bioRxivImmunology
Apolipoprotein E controls Dectin-1-dependent development of monocyte-derived alveolar macrophages upon pulmonary β-glucan-induced inflammatory adaptation
H. Theobald, D. Bejarano, N. Katzmarski, J. Haub, J. Schulte-Schrepping, J. Yu, K. Bassler, C. Osei-Sarpong, F. Piattini, L. Vornholz, X. Xu, S. Sheoran, A. Al Jawazneh, S. Chakarov, K. Haendler, G. D. Brown, D. Williams, L. Bosurgi, F. Ginhoux, J. Ruland, M. D. Beyer, M. Greter, M. Kopf, J. L. Schultze, A. Schlitzer
Abstract
The lung is constantly exposed to the outside world and optimal adaptation of immune responses is crucial for efficient pathogen clearance. However, mechanisms which lead to the functional and developmental adaptation of lung-associated macrophages remain elusive. To reveal such mechanisms, we developed a reductionist model of environmental intranasal {beta}-glucan exposure, allowing for the detailed interrogation of molecular mechanisms of pulmonal macrophage adaptation. Employing single-cell transcriptomics, high dimensional imaging and flow cytometric characterization paired to in vivo and ex vivo challenge models, we reveal that pulmonary low-grade inflammation results in the development of Dectin-1 - Card9 signaling-dependent monocyte-derived macrophages (MoAM). MoAMs expressed high levels of CD11b, ApoE, Gpnmb and Ccl6, were glycolytic and produced large amounts of interleukin 6 upon restimulation. Myeloid cell specific ApoE ablation inhibited monocyte to MoAM differentiation dependent on M-CSF secretion, promoting MoAM cell death thus impeding MoAM maintenance. In vivo, {beta}-glucan-elicited MoAMs limited the bacterial burden of Legionella pneumophilia post infection and ameliorated fibrosis severity in a murine fibrosis model. Collectively these data identify MoAMs that are generated upon environmental cues and ApoE as an important determinant for lung immune resilience.
- organism: mouse
- assay: bulk RNA-seq
- assay: flow cytometry
- assay: imaging
- research focus: host-pathogen & immune response
- approach: experimental assay
- approach: statistical model
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