CD8+ T cell immunosurveillance is based on recognizing oligopeptides presented by MHC class I molecules. Despite decades of study, the importance of protein ubiquitylation to peptide generation remains uncertain. Here, we examine the ability of MLN7243, a recently described ubiquitin activating enzyme E1-inhibitor, to block overall cytosolic peptide generation and generation of specific peptides from vaccinia- and influenza A virus-encoded proteins. We show that MLN7243 rapidly inhibits ubiquitylation in a variety of cell lines, and can profoundly reduce generation of cytosolic peptides. Kinetic analysis of specific peptide generation reveals that ubiquitylation of defective ribosomal products (DRiPs) is rate limiting in generating class I peptide complexes. More generally, our findings demonstrate that the requirement for ubiquitylation in MHC class I restricted antigen processing varies with class I allomorph, cell type, source protein, and peptide context. Thus, both ubiquitin-dependent and independent pathways robustly contribute to MHC class I based immunosurveillance.

Type 1 diabetes is an autoimmune disease caused by T cell-mediated destruction of pancreatic insulin-producing beta cells. The epitopes recognised by pathogenic T cells in human type 1 diabetes are poorly defined; however, a growing body of evidence suggests that T cell responses against neoepitopes contribute to beta cell destruction in type 1 diabetes. Neoepitopes are formed when self-proteins undergo post-translational modification to create a new epitope that is recognised by T-or B cells. Here we review the role of human T cell responses against neoepitopes in the immune pathogenesis of type 1 diabetes. Specifically, we review the different approaches to identifying neoepitopes relevant to human type 1 diabetes and outline several advances in this field that have occurred over the past few years. We also discuss the application of neoepitopes to the development of antigenspecific therapies for type 1 diabetes and the unresolved challenges that need to be overcome before the full repertoire of neoepitopes recognised by pathogenic human T cells in type 1 diabetes can be determined. This information may then be used to develop antigen-specific therapies for type 1 diabetes and assays to monitor changes in pathogenic, beta cell-specific T cell responses.

The accurate prediction of human CD8 T-cell epitopes has great potential clinical and translational implications in the context of infection, cancer and autoimmunity. Prediction algorithms have traditionally focused on calculated peptide affinity for the binding groove of MHC-I. However, over the years it has become increasingly clear that the ultimate T-cell recognition of MHC-I-bound peptides is governed by many contributing factors within the complex antigen presentation pathway. Recent advances in next-generation sequencing and immunnopeptidomics have increased the precision of HLA-I sub-allele classification, and have led to the discovery of peptide processing events and individual allele-specific binding preferences. Here, we review some of the discoveries that initiated the development of peptide prediction algorithms, and outline some of the current available online tools for CD8 T-cell epitope prediction.

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