Langerin-Heparin Interaction: Two Binding Sites for Small and Large Ligands as revealed by a combination of NMR Spectroscopy and Cross-Linking Mapping Experiments

Langerin is a C-type lectin present on Langerhans cells that mediates capture of pathogens in a carbohydrate-dependent manner, leading to subsequent internalization and elimination in the cellular organelles called Birbeck granules. This mechanism mediated by langerin was shown to constitute a natural barrier for HIV-1 particle transmission. Besides interacting specifically with high mannose and fucosylated neutral carbohydrate structures, langerin has the ability to bind sulfated carbohydrate ligands as 6-sulfated galactosides in the Ca2+ dependent binding site. Very recently langerin was demonstrated to interact with sulfated glycosaminoglycans (GAGs), in a Ca2+ independent way, resulting in the proposal of a new binding site for GAGs. Based on those results, we have conducted a structural study of the interactions of small heparin (HEP) like oligosaccharides with langerin in solution. Heparin-bead cross-linking experiments, an approach specifically designed to identify HEP/HS binding sites in proteins were first carried out and experimentally validated the previously proposed model for the interaction of Lg ECD with 6 kDa HEP. High-resolution NMR studies of a set of 8 synthetic HEP-like trisaccharides harboring different sulfation patterns demonstrated that all of them bound to langerin in a Ca2+ dependent way. The binding epitopes were determined by STD NMR and the bound conformations by transferred NOESY experiments. These experimental data were combined with docking and molecular dynamics and resulted in the proposal of a binding mode characterized by the coordination of calcium by the two equatorial hydroxyl groups OH3 and OH4 at the non-reducing end. The binding also includes the carboxylate group at the adjacent iduronate residue. Such epitope is shared by all the 8 ligands, explaining the absence of any impact on binding from their differences in substitution pattern. Finally, in contrast to the small trisaccharides, we demonstrated that a longer HEP-like hexasaccharide, bearing an additional O-sulfate group at the non-reducing end, which precludes binding to the Ca2+ site, interacts with langerin in the previously identified Ca2+ independent binding site

Proteinuria converts hepatic heparan sulfate to an effective proprotein convertase subtilisin kexin type 9 enzyme binding partner:a historical appraisal of its origins and conceptual evolution

International audienc

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

Testing the Effect of Relative Pollen Productivity on the REVEALS Model : A Validated Reconstruction of Europe-Wide Holocene Vegetation

Reliable quantitative vegetation reconstructions for Europe during the Holocene are crucial to improving our understanding of landscape dynamics, making it possible to assess the past effects of environmental variables and land-use change on ecosystems and biodiversity, and mitigating their effects in the future. We present here the most spatially extensive and temporally continuous pollen-based reconstructions of plant cover in Europe (at a spatial resolution of 1° × 1°) over the Holocene (last 11.7 ka BP) using the 'Regional Estimates of VEgetation Abundance from Large Sites' (REVEALS) model. This study has three main aims. First, to present the most accurate and reliable generation of REVEALS reconstructions across Europe so far. This has been achieved by including a larger number of pollen records compared to former analyses, in particular from the Mediterranean area. Second, to discuss methodological issues in the quantification of past land cover by using alternative datasets of relative pollen productivities (RPPs), one of the key input parameters of REVEALS, to test model sensitivity. Finally, to validate our reconstructions with the global forest change dataset. The results suggest that the RPPs.st1 (31 taxa) dataset is best suited to producing regional vegetation cover estimates for Europe. These reconstructions offer a long-term perspective providing unique possibilities to explore spatial-temporal changes in past land cover and biodiversity

BMP2 binds non-specifically to PEG-passivated biomaterials and induces substantial signaling

Biomaterials are widely employed across diverse biomedical applications and represent an attractive strategy to explore physiologically how extracellular matrix components influence the cellular response. In this study, we aimed to use previously developed biomimetic streptavidin platforms to investigate the role of glycosaminoglycans (GAGs) in bone morphogenetic protein 2 (BMP2) signaling. However, we observed that the interpretation of our findings was skewed due to the GAG-unrelated, non-specific adsorption of BMP2 on components of our biomaterials. Non-specific adsorption of proteins is a recurrent and challenging issue for biomaterial studies. Despite the initial incorporation of anti-fouling poly(ethylene glycol) (PEG) chains within our biomaterials, the residual non-specific BMP2 adsorption still triggered BMP2 signaling within the same range as our conditions of interest. To tackle this issue, we explored various options to prevent BMP2 non-specific adsorption. Specifically, we tested alternative constructions of our biomaterials on gold or glass substrate using distinct PEG-based linkers. We identified the aggregation of BMP2 at neutral pH as a potential cause of non-specific adsorption and thus determined specific buffer conditions to prevent it. We also investigated the induced BMP2 signaling over different culture periods. Nevertheless, none of these options resulted in a viable suitable solution to reduce the non-specific BMP2 signaling. Next, we studied the effect of various blocking strategies. We identified a blocking condition involving a combination of bovine serum albumin and trehalose that successfully reduced the unspecific attachment of BMP2 and the non-specific signaling. Furthermore, the effect of this blocking step was improved when using gold platforms instead of glass, particularly with Chinese hamster ovary (CHO) cells that seemed less responsive to non-specifically bound BMP2 than C2C12 cells

Heparan sulfate regulates ADAM12 through a molecular switch mechanism.

International audienceThe disintegrin and metalloproteases (ADAMs) are emerging as therapeutic targets in human disease, but specific drug design is hampered by potential redundancy. Unlike other metzincins, ADAM prodomains remain bound to the mature enzyme to regulate activity. Here ADAM12, a protease that promotes tumor progression and chondrocyte proliferation in osteoarthritic cartilage, is shown to possess a prodomain/catalytic domain cationic molecular switch, regulated by exogenous heparan sulfate and heparin but also endogenous cell surface proteoglycans and the polyanion, calcium pentosan polysulfate. Sheddase functions of ADAM12 are regulated by the switch, as are proteolytic functions in placental tissue and sera of pregnant women. Moreover, human heparanase, an enzyme also linked to tumorigenesis, can promote ADAM12 sheddase activity at the cell surface through cleavage of the inhibitory heparan sulfate. These data present a novel concept that might allow targeting of ADAM12 and suggest that other ADAMs may have specific regulatory activity embedded in their prodomain and catalytic domain structures