Differential phosphorylation of IRS-1 and IRS-2 by insulin and IGF-I receptors

The specific contribution of insulin and IGF-I receptors to IRS-protein activation remains elusive. We studied the signalling properties of AspB10-insulin, an analog with enhanced affinity for the IGF-I receptor, in comparison to native insulin using primary human skeletal muscle cells. In myoblasts regular insulin and AspB10-insulin were equipotent in stimulating the IRS cascade, whereas this analog induced a significantly higher Shc phosphorylation. Phosphorylation of IRS-1 in response to insulin was inhibited equally by blocking either the insulin or the IGF-I receptor. IRS-1 activation by AspB10-insulin was only inhibited by blocking the IGF-I receptor. IRS-2 phosphorylation induced by both insulin and AspB10-insulin was nearly insensitive to blocking the insulin receptor, being predominantly mediated by the IGF-I receptor. We conclude that in myoblasts IRS-2, but not IRS-1, functions as preferred substrate for the IGF-I receptor. These data suggest a specific role for IRS-2 in growth and differentiation of human skeletal muscle.     

A Note on Maritime Delimitation in a Multizonal Context: The Case of the Mediterranean

This article points out some of the issues that may arise during the delimitation of maritime boundary in a sea area where coastal states have proclaimed various maritime zones. Issues considered include delimitation in the presence of overlapping or coincident zones, the role of existing boundaries, use of all-purpose maritime boundaries, and the delimitation of future zones. Special reference is made to the Mediterranean Sea where coastal states have advanced various claims consisting of zones sometimes different from the ones provided for in the 1982 United Nations Convention on the Law of the Sea.     

Cutting edge: L-selectin (CD62L) expression distinguishes small resting memory CD4+ T cells that preferentially respond to recall antigen

Naive CD4+ T cells use L-selectin (CD62L) expression to facilitate immune surveillance. However, the reasons for its expression on a subset of memory CD4+ T cells are unknown. We show that memory CD4+ T cells expressing CD62L were smaller, proliferated well in response to tetanus toxoid, had longer telomeres, and expressed genes and proteins consistent with immune surveillance function. Conversely, memory CD4+ T cells lacking CD62L expression were larger, proliferated poorly in response to tetanus toxoid, had shorter telomeres, and expressed genes and proteins consistent with effector function. These findings suggest that CD62L expression facilitates immune surveillance by programming CD4+ T cell blood and lymph node recirculation, irrespective of naive or memory CD4+ T cell phenotype.     

MHCPred: bringing a quantitative dimension to the online prediction of MHC binding

The accurate prediction of T cell epitopes is one of the key aspirations of immunoinformatics. We have developed a partial least squares-based, robust multivariate statistical method for the quantitative prediction of peptide binding to major histocompatibility complexes (MHCs), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available as a World Wide Web server.     

The Effect of Leflunomide on Cycling and Activation of T-Cells in HIV-1-Infected Participants

Background

The pathogenesis of immunodeficiency due to human immunodeficiency virus (HIV)-1 is incompletely understood, but immune activation is believed to play a central role. Immunomodulatory agents that decrease immune activation may be useful in the treatment of HIV-1 infection.

Methodology

A randomized, double blind, placebo-controlled pilot study of leflunomide for 28 days was performed in participants with HIV-1 infection who were not receiving antiretroviral therapy. Participants randomized to leflunomide were subsequently treated with cholestyramine until leflunomide levels were below detection limit.

Findings

Treatment with leflunomide was well tolerated with mostly low-grade adverse events. Leflunomide administration reduced cycling of CD4 T cells (by ex vivo bromodeoxyuridine uptake and Ki67 expression) and decreased expression of activation markers (HLA-DR/CD38 co-expression) on CD8 T cells in peripheral blood. In addition, decreased expression of HIV-1 co-receptors was observed in both CD4 and CD8 T cells in the leflunomide group. There were no significant changes in naïve and memory T cell subsets, apoptosis of T cells or markers of microbial translocation.

Conclusions

Leflunomide was effective in reducing immune activation in the setting of chronic HIV-1 infection suggesting that targeting immune activation with immunomodulatory agents may be a feasible strategy.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00101374","term_id":"NCT00101374"}}NCT00101374     

Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.