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      Tuning DO:DM Ratios Modulates MHC Class II Immunopeptidomes.

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          Abstract

          Major histocompatibility complex class II (MHC-II) antigen presentation underlies a wide range of immune responses in health and disease. However, how MHC-II antigen presentation is regulated by the peptide-loading catalyst HLA-DM (DM), its associated modulator, HLA-DO (DO), is incompletely understood. This is due largely to technical limitations: model antigen-presenting cell (APC) systems that express these MHC-II peptidome regulators at physiologically variable levels have not been described. Likewise, computational prediction tools that account for DO and DM activities are not presently available. To address these gaps, we created a panel of single MHC-II allele, HLA-DR4-expressing APC lines that cover a wide range of DO:DM ratio states. Using a combined immunopeptidomic and proteomic discovery strategy, we measured the effects DO:DM ratios have on peptide presentation by surveying over 10,000 unique DR4-presented peptides. The resulting data provide insight into peptide characteristics that influence their presentation with increasing DO:DM ratios. These include DM sensitivity, peptide abundance, binding affinity and motif, peptide length, and choice of binding register along the source protein. These findings have implications for designing improved HLA-II prediction algorithms and research strategies for dissecting the variety of functions that different APCs serve in the body.

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          Most cited references65

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Systematic and quantitative assessment of the ubiquitin-modified proteome.

            Despite the diverse biological pathways known to be regulated by ubiquitylation, global identification of substrates that are targeted for ubiquitylation has remained a challenge. To globally characterize the human ubiquitin-modified proteome (ubiquitinome), we utilized a monoclonal antibody that recognizes diglycine (diGly)-containing isopeptides following trypsin digestion. We identify ~19,000 diGly-modified lysine residues within ~5000 proteins. Using quantitative proteomics we monitored temporal changes in diGly site abundance in response to both proteasomal and translational inhibition, indicating both a dependence on ongoing translation to observe alterations in site abundance and distinct dynamics of individual modified lysines in response to proteasome inhibition. Further, we demonstrate that quantitative diGly proteomics can be utilized to identify substrates for cullin-RING ubiquitin ligases. Interrogation of the ubiquitinome allows for not only a quantitative assessment of alterations in protein homeostasis fidelity, but also identification of substrates for individual ubiquitin pathway enzymes. Copyright © 2011 Elsevier Inc. All rights reserved.
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              NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data

              Abstract Major histocompatibility complex (MHC) molecules are expressed on the cell surface, where they present peptides to T cells, which gives them a key role in the development of T-cell immune responses. MHC molecules come in two main variants: MHC Class I (MHC-I) and MHC Class II (MHC-II). MHC-I predominantly present peptides derived from intracellular proteins, whereas MHC-II predominantly presents peptides from extracellular proteins. In both cases, the binding between MHC and antigenic peptides is the most selective step in the antigen presentation pathway. Therefore, the prediction of peptide binding to MHC is a powerful utility to predict the possible specificity of a T-cell immune response. Commonly MHC binding prediction tools are trained on binding affinity or mass spectrometry-eluted ligands. Recent studies have however demonstrated how the integration of both data types can boost predictive performances. Inspired by this, we here present NetMHCpan-4.1 and NetMHCIIpan-4.0, two web servers created to predict binding between peptides and MHC-I and MHC-II, respectively. Both methods exploit tailored machine learning strategies to integrate different training data types, resulting in state-of-the-art performance and outperforming their competitors. The servers are available at http://www.cbs.dtu.dk/services/NetMHCpan-4.1/ and http://www.cbs.dtu.dk/services/NetMHCIIpan-4.0/.
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                Author and article information

                Journal
                Mol Cell Proteomics
                Molecular & cellular proteomics : MCP
                Elsevier BV
                1535-9484
                1535-9476
                March 2022
                : 21
                : 3
                Affiliations
                [1 ] Department of Chemical and Systems Biology, Stanford School of Medicine, Stanford University, Stanford, California, USA.
                [2 ] Department of Pediatrics - Human Gene Therapy, Stanford University School of Medicine, Stanford University, Stanford, California, USA; Stanford Immunology, Stanford University School of Medicine, Stanford, California, USA.
                [3 ] Department of Pediatrics - Human Gene Therapy, Stanford University School of Medicine, Stanford University, Stanford, California, USA.
                [4 ] Department of Pediatrics - Human Gene Therapy, Stanford University School of Medicine, Stanford University, Stanford, California, USA; Stanford Immunology, Stanford University School of Medicine, Stanford, California, USA. Electronic address: mellins@stanford.edu.
                [5 ] Chan Zuckerberg Biohub, Stanford, California, USA. Electronic address: josh.elias@czbiohub.org.
                Article
                S1535-9476(22)00012-3
                10.1016/j.mcpro.2022.100204
                35085787
                137c210b-32bb-44ba-8435-8363fb9d83df
                History

                immunopeptidome,mass spectrometry,proteome,DM,DO,HLA,antigen presentation,MHC

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