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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月20日

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

摘要

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.