Systematic analysis of immune cell motility leveraging the open intravital microscopy database Immunemap

Understanding the spatiotemporal dynamics of immune cells in living organisms is a major goal in bioimaging. Intravital microscopy enables direct observation of cellular behavior over time with tissue-to-subcellular resolution, making it essential for investigating immune responses across tissues, conditions, and disease contexts. However, most intravital microscopy data remain siloed in individual labs, limiting reuse, standardization, and large-scale analysis. To address these limitations, we present Immunemap, an open-data platform and interactive atlas of immune cell motility. Immunemap currently provides access to over 58,000 curated single-cell tracks and more than 1,049,000 cell-centroid annotations from 400 intravital microscopy videos in murine models, spanning diverse tissues and conditions. The platform supports both exploratory and quantitative research. We show here how unsupervised learning identifies distinct motility patterns, and how large-scale mapping enables comparisons across stimuli, imaging setups, and organs. Its cloud-based architecture offers an interactive web interface and public APIs for integration with computational pipelines. By adhering to FAIR principles (Findability, Accessibility, Interoperability, and Reuse) and fostering cross-disciplinary studies, Immunemap supports reproducible research and provides a benchmark for bioimage analysis and tool development in intravital imaging.

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Publication Details

Journal
The EMBO Journal
Published
2025-11-20
DOI
https://doi.org/10.1038/s44318-025-00629-4
Citations
2
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
3.27

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article

Systematic analysis of immune cell motility leveraging the open intravital microscopy database Immunemap

Morgan Campbell Hunter, Pau Carrillo-Barberà, Elisa Palladino, Xenia Ficht et al.
2 citations
The EMBO Journal
Cell Image Analysis Techniques
3.27
article

Systematic analysis of immune cell motility leveraging the open intravital microscopy database Immunemap

Morgan Campbell Hunter, Pau Carrillo-Barberà, Elisa Palladino, Xenia Ficht, Raffaella Fiamma Cabini, Mauro Di Pilato, Alain Pulfer, Tommaso Virgilio, José M. Adrover, Miguel Palomino‐Segura, Milka Sarris, Ulla Norman, Yagmur Farsakoglu, Benedikt Thelen, Jun Abe, Hélène D. Moreau, Wolfgang Kastenmüller, Joy Bordini, Philippe Bousso, Cornelia Halin, Michael J. Hickey, Kevin Ceni, Antonios Georgantzoglou, Georgiana Crainiciuc, Shivashankar Othy, Chris Xu, Thorsten R. Mempel, Daniel Molina Romero, Hans‐Uwe Simon, Jens V. Stein, Santiago González, Rolf Krause, Inge M. N. Wortel, Diego Ulisse Pizzagalli, Nina Germič, Michael D. Cahalan, Sarah Eickhoff, Thomas T. Murooka, Federica Moalli, Kibaek Choe, Johannes C. Textor, Alexandre P. Bénéchet, Javier Pareja, Florentino Luciano Caetano dos Santos, Mykhailo Vladymyrov, Britta Engelhardt, Petra Pfenninger, Neda Haghayegh Jahromi, Irene Latino, Matteo Iannacone, Andrés Hidalgo, Francesco Marangoni, Jordi Sintes, Dorian Obino, Kamil Chahine, Chiara Pizzichetti, Himanshu Bansal, Ana‐Maria Lennon‐Duménil, Enrico Moscatello, Arianna Cappucetti
article en
2 citations

Abstract

Understanding the spatiotemporal dynamics of immune cells in living organisms is a major goal in bioimaging. Intravital microscopy enables direct observation of cellular behavior over time with tissue-to-subcellular resolution, making it essential for investigating immune responses across tissues, conditions, and disease contexts. However, most intravital microscopy data remain siloed in individual labs, limiting reuse, standardization, and large-scale analysis. To address these limitations, we present Immunemap, an open-data platform and interactive atlas of immune cell motility. Immunemap currently provides access to over 58,000 curated single-cell tracks and more than 1,049,000 cell-centroid annotations from 400 intravital microscopy videos in murine models, spanning diverse tissues and conditions. The platform supports both exploratory and quantitative research. We show here how unsupervised learning identifies distinct motility patterns, and how large-scale mapping enables comparisons across stimuli, imaging setups, and organs. Its cloud-based architecture offers an interactive web interface and public APIs for integration with computational pipelines. By adhering to FAIR principles (Findability, Accessibility, Interoperability, and Reuse) and fostering cross-disciplinary studies, Immunemap supports reproducible research and provides a benchmark for bioimage analysis and tool development in intravital imaging.

The EMBO JournalVol. 45(1)
University of Bern (CH), Manitoba Health (CA), Bern University of Applied Sciences (CH), The University of Texas MD Anderson Cancer Center (US), Radboud University Nijmegen (NL), University of Fribourg (CH), Vita-Salute San Raffaele University (IT), Institut Pasteur (FR), Universitat de València (ES), University of Basel (CH), University of California, Irvine (US), Cornell University (US), University of Cambridge (GB), University of Würzburg (DE), Université Paris Sciences et Lettres (FR), University Hospital Bonn (DE), The Francis Crick Institute (GB), University Hospital of Bern (CH), Novo Nordisk Foundation (DK), Instituto de Salud Carlos III (ES), Government of Extremadura (ES), Radboud University Medical Center (NL), ETH Zurich (CH), Massachusetts General Hospital (US), Swiss Institute for Regenerative Medicine (CH), Vir Biotechnology (Switzerland) (CH), Institute of Oncology Research (CH), The Geneva Association (CH), Institute for Biomedicine (IT), Centro Tecnológico Nacional Agroalimentario Extremadura (ES), Instituto de Biomedicina de Valencia (ES), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Ospedale San Luigi Gonzaga (IT), Hospital del Mar Research Institute (ES), Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele (IT), University of Manitoba (CA), Università della Svizzera italiana (CH), Victoria University (AU), Institut Curie (FR), Universidad de Extremadura (ES), University of Lausanne (CH)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Helmut Horten Stiftung
Openalex Percentile: Top 7%
Cell Image Analysis Techniques
3.27
DOIOpen Access PDFOpenAlex
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