Fig. S1. Schematic to accompany the paper (optional graphical abstract).
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•A method was validated for polymer mass concentrations in human whole blood.•Polymers from plastics were ...detected and quantified in human blood.•Polymers in human blood represent several high production volume plastics.•Blood donors were from general public.•Quality control of background plastic throughout sampling and analysis is key.
Plastic particles are ubiquitous pollutants in the living environment and food chain but no study to date has reported on the internal exposure of plastic particles in human blood. This study’s goal was to develop a robust and sensitive sampling and analytical method with double shot pyrolysis - gas chromatography/mass spectrometry and apply it to measure plastic particles ≥700 nm in human whole blood from 22 healthy volunteers. Four high production volume polymers applied in plastic were identified and quantified for the first time in blood. Polyethylene terephthalate, polyethylene and polymers of styrene (a sum parameter of polystyrene, expanded polystyrene, acetonitrile butadiene styrene etc.) were the most widely encountered, followed by poly(methyl methacrylate). Polypropylene was analysed but values were under the limits of quantification. In this study of a small set of donors, the mean of the sum quantifiable concentration of plastic particles in blood was 1.6 µg/ml, showing a first measurement of the mass concentration of the polymeric component of plastic in human blood. This pioneering human biomonitoring study demonstrated that plastic particles are bioavailable for uptake into the human bloodstream. An understanding of the exposure of these substances in humans and the associated hazard of such exposure is needed to determine whether or not plastic particle exposure is a public health risk.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The clinical benefit conferred by vascular endothelial growth factors (VEGF)-targeted therapies is variable, and tumors from treated patients eventually reinitiate growth. Here, we identify a ...glycosylation-dependent pathway that compensates for the absence of cognate ligand and preserves angiogenesis in response to VEGF blockade. Remodeling of the endothelial cell (EC) surface glycome selectively regulated binding of galectin-1 (Gal1), which upon recognition of complex N-glycans on VEGFR2, activated VEGF-like signaling. Vessels within anti-VEGF-sensitive tumors exhibited high levels of α2-6-linked sialic acid, which prevented Gal1 binding. In contrast, anti-VEGF refractory tumors secreted increased Gal1 and their associated vasculature displayed glycosylation patterns that facilitated Gal1-EC interactions. Interruption of β1-6GlcNAc branching in ECs or silencing of tumor-derived Gal1 converted refractory into anti-VEGF-sensitive tumors, whereas elimination of α2-6-linked sialic acid conferred resistance to anti-VEGF. Disruption of the Gal1-N-glycan axis promoted vascular remodeling, immune cell influx and tumor growth inhibition. Thus, targeting glycosylation-dependent lectin-receptor interactions may increase the efficacy of anti-VEGF treatment.
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•Hypoxia promotes glycan remodeling and binding of the lectin Gal1 to vascular cells•Glycosylation-dependent lectin-receptor interactions mimic VEGF-A function•Glycosylation of tumor-associated vessels delineates sensitivity to anti-VEGF•Targeting the Gal1-N-glycan axis overcomes anti-VEGF compensatory programs
Interactions between a lectin and carbohydrates on the VEGFR2 receptor enable ligand-independent signaling, establishing a mechanism underlying continued vessel growth in tumors treated with anti-VEGF antibodies.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Highlights • DC-SIGN is a multifunctional C-type lectin receptor on antigen-presenting cells. • Its functions include adhesion, migration, signaling, and antigen uptake/presentation. • All evidence ...supporting DC-SIGN functions is based on in vitro assays. • The absence of a functional DC-SIGN ortholog hampers the study of its physiological role.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The C‐type lectin MGL activates the ERK‐p90RSK‐CREB axis, which together with TLR2 signaling leads to enhanced secretion of IL‐10 and TNFα.
DCs orchestrate immune responses to infectious pathogens ...and disturbances in tissue integrity. Equipped with C‐type lectins, DCs can respond to environmental changes in glycosylation. Many C‐type lectins are capable of modulating TLR activation, thereby facilitating tailor‐made immune reactions. Here, we investigated the signaling properties of the C‐type lectin MGL and show that MGL engagement by agonistic antibodies or carbohydrate ligands couples to TLR signal transduction for increased IL‐10 and TNF‐α secretion by human monocyte‐derived DCs. MGL triggering especially synergized with TLR2‐induced pathways, leading to elevated IL‐10 mRNA levels and enhanced TNF‐α mRNA stability. In addition, MGL signaling promoted phosphorylation of the MAPK ERK and the transcription factor CREB. Whereas specific inhibitors of p90RSK blocked the MGL‐induced cytokine secretion, AP‐1 was not involved. Strikingly, NF‐κB was only crucial for the IL‐10 response and dispensable for TNF‐α production. Together, our results demonstrate that MGL activation of the ERK‐p90RSK‐CREB axis converges with TLR2‐induced pathways, thereby fine‐tuning the DC maturation phenotype.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Glioblastoma is the most prevalent and aggressive primary brain tumour for which total tumour lysate-pulsed dendritic cell vaccination is currently under clinical evaluation. Glioblastoma ...extracellular vesicles (EVs) may represent an enriched cell-free source of tumour-associated (neo-) antigens to pulse dendritic cells (DCs) for the initiation of an anti-tumour immune response. Capture and uptake of EVs by DCs could occur in a receptor-mediated and presumably glycan-dependent way, yet the glycan composition of glioblastoma EVs is unknown. Here, we set out to characterize the glycocalyx composition of glioblastoma EVs by lectin-binding ELISA and comprehensive immunogold transmission electron microscopy (immuno-TEM). The surface glycan profile of human glioblastoma cell line-derived EVs (50-200 nm) was dominated by α-2,3- and α-2,6 linked sialic acid-capped complex N-glycans and bi-antennary N-glycans. Since sialic acids can trigger immune inhibitory sialic acid-binding Ig-like lectin (Siglec) receptors, we screened for Siglec ligands on the EVs. Glioblastoma EVs showed significant binding to Siglec-9, which is highly expressed on DCs. Surprisingly, however, glioblastoma EVs lack glycans that could bind Dendritic Cell-Specific Intercellular adhesion molecule-3-Grabbing Non-integrin (DC-SIGN, CD209), a receptor that mediates uptake and induction of CD4
+
and CD8
+
T cell activation. Therefore, we explored whether modification of the EV glycan surface could reduce immune inhibitory Siglec binding, while enhancing EV internalization by DCs in a DC-SIGN dependent manner. Desialylation with a pan-sialic acid hydrolase led to reduction of sialic acid expression on EVs. Moreover, insertion of a high-affinity ligand (Lewis
Y
) for DC-SIGN resulted in a four-fold increase of uptake by monocyte-derived DCs. In conclusion, we show that the glycocalyx composition of EVs is a key factor of efficient DC targeting and that modification of the EV glycocalyx potentiates EVs as anti-cancer vaccine.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
A flat-fee user charge by core facilities would greatly benefit both scientists and core facility staff and help them to focus on scientific questions rather than financial considerations.
In recent years, many paradigms concerning central nervous system (CNS) immunology have been challenged and shifted, including the discovery of CNS-draining lymphatic vessels, the origin and ...functional diversity of microglia, the impact of T cells on CNS immunological homeostasis and the role of neuroinflammation in neurodegenerative diseases. In parallel, antigen presentation outside the CNS has revealed the vital role of antigen-presenting cells in maintaining tolerance toward self-proteins, thwarting auto-immunity. Here, we review recent findings that unite these shifted paradigms of microglial functioning, antigen presentation, and CNS-directed T cell activation, focusing on common neurodegenerative diseases. It provides an important update on CNS adaptive immunity, novel targets, and a concept of the microglia T-cell equilibrium.
C-type lectin receptors (CLRs) have long been known as pattern-recognition receptors implicated in the recognition of pathogens by the innate immune system. However, evidence is accumulating that ...many CLRs are also able to recognize endogenous 'self' ligands and that this recognition event often plays an important role in immune homeostasis. In the present review, we focus on the human and mouse CLRs for which endogenous ligands have been described. Special attention is given to the signaling events initiated upon recognition of the self ligand and the regulation of glycosylation as a switch modulating CLR recognition, and therefore, immune homeostasis.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
► Leb and LeX glycans achieve an efficient antigen-targeting to DCs through DC-SIGN. ► Glycan multivalency is a necessary condition for efficient targeting. ► DC-SIGN targeting results in robust CD4+ ...and CD8+ T cell responses.
Dendritic cells are the most efficient professional antigen-presenting cells in pathogen recognition and play a pivotal role in the control of the immune response. Pathogen recognition is ensured by the expression of a vast variety of pattern-recognition receptors. Amongst them are C-type lectins, a large family of receptors characterized by a domain that – in many cases – mediates calcium-dependent glycan binding. C-type lectins facilitate antigen uptake for efficient processing and presentation and, in some cases, also trigger signaling to modulate T cell responses. These properties make C-type lectin receptors ideal candidates for the targeting of antigens to dendritic cells for vaccination. DC-SIGN is a paradigmatic example of C-type lectin receptors on dendritic cells that facilitate vaccination strategies. DC-SIGN is highly expressed on immature conventional dendritic cells, particularly at the mucosa and the dermis, where DCs first encounter pathogens, but also can easily be accessed for vaccination. Upon ligand binding, DC-SIGN rapidly internalizes and directs its cargo into the endo-lysosomal pathway, which results in MHC-II presentation. But antigens targeted to DC-SIGN are also presented efficiently to CD8+ T cells, suggesting there is an additional endocytic route that leads to cross-presentation. Simultaneous triggering of DC-SIGN and TLRs results in the modulation of cytokine responses and facilitates cross-presentation to enhance CD4+ and CD8+ T cell responses. Because the glycan specificity of DC-SIGN has been characterized in detail, glycans can be used for the targeting of antigens to DCs in a DC-SIGN-dependent manner. Glycans represent a great advantage over monoclonal antibodies, they diminish the risk of side effects, are very small, and their production can rely entirely in organic chemistry approaches. Here, we discuss the capacity of glycan-based vaccines to enhance antigen-specific CD4+ and CD8+ T cell responses in human skin and mouse model systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Current methods of high-dimensional unsupervised clustering of mass cytometry data lack means to monitor and evaluate clustering results. Whether unsupervised clustering is correct is typically ...evaluated by agreement with dimensionality reduction techniques or based on benchmarking with manually classified cells. The ambiguity and lack of reproducibility of sequential gating has been replaced with ambiguity in interpretation of clustering results. On the other hand, spurious overclustering of data leads to loss of statistical power. We have developed INFLECT, an R-package designed to give insight in clustering results and provide an optimal number of clusters. In our approach, a mass cytometry dataset is overclustered intentionally to ensure the smallest phenotypically different subsets are captured using FlowSOM. A range of metacluster number endpoints are generated and evaluated using marker interquartile range and distribution unimodality checks. The fraction of marker distributions that pass these checks is taken as a measure of clustering success. The fraction of unimodal distributions within metaclusters is plotted against the number of generated metaclusters and reaches a plateau of diminishing returns. The inflection point at which this occurs gives an optimal point of capturing cellular heterogeneity versus statistical power. We applied INFLECT to four publically available mass cytometry datasets of different size and number of markers. The unimodality score consistently reached a plateau, with an inflection point dependent on dataset size and number of dimensions. We tested both ConsenusClusterPlus metaclustering and hierarchical clustering. While hierarchical clustering is less computationally expensive and thus faster, it achieved similar results to ConsensusClusterPlus. The four datasets consisted of labeled data and we compared INFLECT metaclustering to published results. INFLECT identified a higher optimal number of metaclusters for all datasets. We illustrated the underlying heterogeneity within labels, showing that these labels encompass distinct types of cells. INFLECT addresses a knowledge gap in high-dimensional cytometry analysis, namely assessing clustering results. This is done through monitoring marker distributions for interquartile range and unimodality across a range of metacluster numbers. The inflection point is the optimal trade-off between cellular heterogeneity and statistical power, applied in this work for FlowSOM clustering on mass cytometry datasets.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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