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      The Novel Omega-6 Fatty Acid Docosapentaenoic Acid Positively Modulates Brain Innate Immune Response for Resolving Neuroinflammation at Early and Late Stages of Humanized APOE-Based Alzheimer's Disease Models

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          Abstract

          Neuroinflammation plays a crucial role in the development and progression of Alzheimer's disease (AD), in which activated microglia are found to be associated with neurodegeneration. However, there is limited evidence showing how neuroinflammation and activated microglia are directly linked to neurodegeneration in vivo. Besides, there are currently no effective anti-inflammatory drugs for AD. In this study, we report on an effective anti-inflammatory lipid, linoleic acid (LA) metabolite docosapentaenoic acid (DPAn-6) treatment of aged humanized EFAD mice with advanced AD pathology. We also report the associations of neuroinflammatory and/or activated microglial markers with neurodegeneration in vivo. First, we found that dietary LA reduced proinflammatory cytokines of IL1-β, IL-6, as well as mRNA expression of COX2 toward resolving neuroinflammation with an increase of IL-10 in adult AD models E3FAD and E4FAD mice. Brain fatty acid assays showed a five to six-fold increase in DPAn-6 by dietary LA, especially more in E4FAD mice, when compared to standard diet. Thus, we tested DPAn-6 in aged E4FAD mice. After DPAn-6 was administered to the E4FAD mice by oral gavage for three weeks, we found that DPAn-6 reduced microgliosis and mRNA expressions of inflammatory, microglial, and caspase markers. Further, DPAn-6 increased mRNA expressions of ADCYAP1, VGF, and neuronal pentraxin 2 in parallel, all of which were inversely correlated with inflammatory and microglial markers. Finally, both LA and DPAn-6 directly reduced mRNA expression of COX2 in amyloid-beta42 oligomer-challenged BV2 microglial cells. Together, these data indicated that DPAn-6 modulated neuroinflammatory responses toward resolution and improvement of neurodegeneration in the late stages of AD models.

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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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            voom: precision weights unlock linear model analysis tools for RNA-seq read counts

            New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.
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              A Unique Microglia Type Associated with Restricting Development of Alzheimer's Disease.

              Alzheimer's disease (AD) is a detrimental neurodegenerative disease with no effective treatments. Due to cellular heterogeneity, defining the roles of immune cell subsets in AD onset and progression has been challenging. Using transcriptional single-cell sorting, we comprehensively map all immune populations in wild-type and AD-transgenic (Tg-AD) mouse brains. We describe a novel microglia type associated with neurodegenerative diseases (DAM) and identify markers, spatial localization, and pathways associated with these cells. Immunohistochemical staining of mice and human brain slices shows DAM with intracellular/phagocytic Aβ particles. Single-cell analysis of DAM in Tg-AD and triggering receptor expressed on myeloid cells 2 (Trem2)(-/-) Tg-AD reveals that the DAM program is activated in a two-step process. Activation is initiated in a Trem2-independent manner that involves downregulation of microglia checkpoints, followed by activation of a Trem2-dependent program. This unique microglia-type has the potential to restrict neurodegeneration, which may have important implications for future treatment of AD and other neurodegenerative diseases. VIDEO ABSTRACT.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                16 October 2020
                2020
                : 11
                : 558036
                Affiliations
                [1] 1Department of Neurology, University of California, Los Angeles , Los Angeles, CA, United States
                [2] 2Geriatric Research and Clinical Center, Greater Los Angeles Veterans Affairs Healthcare System, West Los Angeles VA Medical Center , Los Angeles, CA, United States
                [3] 3Department of Neurology, The Third Affiliated Hospital, Sun Yat-sen University , Guangzhou, China
                [4] 4Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles , Los Angeles, CA, United States
                [5] 5Institute for Genomics and Proteomics, University of California, Los Angeles , Los Angeles, CA, United States
                [6] 6Institute for Quantitative and Computational Biology, University of California, Los Angeles , Los Angeles, CA, United States
                [7] 7Department of Biological Chemistry, University of California, Los Angeles , Los Angeles, CA, United States
                [8] 8Molecular Biology Institute, University of California, Los Angeles , Los Angeles, CA, United States
                [9] 9Department of Medicine, University of California, Los Angeles , Los Angeles, CA, United States
                Author notes

                Edited by: Jorge Matias-Guiu, Complutense University of Madrid, Spain

                Reviewed by: Maria F. Cano-Abad, Autonomous University of Madrid, Spain; Jorge Tolivia, University of Oviedo, Spain

                *Correspondence: Qiu-Lan Ma qiulanma@ 123456mednet.ucla.edu

                This article was submitted to Multiple Sclerosis and Neuroimmunology, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2020.558036
                7596305
                33178186
                c1015c42-6977-4425-be09-ffb459eb0c00
                Copyright © 2020 Ma, Zhu, Morselli, Su, Pelligrini, Lu, Jones, Denver, Castro, Gu, Relampagos, Caoili, Teter, Frautschy and Cole.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 May 2020
                : 27 August 2020
                Page count
                Figures: 8, Tables: 1, Equations: 0, References: 77, Pages: 15, Words: 10431
                Categories
                Immunology
                Original Research

                Immunology
                alzheimer's disease,neuroinflammation,fatty acid,linoleic acid,docosapentaenoic acid,apoe,efad
                Immunology
                alzheimer's disease, neuroinflammation, fatty acid, linoleic acid, docosapentaenoic acid, apoe, efad

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