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Macrophages are highly versatile cells, which acquire, depending on their microenvironment, pro- (M1-like), or antiinflammatory (M2-like) phenotypes. Here, we studied the role of the G-protein coupled receptor G2A (GPR132), in chemotactic migration and polarization of macrophages, using the zymosan-model of acute inflammation. G2A-deficient mice showed a reduced zymosan-induced thermal hyperalgesia, which was reversed after macrophage depletion. Fittingly, the number of M1-like macrophages was reduced in the inflamed tissue in G2A-deficient mice. However, G2A activation was not sufficient to promote M1-polarization in bone marrow-derived macrophages. While the number of monocyte-derived macrophages in the inflamed paw was not altered, G2A-deficient mice had less macrophages in the direct vicinity of the origin of inflammation, an area marked by the presence of zymosan, neutrophil accumulation and proinflammatory cytokines. Fittingly neutrophil efferocytosis was decreased in G2A-deficient mice and several lipids, which are released by neutrophils and promote G2A-mediated chemotaxis, were increased in the inflamed tissue. Taken together, G2A is necessary to position macrophages in the proinflammatory microenvironment surrounding the center of inflammation. In absence of G2A the macrophages are localized in an antiinflammatory microenvironment and macrophage polarization is shifted toward M2-like macrophages.
Non-alcoholic steatohepatitis (NASH) and alcoholic steatohepatitis (ASH) are the leading causes of liver disease worldwide. To identify disease-specific pathomechanisms, we analyzed the lipidome, metabolome and immune cell recruitment in livers in both diseases. Mice harboring ASH or NASH had comparable disease severities regarding mortality rate, neurological behavior, expression of fibrosis marker and albumin levels. Lipid droplet size was higher in NASH than ASH and qualitative differences in the lipidome were mainly based on incorporation of diet-specific fatty acids into triglycerides, phosphatidylcholines and lysophosphatidylcholines. Metabolomic analysis showed downregulated nucleoside levels in both models. Here, the corresponding uremic metabolites were only upregulated in NASH suggesting stronger cellular senescence, which was supported by lower antioxidant levels in NASH as compared to ASH. While altered urea cycle metabolites suggest increased nitric oxide synthesis in both models, in ASH, this depended on increased L-homoarginine levels indicating a cardiovascular response mechanism. Interestingly, only in NASH were the levels of tryptophan and its anti-inflammatory metabolite kynurenine upregulated. Fittingly, high-content immunohistochemistry showed a decreased macrophage recruitment and an increased polarization towards M2-like macrophages in NASH. In conclusion, with comparable disease severity in both models, higher lipid storage, oxidative stress and tryptophan/kynurenine levels were seen in NASH, leading to distinct immune responses.
Bacterial and fungal toll-like receptor activation elicits type I IFN responses in mast cells
(2021)
Next to their role in IgE-mediated allergic diseases and in promoting inflammation, mast cells also have antiinflammatory functions. They release pro- as well as antiinflammatory mediators, depending on the biological setting. Here we aimed to better understand the role of mast cells during the resolution phase of a local inflammation induced with the Toll-like receptor (TLR)-2 agonist zymosan. Multiple sequential immunohistology combined with a statistical neighborhood analysis showed that mast cells are located in a predominantly antiinflammatory microenvironment during resolution of inflammation and that mast cell-deficiency causes decreased efferocytosis in the resolution phase. Accordingly, FACS analysis showed decreased phagocytosis of zymosan and neutrophils by macrophages in mast cell-deficient mice. mRNA sequencing using zymosan-induced bone marrow-derived mast cells (BMMC) revealed a strong type I interferon (IFN) response, which is known to enhance phagocytosis by macrophages. Both, zymosan and lipopolysaccharides (LPS) induced IFN-β synthesis in BMMCs in similar amounts as in bone marrow derived macrophages. IFN-β was expressed by mast cells in paws from naïve mice and during zymosan-induced inflammation. As described for macrophages the release of type I IFNs from mast cells depended on TLR internalization and endosome acidification. In conclusion, mast cells are able to produce several mediators including IFN-β, which are alone or in combination with each other able to regulate the phagocytotic activity of macrophages during resolution of inflammation.
Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.