Characterization of a surrogate murine antibody to model anti-human CD3 therapies

Fc-modified anti-human CD3ε monoclonal antibodies (mAbs) are in clinical development for the treatment of autoimmune diseases. These next generation mAbs have completed clinical trials in patients with type-1 diabetes and inflammatory bowel disease demonstrating a narrow therapeutic window. Lowered doses are ineffective, yet higher pharmacologically-active doses cause an undesirable level of adverse events. Thus, there is a critical need for a return to bench research to explore ways of improving clinical outcomes. Indeed, we recently reported that a short course of treatment affords synergy, providing long-term disease amelioration when combining anti-mouse CD3 and anti-mouse tumor necrosis factor mAbs in experimental arthritis. Such strategies may widen the window between risk and benefit; however, to more accurately assess experimentally the biology and pharmacology, reagents that mimic the current development candidates were required. Consequently, we engineered an Fc-modified anti-mouse CD3ε mAb, 2C11-Novi. Here, we report the functional characterization of 2C11-Novi demonstrating that it does not bind FcγR in vitro and elicits little cytokine release in vivo, while maintaining classical pharmacodynamic effects (CD3-TCR downregulation and T cell killing). Furthermore, we observed that oral administration of 2C11-Novi ameliorated progression of remitting-relapsing experimental autoimmune encephalitis in mice, significantly reducing the primary acute and subsequent relapse phase of the disease. With innovative approaches validated in two experimental models of human disease, 2C11-Novi represents a meaningful tool to conduct further mechanistic studies aiming at exploiting the immunoregulatory properties of Fc-modified anti-CD3 therapies via combination therapy using parenteral or oral routes of administration.     

Can Yeast (S. cerevisiae) Metabolic Volatiles Provide Polymorphic Signaling?

Chemical signaling between organisms is a ubiquitous and evolutionarily dynamic process that helps to ensure mate recognition, location of nutrients, avoidance of toxins, and social cooperation. Evolutionary changes in chemical communication systems progress through natural variation within the organism generating the signal as well as the responding individuals. A promising yet poorly understood system with which to probe the importance of this variation exists between D. melanogaster and S. cerevisiae. D. melanogaster relies on yeast for nutrients, while also serving as a vector for yeast cell dispersal. Both are outstanding genetic and genomic models, with Drosophila also serving as a preeminent model for sensory neurobiology. To help develop these two genetic models as an ecological model, we have tested if - and to what extent - S. cerevisiae is capable of producing polymorphic signaling through variation in metabolic volatiles. We have carried out a chemical phenotyping experiment for 14 diverse accessions within a common garden random block design. Leveraging genomic sequences for 11 of the accessions, we ensured a genetically broad sample and tested for phylogenetic signal arising from phenotypic dataset. Our results demonstrate that significant quantitative differences for volatile blends do exist among S. cerevisiae accessions. Of particular ecological relevance, the compounds driving the blend differences (acetoin, 2-phenyl ethanol and 3-methyl-1-butanol) are known ligands for D. melanogasters chemosensory receptors, and are related to sensory behaviors. Though unable to correlate the genetic and volatile measurements, our data point clear ways forward for behavioral assays aimed at understanding the implications of this variation.     

Male Gender,Increased Blood Viscosity,Body Mass Index and Triglyceride Levels Are Independently Associated with Systemic Relative Hypertension in Sickle Cell Anemia

Patients with sickle cell anemia (SCA) have usually lower diastolic, systolic and mean blood pressure (BP) than the general population. However, BP values ≥120/70 mmHg considerably increase the risk for acute and chronic complications in SCA. The aim of this study was to identify biological factors associated with relative hypertension in adults with SCA. We compared the hematological, lipid and hemolytic profiles, as well as blood viscosity, between SCA patients with normal BP (<120/70 mmHg, n = 54) and those with relative hypertension (BP≥120/70 mmHg, n = 43). Our results demonstrated that male gender (OR: 3.49; 95%CI 1.20 to 10.16, p<0.05), triglycerides (OR: 9.19; 95% CI 2.29 to 36.95, p<0.01), blood viscosity (OR: 1.35; 95% CI 1.01 to 1.81, p<0.05) and body mass index (OR: 1.37; 95% CI 1.14 to 1.64, p<0.01) were independent risks factors for relative hypertension in SCA. No association was found between the BP status and the positive history of painful vaso-occlusive crisis or acute chest syndrome. An association between triglycerides level and the occurrence of these two major acute complications was detected. Our study suggests that male gender, increased triglycerides level, BMI and blood viscosity could increase the risk for developing relative hypertension in SCA. In addition, our results support a role of moderately elevated triglycerides in the pathophysiology of vaso-occlusive events.     

Hematological and hemorheological Determinants of the Six-Minute Walk Test Performance in Children with Sickle Cell Anemia

The six-minute walk test is a well-established submaximal exercise reflecting the functional status and the clinical severity of sickle cell patients. The aim of the present cross-sectional study was to investigate the biological determinants of the six-minute walk test performance in children with sickle cell anemia. Hematological and hemorheological parameters, pulmonary function and the six-minute walk test performance were determined in 42 children with sickle cell anemia at steady state. The performance during the six-minute walk test was normalized for age, sex and height and expressed as percentage of the predicted six-minute walk distance. We showed that a high level of anemia, a low fetal hemoglobin expression and low red blood cell deformability were independent predictors of a low six-minute walk test performance. This study describes for the first time the impact of blood rheology in the six-minute walk test performance in children with sickle cell anemia.     

Functional proteomics reveals the protective effects of saffron ethanolic extract on hepatic ischemia‐reperfusion injury

Hepatic ischemia‐reperfusion (IR) injury is a common clinical problem and ROS may be a contributing factor on IR injury. The current study evaluates the potential protective effect of saffron ethanol extract (SEE) in a rat model upon hepatic IR injury. Caspases 3 and terminal deoxynucleotidyl transferase‐mediated dUTP biotin nick end labeling (TUNEL) results showed increased cell death in the IR samples; reversely, minor apoptosis was detected in the SEE/IR group. Pretreatment with SEE significantly restored the content of antioxidant enzymes (SOD1 and catalase) and remarkably inhibited the intracellular ROS concentration in terms of reducing p47phox translocation. Proteome tools revealed that 20 proteins were significantly modulated in protein intensity between IR and SEE/IR groups. Particularly, SEE administration could attenuate the carbonylation level of several chaperone proteins. Network analysis suggested that saffron extract could alleviate IR‐induced ER stress and protein ubiquitination, which finally lead to cell apoptosis. Taken together, SEE could reduce hepatic IR injury through modulating protein oxidation and our results might help to develop novel therapeutic strategies against ROS‐caused diseases.     

Fluorescent (Au@SiO2)SiC Nanohybrids: Influence of Gold Nanoparticle Diameter and SiC Nanoparticle Surface Density

Gold@silica core–shell nanoparticles were prepared with various gold core diameters (ranging from 20 to 150 nm) and silica thicknesses (ranging from 10 to 30 nm). When the gold diameter is increased, the size dispersion became larger, leading to a broader plasmon band. Then, silicon carbide (SiC) nanoparticles were covalently immobilized onto silica to obtain hybrid (Au@SiO₂) SiC nanoparticles. The absorption properties of these hybrid nanoparticles showed that an excess of SiC nanoparticles in the dispersion can be identified by a strong absorption in the UV region. Compared to SiC reference samples, a blue shift of the fluorescence emission, from 582 to 523 nm, was observed, which was previously attributed to the strong surface modification of SiC when immobilized onto silica. Finally, the influence of several elaboration parameters (gold diameter, silica thickness, SiC concentration) on fluorescence enhancement was investigated. It showed that the highest enhancements were obtained with 10 nm silica thickness, low concentration of SiC nanoparticles, and surprisingly, with a 20-nm gold core diameter. This last result could be attributed to the broad plasmon band of big gold colloids. In this case, SiC emission strongly overlapped gold absorption, leading to possible quenching of SiC fluorescence by energy transfer.     

Protein-Protein Interactions in a Crowded Environment: An Analysis via Cross-Docking Simulations and Evolutionary Information

Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and their evolutionary sequence analysis leading to binding site predictions. Download site: http://www.lgm.upmc.fr/CCDMintseris/     

Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor

Despite important advances from Genome Wide Association Studies (GWAS), for most complex human traits and diseases, a sizable proportion of genetic variance remains unexplained and prediction accuracy (PA) is usually low. Evidence suggests that PA can be improved using Whole-Genome Regression (WGR) models where phenotypes are regressed on hundreds of thousands of variants simultaneously. The Genomic Best Linear Unbiased Prediction (G-BLUP, a ridge-regression type method) is a commonly used WGR method and has shown good predictive performance when applied to plant and animal breeding populations. However, breeding and human populations differ greatly in a number of factors that can affect the predictive performance of G-BLUP. Using theory, simulations, and real data analysis, we study the performance of G-BLUP when applied to data from related and unrelated human subjects. Under perfect linkage disequilibrium (LD) between markers and QTL, the prediction R-squared (R²) of G-BLUP reaches trait-heritability, asymptotically. However, under imperfect LD between markers and QTL, prediction R² based on G-BLUP has a much lower upper bound. We show that the minimum decrease in prediction accuracy caused by imperfect LD between markers and QTL is given by (1−b)², where b is the regression of marker-derived genomic relationships on those realized at causal loci. For pairs of related individuals, due to within-family disequilibrium, the patterns of realized genomic similarity are similar across the genome; therefore b is close to one inducing small decrease in R². However, with distantly related individuals b reaches very low values imposing a very low upper bound on prediction R². Our simulations suggest that for the analysis of data from unrelated individuals, the asymptotic upper bound on R² may be of the order of 20% of the trait heritability. We show how PA can be enhanced with use of variable selection or differential shrinkage of estimates of marker effects.     

The Susceptibility of Pseudomonas aeruginosa Strains from Cystic Fibrosis Patients to Bacteriophages

Phage therapy may become a complement to antibiotics in the treatment of chronic Pseudomonas aeruginosa infection. To design efficient therapeutic cocktails, the genetic diversity of the species and the spectrum of susceptibility to bacteriophages must be investigated. Bacterial strains showing high levels of phage resistance need to be identified in order to decipher the underlying mechanisms. Here we have selected genetically diverse P. aeruginosa strains from cystic fibrosis patients and tested their susceptibility to a large collection of phages. Based on plaque morphology and restriction profiles, six different phages were purified from “pyophage”, a commercial cocktail directed against five different bacterial species, including P. aeruginosa. Characterization of these phages by electron microscopy and sequencing of genome fragments showed that they belong to 4 different genera. Among 47 P. aeruginosa strains, 13 were not lysed by any of the isolated phages individually or by pyophage. We isolated two new phages that could lyse some of these strains, and their genomes were sequenced. The presence/absence of a CRISPR-Cas system (Clustered Regularly Interspaced Short Palindromic Repeats and Crisper associated genes) was investigated to evaluate the role of the system in phage resistance. Altogether, the results show that some P. aeruginosa strains cannot support the growth of any of the tested phages belonging to 5 different genera, and suggest that the CRISPR-Cas system is not a major defence mechanism against these lytic phages.