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E1 and E2 (E1E2), the fusion proteins of Hepatitis C Virus (HCV), are unlike that of any other virus yet described, and the detailed molecular mechanisms of HCV entry/fusion remain unknown. Hypervariable region-1 (HVR-1) of E2 is a putative intrinsically disordered protein tail. Here, we demonstrate that HVR-1 has an autoinhibitory function that suppresses the activity of E1E2 on free virions; this is dependent on its conformational entropy. Thus, HVR-1 is akin to a safety catch that prevents premature triggering of E1E2 activity. Crucially, this mechanism is turned off by host receptor interactions at the cell surface to allow entry. Mutations that reduce conformational entropy in HVR-1, or genetic deletion of HVR-1, turn off the safety catch to generate hyper-reactive HCV that exhibits enhanced virus entry but is thermally unstable and acutely sensitive to neutralising antibodies. Therefore, the HVR-1 safety catch controls the efficiency of virus entry and maintains resistance to neutralising antibodies. This discovery provides an explanation for the ability of HCV to persist in the face of continual immune assault and represents a novel regulatory mechanism that is likely to be found in other viral fusion machinery.

We present flexiMAP (flexible Modeling of Alternative PolyAdenylation), a new beta-regression-based method implemented in R, for discovering differential alternative polyadenylation events in standard RNA-seq data. We show, using both simulated and real data, that flexiMAP exhibits a good balance between specificity and sensitivity and compares favourably to existing methods, especially at low fold changes. In addition, the tests on simulated data reveal some hitherto unrecognised caveats of existing methods. Importantly, flexiMAP allows modeling of multiple known covariates that often confound the results of RNA-seq data analysis. This repository contains scripts and all data required to reproduce data in the manuscript. _simulationData zip files contain extensive set of simulations which should serve as a useful resource for the development of similar methods in the future. Additionally, it contains 3’ sequencing data (PolyA-seq) and RNA-seq data from the Human Brain Reference and the Universal Human Reference MAQC samples (Bullard et al., 2010) that was used in the manuscript., {"references":["Krzysztof J. Szkop, David S. Moss and Irene Nobeli flexiMAP: A regression-based method for discovering differential alternative polyadenylation events in standard RNA-seq data"]}

The ultimate aim of the EU-funded ImmunoGrid project is to develop a natural-scale model of the human immune system—that is, one that reflects both the diversity and the relative proportions of the molecules and cells that comprise it—together with the grid infrastructure necessary to apply this model to specific applications in the field of immunology. These objectives present the ImmunoGrid Consortium with formidable challenges in terms of complexity of the immune system, our partial understanding about how the immune system works, the lack of reliable data and the scale of computational resources required. In this paper, we explain the key challenges and the approaches adopted to overcome them. We also consider wider implications for the present ambitious plans to develop natural-scale, integrated models of the human body that can make contributions to personalized health care, such as the European Virtual Physiological Human initiative. Finally, we ask a key question: How long will it take us to resolve these challenges and when can we expect to have fully functional models that will deliver health-care benefits in the form of personalized care solutions and improved disease prevention?

Neutralising antibodies (inhibitors) are increasingly recognized to be a life-time risk in non-severe hemophilia A patients exposed to factor VIII concentrates. It is currently not possible to reliably identify the variable inhibitor risk between individuals. Risk appears to differ between F8 genotypes but also for individuals living with the same F8 genotype. As a T cell dependent process, the wild-type, factor concentrate-derived peptide sequences spanning the F8 mutation position are presented by class II MHC and responsible for driving the T helper response and subsequent B cell response. We hypothesize that the primary sequences of the 20,469 proteins in the human proteome will, coincidentally, contain short primary sequences homologous to key immunogenic peptides derived from the therapeutic factor VIII. We present in silico data and correlation with published registry inhibitor data (Fisher's exact test) to demonstrate the potential impact of such "proteome protection" and future potential to more reliably stratify individuals between low/negligible risk and more significant risk of inhibitor formation. We utilize a well-validated, computational tool, NetMHC-II, to enable large scale, computational comparison of predicted antigen presentation between endogenous, mutated FVIII derived peptides and factor-concentrate derived, wild-type FVIII peptides spanning all 520 F8 missense mutations listed on www.hadb.org. NetMHC-II analyses peptide presentation by 14 class II MHC HLA-DR alleles, resulting in analysis of 7,280 (520 x 14) permutations of F8 -MHC-II. We identify 56% (n=4,077) of these permutations to be at low/negligible risk of inhibitor formation, at a binding threshold of 500nM, defined as absence of a novel peptide-MHC surface capable of driving a helper T cell response (p=0.005). When cross referenced with potential homologous sequences buried anywhere in the human proteome (http://www.ebi.ac.uk/reference_proteomes), a further 1,237 F8 -MHC-II combinations are afforded "proteome protection" due to direct sequence homology between FVIII-derived peptide and peptide(s) derived from other proteins. This increases the total number of F8 -MHC-II combinations predicted to be unable to drive a T cell response to 73% (n=5,314). The residual 1,966 (27%) F8 -MHC-II combinations are predicted to retain the ability to present novel-interface FVIII-derived peptides to T cells with an IC50 Previous work exploring in silico prediction of FVIII-derived peptide presentation may have overestimated the number of F8 -MHC II combinations deemed to be at risk of contributing to inhibitor formation. Our data suggests an additional mechanism "protecting" a larger proportion of those living with non-severe HA from inhibitor formation. The contribution of "proteome protection" further reduces the "at risk" F8 -MHC II permutations to be more representative of clinically observed inhibitor rates. We identify a potential novel tolerance mechanism and provide key data for future in vitro validation strategies. Disclosures No relevant conflicts of interest to declare.