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      A genetic screen in macrophages identifies new regulators of IFNγ-inducible MHCII that contribute to T cell activation

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          Abstract

          Cytokine-mediated activation of host immunity is central to the control of pathogens. Interferon-gamma (IFNγ) is a key cytokine in protective immunity that induces major histocompatibility complex class II molecules (MHCII) to amplify CD4 + T cell activation and effector function. Despite its central role, the dynamic regulation of IFNγ-induced MHCII is not well understood. Using a genome-wide CRISPR-Cas9 screen in murine macrophages, we identified genes that control MHCII surface expression. Mechanistic studies uncovered two parallel pathways of IFNγ-mediated MHCII control that require the multifunctional glycogen synthase kinase three beta (GSK3β) or the mediator complex subunit 16 (MED16). Both pathways control distinct aspects of the IFNγ response and are necessary for IFNγ-mediated induction of the MHCII transactivator Ciita, MHCII expression, and CD4 + T cell activation. Our results define previously unappreciated regulation of MHCII expression that is required to control CD4 + T cell responses.

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          Most cited references76

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              Toward understanding the origin and evolution of cellular organisms

              In this era of high‐throughput biology, bioinformatics has become a major discipline for making sense out of large‐scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                08 November 2021
                2021
                : 10
                : e65110
                Affiliations
                [1 ] Department of Microbiology and Physiological Systems, University of Massachusetts Medical School Worcester United States
                [2 ] Department of Microbiology & Molecular Genetics, College of Osteopathic Medicine, Michigan State University East Lansing United States
                [3 ] Division of Infectious Disease and Immunology, Department of Medicine, University of Massachusetts Medical School Worcester United States
                ShanghaiTech University China
                Harvard T.H. Chan School of Public Health United States
                ShanghaiTech University China
                ShanghaiTech University China
                Mcgill University Canada
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-8364-8088
                https://orcid.org/0000-0002-6177-6916
                https://orcid.org/0000-0003-3441-3113
                Article
                65110
                10.7554/eLife.65110
                8598162
                34747695
                6dd86a93-8246-475b-8e1c-7e31a3331198
                © 2021, Kiritsy et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 23 November 2020
                : 03 November 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: AI146504
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000199, U.S. Department of Agriculture;
                Award ID: NIFA HATCH 1019371
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: AI132130
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Immunology and Inflammation
                Custom metadata
                Med16 and GSK3b regulate interferon gamma-mediated MHCII expression in macrophages and are required for CD4+ T cell activation.

                Life sciences
                ifn-gamma,mhcii expression,cd4+ t cell activation,macrophages,mouse
                Life sciences
                ifn-gamma, mhcii expression, cd4+ t cell activation, macrophages, mouse

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