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      Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection

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          Summary

          The phenotypic and functional dichotomy between IRF8 + type 1 and IRF4 + type 2 conventional dendritic cells (cDC1s and cDC2s, respectively) is well accepted; it is unknown how robust this dichotomy is under inflammatory conditions, when additionally monocyte-derived cells (MCs) become competent antigen-presenting cells (APCs). Using single-cell technologies in models of respiratory viral infection, we found that lung cDC2s acquired expression of the Fc receptor CD64 shared with MCs and of IRF8 shared with cDC1s. These inflammatory cDC2s (inf-cDC2s) were superior in inducing CD4 + T helper (Th) cell polarization while simultaneously presenting antigen to CD8 + T cells. When carefully separated from inf-cDC2s, MCs lacked APC function. Inf-cDC2s matured in response to cell-intrinsic Toll-like receptor and type 1 interferon receptor signaling, upregulated an IRF8-dependent maturation module, and acquired antigens via convalescent serum and Fc receptors. Because hybrid inf-cDC2s are easily confused with monocyte-derived cells, their existence could explain why APC functions have been attributed to MCs.

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          Highlights

          • Type I interferon drives differentiation of inf-cDC2s that closely resemble MCs

          • Inf-cDC2s prime CD4 + and CD8 + T cells, whereas MCs lack APC function

          • Inf-cDC2s internalize antibody-complexed antigen via Fc receptors

          • IRF8 controls maturation gene module in inf-cDC2s

          Abstract

          The dichotomy between type 1 and 2 conventional DCs under steady-state conditions is well defined. Bosteels et al. demonstrate that, upon inflammation, cDC2s acquire a hybrid inf-cDC2 phenotype, sharing phenotype, gene expression, and function with cDC1s and monocyte-derived cells, to optimally boost CD4 and CD8 immunity via Fc receptors.

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          Most cited references76

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          Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity.

          Although in vitro observations suggest that cross-presentation of antigens is mediated primarily by CD8alpha+ dendritic cells, in vivo analysis has been hampered by the lack of systems that selectively eliminate this cell lineage. We show that deletion of the transcription factor Batf3 ablated development of CD8alpha+ dendritic cells, allowing us to examine their role in immunity in vivo. Dendritic cells from Batf3-/- mice were defective in cross-presentation, and Batf3-/- mice lacked virus-specific CD8+ T cell responses to West Nile virus. Importantly, rejection of highly immunogenic syngeneic tumors was impaired in Batf3-/- mice. These results suggest an important role for CD8alpha+ dendritic cells and cross-presentation in responses to viruses and in tumor rejection.
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            Is Open Access

            A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

            Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise and data complexity. The differences between scRNA-seq and bulk RNA-seq data mean that the analysis of the former cannot be performed by recycling bioinformatics pipelines for the latter. Rather, dedicated single-cell methods are required at various steps to exploit the cellular resolution while accounting for technical noise. This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project. It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. Analyses were demonstrated on gene-level count data from several publicly available datasets involving haematopoietic stem cells, brain-derived cells, T-helper cells and mouse embryonic stem cells. This will provide a range of usage scenarios from which readers can construct their own analysis pipelines.
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              The convalescent sera option for containing COVID-19

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                Author and article information

                Contributors
                Journal
                Immunity
                Immunity
                Immunity
                Elsevier Inc.
                1074-7613
                1097-4180
                8 May 2020
                8 May 2020
                Affiliations
                [1 ]Laboratory of Immunoregulation and Mucosal Immunology, VIB-UGent Center for Inflammation Research, Ghent 9052, Belgium
                [2 ]Department of Internal Medicine and Pediatrics, Ghent University, Ghent 9000, Belgium
                [3 ]Laboratory of ER Stress and Inflammation, VIB-UGent Center for Inflammation Research, Ghent 9052, Belgium
                [4 ]Data Mining and Modeling for Biomedicine Group, VIB-UGent Center for Inflammation Research, Ghent 9052, Belgium
                [5 ]Department of Biomedical Molecular Biology, Ghent University, Ghent 9052, Belgium
                [6 ]Argenx BV, Ghent 9052, Belgium
                [7 ]Department of Surgery and Center of Excellence in Inflammation, Infectious Disease and Immunity, Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA
                [8 ]Malaghan Institute of Medical Research, Wellington 6012, New Zealand
                [9 ]Department of Pulmonary Medicine, Erasmus University Medical Center Rotterdam, Rotterdam 3015 GJ, the Netherlands
                [10 ]Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent 9000, Belgium
                Author notes
                []Corresponding author martin.guilliams@ 123456ugent.vib.be
                [∗∗ ]Corresponding author bart.lambrecht@ 123456ugent.be
                [11]

                These authors contributed equally

                [12]

                These authors contributed equally

                [13]

                Lead Contact

                Article
                S1074-7613(20)30163-1
                10.1016/j.immuni.2020.04.005
                7207120
                32392463
                24940db6-e5af-4bcd-991f-bc97759ea363
                © 2020 Elsevier Inc.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 23 October 2019
                : 5 March 2020
                : 14 April 2020
                Categories
                Article

                Immunology
                dendritic cell,monocyte,transcription factor,irf8,virus,cd64,inf-cdc2,inflammation,type 1 interferon,fc receptor,convalescent serum

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