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Single cell RNA sequencing identifies unique inflammatory airspace macrophage subsets
Kara J. Mould, … , Max Seibold, William J. Janssen
Kara J. Mould, … , Max Seibold, William J. Janssen
Published February 5, 2019
Citation Information: JCI Insight. 2019;4(5):e126556. https://doi.org/10.1172/jci.insight.126556.
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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 3

Macrophage polarization states are not mutually exclusive and reflect cell origin.

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Macrophage polarization states are not mutually exclusive and reflect ce...
(A) Cells with high expression of Arg1 and/or Nos2 overlaid on tSNE plot (high versus low expression defined relative to the 85th percentile). (B) Bubble plot shows relative expression of M2 (blue) and M1 (red) markers across clusters. Bubble size is proportional to percentage of cells expressing a gene, and color intensity is proportional to average scaled gene expression within a cluster. (C) Coexpression of Arg1 and Nos2 shown as square root–transformed expression of one gene against the other. Sample color denotes cluster from Figure 1A. (D) Summary expression of genes from B overlaid on tSNE plot. (E and F) Mean normalized expression of M2 (E) and M1 (F) markers relative to homeostatic RAMs. Data are shown across days for RAMs and clusters for RecAMs. Relative-to-baseline expression obtained by subtracting median value observed in clusters 1 and 2 at day 0.

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