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Single cell RNA sequencing identifies unique inflammatory airspace macrophage subsets
Kara J. Mould, Nathan D. Jackson, Peter M. Henson, Max Seibold, William J. Janssen
Kara J. Mould, Nathan D. Jackson, Peter M. Henson, Max Seibold, William J. Janssen
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Research Article Immunology Pulmonology

Single cell RNA sequencing identifies unique inflammatory airspace macrophage subsets

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Abstract

Macrophages are well recognized for their dual roles in orchestrating inflammatory responses and regulating tissue repair. In almost all acutely inflamed tissues, 2 main subclasses of macrophages coexist. These include embryonically derived resident tissue macrophages and BM-derived recruited macrophages. While it is clear that macrophage subsets categorized in this fashion display distinct transcriptional and functional profiles, whether all cells within these categories and in the same inflammatory microenvironment share similar functions or whether further specialization exists has not been determined. To investigate inflammatory macrophage heterogeneity on a more granular level, we induced acute lung inflammation in mice and performed single cell RNA sequencing of macrophages isolated from the airspaces during health, peak inflammation, and resolution of inflammation. In doing so, we confirm that cell origin is the major determinant of alveolar macrophage (AM) programing, and, to our knowledge, we describe 2 previously uncharacterized, transcriptionally distinct subdivisions of AMs based on proliferative capacity and inflammatory programing.

Authors

Kara J. Mould, Nathan D. Jackson, Peter M. Henson, Max Seibold, William J. Janssen

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Figure 4

Resident AMs contain a proliferative subpopulation present during health and inflammation.

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Resident AMs contain a proliferative subpopulation present during health...
(A and B) Mean normalized expression of genes annotated for enriched pathways indicated that they were also upregulated in cluster 1 (A) or cluster 2 (B) when compared with RecAM clusters. (C–E) Normalized expression of 3 classic markers of proliferation overlaid onto tSNE plot. (F–H) Characterization of proliferating RAMs in cluster 2 after statistically removing expression heterogeneity related to cell cycle from dataset. (F) t-SNE plot–based scaled residual expression obtained from modeling relationship between gene expression and estimated cell cycle score. Cells colored based on original clusters in Figure 1A. (G) Time course information overlaid on new t-SNE plot. (H) Distribution of cells from original proliferation cluster across new clusters inferred using cell cycle–corrected dataset. New clusters were broadly similar to original clusters and were, thus, named and colored to match cluster analogs in Figure 1A.

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