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| Item Type: | Article |
|---|---|
| Title: | Ultra-high-scale cytometry-based cellular interaction mapping |
| Creators: |
Vonficht, Dominik  ORCID: https://orcid.org/0000-0002-5579-7083, Jopp-Saile, Lea ORCID: https://orcid.org/0000-0002-7032-3003, Yousefian, Schayan ORCID: https://orcid.org/0000-0003-0902-0369, Flore, Viktoria ORCID: https://orcid.org/0009-0001-3023-433X, Simó Vesperinas, Inés, Teuber, Ruth, Avanesyan, Bogdan ORCID: https://orcid.org/0009-0004-2547-6598, Luo, Yanjiang ORCID: https://orcid.org/0009-0003-0401-467X, Röthemeier, Caroline, Grünschläger, Florian ORCID: https://orcid.org/0000-0003-0021-6912, Fernandez-Vaquero, Mirian, Fregona, Vincent ORCID: https://orcid.org/0000-0003-4857-1737, Ordoñez-Rueda, Diana ORCID: https://orcid.org/0000-0002-8387-6707, Schmalbrock, Laura K. ORCID: https://orcid.org/0000-0002-6080-6175, Deininger, Luca ORCID: https://orcid.org/0009-0005-5125-6422, Yamachui Sitcheu, Angelo Jovin ORCID: https://orcid.org/0009-0002-9384-6496, Gu, Zuguang, Funk, Maja C. ORCID: https://orcid.org/0000-0002-6007-1164, Mikut, Ralf ORCID: https://orcid.org/0000-0001-9100-5496, Heikenwälder, Mathias, Eggert, Angelika, von Stackelberg, Arend, Kobold, Sebastian ORCID: https://orcid.org/0000-0002-5612-4673, Krönke, Jan, Keller, Ulrich ORCID: https://orcid.org/0000-0002-8485-1958, Trumpp, Andreas, Hegazy, Ahmed N., Eckert, Cornelia ORCID: https://orcid.org/0000-0003-1039-2872, Hübschmann, Daniel ORCID: https://orcid.org/0000-0002-6041-7049 and Haas, Simon ORCID: https://orcid.org/0000-0001-9227-2051
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| Abstract: | Cellular interactions are of fundamental importance, orchestrating organismal development, tissue homeostasis and immunity. Recently, powerful methods that use single-cell genomic technologies to dissect physically interacting cells have been developed. However, these approaches are characterized by low cellular throughput, long processing times and high costs and are typically restricted to predefined cell types. Here we introduce Interact-omics, a cytometry-based framework to accurately map cellular landscapes and cellular interactions across all immune cell types at ultra-high resolution and scale. We demonstrate the utility of our approach to study kinetics, mode of action and personalized response prediction of immunotherapies, and organism-wide shifts in cellular composition and cellular interaction dynamics following infection in vivo. Our scalable framework can be applied a posteriori to existing cytometry datasets or incorporated into newly designed cytometry-based studies to map cellular interactions with a broad range of applications from fundamental biology to applied biomedicine. |
| Keywords: | Cell Communication, Flow Cytometry, Single-Cell Analysis, Animals, Mice |
| Source: | Nature Methods |
| ISSN: | 1548-7091 |
| Publisher: | Nature Publishing Group |
| Volume: | 22 |
| Number: | 9 |
| Page Range: | 1887-1899 |
| Date: | September 2025 |
| Official Publication: | https://doi.org/10.1038/s41592-025-02744-w |
| PubMed: | View item in PubMed |
| Related to: |
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