters
- German BioImaging - Society for Microscopy and Image Analysis e.V., Konstanz, Germany,Center for Advanced Imaging, Heinrich Heine University Dusseldorf, Dusseldorf, Germany
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15
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Bourget MH, Kamentsky L, Ghosh SS, Mazzamuto G, Lazari A, Markiewicz CJ, Oostenveld R, Niso G, Halchenko YO, Lipp I, Takerkart S, Toussaint PJ, Khan AR, Nilsonne G, Castelli FM, Cohen-Adad J. Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data. Front Neurosci 2022; 16:871228. [PMID: 35516811 PMCID: PMC9063519 DOI: 10.3389/fnins.2022.871228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/01/2022] [Indexed: 11/13/2022] Open
Abstract
The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.
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Affiliation(s)
- Marie-Hélène Bourget
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Lee Kamentsky
- Kwanghun Chung Lab, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Satrajit S. Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Otolaryngology–Head and Neck Surgery, Harvard Medical School, Boston, MA, United States
| | - Giacomo Mazzamuto
- National Research Council, National Institute of Optics, Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Oxford, United Kingdom
| | | | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Guiomar Niso
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
| | - Yaroslav O. Halchenko
- Department of Psychological and Brain Sciences, Center for Open Neuroscience, Dartmouth College, Hanover, NH, United States
| | - Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Sylvain Takerkart
- Institut de Neurosciences de la Timone, CNRS–Aix Marseille Université, Marseille, France
| | - Paule-Joanne Toussaint
- Department of Neurology and Neurosurgery, Faculty of Medicine and Health Sciences, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Ali R. Khan
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Gustav Nilsonne
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Swedish National Data Service, Gothenburg University, Gothenburg, Sweden
| | | | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
- Mila – Quebec AI Institute, Montreal, QC, Canada
- Functional Neuroimaging Unit, Centre de Recherche de l’Institut Universitaire de Montréal (CRIUGM), Université de Montréal, Montreal, QC, Canada
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16
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Reiche MA, Aaron JS, Boehm U, DeSantis MC, Hobson CM, Khuon S, Lee RM, Chew TL. When light meets biology - how the specimen affects quantitative microscopy. J Cell Sci 2022; 135:274812. [PMID: 35319069 DOI: 10.1242/jcs.259656] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Fluorescence microscopy images should not be treated as perfect representations of biology. Many factors within the biospecimen itself can drastically affect quantitative microscopy data. Whereas some sample-specific considerations, such as photobleaching and autofluorescence, are more commonly discussed, a holistic discussion of sample-related issues (which includes less-routine topics such as quenching, scattering and biological anisotropy) is required to appropriately guide life scientists through the subtleties inherent to bioimaging. Here, we consider how the interplay between light and a sample can cause common experimental pitfalls and unanticipated errors when drawing biological conclusions. Although some of these discrepancies can be minimized or controlled for, others require more pragmatic considerations when interpreting image data. Ultimately, the power lies in the hands of the experimenter. The goal of this Review is therefore to survey how biological samples can skew quantification and interpretation of microscopy data. Furthermore, we offer a perspective on how to manage many of these potential pitfalls.
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Affiliation(s)
- Michael A Reiche
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA
| | - Jesse S Aaron
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA
| | - Ulrike Boehm
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA
| | - Michael C DeSantis
- Light Microscopy Facility, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147,USA
| | - Chad M Hobson
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA
| | - Satya Khuon
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.,Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA
| | - Rachel M Lee
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA
| | - Teng-Leong Chew
- Advanced Imaging Center, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.,Light Microscopy Facility, Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147,USA
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17
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Marx V. Caterina Strambio-De-Castillia. Nat Methods 2021; 18:1413. [PMID: 34862504 DOI: 10.1038/s41592-021-01342-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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18
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Hammer M, Huisman M, Rigano A, Boehm U, Chambers JJ, Gaudreault N, North AJ, Pimentel JA, Sudar D, Bajcsy P, Brown CM, Corbett AD, Faklaris O, Lacoste J, Laude A, Nelson G, Nitschke R, Farzam F, Smith CS, Grunwald D, Strambio-De-Castillia C. Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model. Nat Methods 2021; 18:1427-1440. [PMID: 34862501 PMCID: PMC9271325 DOI: 10.1038/s41592-021-01327-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Rigorous record-keeping and quality control are required to ensure the quality, reproducibility and value of imaging data. The 4DN Initiative and BINA here propose light Microscopy Metadata specifications that extend the OME data model, scale with experimental intent and complexity, and make it possible for scientists to create comprehensive records of imaging experiments.
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Affiliation(s)
- Mathias Hammer
- RNA Therapeutics Institute, UMass Chan Medical School, Worcester, MA, USA
- Department of Biology, Technical University of Darmstadt, Darmstadt, Germany
| | | | - Alessandro Rigano
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - Ulrike Boehm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - James J Chambers
- Institute for Applied Life Sciences, University of Massachusetts, Amherst, MA, USA
| | | | | | - Jaime A Pimentel
- Laboratorio Nacional de Microscopía Avanzada, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México
| | - Damir Sudar
- Quantitative Imaging Systems LLC, Portland, OR, USA
| | - Peter Bajcsy
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Claire M Brown
- Advanced BioImaging Facility (ABIF), McGill University, Montreal, Quebec, Canada
| | | | - Orestis Faklaris
- MRI, BCM, University of Montpellier, CNRS, INSERM, Montpellier, France
| | | | - Alex Laude
- Bioimaging Unit, Newcastle University, Newcastle upon Tyne, UK
| | - Glyn Nelson
- Bioimaging Unit, Newcastle University, Newcastle upon Tyne, UK
| | - Roland Nitschke
- Life Imaging Center and Signalling Research Centres CIBSS and BIOSS, University of Freiburg, Freiburg, Germany
| | - Farzin Farzam
- RNA Therapeutics Institute, UMass Chan Medical School, Worcester, MA, USA
| | - Carlas S Smith
- Delft Center for Systems and Control and Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - David Grunwald
- RNA Therapeutics Institute, UMass Chan Medical School, Worcester, MA, USA
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