The Prion Protein Ligand, Stress-Inducible Phosphoprotein 1, Regulates Amyloid-beta Oligomer Toxicity

In Alzheimer\u27s disease (AD), soluble amyloid-beta oligomers (A beta Os) trigger neurotoxic signaling, at least partially, via the cellular prion protein (PrPC). However, it is unknown whether other ligands of PrPC can regulate this potentially toxic interaction. Stress-inducible phosphoprotein 1 (STI1), an Hsp90 cochaperone secreted by astrocytes, binds to PrPC in the vicinity of the A beta O binding site to protect neurons against toxic stimuli. Here, we investigated a potential role of STI1 in A beta O toxicity. We confirmed the specific binding of A beta Os and STI1 to the PrP and showed that STI1 efficiently inhibited A beta O binding to PrP in vitro (IC50 of similar to 70 nM) and also decreased A beta O binding to cultured mouse primary hippocampal neurons. Treatment with STI1 prevented A beta O-induced synaptic loss and neuronal death in mouse cultured neurons and long-term potentiation inhibition in mouse hippocampal slices. Interestingly, STI1-haploinsufficient neurons were more sensitive to A beta O-induced cell death and could be rescued by treatment with recombinant STI1. Noteworthy, both A beta O binding to PrPC and PrPC-dependent A beta O toxicity were inhibited by TPR2A, the PrPC-interacting domain of STI1. Additionally, PrPC-STI1 engagement activated alpha 7 nicotinic acetylcholine receptors, which participated in neuroprotection against A beta O-induced toxicity. We found an age-dependent upregulation of cortical STI1 in the APPswe/PS1dE9 mouse model of AD and in the brains of AD-affected individuals, suggesting a compensatory response. Our findings reveal a previously unrecognized role of the PrPC ligand STI1 in protecting neurons in AD and suggest a novel pathway that may help to offset A beta O-induced toxicity

Influence de la nanostructuration énergétique des substrats dans l'adhésion et la différenciation des cellules neuronales modèles PC12

Significant advances have been made in understanding surface adhesion parameters. Several studies recently demonstrated the combined impact of chemical, spatial and mechanical cues of cell culture substrates in controlling cell functions, together with the genetic program of the cell. This study focus on the substratum physical cue that is surface energy, and in particular, on the influence of surface-energy spatial distribution on neuronal cell differentiation. The cell model under consideration is constituted by clonal-line PC12 pheochromocytoma-cells. PC12 cells have the ability to undergo terminal neuronal differentiation, typically when treated with nerve growth factor (NGF). In this study, PC12 cells were seeded on glass surfaces modified by the self-assembly of alkylsiloxanes or of biopolymers such as poly-L-lysine. By changing the structure, ordering and chemical nature of the self-assembled monolayers, the spatial distribution of surface-energy polar and dispersive components is altered. When seeded on well-ordered homogeneous substrates (with CH3, NH2, or OH terminal groups), PC12 cell adhesion is driven by chemical affinity, and only a few cells initiate neurites. Conversely, PC12 cell adhesion is always effective when seeded on highly disordered substrates, whatever couple of chemical groups (CH3/OH or NH2/OH) generates the surface heterogeneities. In addition, high levels of PC12 cell neuritogenesis are observed by less than 48 h of culture, and without NGF treatment. This work demonstrates that surface chemical heterogeneities, that generate nanoscale surface-energy gradients, are critical to biological processes such as nerve regeneration on biomaterials.Les paramètres de surface contrôlent les fonctions des cellules, en coopération avec leurs codes génétiques. Des études récentes soulignent l'impact combiné des signaux chimiques, topographiques et mécaniques des substrats d'adhésion sur les processus de différenciation. Cette étude se focalise sur le paramètre énergétique, et plus spécialement, sur l'influence exercée par la distribution spatiale des énergies de surface sur la différenciation des cellules neuronales. Le modèle étudié est constitué par les cellules de la lignée PC12, capables de se différencier en neurones suite au traitement par le facteur de croissance nerveux (NGF). Les cellules sont cultivées sur des surfaces de verre modifiées par auto-assemblage de monocouches d'alkylsiloxanes ou de biopolymères. La modification de la nature chimique et du degré d'organisation des monocouches module la distribution des composantes dispersives et polaires de l'énergie de surface, à une échelle inférieure au micron. Sur des substrats très homogènes (dotés de terminaisons CH3, NH2, ou OH), l'adhésion des cellules PC12 est modulée par le degré d'affinité chimique, et peu de cellules initient des neurites. Inversement, sur des substrats localement très hétérogènes, les cellules adhèrent quel que soit le couple chimique produisant les hétérogénéités (NH2/OH ou CH3/OH), et elles génèrent un nombre important de neurites en moins de 48 h, sans traitement au NGF. Ce travail démontre que les hétérogénéités chimiques de surface exercent une influence critique sur les processus de régénérescence des cellules nerveuses, en induisant des gradients dans les énergies d'adhésion aux échelles nanométriques

Influence de la nanostructuration énergétique des substrats dans l'adhésion et la différenciation des cellules neuronales modèles PC12

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

Lipid peroxidation in turbot (Scophthalmus maximus) tissue : effect of dietary vitamin E and dietary n-6 or n-3 polyunsaturated fatty acids

International audienc

Inverse Correlation between Amyloid Stiffness and Size

International audienceWe reveal that the axial stiffness of amyloid fibrils is inversely correlated with their cross-sectional area. Because amyloid fibrils' stiffness is determined by hydrogen bond (H-bond) density with a linear correlation, our finding implies that amyloid fibrils with larger radial sizes are generally softer and have lower density H-bond networks. In silico calculations show that the stiffness-size relationship of amyloid fibrils is, indeed, driven by the packing densities of residues and H-bonds. Our results suggest that polypeptide chains which form amyloid fibrils with narrow cross sections can optimize packing densities in the fibrillar core structure, in contrast to those forming wide amyloid fibrils. Consequently, the density of residues and H-bonds that contribute to mechanical stability is higher in amyloid fibrils with narrow cross sections. This size dependence of nanomechanics appears to be a global property of amyloid fibrils, just like the well-known cross-β sheet topology

Using the fast-QI mode to dynamically map the nanoscale topography and stiffness of lamellipodia and lamella

International audienceCell migration affects cellular function and can have detrimental effects in many pathologies such as cancer metastasis. To directly probe and quantify the nanoscale dynamics of the structure and mechanics of living cells is a challenging task. At the leading cell edge, the lamellipodium and the lamellum are flat actin modules that interact to drive cell migration [1]. The lamellipodium projects itself from the lamellum and exhibits rapid changes on the timescale of seconds, hence measuring its stiffness has remained difficult. Here we describe the fast-quantitative imaging (fast-QI) mode, and we show that fast-QI is able to map both the lamellipodium and the lamellum at the same time (Figure 1), and with increased spatiotemporal resolution compared to the classic quantitative imaging™(QI) mode [2]. Especially, we demonstrate that, at the leading edge, the lamellipodium is both slightly thinner and much softer than the lamellum. Moreover, we demonstrate that the fast-QI mode produces accurate maps of the height and of the apparent Young’s modulus, through simple and efficient processing of the force-distance curves (Figure 2). The lamellipodium is a mechanosensing machine that can sense substrate stiffness, through the regulation of focal adhesion dynamics by both substrate stiffness and membrane tension [3]. Therefore, our results highlight the potential of the fast-QI mode to study the role that the nanoscale structure and stiffness of motile cell modules might play in mechanosensing

Mapping and Modeling the Nanomechanics of Bare and Protein-Coated Lipid Nanotubes

International audienceMembrane nanotubes are continuously assembled and disassembled by the cell to generate and dispatch transport vesicles, for instance, in endocytosis. While these processes crucially involve the ill-understood local mechanics of the nanotube, existing micromanipulation assays only give access to its global mechanical properties. Here we develop a new platform to study this local mechanics using atomic force microscopy (AFM). On a single coverslip we quickly generate millions of substrate-bound nanotubes, out of which dozens can be imaged by AFM in a single experiment. A full theoretical description of the AFM tip-membrane interaction allows us to accurately relate AFM measurements of the nanotube heights, widths, and rigidities to the membrane bending rigidity and tension, thus demonstrating our assay as an accurate probe of nanotube mechanics. We reveal a universal relationship between nanotube height and rigidity, which is unaffected by the specific conditions of attachment to the substrate. Moreover, we show that the parabolic shape of force-displacement curves results from thermal fluctuations of the membrane that collides intermittently with the AFM tip. We also show that membrane nanotubes can exhibit high resilience against extreme lateral compression. Finally, we mimic in vivo actin polymerization on nanotubes and use AFM to assess the induced changes in nanotube physical properties. Our assay may help unravel the local mechanics of membrane-protein interactions, including membrane remodeling in nanotube scission and vesicle formation

Easyworm: an open-source software tool to determine the mechanical properties of worm-like chains

Background: A growing spectrum of applications for natural and synthetic polymers, whether in industry or for biomedical research, demands for fast and universally applicable tools to determine the mechanical properties of very diverse polymers. To date, determining these properties is the privilege of a limited circle of biophysicists and engineers with appropriate technical skills. Findings: Easyworm is a user-friendly software suite coded in MATLAB that simplifies the image analysis of individual polymeric chains and the extraction of the mechanical properties of these chains. Easyworm contains a comprehensive set of tools that, amongst others, allow the persistence length of single chains and the Young’s modulus of elasticity to be calculated in multiple ways from images of polymers obtained by a variety of techniques (e.g. atomic force microscopy, electron, contrast-phase, or epifluorescence microscopy). Conclusions: Easyworm thus provides a simple and efficient tool for specialists and non-specialists alike to solve a common problem in (bio)polymer science. Stand-alone executables and shell scripts are provided along with source code for further development.Biochemistry and Molecular Biology, Department ofChemistry, Department ofMedicine, Faculty ofScience, Faculty ofOther UBCReviewedFacult