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      Comprehensive innate immune profiling of chikungunya virus infection in pediatric cases

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          Abstract

          Chikungunya virus ( CHIKV) is a mosquito‐borne alphavirus that causes global epidemics of debilitating disease worldwide. To gain functional insight into the host cellular genes required for virus infection, we performed whole‐blood RNA‐seq, 37‐plex mass cytometry of peripheral blood mononuclear cells ( PBMCs), and serum cytokine measurements of acute‐ and convalescent‐phase samples obtained from 42 children naturally infected with CHIKV. Semi‐supervised classification and clustering of single‐cell events into 57 sub‐communities of canonical leukocyte phenotypes revealed a monocyte‐driven response to acute infection, with the greatest expansions in “intermediate” CD14 ++ CD16 + monocytes and an activated subpopulation of CD14 + monocytes. Increases in acute‐phase CHIKV envelope protein E2 expression were highest for monocytes and dendritic cells. Serum cytokine measurements confirmed significant acute‐phase upregulation of monocyte chemoattractants. Distinct transcriptomic signatures were associated with infection timepoint, as well as convalescent‐phase anti‐ CHIKV antibody titer, acute‐phase viremia, and symptom severity. We present a multiscale network that summarizes all observed modulations across cellular and transcriptomic levels and their interactions with clinical outcomes, providing a uniquely global view of the biomolecular landscape of human CHIKV infection.

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          Most cited references61

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          Pathview: an R/Bioconductor package for pathway-based data integration and visualization

          Summary: Pathview is a novel tool set for pathway-based data integration and visualization. It maps and renders user data on relevant pathway graphs. Users only need to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps and integrates user data onto the pathway and renders pathway graphs with the mapped data. Although built as a stand-alone program, Pathview may seamlessly integrate with pathway and functional analysis tools for large-scale and fully automated analysis pipelines. Availability: The package is freely available under the GPLv3 license through Bioconductor and R-Forge. It is available at http://bioconductor.org/packages/release/bioc/html/pathview.html and at http://Pathview.r-forge.r-project.org/. Contact: luo_weijun@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online.
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            Genetics of gene expression and its effect on disease.

            Common human diseases result from the interplay of many genes and environmental factors. Therefore, a more integrative biology approach is needed to unravel the complexity and causes of such diseases. To elucidate the complexity of common human diseases such as obesity, we have analysed the expression of 23,720 transcripts in large population-based blood and adipose tissue cohorts comprehensively assessed for various phenotypes, including traits related to clinical obesity. In contrast to the blood expression profiles, we observed a marked correlation between gene expression in adipose tissue and obesity-related traits. Genome-wide linkage and association mapping revealed a highly significant genetic component to gene expression traits, including a strong genetic effect of proximal (cis) signals, with 50% of the cis signals overlapping between the two tissues profiled. Here we demonstrate an extensive transcriptional network constructed from the human adipose data that exhibits significant overlap with similar network modules constructed from mouse adipose data. A core network module in humans and mice was identified that is enriched for genes involved in the inflammatory and immune response and has been found to be causally associated to obesity-related traits.
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              Monocyte-mediated defense against microbial pathogens.

              Circulating blood monocytes supply peripheral tissues with macrophage and dendritic cell (DC) precursors and, in the setting of infection, also contribute directly to immune defense against microbial pathogens. In humans and mice, monocytes are divided into two major subsets that either specifically traffic into inflamed tissues or, in the absence of overt inflammation, constitutively maintain tissue macrophage/DC populations. Inflammatory monocytes respond rapidly to microbial stimuli by secreting cytokines and antimicrobial factors, express the CCR2 chemokine receptor, and traffic to sites of microbial infection in response to monocyte chemoattractant protein (MCP)-1 (CCL2) secretion. In murine models, CCR2-mediated monocyte recruitment is essential for defense against Listeria monocytogenes, Mycobacterium tuberculosis, Toxoplasma gondii, and Cryptococcus neoformans infection, implicating inflammatory monocytes in defense against bacterial, protozoal, and fungal pathogens. Recent studies indicate that inflammatory monocyte recruitment to sites of infection is complex, involving CCR2-mediated emigration of monocytes from the bone marrow into the bloodstream, followed by trafficking into infected tissues. The in vivo mechanisms that promote chemokine secretion, monocyte differentiation and trafficking, and finally monocyte-mediated microbial killing remain active and important areas of investigation.
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                Author and article information

                Contributors
                eharris@berkeley.edu
                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                10.1002/(ISSN)1744-4292
                MSB
                msb
                Molecular Systems Biology
                John Wiley and Sons Inc. (Hoboken )
                1744-4292
                27 August 2018
                August 2018
                : 14
                : 8 ( doiID: 10.1002/msb.v14.8 )
                : e7862
                Affiliations
                [ 1 ] Division of Infectious Diseases and Vaccinology School of Public Health University of California Berkeley Berkeley CA USA
                [ 2 ] Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA
                [ 3 ] Human Immune Monitoring Center Icahn School of Medicine at Mount Sinai New York NY USA
                [ 4 ] Division of Infectious Diseases Department of Medicine Northwestern University Feinberg School of Medicine Chicago IL USA
                [ 5 ] Department of Population Health and Science Policy Icahn School of Medicine at Mount Sinai New York NY USA
                [ 6 ] Laboratorio Nacional de Virología Centro Nacional de Diagnóstico y Referencia Ministerio de Salud Managua Nicaragua
                Author notes
                [*] [* ]Corresponding author. Tel: +1 510 642 4845; E‐mail: eharris@ 123456berkeley.edu
                [†]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-1676-2523
                http://orcid.org/0000-0002-7436-7396
                http://orcid.org/0000-0003-0834-8178
                http://orcid.org/0000-0002-7238-4037
                Article
                MSB177862
                10.15252/msb.20177862
                6110311
                30150281
                e01ce9d2-aba2-457d-b677-a4a59e4e1ccc
                © 2018 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 03 July 2017
                : 31 May 2018
                : 29 June 2018
                Page count
                Figures: 7, Tables: 3, Pages: 25, Words: 20564
                Funding
                Funded by: HHS|NIH|National Institute of Allergy and Infectious Diseases (NIAID)
                Award ID: U19AI118610
                Award ID: R33AI100186
                Award ID: F30AI122673
                Categories
                Article
                Articles
                Custom metadata
                2.0
                msb177862
                August 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.4 mode:remove_FC converted:27.08.2018

                Quantitative & Systems biology
                chikungunya,cytof,immune profiling,pediatric,rna‐seq,genome-scale & integrative biology,microbiology, virology & host pathogen interaction,molecular biology of disease

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