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      Tissue-specific transcriptional profiling of plasmacytoid dendritic cells reveals a hyperactivated state in chronic SIV infection

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          Abstract

          HIV associated immune activation (IA) is associated with increased morbidity in people living with HIV (PLWH) on antiretroviral therapy, and remains a barrier for strategies aimed at reducing the HIV reservoir. The underlying mechanisms of IA have not been definitively elucidated, however, persistent production of Type I IFNs and expression of ISGs is considered to be one of the primary factors. Plasmacytoid DCs (pDCs) are a major producer of Type I IFN during viral infections, and are highly immunomodulatory in acute HIV and SIV infection, however their role in chronic HIV/SIV infection has not been firmly established. Here, we performed a detailed transcriptomic characterization of pDCs in chronic SIV infection in rhesus macaques, and in sooty mangabeys, a natural host non-human primate (NHP) species that undergoes non-pathogenic SIV infection. We also investigated the immunostimulatory capacity of lymph node homing pDCs in chronic SIV infection by contrasting gene expression of pDCs isolated from lymph nodes with those from blood. We observed that pDCs in LNs, but not blood, produced high levels of IFNα transcripts, and upregulated gene expression programs consistent with T cell activation and exhaustion. We apply a novel strategy to catalogue uncharacterized surface molecules on pDCs, and identified the lymphoid exhaustion markers TIGIT and LAIR1 as highly expressed in SIV infection. pDCs from SIV-infected sooty mangabeys lacked the activation profile of ISG signatures observed in infected macaques. These data demonstrate that pDCs are a primary producer of Type I IFN in chronic SIV infection. Further, this study demonstrated that pDCs trafficking to LNs persist in a highly activated state well into chronic infection. Collectively, these data identify pDCs as a highly immunomodulatory cell population in chronic SIV infection, and a putative therapeutic target to reduce immune activation.

          Author summary

          For people living with HIV (PLWH), persistent immune activation is an obstacle to optimal health. In this study, we investigate the immunostimulatory potential of plasmacytoid dendritic cells in chronic SIV infection using comparative RNA-Seq. We observed that pDCs from SIV-infected rhesus macaques have highly activated profiles relative to uninfected animals; in contrast, pDCs from SIV-infected natural host sooty mangabeys had expression profiles similar to cells from uninfected animals. In chronically infected RMs, pDCs from lymph nodes maintained activation profiles elevated at levels even higher than those in the blood. Further, transcripts for the immunostimulatory cytokine family IFNA were readily detected in LN homing pDCs, but not those from blood. These data confirm pDCs as a major producer of Type I IFN in chronic SIV infection, and identify them as a target for immunotherapy.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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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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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draft
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draft
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Validation
                Role: MethodologyRole: Project administration
                Role: Methodology
                Role: Methodology
                Role: Methodology
                Role: Investigation
                Role: InvestigationRole: Project administration
                Role: Formal analysis
                Role: Investigation
                Role: InvestigationRole: Methodology
                Role: InvestigationRole: Methodology
                Role: Data curationRole: Formal analysis
                Role: InvestigationRole: Methodology
                Role: Formal analysisRole: Investigation
                Role: Resources
                Role: Resources
                Role: Resources
                Role: Formal analysisRole: Resources
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                PLoS Pathogens
                Public Library of Science (San Francisco, CA USA )
                1553-7366
                1553-7374
                28 June 2021
                June 2021
                : 17
                : 6
                : e1009674
                Affiliations
                [1 ] Division of Microbiology & Immunology, Yerkes National Primate Research Center, Atlanta, Georgia, United States of America
                [2 ] Vaccine and Gene Therapy Institute, Oregon Health & Science University, Beaverton, Oregon, United States of America
                [3 ] Flow Cytometry Core, Emory Vaccine Center, Emory University, Atlanta, Georgia, United States of America
                [4 ] Yerkes NHP Genomics Core Laboratory, Yerkes National Primate Research Center, Atlanta, Georgia, United States of America
                [5 ] Southern Research, Frederick, Maryland, United States of America
                [6 ] Department of Pathology and Laboratory Medicine, School of Medicine, Emory University, Atlanta, Georgia, United States of America
                [7 ] Department of Infectious Diseases and Microbiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
                [8 ] Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, Oregon, United States of America
                Vaccine Research Center, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5722-1109
                https://orcid.org/0000-0002-0952-4164
                https://orcid.org/0000-0001-9106-9481
                https://orcid.org/0000-0003-4857-505X
                https://orcid.org/0000-0002-0737-2048
                https://orcid.org/0000-0002-6948-3501
                https://orcid.org/0000-0002-3310-7686
                https://orcid.org/0000-0002-6740-0688
                https://orcid.org/0000-0002-0863-9998
                https://orcid.org/0000-0003-3075-755X
                https://orcid.org/0000-0002-0773-6569
                https://orcid.org/0000-0003-4238-1924
                https://orcid.org/0000-0002-9652-6394
                https://orcid.org/0000-0002-2116-5061
                Article
                PPATHOGENS-D-20-02491
                10.1371/journal.ppat.1009674
                8270445
                34181694
                91eac7d3-6c89-484f-bf39-8a211f2c43fa
                © 2021 Lee et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 November 2020
                : 28 May 2021
                Page count
                Figures: 5, Tables: 0, Pages: 32
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01 AI136990
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: R24 OD010445 (ORIP)
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: P51 OD 011132
                Funded by: funder-id http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: S10 OD026799
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01 AI116379
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: P30 AI050409
                Funded by: funder-id http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: R01 AI143411
                Award Recipient :
                Funded by: National Institute of Health
                Award ID: P51 OD011092
                This study was funded primarily by grant R01 AI136990 from the National Institute of Health, National Institute of Allergy and Infectious Diseases (NIAID) awarded to S.E.B., and also supported by R24 OD010445 (ORIP) from the National Institute of Health, Office of The Director, National Institutes of Health awarded to G.S., P51 OD 011132 from the National Institute of Health, Office of The Director awarded to the Yerkes National Primate Center (Jonathan Lewin), S10 OD026799 from the National Institute of Health, Office of The Director awarded to S.E.B and the Yerkes Genomics Core, grant R01 AI116379 from the NIAID awarded to M.P., and the P30 AI050409 awarded to Carlos Del Rio and the Center for AIDS Research (CFAR) at Emory University. The work for this publication was supported by NIH awards R01AI143411 (J.D.E.) and P51OD011092 to Oregon National Primate Research Center (Peter Barr-Gilliespie). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                Custom metadata
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                2021-07-09
                RNA-Seq data has been deposited in the Gene Expression Omnibus repository (National Center for Biotechnology Information database) under the accession GSE178225.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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