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Complementing cell taxonomies with a multicellular analysis of tissues

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spat...

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Bibliographic Details
Main Authors: Ramirez Flores, Ricardo O. (Author) , Schäfer, Philipp (Author) , Küchenhoff, Leonie (Author) , Sáez Rodríguez, Julio (Author)
Format: Article (Journal)
Language:English
Published: Februray 6, 2024
In: Physiology
Year: 2024, Volume: 39, Issue: 3, Pages: 129-141
ISSN:1548-9221
DOI:10.1152/physiol.00001.2024
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1152/physiol.00001.2024
Verlag, lizenzpflichtig, Volltext: https://journals.physiology.org/doi/full/10.1152/physiol.00001.2024
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Author Notes:Ricardo Omar Ramirez Flores, Philipp Sven Lars Schäfer, Leonie Küchenhoff, and Julio Saez-Rodriguez
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Summary:The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.
Item Description:Gesehen am 23.07.2025
Physical Description:Online Resource
ISSN:1548-9221
DOI:10.1152/physiol.00001.2024

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