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      CD4 + resident memory T cells dominate immunosurveillance and orchestrate local recall responses

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          Abstract

          CD4 T cell localization impacts function and differentiation. Beura et al. show that memory CD4 + T cells are largely resident in both lymphoid and non-lymphoid tissues, organize local recall responses, and share overlapping transcriptional and location-specific features with CD8 + T RM.

          Abstract

          This study examines the extent to which memory CD4 + T cells share immunosurveillance strategies with CD8 + resident memory T cells (T RM). After acute viral infection, memory CD4 + T cells predominantly used residence to survey nonlymphoid tissues, albeit not as stringently as observed for CD8 + T cells. In contrast, memory CD4 + T cells were more likely to be resident within lymphoid organs than CD8 + T cells. Migration properties of memory-phenotype CD4 + T cells in non-SPF parabionts were similar, generalizing these results to diverse infections and conditions. CD4 + and CD8 + T RM shared overlapping transcriptional signatures and location-specific features, such as granzyme B expression in the small intestine, revealing tissue-specific and migration property–specific, in addition to lineage-specific, differentiation programs. Functionally, mucosal CD4 + T RM reactivation locally triggered both chemokine expression and broad immune cell activation. Thus, residence provides a dominant mechanism for regionalizing CD4 + T cell immunity, and location enforces shared transcriptional, phenotypic, and functional properties with CD8 + T cells.

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          Recapitulating adult human immune traits in laboratory mice by normalizing environment

          Our current understanding of immunology was largely defined in laboratory mice because of experimental advantages including inbred homogeneity, tools for genetic manipulation, the ability to perform kinetic tissue analyses starting with the onset of disease, and tractable models. Comparably reductionist experiments are neither technically nor ethically possible in humans. Despite revealing many fundamental principals of immunology, there is growing concern that mice fail to capture relevant aspects of the human immune system, which may account for failures to translate disease treatments from bench to bedside 1–8 . Laboratory mice live in abnormally hygienic “specific pathogen free” (SPF) barrier facilities. Here we show that the standard practice of laboratory mouse husbandry has profound effects on the immune system and that environmental changes result in better recapitulation of features of adult humans. Laboratory mice lack effector-differentiated and mucosally distributed memory T cells, which more closely resembles neonatal than adult humans. These cell populations were present in free-living barn populations of feral mice, pet store mice with diverse microbial experience, and were induced in laboratory mice after co-housing with pet store mice, suggesting a role for environment. Consequences of altering mouse housing profoundly impacted the cellular composition of the innate and adaptive immune system and resulted in global changes in blood cell gene expression patterns that more closely aligned with immune signatures of adult humans rather than neonates, altered the mouse’s resistance to infection, and impacted T cell differentiation to a de novo viral infection. These data highlight the impact of environment on the basal immune state and response to infection and suggest that restoring physiological microbial exposure in laboratory mice could provide a relevant tool for modeling immunological events in free-living organisms, including humans.
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            Moderated statistical tests for assessing differences in tag abundance.

            Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small. We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. Not only is our strategy applicable even with the smallest number of libraries, but it also proves to be more powerful than previous strategies when more libraries are available. The methodology is equally applicable to other counting technologies, such as proteomic spectral counts. An R package can be accessed from http://bioinf.wehi.edu.au/resources/
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              FastQC: a quality-control tool for high-throughput sequence data.

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                Author and article information

                Journal
                J Exp Med
                J. Exp. Med
                jem
                jem
                The Journal of Experimental Medicine
                Rockefeller University Press
                0022-1007
                1540-9538
                06 May 2019
                28 March 2019
                : 216
                : 5
                : 1214-1229
                Affiliations
                [1 ]Department of Microbiology and Immunology, University of Minnesota, Minneapolis, MN
                [2 ]Center for Immunology, University of Minnesota, Minneapolis, MN
                Author notes
                Correspondence to David Masopust: masopust@ 123456umn.edu

                E.M. Steinert’s present address is Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

                E.A. Thompson’s present address is Bluebird Bio, Cambridge, MA.

                K.A. Fraser’s present address is Takeda, Cambridge, MA.

                J.M. Schenkel’s present address is Brigham and Women’s Hospital, Boston, MA.

                Author information
                http://orcid.org/0000-0002-8597-3949
                http://orcid.org/0000-0002-6947-2271
                http://orcid.org/0000-0003-4641-6872
                http://orcid.org/0000-0002-2520-809X
                http://orcid.org/0000-0002-9440-3884
                Article
                20181365
                10.1084/jem.20181365
                6504216
                30923043
                d9e84329-ff68-43fc-8204-61dffcc3974b
                © 2019 Beura et al.

                This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms/). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 4.0 International license, as described at https://creativecommons.org/licenses/by-nc-sa/4.0/).

                History
                : 18 July 2018
                : 22 January 2019
                : 14 March 2019
                Page count
                Pages: 16
                Funding
                Funded by: Howard Hughes Medical Institute, DOI https://doi.org/10.13039/100000011;
                Funded by: National Institutes of Health, DOI https://doi.org/10.13039/100000002;
                Award ID: R01AI111671
                Award ID: R01AI084913
                Categories
                Research Articles
                Article
                319

                Medicine
                Medicine

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