Successful vaccination against intracellular pathogens requires the generation of cellular immune responses. Trehalose-6,6-dibehenate (TDB), the synthetic analog of the mycobacterial cord factor trehalose-6,6-dimycolate (TDM), is a potent adjuvant inducing strong Th1 and Th17 immune responses. We previously identified the C-type lectin Mincle as receptor for these glycolipids that triggers the FcRγ-Syk-Card9 pathway for APC activation and adjuvanticity. Interestingly, in vivo data revealed that the adjuvant effect was not solely Mincle-dependent but also required MyD88. Therefore, we dissected which MyD88-dependent pathways are essential for successful immunization with a tuberculosis subunit vaccine. We show here that antigen-specific Th1/Th17 immune responses required IL-1 receptor-mediated signals independent of IL-18 and IL-33-signaling. ASC-deficient mice had impaired IL-17 but intact IFNγ responses, indicating partial independence of TDB adjuvanticity from inflammasome activation. Our data suggest that the glycolipid adjuvant TDB triggers Mincle-dependent IL-1 production to induce MyD88-dependent Th1/Th17 responses in vivo.
Sensing of infectious danger by toll-like receptors (TLRs) on macrophages causes not only a reprogramming of the transcriptome but also changes in the cytoskeleton important for cell spreading and motility. Since manual determination of cell contact areas from fluorescence micrographs is very time-consuming and prone to bias, we have developed and tested algorithms for automated measurement of macrophage spreading. The two-step method combines identification of cells by nuclear staining with DAPI and cell surface staining of the integrin CD11b. Automated image analysis correlated very well with manual annotation in resting macrophages and early after stimulation, whereas at later time points the automated cell segmentation algorithm and manual annotation showed slightly larger variation. The method was applied to investigate the impact of genetic or pharmacological inhibition of known TLR signaling components. Deficiency in the adapter protein Myd88 strongly reduced spreading activity at the late time points, but had no impact early after LPS-stimulation. A similar effect was observed upon pharmacological inhibition of MEK1, the kinase activating the mitogen-activated protein kinases (MAPK) ERK1/2, indicating that ERK1/2 mediates Myd88-dependent macrophages spreading. In contrast, macrophages lacking the MAPK p38 were impaired in the initial spreading response but responded normally 8–24 h after stimulation. The dichotomy of p38 and ERK1/2 MAPK effects on early and late macrophage spreading raises the question which of the respective substrate proteins mediate(s) cytoskeletal remodeling and spreading. The automated measurement of cell spreading described here increases the objectivity and greatly reduces the time required for such investigations and is therefore expected to facilitate larger throughput analysis of macrophage spreading, e.g., in siRNA knockdown screens.
TLR-mediated recognition of microbial danger induces substantial changes in macrophage migration, adherence, and phagocytosis. Recently, we described the LPSregulated phosphorylation of many cytoskeleton-associated proteins by phosphoproteomics. The functional role of these cytoskeletal and motor proteins in innate immune cell responses is largely unexplored. Here, we first identified both long-tailed class I myosins Myo1e and Myo1f as important contributors to LPS-triggered macrophage spreading. Mouse bone marrow-derived macrophages and DCs deficient in Myo1e selectively secreted increased amounts of the chemokine CCL2. In addition, the cell surface expression of MHC class II (MHC-II) on both cell types was reduced in the absence of Myo1e. However, transcriptional changes in CCL2 and MHC-II were not observed in the absence of Myo1e, indicating that Myo1e regulates specific intracellular transport processes. The capacity of macrophages and DCs lacking Myo1e to stimulate antigen-specific CD4 + T-cell proliferation was impaired, consistent with the reduced MHC-II surface protein levels. Surprisingly, in Myo1e-deficient DCs, the proteolytic cleavage of endocytosed antigen was also increased. Together, our results provide evidence for a nonredundant function of the motor protein Myo1e in the regulation of TLR4-controlled, cytoskeleton-associated functional properties of macrophages and DCs, and in induction of a full MHC-II-restricted adaptive immune response.Keywords: Cytoskeleton r Macrophages r MHC class II r Myosin r Toll-like receptors Additional supporting information may be found in the online version of this article at the publisher's web-site IntroductionThe capacity to migrate in response to chemoattractants and to phagocytose dead cells and invading bacteria are two key functions of macrophages. Migration and phagocytosis require the remodeling of the cytoskeleton to generate the mechanical 226Jens Wenzel et al. Eur. J. Immunol. 2015. 45: 225-237 these proteins form an actin regulatory network, which can be rapidly modulated in response to extracellular stimuli [2,3]. An important aspect of cell shape regulation is the mechanical linkage between the plasma membrane and the underlying actin filaments, which may be mediated by the class I myosins, members of the myosin superfamily of molecular motors. Class I myosins are single-headed molecular motors, composed of a single heavy chain containing the motor domain with an actin-binding site followed by a light chain-binding neck region and a C-terminal tail domain that includes membrane-binding and protein interaction domains. This specific structure allows a simultaneous interaction with actin filaments and membranes or other proteins necessary for active membrane deformation or intracellular vesicle trafficking. The mechanical forces required for these mechanisms are produced through hydrolysis of ATP [4]. In B lymphocytes, Myo1c and Myo1g are both highly expressed [5], localize to plasma membrane compartments, regulate actin reorganization and contrib...
In order to improve reproducibility and objectivity of fluorescence microscopy based experiments and to enable the evaluation of large datasets, flexible segmentation methods are required which are able to adapt to different stainings and cell types. This adaption is usually achieved by the manual adjustment of the segmentation methods parameters, which is time consuming and challenging for biologists with no knowledge on image processing. To avoid this, parameters of the presented methods automatically adapt to user generated ground truth to determine the best method and the optimal parameter setup. These settings can then be used for segmentation of the remaining images. As robust segmentation methods form the core of such a system, the currently used watershed transform based segmentation routine is replaced by a fast marching level set based segmentation routine which incorporates knowledge on the cell nuclei. Our evaluations reveal that incorporation of multimodal information improves segmentation quality for the presented fluorescent datasets.
To evaluate macrophage spreading in immunofluorescence images of macrophages for surface protein CD11b and nuclear counterstaining with DAPI, it is necessary to measure the size of the macrophages at different time points after stimulation. Manual evaluation of fluorescent micrographs is usually a time-consuming and error-prone task, with poor reproducibility. Automatic image analysis methods can be used to improve the results. The quality of the analysis with these methods mainly depends on the quality of the image segmentation. A segmentation and quantification scheme based on shading correction, k-means clustering, and fast marching level sets has been developed for the purpose. An initial application of this approach showed that separating touching and overlapping cells in particular suffers severely in the inevitably blurred conditions, leading to partly erroneous measurements of macrophage spreading. An alternative method of segmentation in fluorescent micrographs was therefore investigated and evaluated in this study. The proposed approach uses a methodology that separates foreground objects from background objects on the basis of Boykov's graph cuts. In this process, a rough estimation of background pixels is used for background seeds. To identify foreground seeds, a difference of Gaussian band pass filter based workflow is developed. Information on foreground and background seeds is then used for a gradient magnitude based graph cut resulting in a robust figure-ground separation method. In addition, a fast marching level set approach is used in the post-processing step, which makes it possible to split touching cells by incorporating information about the cell nuclei. An evaluation based on a total of 553 manually labeled macrophages depicted in 21 micrographs showed that the proposed method significantly improves segmentation and splitting performance for fluorescent micrographs of LPS-stimulated macrophages and reduces the rate of error in automated analysis of macrophage spreading in comparison with alternative methods. ' 2013 International Society for Advancement of Cytometry Key terms image analysis; cell segmentation; optimization; graph cut; fast marching level set; fluorescence imaging; macrophage spreading OBJECTIVETo evaluate macrophage spreading in immunofluorescence images of macrophages for surface protein CD11b and nuclear counterstaining with 4,6-diamino-2-phenylindole (DAPI), it is necessary to measure the size of the macrophages at different time points after stimulation. Unless semi-automatic image analysis tools are used, each macrophage has to be manually delineated to allow measurement and quantification of its size. Automated image analysis methods are needed in order to speed up this very time-consuming and error-prone step of analysis. Figure 1 shows a typical sequence for macrophage spreading at several time points (t 5 0 (control), t 5 15 min, t 5 1 h, t 5 2 h, and t 5 24 h) and the corresponding ground truth, illustrating the challenge represented by increasingly touch...
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