Distinct Mechanisms of T3SS Recognition Control LTB4 Synthesis in Neutrophils versus Macrophages
Brady, A.; Mora Martinez, L. C.; Hammond, B.; Bodduluri, H.; Uriarte, S. M.; Lawrenz, M. B.
Show abstract
Leukotriene B4 (LTB4) is critical for initiating the inflammatory cascade in response to infection. However, Yersinia pestis colonizes the host by inhibiting the timely synthesis of LTB4 and inflammation. Here, we show that the bacterial type 3 secretion system (T3SS) is the primary pathogen associated molecular pattern (PAMP) responsible for LTB4 production by leukocytes in response to Yersinia and Salmonella, but synthesis is inhibited by the Yop effectors during Yersinia interactions. Moreover, we unexpectedly discovered that T3SS-mediated LTB4 synthesis by neutrophils and macrophages require two distinct host signaling pathways. We show that the SKAP2/PLC signaling pathway is essential for LTB4 production by neutrophils but not macrophages. Instead, phagocytosis and the NLRP3/CASP1 inflammasome are needed for LTB4 synthesis by macrophages. Finally, while recognition of the T3SS is required for LTB4 production, we also discovered a second unrelated PAMP-mediated signal independently activates the MAP kinase pathway needed for LTB4 synthesis. Together, these data demonstrate significant differences in the signaling pathways required by macrophages and neutrophils to quickly respond to bacterial infections. SignificanceThe production of inflammatory lipid mediators by the host is essential for timely inflammation in response to invasion by bacterial pathogens. Therefore, defining how immune cells recognize pathogens and rapidly produce these lipids is essential for us to understand how our immune system effectively controls infection. In this study, we discovered that the host signaling pathways required for leukotriene B4 (LTB4) synthesis differ between neutrophils and macrophages, highlighting important differences in how immune cells respond to infection. Together, these data represent a significant improvement in our understanding of how neutrophils and macrophages rapidly react to bacteria and provide new insights into how Yersinia pestis manipulates leukocytes to evade immune recognition to cause disease.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Heightened virulence of Yersinia is associated with decreased function of the YopJ protein 96%
- Iron-sulfur cluster repair contributes to Y. pseudotuberculosis survival within deep tissues 95%
- Precursor abundance influences divergent antigen specific CD8+ T cell responses after Yersinia pseudotuberculosis foodborne infection 95%
Similar papers in this journal
- NLRP11 is required for canonical NLRP3 and non-canonical inflammasome activation during human macrophage infection with mycobacteria 96%
- Phosphoprotein Phosphatase Activity Positively Regulates Oligomeric Pyrin to Trigger Inflammasome Assembly in Phagocytes 95%
- Bacterial strain-dependent dissociation of cell recruitment and cell-to-cell spread in early M. tuberculosis infection 95%
Similar papers in this journal
- The opportunistic intracellular bacterial pathogen Rhodococcus equi elicits type I interferons by engaging cytosolic DNA sensing in macrophages 95%
- Toxoplasma GRA15 and GRA24 are important activators of the host innate immune response in the absence of TLR11 94%
- Genome-scale CRISPR screening reveals that C3aR signaling is critical for rapid capture of fungi by macrophages 94%
Similar papers in this journal
Similar papers in this journal
- RIPK1 activates distinct gasdermins in macrophages and neutrophils upon pathogen blockade of innate immune signalling 95%
- The C terminus of the mycobacterium ESX-1 secretion system substrate ESAT-6 is required for phagosomal membrane damage and virulence 94%
- Tyrosine phosphorylation coupling of one carbon metabolism and virulence in an endogenous pathogen 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.