Soluble CD93 is an apoptotic cell opsonin recognized by αx β2.
Jack W D BlackburnDarius H C LauElaine Y LiuJessica EllinsAngela M VriezeEmily N PawlakJimmy D DikeakosBryan HeitPublished in: European journal of immunology (2019)
Efferocytosis is essential for homeostasis and prevention of the inflammatory and autoimmune diseases resulting from apoptotic cell lysis. CD93 is a transmembrane glycoprotein previously implicated in efferocytosis, with mutations in CD93 predisposing patients to efferocytosis-associated diseases. CD93 is a cell surface protein, which is proteolytically shed under inflammatory conditions, but it is unknown how CD93 mediates efferocytosis or whether its efferocytic activity is mediated by the soluble or membrane-bound form. Herein, using cell lines and human monocytes and macrophages, we demonstrate that soluble CD93 (sCD93) potently opsonizes apoptotic cells but not a broad range of microorganisms, whereas membrane-bound CD93 has no phagocytic, efferocytic, or tethering activity. Using mass spectrometry, we identified αx β2 as the receptor that recognizes sCD93, and via deletion mutagenesis determined that sCD93 binds to apoptotic cells via its C-type lectin-like domain and to αx β2 by its EGF-like repeats. The bridging of apoptotic cells to αx β2 markedly enhanced efferocytosis by macrophages and was abrogated by αx β2 knockdown. Combined, these data elucidate the mechanism by which CD93 regulates efferocytosis and identifies a previously unreported opsonin-receptor system utilized by phagocytes for the efferocytic clearance of apoptotic cells.
Keyphrases
- dendritic cells
- cell death
- cell cycle arrest
- induced apoptosis
- mass spectrometry
- nk cells
- oxidative stress
- end stage renal disease
- ejection fraction
- chronic kidney disease
- signaling pathway
- stem cells
- cell proliferation
- prognostic factors
- artificial intelligence
- newly diagnosed
- machine learning
- dna methylation
- liquid chromatography
- growth factor
- ms ms
- bone marrow
- pi k akt
- high performance liquid chromatography
- deep learning