Characterization of pulmonary immune responses to hyperoxia by high-dimensional mass cytometry analyses

Abstract

Prolonged exposure to hyperoxia has deleterious effects on the lung, provoking both inflammation and alveolar injury. The elements of hyperoxic injury, which result in high rates of lethality in experimental models, are thought to include multicellular immune responses. To characterize these alterations in immune cell populations, we performed time-of-flight mass cytometry (CyTOF) analysis of CD45-expressing immune cells in whole lung parenchyma and the bronchoalveolar space of mice, exposed to 48 hours of hyperoxia together with normoxic controls. At the tested time point, hyperoxia exposure resulted in decreased abundance of immunoregulatory populations (regulatory B cells, myeloid regulatory cells) in lung parenchyma and markedly decreased proliferation rates of myeloid regulatory cells, monocytes and alveolar macrophages. Additionally, hyperoxia caused a shift in the phenotype of alveolar macrophages, increasing proportion of cells with elevated CD68, CD44, CD11c, PD-L1, and CD205 expression levels. These changes occurred in the absence of histologically evident alveolar damage and abundance of neutrophils in the parenchyma or alveolar space did not change at these time points. Collectively, these findings demonstrate that pulmonary response to hyperoxia involves marked changes in specific subsets of myeloid and lymphoid populations. These findings have important implications for therapeutic targeting in acute lung injury.

Figure 1

The viSNE analysis defines distinctive immune cell clusters in the lungs during normoxia and hyperoxia. (A) Whole lung major immune cell clusters^– during normoxia and hyperoxia. Presented tSNE plots were constructed based on data obtained from 7 mice in normoxia and 7 mice in hyperoxia. (B) BALF major immune cell clusters^– during normoxia and hyperoxia. Presented tSNE plots were constructed based on data obtained from 6 mice in normoxia and 8 mice in hyperoxia. FlowSOM was used to color-code the clusters. The immune lineages of the clusters are listed in the corresponding tables.

Figure 2

Proportions of major immune subsets in normoxia and hyperoxia. Frequencies of major subsets in whole lung during normoxia and hyperoxia, compared by unpaired t-test. Each dot represents data from one lung. ****Indicates p < 0.0001. Myeloid regulatory cells are found to be significantly reduced in hyperoxia.

Figure 3

Unbiased identification of immune clusters modified by hyperoxia. (A) CITRUS algorithm identifies 6 major immune cell clusters^– where the abundance is significantly altered between hyperoxia and normoxia. (B) Expression of CD19, Siglec-F, CD3 and NK1.1 relevant for the clusters identified by CITRUS. (C) The boxplots indicate the spread of the abundance of the clusters, and the histograms depict the expression of specific cellular markers (blue depicts background expression in all cells, and red indicates marker expression of cells in a cluster).

Figure 4

Proliferation of immune cell subsets in normoxia and hyperoxia. (A) ki67 staining in tSNE plots from normoxia and hyperoxia. (B) MEI of ki67 from equal sampled fcs files were exported for all 9 major clusters and compared using two-way ANOVA. Proliferation rate of myeloid regulatory cells (cluster 2), monocytes (cluster 3) and alveolar macrophages (cluster 4) is significantly reduced in hyperoxia. ****Indicates p < 0.0001.

Figure 5

Molecular profile of a bulk alveolar macrophage population in normoxic and hyperoxic lung. Comparison of mean expression levels of select markers by alveolar macrophages during normoxia and hyperoxia using two-way ANOVA. **Indicate p < 0.01, ****Indicate p < 0.0001.

Figure 6

Single cell expression of alveolar macrophage markers in normoxic and hyperoxic lung. Parallel tSNE plots depict expression of select macrophage markers in whole lung and BALF during normoxia and hyperoxia. tSNE plots from whole lung and BALF are obtained from independent experiments.