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      Inhibition of macrophage histone demethylase JMJD3 protects against abdominal aortic aneurysms

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          Abstract

          Abdominal aortic aneurysms (AAAs) are a life-threatening disease characterized by macrophage infiltration contributing to pathological vascular remodeling. Herein, we demonstrate that the histone demethylase JMJD3 is a critical regulator of inflammation during AAA development and cell-specific inhibition reduces AAA progression.

          Abstract

          Abdominal aortic aneurysms (AAAs) are a life-threatening disease for which there is a lack of effective therapy preventing aortic rupture. During AAA formation, pathological vascular remodeling is driven by macrophage infiltration, and the mechanisms regulating macrophage-mediated inflammation remain undefined. Recent evidence suggests that an epigenetic enzyme, JMJD3, plays a critical role in establishing macrophage phenotype. Using single-cell RNA sequencing of human AAA tissues, we identified increased JMJD3 in aortic monocyte/macrophages resulting in up-regulation of an inflammatory immune response. Mechanistically, we report that interferon-β regulates Jmjd3 expression via JAK/STAT and that JMJD3 induces NF-κB–mediated inflammatory gene transcription in infiltrating aortic macrophages. In vivo targeted inhibition of JMJD3 with myeloid-specific genetic depletion ( JMJD3 f/fLyz2 Cre+ ) or pharmacological inhibition in the elastase or angiotensin II–induced AAA model preserved the repressive H3K27me3 on inflammatory gene promoters and markedly reduced AAA expansion and attenuated macrophage-mediated inflammation. Together, our findings suggest that cell-specific pharmacologic therapy targeting JMJD3 may be an effective intervention for AAA expansion.

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          Integrating single-cell transcriptomic data across different conditions, technologies, and species

          Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
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            Tissue-Resident Macrophage Ontogeny and Homeostasis.

            Defining the origins and developmental pathways of tissue-resident macrophages should help refine our understanding of the role of these cells in various disease settings and enable the design of novel macrophage-targeted therapies. In recent years the long-held belief that macrophage populations in the adult are continuously replenished by monocytes from the bone marrow (BM) has been overturned with the advent of new techniques to dissect cellular ontogeny. The new paradigm suggests that several tissue-resident macrophage populations are seeded during waves of embryonic hematopoiesis and self-maintain independently of BM contribution during adulthood. However, the exact nature of the embryonic progenitors that give rise to adult tissue-resident macrophages is still debated, and the mechanisms enabling macrophage population maintenance in the adult are undefined. Here, we review the emergence of these concepts and discuss current controversies and future directions in macrophage biology.
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              Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals.

              Cells of a multicellular organism are genetically homogeneous but structurally and functionally heterogeneous owing to the differential expression of genes. Many of these differences in gene expression arise during development and are subsequently retained through mitosis. Stable alterations of this kind are said to be 'epigenetic', because they are heritable in the short term but do not involve mutations of the DNA itself. Research over the past few years has focused on two molecular mechanisms that mediate epigenetic phenomena: DNA methylation and histone modifications. Here, we review advances in the understanding of the mechanism and role of DNA methylation in biological processes. Epigenetic effects by means of DNA methylation have an important role in development but can also arise stochastically as animals age. Identification of proteins that mediate these effects has provided insight into this complex process and diseases that occur when it is perturbed. External influences on epigenetic processes are seen in the effects of diet on long-term diseases such as cancer. Thus, epigenetic mechanisms seem to allow an organism to respond to the environment through changes in gene expression. The extent to which environmental effects can provoke epigenetic responses represents an exciting area of future research.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Software
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: Validation
                Role: MethodologyRole: ValidationRole: Writing - review & editing
                Role: Data curationRole: Formal analysis
                Role: Investigation
                Role: Data curation
                Role: Project administrationRole: SupervisionRole: Writing - review & editing
                Role: Investigation
                Role: Methodology
                Role: Data curationRole: InvestigationRole: Writing - review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - review & editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: Writing - review & editing
                Role: MethodologyRole: Writing - review & editing
                Role: MethodologyRole: Writing - review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing
                Journal
                J Exp Med
                J Exp Med
                jem
                The Journal of Experimental Medicine
                Rockefeller University Press
                0022-1007
                1540-9538
                07 June 2021
                29 March 2021
                : 218
                : 6
                : e20201839
                Affiliations
                [1 ]Section of Vascular Surgery, Department of Surgery, University of Michigan, Ann Arbor, MI
                [2 ]Department Microbiology and Immunology, University of Michigan, Ann Arbor, MI
                [3 ]Department of Dermatology, University of Michigan, Ann Arbor, MI
                [4 ]Department of Computation Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
                [5 ]Department of Biostatistics, University of Michigan, Ann Arbor, MI
                [6 ]Department of Internal Medicine, University of Michigan, Ann Arbor, MI
                [7 ]Department of Pathology, University of Michigan, Ann Arbor, MI
                [8 ]Department of Physiology, Saha Cardiovascular Research Center, University of Kentucky, Lexington, KY
                Author notes
                Correspondence to Frank M. Davis: davisfr@ 123456umich.edu
                Katherine A. Gallagher: kgallag@ 123456med.umich.edu

                Disclosures: The authors declare no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5847-8993
                https://orcid.org/0000-0003-1627-5722
                https://orcid.org/0000-0002-3241-5919
                https://orcid.org/0000-0001-9604-0557
                https://orcid.org/0000-0003-3544-3023
                https://orcid.org/0000-0001-6936-7132
                https://orcid.org/0000-0003-3626-9274
                https://orcid.org/0000-0001-7613-2366
                https://orcid.org/0000-0001-7115-9113
                https://orcid.org/0000-0003-4227-6868
                https://orcid.org/0000-0002-4183-8825
                https://orcid.org/0000-0003-3051-745X
                https://orcid.org/0000-0002-5738-6341
                https://orcid.org/0000-0003-2093-3775
                https://orcid.org/0000-0002-0577-2558
                https://orcid.org/0000-0002-0080-0812
                https://orcid.org/0000-0002-8791-6980
                Article
                jem.20201839
                10.1084/jem.20201839
                8008365
                33779682
                40e3b997-93a4-46cd-a1b5-0a9d9e6c3029
                © 2021 Davis 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
                : 25 August 2020
                : 23 December 2020
                : 19 February 2021
                Page count
                Pages: 19
                Funding
                Funded by: National Institutes of Health, DOI http://dx.doi.org/10.13039/100000002;
                Award ID: R01-HL137919
                Award ID: F32-DK117545
                Funded by: American College of Surgeons, DOI http://dx.doi.org/10.13039/100005301;
                Funded by: Vascular and Endovascular Surgery Society;
                Funded by: National Institutes of Health, DOI http://dx.doi.org/10.13039/100000002;
                Award ID: P30 AR075043
                Award ID: R01-AR069071
                Funded by: Doris Duke Foundation, DOI http://dx.doi.org/10.13039/100000862;
                Categories
                Article
                Cardiovascular Biology
                Innate immunity and inflammation

                Medicine
                Medicine

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