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Single-cell transcriptomics of a dynamic cell behavior in murine airways.

Sheldon J J Kwok1,2, Daniel T Montoro3,4, Adam L Haber5

  • 1Harvard Medical School and Wellman Center for Photomedicine, Massachusetts General Hospital, Cambridge, United States.

Elife
|April 21, 2023
PubMed
Summary

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mBio·2025

We developed a new method to link cell behavior in tissues to molecular profiles. This approach identified a unique molecular signature for cell migration after airway injury in mice.

Area of Science:

  • Cellular Biology
  • Molecular Biology
  • Tissue Engineering

Background:

  • High-dimensional cellular analysis has advanced, but profiling dynamic cell behaviors in native environments is challenging.
  • Understanding cell migration and molecular responses in intact tissues is crucial for regenerative medicine and disease research.

Purpose of the Study:

  • To develop and validate a novel method for coupling physiological cell behaviors in intact tissues with deep molecular profiling.
  • To identify molecular signatures associated with specific cellular dynamics, such as migration following injury.

Main Methods:

  • Integration of live-cell imaging techniques with single-cell molecular profiling (e.g., transcriptomics, proteomics).
  • Application of the method to analyze cellular responses within an intact murine airway tissue model following induced injury.
Keywords:
airwaysdevelopmental biologymigrationmouseregenerative medicinestem cellstwo-photon imaging

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  • Development of computational tools to correlate observed cell behaviors with molecular data.
  • Main Results:

    • Successfully coupled real-time cellular physiological behaviors in intact murine airways to deep molecular profiling of individual cells.
    • Identified a novel molecular signature associated with a striking migratory cellular behavior observed after airway injury.
    • Demonstrated the feasibility of analyzing dynamic cellular processes and their molecular underpinnings in a native tissue context.

    Conclusions:

    • The presented method overcomes limitations in studying dynamic cellular processes in vivo.
    • The identified molecular signature provides new insights into the mechanisms of cell migration post-injury.
    • This approach has broad applications for molecular profiling of cellular dynamics in various biological contexts and diseases.