Working Document: Towards a vision for research, technology and innovation cooperation between Russia and the EU, its Member States and Associated States

This Working Document outlines development perspectives for cooperation in research, technology and innovation (RTI) between the EU, its Member States (MS), countries associated to the EU’s FP7 (AC), and Russia. The Working Document has been prepared in the framework of the ERA.Net RUS project and is based on a comprehensive foresight exercise implemented over the years 2010-2013 and on analysis of ongoing RTI cooperation. In-depth discussions among the ERA.Net RUS and ERA.Net RUS Plus consortiums and Funding Parties, and in the frame of expert workshops with policy makers and analysts provided essential input. Furthermore, results of other related projects (such as BILAT-RUS, BILAT-RUS Advanced, ACCESSRU, etc.) have been studied. The paper proposes a vision on enhancing the cooperation between EU MS/AC and Russia overall, as well as a specific follow-up vision for the ERA.Net RUS and ERA.Net RUS Plus projects.JRC.J.2-Knowledge for Growt

Adipocyte Biology from the Perspective of In Vivo Research: Review of Key Transcription Factors

Obesity and type 2 diabetes are both significant contributors to the contemporary pandemic of non-communicable diseases. Both disorders are interconnected and associated with the disruption of normal homeostasis in adipose tissue. Consequently, exploring adipose tissue differentiation and homeostasis is important for the treatment and prevention of metabolic disorders. The aim of this work is to review the consecutive steps in the postnatal development of adipocytes, with a special emphasis on in vivo studies. We gave particular attention to well-known transcription factors that had been thoroughly described in vitro, and showed that the in vivo research of adipogenic differentiation can lead to surprising findings

Systematic evaluation of B-cell clonal family inference approaches

Abstract The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method

Additional file 1 of Systematic evaluation of B-cell clonal family inference approaches

Additional file 1: Supplementary Figure 1. Data simulation pipeline. Simulation approach is an integration of ImmuneSim, Alakazam and SHazaM tools and equally use the data of CF groupings obtained from each of the 10 CF inference approaches. Supplementary Figure 2. Determination of the number of TP, TN, FP, and FN. Three simulated CFs (2 singletons) and two inferred CFs are shown. Supplementary Figure 3. Overall correlation between the log10(number of CFs) and the standardized sequence depth for all combinations of approach (except SCOPer; A7, A8) and dataset. Supplementary Figure 4. Overall trend between the log10(number of CFs) and the standardized mutation load for all combinations of approach (except SCOPer; A7, A8) and dataset. Supplementary Figure 5. Summary of significant pairwise comparisons between Approaches. Supplementary Figure 6. Number of TP, TN, FP, and FN cases produced by the ten approaches when applied to six samples from three simulated datasets (D10, D11, D12). Supplementary Figure 7. Normalized number of TP, TN, FP, and FN cases produced by the ten approaches when applied to six samples from three simulated datasets (D10, D11, D12)

Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments

Immune complex formation in human diabetic retina enhances toxicity of oxidized LDL towards retinal capillary pericytes

Recently it has been shown that levels of circulating oxidized LDL immune complexes (ox-LDL-ICs) predict the development of diabetic retinopathy (DR). This study aimed to investigate whether ox-LDL-ICs are actually present in the diabetic retina, and to define their effects on human retinal pericytes versus ox-LDL. In retinal sections from people with type 2 diabetes, costaining for ox-LDL and IgG was present, proportionate to DR severity, and detectable even in the absence of clinical DR. In contrast, no such staining was observed in retinas from nondiabetic subjects. In vitro, human retinal pericytes were treated with native LDL, ox-LDL, and ox-LDL-IC (0–200 mg protein/l), and measures of viability, receptor expression, apoptosis, endoplasmic reticulum (ER) and oxidative stresses, and cytokine secretion were evaluated. Ox-LDL-IC exhibited greater cytotoxicity than ox-LDL toward retinal pericytes. Acting through the scavenger (CD36) and IgG (CD64) receptors, low concentrations of ox-LDL-IC triggered apoptosis mediated by oxidative and ER stresses, and enhanced inflammatory cytokine secretion. The data suggest that IC formation in the diabetic retina enhances the injurious effects of ox-LDL. These findings offer new insights into pathogenic mechanisms of DR, and may lead to new preventive measures and treatments

Survivin Monomer Plays an Essential Role in Apoptosis Regulation*

Survivin was initially described as an inhibitor of apoptosis and attracted growing attention as one of the most tumor-specific genes in the human genome and a promising target for cancer therapy. Lately, it has been shown that survivin is a multifunctional protein that takes part in several crucial cell processes. At first, it was supposed that survivin functions only as a homodimer, but now data indicate that many processes require monomeric survivin. Moreover, recent studies reveal a special mechanism regulating the balance between monomeric and dimeric forms of the protein. In this paper we studied the mutant form of survivin that was unable to dimerize and investigated its role in apoptosis. We showed that survivin monomer interacts with Smac/DIABLO and X-linked inhibitor of apoptosis protein (XIAP) both in vitro and in vivo. Due to this feature, it protects cells from caspase-dependent apoptosis even more efficiently than the wild-type survivin. We also identified that mutant monomeric survivin prevents apoptosis-inducing factor release from the mitochondrial intermembrane space, protecting human fibrosarcoma HT1080 cells from caspase-independent apoptosis. On the other hand, our results indicate that only wild-type survivin, but not the monomer mutant form, enhances tubulin stability in cells. These findings suggest that survivin partly performs its functions as a monomer and partly as a dimer. The mechanism of dimer-monomer balance regulation may also work as a “switcher” between survivin functions and thereby explain remarkable functional diversities of this protein