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Related Experiment Video

Updated: Jan 9, 2026

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Spatially Resolved Immune Profiling of the Murine Lung Using In Vivo Labeling and Spectral Cytometry.

Rebecca Palmer1,2, Katherine R Pilkington1, Kit Moloney-Geany1

  • 1Malaghan Institute of Medical Research, Wellington, New Zealand.

Current Protocols
|December 5, 2025
PubMed
Summary

This study presents an optimized spectral flow cytometry method for deep immune cell profiling in mouse lungs. The approach enhances spatial context and resolves diverse cell types for better understanding of pulmonary immunity.

Keywords:
cytometry panelfull‐spectrum flow cytometryhigh‐dimensional flow in vivo antibody labelingpulmonary immune cell populationstissue processing

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Area of Science:

  • Immunology
  • Respiratory Medicine
  • Biotechnology

Background:

  • The lung's complexity requires advanced methods for immune cell analysis.
  • Current flow cytometry techniques face challenges in lung tissue dissociation and spatial information preservation.
  • Understanding pulmonary immune responses is crucial for respiratory disease research and therapeutics.

Purpose of the Study:

  • To develop an optimized spectral flow cytometry platform for deep immunophenotyping of murine lung immune cells.
  • To integrate in vivo labeling strategies for distinguishing immune cell locations within the lung.
  • To enable high-resolution interrogation of pulmonary immunity in both health and disease states.

Main Methods:

  • Utilized a 5-laser Cytek Aurora spectral cytometer for high-parameter analysis.
  • Implemented in vivo CD45 antibody labeling (intravenous and oropharyngeal) to differentiate immune cell origins.
  • Developed refined tissue processing protocols and overnight intracellular staining for enhanced cell recovery and marker resolution.
  • Employed complementary 25+ parameter panels for comprehensive myeloid and lymphoid cell profiling.

Main Results:

  • Successfully resolved stromal, endothelial, epithelial, and diverse immune cell subsets (macrophages, T cells, B cells, ILCs, NK cells, etc.).
  • Enabled subclassification of immune cells based on activation, function, and tissue residency.
  • Validated the platform using an influenza A virus model, revealing dynamic immune responses and novel cell populations.
  • Demonstrated the preservation of spatial context in single-cell suspensions.

Conclusions:

  • The developed spectral flow cytometry platform provides a spatially informed, high-resolution approach for pulmonary immune cell analysis.
  • This method overcomes limitations of traditional techniques, offering deeper insights into lung immunity.
  • The optimized workflow and panels are valuable for advancing respiratory disease research and identifying therapeutic targets.