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Schmidt C, Boissonnet T, Dohle J, Bernhardt K, Ferrando-May E, Wernet T, Nitschke R, Kunis S, Weidtkamp-Peters S. A practical guide to bioimaging research data management in core facilities. J Microsc 2024; 294:350-371. [PMID: 38752662 DOI: 10.1111/jmi.13317] [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: 04/09/2024] [Revised: 04/29/2024] [Accepted: 04/30/2024] [Indexed: 05/21/2024]
Abstract
Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data-driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well-established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management. They are positioned at the intersection of research groups, IT infrastructure providers, the institution´s administration, and microscope vendors. In the frame of German BioImaging - Society for Microscopy and Image Analysis (GerBI-GMB), cross-institutional working groups and third-party funded projects were initiated in recent years to advance the bioimaging community's capability and capacity for FAIR bioimage data management. Here, we provide an imaging-core-facility-centric perspective outlining the experience and current strategies in Germany to facilitate the practical adoption of the FAIR principles closely aligned with the international bioimaging community. We highlight which tools and services are ready to be implemented and what the future directions for FAIR bioimage data have to offer.
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Affiliation(s)
- Christian Schmidt
- Enabling Technology Department, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tom Boissonnet
- Center for Advanced Imaging, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Julia Dohle
- Center of Cellular Nanoanalytics, Integrated Bioimaging Facility iBiOs, University of Osnabrück, Osnabrück, Germany
| | - Karen Bernhardt
- Center of Cellular Nanoanalytics, Integrated Bioimaging Facility iBiOs, University of Osnabrück, Osnabrück, Germany
| | - Elisa Ferrando-May
- Enabling Technology Department, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Tobias Wernet
- Life Imaging Center, University of Freiburg, Freiburg, Germany
| | - Roland Nitschke
- Life Imaging Center, University of Freiburg, Freiburg, Germany
- CIBSS and BIOSS - Centres for Biological Signalling Studies, University of Freiburg, Freiburg, Germany
| | - Susanne Kunis
- Center of Cellular Nanoanalytics, Integrated Bioimaging Facility iBiOs, University of Osnabrück, Osnabrück, Germany
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2
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Nuernberg E, Bruch R, Hafner M, Rudolf R, Vitacolonna M. Quantitative Analysis of Whole-Mount Fluorescence-Stained Tumor Spheroids in Phenotypic Drug Screens. Methods Mol Biol 2024; 2764:311-334. [PMID: 38393603 DOI: 10.1007/978-1-0716-3674-9_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2024]
Abstract
Three-dimensional cell cultures, such as spheroids or organoids, serve as important models for drug screening purposes. Optical tissue clearing (OTC) enhances the visualization of fluorescence stainings and enables in toto microscopy of 3D cell culture models. Furthermore, subsequent automated image analysis tools convert qualitative confocal image sets into quantitative data. In this chapter, we describe a detailed protocol for preparation of HT29 cancer spheroids, 3D in toto immunostaining, glycerol-based OTC, whole-mount imaging, and semi-automated downstream image processing and segmentation for nuclear image analysis using open-source software.
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Affiliation(s)
- Elina Nuernberg
- Institute of Molecular and Cell Biology, Mannheim University of Applied Sciences, Mannheim, Germany
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
| | - Roman Bruch
- Institute of Molecular and Cell Biology, Mannheim University of Applied Sciences, Mannheim, Germany
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen, Germany
| | - Mathias Hafner
- Institute of Molecular and Cell Biology, Mannheim University of Applied Sciences, Mannheim, Germany
| | - Ruediger Rudolf
- Institute of Molecular and Cell Biology, Mannheim University of Applied Sciences, Mannheim, Germany
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany
| | - Mario Vitacolonna
- Institute of Molecular and Cell Biology, Mannheim University of Applied Sciences, Mannheim, Germany.
- Center for Mass Spectrometry and Optical Spectroscopy (CeMOS), Mannheim University of Applied Sciences, Mannheim, Germany.
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3
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Schwayer C, Brückner DB. Connecting theory and experiment in cell and tissue mechanics. J Cell Sci 2023; 136:jcs261515. [PMID: 38149871 DOI: 10.1242/jcs.261515] [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] [Indexed: 12/28/2023] Open
Abstract
Understanding complex living systems, which are fundamentally constrained by physical phenomena, requires combining experimental data with theoretical physical and mathematical models. To develop such models, collaborations between experimental cell biologists and theoreticians are increasingly important but these two groups often face challenges achieving mutual understanding. To help navigate these challenges, this Perspective discusses different modelling approaches, including bottom-up hypothesis-driven and top-down data-driven models, and highlights their strengths and applications. Using cell mechanics as an example, we explore the integration of specific physical models with experimental data from the molecular, cellular and tissue level up to multiscale input. We also emphasize the importance of constraining model complexity and outline strategies for crosstalk between experimental design and model development. Furthermore, we highlight how physical models can provide conceptual insights and produce unifying and generalizable frameworks for biological phenomena. Overall, this Perspective aims to promote fruitful collaborations that advance our understanding of complex biological systems.
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Affiliation(s)
- Cornelia Schwayer
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland
| | - David B Brückner
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
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Way GP, Sailem H, Shave S, Kasprowicz R, Carragher NO. Evolution and impact of high content imaging. SLAS DISCOVERY : ADVANCING LIFE SCIENCES R & D 2023; 28:292-305. [PMID: 37666456 DOI: 10.1016/j.slasd.2023.08.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/09/2023] [Accepted: 08/29/2023] [Indexed: 09/06/2023]
Abstract
The field of high content imaging has steadily evolved and expanded substantially across many industry and academic research institutions since it was first described in the early 1990's. High content imaging refers to the automated acquisition and analysis of microscopic images from a variety of biological sample types. Integration of high content imaging microscopes with multiwell plate handling robotics enables high content imaging to be performed at scale and support medium- to high-throughput screening of pharmacological, genetic and diverse environmental perturbations upon complex biological systems ranging from 2D cell cultures to 3D tissue organoids to small model organisms. In this perspective article the authors provide a collective view on the following key discussion points relevant to the evolution of high content imaging: • Evolution and impact of high content imaging: An academic perspective • Evolution and impact of high content imaging: An industry perspective • Evolution of high content image analysis • Evolution of high content data analysis pipelines towards multiparametric and phenotypic profiling applications • The role of data integration and multiomics • The role and evolution of image data repositories and sharing standards • Future perspective of high content imaging hardware and software.
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Affiliation(s)
- Gregory P Way
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Heba Sailem
- School of Cancer and Pharmaceutical Sciences, King's College London, UK
| | - Steven Shave
- GlaxoSmithKline Medicines Research Centre, Gunnels Wood Rd, Stevenage SG1 2NY, UK; Edinburgh Cancer Research, Cancer Research UK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, UK
| | - Richard Kasprowicz
- GlaxoSmithKline Medicines Research Centre, Gunnels Wood Rd, Stevenage SG1 2NY, UK
| | - Neil O Carragher
- Edinburgh Cancer Research, Cancer Research UK Scotland Centre, Institute of Genetics and Cancer, University of Edinburgh, UK.
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5
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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: 6] [Impact Index Per Article: 6.0] [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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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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7
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Ouyang W, Bowman RW, Wang H, Bumke KE, Collins JT, Spjuth O, Carreras-Puigvert J, Diederich B. An Open-Source Modular Framework for Automated Pipetting and Imaging Applications. Adv Biol (Weinh) 2022; 6:e2101063. [PMID: 34693668 DOI: 10.1002/adbi.202101063] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/14/2021] [Indexed: 01/27/2023]
Abstract
The number of samples in biological experiments is continuously increasing, but complex protocols and human error in many cases lead to suboptimal data quality and hence difficulties in reproducing scientific findings. Laboratory automation can alleviate many of these problems by precisely reproducing machine-readable protocols. These instruments generally require high up-front investments, and due to the lack of open application programming interfaces (APIs), they are notoriously difficult for scientists to customize and control outside of the vendor-supplied software. Here, automated, high-throughput experiments are demonstrated for interdisciplinary research in life science that can be replicated on a modest budget, using open tools to ensure reproducibility by combining the tools OpenFlexure, Opentrons, ImJoy, and UC2. This automated sample preparation and imaging pipeline can easily be replicated and established in many laboratories as well as in educational contexts through easy-to-understand algorithms and easy-to-build microscopes. Additionally, the creation of feedback loops, with later pipetting or imaging steps depending on the analysis of previously acquired images, enables the realization of fully autonomous "smart" microscopy experiments. All documents and source files are publicly available to prove the concept of smart lab automation using inexpensive, open tools. It is believed this democratizes access to the power and repeatability of automated experiments.
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Affiliation(s)
- Wei Ouyang
- W. Ouyang, Science for Life Laboratory School of Engineering Sciences in Chemistry, Biotechnology and Health KTH - Royal Institute of Technology, Stockholm, 114 28, Sweden
| | - Richard W Bowman
- R. W. Bowman, K. E. Bumke, J. T. Collins, Department of Physics, University of Bath, Bath, BA2 7AY, UK
| | - Haoran Wang
- H. Wang, B. Diederich, Leibniz Institute for Photonic Technology, Albert-Einstein-Str. 9, 07749, Jena, Germany.,H. Wang, B. Diederich, Institute of Physical Chemistry, Friedrich-Schiller-Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
| | - Kaspar E Bumke
- R. W. Bowman, K. E. Bumke, J. T. Collins, Department of Physics, University of Bath, Bath, BA2 7AY, UK
| | - Joel T Collins
- R. W. Bowman, K. E. Bumke, J. T. Collins, Department of Physics, University of Bath, Bath, BA2 7AY, UK
| | - Ola Spjuth
- O. Spjuth, J. Carreras-Puigvert, Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, Uppsala, SE-75124, Sweden
| | - Jordi Carreras-Puigvert
- O. Spjuth, J. Carreras-Puigvert, Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, Uppsala, SE-75124, Sweden
| | - Benedict Diederich
- H. Wang, B. Diederich, Leibniz Institute for Photonic Technology, Albert-Einstein-Str. 9, 07749, Jena, Germany.,H. Wang, B. Diederich, Institute of Physical Chemistry, Friedrich-Schiller-Universität Jena, Helmholtzweg 4, 07743, Jena, Germany
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8
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Bertassoni LE. Bioprinting of Complex Multicellular Organs with Advanced Functionality-Recent Progress and Challenges Ahead. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2101321. [PMID: 35060652 PMCID: PMC10171718 DOI: 10.1002/adma.202101321] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/20/2021] [Indexed: 05/12/2023]
Abstract
Bioprinting has emerged as one of the most promising strategies for fabrication of functional organs in the lab as an alternative to transplant organs. While progress in the field has mostly been restricted to a few miniaturized tissues with minimal biological functionality until a few years ago, recent progress has advanced the concept of building three-dimensional multicellular organ complexity remarkably. This review discusses a series of milestones that have paved the way for bioprinting of tissue constructs that have advanced levels of biological and architectural functionality. Critical materials, engineering and biological challenges that are key to addressing the desirable function of engineered organs are presented. These are discussed in light of the many difficulties to replicate the heterotypic organization of multicellular solid organs, the nanoscale precision of the extracellular microenvironment in hierarchical tissues, as well as the advantages and limitations of existing bioprinting methods to adequately overcome these barriers. In summary, the advances of the field toward realistic manufacturing of functional organs have never been so extensive, and this manuscript serves as a road map for some of the recent progress and the challenges ahead.
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Affiliation(s)
- Luiz E Bertassoni
- Division of Biomaterials and Biomechanics, School of Dentistry, Oregon Health and Science University, Portland, OR, 97201, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health and Science University, Portland, OR, 97239, USA
- Center for Regenerative Medicine, Oregon Health and Science University, Portland, OR, 97239, USA
- Cancer Early Detection Advanced Research (CEDAR), Knight Cancer Institute, Oregon Health and Science University, Portland, OR, 97239, USA
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9
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Duckworth BC, Qin RZ, Groom JR. Spatial determinates of effector and memory CD8 + T cell fates. Immunol Rev 2021; 306:76-92. [PMID: 34882817 DOI: 10.1111/imr.13044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 11/06/2021] [Indexed: 12/17/2022]
Abstract
The lymph node plays a critical role in mounting an adaptive immune response to infection, clearance of foreign pathogens, and cancer immunosurveillance. Within this complex structure, intranodal migration is vital for CD8+ T cell activation and differentiation. Combining tissue clearing and volumetric light sheet fluorescent microscopy of intact lymph nodes has allowed us to explore the spatial regulation of T cell fates. This has determined that short-lived effector (TSLEC ) are imprinted in peripheral lymph node interfollicular regions, due to CXCR3 migration. In contrast, stem-like memory cell (TSCM ) differentiation is determined in the T cell paracortex. Here, we detail the inflammatory and chemokine regulators of spatially restricted T cell differentiation, with a focus on how to promote TSCM . We propose a default pathway for TSCM differentiation due to CCR7-directed segregation of precursors away from the inflammatory effector niche. Although volumetric imaging has revealed the consequences of intranodal migration, we still lack knowledge of how this is orchestrated within a complex chemokine environment. Toward this goal, we highlight the potential of combining microfluidic chambers with pre-determined complexity and subcellular resolution microscopy.
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Affiliation(s)
- Brigette C Duckworth
- Division of Immunology, Walter and Eliza Hall Institute of Medical Research, Parkville, Vic, Australia.,Department of Medical Biology, University of Melbourne, Parkville, Vic, Australia
| | - Raymond Z Qin
- Division of Immunology, Walter and Eliza Hall Institute of Medical Research, Parkville, Vic, Australia.,Department of Medical Biology, University of Melbourne, Parkville, Vic, Australia
| | - Joanna R Groom
- Division of Immunology, Walter and Eliza Hall Institute of Medical Research, Parkville, Vic, Australia.,Department of Medical Biology, University of Melbourne, Parkville, Vic, Australia
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Paul-Gilloteaux P, Tosi S, Hériché JK, Gaignard A, Ménager H, Marée R, Baecker V, Klemm A, Kalaš M, Zhang C, Miura K, Colombelli J. Bioimage analysis workflows: community resources to navigate through a complex ecosystem. F1000Res 2021; 10:320. [PMID: 34136134 PMCID: PMC8182692 DOI: 10.12688/f1000research.52569.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/14/2021] [Indexed: 11/20/2022] Open
Abstract
Workflows are the keystone of bioimage analysis, and the NEUBIAS (Network of European BioImage AnalystS) community is trying to gather the actors of this field and organize the information around them. One of its most recent outputs is the opening of the F1000Research NEUBIAS gateway, whose main objective is to offer a channel of publication for bioimage analysis workflows and associated resources. In this paper we want to express some personal opinions and recommendations related to finding, handling and developing bioimage analysis workflows. The emergence of "big data" in bioimaging and resource-intensive analysis algorithms make local data storage and computing solutions a limiting factor. At the same time, the need for data sharing with collaborators and a general shift towards remote work, have created new challenges and avenues for the execution and sharing of bioimage analysis workflows. These challenges are to reproducibly run workflows in remote environments, in particular when their components come from different software packages, but also to document them and link their parameters and results by following the FAIR principles (Findable, Accessible, Interoperable, Reusable) to foster open and reproducible science. In this opinion paper, we focus on giving some directions to the reader to tackle these challenges and navigate through this complex ecosystem, in order to find and use workflows, and to compare workflows addressing the same problem. We also discuss tools to run workflows in the cloud and on High Performance Computing resources, and suggest ways to make these workflows FAIR.
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Affiliation(s)
- Perrine Paul-Gilloteaux
- Université de Nantes, CNRS, INSERM, l’institut du thorax, Nantes, F-44000, France
- Université de Nantes, CHU Nantes, Inserm, CNRS, SFR Santé, Inserm UMS 016, CNRS UMS 3556, Nantes, F-44000, France
| | - Sébastien Tosi
- Institute for Research in Biomedicine, IRB Barcelona, Barcelona Institute of Science and Technology, BIST, Barcelona, Spain
| | - Jean-Karim Hériché
- Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, 69117, Germany
| | - Alban Gaignard
- Université de Nantes, CNRS, INSERM, l’institut du thorax, Nantes, F-44000, France
| | - Hervé Ménager
- Hub de Bioinformatique et Biostatistique, Département Biologie Computationnelle, Institut Pasteur, USR 3756, CNRS, Paris, 75015, France
- CNRS, UMS 3601, Institut Français de Bioinformatique, IFB-core, Evry, 91000, France
| | - Raphaël Marée
- Montefiore Institute, University of Liège, Liège, Belgium
| | - Volker Baecker
- Montpellier Ressources Imagerie, BioCampus Montpellier, CNRS, INSERM, University of Montpellier, Montpellier, F-34000, France
| | - Anna Klemm
- BioImage Informatics Facility, SciLifeLab, Stockholm, Sweden
| | - Matúš Kalaš
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Chong Zhang
- Department of Information and Communication Technologies, University Pompeu Fabra, Barcelona, Spain
| | - Kota Miura
- Nikon Imaging Center, University of Heidelberg, Heidelberg, Germany
| | - Julien Colombelli
- Institute for Research in Biomedicine, IRB Barcelona, Barcelona Institute of Science and Technology, BIST, Barcelona, Spain
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