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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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          Highlights

          • A new cell line panel with varied DO:DM ratios informs MHC-II presentation.

          • Tuning DO:DM ratios corresponds with strikingly divergent MHC-II immunopeptidomes.

          • Our study bridges a gap in understanding and predicting MHC-II antigen presentation.

          In Brief

          Immunopeptide presentation by MHC-II regulates adaptive immunity. The noncanonical MHC molecules HLA-DM and HLA-DO cooperatively regulate MHC-II function, and their relative abundances vary across APCs and cellular contexts. How this variation influences immunopeptide repertoires remains unclear. We addressed this by creating cell lines expressing HLA-DM and HLA-DO, spanning several relative abundances and measuring their immunopeptide repertoires. We found that immunopeptides clustered according to their presentation levels across different DO:DM ratios. Predicted MHC-II binding affinity substantially contributed to but did not fully account for these results.

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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

                Contributors
                Journal
                Mol Cell Proteomics
                Mol Cell Proteomics
                Molecular & Cellular Proteomics : MCP
                American Society for Biochemistry and Molecular Biology
                1535-9476
                1535-9484
                25 January 2022
                March 2022
                25 January 2022
                : 21
                : 3
                : 100204
                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
                [3 ]Stanford Immunology, Stanford University School of Medicine, Stanford, California, USA
                [4 ]Chan Zuckerberg Biohub, Stanford, California, USA
                Author notes
                []For correspondence: Joshua E. Elias; Elizabeth D. Mellins mellins@ 123456stanford.edu josh.elias@ 123456czbiohub.org
                [‡]

                These authors contributed equally to this work.

                Article
                S1535-9476(22)00012-3 100204
                10.1016/j.mcpro.2022.100204
                10329146
                35085787
                137c210b-32bb-44ba-8435-8363fb9d83df
                © 2022 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 5 March 2021
                : 7 January 2022
                Categories
                Research
                Special Issue: Immunopeptidomics

                Molecular biology
                antigen presentation,hla,do,dm,mhc,mass spectrometry,immunopeptidome,proteome
                Molecular biology
                antigen presentation, hla, do, dm, mhc, mass spectrometry, immunopeptidome, proteome

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