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      Dynamics in protein translation sustaining T cell preparedness

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          Abstract

          In response to pathogenic threats, naïve T cells rapidly transition from a quiescent to activated state, yet the underlying mechanisms are incompletely understood. Using a pulsed SILAC approach, we investigated the dynamics of mRNA translation kinetics and protein turnover in human naïve and activated T cells. Our datasets uncovered that transcription factors maintaining T cell quiescence had constitutively high turnover, which facilitated their depletion upon activation. Furthermore, naïve T cells maintained a surprisingly large number of idling ribosomes as well as 242 repressed mRNA species and a reservoir of glycolytic enzymes. These components were rapidly engaged following stimulation, promoting an immediate translational and glycolytic switch to ramp up the T cell activation program. Our data elucidate new insights into how T cells maintain a prepared state to mount a rapid immune response, and provide a resource of protein turnover, absolute translation kinetics and protein synthesis rates in T cells ( www.immunomics.ch).

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          Most cited references61

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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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            Understanding the tumor immune microenvironment (TIME) for effective therapy

            The clinical successes in immunotherapy have been both astounding and at the same time unsatisfactory. Countless patients with varied tumor types have seen pronounced clinical response with immunotherapeutic intervention; however, many more patients have experienced minimal or no clinical benefit when provided the same treatment. As technology has advanced, so has the understanding of the complexity and diversity of the immune context of the tumor microenvironment and its influence on response to therapy. It has been possible to identify different subclasses of immune environment that have an influence on tumor initiation and response and therapy; by parsing the unique classes and subclasses of tumor immune microenvironment (TIME) that exist within a patient’s tumor, the ability to predict and guide immunotherapeutic responsiveness will improve, and new therapeutic targets will be revealed.
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              Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position.

              We describe an assay for transposase-accessible chromatin using sequencing (ATAC-seq), based on direct in vitro transposition of sequencing adaptors into native chromatin, as a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq captures open chromatin sites using a simple two-step protocol with 500-50,000 cells and reveals the interplay between genomic locations of open chromatin, DNA-binding proteins, individual nucleosomes and chromatin compaction at nucleotide resolution. We discovered classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes. Using ATAC-seq maps of human CD4(+) T cells from a proband obtained on consecutive days, we demonstrated the feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making.
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                Author and article information

                Journal
                100941354
                Nat Immunol
                Nat Immunol
                Nature immunology
                1529-2908
                1529-2916
                04 March 2021
                01 August 2020
                06 July 2020
                19 March 2021
                : 21
                : 8
                : 927-937
                Affiliations
                [1 ]Institute for Research in Biomedicine, Università della Svizzera italiana, Switzerland
                [2 ]Institute of Microbiology, ETH Zürich, Switzerland
                [3 ]Biozentrum, University of Basel, Switzerland
                [4 ]Max Planck Institute of Biochemistry, Experimental Systems Immunology, Germany
                [5 ]Institute for Immunodeficiency, Center for Chronic Immunodeficiency, Medical Center, Faculty of Medicine, Albert-Ludwigs-University of Freiburg, Freiburg, Germany
                [6 ]Integrated Research Training Group (IRTG) Medical Epigenetics, Collaborative Research Centre 992, Freiburg, Germany
                [7 ]Institute of Innate Immunity, Department of Systems Immunology and Proteomics, Medical Faculty, University of Bonn
                [8 ]DZIF – German Center for Infection Research, Satellite Center Freiburg, Germany
                [9 ]CIBSS – Centre for Integrative Biological Signalling Studies, Albert-Ludwigs University, Freiburg, Germany
                [10 ]RESIST – Cluster of Excellence 2155 to Hanover Medical School, Satellite Center Freiburg, Germany
                [11 ]Max Planck Institute of Biochemistry, Department of Proteomics and Signal Transduction, Germany
                Author notes
                [§ ]Correspondence to roger.geiger@ 123456irb.usi.ch
                Article
                EMS117975
                10.1038/s41590-020-0714-5
                7610365
                32632289
                dd155f6f-722b-494e-972c-efd9cf106c52

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                Immunology
                Immunology

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