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      CMIP is a negative regulator of T cell signaling

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          Abstract

          Upon their interaction with cognate antigen, T cells integrate different extracellular and intracellular signals involving basal and induced protein–protein interactions, as well as the binding of proteins to lipids, which can lead to either cell activation or inhibition. Here, we show that the selective T cell expression of CMIP, a new adapter protein, by targeted transgenesis drives T cells toward a naïve phenotype. We found that CMIP inhibits activation of the Src kinases Fyn and Lck after CD3/CD28 costimulation and the subsequent localization of Fyn and Lck to LRs. Video microscopy analysis showed that CMIP blocks the recruitment of LAT and the lipid raft marker cholera toxin B at the site of TCR engagement. Proteomic analysis identified several protein clusters differentially modulated by CMIP and, notably, Cofilin-1, which is inactivated in CMIP-expressing T cells. Moreover, transgenic T cells exhibited the downregulation of GM3 synthase, a key enzyme involved in the biosynthesis of gangliosides. These results suggest that CMIP negatively impacts proximal signaling and cytoskeletal rearrangement and defines a new mechanism for the negative regulation of T cells that could be a therapeutic target.

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          MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

          Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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            MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

            First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.
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              The regulation of IL-10 production by immune cells.

              Interleukin-10 (IL-10), a cytokine with anti-inflammatory properties, has a central role in infection by limiting the immune response to pathogens and thereby preventing damage to the host. Recently, an increasing interest in how IL10 expression is regulated in different immune cells has revealed some of the molecular mechanisms involved at the levels of signal transduction, epigenetics, transcription factor binding and gene activation. Understanding the specific molecular events that regulate the production of IL-10 will help to answer the remaining questions that are important for the design of new strategies of immune intervention.
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                Author and article information

                Contributors
                dil.sahali@inserm.fr
                Journal
                Cell Mol Immunol
                Cell Mol Immunol
                Cellular and Molecular Immunology
                Nature Publishing Group UK (London )
                1672-7681
                2042-0226
                8 August 2019
                October 2020
                : 17
                : 10
                : 1026-1041
                Affiliations
                [1 ]GRID grid.457370.2, Institut National de la Santé et de la Recherche Médicale (INSERM), UMRS 955, Equipe 21, ; F-94010 Créteil, France
                [2 ]GRID grid.410511.0, ISNI 0000 0001 2149 7878, Faculté de Médecine, , Université Paris Est, UMRS 955, Equipe 21, ; F-94010 Créteil, France
                [3 ]GRID grid.417843.d, ISNI 0000 0001 1089 0535, Proteomic Platform Necker, PPN-3P5, , Structure Fédérative de Recherche SFR Necker US24, ; 75015 Paris, France
                [4 ]GRID grid.213910.8, ISNI 0000 0001 1955 1644, Department of Biochemistry, Molecular and Cellular Biology, , Georgetown University, ; Washington, DC USA
                [5 ]GRID grid.50550.35, ISNI 0000 0001 2175 4109, AP-HP, Groupe Henri-Mondor Albert-Chenevier, , Service de Néphrologie, ; F-94010 Créteil, France
                [6 ]Institut Francilien De Recherche En Néphrologie Et Transplantation, F-94010 Créteil, France
                Author information
                http://orcid.org/0000-0001-5441-8662
                http://orcid.org/0000-0001-5343-2550
                Article
                266
                10.1038/s41423-019-0266-5
                7609264
                31395948
                15f1bf56-ce7a-42c8-88f0-e8e6368d1d3c
                © CSI and USTC 2019

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 1 December 2018
                : 10 July 2019
                Categories
                Article
                Custom metadata
                © CSI and USTC 2020

                Immunology
                cmip,transgenic mice,t cells,translational immunology,autoimmune diseases
                Immunology
                cmip, transgenic mice, t cells, translational immunology, autoimmune diseases

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