Controlling the overwhelming inflammatory reaction associated with polymicrobial sepsis remains a prevalent clinical challenge with few treatment options. In septic peritonitis, blood neutrophils and monocytes are rapidly recruited into the peritoneal cavity to control infection, but the role of resident sentinel cells during the early phase of infection is less clear. In particular, the influence of mast cells on other tissue-resident cells remains poorly understood. Here, we developed a mouse model that allows both visualization and conditional ablation of mast cells and basophils to investigate the role of mast cells in severe septic peritonitis. Specific depletion of mast cells led to increased survival rates in mice with acute sepsis. Furthermore, we determined that mast cells impair the phagocytic action of resident macrophages, thereby allowing local and systemic bacterial proliferation. Mast cells did not influence local recruitment of neutrophils and monocytes or the release of inflammatory cytokines. Phagocytosis inhibition by mast cells involved their ability to release prestored IL-4 within 15 minutes after bacterial encounter, and treatment with an IL-4–neutralizing antibody prevented this inhibitory effect and improved survival of septic mice. Our study uncovers a local crosstalk between mast cells and macrophages during the early phase of sepsis development that aggravates the outcome of severe bacterial infection.
Albert Dahdah, Gregory Gautier, Tarik Attout, Frédéric Fiore, Emeline Lebourdais, Rasha Msallam, Marc Daëron, Renato C. Monteiro, Marc Benhamou, Nicolas Charles, Jean Davoust, Ulrich Blank, Bernard Malissen, Pierre Launay
Usage data is cumulative from January 2019 through January 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.