Efficient T cell activation requires an optimal dwell-time of interaction between the TCR and the pMHC complex.

Cytotoxic T cell (CTL) activation by antigen requires the specific detection of peptide-major histocompatibility class I (pMHC) molecules on the target-cell surface by the T cell receptor (TCR). We examined the effect of mutations in the antigen-binding site of a Kb-restricted TCR on T cell activation, antigen binding and dissociation from antigen.These parameters were also examined for variants derived from a Kd-restricted peptide that was recognized by a CTL clone. Using these two independent systems, we show that T cell activation can be impaired by mutations that either decrease or increase the binding half-life of the TCR-pMHC interaction. Our data indicate that efficient T cell activation occurs within an optimal dwell-time range of TCR-pMHC interaction. This restricted dwell-time range is consistent with the exclusion of either extremely low or high affinity T cells from the expanded population during immune responses.

A Role for cis Interaction between the Inhibitory Ly49A receptor and MHC class I for natural killer cell education.

Natural killer (NK) cells show enhanced functional competence when they express inhibitory receptors specific for inherited major histocompatibility complex class I (MHC-I) molecules. Current models imply that NK cell education requires an interaction of inhibitory receptors with MHC-I expressed on other cells. However, the inhibitory Ly49A receptor can also bind MHC-I ligand on the NK cell itself (in cis). Here we describe a Ly49A variant, which can engage MHC-I expressed on other cells but not in cis. Even though this variant inhibited NK cell effector function, it failed to educate NK cells. The association with MHC-I in cis sequestered wild-type Ly49A, and this was found to relieve NK cells from a suppressive effect of unengaged Ly49A. These data explain how inhibitory MHC-I receptors can facilitate NK cell activation. They dissociate classical inhibitory from educating functions of Ly49A and suggest that cis interaction of Ly49A is necessary for NK cell education.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Phosphorylation modulates FOXC2 transcriptional program by controlling the high-order interaction with DNA.

Phosphorylation of transcription factors is a rapid and reversible process linking cell signaling and control of gene expression, therefore understanding how it controls the transcription factor functions is one of the challenges of functional genomics. We performed such analysis for the forkhead transcription factor FOXC2 mutated in human hereditary disease lymphedemadistichiasis and important for the development of venous and lymphatic valves and lymphatic collecting vessels. We found that FOXC2 is phosphorylated in a cell-cycle dependent manner on eight evolutionary conserved serine/threonine residues, seven of which are clustered within a 70 amino acid domain. Surprisingly, the mutation of phosphorylation sites or a complete deletion of the domain did not affect the transcriptional activity of FOXC2 in a synthetic reporter assay. However, overexpression of the wild type or phosphorylation-deficient mutant resulted in overlapping but distinct gene expression profiles suggesting that binding of FOXC2 to individual sites under physiological conditions is affected by phosphorylation. To gain a direct insight into the role of FOXC2 phosphorylation, we performed comparative genome-wide location analysis (ChIP-chip) of wild type and phosphorylation-deficient FOXC2 in primary lymphatic endothelial cells. The effect of loss of phosphorylation on FOXC2 binding to genomic sites ranged from no effect to nearly complete inhibition of binding, suggesting a mechanism for how FOXC2 transcriptional program can be differentially regulated depending on FOXC2 phosphorylation status. Based on these results, we propose an extension to the enhanceosome model, where a network of genomic context-dependent DNA-protein and protein-protein interactions not only distinguishes a functional site from a nonphysiological site, but also determines whether binding to the functional site can be regulated by phosphorylation. Moreover, our results indicate that FOXC2 may have different roles in quiescent versus proliferating lymphatic endothelial cells in vivo.

Tabagisme, obésité et diabète: une interaction cliniquement importante [Smoking, obesity and diabetes: a clinically important interaction].

Smoking, obesity and diabetes are among the leading cause of premature death worldwide. Smokers have globally a lower body weight compared with non smokers but they tend to accumulate more fat in the abdomen. Most smokers gain weight when they quit smoking, however this does not seem to diminish the health benefits associated with smoking cessation. Smoking increases the risk of developing type 2 diabetes. Among people with diabetes, smoking significantly increases the risks of complications and mortality. Interventions with pharmacologic help should be offered to all smokers, with or without diabetes, in order to increase smoking cessation rates and limit weight gain.

NS4B Self-Interaction through Conserved C-Terminal Elements Is Required for the Establishment of Functional Hepatitis C Virus Replication Complexes.

Hepatitis C virus (HCV) is an important human pathogen, persistently infecting more than 170 million individuals worldwide. Studies of the HCV life cycle have become possible with the development of cell culture systems supporting the replication of viral RNA and the production of infectious virus. However, the exact functions of individual proteins, especially of nonstructural protein 4B (NS4B), remain poorly understood. NS4B triggers the formation of specific, vesicular membrane rearrangements, referred to as membranous webs, which have been reported to represent sites of HCV RNA replication. However, the mechanism of vesicle induction is not known. In this study, a panel of 15 mutants carrying substitutions in the highly conserved NS4B C-terminal domain was generated. Five mutations had only a minor effect on replication, but two of them enhanced assembly and release of infectious virus. Ten mutants were replication defective and used for selection of pseudoreversions. Most of the pseudoreversions also localized to the highly conserved NS4B C-terminal domain and were found to restore replication competence upon insertion into the corresponding primary mutant. Importantly, pseudoreversions restoring replication competence also restored heterotypic NS4B self-interaction, which was disrupted by the primary mutation. Finally, electron microscopy analyses of membrane alterations induced by NS4B mutants revealed striking morphological abnormalities, which were restored to wild-type morphology by the corresponding pseudoreversion. These findings demonstrate the important role of the C-terminal domain in NS4B self-interaction and the formation of functional HCV replication complexes.

Accurate calculations of intermolecular interaction energies using explicitly correlated coupled cluster wave functions and a dispersion-weighted MP2 method.

Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.

Semi-supervised remote sensing image classification with cluster kernels

A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.

Leukocyte-endothelial cell interaction is necessary for photodynamic therapy induced vascular permeabilization.

BACKGROUND AND OBJECTIVE: Photodynamic therapy (PDT) affects vascular barrier function and thus increases vessel permeability. This phenomenon may be exploited to facilitate targeted drug delivery and may lead to a new clinical application of photodynamic therapy. Here, we investigate the role of leukocyte recruitment for PDT-induced vascular permeabilization. STUDY DESIGN/MATERIAL AND METHODS: Fluorescein isothiocyanate dextran (FITC-D, 2,000 kDa) was injected intravenously 120 minutes after focal PDT on striated muscle in nude mice bearing dorsal skinfold chambers (Visudyne® 800 µg/kg, fluence rate 300 mW/cm2 , light dose of 200 J/cm2). Leukocyte interaction with endothelial cells was inhibited by antibodies functionally blocking adhesion molecules ("MABS-PDT" group, n = 5); control animals had PDT but no antibody injection (group "PDT", n = 7). By intravital microscopy, we monitored leukocyte rolling and sticking in real-time before, 90 and 180 minutes after PDT. The extravasation of FITC-D from striated muscle vessels into the interstitial space was determined in vivo during 45 minutes to assess treatment-induced alterations of vascular permeability. RESULTS: PDT significantly increased the recruitment of leukocytes and enhanced the leakage of FITC-D. Neutralization of adhesion molecules before PDT suppressed the rolling of leukocytes along the venular endothelium and significantly reduced the extravasation of FITC-D as compared to control animals (156 ± 27 vs. 11 ± 2 (mean ± SEM, number of WBC/30 seconds mm vessel circumference; P < 0.05) at 90 minutes after PDT and 194 ± 21 vs. 14 ± 4 at 180 minutes after PDT). In contrast, leukocyte sticking was not downregulated by the antibody treatment. CONCLUSION: Leukocyte recruitment plays an essential role in the permeability-enhancing effect of PDT.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Nouveaux traitements de l'hépatite C: aspects pharmacologiques et potentiel d'interaction [New hepatitis C treatments: pharmacological considerations and potential for drug interactions].

Progress in the understanding of the hepatitis C virus life cycle allowed the development of new, very promising antiviral therapies. Although these new drugs have a favourable profile in terms of efficacy, tolerance and interaction potential, their prescription in the setting of comedication and impaired renal or hepatic function remains a challenge. Here, we provide a summary of pharmacological considerations, focusing on sofosbuvir, simeprevir and daclatasvir. A better understanding of their metabolic pathways and transporters may help the prescriber to identify and manage drug interactions especially in patients under immunosuppressive or anti-HIV therapy. Recommendations for the prescription of these drugs in specific situations are also discussed.

DAI/ZBP1 recruits RIP1 and RIP3 through RIP homotypic interaction motifs to activate NF-kappaB.

Detection of viral nucleic acids is central to antiviral immunity. Recently, DAI/ZBP1 (DNA-dependent activator of IRFs/Z-DNA binding protein 1) was identified as a cytoplasmic DNA sensor and shown to activate the interferon regulatory factor (IRF) and nuclear factor-kappa B (NF-kappaB) transcription factors, leading to type-I interferon production. DAI-induced IRF activation depends on TANK-binding kinase 1 (TBK1), whereas signalling pathways and molecular components involved in NF-kappaB activation remain elusive. Here, we report the identification of two receptor-interacting protein (RIP) homotypic interaction motifs (RHIMs) in the DAI protein sequence, and show that these domains relay DAI-induced NF-kappaB signals through the recruitment of the RHIM-containing kinases RIP1 and RIP3. We show that knockdown of not only RIP1, but also RIP3 affects DAI-induced NF-kappaB activation. Importantly, RIP recruitment to DAI is inhibited by the RHIM-containing murine cytomegalovirus (MCMV) protein M45. These findings delineate the DAI signalling pathway to NF-kappaB and suggest a possible new immune modulation strategy of the MCMV.